Journal of Knowledge Management 11:5 Coming of Age of Knowledge-Based Development: The Coming of Age of Knowledge-Based Development 9781846636172, 9781846636165

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06/09/2007

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ISSN 1367-3270

Volume 11 Number 5 2007

Journal of

Knowledge Management The coming of age of knowledge-based development Guest Edtor: Francisco Javier Carrillo

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Table of contents The coming of age of knowledge-based development Guest Editor: Francisco Javier Carrillo Volume 11 Number 5 2007

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Guest editorial The coming of age of knowledge-based development

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Attracting and retaining knowledge workers in knowledge cities

Francisco Javier Carrillo

Call for papers

Articles

157

The 2007 Emerald/EFMD Outstanding Doctoral Research Awards 158

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Tan Yigitcanlar, Scott Baum and Stephen Horton

Working and learning in a knowledge city: a multilevel development framework for knowledge workers

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Blanca C. Garcia

Knowledge effectiveness, social context and innovation

31

Dimitris Brachos, Konstantinos Kostopoulos, Klas Eric Soderquist and Gregory Prastacos

The social management of embodied knowledge in a knowledge community

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Ahmad Raza, A. Rashid Kausar and David Paul

Conversing cities: the way forward

55

Mimi Tresman, Edna Pa´sher and Francesco Molinari

An integrated decision support model for a knowledge city’s strategy formulation

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Kostas Ergazakis, Kostas Metaxiotis, John Psarras and Dimitrios Askounis

Regional development through knowledge creation in organic agriculture

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Isabel Morales Galindo

Technology districts: proximity and knowledge access

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Antonio Messeni Petruzzelli, Vito Albino and Nunzia Carbonara

Knowledge-driven development indicators: still an eclectic panorama

115

Katia Passerini

The Austrian National Knowledge Report

129

Ursula Schneider

Effective societal knowledge management

141

Karl M. Wiig

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Guest editorial The coming of age of knowledge-based development Francisco Javier Carrillo

Abstract Purpose – To introduce the 2007 annual special issue on knowledge-based development (KBD), from the perspective of the institutionalization of KBD as a field of study and practice, followed by an outline of the contents. Design/methodology/approach – The approach is a discussion of the issues involved.

Francisco Javier Carrillo is based at the Center for Knowledge Systems, Tecnolo´gico de Monterrey, Me´xico and The World Capital Institute. E-mail: [email protected]

Findings – The consolidation of KBD and knowledge cities as a distinctive field of R&D, as well as professional practice, becomes apparent when considering structural elements such as affluents, issues, cases, sources, events, organizations and initiatives. This consolidation seems to underlie the progression of contributions through this special issue and prior ones on the same subject. Originality/value – This special issue may contribute to raise new questions and stimulate further research into knowledge cities, regions and countries. Keywords Knowledge management, Knowledge economy, Knowledge organizations, Information society Paper type Viewpoint

his is the second annual JKM Special Issue on knowledge-based development, following the two initial special issues of 2002 (Vol. 6 No. 4) and 2004 (Vol. 8 No. 5), as well as the first annual special issue of 2006 (Vol. 10 No. 5). What began as a glimpse of the knowledge management community into the social dimension of knowledge value dynamics, is now consolidating as a regular line of contribution to social development. This trend is indicative of the institutionalization of KBD as a field of study and practice.

T

Indeed, the pattern of activities signalling the institutionalization of a new discipline (Ben-David, 1972) can be recognized in recent KBD activities worldwide such as scientific organizations, dedicated publications, international conferences, professional associations, etc. A child of the new millenium, KBD is receiving a growing amount of attention as policy makers and analysts are becoming increasingly aware that the ideas and tools of the industrial economy are exhibiting their limits, that knowledge-based value creation and distribution follow principles of their own and that today’s knowledge citizens and virtual communities are not waiting for policy makers and regulators to explore the new unchartered territories and colonize the worlds of represented reality. Some of these signs are evident in aspects such as the affluents, the issues, the cases, the sources, the events, the organizations and the initiatives showing the vitality of KBD. This includes the broader realities of policy making and development governance of knowledge-based communities as well as the planning and management of knowledge cities, regions and nations. Each of these elements is exemplified next. The affluents of KBD can be traced back to contributing disciplines such as Economics (new or endogenous growth theory), Urban Studies and Planning (new urbanism), Geography (human geography, especially knowledge flows and the territorial dimensions), Psychology of Science and Technology (from cognition through accelerated innovation), Anthropology of Knowledge, Social Studies of Science, Political Economy of Knowledge, Technology and Innovation Management and, of course, Knowledge Management.

DOI 10.1108/13673270710819753

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This unprecedented convergence of conceptual and technical tools is required to tackle issues such as those being covered in this special issue, namely: B

Dynamics of social knowledge-based value creation.

B

Identification, measurement and strategic development of collective intellectual capital.

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National, regional and urban KBD planning and development.

B

Knowledge cities concepts and models.

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Descriptions and assessments of implementation cases.

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Metrics, benchmarkings and comparative analyses.

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Social accounting and strategy deployment.

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Social learning networks and social knowledge bases.

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Knowledge citizenship, access to information and distributed participation.

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ITCs and social bases of instrumental capital.

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KBD policy and cultural issues.

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Global marginalization and the knowledge divide.

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Systems perspectives on KBD.

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Radical KBD as a strategic and disruptive paradigm.

The city and nation cases are exemplified by cities such as Manchester, Singapore, Boston, Sidney, Barcelona, Holon, Montreal, Bilbao, as well as by countries such as Austria, Japan, Finland, New Zealand, Denmark, Ireland, Costa Rica and Sweden. All these, deliberate attempts at KBD policies and arguably some of the leading indications of lessons to be learned in KBD conceptualization and implementation. Some of the sources that are indicative of advances in the field are: the Urban Studies journal, especially Knight (1995) and the special issue of 2002 on knowledge cities (Simmie and Lever, 2002); Bounfour and Edvinsson (Eds); Intellectual Capital for Communities (Bounfour and Edvinsson, 2005); Richard Florida’s Cities and the Creative Class (Florida, 2005); Carrillo (Ed.) Knowledge Cities (Carrillo, 2005); R&B Consulting’s Knowledge Management Austria (R&B Consulting, 2006); PriceWaterhouseCoopers’ Cities of Knowledge Report (2007); Pirjo Stahle’s (Ed.) Five Steps for Finland’s Future (Stahle, 2007); and Yigitcanlar, Velibeyoglu and Baum’s forthcoming Knowledge-based Urban Development (Yigitcanlar et al., n.d.). In terms of electronic sources, web sites such as The Knowledge Cities Clearinghouse (www.knowledgecities.com), Learning City/regions Resources (www.learningcities.net/services/Links/displaycat.cfm?CatIdd ¼ 340), The INK Research Center at SPRU (www.sussex.ac.uk/spru/1-4-9-1-1-2.html), The Metropolitan New Economy Index (www.neweconomyindex.org/metro/) and Knowledgeboard (www.knowledgeboard.com/) are good examples. Events such as conferences, symposia and congresses are well-established scientific socialization practices. It is worth noticing KBD-specialized ones such as the World Summit on the Information Society (UN/ITU: Geneva 2003 and Tunis 2005); the International Symposium on Knowledge Cities (AUDI: Saudi Arabia, 2005), the Intellectual Capital for Communities Annual Conference (U. Paris-Sud/The World Bank and others: Paris 2005, 2006, 2007) and the Eurocities Knowledge Societies Forum (EUROCITIES: Barcelona, 2007). Shortly after this issue is published, the 1st Global Knowledge-based Development Week should be taking place in Monterrey, Mexico (15-21 October) featuring the Knowledge Cities Summit. All of the above are conducted by organizations directly concerned with KBD. Some are established institutions that became deeply concerned with the knowledge society such as The European Commission, UNESCO, The World Bank, the OECD, while others are purpose-created such as The New Club of Paris, The World Capital Institute, Knowledge Desert Australia, The Ibero-American Community for Knowledge Systems, and many others. These organizations also produce some distinctive initiatives such as the Human Development Report (UN), the Knowledge for Development Program (WB), the RICARDIS

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Report (NCP), the European Regions KB Innovation Network (ERIK), and the Most Admired Knowledge City Awards (Teleos/WCI). Shortly after its birth, KBD is at a crossroads: whether continuing to sustain the received transitional view under which knowledge is considered as a resource particularly suited to leverage economic growth in a way that may eventually bring social prosperity. This view is instrumental, incremental and focused on the growth of the monetary base. An alternative view, qualified as a radical KBD perspective, is one where social capital accounts become an instrument for balanced, equitable and sustainable development. This view, in contrast, is purposeful, systemic and focused on the balance of collective capital, both intellectual (such as identity and relational capitals) and traditional (material þ financial). This new annual issue is itself indicative of KBD evolution, yielding a balance between empirical research/cases and theoretical/methodological issues. The paper by Yigitcanlar, Baum and Horton provides an insightful perspective on the factors attracting talent to knowledge cities. Garcia analyzes the facilitation skills required by knowledge workers in Greater Manchester universities. Brachos, Kostopoulos, Soderquist and Prastacos, in turn, report on an empirical study of knowledge transfer effectiveness with reference to organizational context. In all these cases, inter-organizational processes shed light on emerging social knowledge mechanisms. At a broader city and regional scale, Raza, Kausar and Paul provide an epistemological perspective on social knowledge management; next, Tresman, Pasher and Molinari examine trends in the role of conversation in building knowledge cities and regions; while Ergazakis, Metaxiotis, Psarras and Askounis provide a distinctive model for KC strategy formulation. The paper by Morales describes a successful regional KBD case in organic agriculture, followed by Petruzzelli, Albino and Carbonara, who analyze the role of proximity dimensions on knowledge access in technology districts. The last three papers provide methodological and conceptual perspectives at a national and broadest social level. Passerini reviews KBD indicators in order to assess the current alternatives to international coordination. Schneider reports on a prototype model and procedure to account for national IC in the case of Austria. Finally, Wiig suggests a comprehensive KBD framework for citizens and businesses participation in a country-level strategy. Altogether, this collection of valuable contributions provides a picture of contemporary KBD and raises further questions. Those interested in contributing to upcoming editions may find the call for papers for the 2008 annual special issue at the end of this issue. I take the opportunity to thank Rory Chase, the General JKM Editor, for his generous and continued support.

References Ben-David, J. (1972), ‘‘The profession of science and its powers’’, Minerva, Vol. 10, pp. 362-83. Bounfour, A. and Edvinsson, L. (Eds) (2005), Intellectual Capital for Communities: Nations, Regions and Cities, Elsevier Butterworth/Heinemann, New York, NY. Carrillo, F.J. (2005), Knowledge Cities: Approaches, Experiences and Perspectives, Elsevier Butterworth/Heinemann, New York, NY. Florida, R. (2005), Cities and the Creative Class, Routledge, New York, NY. Knight, R. (1995), ‘‘Knowledge-based development: policy and planning implications for cities’’, Urban Studies, Vol. 32 No. 2, pp. 225-60. R&B Consulting (Eds) (2006), Knowledge Management Austria, Assess, Wien. Stahle, P. (Ed.) (2007), Five Steps for Finland’s Future, TEKES, Helsinki. Simmie, J. and Lever, W.F. (Eds) (2002), ‘‘Special issue on ‘the knowledge-based city’’’, Urban Studies, Vol. 39 Nos 5/6. Yigitcanlar, T., Velibeyoglu, K. and Baum, S. (Eds) (n.d.), Knowledge-based Urban Development: Planning and Applications in the Information Era, (forthcoming).

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Attracting and retaining knowledge workers in knowledge cities Tan Yigitcanlar, Scott Baum and Stephen Horton

Abstract Purpose – The purpose of this paper is to investigate ways to attract and retain knowledge workers in a globally successful knowledge city or a city aspiring to become one. Design/methodology/approach – The paper reviews the literature on knowledge work and workers and provides useful recommendations on the fundamentals of how to attract and retain knowledge workers. Findings – The paper sheds light on attracting and retaining knowledge workers that knowledge industries, knowledge-based development and knowledge cities rely on. Originality/value – The paper provides an in-depth discussion on the concepts of knowledge work, knowledge workers and what these workers want when they are not at work. Keywords Employee turnover, Knowledge management, Knowledge organizations, Cities, Economic development, Leisure facilities Paper type Conceptual paper Tan Yigitcanlar, School of Urban Development, Queensland University of Technology, Brisbane, Australia. Scott Baum and Stephen Horton, Urban Research Program, Griffith University, Brisbane, Australia.

Introduction In a growing knowledge economy talent and creativity are becoming increasingly decisive in shaping economic opportunity and knowledge based urban development. Prosperity now depends less on access to physical resources and more and more on the ability to create economically useful new ideas. In knowledge economy and knowledge based urban development the contribution of knowledge workers or creative class is often mentioned as strategic and valuable (Florida, 2005; Baum et al., 2006). For example the scientific literature on the knowledge economy confirms the new importance of knowledge work and knowledge workers as the engines of growth (Glaeser, 2000; Raspe and Van Oort, 2006). The claim that the growth of cities is related to human capital can be dated back to Jacobs’ (1969) work on the economy of cities. Since then, extensive empirical work has confirmed a link between human capital, economic growth and urban development (e.g. Knight, 1995; Eaton and Eckstein, 1997; Black and Henderson, 1999). The basic idea behind human capital theory is that people, rather than money, are the motor force of economic and social growth and urban development. Human capital is, thus, the major variable in endogenous growth models (Reich, 1992; Saxenian, 1994). The conclusion of such models is that the key to regional growth lies in concentrating a critical core of highly educated and productive people, knowledge workers. This paper investigates ways to attract and retain knowledge workers in a globally successful knowledge city region or a city that aspires to become a knowledge city. The paper is organised in five sections. Following the introduction, the second section focuses on knowledge workers in the urban context before outlining a portrait of knowledge workers as urban residents when they are not at work. Following this the paper considers the essentials for attracting and retaining knowledge workers in cities. The paper concludes by providing generalised useful suggestions to attract and retain knowledge workers in knowledge cities.

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DOI 10.1108/13673270710819762

Knowledge workers in urban context The production of contemporary knowledge requires a certain scale and intensity of knowledge infrastructure. It also requires a certain scale of labour power and consumption. The optimal landscape for the production of contemporary knowledge is a big city embedded in a functional urban region with significant global dimensions. In such a landscape the core city concentrates extensive global networks into an intense medium of exchange in which knowledge production and knowledge workers can thrive. For as much as specialised knowledge must be networked from sources around the globe so knowledge workers prefer inspiring cities with a thriving cultural life, an international orientation and high levels of social and cultural diversity (Van den Berg et al., 2004; Carvalho, 2006). Knowledge workers are not only highly mobile in theory, they are also highly mobile in practice. That is to say, knowledge workers expect to change jobs, if not occupation, relatively frequently. They thus favour knowledge cities and regions with a ‘‘thick labour market’’ offering ready opportunity to advance their careers by moving between employers. The benefits of agglomeration have, in short, spread, beyond immediate production, to the employee. According to Florida (2002, p. 223), ‘‘the gathering of people, companies and resources into particular places with particular specialties and capabilities generates efficiencies that power economic growth’’. In this perspective, social space is becoming the central organising unit of the knowledge economy, taking the place of large corporations. The city has always been a place of social discrimination. Fundamental to the earliest urban settlements was the division between the palaces of the ruling kings and priests and the places of the common people. Within these socially-differentiated places, however, integration was the rule. Thus, mixed together, cheek by jowl, in the popular precincts were domestic spaces, places of work, places of pleasure, places of punishment and places to buy and sell. Over time these different land uses began to consolidate and segregate. Nevertheless, even in a European city of the eighteenth century, integration still held sway. With the industrial development of the nineteenth century, however, and the need to organise mass labour in factories, a new and decisive dynamic arose in the spatial organisation of the city. Work spaces separated out from living place and in short, in historic terms, order the negative externalities of mass industry, often pictured in a smoke stack factory, coupled with the development of mass transport, the building of extensive road networks and the long-term rise in workers’ wages all contributed to the disaggregation of the modern city. By the turn of the twenty-first century the contemporary urban region comprised a disaggregation of dispersed land uses connected, if at all, by the thin ribbon of linear transport routes. The separation of work, retail and residential activity has had a number of negative consequences, ranging from extended home-work and return commutes, unsustainable transport options and the isolation of child-carers in uni-dimensional suburban environments (see Hayden, 1984). Knowledge work, too, needs mass organisation. Indeed, insofar as knowledge work is produced in global networks the massing of labour in the twenty-first century is at a level not seen before in human history. The organisation of knowledge work however occurs in virtual space – in electronic media – thus eroding the need for the spatial consolidation of work. In such a context, a real possibility exists for the re-integration of work place and domestic space. Similarly, insofar as retailing too assumes virtual form (e.g. on-line shopping) a further possibility for the reintegration of modern existence presents itself. In short, the virtual realm that underpins knowledge work appears to present – for knowledge workers if not other social groupings – an opportunity to reverse what has been a fundamental historic urban trend of spatial segregation.

Portrait of knowledge worker as urban resident What do knowledge workers want – when not at work? The authors attempt to answer this question with an analytical portrait of the ideal knowledge worker. There are, already, a number of snapshots of the subject: as computer adept, scientist, symbolic analyst, financial wizard, writer, artist, and latter-day Bohemian. These characterisations first place the subject

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in the context of work; while the final three images start to suggest a life away from employment. The portrait will do both. The authors start, as required by convention, with a background. In this case human work through the ages suggests itself as a possibility. The social organisation of work, and work is always social before it is individual, has taken many historical forms. Examples include kinship obligation, ancient slavery, servitude, craft production, modern slavery, and industrial wage labour. The last of these is remembered for neither knowledge nor creativity. Rather, the paradigmatic image of what has come to be called industrial modernity is the factory ‘‘hand’’ functionally chained to an assembly line. In only slight caricature the ideal modern labourer is, therefore, the disembodied hand attending to a machine. As background such a mechanised work environment appears as a uniform surface strangely agitated, as if by the relentless tick of time. It has been commonly suggested that the knowledge worker is a radically new type of worker, precisely one who is free from machine domination. The organisation of knowledge work, the form of its practice and, most decisively, the role of the human body in the production of contemporary knowledge indicate otherwise. As it has been seen, the subject does not ponder alone under an apple tree or dreaming spire. S/he is part of a team: a rationalised organisation, a network for assembling thought. Such contemporary knowledge production is quite distinct from classic western thought that, the philosophy of science shows, was built not by aggregation but produced in discontinuous, paradigmatic forms. In addition, contemporary knowledge has a dimension of quantity that marks it off from the classic intellectual concern for quality through brevity (e.g. Occam’s razor). Contemporary knowledge, in short, bears the distinct marks of the machine. It is, ideally, a massive articulation (e.g. the genome project). The increasingly digital form of the inputs and outputs of modern knowledge production, dependent on the 0/1 logic of the computer, is also telling. As are the video or machine installations of the artistic avant-garde, the decisive consideration, however, is the role of the human body in knowledge production. If in industrial production the body, as a consequence of the machine, is reduced to a hand, then knowledge work takes the process one step further. It, in essence, requires no bodily act. Body appears as a mere bearer of the Knowing Mind. In this context the figure of Stephen Hawking is iconic – which may explain some of the world’s fascination with him. The immediate appearance of knowledge work, like the sun revolving around earth, is, therefore, deceptive. The object of its labour – the idea – is a phantom, an abstraction beyond the material sense of human organs. As such it stands in categorical opposition to the object of industrial labour in all its intractable, too solid mass. Nevertheless, the knowledge worker, as the authors have seen, is not unrelated to the industrial worker, the organisation of modern labour and its consequences for the human body. In knowledge work the marginalisation of the working body approaches completion. This suggests that, although hidden from immediate perception by the virtual dimension of the contemporary work place, the knowledge worker labours in a context of machine hyperactivity. It is against this rationalised background, empty of human form, and tending toward ideal homogeneity, but of increasing temporal agitation, that the life of the knowledge worker takes place. The life of the knowledge worker, away from work, constitutes the foreground of the portrait. Here the subject is obligated by the necessities of existence and motivated by the lures of desire. Again, the authors consider them in turn. The most obvious necessities of life are the basic needs of animal existence (e.g. sustenance and shelter). However, insofar as the knowledge worker is not a lone animal but a social being, s/he is also part of a network of

‘‘ Prosperity now depends less on access to physical resources and more and more on the ability to create economically useful new ideas. ’’

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social necessities (e.g. family, education, citizenship). Before looking at the detail of some of these twenty-first century necessities, the authors pause to consider the processes by which they are provided. In modern society, the necessities of ‘‘social reproduction’’ are provided, mainly through the market and by public organisations. That said, in the last decades the difference between the two media has narrowed as government has inexorably moved to more market-like mechanisms of allocation. Away from work the knowledge worker, before anything else, lives in the market. Here, surrounded by things for sale, s/he buys the necessities of existence. Beyond necessity the knowledge worker, like all humans, is driven by desire. Social anthropology and Freudian psychology has found desire (at a societal level often called culture) to be, in essence, compensatory. A successful culture, such as would attract and retain adherents, that is reproduce itself over time, makes good, or more exactly good enough, those things society requires the individual forgo. There is, then, a contradiction between society that imposes certain disciplines on the individual, and culture which makes good enough these sacrifices. The complexity of humanity, and its ingenuity, has, however, long found ways for the two imperatives to lie down together. Insofar as culture opposes the imperatives of social organisation and the first necessity of society is to organise material production its compensations are, at best, partial or, more often, just ideal/symbolic/virtual (see Levi-Strauss, 1966). The authors suspect compensation for the sacrifice of the body will be a central desire of knowledge worker culture. Again, however, the authors postpone details of content to first consider the more general question of medium or form. From its beginnings modern culture has been marked by pictorial representation. It is no accident, to mention only the most obvious symptoms, that early modernity discovered linear perspective, that the nineteenth century ‘‘invented’’ photography, and the twentieth century the feature film and television. That is not to say image making does not predate modernity or that it is not more widespread than Europe. However, in contrast to the images of other times and places, often sacred images hidden from vulgar eyes, modern images are, overwhelming, made for a public – for sale, even. Modernity makes images to be seen by the masses. Only Imperial ‘‘bread and circuses’’ Rome, itself a market economy, albeit one based on slave labour, readily suggests itself as perhaps comparable in its weakness before the spectacular. Be that as it may, people feel safe in light of the building scale and tempo of contemporary image making to claim, with no further justification, the imaginary as the cultural medium of the age (see Debord, 1994). The knowledge worker is in no way immune to the cultural imagery of modernity. Indeed, quite the opposite. Knowledge, an abstraction lacking material form, most readily presents itself to the human mind in ideal spatialisaton – that is, as image. From Newton, like Adam, sitting under his apple tree, to Einstein’s theory of relativity, constructed precisely around different points of view, to the double helix of life, the age of reason has been wedded to imagery. The authors therefore see the knowledge worker as very much at home in a culture of images. The structural features of the portrait are now complete. Against a uniform background, agitated by the tick of time and empty of human form, the ideal knowledge worker faces the market as a consumer and looks for images of consolation. The authors are now ready for the foreground. It is coloured in urban shades for the knowledge worker’s home ground, before anything else, is the most modern of environments. Thus, in representing the social necessities of knowledge worker life the authors do so in the context of an intense twenty-first century urban environment. The realm of necessity The knowledge worker is a particular type of consumer of the market allocated necessities of life. S/he is a consumer with considerable disposal income. The empirical dimension of the spending power of the knowledge worker – a multiple determination of income, capacity for debt etc. – is difficult to isolate from general social data. Nevertheless, the authors

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‘‘ The optimal landscape for the production of contemporary knowledge is a big city embedded in a functional urban region with significant global dimensions. ’’

confidently suggest the knowledge worker wants a retail rich environment. Policy need only define a hierarchy of retail environments – using, perhaps, retail space, intensity, diversity, proximity – to make this qualitative observation quantitatively useful. The commodities and services demanded by the knowledge worker consumer are legion. The portrait suggests only the most fundamental. The sort of shelter the knowledge worker wants is the result of a complex economic, social, cultural and personal calculation. Within this complex household structure is a pervasive determinant. The fact that basic data on the knowledge worker households, such as size and form (age, gender, dependent ratio etc.), are not readily reflects a policy and research focus on the mainly economic dimensions of the knowledge work. It is the authors’ understanding the knowledge worker household, in caricature, tends toward the ideal of two working adults and a child. Such a structure is unsustainable, there being insufficient children to reproduce the population, raising the already spectral possibility of the machine production of humans (i.e. fertilisation and cloning technology). Be that as it may, the authors’ interest here is to represent the knowledge worker household, and its needs, including the need for accommodation, as more adult than has been the case in the recent suburban past. The authors also lack basic data on the accommodation preferences of the knowledge worker household. Emerging commentary suggests a significant rental property market – on the understanding of the knowledge worker as mobile not only between jobs but between countries, regions and within cities. Similarly, temporary accommodation for visiting knowledge workers has also been suggested. The authors add two broad suggestions. First, knowledge worker accommodation is likely to require smaller structures, in line with smaller households, than has been the twentieth-century norm. On the other hand, such accommodation should make provision for the car – a member, the authors speculate, of the twenty-first century knowledge worker household in all but the most unusual circumstance (e.g. Manhattan – but certainly not Los Angeles or Brisbane). The authors have argued for a knowledge worker household with a decreasing proportion of children. Relative to recent past generations, therefore, the gross burden of child care in the ideal knowledge worker household is diminished. It is also being removed one step away. The knowledge worker household buys much of its childcare in the market. Again, the authors regret the lack of empirical dimension for these speculations. Nevertheless, it is perhaps safe to see, in caricature, the adults of the knowledge worker household leaving their child in another’s care as they take their minds off to work. Knowledge workers, in short, want access to childcare services. This want is slowly evolving into a demand for quality child care services. Here public regulation, the Government, enters the picture. The Government is the major supplier of education – a clear necessity if the household is to be socially reproduced. The demand for education from the child-modest household is for diminished quantity but increased quality. Knowledge workers need access to fewer schools than has been norm, but they want higher quality education for their children. In reverse of the childcare situation, higher income consumers are turning away from the State, and universal provision, and toward selective by income provision by the private sector. This, it should be noted, increases the probability of the generational reproduction of privilege (i.e. social class formation).

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A similar dynamic is to be seen at work in health care. The knowledge worker wants care of a higher quality than that provided to the general public, and is prepared to pay for it. In terms of the urban environment, then, the authors speculate the knowledge worker would like ready access to private health care facilities. The final necessity facing the knowledge worker is age, retirement and death. Significant numbers of knowledge workers born in the baby boom have reached the beginnings of this process. Evidence suggests their material expectations are both greater than their antecedents, and growing. The knowledge worker wants an affluent retirement. In late modern societies the Government has been the traditional provider for life after paid labour – mainly by way of universal superannuation, and free and/or price discounted services. However, as demand for more affluent retirement has emerged, contemporary Governments have begun to shift from single universal provision to helping individuals accumulate for their own retirement. Again empirical research, this time on the structure and pattern of saving, would be useful. Absent of this speculation, again in slight caricature, is of an ageing knowledge worker who wants Government to provide for the private accumulation of retirement savings. Such provision would include incentives (e.g. tax relief) and protection (e.g. flexibility when worker changes jobs, regions and, even, countries). The knowledge worker has many other wants. Some of these are so general, for example the desire for national security, they are neglected. Others like transport and personal security, although they could be included here as necessities of social reproduction, are better seen in a cultural context. This ambiguity shows the distinction between social reproduction and cultural desire to be an analytical convenience. In practice the two are mutually implicated in each other – with culture often taking advantage of necessity to give it a particular form; and necessity taking advantage of culture to give it a particular content. They lie down together. The realm of culture Contemporary culture is spectacular. Support for this contention is to be seen every night on television, and emphasised at regular intervals by such events as publicly-funded fireworks and major athletic games. Within this framework the knowledge worker desires consolation for the bodily sacrifices of abstract work. If modern knowledge production sacrifices the body of the worker on the altar of the virtual machine, culture pictures that body rewarded, to coin a metaphor, in paradise. From the Renaissance resurrection of classic imagery, through the nineteenth century rediscovery of the Olympic Games, to supermodels and gay male display, the cult of the human body has long been an increasingly popular concern of modern culture. Knowledge worker culture is the advanced guard of its contemporary expression. The authors thus suggest, as a prime cultural imperative, the knowledge worker wants to see the perfected human body. The policy implication of this hypothesis is that an environment that can provide such images will attract and retain those who work in abstractions. The spectacle of professional sport is perhaps the clearest expression of a desire to see the human body displayed in full glory. It is significant that even here success beyond display, the reality of winning in short, is increasingly dependent on patterned disciplines that call to mind humanity in the service of the machine. Be that as it may, watching bodies, in sport or not, is a manifest pleasure of a cultural market that importantly includes knowledge workers. For example in Australia the increasing female interest in the Australian football league, rugby league and even rugby union and cricket, not to mention the Olympic and Commonwealth Games, attests that the display of the perfected body transcends any personal identification with the game. Similarly, male interest in female sport (e.g. beach volley, netball) also suggests a wide ranging aesthetic of the human body. The fact that sexual desire, almost certainly, underpins such an aesthetic does not undermine the premise. It entrenches it. The authors contend, therefore, the knowledge worker wants the spectacle of professional sport. If the knowledge worker wants to see human bodies, s/he also wants to be seen as a human body. A central imperative for knowledge worker culture is, therefore, an environment that stages the display of the human body. Cafe´s spilling onto the pavement, brightly lit arcades, harbour-side shopping, walkways down the river, thronging malls, public parks: all so many

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catwalks and stages for the human body. In this context the authors note the warm climate of Australia, which precludes the bundling of bodies in clothes, is a valuable natural stage property and that night-lighting that illuminates public space is similarly very desirable. The knowledge worker wants a style of built environment that displays the human body before the public gaze. Such a built environment – and there are many design alternatives – completes the virtual circle of bodily consolation. Successful contemporary urban development allows the human body to be both seen by, and to see, other bodies. Desire arising from a workplace without bodies looks, in short, for dramatic fulfilment. The knowledge worker wants a built environment that looks like so many stage sets. The paradigmatic stage-like stylings of Southern Californian urban development and the eclectic, assembled quality of much post-modern architecture come to mind. The authors can also locate here a cultural enthusiasm for ‘‘ethnic’’ neighbourhoods, for multiple and diversely gendered communities, as so many exotic settings for recreation – or perhaps, more accurately, for play. Creative people, it appears, desire created places. The contention, in short, is the knowledge worker wants picturesque spaces for human display. The knowledge worker, who at work is confined in a cubicle before a monitor, moves, ideally, scene by scene, through a recreational environment of display. The mode of transport between places should support this cultural quality. Thus, transport for the knowledge worker when not at work should be provided not only in conventional terms of efficiency, or how rapidly it moves between origin and destination, but in terms of picturesque possibility. In a knowledge worker environment, urban pathways, for walking and cycling, and local public transport that allows the human body to see and be seen are at a premium. In contrast to a transport intensive environment constructed around the rapidity of movement the authors summarise this analysis in the formulation: the knowledge worker wants a transport rich environment. The desire of the knowledge worker for public display also has consequences for domestic space. The suburban dream was constructed around the private domesticity of the detached house and its fenced garden. It was, and is, an enclosed space hidden from public view. The knowledge worker in contrast wants to see and be seen. In such a culture the role of the abode is reduced. It becomes, in caricature, a second order place made bearable by the electronic import of images from other worlds. The knowledge worker may still value domestic space, but s/he much prefers to eat, to play and to live, in public. It is as if the human body compensates for its lack of presence at work, with an excess of display in the ‘‘public-home’’. It can be argued that the international success of the Big Brother television show is a social index of the power of such desire. The publicity, as it were, that now surrounds the life of the knowledge worker brings with it anxiety. The knowledge worker in search of an audience must, unlike the stars of reality television, leave the security of suburbia, the private home and the dog, and enter an ambiguous public/private realm. In this realm s/he, like the most famous of fellow travellers, the Hollywood star, wants to be protected from the public at the same time as s/he solicits its gaze. In a culture that turns public space into private stage, the consumer brings the demand that s/he be as safe as if s/he were still in the traditional home. The knowledge worker, in short, wants personal protection in public space. This demand has spawned a contemporary security effort that is distinguished from the past and its protection of property. It culminates in the logic of the gated community. It is in this light people should see the paradoxical contention that the knowledge worker values ‘‘community’’. In a market society individuals with sufficient disposable income do not need other people – they need only shop assistants. Somewhere between friends and shop assistants, the culture of bodily display requires an audience and, even, extras. Such culture values a new sort of ‘‘community’’ – a community of strangers. The new spaces between private place and public realm – the space of the community of strangers – appear in the literature as ‘‘third space’’. Such a descriptive understanding leaves the understanding of ‘‘the home’’ unchanged. The authors, on the other hand, see

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‘‘the home’’, as it has been used and valued, as of diminished importance for the knowledge worker household. One physical consequence of such diminution is apparent in recent newspaper reports of the impending demise of the ‘‘Great Australian Backyard’’. New developments of detached housing with very limited surround are increasingly common even on the suburban fringe. Certainly, people can anticipate a more intensive domestic form in redeveloped inner city areas, where good design will give some priority to the compensatory provision of a range of ‘‘third spaces’’. Such spaces will privilege adult activity. As such they are not as inherently safe as the antecedent suburban backyard designed for children. Ideally, such space is monitored by the knowledge worker ‘‘community’’ – the members of which need only see one another. Thus, knowledge workers jogging or walking through the neighbourhood, early in the morning or as evening falls, are comforted by the sight of fellow travellers who, while they might be recognised from their routine, need never be spoken to – a community of strangers. In addition to what can be termed as ‘‘corporeal consolation’’ the knowledge worker seeks one other major cultural recompense. S/he desires that culture make good industry’s ravage of time. It is commonplace that despite industrial modernity’s century-old promise of time-saving technology, the contemporary human being is increasingly short of time. The knowledge worker, who coined the language of 24/7, desires real and imaginary compensation for this loss. As the authors have seen, the knowledge worker is not a homebody. Even once settled in a particular city precinct, the knowledge worker travels both widely and often. The friction of travel, however, causes time to tick particularly loudly. The knowledge worker, consequently, is drawn to urban regions that mitigate this effect with a dense network of internal and external transport links. While public transport is desirable, especially if it offers an attractive setting for display (e.g. urban and suburban trains, trams), good road linkage that allows the uninterrupted flow of vehicular traffic through the wider urban region and beyond is essential. Intensive external linkages, especially international air services, are of similar import. In sum, the authors contend the knowledge worker wants a transport-intensive environment. There is, of course, a potential conflict between the desire for a transport-rich local environment that displays the human body and a wider transport-intensive environment, ordered around the efficient movement of people and goods. Design must meet this challenge. Beyond the desire for a transport intensive environment that will ‘‘save’’ actual travel time, the knowledge worker also wants some relief from the anxiety of modern temporality. In short, the cultural capital of a knowledge worker precinct should include places where time slows down – if not really then, at least, symbolically. Thus, art, with its imagined timeless human verities, offers significant consolation to many knowledge workers. Indeed, so pervasive is the provision of static and performance art spaces in the knowledge worker environments of the world they can be considered essential. Similarly, the culture of ‘‘authenticity’’ displays for human eyes artefacts that stretch back through time and across space, conjuring if not a timeless zone then certainly one where time endures. Time does not tick away; it attaches itself to the authentic thing, it lives in the authentic place. And finally, the cult of history, that seeks to rediscover and preserve the past, likewise constructs an environment rich in a dream time that stretches back to the earliest of eras. In sum, in contrast to the time-intensive space of contemporary production, the knowledge worker wants places rich in time.

Essentials for attracting and retaining knowledge workers This section discusses the essential aspects for attracting and retaining knowledge workers to a knowledge city. The types of factors considered can be wide ranging and include the city’s knowledge base, its economic base, the level of accessibility and quality of life, the level of urban diversity and urban scale and questions regarding social equity. Here the authors discuss these under four broad headings.

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‘‘ Knowledge workers expect to change jobs, if not occupation, relatively frequently. ’’

Quality of life The quality of urban life is of vital importance to a knowledge region (Florida, 2002). Van den Berg et al. (2004) have found such quality increasingly reflected in the location decisions of workers and firms. Quality of life, the ‘‘liveability’’ of a region, is commonly expressed in an index that includes such factors as the standard and variety of amenitys, education and community facilities, climate, environmental quality, housing affordability, crime level, and transportation access. Similarly, the leisure and cultural possibilities of a region are also of growing significance for mental workers (Van den Berg et al., 2004; Yigitcanlar, 2005). All of which is not to say more traditional considerations such as the quantity, quality, and price of housing, housing affordability, are not also key in attracting knowledge workers (Berry, 2005; Bontje and Musterd, 2005). Knowledge workers, it would appear, want it all. Urban diversity Urban diversity, the most significant dimensions being ethnicity, gender, nationality, sexual orientation, is important to knowledge workers. The range of such diversity spans the person (e.g. gender), the community (e.g. ethnicity) and the place (e.g. the architecture of the urban fabric) (see Van den Berg et al., 2004). Diversity, in the best of all possible worlds, is expressed in a cosmopolitism atmosphere, accepting of strangers and with open channels for the communication/exchange of knowledge (Florida, 2002). On the other hand, of course, diversity can breed social tension and conflict; usually between the resident culture and an unaccepted and/or unaccepting ethnic minority (Carvalho, 2006). Social equity Social equity, some have argued, is a key dimension of sustainable urban economic growth. The 3Es of Ecology, Economy and Equity have been proposed as the triple hinge of sustainable development (EEA, 1997). For developed industrialised countries, deindustrialisation has been accompanied by growing unemployment, especially among young men. The young, under-educated, unemployed, alienated male is the negative role model of the twenty-first century city (Hall and Pfeiffer, 2000). The tendency of contemporary economic growth to increase the gap between social classes is leading to the emergence of a dual economy of knowledge workers and a growing underclass, often of ethnic minorities (Carvalho, 2006). The resultant social tensions and conflicts, expressed, for example, as social exclusion and unemployment, discourage both knowledge workers and investing firms away from a region of perceived social danger (Van den Berg et al., 2004). From the perspective of sustainable growth, therefore, it is important to reduce poverty and inequality. Policy that supports the ‘‘up-skilling’’ of local people and businesses is, some have argued, an important issue for city governments of prospective knowledge cities. Quality of place Richard Florida (2002) has suggested replacing the concept of ‘‘quality of life’’ with that of ‘‘quality of place’’. He finds the former too vague and prefers the stronger material focus of the concept ‘‘quality of place’’. This underlines the importance of place for Florida. His concept of creative capital includes a dimension of place necessary not only to attract knowledge workers but to keep them productive. Quality of place refers to the unique set of characteristics that define a place, making it attractive and liveable. For Florida the set of desirable amenities include parks, bike trails, cultural amenities, such as museums and art galleries, a rich variety of cafe´s and

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restaurants, a vibrant nightlife, and a diverse and tolerant population. From these amenities he derives three major dimensions of quality of place: 1. What’s there: the combination of the built environment and the natural environment – a proper setting for the living of creative lives. 2. Who’s there: diverse kinds of people, interacting and providing cues that anyone will be accepted and can make a life in the communities. 3. What’s going on: the vibrancy of street life, cafe´ culture, arts, music and people engaging in outdoor activities (Florida, 2002, pp. 231-2). Clark (2003), in his paper ‘‘Urban amenities: lakes, operas, and juice bars do they drive development?’’, distinguishes two fundamental types of amenity, namely, ‘‘natural’’ and ‘‘constructed’’ amenity: 1. Natural amenities: climate, lack of humidity, moderate temperature, water access (i.e. waterfronts), topographic variation. 2. Constructed amenities: sidewalk cafes, tattoo/piercing studios, meditation/yoga, coffee houses, bookstores, movie theatres, liberal arts, universities, opera, dance studios, juice bars, bike lanes and trails, gourmet restaurants, research libraries. Clark uses his distinction to explore differences in desire between the constituent strata of knowledge workers. He argues, for example, that the demand of young college graduates is weighted in favour of constructed amenity, while older knowledge workers prefer a greater balance between the two amenity types. He also found his typology useful in characterising the preferences of different ethnic communities and new immigrants groups. Scale of impact has also been used to distinguish between urban amenities. The most commonly suggested metric is a binary distinction between city-wide amenity and community amenity (see Llewelyn, 2006).

Conclusions The new growth theory establishes that human capital accumulation embodied in knowledge workers is essential for sustained growth and economic development of a city. Policy makers have therefore become increasingly concerned about attracting and retaining knowledge workers in their cities. The literature indicates that one of the most effective ways to attract knowledge workers and promote economic development is the creation of amenities (Mathur and Stein, 2005, p. 265). Following on from the above statement, in this paper the authors have attempted to portray the type of urban region and environment most attractive to the knowledge worker. The authors consolidate the findings in two listings. The first records the more detailed of the derivations. The knowledge worker wants: B

a retail-rich environment;

B

the spectacle of professional sport/music;

B

quality childcare services;

B

private school education for the household children;

B

access to private health care facilities;

B

static and performance art spaces;

B

‘‘authentic’’ and ‘‘historical’’ places;

B

affordable housing, particular for PhD students, post-docs; and

B

an affluent retirement.

The second listing consists of more structural conclusions. The knowledge worker wants: B

an intense twenty-first century urban environment;

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B

to see the perfected human body;

B

picturesque spaces for human display;

B

to be part of a new community of strangers – defined by aggregation in action;

B

a transport rich environment; and

B

places rich in time.

In summary, knowledge cities and cities aspiring to become knowledge cities that are capable of addressing abovementioned desires of knowledge workers would likely be successful in attracting and retaining them.

References Baum, S., Yigitcanlar, T., Horton, S., Velibeyoglu, K. and Gleeson, B. (2006), ‘‘The role of community and lifestyle in the making of a knowledge city’’. December, Urban Research Program, Griffith University, Brisbane. Berry, M. (2005), ‘‘Melbourne – Is there life after Florida?’’, Urban Policy and Research, Vol. 23 No. 4, pp. 381-92. Black, D. and Henderson, V. (1999), ‘‘Urban growth’’, Journal of Political Economy, Vol. 107 No. 2, pp. 252-84. Bontje, M. and Musterd, S. (2005), ‘‘What kind of a place do the creative knowledge workers live in?’’, in Franke, S. and Verhagen, E. (Eds), Creativity and the City: How the Creative Economy Changes the City, NAI Publishers, Rotterdam. Carvalho, L. (2006), ‘‘Governance challenges towards a knowledge economy: the case of the metropolitan area of Porto’’, European Institute for Comparative Urban Research, Erasmus University Rotterdam, Rotterdam. Clark, T. (2003), ‘‘Urban amenities: lakes, opera, and juice bars – do they drive development?’’, in Clark, T. (Ed.), The City as an Entertainment Machine, JAI Press/Elsevier, New York, NY. Debord, G. (1994), The Society of the Spectacle, Zone Books, New York, NY. EEA (1997), Towards Sustainable Development for Local Authorities: Approaches, Experiences and Sources, European Environment Agency, Amsterdam. Eaton, J. and Eckstein, Z. (1997), ‘‘Cities and growth: theory and evidence from France and Japan’’, Regional Science and Urban Economics, Vol. 27, pp. 443-74. Florida, R. (2002), The Rise of the Creative Class and How it’s Transforming Work, Leisure, Community and Everyday Life, Basic Books, New York, NY. Florida, R. (2005), The Flight of the Creative Class: the New Global Competition for Talent, Harper Collins, London. Glaeser, E. (2000), ‘‘The new economies of urban and regional growth’’, in Clark, G., Gertler, M. and Feldman, M. (Eds), The Oxford Handbook of Economic Geography, Oxford University Press, Oxford. Hall, P. and Pfeiffer, U. (2000), Urban Future 21: a Global Agenda for 21st Century Cities, E&F.N. Spon, London. Hayden, D. (1984), Redesigning the American Dream, Norton, New York, NY. Jacobs, J. (1969), The Economy of Cities, Random House, New York, NY. Knight, R. (1995), ‘‘Knowledge-based development: policy and planning implications for cities’’, Urban Studies, Vol. 32 No. 2, pp. 225-60. Levi-Strauss, C. (1966), The Savage Mind, University of Chicago Press, Chicago, IL. Llewelyn, D. (2006), Quality of Place: The North’s Residential Offer Phase 1 Report, Llewelyn Davies Yeang Architecture Planning Design, UK, March. Mathur, V. and Stein, S. (2005), ‘‘Do amenities matter in attracting knowledge workers for regional economic development?’’, Regional Science, Vol. 84 No. 2, pp. 251-69.

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Raspe, O. and Van Oort, F. (2006), ‘‘The knowledge economy and urban economic growth’’, Papers in Evolutionary Economic Geography, No. 06-07, Utrecht University, Utrecht. Reich, R. (1992), The Work of Nations: Preparing Ourselves for 21st Century Capitalism, Vintage Books, New York, NY. Saxenian, A. (1994), Regional Advantage: Culture and Competition in Silicon Valley and Route 128, Harvard University Press, Cambridge, MA. Van den Berg, L., Pol, M., Russo, A. and Van Winden, W. (2004), ‘‘Cities in the knowledge economy: a literature review and a research framework’’, The European Institute for Comparative Urban Research, Erasmus University Rotterdam, Rotterdam. Yigitcanlar, T. (2005), ‘‘The making of knowledge cities: lessons learned from Melbourne’’, Proceedings of the International Symposium on Knowledge Cities, Arab Urban Development Institute. Medina, Saudi Arabia, 28-30 November.

About the authors Tan Yigitcanlar is a Lecturer in Urban and Regional Planning at the School of Urban Development, Queensland University of Technology, Brisbane, Australia. Tan Yigitcanlar is the corresponding author and can be contacted at [email protected] Scott Baum is Associate Professor and the Deputy Director of the Urban Research Program, Griffith University, Brisbane, Australia. Stephen Horton is an Adjunct Research Fellow in the Urban Research Program, Griffith University, Brisbane, Australia.

To purchase reprints of this article please e-mail: [email protected] Or visit our web site for further details: www.emeraldinsight.com/reprints

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Working and learning in a knowledge city: a multilevel development framework for knowledge workers Blanca C. Garcia

Abstract Purpose – The purpose of this paper is to present results of a four-year qualitative research project on the dynamics of skill development strategies in e-learning workplace environments.

Blanca C. Garcia, Institute for Development Policy and Management (IDPM), University of Manchester’s School of Environment and Development, Manchester, UK.

Design/methodology/approach – A potential knowledge city, Greater Manchester relies on its human (individual and collective) capitals, put to work in knowledge engines such as its universities. Such context has become a complex and uncharted territory for research. Research analysis within knowledge-based higher education territory clearly demands knowledge-based tools. Therefore, the research behind this paper has adopted Carrillo’s generic system of capitals, an integrative KM3 taxonomy. Such framework has been instrumental in identifying contextual aspects, drivers and rooted strategies of k-facilitators’ adaptation to emergent learning environments. Findings – The grounded model reported here further conceptualised how Mancunian e-learning practitioners seemingly follow an embedded process of adaptation. Practitioners actually develop strategies to adapting in emerging learning spaces while they adapt to swiftly changing conditions in their workplace environments. The skill developments facilitators undertake seemingly allow them to link and connect to learning spaces, as well as to the existing university social systems and networks of learning. Those systems and networks are integrated to the city’s knowledge capitals, and beyond. Originality/value – By exploring Greater Manchester (UK) universities’ e-learning strategies, this paper contributes to KM theoretical understanding of how facilitators develop their knowledge-based skills in emergent higher education learning spaces. Keywords Knowledge management, Knowledge organizations, E-learning Paper type Research paper

Introduction Since Peter Drucker’s 1959 book Landmarks of Tomorrow launched the notion of knowledge worker, it has gradually raised research awareness as a key element in knowledge management (KM) processes of tacit knowledge conversion. The knowledge worker concept would make reference to anyone who works for a living at the tasks of developing or using knowledge, such as programmers, systems analysts, technical writers, and maybe to academic professionals and researchers in the information systems disciplines. However, the term knowledge worker has also progressively included people outside information technology: anyone who communicates and transforms specialised information such as lawyers, teachers, scientists and learners of all kinds. Workplace learners are amongst these emerging types of knowledge workers. They have been identified in particular (mostly educational) contexts, as knowledge managers (Cothrel and Williams, 1999); knowledge facilitators[1] (McNeil, 2004) or knowledge citizens (Martinez, 2006). Still, KM specialists are just beginning to understand what these knowledge workers do and how their work processes and competences can be improved. This piece of research work is aiming to contribute to the development of KM theoretical understanding of skill development in a particular knowledge worker group: that of knowledge facilitators in the context of higher education workplaces.

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DOI 10.1108/13673270710819771

The paper explores the themes and implications concerning workplace skill development of e-learning practitioners through the learning journeys of facilitators in the Greater Manchester (UK) university context. Through a grounded action-learning study on e-learning facilitation, the paper discusses how knowledge facilitators in the Mancunian HEIs have made strenuous efforts in technology-based skill development to adapt to emerging virtual environments. As the Manchester city region advances third generation of KM initiatives as part of its regional development policy, the city itself has become a learning environment under the flag of Knowledge City models, parallel to the workplace environment and the traditional institutional and social settings. As the city becomes a complex and uncharted learning environment, knowledge facilitators develop new learning skills parallel to the skills they have developed for workplace and virtual learning environments: the ones that allow them to link and connect to the existing university social systems and networks of learning. A complex skill development analysis requires a multilayered skill development framework, which this paper will advance. Such framework advances that connectivity and other skills in knowledge facilitators will provide them with the tools needed for individual and collective knowledge sharing and conversion within the wider institutional and social settings, key repositories of the human and social capital of this city region.

Universities as systems of learning Considered an IT-based innovation, e-learning has become the debatable promise of ultimate internet connectivity in our millennial age, constituting an incontestable learning alternative for all those whose working places are connected. The emergence of on-line learning environments in the workplace such as My spacew, web blogs, wikies and video-based webinars are development tools clearly leading to an on-line aspiration of co-creation where individuals, and workplace learners in particular, expect to have a voice in the process of creating content through communicating (Siemens, 2006). Today’s computer-networked workplaces are therefore flooded with different forms of communication, namely chatting rooms, Yahoow Q&A postings, e-mails, Skypew calls, radio chat broadcastings, and discussion boards in on-line communities. All these represent new modes for task agreements and career development opportunities available on Internet networks. By encouraging casual but meaningful ways of communication in the workplace, such spaces are seemingly becoming a new form of robust and creative social hubs. They have thus given way to the still ill-defined, multifaceted notion of virtual communities, and emerging societal forms that are turning our big old world into a global village. At the core of this complex makeover of the social, economic and technical sub-systems, lies the system of learning on which each of our societies rely on. Our systems of learning are historical structures now seemingly developing into systems of meaning creation (Tuomi, 2004, p. 2). Indeed, our societies’ learning systems appear to be challenged by the power of networked communication with varying levels of intensity. More than an information revolution, the new millennium has openly confronted us with a learning revolution (Sloman, 2001), for which intranets, virtual communities and e-learning are seemingly only the tip of a massive iceberg. Given the emphasis of communication in meaning-creation processes, information and communication technologies (ICTs) are indeed playing a major role in the system of learning of emerging knowledge-based societies, or k-societies.

‘‘ Knowledge management specialists are just beginning to understand what knowledge workers do and how their work processes and competences can be improved. ’’

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In such context, universities and HEIs are rapidly evolving from traditional knowledge-producers into unprecedented life-long learning stakeholders. Education and educational sub-systems at regional and global levels are being radically transformed. Academics in the universities of the Greater Manchester city region, as many others around the world, are being encouraged ‘‘to engage formally with learning and teaching in a way that is sharply different from previous university practices’’ (Jones, 2004). As internet-based learning and communication tools continue to grow in volume and complexity, all those working and learning in a university or HEI around the world are challenged to make sense of the co-evolutionary processes between learning and the new information and communication media. In this context, universities as learning systems are hit by skill development drivers such as internationalisation, implying the introduction of an international focus to existing courses, in order to attract international students; professionalisation or a recognised certification of staff skills following lifelong learning schemes; and personalisation, which aims to take into account the student demands of tutoring and mentoring on an individual basis, as emerged in the present grounded study (Table I). Moreover, as mentioned in an earlier work (Garcia, 2004), political and social processes in aspiring knowledge cities like Manchester include city region drivers impacting skill development, such as: centralisation, by which Manchester depends on central government for funding initiatives; fragmentation, since the connection between perceived identity and emerging identities within the global economy seem to be lost. Finally, dislocation skill gaps, access and inclusion issues as obstacles to skill development and lifelong learning schemes. Such complex scenarios permeate the intricacies of research in higher education virtual environments. For research purposes, some scholars have suggested a grounded theory approach for inductive theory building by means of a meta-theoretical framework ‘‘that could develop the story line of research’’ (Sarker et al., 2001, p. 40). The methodological step to include a meta-theory in a grounded research is aiming to ’’string together a theory involving all major categories and sub-categories’’ (Sarker et al., 2001, p. 42). The meta-theory to support constant comparison in these grounded research efforts has been the

Table I Skill development drivers Drivers

Description

Internationalisation

Introduction of an international focus to existing courses, in order to attract international students Establishment of a university campus off-shore Intensification of partnerships and academic exchange programmes with universities in other countries Introduction of an international hub into teaching and research, bringing teams from different countries to work together on a common project. Equivalent to recognised certification A career development process has included the traditional four-year degree into a profession and/or a postgraduate course or degree Regular attendance to the continuous education unit Lifelong learning plan that might include updates on problem-solving models, pedagogical strategies and foreign language and ICT skills Adoption of an individualised learning programme for each student, supported by educational technology in Distance Learning, e-Learning or Distributed Learning schemes In the USA, the UK and other European countries, personalisation includes the introduction of e-portfolios (individual education and career path made public through internet facilities) which have raised privacy issues and the cost of introducing the National Identity Card in the UK

Professionalisation

Personalisation

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knowledge-based development (KBD) framework of generic system of capitals (GSC) (Carrillo, 1998, 2006). The generic system of capitals model The generic system of capitals model (GSC) is a value-based, KBD framework ‘‘at the crossroads of development and change’’, both in organisations and in society (Carrillo, 2004; Tuomi, 2004). In emerging knowledge societies, urban institutions have become knowledge-intensive and have created new learning contexts too complex for traditional research methods. In order to cope with such complexity, KBD meta-theory was an effective tool to first apprehend and then comprehend the role of knowledge facilitation and learning in KBD initiatives such as the ones Manchester city region has undertaken. Although the GSC unit of analysis stands at the city level, by introducing the Knowledge City (KC) concept as unit of analysis, the framework is inclusive of all city levels: individuals, groups, organisations/institutions and all sector clusters private, public and social. The GSC framework seeks to identify the particular traits of each city by accounting its different capitals, including as many city layers as needed. The GSC apprehends a knowledge city as one whose citizenship ‘‘undertakes a deliberate, systematic attempt to identify and develop its capital system, with a balanced and sustainable approach’’ (Carrillo, 2004, p. 34). From this perspective, the value generated by each citizen’s (working and learning) participation, is critical to the city construction of its value capitals. Moreover, generated value is multiplied in terms of its significant relational basis: only shared knowledge amongst connected knowledge citizens contributes to the city system of capitals. For the purposes of this research, these considerations were critical to understand the role of knowledge facilitation, and how it emerges and consolidates in real and virtual environments. Indeed, the KC model of analysis builds up a comprehensive view of traditional and knowledge capitals of a given city, according to the following eight capitals categories: 1. Identity – capability to create and evolve a distinctive and well-positioned urban personality. 2. Intelligence – capability to identify/ foresee and adequately respond to significant agents and events. 3. Financial – capability to generate and sustain a healthy monetary base. 4. Relational – capability to develop quality interactions with all significant internal and external agents. 5. Human individual – capability to create conditions for the full biological and psychological development of residents. 6. Human collective – capability to enhance the goal achievement potential of its constituent communities. 7. Instrumental-material – capability to take advantage of location and to build and renew a world-class physical infrastructure. 8. Instrumental-intangible – capability to transfer knowledge and foster innovation in all major areas of city life. This model has therefore given a systemic perspective of capitals to this research. It also has put in perspective the specific accounts of ‘‘social capital’’ of the Greater Manchester HEIs as the relevant element that brings sense to the theory emergence of knowledge facilitators’ grounded theory (Garcia, 2004, 2006a, b). Most importantly, the GSC framework has placed the role of knowledge facilitators as a key element in the ‘‘Human Individual’’ and ‘‘Human Collective’’ capital accounts relevant in

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emerging knowledge-based societies, bringing to light the rewards and drawbacks of such development initiatives, as discussed in Garcia (2004, 2006a, b).

Inter-twined generations of knowledge This research rests in two major assumptions about learning processes: ‘‘learning is the key factor that distinguishes the knowledge society from the information society’’ (Tuomi, 2004), and ‘‘learning is profoundly conversational’’ (Dvir, 2006). Hence, this research had a sound theoretical standpoint for interaction-based research with e-learning practitioners in the Greater Manchester city region. Such standpoint conveyed a multidisciplinary view of facilitation strategies at different levels: first at practitioners’ level, then within e-learning practitioners groups, finally across different levels of e-learning models corresponding to different generations of KM (Figure 1). Three distinct generations of KM have been accurately scrutinized by a number of KM scholars (e.g. Wiig, 2000; Tuomi, 2004; Carrillo, 2004; Huysman and Wulf, 2005). They have stressed how first-generation of KM created a strong dependence on information and communication technologies (ICTs). They have also identified second generation KM concepts such as innovation and creativity, acknowledging that individual and organisational development depends more on people’s processes than on technology. In KM third generation models, a number of perspectives are emerging, in which societies appear to be challenged by the power of networked communication with varying levels of intensity. More than an information revolution, this third generation is bringing a learning revolution (Sloman, 2001), in which our systems of learning are seemingly developing into systems of meaning creation (Tuomi, 2004, p. 2). In such context, different working definitions of e-Learning have emerged. In fact, at least three generations of e-Learning developed in the last decade: on-line Learning, e-Learning 1.0, e-Learning 2.0. In the specific case of Greater Manchester universities, models of distributed learning, networked learning and computer supported collaborative learning Figure 1 Three dimensions of knowledge facilitation

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‘‘ At the core of the complex makeover of the social, economic and technical sub-systems lies the system of learning on which each of our societies rely. ’’

(CSCL) appeared embedded in their e-learning practices. These distributed learning approaches subscribed different levels of connectivity, defined as interaction density according to participants’ interactions and affordances of technologies (Jones et al., 2006). Most importantly, these different levels of e-learning connectivity, corresponded to contextual influences of first, second and third generations of KM as represented in Figure 1. Such considerations led to a qualitative methodology alternative seeking to discover and articulate the research experiences that would eventually translate into explicit knowledge on e-learning skill development strategies.

Discovery and articulation of knowledge A number of scholars have emphatically exemplified the qualitative side of KM, amongst which, notably Pauleen et al. (2005). Existing qualitative and grounded research into developing facilitators has informed this research (Pauleen et al., 2005; Yoong and Pauleen, 2004; Sarker et al., 2001; Maznevski and Chudoba, 2000; Trauth and Jessup, 2000). From face-to-face to virtual environment facilitation, it is argued that amongst other qualitative tools, Action learning provides a way to ‘‘discover’’ knowledge through ‘‘live’’ data collection; while Grounded Theory methodologies provides a way to ‘‘articulate’’ this knowledge as it provides room for reflection and knowledge creation through models an mental maps, that later become the communication codes to render research (tacit) knowledge operational, explicit and transferable (Pauleen et al., 2005, p. 3). Therefore, a grounded action learning methodology was chosen for this process-oriented research project. The emergence of converging points between development, knowledge sharing and learning in institutional (media-intensive) knowledge-based practice was identified. Most importantly, the emergence of overarching human agency at different institutional levels in Greater Manchester city region was also identified. In terms of data gathering, a total of 20 e-learning/distributed learning events were attended, producing a wealth of written and/or audio documents and transcriptions. Events were participatory in nature, combining a different degree of participation in exhibitions, seminars, conferences, forums, staff development courses and open house days. Also a total of 40 semi-structured interviews were obtained, of which 25 interviews were digitally recorded. Transcriptions of 31 interviews were typed, 25 fully transcribed and six were partly transcribed with annotations. For data analysis, grounded theory methodology (GTM) was a useful instrument for this researcher to develop e-learning constructs through constant comparative analysis of data, looking at the same event or process in different settings or situations (Glaser, 1992, p. 40). By looking at knowledge facilitator profiles in the different university settings in the same basic context (the Greater Manchester region), the author has aimed to include multiple voices, views and visions in our rendering of lived experience (Charmaz, 2000, p. 525). Developing connectivity In grounded theory methodology contexts, seeing the core category emerge is a way of responding to the main concern of research (Glaser, 1978, p. 100). Iterative contact with transcripts and documents (mainly from University of Manchester sources) converted into conceptual categories, and then into theoretical categories, as listed in Table II.

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Table II Developing connectivity strategies Theoretical categories

Conceptual categories

Possible impact on skill development

Connectivity

Degrees of interaction Ability to access Inclusivity Ability to participate Empowerment Ability to build a network of contacts Sense of collaboration – cooperation Communicator abilities Skills to share knowledge Committed to community members Ability to cope with virtuality and reality Sense of a public identity for facilitation practice Ability to embrace change Self-organised learner Autonomous Tolerance to fragmentation, piecemeal work, and uneven distribution of knowledge Regional/global scope Creativity Reflexivity Endurance Patience Continuity

Ability to access and participate

Community membership

Environment adaptation

Systemic view

Lifelong learning

Inclusivity Ability to interact and build knowledge Ability to develop interconnectedness of relationships Ability to share knowledge, willingness to change and adapt

Ability to integrate concepts, and bring opposite views to a comprehensive understanding of reality. Identity development Ability to access

Eventually, the core category that emerged for skill development was established as Developing Connectivity, indicating different degrees of interaction that a knowledge facilitator undertakes with other learners, his ability to access, attitude and possibilities of inclusivity, and his ability to actively participate in the learning setting. Developing Connectivity thus became the basic social process and main aim that practitioners pursue when developing knowledge facilitator skills. Later, following GTM site spreading into University of Salford and Manchester Metropolitan University, the core category and basic social process of Developing Connectivity was finally established. In order to develop this emerging theory, the subcategories and conceptual categories outlined in Table I were further conceptualised, and systematically compared with prior categories. The theoretical categories of community membership (CM), environment adaptation (EA), systemic view (SV) and lifelong learning (LLL) progressively outlined the path of skill development followed by e-learning practitioners going from real learning spaces into virtual learning spaces. Eventually, the four-quadrant model presented in Figure 2 was developed, with Adaptation and Adoption as the extremes of an X continuum that indicated going from difficulty in accepting change (Adaptation) to Adoption, a trait acceptance and agreement to embrace change characteristic of later skill development stages in e-learning environments. This actually means a sensitive responsiveness to the workplace and city environments as learning ones. People and Technology were placed in the Y axis extremes, indicating a continuum in which knowledge facilitators decide their focus: either they concentrate on dialogues and interaction regardless of the platform or they develop media-oriented interactions that favour knowledge creation. The four strongest theoretical categories became fields in the quadrants, as major stages of knowledge facilitator skill development. In a further development of the model, such stages followed a specific four-step order. First, the e-learning practitioner embraces a Lifelong Learning process, then, he undertakes a new environment adaptation. Once comfortable in the new environment, he is able to take a systemic view of his practice, and eventually, he undertakes the steps to earn a community membership, through further interaction with community participants. Such a cycle is depicted in Figure 2.

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Figure 2 Developing connectivity core categories

Once the core category of developing connectivity was established, the four main development strategies that e-learning practitioners undertake to develop their connectivity (LLL, EA, SV and CM) were also established in an orderly cycle. Then, the focus of this research shifted to the underlying values and assumptions permeating in practitioners, educational units, and higher education institutions, in order to identify a comprehensive cycle of institutional skill development for e-learning practitioners in higher education workplaces.

Facilitators as knowledge builders In the meantime, a working definition for knowledge facilitator was progressively consolidated. A k-facilitator was identified as any workplace learner who has the ability to analyse and articulate the data into a form that relates to the workplace situation, usually to bring suggestions, new visions or solutions to workplace issues. To become knowledge workers, workplace learners would have developed a set of skills that include a strong individual and group identity, and a clear awareness of multiple systems, communities and environments, as it emerged from the data. These elements were integrated into a grounded framework of developing connectivity. Clearly, knowledge workers, as any other learners require new skills in order to be able to function in space. Therefore, working environments characterised by continuous changing information and knowledge requires that ‘‘we place greater emphasis on developing the skills of pattern recognition and the ability to make sense of this rapid and continual influx of knowledge’’ (Siemens, 2006). For the purposes of this research paper, it is advanced that any individual who has developed such pattern recognition ability with workplace relevance; in his real or virtual environment has become a knowledge facilitator. Although our unit of analysis of this research was a group of e-learning practitioners, this paper advances that knowledge facilitators are not necessarily exclusive of on-line, virtual environments. In fact, they are found in every workplace; especially in those challenged by swift organisational change. Indeed, they include virtually every level of responsibility, from officers to line management and senior management. The role of the knowledge facilitator This conceptualisation of knowledge facilitator (k-facilitator) in complex Knowledge City contexts was indeed influenced by private sector models of organisational learning. In private sector organisations, a facilitator’s role usually includes providing input to relevant colleagues of learners before, during and after programmes or projects undertaken by the

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organisation. In such settings, the k-facilitator is seen as a critical role for the efficient organisation of learning schemes. Usually, the knowledge facilitator is a knowledge builder, because he: B

Has a strategic and operational view of projects in close co-ordination with line management, middle management and even senior management. He provides assistance and guidance in working unit processes, giving feedback on actions taken, thus fostering learning and knowledge leverage.

B

Organises team communication and interactions, ensuring information is readily available for all relevant participants or members. He establishes and facilitates communications with and amongst partners, stakeholders, customers, suppliers and all relevant participants of a working unit. In this respect, the knowledge facilitator routes messages, documents and key information to specific audiences (Board, donors, national and international networks, and other interested parties or partners, and makes sure that solid alignment is maintained between group, unit and institutional objectives.

B

He identifies the areas of expertise to develop in his working unit, as well as identifying the people whose experience will prove helpful in project completion. Also, he provides support for the monitoring and evaluation of learning activities.

In educational contexts this knowledge facilitator role, still in many ways held by lecturers and teachers, is being replaced by other characterisations of similar responsibilities, although with different approaches: supervisor, tutor, on-line tutor, facilitator, learning (course) facilitator, on-line discussion moderator, and only recently e-moderator and e-learning practitioner. In these lines of thought, e-Learning practitioners are a specific case of knowledge facilitators whose practice is mainly (but not exclusively) performed in virtual environments.

Findings In the context of knowledge city complex models of learning, two major outcomes emerged during this study: a typology of knowledge facilitators that could further identify the skill development cycle of knowledge facilitators, and a cycle of their development journey as observed emerging through grounded theory methodology. These findings have made explicit some of the issues of their skill development as they implemented and led e-learning strategies in a facilitating role. As interaction with data progressed, concepts such as connections, communities of practice and knowledge-building in social settings were identified (Stahl, 1999); some of them having significantly impacted the e-learning experiences of the knowledge workers identified for this study. In consequence, different definitions of knowledge and k-facilitation emerged as well, in parallel to the definitions found in e-Learning generations. In the process, six typologies of knowledge facilitators emerged as part of the grounded theory emergence. Typologies of knowledge facilitators Traditions of distance learning did not necessarily include the use of technology, and did not make any emphasis in facilitator-learner communications. At its best, this mode of learning in the first generation of KM, e-Training contexts required an e-trainer, the kind of facilitator that would transmit knowledge from documents to students’ memories, without a significant learning experience for the students. The co-learner lives in the transition space between e-training and e-learning 1.0 (Figure 1). This knowledge facilitator has renounced to the controlling comfort of knowledge as object and perceives learning as a process. The facilitation skills of a co-learner are under-developed, and places himself/herself as a friendly companion of other workplace learners in order to be able to understand and reflect on his own skill development at the same time he leads a group. As for the e-tutor, he is already influenced by the second generation of KM, with community and knowledge sharing aspirations. The e-tutor’s facilitation skills position him/her not as a companion, but an expert in the topic the tutorees are gaining their skills. Group interaction depends significantly on

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the e-tutors’ interventions, but he purposefully makes room for dialogues amongst the participants in which he has no role to play. It has been the e-moderator kind of facilitator that, at least in the Manchester higher education institutions, has brought the interaction into groups and the purposeful introduction of learning models of social learning, situated knowledge, and communities of practice. The e-moderator leads interaction when required, but most importantly, creates a learning space in which his interventions are limited to guide and foster a spirit of community, and promotes reflection on action. The networker is the kind of knowledge facilitator that builds a space for others to learn; and additionally, provides links to other similar, friendly spaces in which members of his present group can access by right to the membership in the original group. The networker provides access to multiple learning spaces available to the social construction of knowledge. Combining some of the characteristics of the previous knowledge facilitators, the networlder is the kind of facilitator that develops in others a purposeful process of collaboration in virtually any activity of life, with a vision for larger real and virtual regions as possible spaces for interaction and learning. The networlder is possibly the kind of knowledge facilitator that would be emerging as a characteristic role of the third KM generation. A cycle of knowledge facilitator development By identifying the steps that a knowledge facilitator undertakes when starting a skill development journey into virtual learning environments, this research has also identified a cycle for an e-learning journey (Figure 3) which includes a unifying framework of three inter-related steps: Drivers for knowledge facilitator development, Strategies developed to become a knowledge facilitator (LLL, EA, SV and CM), and the possible impacts on knowledge creation, according to knowledge facilitators’ new skill level. Each of the steps implies embedded tacit an explicit sub-cycles in the learning journey, and grounded Developing Connectivity depicting a knowledge facilitator learning cycle constitutes in itself part of a greater institutional cycle of learning. Such cycle aims to express a complex model of three layers: the first layer including the groups of e-learning practitioners, the second layer of institutional levels in which an increasing number of university units include e-learning as a common practice, and the third level of learning opportunities within a knowledge-based city. Moreover, the cycle representation aims to highlight the drivers identified within the institution and the city. Such Figure 3 Developing connectivity diagram

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‘‘ Universities and Higher Education Institutions are rapidly evolving from traditional knowledge producers into unprecedented life-long learning stakeholders. ’’

drivers identified in the grounded study have clearly influenced the skill development strategies adopted by knowledge facilitators throughout the unit learning process their institutions have undertaken.

Theoretical and practical implications As a result of the research project presented in this paper, a typology of knowledge facilitators and a theoretical k-facilitator learning journey have emerged. Such typology based on grounded data reveals specific skill development paths. It also reveals possible competency-development pole-posts for a key emergent type of knowledge worker: the knowledge facilitator type within the Greater Manchester city region in the UK. As depicted in Figure 3, institutional KM strategies are interrelated and interdependent of e-learning and other distributed learning strategies in the workplace. Figure 2 is a summative visual representation of how the interrelationships and interdependencies are expressed at the practitioner level, conceptualizing a learning cycle for knowledge facilitators. As the study presents this grounded view of how workplace learning strategies develop at different levels in a knowledge-intensive institution, a clearer path for institutional knowledge-generating strategies emerges, and brings in the notion that knowledge facilitation has key triggering and escalating effects on how higher education institutions develop their knowledge-based skills. This framework has advanced the importance and role of a skilful knowledge facilitator within working units, but most importantly, it has advanced that grounded basic social process such as Developing Connectivity are a way to lead practitioners through different interrelated and necessary stages of knowledge facilitator development. Figures 1 and 3 are a visual representation of the basic social process and the development cycle of a knowledge facilitator, containing the four major strategies identified from the data: lifelong learning, environment adaptation, systemic view and community membership. Each of these strategies has been emphasized from different angles as stand-alone strategies by scholars inscribed in different generations of KM and e-learning (Jones et al., 2006; Huysman and Wulf, 2005; Tuomi, 2004; Sumner, 2000; Stahl, 1999; Gibbons et al.,1994). Indeed, one of the theoretical developments of this research has been to integrate different workplace learning models and frameworks in a non-linear cycle in order to observe and apply it to the development of skilful facilitators. In combination with the GSC meta-theory, this framework emphasises the need for sytemic, comprehensive development tools that could go far beyond the workplace learning experience and into the city. By developing the knowledge facilitators’ awareness that they could be living, working and learning in a city that purposefully fosters knowledge (a knowledge city), the practical implications of this study could extend to the different spheres of knowledge workers, making the development process an integrated activity in institutions and organisations otherwise separated: industry, science and government. As we ponder how a grounded study on the development of knowledge facilitators can support efforts to developing workplace learners, we are convinced that exploring emerging roles of professionals that are able to leverage and manage knowledge become critically important in the social construction of communities that learn (Tuomi, 2004, p. 1). As we develop access to meaningful communication is such communities, we thus shape our own perceptions and those about other humans, cultures, and value systems in many ways. Clearly, a new breed of professionals with skilful ability is needed to leverage the

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knowledge-generating new processes. This might be the just-in-time learning turn for knowledge facilitators to assume such key role, in universities and beyond.

Note 1. A knowledge facilitator refers to both genders of practicing professionals. However, for the purposes of this research paper the male pronoun (He) has been used to refer to both genders of professionals.

References Carrillo, F.J. (1998), ‘‘Managing knowledge-based value systems’’, Journal of Knowledge Management, Vol. 1 No. 4, pp. 280-6. Carrillo, F.J. (Ed.) (2006), Knowledge Cities: Approaches, Experiences and Perspectives, Butterworth-Heinemann (Elsevier), Burlington, MA. Charmaz, K. (2000), ‘‘Grounded theory: objectivist and constructivist methods’’, in Denzin, N. and Lincoln, Y. (Eds), Handbook of Qualitative Research, 2nd ed., Sage, Thousand Oaks, CA and London, pp. 509-35. Cothrel, J. and Williams, R. (1999), ‘‘On-line communities: helping them form and grow’’, Journal of Knowledge Management, Vol. 3 No. 3, pp. 54-60. Dvir, R. (2006), ‘‘Knowledge city, seen as a collage of human knowledge moments’’, in Carrillo, F.J. (Ed.), Knowledge Cities: Approaches, Experiences and Perspectives, Butterworth-Heinemann (Elsevier), Burlington, MA. Garcia, B. (2004), ‘‘Developing futures:a knowledge-based capital for Manchester’’, Journal of Knowledge Management, Vol. 8 No. 5, available at: www.emeraldinsight.com/10.1108/13673 270410558774 Garcia, B. (2006a), ‘‘Learning conversations: knowledge, meanings and learning networks in Greater Manchester’’, Journal of Knowledge Management, Vol. 10 No. 5, pp. 99-109, available at: www. emeraldinsight.com/10.1108/13673270610691215 Garcia, B. (2006b), ‘‘UniverCities: innovation and social capital in Greater Manchester’’, in Carrillo, F.J. (Ed.), Knowledge Cities: Approaches, Experiences and Perspectives, Butterworth-Heinemann (Elsevier), Burlington, MA. Glaser, B.G. (1978), Theoretical Sensitivity, Sociology Press, Mill Valley, CA. Huysman, M.H. and Wulf, V. (2005), ‘‘The role of information technology in building and sustaining the relational base of communities’’, The Information Society, Vol. 21 No. 2, pp. 81-9. Jones, C. (2004), ‘‘Theory and the practices of learning technology’’, Research Proceedings of the Networked Learning Conference, Sheffield, 2004, available at: www.networkedlearningconference.org. uk/past/nlc2004/proceedings/symposia/symposium1/jones.htm Jones, C., Ferreday, D. and Hodgson, V. (2006), ‘‘Networked learning, a relational approach – weak and strong ties’’, Proceedings of the Networked Learning Conference 2006, 10-12 April, 2006, Lancaster, UK, available at: www.networkedlearningconference.org.uk/abstracts/pdfs/01Jones.pdf McNeil, C. (2004), ‘‘Exploring the supervisor role as a facilitator of knowledge sharing in teams’’, Journal of European Industrial Training, Vol. 28 No. 1, pp. 93-102, available from Emerald Full Text (accessed 5 February 2007). Martinez, A. (2006), ‘‘Knowledge citizens: a competence profile’’, in Carrillo, F.J. (Ed.), Knowledge Cities. Approaches, Experiences and Perspectives, Butterworth-Heinemann (Elsevier), Burlington, MA. Maznevski, M.L. and Chudoba, K.M. (2000), ‘‘Bridging space over time: global virtual team dynamics and effectiveness’’, Organization Science, Vol. 11, pp. 473-92. Pauleen, D., Corbitt, B. and Yoong, P. (2005), ‘‘Discovering and articulating what is not yet known: using action learning and grounded theory as a knowledge management strategy’’, paper presented at the Knowledge Management in Asia Pacific 2005 Conference (KMAP 2005), Victoria University of Wellington, New Zealand, available at: http://kmap2005.vuw.ac.nz/papers/Discovering%20and%20articulating %20what%20is%20not%20yet%20known.pdf

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Sarker, S., Lau, F. and Sahay, S. (2001), ‘‘Using an adapted grounded theory approach for inductive theory building about virtual team development’’, The Data Base for Advances in Information Systems, Vol. 32 No. 1, p. 38, available at: http://heim.ifi.uio.no/,sundeeps/publications/GTVT.pdf Siemens, G. (2006), ‘‘Learning and knowledge at the workplace’’, ePresentation for the Online Educa Berlin 2006 Conference, September, available at: www.onlineeduca2006.org (accessed 28 September 2006). Sloman, M. (2001), The e-Learning Revolution, Chartered Institute of Personnel and Development (CIPD), London. Stahl, G. (1999), ‘‘A model of collaborative knowledge-building’’, paper presented at CSCL ’99 workshop on KBEs and the ICLS, Institute of Cognitive Science. University of Colorado. Trauth, E.M. and Jessup, L.M. (2000), ‘‘Understanding computer-mediated discussions: positivist and interpretative analysis of group support system use’’, MIS Quarterly, Vol. 24 No. 1, pp. 43-79. Tuomi, I. (2004), ‘‘Future challenges of the European knowledge society’’, discussion paper presented at Institute for Prospective Technological Studies, IPTS, 11 August 2004, available at: www. meaningprocessing.com/personalPages/tuomi/articles/TheFutureOfTheEuropeanKnowledgeSociety. pdf Yoong, P. and Pauleen, D. (2004), ‘‘Generating and analysing data for research on emerging technologies: a grounded action learning approach’’, Information Research Journal, Vol. 9 No. 4, available at: http://informationr.net/ir/9-4/paper195.html

Further reading Glaser, B.G. and Strauss, A. (1967), The Discovery of Grounded Theory: Strategies for Qualitative Research, Aldine Publishing, Chicago, IL. Saka, A. (2003), ‘‘Internal change agents’ view of the management of change problem’’, Journal of Organisational Change Management, Vol. 16 No. 5, pp. 480-96. Tuomi, I. (1999), ‘‘Learning and knowing in organisations’’, lectio precursora for dissertation presented as ‘‘Corporate knowledge: theory and practice of intelligent organizations’’, 1999 at Centre for Activity Theory and Developmental Work Research, Helsinki University, Helsinki. Tuomi, I. (2002), ‘‘The future of knowledge management’’, Lifelong Learning in Europe (LLinE), Vol. VII No. 2, pp. 69-79, available at: www.meaningprocessing.com/personalPages/tuomi/articles/ FutureOfKnowledgeManagement.pdf

About the author Blanca C. Garcia is a PhD candidate at the University of Manchester’s School of Environment and Development, Institute for Development Policy and Management (IDPM), UK. She recently completed a multidisciplinary research enquiry about the converging points between development, learning and skill development strategies in the context of institutional knowledge-based initiatives using information technologies. She has recently contributed a case study chapter to Knowledge Cities (Elsevier, 2006). Blanca C. Garcia can be contacted at: [email protected]

To purchase reprints of this article please e-mail: [email protected] Or visit our web site for further details: www.emeraldinsight.com/reprints

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Knowledge effectiveness, social context and innovation Dimitris Brachos, Konstantinos Kostopoulos, Klas Eric Soderquist and Gregory Prastacos

Abstract Purpose – The purpose of this paper is to conduct an investigation into knowledge-sharing mechanisms by empirically testing the role that context plays in the transfer of actionable knowledge, and, in turn, for innovation.

Dimitris Brachos and Konstantinos Kostopoulos, Management Science Laboratory, Athens University of Economics and Business, Greece. Klas Eric Soderquist, Assistant Professor of Innovation and Knowledge Management in Athens University of Economics and Business, Greece. Gregory Prastacos, Professor of Management Science in Athens University of Economics and Business and Director of the Management Science Laboratory, Greece. An earlier version of parts of this paper was presented at the 2006 Annual Academy of Management Conference, 11-16 August 2006, Atlanta, Georgia, USA. This Research is funded by the Greek General Secretarial for Research and Technology, Ministry of Development, by the European Social Fund and by the Commercial Bank of Greece, a member of the Cre´dit Agricole Group.

DOI 10.1108/13673270710819780

Design/methodology/approach – A multiple-respondents survey was performed in 72 business units of companies belonging to the ICT, pharmaceutical and food industries in Greece. In total, 295 useful questionnaires were collected using a multiple respondent strategy. All constructs were measured with multi-item scales and validated using exploratory factor analyses. A total of seven hypotheses were generated following a literature review on the key determinants of context for effective knowledge sharing. The hypotheses were tested using ordinary least squares regression. Findings – The research shows that when units pursue knowledge transfer between their different actors, contextual factors such as trust, motivation to transfer knowledge, management support and learning orientation are crucial for fostering knowledge transfer and innovation. This contribution is important since the need for developing an organizational context where knowledge transfer and innovation flourish is constantly put forth in the business press, while the empirical and research based evidence for its importance has been scarce. Research limitations/implications – There is a research need in knowledge sharing theory to define and identify an integrated model concerning the contextual factors that enable the knowledge sharing process. Having established a firm relationship between organizational context and innovation, the research also sets a foundation for further exploring the organization-environment link in terms of leveraging organizational knowledge dynamics. Originality/value – The research is a first attempt to show that the construct ‘‘perceived usefulness of knowledge’’ is a critical proxy of knowledge transfer effectiveness, as well as to find support for its positive relation to innovation. Keywords Knowledge transfer, Knowledge management, Organizational culture, Innovation, Greece Paper type Research paper

Introduction A primary aim of knowledge management and knowledge-based social development is to enable and encourage knowledge transfer among and between organizational entities such as individuals, communities and units (Newell et al., 2002). Building on earlier ground-breaking work on knowledge transfer and sharing (Kogut and Zander, 1995; Szulanski, 1996), Argote and Ingram (2000, p. 151) argue that ‘‘the creation and transfer of knowledge in organizations provide a basis for competitive advantage in firms’’. In a wider social perspective, this knowledge-driven competitiveness is crucial for ensuring sustained performance and growth in regions and industries alike (e.g. Feldman and Martin, 2005). So far, the majority of empirical research has been concentrated on the types of knowledge that enable or hinder knowledge transfer (Szulanski, 1996; Argote and Ingram, 2000; Reagans and McEvily, 2003; Haas and Hansen, 2005), on the kind of organizational components that support knowledge sharing – such as dyads (Szulanski, 1996; Levin and Cross, 2004), ego-networks and inter-unit relationships (Hansen, 1999; Dyer and Nobeoka, 2000; Tsai,

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2001; Hansen et al., 2005) and knowledge based value systems (Carrillo, 1997) – as well as on the factors determining knowledge inflows and outflows in multi national corporations (MNCs) and strategic business units (SBUs) (Gupta and Govindarajan, 2000). The context where knowledge transfer takes places is an important factor that needs further empirical development, as to what exactly is meant by context and what variables can be conceived as proxies for context when it comes to knowledge sharing. Actually, contextual parameters are important both at the organizational level, which is the focus of this paper, and at the level of the wider social context where organizations operate. In addition, few researchers have attempted to analyze, in depth, knowledge transfer effectiveness (Reagans and McEvily, 2003), that is, the extent to which knowledge transfer actually leads to positive innovation outcomes and other performance effects (Tsai, 2001; Smith et al., 2005). Building on the knowledge transfer, organizational context and new product innovation literature, the authors position the study in business units (marketing divisions), use the term perceived usefulness of knowledge to operationalize knowledge transfer effectiveness, and argue that an organizational context characterized by a combination of trust, motivation, learning orientation, social interaction, and top management support facilitates knowledge usefulness within business units. Further, the authors conceptualize that knowledge usefulness mediates the relationship between these contextual factors and product innovation. The conceptual framework is depicted in Figure 1. To test this model, 295 questionnaires were used and 72 marketing directors were interviewed from 65 medium- to large-sized multinational enterprises located in Greece. Multiple regression analyses were performed. The remaining of this paper is organized as follows: First, the knowledge transfer and related innovation literature is reviewed and the research hypotheses are formulated. Second, the methodology with variables, measures and validation procedures is presented. In section three the results are presented, and last implications, limitations and proposals for future research directions are discussed.

Theory development and hypotheses Making knowledge available is not equal to knowledge transfer. Knowledge also needs to be used by the receiving part. Knowledge transfer actually occurs when received knowledge is used by recipients and this use results in changing their behavior; in other words when experience of one individual or unit influences another unit through changes in behavior (Nelson and Winter, 1982; Argote and Ingram, 2000). Von Krogh (2003, p. 374) adds further precision to the knowledge transfer/sharing processes, arguing that tacit knowledge sharing is a ‘‘sequenced collective action and change. involving alteration and transformation in cognition and action both of the sender and the receiver, whereas Argote and Ingram (2000) point out that knowledge transfer can be measured through changes in knowledge or changes in performance. This specification of ‘‘true’’ knowledge transfer presents strong similarities to learning theory where learning at the individual level occurs when an individual, as a result of learning, modifies his or her mental models – which are representations of an individual’s explicit and implicit understandings of the world (Senge, 1990). The learning literature supports the view Figure 1 Knowledge sharing effectiveness and organizational performance

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that organizations convert their past experience into promises for future action (Hargadon and Fanelli, 2002). By following such a rationale, the authors adopt the view that knowledge transfer can be seen as a building block of organizational learning (Argote, 1999), and, consequently, knowledge is effectively transferred among actors when it is perceived as useful by those actors. The notion of perceived knowledge usefulness as a proxy of knowledge transfer effectiveness is not new in knowledge theory. Menon and Varadarajan (1992), for instance, define usefulness as a judgment made about knowledge from a particular source in a particular context. More recently, Levin and Cross (2004) develop the construct receipt of useful knowledge as an outcome variable to denote the concept of effective knowledge transfer. Building on Hansen (1999), Hansen and Haas (2001) and Szulanski (1996) they combine eight items to formulate this construct, indicating the extent to which received knowledge hindered or promoted different aspects of project and business unit outcomes. Four items related to project efficiency in terms of budget and time, and four items related to business unit effectiveness – in terms of value, performance and quality – were measured in these studies. To sum up, perceived usefulness of knowledge is dependent on the extent to which the concerned actors perceive knowledge as: B

Meaningful – knowledge should make sense to the users.

B

Accurate – knowledge should be related to the tasks and problems facing the users and to the processes and routines through which work gets done.

B

Valid – knowledge should be action-oriented and proven applicable.

B

Innovative – the use of knowledge should lead to something new (i.e. ideas, products, deeper knowledge, etc).

Based on the above, the authors suggest that perceived usefulness of knowledge, which prompts organizational actions, changes in behavior, and innovation outcomes, is an adequate proxy of knowledge transfer effectiveness. Following Levin and Cross (2004), the authors define and measure a unit’s perceived usefulness of knowledge as the extent to which the knowledge which is shared, is perceived as meaningful, relevant, action-oriented, and innovative. Having analyzed and specified the notion of knowledge transfer, the particular context where knowledge transfer actually occurs and in which knowledge is manifested as useful needs to be examined. The knowledge transfer literature suggests that trust (Levin and Cross, 2004), motivation (Osterloh and Frey, 2000), learning orientation (Baker and Sinkula, 1999), social interaction (Hansen, 1999) and management support (Vera and Crossan, 2004) are cornerstones of an organizational context that enables effective knowledge sharing (Gibson and Birkinshaw, 2004). This context, which essentially is built up from variables of social inter-personal nature, will affect the level of perceived usefulness of knowledge, which, in turn, will affect new product and service introduction impacting also the wider social context where the organization is located. Organizational context, knowledge transfer effectiveness, and performance Davenport and Prusak (1998) argue that when knowledge transfer is the objective, the method must always suit the organizational culture and social processes, while De Long and Fahey (2000) advance that different contextual dimensions shape the individuals’ mindsets, behavior and their corresponding relationships. Therefore, the organizational context determines the way that knowledge is created, legitimated and diffused throughout the organization. The authors position the research recognizing that the notions of organizational context, culture and social climate represent overlapping perspectives on the same phenomenon (Ashkanasy et al., 2000; Smith et al., 2005). The factors that have been identified as influencing and characterizing the context for knowledge transfer include social interaction (Hansen, 1999; 2002; Reagans and McEvily, 2003), trust (De Long and Fahey, 2000; Argote et al., 2003; Becerra and Gupta, 2003),

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‘‘ Making knowledge available is not equal to knowledge transfer. ’’

management support (Vera and Crossan, 2004), motivation (Gupta and Govindarajan, 1986; 2000; Osterloh and Frey, 2000; Argote et al., 2003) and learning orientation (Tsai and Ghoshal, 1998; Baker and Sinkula, 1999, Crossan et al., 1999). A key enabler for knowledge transfer is social interaction among organizational members (e.g. participants in problem-solving teams) who rely on knowledge transfer for supporting innovation and for driving performance (Ghoshal et al., 1994; Tsai, 2001; Reagans and McEvily, 2003). Hansen (1999, p. 83) defines such relations as ‘‘regularly occurring contacts between groups of people’’. Social interaction strengthens inter and intra-organizational relationships by integrating actors’ activities in knowledge sharing processes and routines. Key determinants of effective social interaction are closeness and communication frequency (Ghosal et al., 1994; Tsai and Ghoshal, 1998; Tsai, 2001; Becerra and Gupta, 2003). Social-related activities play an important role in the creation, development and cultivation of a space where knowledge sharing takes place. Hansen (1999), in his study of 120 new-product development projects undertaken by 41 divisions within a large multinational firm, shows that weak ties (i.e. distant and infrequent relationships) among business units help project teams search for simple and useful codified knowledge in other business units, whereas, in contrast, strong ties promote complex knowledge transfer. Additionally, Tsai and Ghoshal (1998) emphasize the important role of social ties as channels of knowledge sharing and resource flows, which influence positively the creation and diffusion of innovations. Thus, social interaction among individuals in organizational settings could improve productivity (Reagans and Zuckerman, 2001), increase performance (Tsai, 2001), foster innovation (Tsai, 2001), and stimulate knowledge transfer (Reagans and McEvily, 2003). Taking the above into consideration, the following hypothesis related to social interaction was formulated: H1.

Social interaction, as measured by closeness and communication frequency, will have a positive impact on a business unit’s level of perceived knowledge usefulness.

Although trust has been consistently theorized as an important aspect of organizational context, its role in relation to knowledge transfer is rather ambiguous and underexplored. Some studies, for example, argue that high levels of trust may inhibit monitoring and thereby minimize collective action (Webb, 1996) whereas others argue that trust among participants facilitates knowledge transfer (Argote et al., 2003) and emphasize the mediating role of trust in perceived usefulness of knowledge (Levin and Cross, 2004). Harris et al. (1999) delineate that developing relationships built upon trust is a vital aspect of knowledge transfer effectiveness, although they recognize the difficulty of creating and maintaining high levels of trust with associated implications for management. Thus, even though strong evidence have been found for the supporting role of trust in effective knowledge transfer, the concept still necessitates further specification especially when integrated in a broader explanatory research model. Giddens (1990, p. 34) identifies trust as being a property of both individuals and social contexts. Effective knowledge transfer is characterized by a simultaneous high level of mutual trust and trustworthiness among individuals in all processes and activities (Tsai and Ghoshal, 1998; Von Krogh et al., 2000; Newell et al., 2002). The literature on trust comprises

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strong evidence that trustful relationships are a key prerequisite for knowledge transfer within and among business units (Dirks and Ferrin, 2001; Levin and Cross, 2004). Taking the above into consideration, the following hypothesis related to trust was formulated: H2.

Trust will have a positive impact on a business unit’s level of perceived knowledge usefulness.

Motivation to transfer knowledge constitutes another key determinant for knowledge transfer effectiveness. The motivation to learn is a powerful force driving participation in organizational contexts (Argote et al., 2003). Motivated organizational members can deal easier and more effectively with ill-structured situations and transfer knowledge faster. Osterloh and Frey (2000) distinguish two forms of motivation: extrinsic motivation (pay, incentives, awards and recognition) and intrinsic motivation (work-related factors and work environment), which can motivate participants to share their knowledge. Extrinsic rewards are those that are provided to participants by someone else, while intrinsic rewards are those that individuals generate themselves as a result of accomplishing a task. Intrinsic motivation refers to an undertaken activity for one’s need satisfaction. The ideal incentive system is in the work content itself, which needs to be acceptable, satisfactory and fulfilling for employees (Osterloh and Frey, 2000; Ferrin and Dirks, 2003). Extrinsic motivation contributes to knowledge transfer, maneuvering actors to exploit existing knowledge and explore new one. The behavioral theory of the firm emphasizes intrinsic motivation in the form of identification with organizational strategy and shared purposes. Intrinsic motivation is needed for tasks that require creativity in their execution, and triggers the transfer of knowledge under conditions where extrinsic motivation fails (Osterloh and Frey, 2000). Thus, members of a unit are more likely to transfer knowledge if they are rewarded for utilizing internal knowledge (Argote et al., 2003; Menon and Pfeffer, 2003). Taking the above into consideration, the following hypothesis related to motivation was formulated: H3.

Motivation will have a positive impact on a business unit’s level of perceived knowledge usefulness.

Learning orientation is an organizational characteristic, which affects a firm’s propensity to use, create and share all kinds of knowledge (Baker and Sinkula, 1999). Organization-level learning represents the translation of shared understandings and collective action into new products, procedures, systems, and strategies (Crossan et al., 1999). Organizational context influences knowledge transfer and learning through commitment to learning, open mindedness, and shared vision that collectively make up the learning orientation construct (Vera and Crossan, 2004; Baker and Sinkula, 1999). Firms that are committed to learning, recognize the need to understand the cause and effect of their actions, which, in turn, is necessary for firms to regularly detect and correct errors in their theories in use (Crossan et al., 1999). The learning orientation comprises a set of knowledge questioning values through which organizations proactively question long-held routines, taken-for-granted assumptions and beliefs, resulting in processes of unlearning. Hence, unlearning is at the heart of organization change and, in turn, open mindedness is an organization value that is necessary for unlearning efforts to take place (Baker and Sinkula, 1999). The trading of know-how requires the existence of shared codes and vision within firms (Dyer and Nobeoka, 2000; Tsai and Ghoshal, 1998). Thus, a learning orientation in the business unit prevents participants from hiding and not transferring valuable knowledge and, in parallel, protects from undesired situations (Tsai and Ghosal, 1998). The authors view a learning orientation as a bonding mechanism that helps different parts of a business unit to integrate or to combine knowledge. Taking the above into consideration, the following hypothesis related to learning orientation was formulated:

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H4.

Learning orientation, namely commitment to learning, open-mindedness and shared vision, will have a positive impact on a business unit’s level of perceived knowledge usefulness.

Management literature has emphasized the importance of top management style in implementing and supporting an environment that fosters effective knowledge sharing and innovation within business units (Van de Ven, 1986; Pan and Scarbrough, 1998; Vera and Crossan, 2004). Top management involvement in knowledge sharing is fundamental, since managers need to emphasize the importance of knowledge sharing by frequently urging employees to share their knowledge with their colleagues and by developing, supporting and sustaining the required organizational context. Strategic leadership theorists (e.g. Hambrick and Mason, 1984) stipulate that decision making at the top management level is critical to organization outcomes; ‘‘ultimately, it accounts for what happens to organizations and business units’’ (Hambrick, 1989, p. 5). In addition, strategic leadership is a key driving force for organizational learning (Vera and Crossan, 2004) and for knowledge management (Nonaka et al., 2000). Nonaka et al. (2000) asserts that leaders promote and develop knowledge sharing, create and energize ‘‘ba’’ – the space in which knowledge is created – and trigger knowledge creation and use. The way in which knowledge management practices are designed and implemented is a reflection of corporate and business unit culture, which in turn, is a reflection of the leadership (Pan and Scarbrough, 1998; Figallo and Rhine, 2002). Taking the above into consideration, the following hypothesis related to management support was formulated: H5.

Management support will impact on a business unit’s level of perceived knowledge usefulness.

The introduction of new products and services is an important precursor of organization performance (Damanpour, 1991) and new value creation (Tsai and Ghoshal, 1998). The rate of new product introduction can mirror a firm’s capacity of managing, sharing, creating and combining new and existing knowledge (Smith et al., 2005). The innovation literature explains the processes through which firms create differentiated added value through novelty in products, services and procedures. Innovation can be defined as the generation and development of new products, services or processes (Damanpour, 1991), as ‘‘the creation and exploitation of new ideas’’ (Kanter, 1988, p. 170), or as ‘‘the development and implementation of new ideas (Van de Ven, 1986, p. 590). From an innovation perspective, knowledge provides firms with the raw material for innovation, and knowledge sharing enables a potential of combining shared, but previously disparate ideas, insights and information conductive to the creation of new products, services, and processes (Cohen and Levinthal, 1990; Kogut and Zander, 1992). The knowledge transfer theory is concerned with analyzing, predicting and prescribing the ability and means of an organizational entity to effectively transfer knowledge across its constituting members. Business units need to provide paths and flows where knowledge is deliberately distributed. Moreover, they need to make full use of their knowledge (Levin and Cross, 2004) so as to support innovative activities (Tsai, 2001).

‘‘ The learning organization comprises a set of knowledge questioning values through which organizations proactively question long-held routines, taken-for-granted assumptions and beliefs, resulting in processes of unlearning. ’’

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Taking the above into consideration, the following hypothesis related to new product and services introduction was formulated: H6.

The level of perceived knowledge usefulness of a business unit is associated with the number of new products and services it introduces.

Overall, the authors have argued that a context characterized by a combination of trust, motivation, learning orientation, social interaction, and top management support fosters the perceived usefulness of knowledge within business units and that perceived usefulness of knowledge will, in turn, positively affect the level of new products and services introduction as well as the creation of wealth from a wider social perspective. Accordingly, the authors expect perceived usefulness of knowledge to be an important prerequisite to the innovation process. Taking this into consideration, the following hypothesis was formulated: H7.

The level of perceived knowledge usefulness of a business unit mediates the relationship between the business unit’s context and number of new products and services.

Method The majority of past studies on knowledge sharing and its consequences has either adopted a case study method or has relied on a single informant to answer questions on behalf of an entire organization. Both these approaches have certain limitations. In this paper, the authors use multiple respondents’ methodology to evaluate business units on context, perceived usefulness of knowledge, and innovation output. They then aggregate the multiple responses to create unit – level measures. This was done in 72 marketing divisions in business units of 65 Greek Firms, each of which had distinct context and market orientation. Procedures and sample Data were collected in two ways, through: 1. two detailed questionnaires, one distributed to the senior management of each marketing division and the other to selected knowledge workers; and 2. a structured interview with the marketing director or senior deputy of each unit was conducted to obtain a more complete picture of the organizational context variables. The authors contacted all 194 medium to large enterprises, which employed more than 100 people, from the Greek ICT, pharmaceutical and food industries. These firms constitute the research population. Of the 194 firms contacted, 112 firms agreed to participate in the study (representing a 57.7 percent participation rate). In this paper, preliminary findings of 72 marketing divisions (business units) from 65 of those firms are presented. The total number of survey respondents was 312 including senior, middle and line management. Because of missing data on some measures, 295 questionnaires were used for analyses. In order to mitigate the problem of common method variance or same– source bias (Podsakoff and Organ, 1986), different levels of respondents for the independent variables and the dependent variables were used (Gibson and Birkinshaw, 2004). That is, for the independent variables (i.e. social interaction, trust, motivation, learning orientation, and management support) responses only from those who identified themselves as line management and middle management were aggregated. By contrast, for the dependent variables (i.e. knowledge sharing effectiveness and business unit performance) the authors aggregated only those respondents who identified themselves as senior management. Driven from multilevel theory (Klein and Koslowski, 2000), it is critical to aggregate variables to statistically demonstrate within-unit agreement and between-units differences. Several analyses to ensure this were conducted. First, the ‘‘interrater agreement score’’ (rwg(j)) (James et al., 1993) was calculated for each variable. This measure ranges from 0 (‘‘no agreement’’) to 1 (‘‘total agreement’’). Glick (1985) suggested 0.60 as the cutoff for acceptable interrater agreement values. Mean (median) interrater agreement was above

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0.70 for all variables. The intraclass correlation coefficients – ICC(1) and ICC(2) – were also calculated, using one-way analysis of variance (ANOVA) on the individual level data. Indication of convergence within units is an ICC(1) greater than zero and that F was significant (Kenny and La Voie, 1985). In all cases ICC(1) was greater than zero and F was significant. The ICC(2) values, namely the indication of the reliability of the unit mean were, also, strong and above 0.65 (described below). Measures All constructs were measured with multi-item scales. Scores on these measures were mean-computed across items. Survey items from published scales were used when possible, while in some cases, original items to capture Greek firms peculiarities were developed. These scales were validated with an expert panel of academics and senior managers and a pretest on a sample of ten business units was conducted as well. Subsequently, exploratory factor analyses with principle component method was employed to further validate measures (described below). Social interaction. The authors measured social interaction, in terms of closeness and communication frequency, with six items in a seven-point Likert scale. The first item – closeness of the working relationship – was adapted from Hansen (1999). Respondents, in the first item were asked to assess their closeness (1 ¼ ‘‘very distant’’ to 7 ¼ ‘‘very close’’) within their division. Items of communication frequency were adapted by Gupta and Govindarajan (2000), Hansen (1999), Becerra and Gupta(2003). Respondents were asked to assess their communication frequency (1 ¼ ‘‘once every three months’’ to 7 ¼ ‘‘once a day’’) within their division. All items loaded on a single factor having eigenvalue of 2.56 and accounting for 42.8 percent of the variance. Internal reliability was (a ¼ 0:72) and supported aggregation (ICCð1Þ ¼ 0:21, ICCð2Þ ¼ 0:65). Trust. From the many different existing scales of trust-based concepts, the authors adapted four items from Levin and Cross (2004). Two dimensions of trust were measured (benevolence and competence trust). Respondents were asked to assess their perceived trustworthiness (1 ¼ ‘‘strongly disagree’’ to 7 ¼ ‘‘strongly agree’’) within their division. All items loaded on a single factor having eigenvalue of 2.76 and accounting for 69.1 percent of the variance. Internal reliability was high (a ¼ 0:84) and supported aggregation (ICCð1Þ ¼ 0:57, ICCð2Þ ¼ 0:84). Motivation. Motivation for knowledge transfer was measured with five items of which two were adapted from Bock et al. (2005). The remaining three were developed by the authors[1]. Respondents were asked to assess their agreement (1 ¼ ‘‘strongly disagree’’ to 7 ¼ ‘‘strongly agree’’) concerning their motivation to transfer knowledge within their unit. Items were emphasizing intrinsic motivation, without, however, overlooking extrinsic motivation. All items loaded on a single factor having eigenvalue of 2.81 and accounting for 65.2 percent of the variance. Internal reliability was high (a ¼ 0:83) and supported aggregation (ICCð1Þ ¼ 0:39, ICCð2Þ ¼ 0:76). Learning orientation. The authors measured learning orientation with items based on Baker and Sinkula (1999). Ten items were used for the three dimensions of learning orientation – commitment to learning, open-mindedness, shared vision. Ten further items were aggregated to generate the learning orientation variable. Following Baker and Sinkula (1999), high correlations among the three dimensions suggest that they can be included in a

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common construct. Internal reliability was high (a ¼ 0:92) and supported aggregation (ICCð1Þ ¼ 0:51, ICCð2Þ ¼ 0:91). Management support. The authors measured management support with five items adapted by Vera and Crossan (2004). Respondents were asked to assess their agreement (1 ¼ ‘‘strongly disagree’’ to 7 ¼ ‘‘strongly agree’’) concerning the extent to which leadership facilitates knowledge transfer within their division. All items loaded on a single factor having eigenvalue of 3.5 and accounting for 71.5 percent of the variance. Internal reliability was high (a ¼ 0:89) and supported aggregation (ICCð1Þ ¼ 0:62, ICCð2Þ ¼ 0:89). Perceived usefulness of knowledge. The authors combined six items, from Levin and Cross (2004), Hansen (1999), Szulanski (1996) to create the scale for perceived usefulness of knowledge. Respondents were asked to evaluate (1 ¼ ‘‘strongly disagree’’ to 7 ¼ ‘‘strongly agree’’) the extent to which knowledge transfer within the business unit was useful for business unit’s operation. Principle component analysis demonstrated that all items loaded on a single factor having eigenvalue of 2.59 and accounting for 64.9 percent of the variance. Factor loadings were above 0.7. Internal reliability was high (a ¼ 0:81) and supported aggregation at the unit – level of analysis (ICCð1Þ ¼ 0:45, ICCð2Þ ¼ 0:77). New product and services. This was measured as the number of new products that the marketing division had introduced during the last year (Smith et al., 2005). This measure was significantly correlated with the number of unit personnel (r ¼ 0:50, p , 0:01). Control variables. Business unit size, market share, market growth and competition intensity were used as control variables. Size was measured using the natural logarithmic transformation of a unit’s number of full-time employees. Each of the rest variables were adopted and measured with one item in a seven-point Likert scale.

Results Means, standard deviation and correlations among the variables are reported in Table I. The hypotheses were tested using ordinary least squares (OLS) regression. Table II reports the results of regression analyses, where perceived usefulness of knowledge and new products and services are the corresponding dependent variables. Four models, illustrated in Table II, were produced. Model 1 presents the relationship between the dependent (new products and services) and the mediator (perceived usefulness of knowledge). Model 2 tests the effect of the independent variables (business unit context characteristics) to the mediator (perceived usefulness of knowledge). Model 3 relates the independent variables (business unit context characteristics) to the dependent variable (new products and services) and in Model 4 the effect of independent variables and the mediator to the independent variable is tested. Regarding the impact of business unit context to perceived usefulness of knowledge, (Model 2; H1-H5), social interaction was unrelated to perceived usefulness of knowledge, while trust has positive and significant influence to perceived usefulness of knowledge Table I Descriptive statistics and correlationsa Variableb 1. Trust 2. Motivation 3. Shared vision 4. Open-mindedness 5. Commitment to learning 6. Management support 7. Social interaction 8. Perceived usefulness of knowledge 9. New products and services a

Mean

s.d.

1

2

3

4

5

6

7

8

5.87 5.35 5.81 5.64 5.63 5.54 6.06 6.14 3.61

0.79 0.97 1.18 0.95 0.98 0.86 0.75 0.65 3.97

0.45** 0.74 0.72** 0.62** 0.63** 0.50** 0.45** 0.03*

0.52** 0.33** 0.62** 0.49** 0.29** 0.51** 0.01*

0.62** 0.69** 0.55** 0.53** 0.42** 0.06

0.59** 0.60** 0.40** 0.30** 0.08

0.57** 0.38** 0.56** 0.02

0.40** 0.18 0.07

0.22* 0.07

20.05

b

Notes: n ¼ 72 (business units); learning orientation includes shared vision, open-mindedness and commitment to learning; *p , 0.05; **p , 0.01

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Table II Results of regression analysisa Model 1: dependent variable, new products and services b t

Variables No. of employees Competition Market growth Market share Trust Motivation Management support Social interaction Learning orientation Perceived usefulness of knowledge R2 Adjusted R2 F

0.40 0.14 0.01 0.06

20.11 0.33 0.28 6.525***

2.48* 3.15* 0.50 2.63*

Model 2: dependent variable, perceived usefulness of knowledge b t

Model 3: dependent variable, new products and services b t

Model 4: dependent variable, new products and services b t

0.51 0.12 0.02 20.03 0.31 0.22 20.33 20.02 0.26

0.43 0.14 0.02 0.05 0.05 20.09 0.02 0.02 20.01

0.50 0.16 0.03 0.04 0.09 20.05 20.03 0.02 0.04 20.15 0.38 0.29 3.697**

1.70** 1.47 0.43 20.70 2.32* 2.60* 23.40*** 20.23 2.06*

22.02* 0.48 0.40 6.320***

0.33 0.23 3.425**

2.48* 3.01** 0.80 1.81b 0.60 21.81b 0.32 0.44 20.02

2.93** 3.43** 0.94 1.67b 1.19 21.11 20.53 0.39 0.51 22.10*

Notes: an ¼ 72 business units; bp , 0.10; *p , 0.05; **p , 0.01; ***p , 0.001

(b ¼ 0:31, p , 0:05), thus supporting H2. Motivation was also found positively related to perceived usefulness of knowledge (b ¼ 0:22, p , 0:05), supporting H3 and learning orientation – namely shared vision, open-mindedness, commitment to learning – was marginally positively to perceived usefulness of knowledge (b ¼ 0:26, p , 0:05), hence confirming H4. Management support has strong and significant relation with perceived usefulness of knowledge (b ¼ 20:33, p , 0:001), thus providing support for H5. Consistent with H6, a unit’s level of perceived usefulness of knowledge was significantly associated to its number of new products and services (b ¼ 20:11, p , 0:05). In addition, unit size (b ¼ 0:50, p , 0:01), competition intensity (b ¼ 0:16, p , 0:01), and market share (b ¼ 0:04, p , 0:10) were directly related to innovation as expected, whereas market growth was unrelated. It was also expected that perceived usefulness of knowledge would mediate the relationships between the independent variables (trust, motivation, management support, social interaction and learning orientation) and the number of new products and services. Following Baron and Kenny (1986) the mediation analysis includes three steps. The first step is to ensure and examine the existence of a relationship between independent variables (here trust, motivation, management support, social interaction and learning orientation) and the mediator (here perceived usefulness of knowledge). As shown in model 2 (see Table II), with the exception of social interaction, all of the variables were significantly related with the mediator. The second step is to analyze whether a significant relationship between the independent variables and the dependent variable (here new products and services) exists. In model 3 (Table II) this is found for the management support variable. As a final third step, the previously significant relationships between dependent variable (here new products and services) and independent variables (here management support) from model 4 were no longer significant when a business unit’s level perceived usefulness of knowledge was entered in the equation.

Discussion This study is a first attempt to show that the construct ‘‘perceived usefulness of knowledge’’ is a critical proxy of knowledge transfer effectiveness, as well as to find support for its positive relationship with innovation. The research attempted to answer two basic questions: first, how do factors of a business unit context affect the level of perceived usefulness of knowledge; and second, how does the unit’s level of perceived knowledge usefulness influence innovation-related outputs?

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The research shows that when units pursue knowledge transfer between their different actors, contextual factors such as trust, motivation to transfer knowledge, management support and learning orientation are crucial for fostering knowledge transfer and innovation. This contribution is important since the need for developing an organizational context where knowledge transfer and innovation flourish is constantly put forth in the business press, while the empirical and research based evidence for its importance has been scarce. The analysis further reveals that perceived usefulness of knowledge leads to innovation, measured by new product introduction. In turn, the authors showed that perceived usefulness of knowledge fully mediates the relationship between management support and the number of new products and services, which is a contribution to innovation theory and its relation to knowledge. These results can also have a wider implication at the spatial level. Over the last three years, the Attica region in Greece has scored very high in terms of innovation in the IT services sector (European Commission, 2006), one of the sectors analyzed in this research. It is clear that the emergence of such a knowledge intensive industry in a country that traditionally has been characterized as an innovation follower depends on the extent to which individual organizations can leverage knowledge dynamics. This knowledge exploitation must be rooted in the deeper social processes with the organization. Having established a firm relationship between organizational context and innovation, this research sets a foundation for further exploring the organization-environment link in terms of leveraging organizational knowledge dynamics to create and maintain regional competitiveness and knowledge clusters. The study has limitations that should be acknowledged. In the research it was assumed that knowledge transfer has occurred within business units if the unit’s outcomes are reported to have improved as a result of perceived usefulness of knowledge. Hence it is assumed beforehand that some process of knowledge transfer occurs within the organizational unit. Moreover, the study required respondents to report on their perceptions within business units. To overcome this problem and minimize perception bias, besides using a multiple-respondent research design, the authors prompted respondents to answer questions beginning with ‘‘to the best of your knowledge, regardless of whether or not you had a prior relationship with this person . . . ’’.

Note 1. The steps followed to develop these three items were: extensive literature review; in-depth interviews with both academics and business experts (face and content validity); pretest of the survey for clarity and appropriateness; and exploratory factor analysis.

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Hansen, M.T. (1999), ‘‘The search-transfer problem: the role of weak ties in sharing knowledge across organization subunits’’, Administrative Science Quarterly, Vol. 44, pp. 82-111. Hansen, M.T. (2002), ‘‘Knowledge networks: explaining effective knowledge sharing in multiunit companies’’, Organization Science, Vol. 13 No. 3, pp. 232-48. Hansen, M.T. and Haas, M. (2001), ‘‘Different knowledge, different benefits: toward a productivity perspective on knowledge sharing in organizations’’, presented at the Academy of Management Annual Meeting. Hansen, M.T., Mors, M.L. and Lovas, B. (2005), ‘‘Knowledge sharing in organizations: multiple networks, multiple phases’’, Academy of Management Journal, Vol. 48 No. 5, pp. 776-93. Hargadon, A. and Fanelli, A. (2002), ‘‘Action and possibility: reconciling dual perspectives of knowledge in organizations’’, Organization Science, Vol. 12 No. 3, pp. 290-302. Harris, L., Coles, A., Dickson, K. and Mcloughlin, I. (1999), ‘‘Building collaborative networks: new product development across organizational boundaries’’, in Jackson, P. (Ed.), Virtual Working: Social and Organizational Dynamics, Routledge, London. James, L.R., Demaree, R.G. and Wolf, G. (1993), ‘‘rwg: an assessment of within group inter-rater agreement’’, Journal of Applied Psychology, Vol. 78, pp. 306-39. Kanter, R.M. (1988), ‘‘When a thousand flowers bloom: structural, collective, and social conditions form innovation in organizations’’, in Staw, B.M. and Cummings, L.L. (Eds), Research in Organizational Behavior, Vol. 10, JAI Press, Greenwich, CT. Kenny, D.A. and La Voie, L. (1985), ‘‘Separating individual and group effects’’, Journal of Personality and Social Psychology, Vol. 48, pp. 339-48. Klein, K.J. and Kozlowski, S.W.J. (2000), Multilevel Theory: Research and Methods in Organizations, Jossey-Bass, San Fransisco, CA. Kogut, B. and Zander, U. (1992), ‘‘Knowledge of the firm, combinative capabilities, and the replication of technology’’, Organization Science, Vol. 3, pp. 383-97. Levin, D.Z. and Cross, R. (2004), ‘‘The strength of weak ties you can trust: the mediating role of trust in effective knowledge transfer’’, Management Science, Vol. 50 No. 11, pp. 1477-90. Menon, A. and Varadarajan, P.R. (1992), ‘‘A model of marketing knowledge use within firms’’, Journal of Marketing, Vol. 56, pp. 53-71. Menon, T. and Pfeffer, J. (2003), ‘‘Valuing internal versus external knowledge’’, Management Science, Vol. 49 No. 4, pp. 497-513. Nelson, R. and Winter, S. (1982), An Evolutionary Theory of Economic Change, The Belknap Press of Harvard University Press, Cambridge, MA. Newell, S., Robertshon, M., Scarborough, H. and Swan, J. (2002), Managing Knowledge Work, Palgrave, New York, NY. Nonaka, I., Toyama, R. and Konno, N. (2000), ‘‘SECI, Ba and leadership: a unified model of dynamic knowledge creation’’, Long Range Planning, Vol. 33, pp. 5-34. Osterloh, M. and Frey, B. (2000), ‘‘Motivation, knowledge transfer, and organizational forms’’, Organization Science, Vol. 11 No. 5, pp. 538-50. Pan, S. and Scarbrough, H. (1998), ‘‘A socio-technical view of knowledge-sharing at Buckman Laboratories’’, Journal of Knowledge Management, Vol. 2 No. 1, pp. 55-66. Podsakoff, P.M. and Organ, D.W. (1986), ‘‘Self reporting in organization research: problems and prospects’’, Journal of Management, Vol. 12 No. 4, pp. 531-44. Reagans, R. and McEvily, B. (2003), ‘‘Network structure and knowledge transfer: the effects of cohesion and range’’, Administrative Science Quarterly, Vol. 48, pp. 240-67. Reagans, R. and Zuckerman, E.W. (2001), ‘‘Networks, diversity, and productivity: the social capital of corporate R&D teams’’, Organization Science, Vol. 12 No. 4, pp. 502-17. Senge, P. (1990), The Fifth Discipline: The Art and Practice of the Learning Organization, Doubleday, New York, NY.

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Further reading Ingram, M. and Roberts, L. (2000), ‘‘Friendships among competitors in the Sydney hotel industry’’, American Journal of Sociology, Vol. 106 No. 2, pp. 387-423.

About the authors Dimitris Brachos is a research fellow at the Management Science Laboratory (MSL) in Athens University of Economics and Business (AUEB). He holds a PhD from Athens University of Economics and Business, Greece. His research concentrates on knowledge management, knowledge sharing and innovation. He is the corresponding author and can be contacted at: [email protected] (www.msl.aueb.gr) Konstantinos Kostopoulos is a research fellow at MSL, AUEB from where he also holds his PhD in Innovation Management. His research concentrates on innovation and learning, and knowledge management. Klas Eric So¨derquist is an Assistant Professor and head of the MSL’s Innovation and Knowledge Management Unit at (AUEB). He holds and MSc from the Royal Institute of Technology in Stockholm, Sweden and a DBA from Brunel Univeristy. He is also a Visiting Professor at the Grenoble Ecole de Management, France. His research concentrates on knowledge management, R&D and innovation management, and he has published in the Journal of Product Innovation Management, Long Range Planning, R&D Management and Omega, among others. Gregory Prastacos is a Professor and Director of the Management Science Laboratory at the Athens University of Economics and Business. He holds a PhD from Columbia University, USA. His research concentrates on management science, information technology, and their use for business transformation in the information society. He has published in Management Science, Operations Research, Long Range Planning, Journal of Knowledge Management, Journal of Innovation Management, among others.

To purchase reprints of this article please e-mail: [email protected] Or visit our web site for further details: www.emeraldinsight.com/reprints

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The social management of embodied knowledge in a knowledge community Ahmad Raza, A. Rashid Kausar and David Paul

Abstract Purpose – The purpose of this paper is to examine the patterns of social management of knowledge in a knowledge-community, reflecting on multiple social processes at work. Design/methodology/approach – This is a social epistemological critique of management of knowledge.

Ahmad Raza and A. Rashid Kausar are both based at the School of Business and Economics, University of Management and Technology, Pakistan. David Paul is Director, Centre for Professional Development, University of Macquarie, Australia.

Findings – First, knowledge communities are essentially multiple interactive social structures ranging from localization in space to emergent cross-boundary social spaces operating at micro, meso and macro-social levels. Second, patterns of knowledge management in different contexts such as organizations, groups, communities and virtual communities are predominantly social in nature and new knowledge emerges through social interactions. Originality/value – The paper underscores the significance of a social-epistemological view of knowledge communities and management of knowledge. Keywords Social processes, Cultural synergy, Social interaction, Knowledge management, Knowledge organizations Paper type Conceptual paper

The structure of knowledge community The twenty-first century marks the beginning of a new human consciousness. The technological-communication revolution has transformed the fundamental structures of societies, economies and governments. The boundaries of the ‘‘local’’ are merging into the ‘‘global’’ and vice versa (Fardon, 1995; Appadurai, 1995).The meanings of concepts such as ‘‘knowledge’’, ‘‘community’’ and ‘‘economy’’ are no more objectively valid across cultures. The internet and computers have caused cultural shifts in social cognition of humanity concerning these concepts (Jasanoff, 2004; Goldman, 1999, 2002). These emerging complexities of social phenomena are not explainable in terms of a single social cause. Mannheim (1952) has traced causes of cultural changes to shifts in weltanschauung brought by changes in our intellectual and technological apparatus. Wittgenstein (1985) investigated the complexity of ‘‘language-games’’ and its relationship with our perception of reality. He argued that meanings and interpretations of ‘‘concepts’’ vary across ‘‘forms’’ of social life. The outpouring of new ‘‘forms’’ of social communications (Hakken, 2003) has dissolved the Cartesian-Kantian epistemic synthesis of yesteryears, when epistemic context was considered to be universal. Several writers have tried to restore this universal epistemic quality to human inquiry but with very little success (McGinn, 1999; Azzouni, 2000; Gibson, 1988; Blackburn, 2001; Groff, 2004). On the contrary, current discourse in literature demonstrate an increasing critique of an indivuialistic,universalistic and objectivist descriptions of these concepts, by writers who contend that human thought and action is a socially constituted reality, hence it lacks universal epistemic context as well as relevance to diverse human cultures (Goldman, 1999, 2002; Carpendale and Ulrich, 2004; Kitchener, 2004; Nonaka et al., 2001; Desouza, 2002).

DOI 10.1108/13673270710819799

VOL. 11 NO. 5 2007, pp. 45-54, Q Emerald Group Publishing Limited, ISSN 1367-3270

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The ‘‘forces’’ of science and technology, particularly internet and computers (Zimmerman and Meyer, 2005; Stevenson, 2005; Brown, 2002; Fuller, 1991) have created new social context of communications, which shape contemporary social structure of both ‘‘knowledge’’ and ‘‘community’’. These concepts are being ‘‘reconfigured’’ due to intensive social interactions with new technologies of communications (Bull, 2000). Goldman (1999) and Fuller (1991) have provided a critical analysis on the role of communication technologies in the creation, dissemination and distribution of emergent forms of social spaces characterized by knowledge revolution, cyberspace, e-mail and World Wide Web. Goldman (1999) has asserted that, ‘‘social advance of knowledge hinges on communication’’. This social advance in communication practices have led to the emergence of new forms of ‘‘communitarian’’ social experiences termed as knowledge community. The knowledge community is thus an emergent form of multiple interactive social spaces of individuals formed by new communicative practices arising out of communication technologies characterized by social reciprocation of their ‘‘informational states’’ with each other in a dynamic ‘‘cyberspace’’ (Goldman, 1999; Fuller, 1991). These informational states can relate to ideas, values, products and stories. It appears that quintessence of social ontology of knowledge community revolves around the social communication networks of people. This process of social communication is multidimensional, cross-boundary, dynamic and self-organizing. Nonetheless, it is obvious that the emergent social structures of knowledge communities have become ‘‘de-territorialized’’ and are perpetually extended and created through information networks leading to new forms of cultural creation in a computer-mediated communicative social experience (Howell, 2002; Kempny, 2002; Amit, 2002). Those who participate and exist in a knowledge community negotiate part of their cultural identity, simultaneously transcending the boundaries of their limited social space-time and internalizing some part of the larger human identity. The quantum of information received and transmitted by the members of the knowledge community across social communicative networks determines prima facie social existence of knowledge community, its structure, economy and sustainability. The members of the knowledge-community exist as information beings creating new knowledge about a business enterprise, a product or a new research and thus forming a new social communicative space-time of collective existence. Kramer (1999) underscores the significance of this ‘‘collective‘‘ nature of knowledge communities and comments: ‘‘Knowledge communities can be conceptualized as groups or organizations whose primary purpose is the development and promulgation of collective knowledge. Knowledge communities are a prevalent and increasingly important form of contemporary organization. For example, all of the major social sciences are organized as knowledge communities consisting of numerous researchers whose common goal is the advancement of knowledge within their discipline. At a micro level, organizations within an industry, or even small groups within a single organization, often find it useful to participate in strategic collaborations or ‘learning alliances’ in order to mutually benefit from their unique knowledge and distinctive competencies.’’ Kramer further articulates that knowledge communities are characteristically ‘‘cooperative and collaborative’’ in their social outlook. Nevertheless, he adds that knowledge communities suffer from ‘‘trust dilemma’’ and need to overcome this fear in order to be

‘‘ The members of the knowledge community exist as information beings creating new knowledge about a business enterprise, a product or a new research and thus forming a new social communicative space-time of collective existence. ’’

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effective social entities where knowledge and research reciprocate to promote the cause of social good. However, it can be argued that, despite ‘‘trust dilemmas’’ suffered by knowledge communities in effective knowledge sharing and knowledge creation process; the social structure of knowledge communities remain through and through ‘‘communitarian’’ and ‘‘testimonial’’ transcending traditional notions of both ‘‘knowledge’’ and ‘‘community’’ and the way it was perceived by the human beings before the knowledge revolution (Kusch,2002). Moreover, knowledge communities have created new social space-time of social interactions, where cultural generality embraces cultural specificity and technology shakes hand with moral diversity (Audi, 2002; Cheater, 1995). In addition to the social-technological context of knowledge community, Jason (1997) and Craig (1999) have underscored the significance of a ‘‘psychological sense’’ of belonging to a community. They have proposed that positive thinking, commitment, flexibility and open channels of communication can effectively build community sense. Knowledge communities also exhibit this ‘‘psychological sense’’ of cohesion, collectivity, and commonality of vision and commitment to knowledge sharing, its dissemination and creation. Alternatively, knowledge communities as non-Euclidean social structures embedded in broader knowledge patterns generated by the communicative flux of knowledge-based environment must respond to the logic of knowledge economy. These social structures are fundamentally interactive collective episteme, allowing both a ‘‘layman’’ and a ‘‘scientist’’ to encounter each other in a true human context. Concepts, ideas and values misinterpreted and miscommunicated amongst people, societies and cultures and legitimized by age old cultural stereotypes have lost their meaningfulness and relevance in the wake of dynamic knowledge states of cyberspace. It appears that knowledge communities can transform the ancient regime of human hate, killing and exploitation and show human societies a true path of liberation and harmonious collective development cherished and shared by every living soul on the earth. The nostalgia that filled the human mind with symbols of ‘‘community’’ and ‘‘knowledge’’ has finally reached a moment of total realization by humankind (Jason, 1997).

Patterns of social management of knowledge Martens (2004) has categorized economic knowledge into symbolic knowledge communication and embodied knowledge communication. Symbolic knowledge communication reflects itself in conceptual learning. Abstract ideas and concepts characterize this kind of learning and knowledge. Martens (2004) assert that symbolic knowledge is difficult to acquire and learn. It might have an economic cost unbearable for its seekers. Hence, new ideas and concepts travel slowly across human societies. Embodied knowledge on the other hand is much easier to acquire, use and manage. This knowledge emerges in trade and new production of goods. This efficiency achieved by the embodied knowledge for the larger public good is, what Loasby (1999) states economic systems stand for, as they ‘‘are ways of organizing human knowledge so that it can deal more efficiently with its inherent incompleteness’’. The ‘‘embodied knowledge’’ is essentially instrumental, transactional in nature, and applied to satisfy human needs and thus overcome their inherent social incompleteness. In fact, all technological innovations belong to the embodied knowledge category. Martens (2004) has further stated that the wider social use and application of this knowledge can yield economic advantage to its consumers without exposing them to learn complexities of the entire process of knowledge creation behind the object, product or service. There are three fundamental social patterns, which explain the effective utilization and management of such type of knowledge. First, embodied knowledge exchanges take place within knowledge communities and within their own organizational frameworks. This constitutes the micro social level of knowledge utilization. The knowledge communities can be of scientist, researchers, local farmers, students and business enterprises. Second, embodied knowledge exchanges occur across knowledge communities. This signifies the meso social level of knowledge utilization. At this level, two or more different knowledge communities exchange and share information on areas of mutual interest. For example, a knowledge community of architects can utilize knowledge of local environmental group in designing eco-friendly architecture for urban areas. The knowledge community of

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‘‘ There is already emerging a profound and dynamic knowledge utilization pattern in knowledge communities of developing countries due to modern communicative practices. ’’

physicians can share their clinical insights and practices with an NGO working to create public awareness about HIV/AIDS in a local community. At this level, two or more knowledge communities socially interact to share their expertise and knowledge in their respective domains of knowledge. Societal reciprocity is quite evident at the meso-level of social interaction of knowledge communities. Third, embodied knowledge exchanges happen on a much broader level. This level of knowledge utilization emerges at the macro social exchange of knowledge across divergent knowledge communities. The divergent ideologies, religious beliefs and cultural sentiments reciprocate at this level of social exchange. World Economic Forum, World Social Forum, UN Global Compact, EFMD’s GRLI are examples of such forms of knowledge communities which function across different cultures, values and societies to create global harmony and understanding. Nonaka et al. (2001), Siebers (2003) Buil and Bergua (1998) have furnished critical investigations into the social patterns of management of knowledge in different contexts. Hakken (2004) Goldman (1999) Kitchener (2004), Bull (2000) Foss (2005) and Bounfour (2003) have also provided useful insights into the social utilization of new economic and social knowledge created by the new ‘‘technologies of knowing’’ (Cheater, 1995). Nonaka et al. (2001) have developed a very useful concept of management of knowledge at the organizational or micro social level. They have asserted that, ‘‘what knowledge management should achieve is not a static management of information or existing knowledge, but a dynamic management of the process of creating knowledge out of knowledge’’ and hence they have argued that, ‘‘organizational knowledge creation is a continuous self-transcending process’’. This can only be cultivated at organization level, if the view of knowledge shifts from static to dynamic one. The definition of knowledge as ‘‘justified true belief, as is done in the traditional Western epistemology’’, should be abandoned because it presents us with ‘‘an absolute, static and nonhuman view of knowledge and fails to address the relative, dynamic and humanistic dimensions of knowledge’’ (Nonaka et al. 2001). Nonaka et al. propose that we should interpret knowledge ‘‘dynamic because it is dynamically created in social interactions. Knowledge is also humanistic, and it has both an active and a subjective nature’’. Moreover, Nonaka et al. state, since knowledge is dynamic and intangible, therefore it needs a certain time and space, where it can be created. They have termed this space as ‘‘Ba’’ (roughly translated as place). By creating and managing Ba, ‘‘an organization can manage the knowledge creating process effectively’’. Nonaka et al. have further described the attributes of Ba in these words: Thus we consider ‘‘ba’’ to be a shared time and space for emerging relationship among individuals and groups to create knowledge. It can be physical (e.g., office, dispersed business space), virtual (e.g., e-mail, teleconference), mental (e.g., shared experiences, ideas and ideals), or any combination of these. It can be a shared space and time(from face-to-face to virtual) for a project team, a space for informal dialogues, a space to share experiences with customers, a space for interdivisional cooperation, or a space shared by virtual companies.

Knowledge communities operate in ‘‘ba’’ at the micro social level. The members of knowledge communities dynamically associate with fellow members, learn, and share their best practices or professional insights. Nonaka et al. (2001) have cited example of Seven Eleven Japan and how workers by using the four ba processes, namely; originating, dialoguing, systematizing, and exercising create and distribute effective practical knowledge of business enterprise at the sales floors of the company. The modern communicative practices such as wikis (particularly Wikipedia, a free encyclopedia,

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managed and accessed by people from across the globe) and web blogs are excellent examples of ‘‘ba’’ where knowledge is continuously created, and redistributed for obvious social and economic benefits of knowledge communities. People share and exchange both tacit and embodied knowledge for mutual benefit, for economic, social and political reasons at these forums. Khalil et al. (2006), Buckley and Carter (2004) and Mbaatyo (2001) have also studied the management of knowledge creation at the organizational level. They have found out that proper social and cultural integration of the modern technologies of knowing into the knowledge transfer processes can bear upon the profit, and productivity of business organizations. Furthermore, the efficacy of knowledge-based environment largely depends upon the effective social interactions of the managers and the knowledge environment of the organization. Siebers (2003) has undertaken a very insightful fieldwork into the meso-cultural level of knowledge creation and dissemination between traditional knowledge communities and contemporary forms of knowledge communities driven by modern scientifically elaborated knowledge at a Guatemala village. He has commented: In social terms the application of a specific body of knowledge may be rational for some while being irrational for others. The efficacy of both indigenous knowledge and modern technology would adopt a fetishsized character – expressed in meaningless quantitative terms – when delinked from the various groups of people involved and isolated from the cultural and power contexts in which they are always embedded.

Siebers has recorded that a significant pattern of social interaction exist between local Q’eqchi communities and the representatives of farmers. He has found out that farmers’ representatives perceive their cultural interaction with the local Q’eqchi in a ‘‘hierarchical’’ fashion, placing the Western civilization at the top. On the other hand Q’eqchi, integrate modern agricultural knowledge with their traditional agricultural knowledge, called ‘‘na’leb’’ within their unique cultural worldview. They are not afraid of using modern fertilizers, as Siebers has observed, but are reluctant to apply these to the traditional land use patterns due to lack of trust and fear of over reliance upon urban source of their indigenous economic activity. This shows that knowledge creation and knowledge dissemination at the meso-social level might require broader understanding of the social networks working within and without knowledge communities. It is relevant to state here that meso-level social interaction require a greater deal of trustworthiness, commitment and ethical sensibility to harness the ‘‘social capital’’ of knowledge communities (McElroy et al., 2006; Meyerson, 2001). Moreover, international strategic alliances in business cooperation also show a social ‘‘context-specific’’ interaction of different stakeholders in knowledge transfer processes across organizational boundaries. They learn from each other’s competencies during social knowledge transfer processes (Simonin, 2004). Buil and Bergua (1998) have also explored the meso-level social interactions in the management of risk perception in the construction of a dam in the Spanish villages of Campo, Morillo deLiena, Navarri and Las Colladas. They have discovered that the cultural dimension plays a very important role in the management of risk by local communities. It is important to note that at the societal level knowledge communities are reluctant to assimilate new knowledge because of lack of trust and other political and cultural influences such as shared beliefs and values. It is evident that the social management of knowledge in knowledge communities depends heavily on the ‘‘veritistic’’ and ‘‘trust’’ aspect of the social interactions (Goldman, 1999; Hakken, 2003). Culure, shared beliefs, values and cognitive uniformities must significantly, resonate as a part of a broader ‘‘social informatics’’ which places ‘‘knowledge-networking’’ at the core of whole process of knowledge creation, utilization and dissemination within knowledge communities as well as across different knowledge communities (Hakken, 2003). The conflicts of values can arise at the macro-level of social interaction between knowledge communities due to divergent cultures and worldviews. The external factor of growth in the knowledge-based environment of groups, organizations and nations at large would play a fundamental role in the resolution of these socio-cultural conflicts. The emergent social structures of knowledge integration, knowledge transfer and knowledge sharing would grow and enlarge because of continuous inflow of new technologies of knowing. The prevalent

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shyness, anxiety and unpredictability in new knowledge-driven social exchange process would dissolve, placing trust and human good at the core (Brown, 2002; Cooke, 2001; Foss, 2005; Amit, 2002; Cheater, 1995). There is already emerging a profound and dynamic knowledge utilization pattern in knowledge-communities of developing countries due to modern communicative practices. The embodied knowledge transferred to these regions in the form of different innovative products such as cellular phone, wireless communications, internet and computers have tremendously shifted the balance of social and economic prosperity in favor of ordinary and common citizens. Two technologies in particular are note worthy to mention here, i.e. cellular and wireless phones. These technologies are rapidly reshaping the traditional social and economic structure of less developed communities of developing countries into contemporary knowledge communities, which can now seize the opportunity of health, education and prosperity within affordable low-cost budget. This has led to an improvement in the general quality of life, in terms of new economic and social advantages such as increased rate of literacy, accessibility to new sources of information and knowledge via internet and better health awareness. In the developing countries of Asia, Africa and Latin America, knowledge communities working in areas of good governance, agricultural knowledge sharing, health awareness particularly HIV and family health, ecological crisis, gender issues, and literacy are fast growing. The governments of these developing countries are also fast responding to the globally networked knowledge economy. They are attempting to democratize their governance and liberalize their economies in order to remain relevant in an interdependent world. They are creating social conditions, which allow their citizens to engage on pressing global issue such as climate change, nonproliferation of nuclear arms and gender equality in socio-economic development of their respective societies. It would not be out of place to discuss the role of one global and one regional knowledge community in creating social awareness about ecological issues and promoting economic development of downtrodden communities of the region. These knowledge communities are respectively Greenpeace and The Grameen Bank of Bangladesh. Greenpeace, initially started as social community to register its protest against environmental pollution caused by the industrialized North, has now transformed into a global symbol of ecological responsiveness and made its inroads into strategic political and economic development policy frameworks of Europe and North America. The Greenpeace social phenomena did not remain confined to the West European societies. It has proliferated to the entire globe. It has created global consciousness amongst divergent cultures, values and religious tradition for a responsible ecological management of the world ecology. This is fundamental to the very survival and continuity of future human generations. The ecological knowledge created and shared by Greenpeace has radically altered the modern man’s view of nature as well as his social relationship to economic and technological development in decades to come. No global business corporation can operate successfully across the globe without showing a firm and tangible viewpoint on ecological responsibility. The Grameen Bank of Bangladesh is another pertinent example of socially relevant knowledge community. Its achievement is particularly exemplary for the developing countries of the South. Dr Muhammad Yunus, founder of Grameen and now a Nobel Laureate in Peace (2006), mobilized the poor communities of the rural Bangladesh with his vision to alleviate their poverty. He poured his savings into the socio-economic uplift of the rural communities of Bangladesh. He introduced the concept of ‘‘micro-credit’’ to farmers and weavers of less developed rural areas, focusing particularly on economic empowerment. This led to a rapid economic growth of rural communities ameliorating their social and economic disparities with more privileged stratas of the society. The concept of ‘‘micro-credit’’ has gained currency and application in large countries of South Asia, India and Pakistan. Both governments and civil society are actively pursuing the implementation of micro-credit in rural communities of South Asian region to transform poverty into social opportunity for creating prosperity and equality for less developed areas.

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‘‘ The knowledge-driven global mind thrives on more and more diverse sources of knowledge. ’’

It is obvious that knowledge creation and knowledge utilization by one knowledge community go hand in hand to the social advantage of diverse communities. The knowledge-based environment has become a key external factor in this regard. The dynamic social structure of technologies of knowing is reshaping everything. From statecraft to worship in a temple, every social act now constitutes meaningfulness in the flux of socially networked information world. Nothing exists outside this socially networked information world. The old Lamas of the ancient Tibet used to say that ‘‘Nothing exists but the mind (bodhisattva)’’. It appears that they foretold the shape of contemporary information economy, where people transact in real-time in diverse time zones. The socially networked economy as well as society constitutes the emerging form of global mind. This knowledge driven global mind thrives on more and more diverse sources of knowledge. It thrives on multiplicity of worldviews, values and beliefs. This is the very essence of emergent global existence of humanity. It is here that every human act is both local and global, because continuous flux of knowledge forces them to negotiate part of their localized existences and assume a chunk of new form of essential human identity from the emerging global mind. The real task of the knowledge communities lies here. They can transform the world to be a more harmonious place. The place which belongs to every living soul yet beyond all sorts of ‘‘title’’ and ownership (Sen, 1982), which is the root cause of social divisions, conflicts and poverty. In the genesis of emergent knowledge communities, a hope for the ‘‘Tao’’ of knowledge creation seems overwhelming. By understanding the inherent incompleteness of human condition and its eternal quest for perfection, it might transform to a new level of global human consciousness, helping it shed its age-old phobias and paranoias about the nature of ultimate meaning of all existence, rooted in the obsolete notions of duality and objectivity. Socrates uttered many years ago that, ‘‘All good is knowledge and all evil is ignorance’’; he in fact prescribed the elixir for the social ills of our times. There is less knowledge about HIV, so people socially exclude the sufferer of HIV/AIDS. There is less knowledge about the ability of women, so people alienate them out of decision making and leading. There is less knowledge about the biological role of rivers and oceans, so people relentlessly pollute oceans and rivers. There is less knowledge about democracy and freedom, so people feel secure under authoritarianism and desist from realizing their natural liberty. The socially networked global knowledge communities can help ignorant and underprivileged people of developing countries to develop and cherish the dream of social prosperity and economic freedom at par with the developed North. It is possible that with the emergence of collective global consciousness, the cultural obstacles for sharing and distribution of each other’s knowledge disappear. The knowledge environment creates those socially dynamic states where one epistemology, or one philosophy and economy become irrelevant. The inherent cultural multiplicity leads to new knowledge creation. The knowledge environment forces all human actors to reconsider their self-image in the light of a broader human collective image, surging out of the nexus of knowledge era. This broader collective human image formed of global mind lead everyone to some minimum common social themes, on which the bases of human existence depend, such as respect for other’s worldview, trust and sharing.

Conclusion Knowledge creation and its management is essentially a social activity. Knowledge communities particularly reflect the social forms of knowledge management and knowledge sharing. A ‘‘morphological’’ view of organizations, groups, communities and economies, which interprets these processes as socially organic and dynamically evolving, boundaryless, multiple, and interdependent social structures would be more in line with

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the current growth of knowledge globally (Stephenson, 1995). Cyberspace and computer mediated communications have created new social structures of collective cognition among knowledge communities to create and share their socio-economically advantageous practices with each other. These new modes of social communications have greatly expanded the effective social and economic uses of embodied knowledge as manifested in much of the new technologies of knowing, which include cellular phone, internet, wireless communications etc. Knowledge communities are socially interactive knowledge spaces that can be functional at the micro, meso and macro social levels. It is again the knowledge communities that are dynamically driving the developed and developing countries to share their knowledge repositories, in order to promote the shared values and divergent worldviews, for a better global civilization. Knowledge-based environment along with the culture of the knowledge communities shape their pragmatic value. Social interactions at various levels of knowledge communities can significantly influence the increase or decrease in their respective social capital. Moreover, the dynamic growth of knowledge communities heavily depends upon the social structures of trust, sense of community, commitment, shared vision, and continuous spirit of knowledge creation. Overcoming social digression (inequalities, conflicts on knowledge capital rights) at the meso-social levels of knowledge communities and at the macro-social level (global) is possible by the increased social interactions between the actors involved in the socially networked transfer of knowledge.

References Amit, V. (2002), Realizing Community: Concepts, Social Relationships and Sentiments, Routledge, London. Appadurai, A. (1995), ‘‘The production of locality’’, in Fardon, R. (Ed.), Counterworks: Managing the Diversity of Knowledge, Routledge, London. Audi, R. (2002), Epistemology; A Contemporary Introduction to the Theory of Knowledge, Routledge, London. Azzouni, J. (2000), Knowledge and Reference in Empirical Science, Routledge, London. Blackburn, S. (2001), ‘‘Reason, virtue, and knowledge’’, in Fairweather, A. and Zagzebski, L. (Eds), Virtue Epistemology: Essay on Epistemic Virtue and Responsibility, Oxford University Press, Oxford. Bounfour, A. (2003), The Management of Intangibles: The Organization’s Most Valuable Assets, Routledge, London. Brown, N.R. (2002), ‘‘‘Community’ metaphors online: a critical and rhetorical study concerning online groups’’, Business Communication Quarterly, Vol. 6 No. 2, p. 92. Buckley, J.P. and Carter, J.M. (2004), ‘‘A formal analysis of knowledge combination in multinational enterprises’’, Journal of International Business Studies, Vol. 35 No. 5, p. pp371. Buil, M.G. and Bergua, J.A. (1998), ‘‘From economism to culturalism;the social and cultural construction of risk in the River Esera (Spain)’’, in Abram, S. and Waldren, J. (Eds), Anthropological Perspectives on Local Development: Knowledge and Sentiments in Conflict, Routledge, London. Bull, M. (2000), Sounding out the City: Personal Stereos and the Management of Everyday Life, Berg Publishers, Oxford. Carpendale, J.I.M. and Ulrich, M. (2004), Social Interaction and the Development of Knowledge, Lawrence Erlbaum Associates, Mahwah, NJ. Cheater, P.A. (1995), ‘‘Globalization and the new technologies of knowing: anthropological calculus or chaos?’’, in Strathern, M. (Ed.), Shifting Contexts: Transformations in Anthropological Knowledge, Routledge, London. Cooke, P. (2001), Knowledge Economies: Clusters, Learning and Co-Operative Advantage, Routledge, London. Craig, E. (1999), Knowledge and the State of Nature: An Essay in Conceptual Synthesis, Clarendon Press, Oxford.

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Desouza, K.C. (2002), Managing Knowledge with Artificial Intelligence: An Introduction with Guidelines for Nonspecialists, Quorum Books, Westport, CT. Fardon, R. (1995), Counterworks: Managing Diversity of Knowledge, Routledge, London. Foss, J.N. (2005), Strategy, Economic Organization, and Knowledge Economy: The Coordination of Firms and Resources, Oxford University Press, Oxford. Fuller, S. (1991), ‘‘Realism, the moving aspect of science studies: a tale of philosophers, historians and sociologists in hot pursuit’’, in Giere, R.N. and Gleryn, T.F. (Eds), Social Epistemology, Indiana University Press, Bloomington, IN. Gibson, R.F. Jr (1988), Enlightened Empiricism: an Examination of W.V.O. Quine’s Theory of Knowledge, University Press of Florida, Gainesville, FL. Goldman, A.I. (1999), Knowledge in a Social World, Clarendon Press, Oxford. Goldman, A.I. (2002), Pathways to Knowledge: Private and Public, Oxford University Press, New York, NY. Groff, R. (2004), Critical Realism, Post-Positivism and the Possibility of Knowledge, Routledge, London. Hakken, D. (2003), The Knowledge Landscapes of Cyberspace, Routledge, New York, NY. Howell, S. (2002), ‘‘Community beyond place: adoptive families in Norway’’, in Amit, V. (Ed.), Realizing Community: Concepts, Social Relationships and Sentiments, Routledge, London. Jasanoff, S. (2004), States of Knowledge: The Co-production of Science and Social Order, Routledge, London. Jason, A.L. (1997), Community Building: Values for a Sustainable Future, Praeger Publishers, Westport, CT. Kempny, M. (2002), ‘‘Cultural islands in the globalizing world; community-cum-locality of the Cieszyn Silesian Lutherans’’, in Amit, V. (Ed.), Realizing Community: Concepts, Social Relationships and Sentiments, Routledge, London. Khalil, O., Claudio, A. and Seliem, A. (2006), ‘‘Knowledge management: the case of Acushnet Company’’, SAM Advanced Management Journal, Vol. 7 No. 3, p. 34. Kitchener, F.R. (2004), ‘‘Piaget’s social epistemology’’, in Carpendale, J.I.M. and Ulrich, M. (Eds), Social Interaction and the Development of Knowledge, Lawrence Erlbaum Associates, Mahwah, NJ. Kramer, M.R. (1999), ‘‘Social uncertainty and collective paranoia in knowledge communities: thinking and acting in the shadow of doubt’’, in Levine, M.J., Messick, M.D. and Leigh, T.L. (Eds), Shared Cognition in Organizations; the Management of Knowledge, Lawrence Erlbaum Associates, Mahwah, NJ. Kusch, M. (2002), Knowledge by Agreement: The Programme of Communitarian Epistemology, Clarendon Press, Oxford. Loasby, J.B. (1999), Knowledge, Institutions and Evolution in Economics, Routledge, London. McElroy, W.M., Jorna, J.R. and Van Engelen, J. (2006), ‘‘Rethinking social capital theory: a knowledge management perspective’’, Journal of Knowledge Management, Vol. 10 No. 5, p. 124. McGinn, C. (1999), Knowledge and Reality: Selected Essays, Clarendon Press, Oxford. Mannheim, K. (1952), Essays on the Sociology of Knowledge, Oxford University Press, Oxford. Martens, B. (2004), The Cognitive Mechanics of Economic Development and Institutional Change, Routledge, New York, NY. Mbaatyo, A. (2001), ‘‘Managing schools of business in the age of knowledge’’, SAM Advanced Management Journal, Vol. 66 No. 2, p. 29. Meyerson, M.E. (2001), ‘‘Human capital, social capital and compensation: the relative contribution of social contacts to managers’ incomes’’, in Lesser, L.E. (Ed.), Knowledge and Social Capital: Foundations and Applications, Butterworth-Heinemann, New Dehli. Nonaka, I., Konno, N. and Toyama, R. (2001), ‘‘Emergence of ‘Ba’: a conceptual framework for the continuous and self-transcending process of knowledge creation’’, in Nonaka, I. and Nishiguchi, T. (Eds), Knowledge Emergence: Social, Technical and Evolutionary Dimensions of Knowledge Creation, Oxford University Press, Oxford.

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Sen, A. (1982), Poverty and Famines: An Essay on Entitlement and Deprivation, Oxford University Press, Oxford. Siebers, H. (2003), ‘‘Management of knowledge and social transformation: a case study of Guatemala’’, in Bicker, A., Pottier, J. and Sillitoe, P. (Eds), Development and Local Knowledge: New Issues in Natural Resources Management, Conservation, and Agriculture, Routledge, New York, NY. Simonin, L.B. (2004), ‘‘An empirical investigation of the process of knowledge transfer in international strategic alliances’’, Journal of International Business Studies, Vol. 35 No. 5, p. 407. Stephenson, R.H. (1995), Goethe’s Conception of Knowledge and Science, Edinburgh University Press, Edinburgh. Stevenson, P. (2005), ‘‘Knowledge: economy or community?’’, Futures, Vol. 37 No. 8, p. 881. Wittgenstein, L. (1985), Philosophical Investigations, Basil Blackwell, Oxford. Zimmerman, J.N. and Meyer, A. (2005), ‘‘Building knowledge, building community: integrating internet access to secondary data as part of the community development process’’, Journal of the Community Development Society, Vol. 36 No. 1, p. 93.

Further reading Mason, A. (2000), Community, Solidarity, and Belonging: Levels of Community and their Normative Significance, Cambridge University Press, Cambridge.

About the authors Ahmad Raza is a Senior Research Associate in Management Sciences at the School of Business and Economics, University of Management and Technology, Lahore, Pakistan. E-mail: [email protected] A. Rashid Kausar is a Professor of Knowledge Management at the School of Business and Economics, University of Management and Technology, Lahore, Pakistan. E-mail: [email protected] David Paul is a Professor of Management at the Centre for Vocational Development, University of Macquaire, Sydney, Australia. E-mail: [email protected]

To purchase reprints of this article please e-mail: [email protected] Or visit our web site for further details: www.emeraldinsight.com/reprints

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Conversing cities: the way forward Mimi Tresman, Edna Pa´sher and Francesco Molinari

Mimi Tresman is a Consultant and Researcher at Edna Pa´sher PhD & Associates, Israel. Edna Pa´sher (PhD) is CEO of Edna Pa´sher PhD & Associates, Israel. Francesco Molinari (MSc, BA) is a PhD Scholar on Public Sector Economy and Regulated Sectors Management at the University of Siena, Department of Business and Social Studies, Siena, Italy.

Abstract Purpose – The purpose of this paper is to address the importance of conversing within cities, organizations and beyond, in order to adapt to the rapidly changing environment and promote co-operation, participation and with special reference to European cities. Design/methodology/approach – This paper brings examples and case studies of how the concepts of conversing cities has been and is being integrated into existing cities focusing on the future – youth, employment, education and quality of live as essential factors for the future prosperity of cities. Findings – With the rapid changes in society, economy and technology, not only business organizations need to adapt to the new reality but also cities. Conversing is an important part of adaptation – communicating, making contact, networking, sharing ideas, creating new knowledge. Originality/value – This article shows how interactions which have been formulated for organizations (businesses) can be relevant and essential to cities as living and changing units and shows how conversing cities have benefited and prospered. Keywords Knowledge management, Innovation, Citizen participation, Democracy, Cities, Europe Paper type Conceptual paper

Introduction With the rapid changes in society, the move towards knowledge economies and the migration of traditional industries out from Europe, rapid urbanization and the raise in the urban standard of living, European cities need to re-invent themselves (Carrillo, 2006) or they may die. The Lisbon Agenda addresses these issues and others in the following strategic goal of becoming ‘‘the most competitive and dynamic knowledge-based economy in the world, capable of sustainable economic growth with more and better jobs and greater social cohesion’’ (Lisbon European Council, March 2000). In order to deal with the shift towards an intangible knowledge economy it is necessary to create knowledge societies (New Club of Paris, 2006), empowering citizens into knowledge citizens (Goldberg et al., 2006).

Preparing for the future The migration of rural populations into cities, which started in the onset of industrial revolution, is still happening. Today 50 per cent of the world’s population lives in cities, and it is expected that by 2025, 75 per cent of the population will be urban (Carrillo, 2006). For EU27, the share of people that lives in urban areas is more than four in ten (SERA, 2006), only two out of ten live in predominantly rural areas. In addition, the deterioration of the sense of community in many cities (crime, unemployment, ethnic divide) has been emphasized by a number of incidents of social unrest in Europe over the past years. This has an effect on the social fabric which the city consists of and in order to create a city which is to survive and prosper there is a need to create more social cohesion, both for preserving and raising standards of living (by reducing crime, better education, welfare and jobs) and for creating,

DOI 10.1108/13673270710819807

VOL. 11 NO. 5 2007, pp. 55-64, Q Emerald Group Publishing Limited, ISSN 1367-3270

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renewing and sharing the diversity of knowledge (through research, participation, dialogue and inclusion).

Knowledge cities must be conversing cities: Conversations are seen by some scholars as a ‘‘unifying principle’’ for the generation of innovation in corporate, as well as urban, environments (Stewart, 2001; Dvir and Pasher, 2004). This has much to do with empowering people in the process of city governance and at the same time, with a restored or strengthened legitimacy of governments (Pellizzoni, 2004). In the context of knowledge cities, conversations can involve the inhabitants of a same city and/or different cities (Ergazakis et al., 2004), on one hand, or the practice of ‘‘social dialogue’’ between public administrators and citizens (Wiig, 2002), on the other. However, the latter must be more than a periodic consultation with selected groups or communities of people (including their elected representatives); for three reasons: 1. Attention centers on individual knowledge that should be made available for public purposes, in the interest of the whole community. 2. Citizen engagement in policy making has a significant impact on the quantity and quality of deliberations, especially when these are affecting a sub-sample of the whole population (e.g. in the case of the location of hazardous waste treatment plants). 3. People’s participation in the democratic process (especially at local level) has always been seen as a way to increase the level of acceptance, and confidence, in the direction that the whole community is taking towards the future. While very few doubt of the positive relation between knowledge sharing and conversations, a more sensitive issue is the inherent dilemma (or contradiction) between participation and representation: hearings, fora, small talks and other forms of public involvement, differently from voting, do not ensure a fair representation of the interests of the whole population. Quite usually, the floor will be limited to ‘‘the best informed’’, ‘‘the affluent’’, or ‘‘the most educated’’ part of society, which can lead to severely distorted results. Another sensitive issue can be identified as ‘‘noise in conversations’’, or ‘‘the paradox of scale’’ (Fishkin, 1995): too many voices rarely lead to a clear conclusion, or rather fall victims of someone else’s ‘‘summing up’’. It is then part of a city government’s responsibility to ensure that the results – not just the topics, or the frames – of people’s conversations be really reflecting a free, open and comprehensive social debate, able to build intellectual skills or to leverage upon existing ones.

Knowledge cities – conversing innovative living environments: A knowledge city refers to a city as a dynamic and complex living system, much like a living organism, a network of integrated systems, processes and structures which exists within an environment which experiences and must adapt to internal and external changes. A culture of conversing promotes what is required in order to adapt successfully to change and the unknown (Stewart, 2001). As Albert Einstein said, you can’t solve problems with the same way of thinking which created them. Along this line, knowledge cities are a part of a ‘‘new paradigm which develops new strategies which go far beyond the repetition of ‘old recipes’ to ‘make the future’, or variations of the same mistake’’ (New Club of Paris, 2006). Expansion of the concept of wealth to intangible concepts such as intellectual capital, which includes human abilities, relationships and innovation, creates a new way of viewing the world in financial terms. Thus, future economic growth is interconnected with many different systems in society, the environment and the global economy. The ability to create a connected and conversing network of key players (industry, academia, schools, health, government) reflects on the city’s ability as a system to adapt to internal and external changes and utilize the value of a heterogenic society, not only in the way of tolerance but in the creation of value and knowledge from this diversity.

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‘‘ While very few doubt the positive relation between knowledge sharing and conversations, a more sensitive issue is the inherent dilemma (or contradiction) between participation and representation. ’’

The benefits of a tolerant and conversing culture, created through continuous interaction between regions, are acceptance and respect, trust, co-operation between and within groups, creativity, inclusion, participation and ethical behaviour. So is the spontaneous appearance of other important and emerging issues such as ecological awareness and responsibility (Ximena et al., 2004).

The importance of conversing for organizational learning: In a culture where dialogue, communication and conversing are common, people feel confident to express their thoughts and ideas in regard to questions that matter. A culture of trust enables the creation of ‘‘new knowledge which is created from questions that arise in conversation’’ (Stewart, 2001). As Alan Webber said: ‘‘In the new economy, conversations are the most important form of work. Conversations are the way knowledge workers discover what they know, share it with their colleagues, and in the process create new knowledge’’ (Stewart, 2001). Through creating a culture of dialogue, trust, inclusiveness, confidence and hope are promoted. People feel and become part of the decision-making process and community building, generating new ideas, participation, knowledge, issues to be dealt with, and ways of dealing with them. In cities, like in organizations, there is a process of organizational learning. This is rooted in individual learning and a synergy of knowledge and insights and create a common value greater than the sum of its parts through knowledge sharing. Feedback is a way of maintaining good relationships between management/municipality and employees/citizens and encourages individuals to express their views and ideas. As it has been found by Goldberg et al. (2006): ‘‘A learning city, just like a learning organization, needs to be a place where both individual and group learning occurs through conversation and feedback.’’

Case study: the city of Holon, City of Children The city of Holon, in central Israel, was experiencing problems such as young people leaving the city and becoming an unattractive place to the young and the old alike, in the early 1990s. As a result of the ongoing situation, the new mayor at the time initiated a new client-supplier relationship between the city and its inhabitants. And through a survey on the municipal demographics, economic, cultural and social profile a new strategy was developed to transform the city through the vision of Holon as the City of Children. This emphasized the focus on the future, nurturing of knowledge and drawing young people and families to the city. Inviting people to converse had an effect on their attitude and their willingness to participate and contribute. As a result, new cultural institutions were created to educate, enrich and focus on children, such as: the Israeli Children’s Museum, a unique museum that offers an interactive experience through the use of advanced technology. ‘‘Meet the Eye’’, a centre for experiencing art through advanced technology, aimed at enriching the children’s world through the language of art. The Centre for Digital Art, a technological institute which teaches children about science and technology through interactive experience (Levin-Sagi et al., 2006).

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The physical surroundings of the city were an important aspect in Holon’s strategy and renewal, promoting the creation and preservation of parks and green spaces, public art gardens, integrating public knowledge in a natural setting. In addition, the city developed economically, aiming to provide future opportunities and contribute to a rising standard of living and attractiveness. In order to do just that, the city improved its own services to the public. This could be measured through its performance as a knowledge city in the way of intellectual capital management.

Putting youths in the centre The Israeli Ministry of Education has recently launched a long-term project for the inclusion of youths (aged 12-18) in the planning and creation of their Future and the future of their cities. This is done on a municipal or regional level by adopting a systems thinking approach which leads to the creation of a space in which young people can converse and work together with key players from different fields such as the mayor, schools, after school activities, youth groups, social services, industry, academia, culture and sports. Creating an environment in which different organizations and people work together at a round table and share knowledge, expectations, fears, and together evaluate and implement ways of addressing these issues. In the authors’ work with the Israeli Ministry of Education, the idea of creating Future Centers as hubs for these roundtables was introduced. A long exploration of Future Centers which started in a collaboration with Leif Edvinsson in the Skandia Future Center on creating the Intellectual Capital report of Israel in 1998, has evolved into a European-funded project on Future Centers (OpenFutures in FP6) in which the authors are partners and in which the potential of shared spaces for conversations on questions that matter for the future of organizations and cities is explored. By addressing young people’s interests, it is possible to make a city more attractive to them. This includes investment in future jobs to make it attractive to today’s youth in the future. Having a high level of education will give young people a good starting point with many future opportunities, raising the standard of education, employment and living overall, and making the city a more attractive and sustainable place to live in: Society must consist of three generations . . . The older generation holds experience and knowledge that the young have not yet acquired. While the younger generation hold knowledge that is more technologically oriented, up to date, and innovative (Levin-Sagi et al., 2006. p. 114).

This is why cities must be attractive to all groups in society and promote exchange of knowledge, new ideas, methods and lessons leaned. This in itself encourages social cohesion, conversations, general atmosphere and standard of living: Creating a positive future begins with human conversation. The simplest and most powerful investment a member of a community or an organization may make in renewal is to begin talking with other people as though the answers mattered (Stewart, 2001).

The future of cities in Europe In order to address the EU’s goals as stated in the Lisbon Agenda, it is necessary to create a new way of living in a community and participating in society. With technological advances and the internet, the unknown of climate change and the rapid changes to European economies, cities need to become favourable environments for exchanging and creating knowledge. By promoting knowledge-based industries and networks, cities can maintain high standards of living through low unemployment levels and better jobs, research, education and investment in infrastructure and services. The investment knowledge cities make in education, raise the standard and skills for further education and skilled labour, working towards sustaining the future of the city. In addition, the investment in culture, arts and sports contributes to a high standard of living, natural environment and attractiveness of a city and a region.

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‘‘ Inviting people to converse had an effect on their attitude and their willingness to participate and contribute. ’’

The processes which drive knowledge cities produce a democratic system which enables and encourages citizen participation and dialogue in order to create an urban community and a sustainable society in the twenty-first century. Thus, contributing to the creation of a ‘‘competitive and dynamic knowledge-based economy . . . capable of sustainable economic growth with more and better jobs and greater social cohesion’’ by ‘‘supporting the transformation of our society and economy into a knowledge society and a knowledge economy’’ (New Club of Paris, 2006).

Inspiring a ‘‘conversing democracy’’ model Let the enemies of the Persians be ruled by democracies; but let us choose out from the citizens a certain number of the worthiest, and put the government into their hands. For thus both we ourselves shall be among the governors, and power being entrusted to the best men, it is likely that the best counsels will prevail in the state (Herodotus, The Histories III.81).

Democracy was born in Athens almost 2,500 years ago, and still then something was wrong with it. Herodotus, the Greek writer known as the Father of History, describes a debate on the three known government types (monarchy, oligarchy and democracy), stating that in democracy, deliberations are made by the entire citizenry, while the magistrates are held accountable and selected by lot. None of these conditions is reflected in current democracies. In particular, ‘‘the entire citizenry’’ is just too large to assemble and discuss, let alone decide, on any specific issue. Public officials are not randomly selected but delegated through a majority vote. Universal deliberation is substituted by the universal (and untouchable) right to cast a ballot in the polls. However, the elected members of modern parliaments and councils – including the professional bureaucrats – are hardly made accountable to the citizenry, and what is probably worse, a bulk of evidence on political business cycles is there to show that ‘‘being accountable’’ simply does not increase the incumbents’ chances to get re-elected. (Neither does it lower them, of course, but the two events seem largely uncorrelated.) Looking also at the growing costs of electoral campaigns and the increasing level of ‘‘professionalism’’ (c.f. Weber, 1919) of modern politics and politicians, one might be tempted to conclude that Herodotus’ conditions for oligarchy, rather than democracy, are satisfied in our times. However, his prophecy seems far from realized, as the needs for a managerial injection and repeated accountability prescriptions are ‘‘top of the list’’ of remedies to our ailing political class. The ICT (information and communication technology) revolution of the past 20 years and the internet explosion in the past ten have given new momentum and offered a wider perspective not just to (e-)voting, but also to (e-)participation in collective dialogue and decision making. Yet as was emphasized by Pateman (1970) almost forty years ago, modern theories of democracy attach little value to citizens engagement and universal deliberation. A paradigm shift is probably needed to make room for normative concepts like Dahl’s (1998) conditions for democratic decision making, i.e. B

Effective participation.

B

Equality in voting.

B

Gaining enlightened understanding.

B

Exercising final control over the agenda.

B

Inclusion of adults.

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Each of the above conditions raises sensitive and unsolved issues; for instance, it is known from Arnstein’s (1969) seminal work that the development of participation in a selected context can reach different levels of granularity, including ‘‘loose coupling’’ and rhetoric ‘‘manipulation’’. At the other extreme, Dahl himself admits that in the real world, it is very unlikely that every citizen can have equal opportunities to influence the policy agenda. The recent popularity of electronic voting is partly related with the possibility of enhancing people’s control over policy makers. Yet in the State of California, as reported by Zakaria (2003), when people were asked to vote electronically on more than 200 pieces of legislation in one single year, this instead of opening up a new perspective to participatory democracy, simply turned into the creation of ‘‘a jumble of laws, often contradictory, without any of the debate, deliberation, and compromise that characterize legislation’’. Herodotus’ worries about the risks of magistrates selection by lot are echoed in this description. Using Zakaria’s words, ‘‘politics did not work well when kings ruled by fiat and it does not work well when the people do the same’’. However, this would not necessarily imply that ‘‘the elected’’, not to speak of ‘‘the appointed’’, public officials could take better decisions on their own in the interest of the whole population. As Fishkin (1995) clearly stated: ‘‘The (real) problem of democratic reform is . . . how to bring people into the process under conditions where they can be engaged to think seriously and fully about public issues’’. This is exactly what a conversing city should be aiming at. Requirements for this do not only include the establishment of mechanisms for expressing a ‘‘separate judgement’’ of the electors with respect to the elected, but also the settlement of conditions for a timely, informed and responsible judgement, that are definitely harder to achieve. Internet and the ICT are not a viable solution to that. Apart from any consideration on the digital divide running across homes, boroughs and regions, the internet’s capacity to ensure many-to-many deliberative discussions is questioned by some, who argue that these are best conducted in face-to-face settings involving relatively few people (Coleman and Gøtze, 2001). Thus, a solution is lacking for connecting, consulting and engaging citizens without a personal access to the Internet. Public kiosks, cyber-cafe´s and community centres lack of the necessary diffusion, while TV and other digital platforms need to be integrated with a socio-technical solution to favour conversations and deliberations within groups of people. This may also recall Plato’s belief that 5,040 is the ideal number of citizens to take part in a working democracy; that figure, however, would be high enough to require the provision of supporting facilities to enable Dahl’s ‘‘enlightened understanding’’ of decision matters and the establishment of fair rules to collect and aggregate the opinions of everyone.

Case study: the regional law on (e-)participation in Tuscany Tuscany is, indeed, one of the Italian regions which are most active in e-Government projects. Apart from the State-funded initiatives in the ICT area, a good share of which belongs to the Tuscan Public Administration, it is worth to mention here the following:

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1995-now: building up and maintenance of a region-wide telematic infrastructure, called RTRT (first example in Italy), linking all the main public entities of Tuscany and with a significant representation of the private sector (both profit and non-profit).

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2001-now: conception and implementation of the ‘‘e-Toscana’’ initiative (the Action Plan of Tuscany Regional Administration), including a ‘‘long list’’ of 50 specific projects for ICT solutions development in the business area, the deployment of e-Government services and the promotion of e-Inclusion in the Regional Information Society, with an overall investment of more than e100 million.

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Ongoing activities for dissemination of free and open source software and the testing of broad band and other innovative infrastructure solutions in remote and rural areas.

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Another example of public intervention in the field is the e5.7-million investment plan funded by the Regional Administration over the past three years, in order to spread some 300 ‘‘PAAS’’ within 192 Tuscan Municipalities, in cooperation with non profit entities, NGOs and voluntary associations. Each PAAS has been built with a financial contribution of e15,000 and is now up and running at least 12 hours a week (50 per cent of time between 6 p.m.-10 p.m., at least once on Saturdays or Sundays), under the supervision of an NGO and/or Municipality. In this specific instance, public intervention was motivated by the awareness of a delay accumulated by Tuscany with respect to its ‘‘competing Regions’’ and of the opportunities that investments in the area of ICT could create both for citizens and businesses. However, with a twenty-first century hardware and software installed at each PAAS, and an old tradition of meeting and teaming up in their off-duty activities, a side effect of this operation was to start looking at the Tuscan population as a potential testbed for an ICT-supported participatory legislation process. Not surprisingly, the starting point was a proposal for institutional change. The Regional Cabinet, led by President Claudio Martini, appointed Mr Agostino Fragai as delegated member to the reform of the political decision making and ‘‘cooperative governance system’’ in Tuscany, with a specific orientation to citizens’ involvement in the legislative process. In January and May 2006, two specific events were organised, to collect and discuss the international evidence on (e-)Participation in Europe and worldwide. A specific website was created counting more than 100,000 hits in just a few months. More than 50 public meetings were held throughout the Tuscan territory, including ‘‘focus groups’’ and other forms of structured interactivity. The idea has been to initiate the discussion around a draft regional law on citizens’ participation, using a ‘‘bottom-up approach’’, in order to identify the core issues and the possible guidelines of this legislation effort, without starting from a predefined text, but rather recognizing the participation experiences already on course in Tuscany. In parallel, a coordinating group was created at the Department for Public Administration of the National Government, with the presence of several Regions, to enlarge the discussion about the topic at a multilateral level. On 18 November 2006 in Marina di Carrara, the Region organized an Electronic Town Meeting, a participatory method allowing involvement of large audiences, where the participants could carry on a simultaneous discussion in small groups, individually expressing their opinions through an electronic polling system. Domain experts contributed to the process, stimulating reflection about the various issues at stake. The work sessions incorporated participatory planning techniques such as Open Space Technology and Focus Groups: In a large pavilion of one of the most important exhibition areas of Tuscany, almost 500 people – equally representative by gender, and belonging to all social and professional groups, including immigrants, religious minorities and policy makers – coming from the ten provinces of the Region, were gathered and let interact for one full day throughout three different working sessions: 1. how to improve citizens’ participation on a specific public project (e.g. on the topics of participatory budget, urban planning, etc.); 2. how to manage the impact of major public works to the communities involved (similar to the experience of the French de´bats publics – see, e.g. www.debatpublic-iter.org); and 3. how to get more information on public policies and create a wider ‘‘culture of participation’’ within the Tuscan polity and society. Fifty tables were set up, each seating ten people. Every table was equipped with a computer, connected to the others and to a central server by means of a wireless network,

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and was presided over by a facilitator who conducted the discussions; each member of the panel also had a remote control for voting. The discussion on each subject of the three sessions was briefly introduced by a domain expert, and supported by a ‘‘Discussion Guide’’ that was circulated before the meeting. The participants in each table were allowed some predefined time to interact and send their comments to a managing group of experts (the ‘‘Theme Team’’), who were in charge of summarizing the feed-back received and sending questions back to the tables for a final vote on each of them. Much of the day’s organization was ensured by some 100 volunteers, who carried out not only the most important logistic tasks (such as reception and visitors orientation), but also the delicate roles of table facilitators and/or members of the ‘‘Theme Team’’, thus giving life to the supporting structure for the whole process. The activities of the Electronic Town Meeting were disseminated through webcasting on a national TV channel (MTV) and to the PAAS network mentioned above, to ensure the widest possible impact. The results of this experiment were later fed into the law-making agenda of the Cabinet, that is currently ongoing (see www.regione.toscana.it/partecipazione). In March 2007, the Regional Council discussed the results and confirmed the validity of the work performed until then, by approving a list of recommendations; a first draft of the Law on (e-)Participation will appear by April and consultations will then take place with the stakeholders of the Tuscan ‘‘cooperative governance system’’, including the table facilitators and the participants in the Electronic Town Meeting of November 2006.

The importance of conversing for legislation: This ongoing experience of the Tuscany region is worthwhile in two respects: 1. on the one hand, it tackles with the issue of participatory legislation in a ‘‘self-mirroring’’ way, as it started with a participatory law drafting on the topics, procedures and methods that can ensure further integration of citizens ‘‘will’’ in the future decision-making process; and 2. on the other hand, it offers an intelligent and measured way to integrate the Tuscan people’s ‘‘informed judgment’’ into the existing constitutional setup, without imposing limitations to the law making competency of elected bodies (the Regional Council and the Cabinet), nor reducing the supplementary role of consultations with the economic and social stakeholders of the region. The next logical step will be to develop a coherent evaluation framework (Macintosh and Whyte, 2006) to assess the impact, benefits and limitations of the participatory framework created. Allowing citizens to ‘‘have their say’’ on the evaluation of public sector performance is also very much in line with the wave of government reforms aiming to increase the quality and accountability of results (Mussari and Steccolini, 2006). A person-centric, experience-based perspective can ensure a more sustainable innovation in the design and management of public services, by taking benefit of the ideas, suggestions and knowledge of the people involved with respect to their daily needs, in their every day lives, encompassing all their societal roles. Trying to build a participatory system of performance measurement is

‘‘ Expansion of the concept of wealth to intangible concepts such as intellectual capital, which includes human abilities, relationships and innovation, creates a new way of viewing the world in financial terms. ’’

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coherent with the increasingly ‘‘networked’’ outlook of modern public administrations and the delicate equilibrium to be searched between budget restrictions and continuous improvement of policy outcomes.

Conclusions The model of ‘‘conversing democracy’’ has still to be founded and better rooted in the (classical or) modern theorising, yet it presents some immediate advantages over the current state of things: B

it is related with a concept of ‘‘wise’’ (and ‘‘advised’’) citizenship, that perfectly fits into that of learning city (and knowledge society);

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it can provide a sensible solution to the ‘‘dilemma’’ between representative and deliberative democracy, allowing people to have their say without dismissing or undermining the familiar gateway of free elections as access to the power and governance; and

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it can offer a new perspective for measuring the accountability of governments and allowing a participatory evaluation of law and policy making.

References Arnstein, S.R. (1969), ‘‘A ladder of citizen participation’’, Journal of the American Institute of Planners, Vol. 35 No. 4, pp. 216-24. Carrillo, F.J. (Ed.) (2006), Knowledge Cities, Approaches, Experiences and Perspectives, Butterworth-Heinemann, Burlington, MA. Coleman, S. and Gøtze, J. (2001), Bowling Together: Online Public Engagement in Policy Deliberation, available at: www.bowlingtogether.net, Hansard Society, London. Dahl, R. (1998), On Democracy, Yale University Press, Yale, CT. Dvir, R. and Pasher, E. (2004), ‘‘Innovation engines for knowledge cities: an innovation ecology perspective’’, Journal of Knowledge Management, Vol. 8 No. 5, pp. 16-27. Ergazakis, K., Metaxiotis, K. and Psarras, J. (2004), ‘‘Towards knowledge cities: conceptual analysis and success stories’’, Journal of Knowledge Management, Vol. 8 No. 5, pp. 5-15. Fishkin, J. (1995), The Voice of the People: Public Opinion and Democracy, Yale University Press, Yale, CT. Goldberg, M., Pasher, E. and Levin-Sagi, M. (2006), ‘‘Citizen participation in decision-making processes: knowledge sharing in knowledge cities’’, Journal of Knowledge Management, Vol. 10 No. 5, pp. 92-8. Levin-Sagi, M., Pasher, E. and Hertzman, H. (2006), ‘‘Holon: transition into City of Children’’, in Carrillo, F.J. (Ed.), Knowledge Cities, Butterworth-Heinemann, Oxford, UK. Macintosh, A. and Whyte, A. (2006), ‘‘Evaluating how eParticipation changes local democracy’’, in Irani, Z. and Ghoneim, A. (Eds), Proceedings of the eGovernment Workshop 2006: eGov06, Brunel University, ITC Publications, Edinburgh, 11 September. Mussari, R. and Steccolini, I. (2006), ‘‘Using the internet for communicating performance information’’, Public Money and Management, June, pp. 193-6. New Club of Paris (2006), The Manifesto of ‘‘The New Club of Paris’’ on the Knowledge Society and its Economic Foundations, available at: www.execupery.com/dokumente/NCP_manifesto_final_for_ decision_by_the_first_GA.pdf Pateman, C. (1970), Participation and Democratic Theory, Cambridge University Press, Cambridge. Pellizzoni, L. (2004), ‘‘Responsibility and environmental governance’’, Environmental Politics, Vol. 13 No. 3, pp. 541-65. SERA (2006), Study on Employment in Rural Areas: A study Commissioned by the European Commission, European Commission, Brussels.

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Stewart, A. (2001), ‘‘The conversing company: its structure, power and potential’’, presented at the 1st World Conference for Systemic Management, Vienna, May. Weber, M. (1919), ‘‘Politik als Beruf, English translation by Ronald Speirs as ‘‘The profession and vocation of policy’’, in Weber, M. (Ed.), Political Writings (1994), Cambridge University Press, Cambridge, pp. 309-69. Wiig, K.M. (2002), ‘‘Knowledge management in public administration’’, Journal of Knowledge Management, Vol. 6 No. 3, pp. 224-39. Ximena, D.Y. and Maturana, H. (2004), Organizational Matriztic Understanding. Matriztica Institute, Santiago, Chile, available at: www.matriztica.org Zakaria, F. (2003), The Future of Freedom, Norton Publishing, New York, NY.

About the authors Mimi Tresman is a consultant and researcher at Edna Pasher PhD & Associates, working with organisations on sustainable development and social aspects, part of which is the creation of knowledge/conversing cities, future centers and dialogue creation. She is the corresponding author and can be contacted at: [email protected] Edna Pasher (PhD) is CEO of Edna Pasher PhD & Associates, a management consultancy which was established in 1978. Edna Pasher has been at the forefront of social and organisational development which includes extensive work on: knowledge cities, knowledge management, sustainability and intellectual capital. Creating the future and preparing for it is a central focus in the work. Francesco Molinari (MSc, BA) is a PhD Scholar on Public Sector Economy and Regulated Sectors Management at the University of Siena, Department of Business and Social Studies. As consultant for several public and private organizations, he has been involved for several years in the coordination of EU-funded, IST-related research and training projects. Currently he is also a strategic advisor to the Mayor of a middle-sized Italian city.

To purchase reprints of this article please e-mail: [email protected] Or visit our web site for further details: www.emeraldinsight.com/reprints

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An integrated decision support model for a knowledge city’s strategy formulation Kostas Ergazakis, Kostas Metaxiotis, John Psarras and Dimitrios Askounis

Abstract Purpose – The concept of knowledge cities (KCs) offers advantages to any urban region. Many cities globally claim themselves as being already KCs, while other cities have elaborated strategic plans in order to integrate this concept into their operational structures. The examination of their approaches reveals however that these initiatives are fragmented. The purpose of this paper is to present a multi-dimensional and integrated decision support model for a KC’s strategy formulation. Design/methodology/approach – Reference is made to a methodological approach (KnowCis) for the integrated development of a KC, consisting of five main phases and taking into account nine different dimensions. The strategy formulation phase is a particularly complex procedure for any authority (e.g. local government or city’s development agency). The reasons for this complexity are related to the amplitude of the KC concept, to the variety of the factors to be considered as well as to the challenge for balancing the needs and interests of different target groups. Kostas Ergazakis, School of Electrical and Computer Engineering, National Technical University of Athens (NTUA), Greece. Kostas Metaxiotis, Greek Ministry of Economy and Finance, Athens, Greece. John Psarras, School of Electrical and Computer Engineering, National Technical University of Athens (NTUA), Greece. Dimitris Askounis, School of Electrical and Comuter Engineering, National Technical University of Athens (NTUA), Greece.

Findings – The proposed model consists of the following building blocks: identification of the appropriate actions (based on the KnowCis methodology), modeling of the city’s current status as a KC (via the development of related indicators), assessment of actions’ necessity (based on the indicators’ outcomes and through the benchmarking of other successful KCs cases), selection of the most appropriate form for each proposed action (based on their efficiency during the last reference period) and, finally, prioritisation of the proposed actions (based on a multi-criteria approach). Research limitations/implications – The main suggestion for future research is the development of an intelligent information system which will incorporate the building blocks of the proposed model. Originality/value – The originality and value of the paper is that the proposed model can be a really helpful decision support tool for any city which is developing a knowledge-based strategy. Keywords Decision making, Emergent strategy, Knowledge management, Cities, Citizens Paper type Research paper

Introduction According to Carrillo (2006a): ‘‘few aspects of today’s world may characterize better the dawn of the new millennium than the transformation of regions into knowledge societies’’. Carrillo also underlines the fact that major international organisations (EU, World Bank, UN) have all stressed the critical importance of the knowledge economy as a global reality established over the turn of the century. In this context, the concept knowledge cities (KCs) came recently to the front. It is a subfield of knowledge-based development (KBD) and ‘‘it constitutes one of the most complex phenomena ever faced by mankind and probably a critical one for its future evolution’’ (Carrillo, 2006a). There are various definitions of what a KC is and of its main characteristics and advantages (Ergazakis et al., 2004, 2006a, b; Carrillo, 2004, 2006b; Chatzkel, 2006). Many cities have undertaken considerable efforts and initiatives so as to be developed or to enhance their status as a KC. However, their approaches were rather ad hoc, spontaneous and not based on a pre-defined method (see Ergazakis et al., 2004, 2006a, c). The field still

DOI 10.1108/13673270710819816

VOL. 11 NO. 5 2007, pp. 65-86, Q Emerald Group Publishing Limited, ISSN 1367-3270

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‘‘ Many cities have undertaken considerable efforts and initiatives so as to be developed or to enhance their status as a knowledge city. ’’

lacks a consensus regarding appropriate conceptual and methodological frameworks (Carrillo, 2006b). This is the reason why the related research has begun to concentrate on the direction to substantiate the fundamental principles of KCs and to define unified methods for their design, development and operation. Under this prism, the authors have recently introduced a method, called ‘‘KnowCis’’ (Ergazakis et al., 2006c). The method consists of five main phases and takes into account nine different dimensions, so as to reflect the variety of social, economic and cultural life in a city (Ergazakis et al., 2004). This paper focuses on the second phase of KnowCis, i.e. the strategy formulation, which is a particularly complex procedure. The reasons for this complexity are related to the amplitude of the KC concept and to the factors that should be considered when a development strategy for any city is being formulated. The main aim of this paper is to present a multi-dimensional and integrated decision-making model so as to assist the authorities charged with the duty to develop a KC’s strategy. Next section briefly presents the KnowCis method and the need for a decision support model. The following section analyzes the model’s main building blocks, while the other section provides information on its pilot application to a Greek municipality. The final section is devoted to presenting some main conclusions and future research challenges.

The KnowCis method and the need for a decision support model The KnowCis (Knowledge Cities) method was developed by the authors, in 2005 (Figure 1). It is the outcome of a multi-annual research on the fields of knowledge-management (KM), knowledge-based development (KBD) and knowledge cities. The first priority of the method is the setting-up of a committee (knowledge city committee – KCC) which is co-responsible, along with the city’s local government, for the consultation and co-ordination of the whole effort, from its very beginning. Government representatives, and representatives of citizens, enterprises and cultural organizations can equally participate in the KCC. The method consists of five main phases: 1. Phase 1: Diagnosis. Before any attempt to outline a strategy, the KCC proceeds to a thorough diagnosis of the current city’s status as a KC, based on studies, opinion polls and qualitative evaluations. 2. Phase 2: Formulation of strategy. The diagnosis of the previous phase is important for the formulation of strategy that will be adopted. This strategy considers nine dimensions comprising sets of particular actions. The specific characteristics, the particularities, strengths and weaknesses of the city determine which actions and interventions are needed as well as the priority of each one. Their implementation contributes to the attainment of various objectives which are substantial for the success of a KBD effort (Ergazakis et al., 2006b). 3. Phase 3: Creation of detailed action plan. This phase is devoted to the creation of a detailed action plan for realising the defined strategy. The action plan comprises specific projects to be implemented (project-oriented approach) as well as interventions to specific processes that need improvement (process oriented approach). Each project or intervention is thoroughly selected, designed and prepared. They incorporate, by design, a component related to continuous sharing of knowledge. Obviously, the appropriate financing must have been reassured.

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Figure 1 The KnowCis methodology

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4. Phase 4: Implementation. The KCC, the agencies and stakeholders participating in it, the local government, and other public or private organisations and companies are implementing the defined actions, measures and projects. In this way, each stakeholder remains committed and contributes to the effort. 5. Phase 5: Measurement/evaluation. It is indispensable to measure the progress of the whole effort and evaluate the performance of the city as a KC, based on indicators and the consultation of evaluation experts. Horizontal aspects are also considered in the method, i.e. the open and equal participation of all citizens and stakeholders, the political and societal leadership/commitment and the KM procedures related to the effort. For further details on the method see Ergazakis et al., 2006c. It should be noted at this point that, in general, the following factors are important and affect the process of formulating development strategies for any city: B

Availability of resources that can be allocated for the implementation of the strategy.

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Main results achieved in the past and the efficiency of particular actions and measures.

B

Existence of time limits which may affect the strategy formulation process.

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Expectations of various actors in the city, whose interests and needs may differ.

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Particular characteristics of the city or special circumstances.

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Threats and opportunities deriving from the international environment.

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General socio-economical context of the country.

Figure 2 presents these factors. Moreover, as it is proposed by many researchers in the literature (Carrillo, 2002, 2004, 2006a, b; Chatzkel, 2006; Dvir and Pasher, 2004; Ergazakis et al., 2004, 2006a, b, c, d, e; Garcia, 2004; Gonzalez et al., 2004; Malone and Yohe, 2002; Martinez, 2006; Montreal Knowledge City Advisory Committee, 2003; Palacios and Galvan, 2006; Ploeger, 2001; Raza et al., 2006; Rodriguez and Viedma, 2006), a successful KC should take under consideration Figure 2 Main factors influencing the strategy formulation process for any city

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many different aspects of social, economic and cultural life in the city, in order to achieve desired strategic objectives in the context of the knowledge economy. Thus, phase 2 of KnowCis (formulation of strategy) is the most complex and critical for the success of the whole effort and it incorporates nine different dimensions and 25 actions. In this way, it is understood that any authority (local government, city’s development agencies, public institutions etc.) which is charged with the duty to select the appropriate strategic interventions for a KC, should consider a wide variety of factors, as referred to the last two paragraphs. Consequently the task of selecting and prioritising the needed interventions and actions is becoming a multi-parameter and complex procedure. Thus, a decision support model which could assist the decision makers in the above procedure would be really useful. The main objective of this paper is to present such an approach which, in combination with KnowCis, constitutes an integrated decision support model for a KC’s strategy formulation.

The decision support model The proposed model (depicted in Figure 3) consists of five main building blocks. Building block 1. Identification This building block concerns the identification, based on the international experience regarding KCs and other KBD strategies and approaches, of 25 actions (Aij), belonging to the nine dimensions (Di) (i ¼ 1,2 . . . 9). The actions are illustrated in Table I. At this point, the ‘‘history’’ of identification of these dimensions, actions, and of the author’s prior research in the fields of KM, KBD and KCs should be shortly referred: The first basic step was the substantiation of a KC model, the foundation of KCs’ basic characteristics, benefits and key success factors as well as the exploration of the concept’s relation with KM and KBD strategies. For this purpose, a thorough review of published reports, papers, books and web-sites has taken place (Ergazakis et al., 2004), including a review of contemporary knowledge-based development strategies. This review resulted in a set of five main challenges that these strategies should address, namely: increase of knowledge intensity in the region; democratization of KM processes and increased citizen’s participation; reinforcement of the business environment; replacement of ‘‘digital divide’’ with ‘‘digital inclustion’’; sustainable urban development. It has been concluded that the concept of KCs, being a sub-field of KBD, is particularly appropriate and advantageous because it has the necessary potential so as to comply with and satisfy these challenges (Ergazakis et al., 2006b). The next step was the thorough examination of city’s cases that successfully embraced KBD strategies so as to be developed as KCs. The main conclusion was that their initiatives were not unified and their decision-making processes regarding the strategy formulation were deficient and incomplete. Nevertheless, even though the approaches had conceptual differences, common characteristics could be found. The authors drew a pattern of recurrence of these significant features and their key findings were expressed as hypotheses for designing, developing and operating successful KCs. The majority of these hypotheses were fully supported by the examined case studies. Consequently, they have been incorporated, at a satisfactory level of trust, to a framework for successful KCs (Ergazakis et al., 2006d). This framework, the experience accumulated from the thorough study of ten (10) KCs case studies, as well as the review of KBD strategies and approaches, has been the scientific basis for defining the dimensions and actions which were incorporated to the KnowCis method, of the related indicators and their thresholds (Figure 4). During the strategy formulation process, a KC has to choose on which of the available actions the strategy will be focused, under which form (e.g. continuation of specific projects and improvement of processes) and in which order.

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Figure 3 The proposed integrated model for a KC’s strategy formulation

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Table I The dimensions and actions D1: KM processes with the city Introduction of KM practices in local administration’s processes A1.1 Creation of formal and informal networks for knowledge sharing A1.2 Provision of incentives for knowledge sharing A1.3 Reinforcement of public libraries’ network A1.4 D2: City’s ICT infrastructure and citizens’ ICT literacy level Creation of high quality telecommunication network A2.1 Assurance of low-cost access to broadband connectivity A2.2 Improvement of citizens’ ICT literacy level A2.3 Creation/improvement of metropolitan web site A2.4 D3: Knowledge society citizens’ rights Definition and reassurance of knowledge society rights (accessibility, information, A3.1 education and training, participation) for all citizens A3.2 Creation of necessary conditions so as the citizens make use of these rights D4: Research, business innovation and entrepreneurship Improvement of city’s performance in knowledge-intensive sectors A4.1 Provision of incentives to companies for innovation A4.2 Support of entrepreneurship and promotion of new ideas A4.3 Support of research/efficient promotion of research results throughout the city’s knowledge A4.4 agents D5: Challenge that KM poses to the public sector Continuous review of the international environment, for the latest developments concerning A5.1 the services that modern cities offer Adaptation and integration of best practices to the policies, processes and services offered A5.2 by the city D6: Networking and synergies among all city’s actors/with other KCs Reinforcement of networking and interactions among all actors in the city A6.1 Establishment of links and partnership with other KCs A6.2 D7: Availability and skill level of human capital Attraction and retention of high-level human capital A7.1 Improvement of existing human capital’s skill level A7.2 D8: Inclusive, international and multi-ethnic character of the city Improvement of immigrants’ and minorities’ living conditions A8.1 Enhancement and reinforcement of the cultural, recreational and sporting activities taking A8.2 place in the city and therefore of the city’s visitors Reinforcement of all the social groups’ participation in the public affairs A8.3 D9: KC concept’s publicity and visibility Creation of a special organisation responsible for the improvement of KC concept’s visibility A9.1 throughout the city Continuous promotion/publicity of achieved/envisaged results A9.2

Building block 2. Modelling This building block concerns the modelling of the available actions and interventions that a KC can select so as to formulate its strategy, via the development of appropriate decision indicators. The identification of the indicators, as well as of their thresholds, was based to the review of KBD strategies and of other KCs case studies. Moreover, an exhaustive review of literature regarding intellectual capital (IC) measurement methodologies and techniques has been accomplished (e.g. Aubert, 2005; Bontis, 2004; Bounfour, 2005; Cinca et al., 2003; Edvinsson and Malone, 1997; Edvinsson and Stenfelt, 1999; Florida, 2002; Furman et al., 2002; MERITUM, 2002; Oliver and Porta, 2006; Porter, 1998; Poyhonen and Smedlund, 2004; Roos, 1996; Sveiby, 1997, 2000, 2001; Viedma, 1999, 2002, 2003; World Bank, 1999, 2001; Wu and Hus, 2005). The decision indicators are categorized as follows:

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Figure 4 The identification of dimensions, actions and indicators

B

25 main indicators, one for each Action: Mij, i ¼ 1,2 . . . 9 and j ¼ 1, . . . x (1) where: Mij: The main indicator describing the corresponding action Aij; i: The number of dimension j: The number of the action and its corresponding main indicator in the examined dimension x: The quantity of main indicators in the examined dimension These indicators represent the most essential information and knowledge regarding the diagnosis of the current status of the city as a KC, based on the defined dimensions. The main indicator is the key means of decision making regarding the necessity of each action.

B

97 secondary indicators: Sijk, i ¼ 1,. . .9, j ¼ 1,. . .x, k ¼ 1,. . .y (2) where: Sijk: The secondary indicator describing the corresponding action Aij. i: The number of dimension j: The number of the action in the examined dimension k: The number of the secondary indicator used for the examination of the action Aij x: The quantity of main indicators in the examined dimension y: The quantity of secondary indicators used for the examination of the action Aij These indicators represent additional and further information and knowledge regarding the status of each dimension, and are also examined during the diagnosis. They are also used by the model for estimating the necessity of each action.

It should be noted that these indicators are either measurable (M, with specific measurable unit) or qualitative (Q). In the latter case, their values are defined through the following scale: 5: Very good performance; 4: Good performance; 3: Slightly good performance; 2: Inadequate performance. 1: Bad performance.

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The main and secondary decision indicators for each dimension, as well as their type (Q or M), are presented in Tables II and III. Building block 3. Assessment This building block concerns the assessment of the necessity for each action Aij. This is done through the value control of the decision indicators, as identified on the previous building block. For this purpose, the input from the phase 1 of the KnowCis is needed: the KCC (or any other entity responsible for the formulation of strategy), conducts a series of studies, opinion polls, qualitative assessments and debates, so as to measure and estimate the values of each one of the decision indicators. As it has been stressed (Ergazakis et al., 2006c), it is absolutely necessary that in this process equally participate representatives of Table II The main indicators D1: KM processes with the city Degree of KM practices’ incorporation in local administration processes M1.1 Degree of networking among companies, organisations and other important M1.2 knowledge agents in the city (e.g. universities, research centres) Number of measures and actions for provision of incentives for knowledge M1.3 sharing M1.4 Number of networked public libraries operating in the city

Q Q M M

D2: City’s ICT infrastructure and citizens’ ICT literacy level Status of city’s telecommunication’ network (connectivity, availability of M2.1 connections of ADSL, Wi-Fi, WiMAX, etc.) M2.2 Mean cost of access to broadband connectivity (eMbps) Citizens’ ICT literacy level M2.3 Status of present metropolitan web site M2.4

Q M Q Q

D3: Knowledge society citizens’ rights Number of initiatives for the reassurance of citizens’ rights in a knowledge society M3.1 Number of actions and measures encouraging citizens to make use of their rights M3.2 in the knowledge society

M M

D4: Research business innovation and entrepreneurship Share of knowledge-intensive sectors in the city’s annual turnover (%) M4.1 Number of programmes, actions and measures supporting innovation M4.2 Number of programmes, actions and measures supporting entrepreneurship M4.3 Rate of city’s budget allocated to research activities (%) M4.4

M M M M

D5: Challenges that KM poses to the public sector Rate of city’s allocated budget for the review of the international environment (%) M5.1 Degree of best practices’ integration to the policies followed and the services M5.2 offered by the city

M Q

D6: Networking and synergies among all city’s actors/with other KCs Degree of networking and interactions among all actors in the city M6.1 Status of links and partnerships with other KCs M6.2

Q Q

D7: Availability and skill level of human capital Number of initiatives designed so as to attract high-level human capital M7.1 Rate of highly educated (at least university level) human capital (%) M7.2

M M

D8: Inclusive, international and multi-ethnic character of the city Degree of immigrants’ and minorities’ satisfaction from their life in the city M8.1 Number of cultural, recreational and sporting activities taking place in the city M8.2 Degree of citizens’ participation and interest for the public life and affairs in their M8.3 city

Q M Q

D9: KC concept’s publicity and visibility Degree of KC concept’s visibility to the public M9.1 Effectiveness of publicity campaign/promotional activities M9.2

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Table III The secondary indicators D1: KM processes within the city M1.1 S1.1.1: Percentage of local administration’s processes designed or created so as to incorporate KM practices (%) S1.1.2: Degree of familiarisation, acceptance and use of KM practices on the part of employees in municipal organisations/companies M1.2 S1.2.1: Degree and amplitude of knowledge sharing in the city S1.2.2: Estimation of the number of communities of practice in the city S1.2.3: Quality and thoroughness of available knowledge and information in the metropolitan web site S1.2.4: Regular dispatching of city’s e-newsletter to interested citizens S1.2.5: Availability of all data, information and knowledge concerning city’s government and administration, through the metropolitan web site S1.2.6: Number of other cities’ web pages and portals providing access to important information and knowledge concerning the city M1.3 S1.3.1: Rate of total city’s budget allocated to the provision of incentives for knowledge sharing (%) S1.3.2: Degree of acceptance and use of the above-mentioned incentives on the part of important city’s knowledge agents (universities, research centres, companies) M1.4 S1.4.1: Available book titles per person (book titles/1,000 persons) S1.4.2: Quality of e-services provided by public libraries S1.4.3: Rate of libraries’ members using the above-mentioned e-services (%) D2: City’s ICT infrastructure and citizens’ ICT literacy level M2.1 S2.1.1: Number of companies providing telecommunication services S2.1.2: Number of companies owing private telecommunication networks S2.1.3: Provision of modern telecommunication services (e.g. triple play) M2.2 S2.2.1: Rate of broadband connections in relation to the total internet connections (%) S2.2.2: Rate of citizens using the internet on a daily basis (%) S2.2.3: Rate of schools with internet access (%) S2.2.4: Rate of companies using the internet on a daily basis in their professional activites (%) M2.3 S2.3.1: Rate of households owning a PC (%) S2.3.2: Number of PCs per school student (PCs/school student) S2.3.3: Status of education and training activities in relation to ICTs S2.3.4: Degree of use of available e-services by citizens and companies (through the metropolitan web site) S2.3.5: Availability and degree of use of e-learning services M2.4 S2.4.1: Amplitude and variety of available knowledge and information on the metropolitan web site S2.4.2: Number of available e-services through the metropolitan web site S2.4.3: Quality and degree of integration of available e-services S2.4.4: Integration degree of various information systems used in the city’s administration S2.4.5: Regular dispatching of city’s e-newsletter to interested citizens

M Q Q M Q Q Q M M Q M Q M M M Q M M M M M M Q Q Q Q M Q Q Q

D3: Knowledge society citizens’ rights M3.1 S3.1.1: Transparency degree of local administration S3.1.2: Existence of laws/regulations related to intellectual property issues and degree of their application/support on the part of local administration S3.1.3: Number of processes/structures allowing citizens to take part in decision-making processes for their city M3.2 S3.2.1: Degree of use of available e-services on the part of citizens and companies (through the metropolitan web site) S3.2.2: Rate of citizens taking part (directly or indirectly) in the Knowledge City Committee and the implementation of strategy (%) S3.2.3: Existence of structure for the acceptance of complaints/remarks from citizens and degree of its use S3.2.4: Freedom of press and mass media D4: Research, business innovation and entrepreneurship M4.1 S4.1.1: Rate of companies belonging to knowledge intensive sectors (%) S4.1.2: Rate of labour force employed in knowledge intensive sectors (%) M4.2 S4.2.1: Number of patents per person (patents/1 million citizens) S4.2.2: Number of actions for provision of incentives to innovative companies to be settled in the city S4.2.3: Investments to knowledge and high-tech sectors, deriving from venture capitals (me) S4.2.4: Rate of ICT sector’s turnover to the total GDP of the city (%) M4.3 S4.3.1: Number of new companies’ start-ups per citizen (companies’ start up/1,000 citizens) S4.3.2: Rate of companies belonging to knowledge intensive sectors (%) S4.3.3: Mean unemployment rate per sex, age and education level (%) S4.3.4: Degree of transformation of new/innovative ideas to business plans and new products/services S4.3.5: Rate of city’s inhabitants employed in the city’s companies (%) M4.3 S4.3.6: Provision of information and knowledge through the metropolitan web site, for business opportunities, access to capital and loans, etc. S4.3.7: Degree of ‘‘bureaucracy’’ for the start-up of a new company

Q Q M Q M Q Q M M M M M M M M M Q M Q Q

(Continued)

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Table III M4.4

S4.4.1: S4.4.2: S4.4.3: S4.4.4: S4.4.5:

Number of research centres/institutes operating in the city Quality of research results Degree of diffusion/sharing of research results to the city’s companies Rate of city’s companies with a R&D department (%) Number of scientific publications (publications/1 million citizens)

M Q Q M M

D5: Challenges that KM poses to the public sector M5.1 S5.1.1: Rate of local administrations’ employees charged with the review of the international environment (%) S5.1.2: Capability of local administration to ‘‘preserve’’ and ‘‘maintain’’ its experienced staff S5.2.1: Number of improvements to the services offered by the city, due to knowledge acquired by the review of the international environment S5.2.2: Mean cost of adaptation/creation of new services (e/service) S5.2.3: Degree of citizens’ satisfaction with the services offered by the city

M Q M M Q

D6: Networking and synergies among all city’s actors/with other KCs M6.1 S6.1.1: Number of formal networks of co-operation and joint work S6.1.2: Number of workshops, seminars and special events related to the opportunities offered by the city, collaboration and co-operation possibilities etc. M6.2 S6.2.1: Number of collaborations and initiatives commonly organised with other cities S6.2.2: Hi-tech and knowledge intensive exports as a rate of the total city’s exports (%) S6.2.3: Rate of key capital cities accessible by direct flights (%) S6.2.4: Rate of city’s students studying in universities of other cities (%)

M M M M M M

D7: Availability and skill level of human capital M7.1 S7.1.1: Rate of immigrants with university level education (%) S7.1.2: Amplitude and quality of information and knowledge in relation to history, culture, arts, etc. offered through the metropolitan web site S7.1.3: Number of foreign languages into which the metropolitan web site translated S7.1.4: Rate of citizens speaking at least one foreign language (%) M7.2 S7.2.1: Average household spending on education as a percentage of household income (%) S7.2.2: Number of actions/measures for the improvement/adaptation of educational and training services offered by the city S7.2.3: Rate of citizens participating in life-long learning activities (%)

M Q M M M M M

D8: Inclusive, international and multi-ethnic character of the city M8.1 S8.1.1: Number of measures and actions addressed to immigrants and citizens with different cultural background S8.2.1: Rate of immigrants’ and minorities’ participation in cultural, recreational etc. activities (%) M8.2 S8.2.1: Effective mareketing/promotion of cultural, recreational, etc. activities S8.2.2: Rate of citizens’ participation to cultural, recreational, etc. activites (%) S8.2.3: Mean cost of participation per activity (e/activity) S8.2.4: Average household spending on recreation and leisure activities as a percentage of household income (%) S8.2.5: Rate of city’s visitors per year who intend to take part in cultural, etc. activities (%) S8.2.6: Rate of labour force occupied in creative sectors (arts, design, architecture, etc.) (%) S8.2.7: Amplitude and quality of information and knowledge in relation to history, culture, arts etc., offered through the metropolitan web site M8.3 S8.3.1: Number of processes/structures allowing citizens to take part in decision-making processes for their city S8.3.2: Rate of citizens participating in the above-mentioned structures/processes (%) S8.3.3: Degree of use of available services and public spaces offered by the city S8.3.4: Citizens’ degree of satisfaction with the local administration of their city S8.3.5: Availability of all data, information and knowledge concerning city’s government and administration, through the metropolitan web site

M M M M M M M M Q M M Q Q Q

D9: KC concept’s publicity and visibility M9.1 S9.1.1: Rate of citizens being aware of their city’s initiative S9.1.2: Rate of companies and organisations being aware of their city’sn initiative S9.1.3: Number of workshops/conferences organised for the promotion of the initiative S9.1.4: Number of internet discussion forums related to the initiative S9.1.5: Rate of citizens taking part (directly or indirectly) in the Knowledge City Committee and the implementation of strategy (%) M9.2 S9.2.1: Number of activities and special events organised for the promotion of achieved/envisaged results S9.2.2: Rate of citizens who participated in the promotional events (%) S9.2.3: Number of informative brochures distributed to citizens and companies S9.2.4: Number of TV broadcasts/articles in local mass media, related to the initiative S9.2.5: Number of TV spots/commercials in mass media

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all possible actors and stakeholders in the city (from the part of citizens, companies, education sector, culture, etc.). Moreover, the use of web questionnaires, electronic discussion forums and e-voting services can significantly help. The process in this building block, as it is depicted in Figure 3, is based on the control of indicator’s values: B

Value control of main indicators Mij. The process starts with the value control of each indicator Mij, in relation to the threshold value, deriving from the ‘‘experience’’ (i.e. other KCs case studies, benchmarking, etc.). In case of significant deviation between the desired and actual indicator’s value, the model suggests the need for the corresponding action Aij. In smaller deviations, the model continues with the control of secondary indicators.

B

Value control of secondary indicators Sijk. The value of each secondary indicator which is affiliated to the corresponding action Aij, is compared to the threshold value. Even a small deviation results to the necessity for the action. On the contrary, the convergence of real values with the thresholds values, has as output the definitive non-choice of the action, given that all its affiliated indicators (main and secondary) are within their desired values.

Building block 4. Actions’ form After the assessment of each action’s necessity, the model focuses on the historic evolution of the main and secondary indicators as well as on the projects/processes related to the actions during the last year (action plan, phases 3 and 5 of KnowCis). The choices that the model can propose for the form of each action are: 1. Continuation/preservation of existing projects/processes. 2. Design and implementation of new projects/processes. 3. Modification/re-engineering of existing projects/processes. The process of selection of the most appropriate form is the following: B

Concerning the measurable indicators, the Evolution indicators EMij and ESijk are used. They are based on the evolution of the main and secondary indicators: EM ij ¼

M year_n ij M year_n21 ij

21

ð3Þ

21

ð4Þ

and ES ijk ¼

S year_n ijk S year_n21 ijk

where: EMij and ESijk: the evolution indicators i: The number of dimension j: the number of the action and its corresponding main indicator in the examined dimension k: the number of the secondary indicator used for the examination of the action Aij M year_n : the value of the main indicator for the present year (n) ij : the value of the main indicator for the previous year (n2 1) M year_n21 ij S year_n : the value of the secondary indicator for the present year (n) ijk year_n21 S ijk : the value of the secondary indicator for the previous year (n 2 1). Based on the value control of the evolution indicator in relation to its threshold value (which is defined using the ‘‘experience’’ but also the preferences of the decision maker) and on the existence of specific projects or processes for the particular action, the model proposes the most appropriate form for the action. B

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Concerning the qualitative indicators, the model does not use the equation (3), but assesses their evolution using appropriate thresholds.

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Building block 5. Prioritisation The last building block receives input from the previous building blocks, i.e. the group of necessary actions, so as to evaluate them and create a priority list. This evaluation is based on the quantification of multiple qualitative judgements, based on a multi-criteria decision making (MCDM) method, the ELECTRE III. Reader can refer to the Appendix for a short presentation of the main mathematical equations of which the ELECTREE III is constituted (Maystre et al., 1994; Rogers et al., 2000). Multi-criteria analysis has been used in order to select from multi-attribute discrete options, which is the case for our problem. Both in scientific literature and in real life, there are many controversies about the most appropriate MCDM method (Jacquet-Lagreze and Siskos, 2001). The selection of a method for a specific multi-criteria problem is a complex procedure which depends on the problem type, the quantity and quality of knowledge related to the problem as well as the number of decision makers. Methods based on the utility function (such as the multi-attribute value function and the analytic hierarchy process) require particularly detailed information from the part of the decision maker. The mathematic representation and comparison through the utility function, does not offer the possibility for non-comparison between alternatives, which is a common phenomenon in real life. On the other side, methods based on the outranking relation (such as the PROMETHEE and ELECTRE family) have the characteristic that they require less information from the part of the decision maker. The binary approach (concordance-discordance) is a basic advantage in comparison to other methods. They also permit the non-comparison between alternatives. In this way, the decision maker can express its hesitation about some alternatives. The PROMETHEE methods have the characteristic of choosing the criterion functions between six types (Brans et al., 1986), something that limits the criteria selection, on a problem such as the one that this paper addresses. For these reasons, the authors have chosen to use the ELECTRE III method. The first step is the definition of the criteria that will be used for the prioritisation of the actions. For this purpose, the main outcomes of author’s prior research concerning main challenges that contemporary KBD strategies should respond to (Ergazakis et al., 2006b), have been considered. An unquestionable need is also to increase the knowledge intensity in a region, which has as strategic objective to be developed as a KC (Montreal Knowledge City Advisory Committee, 2003, pp. 18-19). Table IV presents these criteria. The next step is the definition of decision maker’s preferences, through the introduction of weights for each criterion. There are various methods for the weights’ definition: Hokkanen and Salminen, 1994; Figueira and Roy, 2002 (Simos’ method); Rogers et al., 2000 (personal construct theory – PCT); Mousseau (1993). In our case, the PCT method has been chosen, which is relatively simple and easily understood to all the implicated parties in the decision making process. Moreover, the decision maker defines the thresholds of indifference, (q), preference (p), and veto (v). The values q, p and v are subjective and express the preferences of the decision maker. The decision maker must also define the values g(a) which reflect the value that is attributed to an action, for each criterion. The possible values are: 5: Very high effect; 4: High effect; 3: Slightly high effect; 2: Low effect; 1: Very low effect; 0: No effect.This means that an action can have a particular effect, to any of the criteria. However, each dimension (and their respective actions) contributes mainly to some of the criteria (Ergazakis et al., 2006c). The main contribution of each dimension to one or more criteria is illustrated in Figure 5. The final step concerns the prioritisation of proposed actions, based on the data provided by the decision maker and to the standard mathematical equations used in the ELECTRE III method.

The model’s application on a Greek municipality The Greek municipality of Maroussi, located in the north suburbs of Athens, has already been engaged in a KBD effort, adopting the KnowCis method. It should be noted that due to important restrictions regarding available resources, it was impossible to fully implement the KnowCis method. The reader could refer to Ergazakis et al., 2006e for further details. At the

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Table IV The criteria Increase of knowledge intensity C1. Degree of knowledge production

C2. Pace of assimilation and use of new knowledge

C3. Scope of knowledge circulation

Respond to KBD challenges C4. Democratisation of KM processes/increased citizens’ participation

C5. Digital divide replacement by digital inclusion

C6. Reinforcement of business environment

This criterion evaluates the degree in which the proposed action contributes to the degree of dynamics of knowledge produced in the city as well as to the strong flow of this knowledge which is, in turn, conducive to various types of innovation This criterion evaluates the degree in which the proposed action contributes to the pace of assimilation and use of new knowledge, that is to say to the city’s ability to consistently reap benefits of new knowledge and new expertise This criterion evaluates the degree in which the proposed action contributes to the scope of knowledge circulation in the city, that is to say to the amount dissemination and sharing of knowledge (whether among the individuals or organisations, across industry segments or geographical regions), which is another benchmark for quality in a KC

This criterion evaluates the degree in which the proposed action contributes to the democratisation of processes through which knowledge is created, stored, shared and used and consequently to the increase of broad citizen’s participation in these KM processes This criterion evaluates the degree in which the proposed action contributes to the replacement of digital divide by digital inclusion, as well as to the availability and flow of the new ICTs’ benefits to all citizens This criterion evaluates the degree in which the action contributes to the creation and formation of an appropriate business environment, which fosters innovation and favours the acquisition and dissemination of knowledge and learning, and consequently is necessary for companies to survive, in the context of the knowledge-based economy

present stage, the detailed action plan has been almost finalised, taking into consideration the priority of the actions to be implemented. In what follows, the basic conclusions from the first two phases of the method and especially regarding the simulation that took place by using the developed decision support model, are presented Phase 1: diagnosis of present situation In the qualitative diagnosis of the municipality’s current situation, executives of local administration as well as certain representatives of citizens, enterprises and cultural organizations (working group) have participated. The basis for this diagnosis was each dimension of the KnowCis method. Many of the included indicators acted as catalyst for a series of discussions and debates. For each dimension, basic advantages and disadvantages of the municipality have been identified, with regards to its capacity to meet the requirements deriving from it. Phase 2: formulation of strategy As stated above, due to some important restrictions, it was impossible to carry out analytical measurement of all the indicators included in KnowCis. Thus, the next stage of the pilot

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Figure 5 The main contribution of each dimension to the criteria

application was the selection and the prioritization, from the part of the working group, of the actions (among the ones existing in KnowCis) considering them necessary for the municipality. This process was realized exclusively by this working group, without any external influences and it was based on the former diagnosis, on available data from existing polls and studies, on qualitative criteria, on the experience of the participants and finally on their in-depth knowledge regarding the characteristics, the needs and the prospects of their Municipality. Out of 25 actions, 22 were selected. They are presented in Figure 6. The next stage of the pilot application was the simulation through the developed decision support model. For this purpose, the following actions took place: B

All the available data from studies, polls and other measurements were collected and used so as to calculate the values for some main and secondary indicators.

B

For the remaining indicators it was impossible, in the framework of the particular research, to conduct new polls, measurements and studies. For this reason, a qualitative determination of their values, based on the experience of municipality’s executives and representatives, took place.

B

The threshold values of preference, indifference and veto were determined as well as the value of each action for the used criteria, so as to reflect the preferences of the working group.

The above data were supplied to the proposed decision support model. Its output was the proposal of 23 necessary actions, prioritized as depicted in Figure 7. Comparison with the corresponding results resulted based on the experience (Figure 8) shows that:

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Figure 6 Actions’ selection and classification based on the experience of the working group

1. The number of proposed actions is almost the same (23 using the decision support model, 22 based on the experience). 2. The differentiations in the final priority lists are:

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Two (2) actions (9.09 percent) are in the same order of prioritization.

B

Ten (10) actions (45.45 percent) differ one (1) place in the final prioritization.

B

Six (6) actions (27.27 percent) differ two (2) places in the final prioritization.

B

Three (3) actions (13.64) differ three (3) places in the final prioritization.

B

One (1) action (4.55 percent) differs seven (7) places in the final prioritization.

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Figure 7 Actions’ selection and classification based on the decision support model

The main conclusion is that the variations between the two methods are not important. Of course, in order for this conclusion to be verified with absolute confidence, it is obligatory to precise accurately the values for all the indicators.

Conclusions and future research challenges The concept of a KC and the advantages that can offer on a global and local scale are important, so as to be ignored by the policy makers (Ergazakis et al., 2006a). In this respect and given that the research on the field is still on embryonic phase, the need to identify and

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Figure 8 Differentiations in actions’ final priority lists

propose integrated and unified methodologies for the development and formulation of related strategies, is realistic. The authors, based on a recently developed method (KnowCis), proposed a decision support model for the formulation of KC’s strategy. The model consists of the following building blocks: identification of the appropriate actions (based on KnowCis), modelling of the city’s current status as a KC (via the development of related indicators), assessment of the necessity for the actions (based on the indicators’ outcomes and through the benchmarking of other successful KCs cases), selection of the most appropriate form of each proposed action (based on their efficiency during the last reference period) and, finally, prioritisation of the proposed actions (based on a multi-criteria approach). The model has the following advantages: B

Integrated. Combined with the KnowCis method, it constitutes an integrated tool that can be used by a city or urban region with the vision to develop a knowledge-based strategy.

B

Flexible. The model is easily adaptable so as to incorporate and reflect the city’s specific strengths, weaknesses, opportunities and objectives. This can be achieved by the right selection of indicators and their thresholds, appropriate criteria and relative weights, and actions.

B

Encouraging preliminary results. As described in the last section, the preliminary results from the pilot application of the decision support model to a Greek municipality are encouraging, in the sense that variations between the two methods (based on experience and based on the model) are not important. Of course, as already stated, it is more than necessary to precise accurately the values for all the indicators, in order for this conclusion to be verified with absolute confidence.

Two major streams of future research are the following: 1. The development of an intelligent decision support system incorporating the building blocks of the proposed model. Such a system would help the decision maker to quickly implement the proposed model on this paper. Expert systems technology could offer a series of advantages for the design and development of such a system. 2. Further enhancement of KnowCis method so as to render it more relevant and realistic in regards to the variety of aspects on a real city: incorporation of additional dimensions, actions and indicators are simple examples of such enhancements.

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Furman, J.L., Porter, M.E. and Stern, S. (2002), ‘‘The determinants of national innovative capacity’’, Research Policy, Vol. 31 No. 6, pp. 899-933. Garcia, B. (2004), ‘‘Developing futures: a knowledge-based capital for Manchester’’, Journal of Knowledge Management, Vol. 8 No. 5, pp. 47-60. Gonza´lez Ovalle, M.R., Ma´rquez, J.A.A. and Salomo´n, S.D.M. (2004), ‘‘A compilation of resources on KCs and knowledge-based development’’, Journal of Knowledge Management, Vol. 8 No. 5, pp. 107-27. Hokkanen, J. and Salminen, P. (1994), ‘‘Choice of solid waste management system by using ELECTRE III method’’, in Paruccini, M. (Ed.), Applying Multicriteria Aid for Decision to Environmental Management, Kluwer Academic Publishers, Dordrecht. Jacquet-Lagreze, E. and Siskos, Y. (2001), ‘‘Preference disaggregation: 20 years of MCDA experience’’, European Journal of Operational Research, Vol. 130 No. 2, pp. 233-45. MERITUM (2002), Guidelines for Managing and Reporting on Intangibles (IC Report), Technical Report of the MERITUM EU-funded project, Airtel-Vodafone Foundation, Madrid. Malone, T.F. and Yohe, G.W. (2002), ‘‘Knowledge partnerships for a sustainable, equitable and stable society’’, Journal of Knowledge Management, Vol. 6 No. 4, pp. 368-78. Martı´nez, S.D. (2006), ‘‘A comparative framework for knowledge cities’’, in Carrillo, J. (Ed.), Knowledge Cities: Approaches, Experiences and Perspectives, Butterworth-Heinemann/Elsevier, Oxford, pp. 17-30. Maystre, L.Y., Pictet, J. and Simos, J. (1994), Me´thodes multicrite`res ELECTRE, Press Poly-techniques et Universitaires Romandes, Lausanne. Montre´al Knowledge City Advisory Committee (2003), Montre´al, Knowledge City, report prepared by the Montre´al, Knowledge City Advisory Committee, available at: www.montrealinternational.com/docs/ MtlSavoir_En.pdf Mousseau, V. (1993), ‘‘Proble`mes lie´s a` l’e´valuation de l’importance relative des crite`res en aide multicrite`re a` la de´cision: re´flexions the´oriques, expe´rimentations et imple´mentations informatiques!’’, PhD thesis, Universite´ Paris-Dauphine. Oliver, J.L.H. and Porta, J.I.D. (2006), ‘‘How to measure IC in clusters: empirical evidence’’, Journal of Intellectual Capital, Vol. 7 No. 3, pp. 354-80. Palacios, T.B. and Galvan, R.S. (2006), ‘‘Intellectual capital within Iberian municipalities (network)’’, Journal of Knowledge Cities, Vol. 10 No. 5, pp. 55-64. Ploeger, R. (2001), Innovation and New Entrepreneurship: A Cross National Survey of Policies in 13 European Cities, Amsterdam Study Centre for the Metropolitan Environment, Amsterdam, available at: www.ez.amsterdam.nl/eurocities/ Porter, M. (1998), ‘‘Clusters and the new economics of competition’’, Harvard Business Review, Vol. 76 No. 6, pp. 77-90. Poyhonen, A. and Smedlund, A. (2004), ‘‘Assessing intellectual capital creation in regional clusters’’, Journal of Intellectual Capital, Vol. 5 No. 3, pp. 351-65. Raza, A., Kausar, A.R. and Paul, D. (2006), ‘‘Culture, cognition and knowledge-based development’’, Journal of Knowledge Management, Vol. 10 No. 5, pp. 137-45. Rodriguez, B.M. and Viedma, J.M. (2006), ‘‘The region’s intellectual capital benchmarking system: enabling economic growth through evaluation’’, Journal of Knowledge Management, Vol. 10 No. 5, pp. 41-54. Rogers, M., Bruen, M. and Maystre, L. (2000), ELECTRE and Decision Support, Kluwer Academic Publishers, Dordrecht. Roos, J. (1996), ‘‘Intellectual capital – what you can measure you can manage’’, IMD Perspectives for Managers, Vol. 26 No. 10. Sveiby, K. (1997), The Invisible Balance Sheet: Key Indicators for Accounting, The Konrad Group, Stockholm. Sveiby, K. (2000), ‘‘Measuring intangible assets – an emerging standard’’, in Morey, D., Maybury, M. and Thuraisingham, B. (Eds), Knowledge Management – Classic and Contemporary Works, MIT Press, Cambridge, MA.

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Sveiby, K.E. (2001), ‘‘A knowledge-based theory of the firm to guide strategy formulation’’, Journal of Intellectual Capital, Vol. 2 No. 4, pp. 344-58. Viedma, J.M. (1999), ‘‘ICBS intellectual capital benchmarking system’’, paper presented at the 3rd World Congress on Intellectual Capital, McMaster University, Hamilton. Viedma, J.M. (2002), ‘‘SCBS social capital benchmarking system’’, paper presented at the 5th World Congress on Intellectual Capital, McMaster University, Hamilton. Viedma, J.M. (2003), ‘‘CICBS: cities’ international capital benchmarking system: a methodology and a framework for measuring and managing intellectual capital of cities: a practical application in the city of Mataro’’, presented at the 6th World Congress on Intellectual Capital, McMaster University, Hamilton, 15-17 January, available at: www.intellectualcapitalmanagementsystems.com World Bank (1999), Knowledge for Development, Oxford University Press, New York, NY. World Bank (2001), World Development Indicators, World Bank, Washington, DC. Wu, S. and Hus, M. (2005), Intellectual Capital for Communities in the Knowledge Economy, Technical Report, Taiwan Intellectual Capital Research Centre, Taipei City, Taiwan.

Further reading Edvinsson, L. (2006), ‘‘Aspects on the city as a knowledge tool’’, Journal of Knowledge Management, Vol. 10 No. 5, pp. 6-13.

Appendix: ELECTRE III multi-criteria decision making a and b represent two possible alternatives (actions in our case). g(a) represents the value that is attributed to an action, for each criterion. The following thresholds must be defined: B

Indifference (q) is the threshold below which the decision maker is indifferent as regards two alternatives.

B

Preference (p) is the threshold above which the decision maker strongly prefers one alternative over another.

B

Veto (v) is the threshold where a difference above which the decision maker must deny any advantage deriving from other criteria.

It is: B

apb (alternative a is preferred by b) ,g(a) . g(b) þ p

B

aqb (alternative a is preferred partially by b),q # g(a) – g(b) # p

B

aIb (alternative a is indifferent to b) ,jg(a) – g(b)j # q

Using thresholds, ELECTRE III creates a new relation S. The relation asb implies that the alternative a is at least as good as b or that a is not worse than b. There are two principles: B

a concordance principle which requires that a majority of criteria, after considering their relative importance, is in favor of the hypothesis – the majority principle; and

B

a non-discordance principle which requires that within the minority of criteria which do not support the hypothesis, none of them is strongly against the hypothesis – the respect of minorities’ principle.

In order to find if the hypothesis asb is true, a concordance matrix C(a,b) for each pair of alternative action is being calculated:

Cða; bÞ ¼

n 1X wt ct ða; bÞ w t¼1

where wt is the relative weight of criterion t, with w ¼

n X

wt .

t¼1

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Also:

ct ða; bÞ ¼

8 > > >
pt þgt ðaÞ2gt ðbÞ > > ; else : pt 2qj

The matrix of discordance for each criterion is also calculated, taking into consideration an additional threshold (veto) which allows the refusal of the hypothesis asb, for every criterion for which gt(b) . gt(a) þ vt is true. Thus, the matrix of discordance is calculated:

dt ða; bÞ ¼

8 > > >
gt ðbÞ 2 gt ðaÞ2pt > > : vt 2pt

if gt ðaÞ þ pt $ gt ðbÞ if gt ðaÞ þ vt # gt ðbÞ;

t ¼ 1; 2; . . .n

By combining the matrices of concordance and discordance, a degree of outranking is produced. The credibility degree for each pair (a,b) is defined as: 8 Cða; bÞ if dt ða; bÞ # Cða; bÞ;t > < Q 12dt ða;bÞ Sða; bÞ ¼ Cða; bÞ · 12Cða;bÞ > : t[Tða;bÞ

Where T (a, b) is a team of criteria for which dt(a, b) . C (a, b). The interpretation of credibility degree S(a,b) must be done with particular attention. It could be also characterized as ‘‘order of importance’’ in order to support the statement that alternative a prevails b.

About the authors Kostas Ergazakis is a researcher at the School of Electrical and Computer Engineering, National Technical University of Athens (NTUA), Greece. He is the corresponding author and can be contacted at: [email protected] Kostas Metaxiotis is an advisor to the secretary for the Information Society in the Greek Ministry of Economy and Finance. John Psarras is an Associate Professor at the School of Electrical and Computer Engineering, National Technical University of Athens (NTUA), Greece. Dimitris Askounis is an Assistant Professor at the School of Electrical and Computer Engineering, National Technical University of Athens (NTUA), Greece.

To purchase reprints of this article please e-mail: [email protected] Or visit our web site for further details: www.emeraldinsight.com/reprints

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Regional development through knowledge creation in organic agriculture Isabel Morales Galindo

Abstract Purpose – Rural regions have rarely been the topic of inquiry in economic development studies or research related to knowledge management. Most studies on knowledge management have focused on high-tech regions. The purpose of this paper is to present a case which illustrates the mechanism and factors of learning regions with knowledge-based development engaged in growing agricultural activities such as organic agriculture. Isabel Morales Galindo is the Director of the Business and Humanities Department, Tecnolo´gico de Monterrey (ITESM), Mexico.

Design/methodology approach – The paper is a case study of a Mexican cooperative. Findings – The case study illustrates how organic agriculture standards and the attractiveness of the market change the rural setting by promoting knowledge creation and application in the field. The results of such knowledge generation are endogenous growth practices for people who otherwise abandon agriculture as a means of living. Learning, innovating and networking are requirements and outcomes of following organic standards. Simultaneously, the creation of efficient institutions and the solidity of local governance are promoted within the region. Research limitations/implications – This paper focuses on the description of the case rather than the theoretical features. This paper highlights characteristics and critical elements present in an agricultural success through the depiction of knowledge creation within a cooperative and surrounding community, that pose elements which consequently can be extended to promote regional development in other rural settings. Originality/value – Characteristics of the organic industry place a region in a competitive position and encourage community involvement to coordinate, to learn, and to improve processes. The organic agriculture industry requires a knowledge foundation essential for meeting industry standards and, thus, requires organization of the community including farmers as well as local institutions. Keywords Knowledge creation, Rural regions, Agricultural products, Community development, Organic foods, Mexico Paper type Case study

Background Not all agricultural regions promote community-wide learning environments; however, when such environments do occur, knowledge dissemination creates positive externalities directly related to prosperity and development. Organic agriculture is a sophisticated industry where many actors play a role in avoiding the use of non-natural inputs into products as well as meeting numerous standards defined by the industry’s international norms. The restrictive nature of organic agriculture requires farmers and the surrounding community to utilize creativity in adapting the standards to their local agricultural processes. Farmers, government institutions, laboratories, and research and development centers join forces and learn from the requirements of the industry and from the experiences in the locality, knowing that they will receive a price premium as a reward and eventually economic prosperity in the community. In other words, the demanding nature of organic certification agencies and consumers feeds the motivation for learning and knowledge capacity of the production community.

DOI 10.1108/13673270710819825

VOL. 11 NO. 5 2007, pp. 87-97, Q Emerald Group Publishing Limited, ISSN 1367-3270

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‘‘ Not all agricultural regions promote community-wide learning environments; however, when such environments do occur, knowledge dissemination creates positive externalities directly related to prosperity and development. ’’

The first part of this paper explains the externalities created by the organic industry. The paper then depicts a specific case describing how innovation and learning encourage development in a rural agricultural region in Mexico. Conclusions explore how this case represents a valuable example of knowledge-based development which can be applied to extend growth opportunities to other developing regions.

Knowledge and the concept of learning regions The concepts of knowledge and learning regions are very much intertwined since one is part of the other (Morgan, 1997; Asheim and Dunford, 1997; Simmie, 1997; Johansson et al., 2001; Scheff, 2001). Boekema describes a learning region as a paradigm in which a learning region ‘‘is the physical expression of the understanding that economic growth is dependent on innovation, which in turn is dependent on the creation, dissemination and application of knowledge . . . [translated into] learning . . . and generally learning processes are connected with space’’ (Boekema et al., 2000, p. 3). Similarly, Maillat and Kebir (2001) define a learning economy as one that has the capability to learn permanently and expand the knowledge base with cooperation and trust. The regions focused on knowledge creation and learning go beyond individual firms, including inputs and infrastructure, where tacit knowledge is best exchanged face to face (Florida, in Asheim, 1998). The exchange of information, knowledge, and the responses to global markets create a virtuous cycle of competitiveness for the region and all its actors. Maskell et al. (1998) assures that the dynamism in an industry is socially embedded and driven by innovation with constant knowledge creation. Even in countries with low technology and high costs, it is feasible to maintain competitiveness through the development of local capabilities, difficult to imitate for others and key for the place and their economic activity (Maskell et al., 1998). The industry tends to agglomerate entrepreneurial activities and innovations, and specialize according to the local environment. In unison, the exchange of knowledge under prosperity can also stimulate entrepreneurship and innovation, creating a local culture and behavioral patterns that, in turn, disseminate know-how (Maskell et al., 1998). Knowledge not only pertains to technology but also to logistics, organization, marketing, sales, distribution, and relations. With any type of knowledge, trust is vital to ensure the effectiveness of the collectivity and to increase competitiveness through the sharing of tacit knowledge. The notions of innovation, learning, and networking are closely related to the concept of knowledge-based development. The organic agriculture industry and the case study of an organic vegetable organization in Baja California Sur, Mexico further illustrate and clarify these concepts. The organic agriculture elements are shown first and the case study second.

Organic agriculture industry The organic agriculture environment has an institutional framework as well as networks that are attractive to farmers. Such networks provide farmers with the opportunity to become global players and to create or participate in an environment that requires constant knowledge creation, dissemination and benchmarking. Significantly, the organic agriculture industry requires a key ingredient from all its participants: learning. In other words, producing organic products can help develop participating regions through innovation,

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following international norms, and by becoming part of a global network. Table I outlines the characteristics of the determinant factors of a learning region working in the organic industry. The organic agriculture movement can generate development by innovating, by following norms and standards, and by networking. All three tools can be related to the learning region concept and are also useful for describing the knowledge environment in a developing area (Boekema et al., 2000). The following three subsections describe how the organic agriculture strengthens each determinant factor. Innovating Organics is an alternative for production not only due to different production procedures, but also because of distribution and marketing innovations required to successfully place organic products within the market. As a new trend, farmers participate in a corporate fashion in order to guarantee sales throughout the year. Furthermore, farmers are privileged with more resources for innovation. For example, 900 scientists are available to farmers producing organic brands for General Mills alone (Pollan, 2001). Innovations in the organic industry are ubiquitous. Farmers must learn new and improved production techniques involving machinery, equipment, procedures, raw materials and inputs. Additionally, the market demands different varieties, different specificities (e.g. color, size, durability), which encourage organic producers to find solutions and new products. Science and innovation play important roles in overcoming processing and production challenges of organic products. Such products involve technical agricultural issues as well as managerial and logistical procedures for the development of both local and international markets. For example, distribution procedures of organic products have forced transportation companies to innovate containers and handling procedures in order to meet the norms and standards of innocuousness and isolation to avoid contamination required by the organic industry. Changes in the organic industry are constant, and thus communication must be constant. When a product or a plot is found contaminated, all farmers and handlers must be informed quickly to either stop the use of inputs or to put in quarantine immediately, in order to continue producing and guarantee minimal loses. On the other hand, local soils require constant adaptation to the weather and to new crops. When researchers or farmers find Table I Summary of factors in the organic industry Determinant factor

Characteristics in the organic industry

a. Innovation and learning

Constant innovation adapted to local needs New and indigenous methods of production Technical, managerial and procedural aspects Constant research and development by specialized researchers and formal lab tests Collaborative learning where all improvements benefit the organizations involved as well as the region Families involved in production pass on know-how quickly The cooperative nature of the organizations producing organics Global norms defined by USDA, IFOAM, European Union International certification agents Organizations involved with local governments, traders and international organisms Global networks Networks developed around farmer associations

b. Institutions and governance

c. Networks

Source: Morales Galindo (2004)

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better practices they are immediately passed on to the organization or community in order to assure quality and increase productivity. Also, market-needs of organics induce for innovations similar to those of the high-tech industry; the main difference being that the organic industry is market driven and the high-tech industry is supplier driven, using Gereffi’s interpretation (Gereffi and Korzeniewicz, 1994). Farmers and distributors must constantly monitor changes in market preferences in order to secure demand. In turn, these innovations develop new and better ways of competing (Boekema et al., 2000). To sum up, the organic industry involves more than the farmers in the learning process; it involves the management team, logistics suppliers, local government, and certification agents as well. The constant evolution of the industry sparks both innovation and learning, while the global nature of organics encourages the sharing of knowledge and common practices.

Norms and standards International norms and standards required for organic products are well-defined and well-known to leaders in organic communities. Following norms involves a costly strategy for development. Becoming ‘‘organic’’ is costly due to the expenses that farmers incur for certification; clean-up; book keeping; and investments to assure innocuousness. Once a group of farmers have decided to produce organic products, learning is set in motion almost immediately. Farmers must learn the process, the norms, the market, the certification agencies, and the production itself. Transforming soils into organic soil may take three to four years. The upside of this situation is that it gives the organization of farmers enough time to learn about the markets and to identify specific clients for future sales, while selling in traditional markets and testing production techniques. New clients will require a specific delivery-schedule throughout the year (for example, a specified number of boxes weekly), and this forces the organization to plan annual production in advance, promoting professional procedures not generally used in small-scale agriculture. Some organics are sold at market price, but most industry actors in Mexico have contracts with agreed prices at an annual basis to avoid the risk (Go´mez Tovar et al., 2000). Organic certification is offered for products, packaging, processing plants, intermediaries or handlers, and restaurants that serve organic foods. Certain standards and norms define the process and requirements for farms and producers that choose to carry the label. Because the organic label distinguishes the quality of organically produced agricultural products from conventional ones, producers are able to assign a higher price to their organic products. The ultimate purpose of certification, therefore, is to provide consumers with certainty that the products they purchase are indeed organically produced and thus warrant higher prices. At the same time, certification is a procedural requirement utilized to identify organic products which meet certain importation standards. As farmers identify their potential international markets, they must choose the appropriate certifying agencies accepted by the countries to which they will export their products. There are at least 200 certification agents in the world. Each agency follows norms according to its country of origin as well as international norms. The International Federation of Organic Agriculture Movements (IFOAM) is the founding institution of the organic movement in Europe. The IFOAM only accredits organizations in charge of certifying and does not certify actual products. Organic certification agencies have to be approved by higher-level institutions in order to have credibility when issuing labels and certifying farms. The major institutions include IFOAM and the US Department of Agriculture (USDA) that follow specifications based on the National Organic Standard Board (NOSB), and the National Organic Program (NOP), under the norm ISO 65 (quality norm for agricultural products). Most institutions use the list from the Organic Material Review Institute (OMRI) to select approved inputs. Other institutions include the Conseil d’accre´ditation du Que´bec, Costa Rican Ministry of Agriculture and Livestock, and Japan Agriculture Standards.

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Information is crucial for organic agriculture. Information about the product is vital to the industry as well as information about norms on inputs, fertilizers, processing, packaging, transportation, and labels. By following norms, organic producers and agencies are able to remain informed about new laws and requirements that constantly and rapidly change to meet new export standards. The fact that no chemicals may be used in the production of organic products and that all material must be recyclable demonstrates much sophistication in the industry (Go´mez Tovar et al., 2000). Networking Participating in the organic industry carries the additional benefit of access to several networks pertaining to education, small loans and credits, medical services, and communitarian stores (Go´mez Tovar et al., 2000). An initial contact is established with international networks of other organic organizations such as certification agencies and organic consumer networks, with the intention of obtaining information on labels or market preferences. Inspectors, researchers, and technicians also are contacted to evaluate and transform certain regions into areas which produce organic products. Eventually other NGOs, distribution channels, and traders are added to the network. Relationships become very valuable while language differences become a minor concern due to the collaborative nature of networks. Figure 1 depicts the network of organic production and demonstrates how organized farmers are closely and directly related with government, certification agencies, research and development centers, and commercialization channels. The organics network has farmers at the center resulting in increased benefits when compared to the traditional, horizontal, chain where the information and monetary value is diminished in the long production chain (Dussel Peters, 2002) towards the final consumer. Closeness to the Figure 1 An organic farmer network

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market allows farmers to adjust promptly and therefore securing sales, and in some cases, avoiding added costs, that in turn could benefit in increased profit margins. Aside from the certification agencies mentioned previously, other institutions related to the organic movement in the world include: Organic Trade Association (OTA), Organic Farmers Marketing Association (OFMA) Produce/Perishables Committee, and the Independent Organic Inspectors Association (IOIA). Also NGO’s such as ‘‘Buy Local’’ and ‘‘Fair Trade’’ movements are closely linked to farmers. Ultimately, the organic agriculture industry silently promotes innovation, international norms and networking where knowledge is the bonding element. These ingredients become cultural essentials for an endogenous growth system. Development and entrepreneurship surge locally and organically through time, becoming later a virtuous cycle of development from within. Following, the case study of an organic vegetable cooperative in Baja California Sur, Mexico exemplifies these determinant factors further in an actual rural setting.

A case in Baja California Sur In order to illustrate rural development under knowledge structures, the case of a Mexican cooperative-like structure is valuable. According to the true local story, in 1985, a farmer/tourist from the USA arrived at Baja California Sur on a bike carrying vegetable seeds in his hand. This farmer allied himself with six local farmers, and together they produced and exported US$52,000 worth of organic vegetables and fine herbs in the first year. The following cycle, this bi-national group increased to 18 members and farmed a territory of 40 hectares (ha), increasing their sales by six times. By 1987, 40 members had joined the group of organic farmers; and in 1988, 167 farmers represented the company. Significantly, both years yielded a 100 percent growth margin in production and sales. By 1989, sales were up to US$1 million and approximately 160 members were working in the organization. Two members from the USA had become in charge of commercialization. Production continued, and in 1990, a restructuring of the organization resulted in a decrease of membership to 141 members. The producers and commercial agent who left the organization created a new company elsewhere in the state of Baja California. In 1993, the organization aimed to make management more efficient, and thus separated the activities of commercialization and production. Commercialization was managed by the initial founding member from the USA and was based in the state of California, USA. For production and packing activities, the organization created a formal legal structure referred to as a Social Solidarity Society (SSS). A SSS is a mode of cooperative including a professional administrative team independent from the cooperative’s members. In 1993, the SSS included 141 members in eight communities and covered 350 ha with one packing plant in San Jose´ del Cabo. In recent years the organization continues to operate with the same number of members in the SSS, yet now have three more packing plants and is associated with 450 other producers (a total of 591 farmers involved) with a constant, annual growth rate of 20 percent between 2000 and 2004. For each member there is one worker at the packing plant and two additional producers. One region alone has 53 members, there are 24 temporary workers and 76 associated producers, benefiting 153 families at the packing plant. In total, 1,500 families have benefited directly or indirectly from the production of organic vegetables and fine herbs. The producers, whether members or not, have obtained individual organic certificates since 1990, and now have a total of 1,200 Ha certified for future use. Learning and innovation in the SSS The initial innovation was to produce only organic agricultural products. Learning was not difficult, and organics was the natural way to produce crops in this particular region during the 1980s. The wealth accumulation through the sales of organic products became the learning incentive in Baja California Sur, which in turn persuaded other farmers in the region to follow the norms of organic agriculture. The major change that occurred in the region was that instead of using chemicals to control pests, the farmers began to use their own labor and the work of their families to control each plant by hand. The family nucleus has become

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‘‘ The notions of innovation, learning and networking are closely related to the concept of knowledge-based development. ’’

the labor force and in turn has promoted a faster dissemination of knowledge that has evolved into providing new opportunities for children. At the same time, knowledge remains in the region because the SSS hires local engineers for the administration staff and packers for all three packing plants. The modernization and improvement process is motivated by the needs of farmers and the requirements of the market. For the former, the many problems and needs of the farmers become the daily duties of the administrative and technical staff. In this way, the SSS staff plays a vital role in solving the region’s problems. The learning process is problem based. In other words, when a problem or difficulty arises in a parcel, the staff’s technical team unites to work on solving the problem as soon as possible. In this way, the workers have learned to master most problems themselves. The nursery (or greenery) is in constant evolution and uses a quarter of a hectare to test new plants, new varieties of basil and tomato, and to produce all the plantlets for the cycle. Additionally, the nursery tests different types of irrigation systems and produces compost using local soil and sands. In 2003, the nursery hired an Israeli geneticist to obtain a local cherry tomato variety exclusive to the region. As a part of the research, 109 lines of tomato were tested. The nursery is currently working on controlling insect plagues and creating composts and natural pesticides such as garlic and onions. Projects at the nursery also include demonstrative varieties of vegetables, tryouts to lengthen the productive life of the plant, and testing new vegetables (e.g. zucchini, eggplant, cucumber) for the summer season. The market dictates the new varieties desired, and the greenhouse tests the vegetables that can most likely adapt to the region’s climatic and soil characteristics. Twenty percent of all parcels use irrigation systems that make the consumption of water more efficient, the rest use more traditional methods with innovative adaptations to avoid waste. Technology-use in parcels is low due to the fear of losing it along with the infrastructure in the hurricane season almost every summer. On the other hand, the packing plants are more responsive to technological alternatives to increase productivity and decrease costs. Most learning has occurred with modernization efforts in aspects other than the agricultural activity. In the pre-production line (greenhouse) the plantlet trays have evolved constantly using new and more resistant materials in compliance with organic norms. Also, internal transportation has improved over the years through facilitating the system to move vegetables and herbs in bulk. The technical team continuously tests new materials for containers to increase effectiveness, organize space, and decrease costs. The packing process itself has also gone through modernization. The line has gone from packing eight boxes in eight hours to now packing three to four boxes an hour. One person alone went from packing eight boxes a day to 30-35 boxes a day. The SSS formalized their training program in order to assure productivity and reduce rotation that in turn increases awareness on quality standards. The export process requires precise paperwork daily. The administrative staff has internally designed software programs and databases to keep historical records and to complete forms and formats consistently and systematically. The administrative team has mastered procedures and programs in such a way that has helped the organization to systematize their operational statistics and the definition of internal processes.

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Learning occurs every day, and it is a cooperative process that takes place inside the family, the community and among institutions. The commercialization company absorbs new information and market trends, and in turn is passed to the SSS as an internal norm. The assortment of information and experiences has created a solid foundation of tacit knowledge. The collectivity in actions is additionally reflected in the learning process; knowledge is shared among farmers, their associates, and their families. Institutions and governance in the SSS There are many institutions in the region, not necessarily concentrated in governmental agencies. The strongest institution is the organization of farmers, the SSS. Additionally, government agencies in the municipality have adapted and evolved according to the needs of the exporters; which at the same time became the facilitators of the development of agriculture taking the role of visionaries. The local office of the Ministry of Agriculture (SAGAR) has been supportive in providing the export paperwork for shipments, even on weekends when their offices are not officially opened. Both local institutions have a preference for organic agriculture and most aid is directed to these efforts. Locally, the SSS is actively involved in many regulations, especially concerning transforming the municipality into 100 percent organic. The certification director of the SSS is constantly involved in national forums where they have participated on changes and proposals for the new agricultural laws. The close link between the farmers, administrative staff and governmental institutions has enhanced local governance. There are few written agreements or contracts governing the actions and commitments of the SSS with other institutions. Yet, there is a formal agreement between the commercial agent in California and the SSS. Most agreements are formal and voluntary, but not contractual. At the same time, farmers have informal agreements with their associates with a strong connection that assures compliance with standards and production quotas. All members have a commitment to produce as planned. The SSS commits to buying 100 percent of the planned production, so members also have a moral agreement not to sell organic products to another client on their own. Each cycle, a new plan is set with each member, and in turn members agree with their own associates on allocated production quotas. The Local Bureau of Vegetable Health (the office in charge of certifying soil and plant wellbeing) has an informal arrangement with the SSS in order to have the certificates completed daily for exports; thus, both institution and organization help each other. Negotiations and agreements are uncomplicated because the SSS has been an active participant in the Bureau; they have, at times, members that are involved as vocals, commissioners, treasurer, or even occupying the presidency. Additionally, the local Bureau is an active participant in attacking pests in their jurisdiction; they monitor all transportation coming into the region with plants to avoid unwanted pollutants. The Bureau has funds for research on new organic methods of pest control valuable for the SSS and other farmers in the locality. All members and associates have to be certified. The certification agency visit the state every year to supervise a sample of farms and continuously gives the SSS specific recommendations to be followed by each producer as well as in the packing plant. The strong relationship between the certification agency and the SSS has facilitated the application of all new USDA norms with few complications, assuring the continuance of operations. The mode of governance has given the region the strength that the institutions individually do not have; while the proactive nature of participants and the willingness to grow and develop balance the lack of written norms. Informal agreements and conventions are shared by the organization, their families, the government and all farmers in the municipality. One important factor in the strengthening of local governance is the promotion of trust and self-management of farmers. For example, each member has the right to find and associate with other farmers that have an organic certificate, and coordinate production of both under

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the member’s code (ID number) by making individual and personal arrangements – members are the original 141 in the SSS, while associates are related with members only, not the organization. Leadership in this case has been the key; one person had the vision to produce organic products and sell them in the growing market of organics in the USA at a premium price so that farmers could make a living from agriculture. The six local farmer-founders have been as committed to organics as well, and their involvement assures knowledge dissemination and creation. Over the years, all farmers have learned the administrative tasks that have to be performed by participating in the executive committee and leading the operations of the packing plant or nursery. They rotate the committee every two years to make it more democratic and avoid power accumulation and conflicts of interest. Trust has been the key to the success of governance in this case. Agriculture is organized, the producers receive direct benefits, their families have better houses, and the quality of life has improved considerably. SSS members and all producers associated to them prefer to share knowledge on organic care rather than keep the information to themselves, since it will benefit the surrounding environment and avoid pests and contamination, while knowing that increased production of similar vegetables in the region will not affect their income or market price due to the annual contract signed ahead. For this reason, the impact of this SSS in the region has in turn invited many producers and entrepreneurs to take advantage of the benefits of exporting products at a premium price using a similar business model with diverse legal structures. New exporters and the SSS are not competing directly because the market is big enough for all to work in it. There have been up to eight exporters in the region in ten years, but three are the most consistent. The market is highly demanding, thus forcing improvements. Farmers are aware enough of the standards and international norms. Even with few local and national norms, they base their activities on the norms set by the market. In the region, many initiatives are private as well as public, and many of the campaigns have been organized by farmers having the full support of the local government. Social capital and networks in the SSS All networks and organizations that have surged are based on trust. The benefits for the city and region are evident to all actors and in this way each has to trust others to do their best in an efficient manner in order for all to succeed. A motivation factor to all SSS members is that they own a growing and successful company, where they can direct and decide. The second motivation is the assured earnings throughout the year that have allowed them to accumulate capital for their families. Social capital is bonded by the attractiveness of making a good living. Although some producers may not be part of the SSS, most farmers in the region have the motivation of becoming organic to sell at a premium. Families work the land and very rarely hire someone external to attend production in the farm; only family members are committed to their own income. Alternatively, the managerial, transportation and packing activities hire many local and regional employees and professionals. The blend of families of farmers, technicians and professionals in this region has fortified the social capital that in turn has made the place more competitive. The most important network embedded in the SSS organization is the organic industry network: the certifiers, inspectors, USDA, and the transportation channels. For the SSS, networking internationally across borders is an everyday activity. Their network grows according with needs, modernization, changes in standards, problems, and new clients. In the region, an increased number of entrepreneurs are easily connected with new potential customers in importing markets, taking advantage of the existing network. Farmers and the SSS have slowly increased relationships with other institutions that can teach better practices or new technologies. Most research needs are met through contacting agricultural universities in Mexico and the USA. The strength of the network has allowed a clear and assured relationship with researchers regardless of their location, diminishing the need to have a research center locally.

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Most engineers hired in the SSS are local or regional. Many agricultural engineers have few alternatives to work professionally on the state other than in tourism, while this SSS is attracting professionals. This employment practice is promoting education and training progress in the region. The SSS is the intermediary between producers and the government and related institutions. The organization has teamed up with the Local Bureau of Vegetable Health, the local government, the only customs agent, labs and airlines. A success factor in logistics for the SSS is precisely their relationship with the airport and the agreements with airlines since it is the fastest gateway to arrive to their markets. On the other hand, one laboratory in the city is dedicated solely to soil indicators. The SSS has a contractual agreement with this lab to perform 30 weekly tests. This agreement assures delivery times for the SSS and demand for the lab services. The organic market is seemingly unlimited – and it can grow a lot more. It is trendy to sell to restaurants in the US market, while in Mexico production is directed mostly for exports because the Mexican organic market is not mature enough to buy at a premium. The characteristics of network in this state smooth the progress of organic agriculture and exports.

Challenges and final remarks Competitiveness is critical for regions to develop, and the state and private enterprises have mutual responsibilities. Globalization has created new conditions that require companies and regions to meet global norms and standards, and to accumulate knowledge to assure the greatest benefits. With the case of the organic producers in Baja California Sur, it is possible to see that the organic agricultural industry has characteristics that foster the creation of learning regions through the creation of tacit knowledge, encouraging individuals and companies to organize in order to meet the global standards, creating added value and participating in globalization. The decision to grow organic agriculture transformed farmers and the agricultural region in Baja California Sur, in a way that they constantly searched to meet market needs and the certification standards. An endogenous scheme was created and the outcome was economic growth, increased number of jobs and the continuous creation of companies, services and institutions. The organic agriculture also forced the region to relate with international public and private organisms transforming the local dynamic into a global one. However, to learn from this experience and capitalize in similar regions present the challenge to identify who could become the bonding intermediary that can coordinate the diverse actors involved in rural regions; especially to involve authorities in a way that they can assume the visionary role and have the disposition to become facilitators for development. Organic agriculture per se is not the only alternative for development, although it is an attractive solution for many current environmental concerns. Still, a similar industry that involves such a global and comprehensive structure with the bonding ingredient of knowledge could be a special opportunity for rural regions to develop.

References Asheim, B.T. (1998), ‘‘Learning regions as development coalitions: partnership as governance in European workfare states?’’, paper presented at the Second European Urban and Regional Studies Conference on Culture, Place and Space in Contemporary Europe, University of Durham, Durham, 17-20 September. Asheim, B. and Dunford, M. (1997), ‘‘Regional futures’’, Regional Studies, Vol. 31 No. 5, pp. 445-55. Boekema, F., Morgan, K., Bakkers, S. and Rutten, R. (2000), Knowledge, Innovation and Economic Growth: The Theory and Practice of Learning Regions, Edward Elgar Publishing Inc., Cheltenham/Northampton, MA.

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Dussel Peters, E. (2002), Territorio y Competitividad en la Agroindustria en Me´xico: Condiciones y propuestas de polı´tica para los clusters del limo´n mexicano en Colima y la pin˜a en Veracruz, CEPAL; Secretarı´a de Economı´a; PyV editores, Me´xico, DF. Gereffi, G. and Korzeniewicz, M. (Eds) (1994), Commodity Chains and Global Capitalism, Greenwood Press, Westport, CT. Go´mez Tovar, L., Go´mez, M.A. and Schwentesius, R. (2000), Desafı´os de la Agricultura Orga´nica: Comercializacio´n y Certificacio´n, CIESTAAM-UACH-MundiPrensa, Edo. Johansson, B., Karlsson, C. and Stough, R.R. (Eds) (2001), Theories of Endogenous Regional Growth, Springer, Berlin and New York, NY. Maillat, D. and Kebir, L. (2001), ‘‘Chapter 12’’, in Johansson, B., Karlsson, C. and Stough, R.R. (Eds), Theories of Endogenous Regional Growth, Springer, Berlin and New York, NY. Maskell, P., Eskelinen, H., Hamibalsson, I., Malmberg, A. and Vatre, E. (1998), Competitiveness; Localised Learning, and Regional Development, Routledge Political Economy, New York, NY and London. Morales Galindo, I. (2004) of, ‘‘Building rural learning regions: innovations in the organic agriculture industry’’, dissertation, University of Colorado, Boulder, CO. Morgan, K. (1997), ‘‘The learning region: institutions, innovation and regional renewal’’, Regional Studies, Vol. 31 No. 5, pp. 491-503. Pollan, M. (2001), ‘‘Naturally: how organic became a marketing niche and multibillion dollar industry’’, The New York Times Magazine, 13 May, p. 30-37, 57-58, 63-65. Scheff, J. (2001), Learning Regions: Regional Networks as an Answer to Global Challenges, Peter Lang, Frankfurt am Main and New York, NY. Simmie, J. (Ed.) (1997), Innovation, Networks and Learning Regions, Jessica Kingsley/Regional Studies Association, London and Bristol, PA.

About the author Isabel Morales Galindo has a PhD in Design and Planning from the University of Colorado at Denver, as well as an MBA and MA in Latin American Studies from the University of Texas at Austin. Her doctoral dissertation was titled ‘‘Building rural learning regions: innovations in the food production industry’’ and is currently working as Director of Business and Humanities Department at Tecnolo´gico de Monterrey (ITESM) in Morelia, Mexico. Her interests include economic development alternatives for rural regions and the evolution of clusters in lesser developed states. She can be contacted at: [email protected]

To purchase reprints of this article please e-mail: [email protected] Or visit our web site for further details: www.emeraldinsight.com/reprints

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Technology districts: proximity and knowledge access Antonio Messeni Petruzzelli, Vito Albino and Nunzia Carbonara

Abstract Purpose – The purpose of this paper is to analyse if and how technology districts use proximity dimensions (such as geographical, organizational, and cognitive) as a communication resource for accessing external knowledge sources. Design/methodology/approach – To achieve this purpose, the organizational and cognitive links between technology districts’ actors and external ones are identified and then the new geographical boundaries of the districts are drawn. A case study related to an Italian technology district (Torino Wireless) is provided in order to identify how different research organizations located in the district use proximity dimensions for reaching knowledge sources external to the district, then re-shaping its geographical boundaries.

Antonio Messeni Petruzzelli, Vito Albino and Nunzia Carbonara are all based at the Politecnico di Bari, DIMeG, Bari, Italy.

Findings – The empirical study enables identification of the actors connected to the technology districts by means of geographical, organizational, and cognitive proximity, and their locations. Moreover, results show that organizational proximity is mainly adopted to link actors located near the district area. While, cognitive proximity is mainly adopted to connect actors geographically distant from the district. Research limitations/implications – As regards technology district strategic behaviour, it seems particularly crucial to exploit all the three dimensions of proximity. In particular, the technology district of Torino Wireless should increase its use of organizational proximity to be connected with external knowledge sources. Originality/value – The paper proposes a methodology for identifying the external actors connected with the technology districts by means of proximity. Furthermore, the relationships between organizational and geographical proximity, and cognitive and geographical proximity are also investigated. Keywords Knowledge management, Communication technologies, Italy Paper type Research paper

Introduction Technology districts represent a regional system, constituted by economic actors whose success and survival depend on their capability to create new knowledge and then innovation. New technological knowledge results as the collection of pieces of information and knowledge owned by a variety of parties, and then requires, to be developed, the combination of external learning processes (e.g. learning by imitation and learning by interaction) with internal ones (R&D activities, learning by doing and by using). However, access to the technological knowledge is made difficult by several factors, such as its tacit and idiosyncratic character, transaction and communication costs, and also depends on the ‘‘absorptive capacity’’ (Cohen and Levinthal, 1990) of the agents involved in the process. The co-localization of firms in a geographically bounded area, and then the geographical proximity, can enhance the effectiveness of external learning processes and the access to knowledge. In fact, face-to-face contacts, the establishment of mutual trust, the building of the so-called social capital (Tura and Harmaakorpi, 2005), and the low communication costs are especially conducive for raising the rate of introduction of technological changes and

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DOI 10.1108/13673270710819834

‘‘ Technology districts represent a regional system, constituted by economic actors whose success and survival depend on their capability to create new knowledge and then innovation. ’’

increasing the positive effects of agglomeration in terms of economic and technical externalities (Antonelli, 2000). However, in the modern globalised economy knowledge sources are not always located in the same geographical areas. Then, scholars have stressed the importance for firms and regions’ innovation and competitiveness to open geographical clusters to the external environment by establishing relationships with economic actors world-wide located and creating global networks (Owen-Smith and Powell, 2004). These structures can be defined as organizational configurations aimed at transmitting data, information, and knowledge by using or making connections with various degree of intensity (Lambooy, 2004). The important role played by networks as innovation mechanisms has been pointed out by the network theory of innovation (Florida, 1995; Baptista and Swan, 1998), which states that individual actors are seldom capable of innovating independently, and never innovate in vacuum. In fact, networks through the establishing of ‘‘weak and strong ties’’ (Granovetter, 1973; Hansen, 1999) and the bridging of ‘‘structural holes’’ (Burt, 1992) can greatly enhance the processes of knowledge creation and sharing, and then support the raise of innovation (McEvily and Zaheer, 1999; Reagans and McEvily, 2003). Once recognized, the importance of knowledge for innovating and the role played by networks as channels for knowledge flowing, it becomes necessary to identify how these networks can be created. Large attention has been paid by the literature to the notion of proximity as a means by which economic actors establish relationships, interact and exchange knowledge and information. In fact, proximity dimensions, such as organizational and cognitive, can act as ‘‘bridges’’ for reaching external knowledge sources, and connecting actors distant from the spatial point of view. In particular, organizational proximity can be defined as the extent to which relations are shared in an organizational system, either within or between organizations (Boschma, 2005) and can be analyzed at two different levels, namely the structural level and the dyadic level. The former refers to the concept of belonging to the same organization (Oerlemans and Meeus, 2005), while the latter deals with the similarity in organizational context in which members of different organizations operate (Wilkof et al., 1995). Cognitive proximity is generally defined in terms of common knowledge base and expertise among people. The concept of cognitive proximity has been developed by Nooteboom (2000) as a relational attribute. However, several authors (e.g. Torre and Rallet, 2005) use this term for referring to a group of people that belong to a community of practice and therefore can interact easily despite large geographical distance. The paper aims at analysing how technology districts use proximity to reach external knowledge sources and at identifying the related technology clusters. In particular, they can be defined as technology districts that widen their geographical boundaries being connected through proximity with external knowledge sources. Then, the new geographical boundaries of technology districts are outlined by identifying organizational and cognitive links between districts’ actors and external ones, such as firms and research organizations. In particular, links based on organizational and cognitive proximity are analysed by means of proxies. The paper is structured as follows. In the next section the theoretical background of the paper is provided. In particular, two main topics are analyzed: first, the notion of technology

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districts and the relevant role played by knowledge and innovation for their success and survival; second, the use of proximity dimensions (geographical, organizational, and cognitive) as a communication resource. In section three, the relationship between proximity and external knowledge sources is studied. Then, the notion of technology cluster is presented and proxies for organizational and cognitive proximity are identified. Finally, a case study related to an Italian technology district is presented and the main results and findings are summarized and discussed.

Theoretical background Technology districts as cognitive systems The concept of technology district has been introduced in the literature as a modern and dynamic variant of industrial district, highly characterized by three main features: knowledge creation, innovation, and geographical proximity. In fact, technology districts can be considered as key parts of ‘‘product based technological learning’’ (PBTL) industries, concentrated in distinctive geographically bounded areas (Storper, 1992). These areas possess the ability to innovate which enables them to withstand the instability arising from technological changes, and this distinguishes them from the other forms of production system. Compared with the Porter (1998) definition of geographical cluster, technology districts are a subset of more knowledge-based industry clusters (Cesaroni and Piccaluga, 2003). In these clusters, firms co-locate looking for high quality suppliers, a large pool of skilled workers or local knowledge stock. Using a knowledge-based perspective, technology districts can be considered as cognitive systems (Maskell, 2001) that develop, acquire, and manage new technological knowledge in order to create product and process innovations and be competitive (Tallman et al., 2004; Iammarino and McCann, 2006). Knowledge can be considered as a collective good since its generation is the result of a process that combines pieces of information and knowledge that are owned by different and heterogeneous actors and cannot be traded as such (Antonelli, 2000). In particular, knowledge is the combination of knowledge internal to the firms, resulting by R&D activities, by processes of learning by doing and by using, by formal and informal interaction among individuals within the organization, and of knowledge external to the firms. This can be external to the firms but internal to the geographical area in which the district is localized and external to the firms and to the area; in both cases it is the result of external learning processes (Malerba, 1992). Among the different types of external learning processes, those that strongly characterize technology districts are learning by interaction and learning by imitation (Maskell and Malmberg, 1999). Processes of learning by interaction can be activated within the network of inter-firm relationships established inside the technology district but can be also activated by relationships with actors located outside the technology district. In the first case the learning processes is based on knowledge sources external to the firm but internal to the geographical area in which the technology district is localized. In the second case the knowledge sources are external to the firm and to the geographical area. Processes of learning by interaction are based on the continuous exchange of information and knowledge among complementary firms, among firms and customers, and among firms and universities/research centres. Learning by imitation is concerned with the gathering and reproduction of knowledge elsewhere created. In this process different knowledge channels can be used, such as the consultation of scientific and technical publications, the examination of suppliers, customers, and competitors, as well as the participation at events (e.g. conferences, trade fairs). Both the external learning processes are based on knowledge spillovers (intra-industry, inter-industry, and science-technology), which can be intentional and unintentional (Torre and Gilly, 2000; Breschi and Lissoni, 2001), creating both positive (Lublinski, 2003) and negative (Shaver and Flyer, 2000) externalities.

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‘‘ Processes of learning by interaction are based on the continuous exchange of information and knowledge among complementary firms, among firms and customers, and among firms and universities/research centers. ’’

In the highly innovative and fast-changing scenario in which firms of technology districts operate and compete, successful innovation partly depends on intra-firm determinants, namely firm-specific resources, internal R&D activities, and employees, and strongly depends on determinants that are external to the firms. In fact, ideas and knowledge needed to develop innovation are often the product of the confrontation and combination of different fields of knowledge and of heterogeneous resources. Firms often are specialized on one field of knowledge and rarely have all required heterogeneous resources internally; therefore to successfully innovate they need to acquire technical knowledge from external sources (Freeman, 1987), such as customers, suppliers, institutions (chambers of commerce, trade associations, etc.), public research organizations and universities, competitors, consultants, affiliated firms (Arundel and Geuna, 2004). Considering firms of technology districts, these external knowledge sources can be further distinguished into: knowledge sources external to the firm and internal to the technology district and knowledge sources external to the firm and to the district area. The former develop a knowledge that is strictly contextualised and strongly linked to the environmental and cultural factors characterising the local area. This knowledge circulate within the district through local pipelines and it is easily transferred among the technology district actors because of their co-localization. The latter develop competencies and knowledge that are different and complementary respect to those characterizing the district. Such a not-contextual and complementary knowledge is very important to develop radical innovations and then it is a very critical resource for the technology district innovative performance (Antonelli, 2003). Furthermore, this external knowledge circulate through global pipelines and can be difficult to reach because firms cannot exploit the advantages of the co-localization and the face-to-face contacts. Therefore, to sustain their competitive advantage by increasing their innovative performance, it is particularly important for the local actors of technology districts to reach knowledge sources external to the districts (Romijn and Albu, 2002; Lechner and Dowling, 2003). Different kinds of connection can be settled by the technology district actors to reach the external knowledge sources and different actors can play an important role to do this (Albino and Garavelli, 1996; Cantwell and Piscitello, 2005; Davenport, 2005). In particular, research organizations located in the districts, are usually involved in networks connecting economic agents world-wide located and then can be considered as key agents that act as gatekeeper for the technology districts (Santoro and Gopalakrishnan, 2001; Gittelman, 2006). Once we recognize the importance of the external knowledge sources, it is possible to affirm that geographical proximity is not the only dimension of proximity that is relevant for technology districts (Albino et al., 2007). In fact, it is necessary to exploit dimensions of proximity different from the geographical one that allow the external knowledge sources to be reached by the technology districts. In particular organizational and cognitive proximity can act as ‘‘bridges’’ to reach these external knowledge sources. In fact, actors that are not co-located can be connected each others and then have access to external knowledge sources by using different organizational arrangements, thereby increasing their organizational proximity (Freel, 2003). Also, not geographically proximate actors that cannot share knowledge and information by mean of face-to-face contacts may compensate for this difficulty by having an

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high mutual understanding if they are characterized by a similar cognition (Wuyts et al., 2005), thereby increasing their cognitive proximity. Proximity as a communication resource The literature on innovation (e.g. Torre and Gilly, 2000) recognizes that proximity covers a number of dimensions, i.e. proximity means a lot more than just geography. Boschma (2005) identifies five dimensions of proximity: cognitive, organizational, geographical, social, and institutional. Knoben and Oerlemans (2006) in a recent literature review consider also other two dimensions of proximity, namely cultural and technological. In a recent study Albino et al. (2007) have analyzed the role played by proximity dimensions as a communication resource that can be exploited by firms and regions for sustaining their competitive advantage, by increasing the effectiveness of the external learning processes and their innovative capability. With this regard, in this section we analyse the communication properties of proximity. In particular we focus on three dimensions of proximity, namely cognitive, organizational, and geographic, and for each of them we analyze the effects on the external learning processes. The effectiveness of external learning processes is positively affected by cognitive proximity, in terms of common knowledge base and expertise among people. In fact, in order to communicate and transfer (new) knowledge effectively and efficiently, actors need to have similar (but not necessarily identical) frames of knowledge. Too little cognitive proximity increases the difference between the cognitive maps of two firms and then decreases the capacity of one firm to identify, interpret, and exploit the knowledge possessed by the other firm (Cohen and Levinthal, 1990). However, too much cognitive proximity may be not effective for learning and innovation. With this regard, Nooteboom (2000) stated that too little cognitive distance means a lack of novelty, while too much cognitive distance implies problems of communication. For analytical purposes, organizational proximity can be defined by the rate of autonomy and the degree of control that can be exerted in organizational arrangements. A continuum is assumed from one extreme (i.e. low organizational proximity, meaning no ties between interdependent actors, as in the pure market), to the other extreme (i.e. high organizational proximity, embodied in strong ties, as in a hierarchically organized firm or network). In the middle there are loosely coupled networks (weak ties between autonomous entities, as in a joint venture or in a network). Organizational arrangements are both mechanisms that coordinate transactions, and vehicles that enable the transfer and exchange of information and knowledge (Cooke and Morgan, 1998). Therefore, organizational proximity has a positive effect on the processes of external learning. In fact, learning by interaction depends on the capacity to coordinate the exchange of complementary pieces of knowledge owned by a variety of actors within and between organizations (Boschma, 2005). Moreover, belonging to the same organizational context facilitates the mutual understanding among similar actors (Knoben and Oerlemans, 2006). However, too much organizational proximity can negatively affect learning and innovation. First, there is the risk of being locked in a specific exchange relations. Second, intra- and inter-organizational networks may evolve in closed and inward-locking systems. Third, excessive organizational proximity may be not able to provide the organizational flexibility required by innovation (Blanc and Sierra, 1999). Therefore, while too much organizational proximity is accompanied by a lack of flexibility, too little organizational proximity goes along with a lack of control increasing the risk of opportunism. A large body of literature claims that firms geographically proximate benefit from positive knowledge-based externalities. In fact, short distances bring people together and favour face-to-face contacts, thereby facilitating the exchange of tacit knowledge and the processes of external learning, e.g. learning by imitation and learning by interaction (Audretsch and Feldman, 1996). According to Antonelli (2000), the co-localization can play a major role in enhancing technological knowledge transfer because of its positive effects on both connectivity and receptivity caused by a variety of communication channels that can be activated in a geographical bounded area, such as factor market conditions, the features of

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‘‘ It is necessary to exploit dimensions of proximity different from the geographical one that allow the external knowledge sources to be reached by the technology districts. ’’

local industrial structure, the knowledge infrastructure of the local innovation system, the quality of local communication infrastructure, and the localization and technological strategies. Then, geographical proximity acts as a communication system between economic actors and then it can determine both economic and knowledge-based externalities. The former are mainly due to the reduction of transaction and transportation costs, the latter are mainly due to the reduction of communication costs, to the easy access to external knowledge, and to the increasing of knowledge spillovers. However, excessive geographical proximity may also be harmful for external learning and innovation (Boschma, 2005). In fact, when regions become too much inward locking, the learning ability of local actors may be weakened to such an extent that they lose their innovative capacity and cannot deal with competitive pressure. Spatial lock-in may be mitigated by establishing non-local linkages, which enable the access to the external sources of knowledge. Some argue that knowledge creation requires a balance or mixture of local (local buzz) (Storper and Venables, 2003) and non-local relations (global pipelines) (Owen-Smith and Powell, 2004). From the above review on the concept of proximity, it is possible to state that each type of proximity influences the effectiveness of external learning processes according to an inverse U-shaped relation. Moreover, proximity can be also considered as a dimension for clustering, since each proximity dimensions give rise to distinct types of cluster. In particular, three archetypes of cluster can be identified: pure geographical cluster, constituted by actors mainly connected by means of geographical proximity (e.g. industrial districts); pure organizational cluster, constituted by actors mainly connected by means of organizational proximity (e.g. multinational companies); and pure cognitive cluster, constituted by actors mainly connected by means of cognitive proximity (e.g. virtual professional communities) (Figure 1).

Proximity and external knowledge sources The forgoing analysis has evidenced that proximity can be considered as a resource for firms and districts competitiveness, acting as a multi-dimensional communication system that support the external learning processes. Furthermore, it is shown that organizational and cognitive proximity can bring together actors that are spatially distant each others, thus they can be used by the actors of technology districts to reach knowledge sources that are external to the geographical bounded area in which the district is localized. There are different ways in which actors can establish an organizational and cognitive proximity with external knowledge sources. In particular, organizational proximity depends on organizational arrangements, which range from formal arrangements to informal ones. Therefore, there is a positive relationship between organizational proximity and organizational arrangements existing among economic actors. Different types of arrangements can be identified according to the intensity and the scope of the interactions and may involve actors located in the same geographical area or actors located in different areas. The latter allow actors of technology districts to reach external knowledge sources and mainly involve: international strategic alliances, such as joint ventures, licensing agreements, distribution and supply agreements, R&D partnerships, and technical exchanges (Borys and Jemison, 1989; Hagedoorn, 2002); merger & acquisitions (Gammelgaard, 2005); international consortia (Niosi and Zhegu, 2005); foreign direct investments (Gong and Keller, 2003); and hierarchical dependences among the units of multinational companies (Veugelers and Cassiman, 2002).

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Figure 1 Representation of proximity’s dimensions and cluster archetypes

Cognitive proximity depends on the knowledge base characterizing economic actors, more heterogeneous the knowledge base of the system, lower the cognitive proximity. Notice that two actors are cognitively distant for two main reasons: i) they know different topics, ii) they have a different level of knowledge deepening on the same topic. Therefore, the cognitive proximity is affected by several elements such as the industrial sectors, reference markets, organizations size, number and skills of labour force, R&D expenditures, and number of hold patents (Feldman, 1999; Kaiser, 2002; Hu and Jaffe, 2003). Different mechanisms may increase the cognitive proximity among economic actors. These mechanisms mainly involve the mobility of workers, the recruitment of students graduated in highly qualified universities, the exchange of information by technical conferences and scientific and technological literature, reverse engineering, and industrial espionage (Maruseth and Verspagen, 2002; Mason et al., 2004; Audretsch et al., 2005). These mechanisms allow organizations to be cognitive close without any kind of organizational arrangements. Setting in motion the forgoing mechanisms, actors world-wide located increase their organizational and cognitive proximity and so doing they establish a communication channel in which knowledge and information flow. Then, organizational and cognitive proximity contribute to create global clusters, involving actors located in every region of the world (Lechner and Dowling, 2003).

The use of proximity in technology districts External knowledge sources are very relevant for technology districts competitiveness. Proximity, by means of its different dimensions, can be exploited as a resource for reaching the external knowledge. According to this, technology districts should be considered not just as a pure geographical cluster, characterized by actors with a high geographical proximity, but as a mix of three archetypes of cluster: geographical, organizational, and cognitive. This means that technology districts involve not only actors located in a geographical bounded area, which are geographically proximate and may be cognitively and organizationally proximate, but also actors external to the districts but linked with the actors located inside the districts through organizational and cognitive proximity. The whole system of actors can be defined

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as technology cluster, which is constituted by the district’s actors and by the actors external to the district but linked with it by means of organizational and cognitive proximity. In order to define the boundary of the technology cluster and trace the new geography of technology districts, it is needed to map the actors that belong to the system, both those linked through geographical proximity and those external to the geographical area and linked through organizational and cognitive proximity with the actors located inside the technology district. To cope with this aim, some proxies are identified to evaluate the geographical, cognitive, and organizational proximity existing among different actors. For the geographical proximity among actors their physical distance is considered. Therefore, actors that are co-located in the same bounded geographical area are geographically proximate and then are connected mainly through geographical proximity. For the organizational proximity among actors, hierarchical dependences, strategic alliances in terms of R&D partnerships, and research consortia are considered. In particular, focusing on the organizational links among actors located inside a technology district and actors word-wide located, it is assumed that the business units of a multinational company located in the district are connected mainly through organizational proximity to their parent companies located elsewhere. Furthermore, it is assumed that actors located in the district, such as firms, research centres and universities, that have developed a patent with other applicants located elsewhere are also connected mainly through organizational proximity with those applicants. Then, patent’s joint application can be considered as a proxy of R&D partnership. At last, actors belonging to research consortia are assumed to be connected mainly through organizational proximity. To evaluate the cognitive proximity among actors the patents’ citations are used. Citations are the proxy of knowledge spillovers and cognitive proximity largely used in the literature (Almeida and Kogut, 1999; Fung, 2003; MacGarvie, 2005; Coombs and Bierly III, 2006), because it means that organizations deal with the same topic and have a similar level of understanding of that topic. Then, it is assumed that all the actors, such as firms and research organizations, cited in the patents of a technology district’s actors are connected with them through cognitive proximity. The system of actors characterized by geographical proximity constitutes a geographical cluster and in particular they shape the boundary of a technology district. The system of actors characterized by organizational proximity constitutes an organizational cluster. The system of actors characterized by cognitive proximity constitutes a cognitive cluster. All the actors belonging to the three archetypes of cluster form the technology cluster.

A case study In this section an exploratory empirical research, based on a case study, is carried out, aimed at defining how different research organizations located in an actual technology district use proximity dimensions for reaching knowledge sources external to the district. The case study examines the district of Torino Wireless, which operates in the ICT industry and it is localized in the North-West of Italy. Both quantitative and qualitative data on the technology district have been collected in two different stages. At the first stage, to characterize the structure of the district, documents and data have been collected. At the second stage, a sample of research organizations located in the district has been selected, in order to identify the external economic actors linked through organizational and cognitive proximity with them. In particular, the research organizations have been selected adopting a reputational sampling technique (Laumann et al. 1983; Scott, 1991) based on their reputations as both main innovative players of the technology district and anchors of the local economy (see, for instance, Albino et al., 1998). Then, the following research organizations are considered: Politecnico di Torino, Universita` degli Studi di Torino, Universita` degli Studi del Piemonte Orientale Amedeo Avogadro, Istituto Superiore Mario Boella, Istituto Nazionale Elettrotecnico Galileo Ferraris, Istituto di Elettronica e di Ingegneria dell’Informazione e delle Telecomunicazioni, as public research

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organizations, Telecom Italia Lab, Motorola Technology Center, Centro Ricerche FIAT, Centro Ricerce RAI, as private research organizations, and Environment Park, Virtual Reality and Multimedia Park, Bioindustry Park, Parco Tecnologico e Scientifico Valle Scrivia, Tecnoparco del Lago Maggiore, as scientific and technological parks. For the sampled actors it has been evaluated: 1. the actors with which they have established formal organizational arrangements, in terms of research consortia; 2. the business units of their transnational network, namely subsidiaries (satellite units and parent firms); 3. the actors with which they have jointly developed an innovation, that are the other applicants of their patents registered at the European Patent Office (EPO)[1]; and 4. the actors cited in their patents. The measures at points 1, 2, and 3 allow the identification of the actors connected through organizational proximity. The measure at point 4 permits the identification of the actors connected through cognitive proximity. In the next subsections the case study is presented. In particular, first the main structural features of the district are described and then the actors linked with the research organizations are identified. The technology district of Torino Wireless The technology district of Torino Wireless (Table I) involves both multinational companies, such as FIAT, Telecom Italia, and Motorola, and small-medium enterprises, operating in the following fields: software technologies, multimedia technologies, microelectronic and optical devices, wireline and wireless technologies. Moreover, the district employs more than 53,000 workers and 2,000 researchers. The district is the first Italian technology district founded with the agreement of national and local institutions, universities, research centres, firms, and financial institutes. Table I Technology district of Torino Wireless Sector Region Multinational firms Universities Research Organizations

Anchor institution Founders

Number of firms Number of employees Investments plan Source: www.torinowireless.it

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ICT Piedmont Telecom Italia; Motorola; Fiat; ST Microelectronics; Alenia Politecnico di Torino, Universita` degli Studi di Torino, Universita` degli Studi del Piemonte Orientale Amedeo Avogadro Istituto Superiore Mario Boella, Istituto Nazionale Elettrotecnico Galileo Ferraris, Istituto di Elettronica e di Ingegneria dell’Informazione e delle Telecomunicazioni, Telecom Italia Lab, Motorola Technology Center, Centro Ricerche Fiat, Centro Ricerce RAI, Environment Park, Virtual Reality and Multimedia Park, Bioindustry Park, Parco Tecnologico e Scientifico Valle Scrivia, Tecnoparco del Lago Maggiore Fondazione Torino Wireless Ministero dell’Istruzione, dell’Universita` e della Ricerca; Regione Piemonte; Provincia di Torino; Citta` di Torino; Camera di Commercio, Industria, Artigianato e Agricoltura di Torino; Politecnico di Torino; Universita` degli Studi di Torino; Universita` degli Studi del Piemonte Orientale Amedeo Avogadro; Istituto Superiore Mario Boella; Istituto di Elettronica e di Ingegneria dell’Informazione e delle Telecomunicazioni del CNR; Istituto Elettrotecnico Nazionale Galileo Ferrarsi; Unione Industriale di Torino; Alenia; Fiat; Motorola; Telecom Italia; ST Microelectronics; San Paolo IMI; Unicredit 230 55,000 130 Me

The district is coordinated by the Fondazione Torino Wireless, which is an organization constituted by means of a framework agreement on May 2003 by both private and public actors, aimed at defining the district strategies, in terms of R&D activities, and at assuring the financial support to the district’s actors. The activity of the district is based on a five-year project, which counts the investment plan of 130 million of euro, sustained by the Italian government and by multinational companies headquartered in Italy. An important feature of the district is the great attention paid to the protection of the intellectual property. In fact, the project Intellectual Asset Management (AIM) has been launched, aimed at supporting firms in all the necessary activities to protect the intellectual property (patents, trademarks, utility models). Finally, it is important to underline the role played by the firm incubators of the Politecnico di Torino (I3P) and of the Universita` degli Studi di Torino (I3T), which favour the start-up of new innovative firms. Proximity dimensions of the Torino Wireless technology district. As regards the geographical proximity, all the economic actors (230) located in the geographical area characterizing the district are geographically proximate; therefore, they are at least connected by means of geographical proximity. Evaluating the formal organization arrangements (consortia), hierarchical dependences, and the R&D relationships for the sampled actors, we have identified the actors connected by means of organizational proximity, and their location. Evaluating the sampled actors’ patent citations, we have identified the actors connected through cognitive proximity and their location. In particular, we have distinguished four types of locations: regional, national, EU, and extra-EU. In Table II and Table III the number of actors linked with the technology district of Torino Wireless through organizational and cognitive proximity and their location is reported. By using these data, it is possible to map the actors involved in the activities of Torino Wireless’s district and connected by means of geographical, organizational, and cognitive proximity. These actors are both internal and external to the district geographical area and they constitute the technology cluster of Torino Wireless. The technology cluster of Torino Wireless Analysing the data reported in Table II, it is possible to notice that organizational proximity is mainly used to connect firms located within the regional geographical boundaries. In fact, Table II Number and location of actors connected through organizational proximity with the district of Torino Wireless Sample actors by type Firms Research organizations

No. of actors connected through organizational proximity Regional National EU Extra-EU Total 81 (75) 45 (39.2)

24 (22.2) 66 (57.4)

2 (1.9) 2 (1.7)

1 (0.9) 2 (1.7)

108 115

Note: Figures in parentheses are percentages

Table III Number and location of actors connected thorough cognitive proximity with the district of Torino Wireless Sample actors by type Firms Research organizations

No. of actors connected through cognitive proximity Regional National EU Extra-EU 3 (1.1) –

9 (3.4) 2 (6.2)

72 (27.4) 10 (31.2)

Total

178 (68.1) 20 (62.6)

262 32

Note: Figures in parentheses are percentages

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Figure 2 shows that the number of firms connected through organizational proximity decreases moving from regional to international locations. This result is consistent with the great degree of local connectedness characterising the district, due to the presence of many technological consortia. Regarding the research organizations, organizational proximity is mainly adopted to connect research organizations located within the national geographical boundaries. Figure 2 reveals how the number of organizational proximate research organizations increases moving from the regional area to the national one and, successively, decreases. Probably, this depends on the fact that the sample, mainly constituted by Italian research organizations, is connected with a great number of universities and research centres located within the Italian boundaries. On the contrary, the use of cognitive proximity as a means by which connecting economic actors to the district is positively related to their geographical distance from the district. In fact, as shown in Table III, the most part of firms (68.1 per cent) and of research organizations (62.6 per cent) linked to Torino Wireless through cognitive proximity are located outside Europe. Figure 3 indicates the relationship between the number of firms and research organizations cognitively proximate and their geographical location. Figure 4 reports how organizational Figure 2 Location and number of actors connected through organizational proximity

Figure 3 Location and number of actors connected through cognitive proximity

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Figure 4 Actors connected through organizational and cognitive proximity in the technology cluster of Torino Wireless

and cognitive proximity are used by the sample of research organizations as communication resources. Notice that the use of organizational and cognitive proximity as means by which connecting economic actors everywhere located is quite similar. In fact, 223 actors are linked through organizational proximity while 294 actors are linked through cognitive proximity. However, it is important to point out that the research organizations operating in the district use organizational proximity mainly to connect actors located in the Piedmont region, i.e. geographical proximate actors (Figure 5). On the contrary, the use of cognitive proximity is mainly related to connect actors located outside the district area (Figure 6), especially located outside Europe.

Conclusions In the paper the role of proximity as a resource for technology district competitiveness has been analysed. With this regard, taking into account three different dimensions of proximity, namely geographical, organizational, and cognitive, the positive influence of proximity on the effectiveness of external learning processes has been considered. Then, recognizing the importance of external knowledge sources to improve the technology district innovative performance, it has been shown that proximity, by means of its different dimensions, can be exploited as a resource for reaching external knowledge sources. In particular, organizational and cognitive proximity can bring together actors that are spatially distant Figure 5 Actors connected through organizational proximity in the technology cluster of Torino Wireless

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Figure 6 Actors connected through cognitive proximity in the technology cluster of Torino Wireless

each others, thus they can be used by the actors of technology districts to reach knowledge sources that are external to the geographical bounded area in which the district is localized. According to this, technology districts should be considered not just as a pure geographical cluster, characterized by actors with a high geographical proximity, but as a mix of three archetypes of cluster: geographical, organizational, and cognitive. Then, the notion of technology cluster has been proposed, which encompasses all the three dimensions of proximity, in order to define the whole system of actors involved in a technology district that are located both inside the geographical bounded area characterizing the technology district but also outside the area. In order to investigate if and how actual technology districts use proximity to reach external knowledge sources, some proxies have been defined to evaluate the geographical, cognitive, and organizational proximity existing among different actors. An empirical study on an Italian technology district, namely Torino Wireless, has been carried out. In particular, the role played by public and private research organizations located in the district in order to reach the external knowledge sources is studied. Two main results have been obtained by the empirical study: the identification of the actors connected to the technology district by means of geographical, organizational, and cognitive proximity, and second, the identification of the location of the actors belonging to the technology cluster. Results have shown how the technology district involves a large number of external actors in its activities, highlighting, then, the existence of the technology cluster arisen from the same district. Moreover, it seems to be relevant to underline how the district’s research organizations differently use organizational and cognitive proximity as communication resources. In fact, organizational proximity is mainly adopted to link regional and national actors. This can be due to the geographical proximity between the actors that facilitate the establishment of formal organizational arrangements (consortia, hierarchical dependences, and R&D partnerships). On the contrary, cognitive proximity is mainly adopted to connect actors geographically distant from the district. In particular, European and extra-European actors (Figure 5). In fact, as shown by Figure 2, the geographical distance from the technology district positively affect the number of actors linked to the district’s actors through cognitive proximity. Finally, some implications can be derived from this research. As regards the firm strategic behaviours, it seems particularly crucial to exploit all the three dimensions of proximity. To do this, firms should activate local and global links, with a certain degree of formalization. The latter may be direct links, with actors located outside the local area in which the firm

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operates, but also indirect links, with actors located in the same area but characterized by an international activity, e.g. universities, research centres, and multinational companies. In this regard, the technology district of Torino Wireless should increase its use of organizational proximity as a means of being connected with actors located outside the district area and then reaching external knowledge sources. To achieve this goal, the involvement in international R&D projects, the establishment of foreign multinational companies, and the relationships between firms and local and global research organizations should be favoured and supported by the local government. Moreover, the local governments should address their actions to sustain also local firms that are part of a technology cluster but not of a technology district. In fact, by increasing their connection and competitive position in the cluster, these may generate positive externalities in the local area, fostering the diffusion and sharing of knowledge and then acting as knowledge gatekeepers for the whole area. Further researches should be devoted to evaluating the impact of proximity on the innovative performance of technology districts. In particular, which combinations of the three proximity dimensions assure the best innovative performance should be identified.

Note 1. Notice that the EPO database not always provides the full list of the patents. In fact, when the patents number exceeds 500, only the last 500 patents are shown.

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Torre, A. and Gilly, J.P. (2000), ‘‘On the analytical dimension of proximity dynamics’’, Regional Studies, Vol. 34, pp. 169-80. Torre, A. and Rallet, A. (2005), ‘‘Proximity and localization’’, Regional Studies, Vol. 39, pp. 47-59. Tura, T. and Harmaakorpi, V. (2005), ‘‘Social capital in building regional innovative capability’’, Regional Studies, Vol. 39, pp. 1111-25. Veugelers, R. and Cassiman, B. (2002), ‘‘Foreign subsidiaries as a channel of international technology diffusion: some direct firm level evidence from Belgium’’, The European Economic Review, Vol. 48 No. 2, pp. 455-76. Wilkof, M.V., Brown, D.W. and Selsky, J.W. (1995), ‘‘When the stories are different: the influence of corporate culture mismatches on interorganizational relations’’, The Journal of Applied Behavioural Science, Vol. 31, pp. 373-88. Wuyts, S., Colombo, M.G., Dutta, S. and Noteboom, B. (2005), ‘‘Empirical tests of optimal cognitive distance’’, Journal of Economic Behavioral & Organization, Vol. 58, pp. 277-302.

Further reading Huber, G.P. (1991), ‘‘Organizational learning: the contributing processes and the literature’’, Organization Science, Vol. 2, pp. 81-115.

About the authors Antonio Messeni Petruzzelli is a PhD student in Business Engineering, Politecnico di Bari, DIMeG, Bari, Italy. He obtained the laurea degree in Business Engineering at the Polytechnic University of Bari. His research activities are focused on technology districts, logistics coordination, and system dynamics. He is the corresponding author and can be contacted at: [email protected] Vito Albino is a Full Professor in Business Engineering, Politecnico di Bari, DIMeG, Bari, Italy. He obtained the laurea degree in Mechanical Engineering. He was visiting scholar (1986) at the University of Cincinnati (USA) and visiting professor (1994) at the University of South Florida (Tampa, USA) from 1988 to 2000. He has taught Engineering Management at the University of Basilicata, Italy. He is now Full Professor of Innovation and Project Management at the Polytechnic of Bari, Italy. He is a member of several national and international associations and author of more than 70 papers published in national and international journals and conference proceedings in the fields of project management, operations management and firm clusters. Nunzia Carbonara is an Assistant Professor in Business Engineering, Politecnico di Bari, DIMeG, Bari, Italy. She obtained her PhD in Engineering of Advanced Production Systems at the Polytechnic of Bari, Italy in 1999. She was visiting research fellow (2001) at the University of Central England (Birmingham, UK). Her research interests are focused around geographical clusters and local development, including inter-firm networks. She is involved in many national and international research projects and associations and is author of papers published in national and international journals and conference proceedings.

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Knowledge-driven development indicators: still an eclectic panorama Katia Passerini

Abstract Purpose – The purpose of this paper is to highlight that research on the measurement of key indicators that represent drivers of the knowledge economy still spans several different, although interrelated, directions. The results of this review call for further integration of metrics through cross-disciplinary international, multinational and organizational partnerships that could reconcile and define de facto standards for the assessment of the drivers of knowledge-based growth. Katia Passerini, Hurlburt Chair and Assistant Professor, Management Information Systems, School of Management & College of Computing Sciences, New Jersey Institute of Technology, Newark, New Jersey, USA.

Design/methodology/approach – General review, literature review. The paper reviews extant literature and practical experiences in knowledge-based development assessments. Findings – The review finds that many institutions are still adopting a variety of approaches which are difficult to reconcile. Additional coordination efforts are required to overcome contextual and non-replicable approaches and, thus, increase standardization of metrics. Research limitations/implications – While the paper discusses limitations of extant approaches, it does not build (another) alternative theoretical solution. Rather it suggests actionable strategies that require a high level of international coordination. Practical implications – The paper shows the path and examples of multi-agency approach to achieve standardization. Originality/value – The value of the paper stems from its classification and review of selected approaches both at the country and organizational level. While it is motivated by a call for integration that is not novel to the field of knowledge management, it suggests that this coordination: needs to occur simultaneously both at the country and the organizational levels, whereby country approaches could inform and drive industry approaches; and needs to leverage international coordination models such as those of international standardization bodies. Keywords Knowledge economy, Knowledge management, Assessment, Intellectual capital, De facto standards, Measurement Paper type General review

An introduction to the knowledge economy The best-selling author and New York Times columnist, Thomas Friedman, describes the current global economy as ‘‘flat’’ and ‘‘interconnected’’ (Friedman, 2006). In such an economy, sustainable competitive advantage must thrive from creative, innovative and sophisticated use of knowledge and intellectual assets as strategic factors that enable dealing with the challenges of pervasive globalization. The technological developments of information and communication technologies and the advent of global interconnected social and technical networks are key drivers of the new global and complex economy. This knowledge-driven economy is one in which the creation, transfer and application of knowledge are key drivers of wealth creation (Hepworth et al., 2005). In the development literature, the definition of a knowledge-based economy refers to ‘‘an economy that makes effective use of knowledge for its economic and social development. This includes tapping foreign knowledge as well as adapting and creating knowledge for its specific needs’’ (Dahlman and Andersson, 2000).

DOI 10.1108/13673270710819843

VOL. 11 NO. 5 2007, pp. 115-128, Q Emerald Group Publishing Limited, ISSN 1367-3270

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The role of knowledge is increasingly important for developing and developed economies. A knowledge-based economy stems from the transformation of information into knowledge. At the macro-economic level, countries that display capabilities to continuously adapt institutional, information and innovations systems through incentives that support human resource development are generally more effective at stimulating and reinvigorating their stock of knowledge (Teece et al., 1997; Teece, 2000). While academic institutions, governments, businesses and societies appreciate the benefits and potential returns of investments stirring knowledge-based growth, identifying a generally accepted and replicable framework that can elicit the true value of knowledge assets remains a major challenge. Several researchers argue that it is critically important to define specific and overarching metrics that can account for the value-creation of knowledge-based work. Others (Dorothy Leonard in Chatzkel, 2004) recognize that we need some flexibility and dynamisms when we try to evaluate knowledge assets. Leonard alerts that narrow and specific definitions and operationalizations of today’s knowledge-related metrics may not offer the capabilities for renewal that are generally needed in highly changing environments, like those of the knowledge economy. This dynamic view recognizes that by defining key capabilities more generically ‘‘you have more room to morph, to change, and to adapt’’ (Chatzkel, 2004, p. 26). The paper starts with a broad overview of the knowledge economy and the interrelated knowledge creation processes subsiding knowledge management at the national and organizational level. It then provides examples of knowledge-driven measurements and knowledge-value assessment in selected countries, international development groups, and specific organizations. It concludes with a call for an integrated effort to achieve standardization of measurements, including leveraging lessons learned from multiple stakeholders.

Characteristics of knowledge economies and overlapping frameworks Knowledge-rich economies are characterized by products and services that portray specific economic behaviors and patterns. Contrary to traditional resource-limited economies (agricultural and industrial economies) that display decreasing returns to scale from land and capital resources utilization, knowledge economies display increasing returns (Arthur, 1996). Knowledge is not consumed by its use, but it grows with its utilization and application. This economic pattern has implications for development as it decouples the causal relationship among the resource endowment of a country and its knowledge growth potential (see new growth theories by Romer, 1986; and human capital theories by Grant, 1991, 1996; Nonaka, 1994). A knowledge economy grows when knowledge is shared and circulated. Growth is a dynamic and fluid process that returns higher value through managing the process of knowledge identification, organization, transfer, and application (Alavi and Leidner, 2001). The dynamics of the knowledge management lifecycle have been amply discussed by Nonaka and Takeuchi (1995). Nonaka introduces the concept of the knowledge spiral and defines an evolution of knowledge through concentric circles that involve individuals, groups, organizations and inter-organizational resources. Individuals’ socialization of knowledge with groups enables the combination of experiences and the codification of

‘‘ The technological developments of information and communication technologies and the advent of global interconnected social and technical networks are key drivers of the new global and complex economy. ’’

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personal (tacit, implicit) knowledge into explicit know-how (explicit and codified knowledge). The subsequent externalization of a firm’s codified knowledge enables knowledge transfer across organizations. The cycle returns to a new level of tacit and internalized knowledge which re-starts another knowledge creation cycle. Figure 1 builds on Nonaka’s SECI model (socialization, externalization, combination and internalization) by showing the flows and transformation of knowledge as it moves from individuals to groups, organizations and inter-organizations. It also presents key processes (grouped herein under Identification, Organization, Transfer, and Application – IOTA) of the knowledge lifecycle, highlighting key outcomes of each process step (capabilities, artifacts, knowledge-intensive products and services). Although the concept of knowledge-spiral has been originally discussed in organizational contexts, the flows represented in Figure 1 can be seamlessly applied to a national level-analysis. While the actors at the national level may vary compared to organizations (involving citizens; groups and Communities of Practice – CoP; governmental and para-governmental entities; and international organizations), the key processes and theories of knowledge creation (Nonaka, 1994, 1995) still stand. Applying the concept of the knowledge spiral to nations, a knowledge economy identifies the resources and capabilities of the knowledge growth lifecycle. It represents systems that codify and map existing capabilities (to establish a baseline against target points). It promotes access to knowledge and motivation to share existing capabilities – for example by protecting intellectual property to foster innovation. It enables knowledge transmission and diffusion through the creation of opportunities for sharing experiences (with supportive information and communication technologies policies and investments). Lastly, a knowledge economy promotes the generation of new knowledge through learning, education and application.

Knowledge economies, knowledge assets and intellectual capital In the knowledge economy, for knowledge to attain its value it needs to be contextualized and embedded in physical products and processes (patents, trademarks, intellectual property, but also procedures, rules and heuristics). Human capital and resources are the Figure 1 Organizational and national level knowledge spiral and IOTA processes

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‘‘ Applying the concept of the knowledge spiral to nations, a knowledge economy identifies the resources and capabilities of the knowledge growth lifecycle. ’’

key fundamental holders and drivers of knowledge creation and, therefore, need to be nurtured, recognized, trained and educated (Bartel, 1992). However, the potential value of the wealth of human interactions and knowledge creation driven by the people and their social network is hard to quantify. Knowledge is measurable only when its implicit or tacit components have been made explicit through codification and application. But the wealth, possibilities, and potential of the tacit dimensions are potentially higher than the explicit and measurable dimensions (Sveiby, 1997). This dichotomy permeates the difficulty in assessing knowledge and intangible assets and explains the eclectic list of methods and procedures that have surfaced to identify the value of knowledge management and, more specifically, identify the value of knowledge assets in nations and organizations. Related to the notion of knowledge economy is the concept of national knowledge assets defined as the intangible assets of a country that have significant impact on a country’s potential growth and progress (Boisot, 1998; Malhotra, 2003a). Malhotra further defines knowledge assets or intellectual capital as the hidden assets of a country that underpin and fuel a country’s growth. As knowledge becomes a key production factor it is important to understand the value of knowledge capital. Many countries understand how value creation and GDP growth is spurred by service and knowledge-based output in addition to manufacturing output (Guthrie and Petty, 2000). However assessment of national economic performance is still tied to traditional factors of production (land, capital, labor) rather than a thorough understanding of the value of knowledge assets, which are assets governed by the law of increasing returns’’ (Arthur, 1996). If assets can be described as physical claims to future benefits (potentially generating value or cash flows), intangibles assets represent the ‘‘non-physical’’ claim of future benefits and values (Value Based Management.net, 2006). These assets can lead to the production of goods and services that display a high-knowledge content and value (for example, high-technology products; consulting services, etc.). The value of knowledge assets is not elicited by current accounting practices and intangible assets continue to represent the ‘‘hidden’’ value of a firm (Edvinsson and Malone, 1997; Stewart, 1997) or a country. While assessing the hidden value/s is critical, this assessment presents many challenges and naturally leads to multiple approaches, as described in the next sections.

The international focus on knowledge-economies Country-specific and regional efforts The understanding that the creation of knowledge permeates the entire economic and social environment of nations has led several countries and international development institutions to focus on strategies for enhancing knowledge management programs at the macro-economic level. For example, the regional Bureau for Arab States at the United Nations Development Programme (UNDP) supported a study of intellectual capital (Bontis, 2004) to benchmark Arab countries’ creation of national wealth based on the combination of financial capital, human and structural capital. Bontis found that national human capital, process capital, market and renewal capital explain about one fifth (R 2 ¼ 20.9 percent) of the variance of national financial capital, thus establishing a link between non-monetary and monetary results (Bontis, 2004). The study also highlights the importance of cultural and

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process changes that foster knowledge creation as an essential ingredient for public and private institutions in the Arab states to succeed in the knowledge-based economy. Malhotra (2003a) explains that leaders of national economies are trying to find reliable ways for measuring knowledge assets to understand how they relate to future performance. Several international development organizations – such as the World Bank, the Organization for Economic Cooperation and Development (OECD), the United Nations, etc. – have been investing and financing knowledge management projects both internally (within their divisions and operational units) and externally, in the countries they represent. These projects span over the entire knowledge management lifecycle: from knowledge identification (definition, assessment), to knowledge organization, transfer and application. At the macro-economic level most of the efforts have started from analytical assessments of a country’s knowledge endowments. For example, Malhotra (2003a, b) represents efforts from the Nordic European countries to identify knowledge assets and the value of intellectual capital. The Danish and Norwegian governments have sponsored efforts to identify a financial reporting system that would elicit companies’ intellectual capital assets to be included in firms’ annual reports. Guthrie and Petty empirically evaluated mechanisms for reporting intellectual capital metrics in Australia (Guthrie and Petty, 2000). They concluded that reporting activities are still piecemeal efforts and are not consistently embedded in an overarching framework. They call for further developments of best practices within Australia to better compare with firms in other nations, and most notably in European countries. In Europe, Sweden has been at the forefront of establishing formal measurement criteria to document and report on a country’s competitiveness. The local government and Stockholm University adapted the Skandia Navigatore (Edvisson and Malone, 1997) to quantify Sweden’s key indicators for success. Bounfour (2003) discusses a methodology adopted to benchmark various European countries on the basis of an instrument that assesses the dynamic value of intellectual capital (IC-dVALw). Bounfour applies this methodology to appraise resources, processes, outputs and assets of a number of countries in Europe, compared to the USA and Japan, and argues that this approach is suitable to evaluate performance both at the micro-economic and the macro-economic level. However, he also recognizes a number of limitations related to generalizations (such as the identification of simplistic proxies for intellectual assets measurement) and recommends continuing cross-sectional process comparisons at intermediate levels (clusters, regions, public organizations or consortia of companies). Israel, another country that focused on evaluating intellectual capital very early, implemented a measurement approach based upon the Skandia Navigatore model developed and applied by Edvinsson (Edvisson and Malone, 1997; Pasher and Shachar, 2005). Edna Pasher, a leader in the knowledge management movement in Israel and an active participant in the community of intellectual capital researchers, identified knowledge management as a critical success factor for organizational renewal. Realizing the implications of knowledge strategy at the national level, she co-authored a report called ‘‘The Intellectual Capital of the State of Israel 1998: A look at the future’’ (Pasher, 1998) to consider the tangible and intangible assets of Israel, namely: financial capital, process capital, market capital and renewal and development capital. The financial and intellectual capital indicators defined in the report provide a benchmark of the progress of Israel compared to other industrialized nations of the world, and explain the top priority role that learning and education play in the country. Ante Pulic (Pulic, 2005) led research studies on the measurement of intellectual capital performance in Croatia and other European countries. He developed a ‘‘Value Creation Efficiency Analysis,’’ a measurement system that links performance of key physical, financial, and intellectual capital resources to financial data. His work recognizes the value of intellectual capital by bridging the gap between the new economic drivers and the traditional accounting standards and provides a new way to look at the national economy’s

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performance. His research focuses on Croatia as a case study and compares measures of intellectual capital efficiency to other Eastern European countries (such as Slovenia, Hungary, the Czech Republic, and Poland). Pulic’s work offers important national and regional insights into measuring the value of intellectual capital. Many other countries have focused on projects directed at identifying measures of knowledge assets and economies for comparative purposes. In Japan and China, researchers (Masuyama, 2005) discuss an East Asian agenda for the transformation of Asian economies into knowledge-based economies (KBEs) through a strong focus on innovation and R&D, education, and the development of international production networks beyond the traditional expansion drivers represented by low-cost manufacturing. Additional studies and reports in the United Kingdom and Poland show a significant interest in micro and macro-drivers. Some case studies focus on highlighting key knowledge-creation drivers from regional communities (Karlsson and Martinez, 2005). International development efforts International development institutions (IDIs) have launched numerous assessment efforts to identify the value of knowledge in economies. Figure 2 presents a summary of the qualitative and quantitative methodologies adopted by development institutions, non-profit organizations and governments to assess countries in their capabilities as knowledge-intensive nations based on type of the evaluation and the scope of the knowledge management programmes. Qualitative methods with regional and national symposia have been implemented by the World Bank in the late 1990s based on the national knowledge assessment model elaborated by the US National Research Council (National Research Council et al., 1996). The World Bank and developmental organizations that have since then undertaken large scale initiatives in knowledge management and measurement, mostly focused on international benchmarking and the use of comparative scorecards (Malhotra, 2003a; Passerini, 2003). For example, the World Bank uses the KAM (Knowledge Assessment Model) a widely available knowledge management measurement framework thanks to its accessibility and ease of use online. The KAM evaluates countries based on their relative Figure 2 International and national approaches to knowledge and intellectual capital evaluation

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standing and structural/qualitative indicators of performance on four areas that drive knowledge development. The model synthesizes drivers into scorecards and indexes such as a Knowledge Economy Index (KEI) – the average of the performance scores of a country or region in all four KE pillars (Economic Incentives Regime, Education, Innovation, and Information Communications & Technology) – and the Knowledge Index (KI) – the simple average of the performance of a region or country in Education, Innovation and Information Communications & Technology. In addition to the quantitative evaluation methods embedded in the KAM model, the World Bank has also led qualitative and case study research in knowledge benchmarking with local projects and regional symposia in several countries, for example in the Pacific Island economies (Aubert, 2005). The Organization for Economic Cooperation and Development (OECD) is focused on definitions of knowledge-based economy and knowledge assets that include a particular attention to human capital. OECD (2003) defines human capital as the ‘‘knowledge, skills and attributes derived from education, training and experience that represent some our most valuable resources.’’ It also extends the human capital into social capital, a more recent perspective on the importance of ‘‘established social relationships, norms of behaviors and mutual trust in many kinds of social and economic endeavors.’’ The OECD supports efforts for the development of a unified model for measuring social capital. The European Union undertakes multiple initiatives to define measurement models for knowledge management. Veugelers (2005) reviews the set of policy actions and indicators that European Union nations have agreed to monitor to track the performance of member states towards ‘‘the most dynamic and competitive knowledge-based economy in the world capable of sustainable economic growth with more and better jobs and greater social cohesion’’ as well as ‘‘an increasing respect for the environment’’. The EU indicators were identified at the European Council of March 2000 in Lisbon, when the EU launched a ten-year long comprehensive set of integrated structural reforms to become the most competitive knowledge-based economy by 2010. However, the EU assessment model is only a benchmark that needs to be preceded by profound reforms addressing the challenges of an aging population, enlargement and globalization of the European Union. Different agencies within the United Nations are focusing their efforts in defining and identifying drivers for knowledge development in the countries they serve. Parallel efforts are being conducted with the objective to measure information and communication technologies (ICT) development, innovation and e-commerce drivers. In this effort, a plethora of measurement models have been proposed. Most of the time, these models overlap drivers and indicators, and provide different synthetic formulas. Despite these differences, they all start from the same number of factors that are key inputs to knowledge development: connectivity, access, policy environment, usage, social and cultural infrastructure and education/literacy. The United Nations Conference on Trade and Development (UNCTAD) is also an active player of an international effort to define development indices. In the 2003 Report (UNCTAD, 2003) a list of key variables that concur to form ICT indices are identified also based on their contribution to knowledge creation. The UNCTAD report defines synthetic measures and attempts to identify the correlation among a number of related indicators. It proposes a specific country ranking based on ICT endowment (a prerequisite for the knowledge society). It relies on multiple frameworks, but gathers the majority of the country data from the International Telecommunication Union (ITU).

The organizational focus on knowledge evaluation Although the focus of this paper is on knowledge-based development at the national and international level, the eclectic panorama presented for countries and IDIs mimics the eclectic panorama characterizing firms and industry levels. Therefore, it is important to briefly highlight key aspects (such as the notions of intellectual capital and intangible assets) of organizational-level measurements. Starting from the mid-1990s, several researchers and practitioners have tried to identify models to associate specific financial value to knowledge

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assets (defined as the intangible assets) of organizations. Historically, intangible assets were classified as the ‘‘goodwill’’ of the firm (Malhotra, 2003a). Other views (Davenport and Prusak, 2000) have defined intellectual capital as the difference between the market value of the firm and its book value. Other researchers such as Kaplan and Norton (1996), Sveiby (1997), Bontis (1999), Stewart (1997), Brooking (1996) and Roos et al. (1997) have moved beyond tying the value of knowledge asset to financial performance and have proposed a larger set of non-monetary measurement models focused on eliciting people and processes values. Figure 3 displays a list of measurement approaches that have been proposed to identify the value of intangible assets. Rather than being divided into qualitative and quantitative methods, these approaches are mostly quantitative (or based on qualitative judgments transformed into quantitative metrics) and have been grouped by Sveiby (2001) into monetary and non-monetary methods depending on their reliance on traditional and emerging accounting/financial standards. While for a comprehensive review of the measurement mechanisms, we refer to Sveiby (2001) and Malhotra (2003a), some of these measures are briefly discussed in more details as they are the basis for many national level adaptations. The Intellectual Capital Index (IC-Index) is a broad and higher-level non-monetary approach that attempts to consolidate different indicators into a single index and correlate the changes in intellectual capital with changes in the market (Roos et al.,1997). The IC-Index value lies in its measurement of changes in IC stocks. Bontis et al. (1999) suggest that changes in an IC-Index reflect changes in the underlying drivers of future earnings potential. Among other non-monetary methods, the Skandia Navigatore (Edvisson and Malone, 1997); the Balanced Scorecard (Kaplan and Norton, 1992, 1996, 2000); and the Intangible Assets Monitor (Sveiby, 1997) have been widely utilized. The Balanced Scorecard approach is largely implemented in other areas beyond knowledge management. The Balanced Scorecard (BSC) is a reporting model that focuses on assessing organizations on multiple elements that can also be related to the firm’s knowledge endowment. The BSC includes a customer perspective; a growth and learning dimension; a business processes perspective; and a financial perspective. Figure 3 Organizational approaches to knowledge and intellectual capital evaluation

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The Skandia Navigatore and the Intangible Assets Monitor are closely related to (and precede) the BSC. The Intangible Assets Monitor (Sveiby, 1997) focuses more on personnel-based measures, both internal and external. Sveiby looks at growth and renewal of the external structure (market share and customers); the internal structure (IT investments, R&D, and personnel behaviors); and the personnel competence (turnover average, competency levels). For each of these variables, Sveiby proposes an evaluation of growth, renewal, efficiency and stability metrics. The Skandia Navigatore (Edvisson and Malone, 1997) also focuses on structural, human, customer and organizational capital and it proposes a very large set of variables (91 intellectual þ73 traditional metrics) to assess the value of knowledge assets (Malhotra, 2003a). The monetary methods, such as Tobin’s Q, the Earned Value Added (EVA), the Calculated Intangible Value (Stewart, 1997) and the market-to-book value measures are advanced financial measures that attempt to associate a specific economic value to intangible assets. However, they are limited to a financial perspective (not including social and human factors) and are based on a preliminary assumption of a direct causal relationship between the financial measures (gross margin, returns on assets, etc.) and the intangible company resources. They do not take into account contingency factors that can also impact company performance. They are broad and holistic measures that look at firms’ activities in their entirety. More specialized and focused monetary methods include approaches such as Human Resource Capital Accounting (HRCA). According to Sackmann et al. (1989) human resource accounting enables quantifying the economic value of people in the organization based on three models: costs; human resource value; and monetary values. However this model has limited application because of issues of reliability and generalization of the measurement framework. Annie Brooking’s model, the Technology Broker (Brooking, 1996), looks at intellectual capital as the combination of market assets; human-centered assets; intellectual property assets; and infrastructure assets. This approach starts with a diagnostic process whereby organizations answer questions that make up an intellectual capital indicator. Brooking suggests three measurement models to help calculate the value of intellectual capital: 1. the cost approach, which is based on assessment of replacement costs; 2. the market approach, which uses market equivalents to assess value; and 3. the income approach, which assesses the income producing capability of the asset. This approach helps to quantify intellectual capital and leverages a mix of quantitative and qualitative methods whereby the questions asked in the intellectual capital audit process can be easily transformed into Likert scales.

Graphical approaches: bridging qualitative and quantitative analyses Knowledge assessment researchers at the macro and micro-level of analysis continue to agree that monetary and quantitative approaches need to be supplemented by qualitative analysis and triangulation. Unstructured surveys, interviews, workshops and focus groups activities need to support quantitative data collection. The use of qualitative approaches and the collection of anecdotal evidence are particularly important at the outset of a knowledge management initiative. When exposure and competences are still low, informal interviews, and the famous ‘‘water-cooler discussions,’’ may in fact support a better understanding of the impact of knowledge management and the effective transfer of knowledge among employees in an organization. The Technology Broker’s IC audit (Brooking, 1996) is an example. Knowledge assessment approaches have been criticized for lack of focus on soft factors such as organizational culture as drivers of knowledge sharing processes in organizations and countries. Qualitative approaches add a positive twist to knowledge assessment as they

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are usually dynamic and lead to further actionable initiatives. Several of the approaches discussed earlier, particularly the quantitative ones, are limited in their predictive capabilities. Graphical and belief-based analytical approaches can be applied to identify a dynamic and predictive model (Bayesian network analysis). Bayesian network has been applied, for example, to the knowledge assessment model (Passerini and Cakici, 2004). Bayesian networks and decision graphs can be used to map the relationships between the KAM variables, the knowledge drivers, and the resulting country knowledge potential (dependent variable). The network structure illustrates the relationship among variables and discovers the interactions within the underlying dataset. The power of a Bayesian simulation model is that of assessing the impact on all knowledge activities caused by country level economical, social, and political change (expressed through sets of probability distributions). Bayesian models can be used to determine the impact of a change in a variable caused by a political decision, a cultural norm shift, an economic policy decision, a trade law and educational system change on a country’s knowledge index. Extending this methodology to incorporate the time-effect on such data using dynamic Bayesian models may reveal hidden economical, cultural and political variables that play a role in a country’s knowledge-based development.

Open issues and forward-looking initiatives A number of issues emerge from the review presented in this paper. First and foremost, the understanding that while knowledge management and intellectual capital may generate competitive advantage through intangible assets, organizations do not understand their nature and value (Bontis, 1999). Carrillo (2002) recognizes that while IC has become one of the most fertile areas of KM, to what extent the basic dimensions describing knowledge-based value generations have been grasped remains an open question’’ (Carrillo, 2002, p. 17). All the efforts that have been developed to date seem to be far from emerging as a single common set of metrics. The high number of alternative models presented in this review shows that there is no agreement on national and organizational approaches for evaluating knowledge assets and knowledge management programs. There are no universal best tools (Bontis, 1999). While it is difficult to define which model should be followed, discussions about standardization and international measurement models should focus on providing highly accessible and user-friendly results. The World Bank interactive scorecards approach offers an example of user-friendly and accessible systems to share information about indicators relating to knowledge indexes. Making the underlying data set easily available for research and benchmarking would encourage further analysis on correlations and predictive capabilities of the indices. Such visibility and access will be difficult to achieve in the business arena (firms might not be willing to disclose internal data) but it should be an easier proposition for international development institutions (and one that should comply with their development agenda). The United Nations has recently been progressing in the strategic planning of widespread and coordinated development, particularly in the area of (and through) knowledge management. The UN agencies are now building the right framework to replicate lessons learned in the World Bank’s internal and external knowledge management model and programmes. The ‘‘One United Nations’’ is a global initiative coordinated by the UN Chief Executive Board (CEB) that envisions the renewal of a united development agenda deployed using common and accessible communication platforms. Among the common objectives, the need for deepening the understanding and managing knowledge better is the first agenda item (CEB Report, 2005). Some of the actionable items include:

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defining common, more reliable, widely accessible and user-friendly country data (including strengthening data collection and analysis techniques in member countries);

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implementing a common strategy in the development and utilization of information and communication technologies; and

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promoting a common knowledge creation and learning culture.

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While the last two bullet points refer to the internal management of knowledge initiatives; the first bullet clearly implies the implementation of an overarching and integrated framework for the definition of critical measurement methods. As highlighted in the Millennium Development Goals – MDGs – (United Nations, 2006), these methods will need to integrate social objectives (and frameworks) into economic decision making (CEB Report, 2005). This notion is being translated internally into the deployment of balanced scorecard approaches to organizational performance that are well underway in selected agencies, such as the United Nations Population Fund (UNFPA). If such integrated efforts are successful, macro-economic frameworks could play an important role in shaping firm-wide approaches. For example, a country-driven approach could be extended to organizations to leverage lessons learned (particularly in the area of results standardization) and define models for businesses that are aligned to national measures. It may not be useful to continue to separate the ‘‘macro’’ and ‘‘micro’’ when in fact the country knowledge assets and potential can drive (and be driven by) the local organizational framework. In such a scenario, international development institutions could define opportunities to consolidate industry measures as piloted by the Nordic European governments. Even further, international organizations could lead the definition of a common tri-lateral research and implementation framework that brings together governments, academia and businesses. While we should continue to debate and compare distinct aspects and frameworks, it will be important to identify ways for effectively applying and standardizing these frameworks so that they can drive common results. Multilateral industry, government and academic partnerships could emerge in a similar model followed by international standardization bodies. Some examples are the International Organization for Standardization (ISO) and the International Electrotechnical Commission (IEC), which represent private and voluntary organizations. Other examples include US-based organizations that are developing de facto global standards that are increasingly being accepted internationally. These are usually private and public consortia in specific technical areas such as wireless telecommunications, e-commerce, Web services, etc. Such multilateral efforts in the field of knowledge management could be a step forward in a consistent and common direction.

Summary and conclusions The evaluation efforts herein described have been focused on identifying different measurement models starting from typical and traditional performance indicators to include (from the millennium onwards) measures of human and social development. This transition has been the result of a learning process where developmental organizations have realized that social and human processes are the key factors of the knowledge growth cycle. Regardless of these developments and inclusion of human and social capital metrics in both international and organizational measurement frameworks, there is still a need for more standardization in a very eclectic panorama of measurement and approaches. Our review finds that many institutions are still adopting a variety of approaches which are difficult to reconcile. In a field that stems from the notion of leveraging lessons learned, existing models show limited capabilities for replication and propose similar, yet not generalizable, approaches. Additional coordination efforts are required to overcome contextual and non-replicable approaches and, thus, increase replicability and reliability of comparative analyses. Some of these efforts have been briefly highlighted in the paper, with the hope that they will contribute to the shaping of a common research and implementation agenda.

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Malhotra, Y. (2003a), ‘‘Measuring knowledge assets of a nation: knowledge systems for development’’, keynote address for the United Nations Advisory Meeting of the Department of Economic and Social Affairs, Division of Public Administration and Development Management, New York, NY, 4-5 September. Malhotra, Y. (2003b), ‘‘Knowledge assets and intellectual capital measurement models’’, working paper, Syracuse University School of Management. Masuyama, S. (2005), ‘‘Japan and other East Asian economies under the knowledge-based economy’’, in Bounfour, A. and Edvisson, L. (Eds), Intellectual Capital for Communities, Elsevier, New York, NY, pp. 165-93. National Research Council, Committee on Knowledge Assessment and Office of International Affairs (1996), Prospectus for National Knowledge Assessment, National Academy Press, Washington, DC. Nonaka, I. (1994), ‘‘A dynamic theory of organizational knowledge creation’’, Organization Science, Vol. 5 No. 1, pp. 14-37. Nonaka, I. and Takeuchi, H. (1995), The Knowledge-creating Company, Oxford University Press, New York, NY. OECD (2003), Science, Technology and Industry Scoreboard 2003 – Towards a Knowledge-based Economy, available at: www1.oecd.org/publications/e-book/92-2003-04-1-7294/ Pasher, E. (1998), The Intellectual Capital of the State of Israel 1998: a Look to the Future, Edna Pasher and Associates, Herzliya. Pasher, E. and Shachar, S. (2005), ‘‘The intellectual capital of the State of Israel’’, in Bounfour, A. and Edvisson, L. (Eds), Intellectual Capital for Communities, Elsevier, New York, NY, pp. 139-49. Passerini, K. (2003), ‘‘Knowledge assessment in developing/developed economies: frameworks and implementation examples’’, Proceedings of 9th American Conference on Information Systems (AMCIS), 4-6 August, Tampa, FL. Passerini, K. and Cakici, K. (2004), ‘‘A Bayesian approach for knowledge management evaluation’’, Proceedings of FUBUTEC (Future Business Technology Conference), 12-13 March INSEAD, Fontainebleau, France. Pulic, A. (2005), ‘‘Value creation efficiency at national and regional level’’, in Bounfour, A. and Edvisson, L. (Eds), Intellectual Capital for Communities, Elsevier, New York, NY, pp. 197-211. Romer, P.M. (1986), ‘‘Increasing returns and long-run growth’’, The Journal of Political Economy, Vol. 94 No. 5, pp. 1002-37. Roos, G., Dragonetti, N.C. and Edvinsson, L. (1997), Intellectual Capital: Navigating in the New Business Landscape, Macmillan, London. Sackmann, S.A., Flamholtz, E.G. and Bullen, M.L. (1989), ‘‘Human resource accounting: a state of the art review’’, Journal of Accounting Literature, Vol. 8, pp. 235-64. Stewart, T.A. (1997), Intellectual Capital: The New Wealth of Organizations, Doubleday, New York, NY. Sveiby, K.E. (1997), ‘‘The intangible assets monitor’’, Journal of Human Resource Costing and Accounting, Vol. 2 No. 1, pp. 73-97. Sveiby, K.E. (2001), ‘‘Methods for measuring intangible assets’’, available at: www.sveiby.com/Portals/0/ articles/IntangibleMethods.htm Teece, D.J. (2000), Managing Intellectual Capital, Oxford University Press, Oxford and New York, NY. Teece, D.J., Pisano, G. and Shuen, A. (1997), ‘‘Dynamic capabilities and strategic management’’, Strategic Management Journal, Vol. 18 No. 7, pp. 509-33. UNCTAD (2003), Information and Communication Technology Development Indices, United Nations, New York, NY and Geneva. United Nations (2006), The Millennium Development Goals Report, available at: http://unstats.un.org/ unsd/mdg/Resources/Static/Products/Progress2006/MDGReport2006.pdf Value Based Management.net (2006), ‘‘Intangible assets’’, available at: www.valuebasedmanagement. net/faq_what_are_intangible_assets.html

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Veugelers, R. (2005), ‘‘Assessing innovation capacity: fitting strategy, indicators and policy to the right framework’’, Proceedings of the Conference on Advancing Knowledge and the Knowledge Economy, National Academies, 10-11 January, Washington, DC, available at: http://advancingknowledge.com/ drafts/Veugelers-NAS-Wash-paperv2.doc

About the author Katia Passerini is an Assistant Professor and the Hurlburt Chair of Management Information Systems at the School of Management of the New Jersey Institute of Technology (NJIT) where she teaches courses in MIS, knowledge management and IT strategy. She has published in refereed journals and proceedings (Communications of the ACM, CAIS, Society and Business Review, International Journal of Knowledge Management, Computers & Education, Journal of Educational Hypermedia and Multimedia, IEEE Internet Computing) and professional journals (Project Management Network, Cutter IT Journal, Cutter Benchmark Review), particularly in the area of computer-mediated learning, IT productivity and knowledge management. Her professional experience includes multi-industry projects at Booz Allen Hamilton and the World Bank, where she worked on information technology projects in Europe, North America and the South Pacific. Dr Passerini earned both a MBA and a PhD degree in Information & Decision Systems from the George Washington University, USA. She can be contacted at: [email protected]

To purchase reprints of this article please e-mail: [email protected] Or visit our web site for further details: www.emeraldinsight.com/reprints

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The Austrian National Knowledge Report Ursula Schneider

Abstract

Ursula Schneider is Dean of the Faculty of Economics and Social Sciences, University of Graz, Graz, Austria.

Purpose – The purpose of this paper is to examine the transferability of the intellectual capital approach methodology from the corporate to the national level. Just as financial measures fall short of covering major value drivers at the corporate level, gross national product does not sufficiently reflect future potentials to grow and to contribute to a globalising economy with trans-national value chains, value cycles and value networks. There have been many efforts to develop core indicators of economic performance, such as ratings of competitiveness, global embeddedness, high-tech exposure, spending in R&D, competencies to read and calculate of students and many more. The project team concluded that those measures showed two major weaknesses: they lack an overall framework and thus an analysis of their interplay and they overemphasise the reporting in relation to the development or management aspect of the factors considered by the respective approaches. Design/methodology/approach – The team aspired to create a prototype knowledge report for Austria as part of a prototype procedure, the ‘‘Agenda Knowledge’’, which should fuel efforts of the country to change its role in the emerging knowledge society from imitator to inventor. The endeavour was based on the Lisbon Agenda of the European Union, which integrates economic competitiveness and social cohesion. A trans-disciplinary design was applied which is best described as action research and makes use of many different methods at different stages of the process; all methods were evaluated in terms of their effectiveness, efficiency and social acceptance. Findings – Results of the pilot project comprise a prototype national knowledge report as part of an overarching prototype procedure which is able to deal with incommensurabilities at the level of visions and ends as well as with different paradigms at the level of end-mean relations in a political rather than in an academic manner. Originality/value – First process-oriented approach to the development and monitoring of intellectual capital at the national level. Keywords Intellectual capital, National standards, Austria, Assets, Knowledge transfer Paper type Case study

Introduction: roots of the initiative and structure of the paper The private-public Austrian research corporation Seibersdorf (ARCS) has acted as a pioneer of intellectual capital (IC) reporting by developing a knowledge report at the corporate level as early as 1999 (Schneider and Koch, 1999). Inspired by the work of Swedish pioneers (e.g. Sveiby, 1997) the approach has spun off other initiatives with its basic conception of combining structural and process elements and of linking IC development to strategy by introducing visions and objectives. Ever since then ARCS has been reporting its IC-related activities (ARCS, Wissensbilanzen 1999-2005). The model was adopted by the legislator when parliament reformed the Austrian university system. Austrian universities are obliged to deliver knowledge reports and will publish first reports in 2007 (Seeboek, 2003). Against this background it was only a logical next step to ask the question whether the methods of IC reporting – albeit still under development – could be transformed to the next level, that of national efforts to ‘‘succeed’’ in a new political, economic and cultural setting which has been coined as globalisation.

DOI 10.1108/13673270710819852

VOL. 11 NO. 5 2007, pp. 129-140, Q Emerald Group Publishing Limited, ISSN 1367-3270

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The paper reports on a project which aimed at examining the transferability of intellectual capital approaches from the corporate to the national level. In a first step it will describe changes which affect Austria as well as others of its EU partner countries and are often summarized under headlines such as knowledge society, globalisation and digitalisation. Those changes result in a shift of Austrian economic and social aspirations from a country that imports technology to a technology exporting country. In a second step the state of the art in corporate IC reporting will be reviewed in order to extract its common core and to understand its major problems, which can be expected to amplify at the national level. In the third section the author will provide a description of the philosophy, the research design and the outcomes of the pilot project. As we have applied a trans-disciplinary and action research design, results cannot be generalized[1]. However, they can point to relevant variables in an explorative way, whose interplay should be studied empirically if and after the prototype report and procedure will have been adopted in Austria. In section four results and problems of the research design will be discussed. Finally the paper will conclude with an outlook towards next steps.

The national background According to various statistics, which differ slightly in ranks, Austria has succeeded in becoming one of the five richest countries of the world as measured by per capita income (Aiginger, 2007). Gross national product, however, is a measure, which reflects past investments into the tangible and intangible infrastructure of a country. Furthermore, it counts the destruction of natural resources as growth and therefore lacks sustainability (Van. Dieren, 1995). To capture future potentials it seems necessary to develop a national strategy, which positions the country within the dynamic environment of a globalising world, fuelled by scientific and technological discoveries as well as by the entering of the large and potent economies of India and China, Russia and Brazil into the global and free exchange of goods, services, capital and talent. Traditionally Austria has been focused on catching up with the more advanced Western European economies and its major trading partner, Germany. This strategy relied on the following strengths: early adoption of technological inventions, focus on niche strategies, average spending on R&D and a sound and broad educational system as well as wage differences to Western European countries in order to attract FDI in production facilities. After the country has measured up with and even overtaken the benchmark countries, this strategy can be considered as no longer adequate. In a world society under the condition of dynamic change, which has been termed differently, such as risk society (Beck, 1986), post-modern society (Bauman, 1998) digital society (Tapscott, 1996) and above all, knowledge society (Drucker, 1969, 1993), national policies have to respond to major changes:

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B

Decision makers find themselves under pressure to select the ‘‘right’’ path, where the future is volatile and uncertain and where path-dependencies increase the risk to select inadequately. Therefore politicians have turned to the corporate system and to insights by strategic management theories to support them. The latter may be due to Dunning’s observation that in the twentieth century companies competed and states cooperated, while in the twenty-first century corporations are cooperating and states are competing. They compete in principle for mobile factors such as talent and capital and most states have developed sophisticated schemes to attract those factors (cf. Schneider, 1996).

B

National strategies should provide for investment in future potentials to create value: This implies a focus on the country’s contribution to leading edge science, on its participation rates in new technologies, on the quality of its research and educational system.

B

As intangible assets require high upfront investments (fixed costs) and can then mostly be multiplied at relatively low variable costs, traditional accounting methods with their focus on costs of acquiring (or producing) an asset do not seem adequate to capture potentials of future returns. Therefore shifts from input to output control as well as from past spending to future earnings have occurred. However, outputs and future earnings are uncertain and decision makers feel an urge to control the processes which lead to the

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desired outcomes. This may be one reason why more and more measures, indicators, benchmarks and auditing procedures have been emerging and are being reinforced by industry or international standards or even by law. Although each auditing model can be considered as a learning step, providing additional insight, its hidden agenda to ‘‘fake’’ certainty, where there can only remain uncertainty, is dangerous. B

Economic competitiveness is a crucial factor of a country’s future success. However, it is embedded in a complex socio-cultural pattern, which influences factors such as openness to the world, entrepreneurship, acceptance of change, curiosity to adopt new technologies, ambition and inclination to hard work as well as social peace. Therefore a country’s strategy must not be reduced to a narrow concept of economic performance.

Against this background many governments thrust to manage the factors which can contribute to a bright future of their countries. Experts around the world point out that those factors are no longer only of a physical or material but more and more of an intangible, immaterial nature. Therefore the focus is on research and development (in the broad and evolutionary sense of V. Bush’s report to President Roosevelt, (cf. Bush, 1945), on education and on culture in both of its meanings. However, we still know little about the nature and growth of those important intangible factors, although all over the world a community of researchers has started to elaborate proposals how they could be monitored and measured (cf. OECD, 1999; or Manifesto of the New Club of Paris, (Founding Committee, 2006)). To translate the international state of the art to the needs of a small country which is heavily dependent on trade, a group of Austrian researchers and practitioners has set out to develop a national knowledge report in the frame of a trans-disciplinary pilot project whose design and results will be described in the section ‘‘the pilot project’’.

Intellectual capital reporting at the corporate level: core components, open questions Various studies have been conducted to gain an overview on IC reporting. Some are summarized in Vandemaele et al. (2005) who found a rather poor state of the art as illustrated by a reference to Guthrie and Petty (2000). The latter concluded their research on Australian listed companies as follows. ‘‘. . . the key components of intellectual capital are poorly understood, inadequately identified, inefficiently managed, and not reported within a consistent framework, when reported at all’’ (in Vandemaele et al., 2005, p. 418). In a similar way, Housel and Nelson state that ‘‘. . . current knowledge resource identification and measurement tools (such as patent or citation accounts) are crude and often inadequate’’ (Housel and Nelson, 2005, p. 544). Schneider has summarized the weaknesses of current macro- and micro approaches to IC measurement as follows: B

isolated indicators, instead of a complex analysis of factor interplay;

B

orientation on the past with a focus on stocks and accrued costs; and

B

more emphasis on measuring and reporting than on managing IC (Schneider, 2001, Ch. 5).

At the national level the MERITUM project in Spain (MERITUM Project, 2002), the Danish Guideline for Intellectual Capital Statements (Danish Ministry of Science, Technology and Innovation, 2005) and the Japanese Intellectual Capital Reporting Guideline (Johanson et al., 2006), as well as the Austrian legislation on universities all try to establish a balance with regard to the challenges of costs versus benefits, of confidentiality versus accountability, of uniqueness versus comparability and of internal control versus external communication.

‘‘ Economic competitiveness is a crucial factor of a country’s future success. ’’

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There is much to be done to improve the balances. As Johanson et al. state: ‘‘However, the importance of intangibles exceeds the current ability to recognize and measure them’’ (Johanson et al., 2006, p. 474). Still, all efforts mentioned above, share some common features: B

Most reports use a typology of IC which includes at least three components: human, structural and relational capital, or in Sveiby’s terms, human capital, internal and external structure. Authors treat the notions of resources, assets and capital differently, some use them synonymously, others separate them. For the purpose of this paper, differentiations can be forgone over the first step to establish a procedure at the national level.

B

There seems to be consensus that – due to immature state of the art – uniqueness is acceptable, although it forecloses comparability, that voluntary reporting may be preferred to mandatory accountability, although this may inspire managers to set an agenda by window-dressing and masking out intellectual liabilities and that internal control is as important as external communication although it is difficult to serve both purposes with one single report.

B

Although empirical findings on the significance of IC disclosure for analysts and investors show mixed results, there is evidence that significance is increasing (Abdolmohammadi, 2005).

B

Although the adage ‘‘what is not measured cannot be managed’’ may result from a narrow view, authors agree on the necessity to draw attention to the way IC assets translate into value creation (Burgmann et al., 2005).

B

Most reports combine metrics from an accounting or financial perspective with narrative elements to capture ‘‘qualities’’, which emerge from the interplay of various factors, but cannot be reduced to their addition.

Given this state of the field, it may seem premature to transfer a theory which remains in its infancy to the national level. However, the pressing requirements identified in section 1 inspired the project team to follow this track, while remaining aware of the difficulties inherent to it.

The pilot project The project was executed from fall 2005 to December 2006 by a core team of researchers and practitioners with different disciplinary backgrounds. The team had applied for a grant from funds dedicated to foster trans-disciplinary research. In the following, the project will be described along the lines of philosophy, assumptions, methods and results. Philosophy of the project While it is important for any researcher to reflect in her or his implicit assumptions on the research issues, this is indispensable in an interdisciplinary team. Otherwise no common understanding of the project can form and endless conflicts on single aspects will enfold that root in different implicit assumptions. The group started from the following basic assumptions, which were made explicit right at the first meeting but have been gaining substance over the research process:

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B

The NKR should help Austria to fulfil its part in the Lisbon Agenda, which aims explicitly at knowledge-based competitiveness and social cohesion.

B

The NKR is to be seen as a controlling cycle and not as a one-shot measurement. The focus thus is on developing intellectual capital not only on measuring and benchmarking.

B

The NKR is not to reinvent the wheel of partial policies, success factors and indicators in different fields, such as technology, R&D, education, health etc., but rather to complement and to integrate those approaches.

B

Policies for important aspects of social life are usually designed in disciplinary ways with interfaces being under defined. This provokes challenges of their overall effectiveness.

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Therefore a NKR should provide a general frame to integrate those policies and to deal with contradictions and countervailing effects. B

The Austrian NKR should act on existing models and then develop a custom-made procedure and frame. Thus in the conflict of standardization for the sake of better comparison (benchmarking, external addressees) and adaptation to special needs and learning (internal addressees) we would tend to the latter while insisting on some indicators with international comparability (cf. OECD, 1999).

B

Austria was considered by the research team as especially ripe for intellectual capital reporting as it is involved in strategic redesign after achieving its objectives to overhaul Western European nations (see Appendix).

B

Following Leif Edvinsson’s approach the team intended to reach beyond unrelated single indicators of R & D spending or participation in certain educational programs and to dip into potentials of cultural knowledge spaces, where relations between elements of intellectual capital are considered to be as important as characteristics of the elements in isolation: The Austrian NKR should be based on a complex – adaptive – systems design (cf. Kauffmann, 1993).

The research design As a blueprint the team used the model of IC Reports developed by two of the team members at the end of the twentieth century for ARCS. Its main innovative characteristics, as compared with the state of the art at the time, were to combine a structural, that is, stock-oriented view with a process or flow-oriented view on the one hand and to link both to strategy by introducing visions and objectives. Furthermore, the model puts a focus on feed-back loops from outcomes to intellectual capital (cf. Schneider and Koch, 1999; Schneider, 2001, p. 107). An adaptation of this model to the national context was developed by another member of the research team, as illustrated in Figure 1 (cf. Brandner, 2005). Following the core team’s values and assumptions team members intended to develop a pilot design for a national process of ‘‘wealth creation based on a system of variables that helps to uncover and manage the invisible wealth of a country’’ (cf. Bontis, 2004, p. 13). The core team was aware that it could have proceeded in a mono-disciplinary, expertise-based manner. Over the duration of the project the core team conducted this kind of research by analysing the content of different approaches at the corporate and national level. Team members collected reports and indicators as input in its collective process, but left it to the process how those inputs were integrated. The core team could for instance have relied on the 60 indicators collected by Abdolmohammadi to present a more Figure 1 Model of a national knowledge report

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differentiated picture of its three structural IC components (Abdolmohammadi, 2005). It could have developed a new model by joining the best aspects of the different models, which had been elaborated and published so far, as a mono-disciplinary project would have required. All this would have happened purely on paper and would have remained far from exercising impact. Therefore the team decided to work on a prototype procedure, based on the integrated wisdom of a larger collective unit, whose members come from heterogeneous backgrounds. It recruited a larger team of 30 representatives of important societal groups to elaborate the blue print and to integrate indicators of social cohesion, entrepreneurial initiative and cultural values to reflect the other half of the Lisbon agenda. The broader agenda (in comparison to other national reports) of economic competitiveness, of social cohesion and of cultural creativity, relies on the assumption that the latter act as enablers of the former. As the project intended to activate experiential and implicit knowledge, it needed to establish a common practice (Brown and Duguid, 1991) and to trigger creativity by special methods, such as ‘‘World-Cafe´’’ (cf. Brown and Isaacs, 2005), Future-Conferences and other open space technologies. This was reflected in a sophisticated overall design which combined plenary meetings and workshops in variable designs of singular events. The latter always included a facilitator and observer who documented results as well as the process (cf. Figure 2). As the core team was driven by the objective to create a process with political impact, it did not follow a specific method by the letter, but developed an action research design which combined many different methods and tools. Members of the core team fulfilled the double role of observers (and reflectors) and participants of the process. As they went along, they applied different methods to cover the ‘‘observation-reflection’’ side: narrative interviews and structured text analysis at the beginning in order to capture individual visions and individual knowledge on IC. This was followed by a plenary session, which facilitated ‘‘dynamic teaming’’ and enhanced the formation of a community of practice. After this session smaller teams focused on components of the basic model to elaborate on key success factors and indicators. These efforts were summarized and condensed by the core team and fed back to the larger team by virtual means and in another plenary meeting. The feedback session entailed a redesign of the second half of the project. Instead of developing indicators as proxies for the success factors identified in the process, the enlarged team decided to dig deeper into some content-related issues, such as competitiveness, sustainability, gender mainstreaming. Furthermore the concept of ‘‘Knowledge Partnership’’ of major contributors to an Austrian knowledge-based society was elaborated, by building on the experiences in the enlarged pilot group.

Figure 2 Design of the research process

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The table of impacts, depicted in Table I, comprises a synopsis of different perspectives on societal objectives on the one hand and on the instrumentality of measures to account for the overall vision of a socially cohesive, culturally creative and economically competitive society on the other hand. The factors result rather from a trans-disciplinary practice and from political compromise than from theoretical deduction or empirical evidence on the issue of instrumentality. As most members of the enlarged team hold university degrees, theories and empirical evidence were used to support problem solving but not a primary focus. Results at the process level of trans-disciplinary methods are sounder in an academic sense, as each step was evaluated by questionnaires and focus groups. As is to be expected from inter- or trans-disciplinary work, it took months as well as adaptations of the initial structure of the model (as outlined in Figure 1) in order to create a common language of communication. Major changes of the wording include a renaming of intellectual capital components as human, structural and relational potential. As put forward by Schneider (1997), this points to the fact that intangible assets don’t become effective by their mere existence but need to be activated by leadership or self-organisation. However, there is a downside to losing the notion of capital. The word capital elicits expectations of capitalisation and seems closer linked to the creation of monetary value. Another characteristic of our results deserves attention: success factors are defined at a rather Table I Synoptic table of impacts

Individual

Organization

Society

Individual

Organization

Society

Competence of the individual to contribute to his/her own prosperity and to the prosperity within his/her private surroundings

Competence of the individual to contribute to the organization’s prosperity

Competence of the individual to contribute to the society’s prosperity

Competence to deal with changes and to integrate them wisely Perception of the individual responsibility for knowledge and learning Better employability and integration into society Competence of the organization to contribute to the individual’s prosperity Better rated Implicit Knowledge Better possibilities of life-long learning More space for reflection and re-orientation Work-life-balance Competence of the society to contribute to the individual’s prosperity Support of individual talents and uniqueness Social participation for all Vielfalt und u¨berpru¨fbare Qualita¨t von Bildung und Wissensdiensten gesichert Variety and supervised quality of education and knowledge-related services secured

Entrepreneurial application of acquired knowledge Key-qualifications enhanced

Living solidarity Competent perception of citizens’ rights to participation Active participation of citizens in cultural and societal life

Competence of the organization to contribute to its own prosperity

Competence of the organization to contribute to the society’s prosperity

Attractive and gender-sensitive framework for knowledge based tasks International leadership within priorised core-competences International network built up Competence of the society to contribute to the organization’s prosperity Innovative organizations National and international elites Attractive location for economy, science and research, also for high potentials and top experts Upswing of innovative from the society accepted economic fields and business areas

Locational advantage secured and more attractive More high specialized tasks, functional clusters and networks Sustainable organizations’ actions

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Competence of the society to contribute to its own prosperity Financial, social and ecological standards secured Social, ethnic and gender related discrepancies in educational behaviour reduced Higher level of education within all social classes Fertile climate for discourses Independence and variety of media and sources of information as critical control tool Opening towards not used knowledge potentials (e.g. emigrants)

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abstract level. Factors at lower levels of abstractions than those displayed in Figure 2 would allow for quantification and require less effort to be translated to political measures. Still, the group voted for potential and needed the higher level of abstraction to maintain consensus. Members of the enlarged team contributed in an open source modus, motivated only by the opportunity to be part of a greater whole and to decide individually on the amount of time and effort of their involvements under a tacit creative commons license. Results The project generated results at the level of products and at the level of the process. The former include: B

A glossary as a documentation of major concepts which had become relevant over the course of the project.

B

Six synoptic tables which identify success factors for the categories of the Austrian Knowledge Report, namely visions/impact – human capital (potential), structural capital (potential), relational capital (potential) – processes – outputs and outcomes.

B

In order to preserve the implicit knowledge, activated by the specific research design and thus emerging from discourse in various forms, the six synoptic tables related to the components of the NKR were completed by hypertexts. These texts can be interpreted in analogy to the process of legislation; it does not only provide the final text of laws but also protocols of their becoming.

B

The concept of ‘‘Knowledge Partnership’’, in analogy to Austria’s successful social partnership, effective over the last period of major structural changes, namely the post-war era. The concept of knowledge partnership or of an ‘‘Agenda Knowledge’’ is understood as a basic process-oriented philosophy: The focus is on policies and the integrated development of sustainable (!) competitive advantage and of quality of life. The NKR is a tool within this process to monitor results of an integrated agenda.

B

A follow-up project which will work on indicators to monitor success factors. Again the team will not reinvent the wheel but work with a synopsis of major indicators at the national level, provided by a growing number of comparative reports issued by (inter)national associations such as the World Bank, the OECD, the European Commission or by private research institutions such as the Brookings Institute or the IMD in Lausanne or by national knowledge reports, such as the work of Bontis or the Israeli report (for an overview see Bonfour and Edvinsson , 2005, ch. 8f.).

At the process level, the results transcend the explicit level. Despite a high workload members of the enlarged team are ready and motivated to continue and to diffuse findings within their networks. As mentioned above, this is part of the new movement to collectively create knowledge under a copyleft or a creative commons license. Just like Wikipedia or Linux the project would not have succeeded without the effort of the core team, which provided the overall design, a virtual meeting place, agendas of face-to-face meetings and stimulating inputs. Still, the outputs at the product level could not have been achieved without the arrangements for joint contributions by members of the larger team with their heterogeneous backgrounds.

Discussion As a singular case the project is of an explorative character. It has not assumed mono-causal relationships in a chain of cause-effect relations from intellectual capital components to performance indicators and then tested hypotheses with macro economic data. Although the author is convinced that it is of utmost significance to support causal relations by empirical evidence, she also holds that the field has not yet been sufficiently understood to proceed to such rigorous methodology. The exploration by the project ‘‘Austrian Knowledge Report’’ has supported the elaboration of three major levels or nested systems at which an ‘‘Agenda Knowledge’’ aims, namely (national) society as a whole, organizations and individuals.

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‘‘ National strategies should provide for investment in future potentials to create value. ’’

Thus the model-process tries to trace the emergence of intellectual potential from the inner core (individuals) to the outer circle (Austrian society) in order to find supporting policies with a deeper leverage effect. An example is illustrated in Table I. Procedure challenges Although selected to represent a significant societal group, the members of the enlarged team could not be representative of the whole nation. We had first gathered their individual statements to benefit from the wisdom of crowds (Surowiecki, 2004) and then relied on discourse elicited by facilitating methods. The result is therefore unique and hardly reproducible. As experts were gathered throughout the teams, experts of important knowledge-creating processes as well as experts of measurement, relatively important inputs of knowledge and experience should have guaranteed findings not to be arbitrary. Still, they are the outcome of a unique process rather than of positivistic research methodology. Philosophy challenges Why do we see an audit explosion in modern society? And why do we trust a verification, which . . . ‘‘emerges as a more negotiated and interactive practice than is commonly imagined?’’ (Power, 1997, p. 12). If . . . ‘‘the epistemic foundation of . . . auditing, i.e. the relation between its inputs and the production of assurance, is essentially obscure . . . ’’ (Power, 1997, p. 15), how can we then legitimize our decisions for models, variables (success factors), indicators, benchmarks and interpretations? Measurement has no purpose of its own. Any evaluation is driven by a purpose and designed accordingly. Therefore it is crucial to provide transparent answers to the following questions: Who will be the addressees of reports? Who will be in charge of the operational aspects of the procedure? Who will decide on the degree to which objectives have been met, surpassed or failed? Who will be affected by which kinds of consequences? Our procedure cannot exclude biases but it is designed to create transparency of actors, of sequences of the staged approach and of content. Transactional costs and their proportion of benefits, such as economic growth, social welfare and cultural creativity, are another issue for a state like Austria with a mild non-compliance of the Maastricht criterion covering national debt (the limit is set with 60 percent of GDP). If tax payers’ money is spent on an Agenda Knowledge there need to be returns, albeit they might occur in a longer run and scattered over different IC components. Finally, as validity is dependent on epistemological paradigms and basic assumptions, a national knowledge report cannot escape questions of basic values. With regard to values the scientific method provides arguments and structure, but no solutions. Therefore the process will remain fundamentally political, where different interests and power are involved. This entails questions of accountability of those who design systems, whose purpose is to hold decision makers accountable. Can those who work on a greater accountability of decision makers in societal processes, which deliver knowledge, be hold accountable themselves? This seems all the more important as models, variables and indicators can never be neutral (Power, 1997, p. 13). Their selections need to be based on valuations and thus on political decisions for which Rawl’s idealistic construction should be approximated: those who decide on weighted criteria do not know their future position in society, which implies that they could be affected by positive as well as negative outcomes of their decision making (Rawls, 1999). In addition to the difficulties mentioned above, namely epistemological issues of reliability, objectivity and validity, economic issues of effectiveness and efficiency and political issues of

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purpose, questions of social acceptance arise, if a national knowledge report is to be applied and to enfold impact. Those issues are closely linked to the way in which the whole agenda knowledge, that is the strategic process cycle, is organised and socially embedded. The trans-disciplinary research approach reported in this paper (cf. Gibbons et al., 1994; Novotny et al., 2001) took these questions into account. It acknowledged the negotiated character of outcomes by the research design, it resulted among other outcomes in the ‘‘Knowledge Partnership’’ as a hybrid procedure between political decision making and political consultancy and the core team made clear in its report that the outcome was a negotiated compromise, as was its starting point, the Lisbon Agenda.

Outlook The results will be published and diffused in the academic as well as the political community. Strong partners need to be found in order to realise the ‘‘Knowledge Partnership’’ as a procedure which allows for a pluralistic discourse on matters of a knowledge society. In addition, the procedure makes sure that discourse is not continued for ever as it foresees milestones, where discourse must turn into the planning and execution of action. Important stakeholder groups have become curious to learn about the project. We hope that we will be able to implement our prototypes and follow up on our research.

Note 1. The project is based on the common work of the wb:o¨ team, cf. www.wboe.at

References Abdolmohammadi, M.J. (2005), ‘‘Intellectual capital disclosure and market capitalisation’’, Journal of Intellectual Capital, Vol. 6 No. 3, pp. 397-416. Aiginger, K. (2007), Konjunkturgespra¨ch Steiermark: White Paper of the Austrian Institute of Economic Research (WIFO), WIFO, Vienna. Bauman, Z. (1998), Postmodernity and its Discontents, Cambridge University Press, Cambridge. Beck, U. (1986), Risikogesellschaft: Auf dem Weg in eine andere Moderne, Suhrkamp, Frankfurt a. Main. Bonfour, A. and Edvinsson, L. (Eds) (2005), Intellectual Capital for Communities, Nations, Regions, and Cities, Butterworth-Heinemann, New York, NY. Bontis, N. (2004), ‘‘National Intelligence Capital Index: A United Nations Initiative for the Arab region’’, Journal of Intellectual Capital, Vol. 5 No. 1, pp. 13-39. ¨ sterreichische Wissensbilanz’’, working papers, Vienna. Brandner, A. (2005), ‘‘O Brown, J.S. and Duguid, P. (1991), ‘‘Organizational learning and communities of practice: towards a unified view of working, learning, and innovation’’, Organization Science, Vol. 2 No. 1, pp. 40-58. Brown, J. and Isaacs, D. (2005), The World Cafe´: Shaping Our Futures Through Conversations That Matter, Berrett-Koehler, San Francisco, CA. Burgmann, R.J., Roos, G., Ballow, J.J. and Thomas, R.J. (2005), ‘‘No longer out of sight, out of mind: intellectual capital approach in Asset Economics and Accenture LLP’’, Journal of Intellectual Capital, Vol. 6 No. 4, pp. 588-614. Bush, V. (1945), ‘‘Science: the endless frontier’’, available at: www.nsf.gov/od/lpa/nsf50/vbush1945.htm (accessed 11 May 2005). Danish Ministry of Science, Technology and Innovation (2005), Intellectual Capital Statements – the New Guideline, available at: www.urjc.es/innotec/tools/Intellectual%20Capital%20Statements%20-%20The %20New%20Guideline.pdf (accessed 14 May 2005), Danish Ministry of Science, Technology and Innovation, Copenhagen. Drucker, P.F. (1969), The Age of Discontinuity, Heinemann, London. Drucker, P.F. (1993), The Post-Capitalist Society, HarperBusiness, New York, NY. Founding Committee (2006), Manifesto of the New Club of Paris: Constitutional Paper, Vienna and Paris, available at: www.the-new-club-of-paris.org/

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Gibbons, M., Limoges, C., Nowotny, H., Schwartzmann, S., Scott, P. and Trow, M. (1994), The New Production of Knowledge: The Dynamics of Science and Research in Contemporary Societies, Sage Publications, London. Guthrie, J. and Petty, R. (2000), ‘‘Intellectual capital: Australian annual reporting practices’’, Journal of Intellectual Capital, Vol. 1 No. 3, pp. 241-51. Housel, T.J. and Nelson, S. (2005), ‘‘Knowledge valuation analysis: applications for organizational intellectual capital’’, Journal of Intellectual Capital, Vol. 6 No. 4, pp. 544-57. Johanson, U., Koga, C., Skoog, M. and Henningsson, J. (2006), ‘‘The Japanese Government’s intellectual capital reporting guideline’’, Journal of Intellectual Capital, Vol. 7 No. 4, pp. 474-91. Kauffmann, S. (1993), The Origins of Order: Self-Organization and Selection in Evolution, Oxford University Press, Oxford. Kettner, C., Radlberger, P., Schleicher, S.P. and Thenius, G. (2006), ‘‘Potentials for extending national income accounts by integrating sustainable development indicators’’, research paper, Wegener Center, Graz. MERITUM Project (2002), Guidelines for Managing and Reporting on Intangibles, Airtel-Vodafone Foundation, Madrid. Nordhaus, W.D. and Tobin, J. (1972), ‘‘Is economic growth obsolete?’’, Proceedings of the 50th Anniversary Colloquium of the National Bureau of Economic Research: Economic Growth, Columbia University Press, New York, NY. Novotny, H., Scott, P. and Gibbons, M. (2001), Rethinking Science, Polity Press, Oxford. OECD (1999), ‘‘Measuring and reporting intellectual capital; experience, issues and prospects’’, available at: www.oecd.org/document/15/0,2340,en_2649_201185_1943055_1_1_1_1,00.html Power, M. (1997), The Audit Society: Rituals of Verification, Oxford University Press, Oxford and New York, NY. Rawls, J. (1999), A Theory of Justice, 2nd ed., Harvard University Press, Cambridge, MA. Schneider, U. (1996), Wissensmanagement: Die Aktivierung des intellektuellen Kapitals, FAZ Verlag, Frankfurt. Schneider, U. (1997), ‘‘Asset, capital or potential? How to structure intangibles?’’, Keynote at the IC Seminar in Zagreb (arranged by the Austrian Research Group on IC). Schneider, U. (2001), Die 7 Todsu¨nden im Wissensmanagement, FAZ Verlag, Frankfurt. Schneider, U. and Koch, G. (1999), ‘‘Basismodell der Wissensbilanz fu¨r ARCS’’, working paper, Graz. Seeboek, M. (2003), Universita¨tsgesetz 2002: Gesetzestext und Kommentar, 2, Erweiterte Auflage, Wiener Universita¨tsverlag, Wien. Surowiecki, J. (2004), The Wisdom of Crowds: Why the Many are Smarter than the Few and How Collective Wisdom Shapes Business, Economics, Societies and Nations, Doubleday, New York, NY. Sveiby, K.E. (1997), The New Organisational Wealth: Managing and Measuring Knowledge-based Assets, Berret-Koehler Publishers, Sydney. Tapscott, D. (1996), The Digital Economy: Promise and Peril in the Age of Networked Intelligence, McGraw-Hill, New York, NY. Van Dieren, W. (1995), Mit der Natur rechnen: Der neue Club of Rom Bericht, Birkha¨user, Basel. Vandemaele, S.N., Vergauwen, P.G. and Smits, A.J. (2005), ‘‘Intellectual capital disclosure in The Netherlands, Sweden and the UK’’, Journal of Intellectual Capital, Vol. 6 No. 3, pp. 417-26.

Further reading Bauman, Z. (1992), Intimations of Postmodernity, Routledge, London. Bell, D. (1975), Die nachindustrielle Gesellschaft, Campus Fachbuch, Frankfurt a. M. and New York. Koch, G. (2001), ‘‘Wissen ist Markt’’, available at: www.wissen-nordhessen.net/fileadmin/templates/ wissen-nordhessen/PDF þ MP3/Vortrag_Koch.pdf (accessed 11 May 2005).

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Appendix. Austria’s strategic challenge With a per capita GDP (2005) of e29,800 – Austria belongs to the richest economies of the world. Its growth rate of 3.2 percent (nominal) in 2005 is above the European average, while its unemployment rate of 5.2 percent is far below that average. With a (nearly) balanced foreign trade account and an export ratio of 39 percent or 54 percent (including services) of the GDP the country is fully integrated into the world economy albeit with a focus on the enlarged European Union, to which its major trading partners belong. Corrected for demography and purchasing power and a disamenity premium, Austria’s per capita GDP ranks even higher (cf. Nordhaus and Tobin, 1972; Kettner et al., 2006). The rosy picture changes, nevertheless, if future potentials to create returns are included: Some structural changes seem necessary. Post-war Austria’s strategy had its focus on the rebuilding of destructed stock and on catching up with more advanced northern and western European countries. At this time a focus on creative imitation, a focus on a ‘‘upper-medium’’ range of technology and on a broad educational system, which delivered sound upper-medium quality was adequate. After matching and even overtaking western European levels of per capita income a change in strategy is required. A focus on niches with leading positions on the world market needs to be supported by educational institutions which follow the highest standards. The broad medium-range educational system needs to be complemented (not substituted!) by conditions which foster the emergence of elites, application-oriented research needs to be embedded into selected areas of basic research at the edge, the percentage of ‘‘smart’’ components in products and services needs to be increased. Austria’s rank in the following areas requires ameliorations: B

Pisa results.

B

Degrees in mathematics and natural sciences.

B

R&D funding and results.

B

Advanced, (high) technology-based production.

B

Leveraging IT potential into productivity gains.

About the author Ursula Schneider is Professor of International Management at the University of Graz and acts currently as dean of the Faculty of Economics and Social Sciences. She published the first book on knowledge management in the German language in spring 1996 and developed the first Austrian IC Report for a national research organisation in 1999. She can be contacted at: [email protected]

To purchase reprints of this article please e-mail: [email protected] Or visit our web site for further details: www.emeraldinsight.com/reprints

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Effective societal knowledge management Karl M. Wiig

Abstract Purpose – The purpose of this paper is to suggest principles and framework for comprehensive societal knowledge management (SKM) for countries to provide acceptable conditions for their citizens and businesses and to participate equitable in the globalized knowledge economy.

Karl M. Wiig is Chairman and CEO of Knowledge Research Institute, Inc., Arlington, Texas, USA and Knowledge Management Adjunct Professor at The Hong Kong Polytechnic University.

Design/methodology/approach – Foundations for SKM principles and framework are based on requirements and practical experiences reported in literature and expanded by the author’s work and concepts. Findings – Comprehensive SKM is not commonly pursued in spite of its importance for national survival. Many countries need SKM guidelines and concepts and will benefit by development of an acceptable and well-substantiated framework. Research limitations/implications – Extensive research should be pursued in scientific, economic, social, and educational fields to identify good SKM options. Understanding must be developed of how best to undertake SKM. Practical implications – Implications are that comprehensive SKM by nations promises to improve quality-of-life worldwide. Originality/value – Notwithstanding the need for a comprehensive SKM framework, little work has been available until now. Keywords Society, Knowledge management, Economic growth, Globalization, Quality-of-life, Literacy Paper type Conceptual paper

Introduction Most nations seek good conditions for their public and private institutions and citizens. Sustaining satisfactory levels of economic activities and development, personal and shared qualities of life (QoL) are particularly important. Strong societal intellectual capital[1] (IC) is required to create and maintain acceptable internal domestic and local conditions and to participate effectively in the global knowledge economy. Acceptable QoL is achieved when the society is capable, balanced, and just and when appropriate IC is possessed by citizens, public servants, and organizations and incorporated in their practices, systems, and procedures. Societal success rests on widespread knowledge, cities are major generators of ideas, and widespread knowledge is fostered by effective societal knowledge management (SKM) to build, maintain, and make the best use of IC assets. In 1945, Hayek outlined the importance of knowledge for societal guidance and governance, albeit the importance of knowledge was not yet clear (Hayek, 1945). That became clearer in 1986 and 1990 when Romer provided the economic understanding that knowledge is the underlying factor that fuels performance, progress and economic growth, locally, nationally and globally (Romer, 1986, 1990; Warsh, 2006). From a more practical and operational view, Drucker introduced the understanding of the knowledge worker and this mode of work to the modern knowledge economy (Drucker, 1969).

DOI 10.1108/13673270710819861

VOL. 11 NO. 5 2007, pp. 141-156, Q Emerald Group Publishing Limited, ISSN 1367-3270

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This article explores knowledge-related possibilities for societal progress and success. In today’s global knowledge economy, new perspectives, approaches, and practices – as cultural drivers – are also drivers of societal advances, not only for developing nations but also for highly industrialized nations. The article emphasizes building competent people, profitable enterprises, effective cities, and desirable societies. Such developments result less from central planning and design – they primarily result from actions of people and organizations with detailed localized knowledge of needs and opportunities. Instead of specific prescriptions for how to build capabilities, the emphasis is on a knowledge-focused framework to foster environments, culture, and infrastructure. Countries throughout the world struggle to meet the demands of the globalized knowledge economy. All have the requirement to build, manage, and utilize the knowledge needed to participate successfully in the global economy. Every nation needs to manage knowledge effectively. It is surprising that though societal knowledge management (SKM) is a fundamental necessity, few nations do it comprehensively (Malhotra, 2002; Ntoso, 2006; Riege and Lindsay, 2006). Many do not consider SKM at all. Even advanced countries like the USA allow literacy to decline (Gordon and Gordon, 2002). Secondary and college education are often inadequate for national needs. In the USA there are serious undersupplies of trained engineers, scientists, and healthcare professionals to serve expanding needs and to replace retiring professionals (Engardio, 2005; Rose, 2006). Literacy in developing nations is below levels required to support participation in the global economy and provide acceptable quality-of-life. In 2007 cities will be home to 50 percent of the world’s population with 20 percent living in city slums. In China, 400 million will move to cities by 2015. UN and WHO warns that urban poverty has severe economic and health impacts and states: ‘‘In 2005 there were more people in Mumbai’s slums than in all of Norway!’’ (UN-Habitat, 2006).

Societies seek progress and success The world inside and outside a country is in constant flux – economically, environmentally, technically, socially, and politically. There is constant progress with growth of technology and scientific understanding, of wealth, of quality-of-life, and in many other areas. In these processes, knowledge is the driver of growth (Romer, 2007). Many developing nations need to initiate and accelerate growth of both knowledge and the economy, as indicated in the simple model presented in Figure 1. This model portrays the dual positive feedback process that contributes to knowledge growth when seed funding is provided for financial aid for educating individuals to be competent workers, and for enterprises to expand and provide employment opportunities. As people become proficient and obtain employment, they are able to seek further education. Similarly, as enterprises improve their capabilities, they generate both funds for expansion and better knowledge for increased productivity and improvements. To deal with societal flux, governments have two general purposes. One is to manage change and guide progress as local and global conditions, capabilities, people, and perspectives change. The second is to ascertain that laws and regulations are followed and enforced, often in new contextual situations when they fall outside the initial intents. Both of these purposes require knowledgeable judgment, not only within the legislative, executive, and judicial branches but also by public servants down to the lowest levels. Contextual interpretation requires better knowledge to support timely and competent handling of work, often involving novel challenges that require innovation.

‘‘ Countries throughout the world struggle to meet the demands of the globalized knowledge economy. ’’

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Figure 1 A simple model of knowledge-supported economic growth

Other factors are also important, as indicated by these examples: The ability to obtain title for ownership of property in a timely and non-bureaucratic fashion strongly affects economic growth and progress and is made more efficient with more knowledgeable public servants (de Soto, 2000). Similarly, personal outlook for opportunities – influenced by being more knowledgeable – affects motivation and ability to pursue better conditions, be they business or personal improvements (Harrison, 2000).

The balanced knowledge society The global knowledge economy changes the rules for national progress. Taylorism’s command-and-control top-down models and other single-focus government systems have limited success. Instead, distributed and delegated public planning and decision making are needed in a balanced society to provide understandings, decisions and actions that address local contexts and opportunities to fulfill shared objectives (Galbraith, 1996). Any analysis of how knowledge may improve society is based on reference models, perspectives, and understandings. This article is no exception and the underlying model is a balanced, just, and democratic society. A balanced society has goals such as a peaceful, stable, prosperous, and durable future for its citizens and enterprises. It also seeks to be a responsible international partner. Several factors influence desired societal balance. Mintzberg proposed three main sectors of society as often being out of balance with one another: the political, social, and economic sectors (Mintzberg, 2001, 2002; Skapinker, 2003). This article broadens Mintzberg’s societal balance concepts to four major sectors: Governance, Economy, Quality of Life (QoL), and Culture, as indicated in Table I. The performance of each factor and the degree to which societal goals are reached relies on knowledge. All benefit from deliberate SKM to build better knowledge. Reaching balanced society goals requires that citizens are knowledgeable to participate intelligently in public affairs and government (Wiig, 2002). Once a society determines which knowledge-related factors will affect its goals and intents, it can set priorities for SKM and pursue initiatives. However, one caveat must be considered. Practical knowledge is very important. Theoretical academic knowledge does not ensure good governance. Nor does knowledge by itself ensure ethical behavior and governmental transparency.

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Table I Examples of factors that contribute to a balanced society Governance sector

Economic sector

Quality of life sector

Cultural sector

Representative and knowledgeable legislature Executive government Impartial justice system Defense/public order Fiscal governance Infrastructure International relations Ethical governance

Personal wealth and livelihood R&D and industrial activities Domestic and international commerce Financial system Global competitiveness

Personal welfare Health care Social services Availability of quality education Just security for all Freedom of action Sense of opportunities

Ethics and social values Religious freedom Respect for the individual Civil behaviors Tolerance Arts and leisure

Successful participation in the global knowledge economy Every nation wishes to participate equitably in the global knowledge economy by having domestic enterprises that serve international customers. International trade provides profits for private and public enterprises, good incomes for employees, and balance of payment contributions to the nation. However, building acceptable international trade requires domestic conditions that favor economic activities. Long-term widespread economic success relies on societal stability and good intellectual capital. Stability depends on citizen satisfaction, their wellbeing, and the resulting social sentiment and culture. Dissatisfied citizens create problems of social unrest, corruption and crime, and lack of motivation to participate in the economy. A significant result of worldwide progress is that work in general has become more complex. There are many reasons and the pressure to tackle more difficult challenges are felt almost everywhere. In advanced organizations, including governmental functions, routine work is increasingly automated and people are asked to address more challenging and important tasks that previously were not addressed. Handling these new situations competently requires more and better knowledge than was required for ‘‘past work.’’ In addition, to compete successfully the need is to provide more sophisticated goods and services which are harder to make but provide greater acceptance and value to customers. In non-traded economic sectors, such as healthcare and local services, the situation is different but still affected by globalization. As people throughout the world are better informed through media and the Internet, they become more knowledgeable and discriminating and require better services as part of improving their QoL. Hence, indirect globalization pressures are felt in local services and for example, innovation in local health care becomes an important issue. Small and medium-sized enterprises (SMEs) are pressured to be more effective and innovative to compete. Often competition is felt in local markets invaded by efficient external competitors with a wider range of goods and services that also may be less expensive. From one perspective this is progress on a global scale. From another perspective this is unwelcome intrusion with unwanted changes that threaten the livelihood of those who are unprepared. The public sector is similarly affected. Comprehensive information and communication technologies (ICT) provide new capabilities and practices that change much of the nature of public service and interactions with the public-at-large. As citizens learn from television, internet, and other sources about what happens elsewhere in the world, they become more discriminating and demand better and more transparent public services. The new work requires greater knowledge – targeted task knowledge, broad enterprise knowledge with understanding of operations, local navigational knowledge, and reliable world knowledge (Wiig, 2002).

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The importance of broad literacy The ability to perform well in the twenty-first century requires broad literacy and that is important in the modern world (Katz, 2000). Literacy normally means to have knowledge to read, write and perform mathematics at certain levels. Workers must understand written instructions, make notations, perform simple calculations, and so on. However, literacy is also required in other generic areas such as finance, computer use, world understanding, science, and geography (NEFE, 2002; Hazen, 2002). Unfortunately, reading-writing-arithmetic literacy is inequitably distributed throughout the world (UNESCO, 2001, 2002): B

26 percent of the world’s adult population is illiterate;

B

98 percent of non-literates live in developing countries;

B

in the least developed countries, the overall illiteracy rate is 49 percent;

B

52 percent of all non-literates live in India and China, which have one-third of world population;

B

less than 60 percent of adults are literate in Africa; and

B

women make up two-thirds of all non-literates.

With a large portion of the world’s population being illiterate, the lack of literacy knowledge severely affects societal success. The economic impact of illiteracy is immense and hampers developing nations in their efforts to provide for their citizens and to participate equitably in the global economy. Over 100 countries are severely affected. The opportunity is significant. Long-term effects of improved knowledge indicate that an increase of 1 percent literacy score leads to a 2.5 percent personal productivity increase and to a 1.5 percent increase in GDP (Coulombe et al., 2004). The relationship between average personal annual income and national literacy rate is indicated in Figure 2 for representative nations. Clearly, the potential economic return to a nation will be large by increasing literacy. However, in some nations autocratic regimes benefit from illiteracy since that makes it easier to govern and manipulate the public without opposition. Figure 2 The relationship between literacy and annual personal income

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Personal and shared quality of life Securing a progressive and viable society requires an environment that promotes citizen QoL or wellbeing by providing security through just law and order, a safe future, equitable economic order, and so on (Polany Levitt, 2006; Prescott-Allen, 2001). Perceived QoL contributes strongly to personal wellbeing through adequacy of food, shelter, security, sense of opportunities, and freedom of self-determination. It also affects people’s motivation and capability to improve their situation (Harrison, 2000). Personal QoL refers to an individual’s condition and is partly determined by personal life choices and behavior. Shared QoL is mostly under societal control and results from available natural, industrial, and human resources and society’s past and present choices. Hence, shared QoL relies on collective decisions about priorities and resource commitments and agreements for governing as determined by constitution, laws, and regulation. Although personal QoL is heavily influenced by natural conditions and societal actions, people have freedom to influence their QoL by decisions about education, employment, and where to live.

Societal success relies on different kinds of knowledge People, private enterprises, agencies that provide educational, health, social, law and order, infrastructure and other services, cities, districts, and regions, and the society’s governing institutions are all interconnected and dynamically coupled. The quality, availability, and applicability of personal and organizational knowledge determine their individual and combined effectiveness. Different knowledge is required to tackle tasks and challenges and all parties must innovate and collaborate to create and renew knowledge. Major roles of knowledge are (Wiig, 2004): B

Awareness creation – uses knowledge to observe circumstances, i.e. situations, contexts, ideas, etc. from one or more perspectives.

B

Sense making – uses knowledge to assess, analyze and understand what the circumstances mean.

B

Problem solving – uses knowledge to evaluate, problem solve, innovate and decide to determine how to handle the circumstances.

B

Decision implementation – uses knowledge to execute the chosen decisions and implement the decisions through actions.

B

Governance – uses knowledge to monitor and judge appropriateness of deliberations, considerations and actions.

Knowledge consists of the tacit and explicit actionable capabilities required to reason and deal intelligently and effectively with situations. Knowledge of different kinds cannot be treated the same and that influences its use and management. When associated with individuals, organizations, cities and societies, knowledge serves different functions and has different forms. Knowledge may be personal, shared among people, embedded in artefacts, or be part of an organization’s or society’s makeup and culture. Knowledge possessed by people is mostly in their minds but it can also be external, as in personal documents. We distinguish between the following forms: Knowledge-as-object (KaO) is explicit, regularly observable and inspectable. It is regularly communicated as information. KaO is a small part of the total body of knowledge that is created and used by individuals, organizations and society. Explicable KaO can be possessed in a person’s mind as recallable mental models, specific episodic memories, and other mental objects that can be communicated on demand. Organizational KaO is included in narratives and stories, books, documents, or embedded computer software and hardware, etc. Implicit knowledge is not made explicit and may only be available through analysis of documents, stories, and the like. It can be implicit in stories, practices, software, systems, and procedures. It is also included in the collection of cases in case-based reasoning (CBR) systems and embedded in trained neural nets where it is difficult to explicate.

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‘‘ The world inside and outside a country is in constant flux – economically, environmentally, technically, socially and politically. ’’

Knowledge-as-process (KaP) results when individuals, groups or entire organizations tackle challenges that fall outside routine experiences. Individuals apply tacit knowledge to explore, engage in conceptual blending (Fauconnier and Turner, 2003), and seek explicit knowledge from available sources to handle challenges and by doing so learn from the evolving process. To address challenges, groups of people collaborate, help each other, and pool understanding to co-create while guided by shared goals. Organizations engage their people, systems, procedures, traditions, and culture to find and execute solutions. New knowledge often consists of innovative approaches that address the challenge. However, it may be ephemeral and tacit, result in personal learning, or be captured for further use. Tacit knowledge is embedded and may be impossible or difficult to make explicit. Some tacit knowledge can be made explicit over time. In people, tacit knowledge is generally inaccessible to conscious recall and reasoning when it is not well understood or highly automatized and has transgressed the recall barrier (Gazzaniga, 2004). In organizations, tacit knowledge is part of traditions, practices, reasons, and motivations behind networking. Metastrategic knowledge is part of metacognitive knowledge. It provides metacognitive perspectives that govern the attitude by which a person or an organization approaches complex challenges. Metastrategic knowledge generates the mentality for how challenges may be approached from a conceptual level given prior experiences with challenges in general. Metastrategic knowledge leads some people or organizations to be reluctant and risk averse while others are confident and action oriented (Johnson-Laird, 2006; Kuhn, 2000).A major SKM function is transfer of knowledge. Table II provides examples of various knowledge transfer modes and how some activities and knowledge-containing artefacts contribute to the different forms of knowledge. On education People are society’s basic knowledge agents and their knowledge growth through formal and informal education are required for competence to tackle challenges in the private and public sectors and are central for society to function and progress. Advanced tertiary and life-long-learning environments must be created. Modern primary and secondary school curricula such as the International Baccalaureate (IB) curriculum (Wikipedia, 2007) must be introduced along with specialized curricula for people with different intelligences and aspirations such as crafts people and others (Gardner, 1993, 2006, 2007). In addition, for many, the informal daily education obtained in rich cultures and work environments can be as important as formal schooling. Given the complex work environments that modern technology and general sophistication foster, people must be able to engage in contextual judgments and higher order and complex reasoning that provide proficiency for work and success in daily life (Adey and Shayer, 1994; Johnson-Laird, 2006; Kuhn, 2000; O’Brien, 2000). In general, people must possess schema and metaknowledge to innovate and to handle situations with dilemmas and trade-offs in multi-objective situations, long-term event chains, uncertainties, and missing information. Realistic participative learning environments must be developed and deployed. Conventional and technology-based interactive educational games and simulators must be created for selected knowledge areas and challenges. Examples include computer-based simulators to educate people to start and operate SMEs and prepare for pursuing job opportunities. Such capabilities will help people of all ages internalize libraries

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j Texts and other books Articles Educational software

Best practices studies

Personal ‘‘job hopping’’

Personally known facts Procedures Reports Presentations

Daily work by person single Articles Reports Manuals Knowledge bases Team work/collaboration Explicit working materials Books Reports Articles Briefings Communities of practice Shared documents (CoP) Articles Software Devices Presentations Networks of practice (NoP) Shared documents Presentations

General education

Knowledge transfer mode

Knowledge-as-object obtained from

Systems and procedures Work artefacts, e.g. machines, software, protocols Collaborators’ work products Systems and procedures Work artefacts, e.g. machines, protocols, practices Stories Articles Presentations Work products Practices Stories Presentations Articles Practices such as: ‘‘This is how we did it in my last job.’’ Case stories

Procedures Case histories Educational software

Implicit knowledge obtained from

Discussing Trying to understand others’ experiences Explaining last job practices to new employer Participating personally in study team

(Contained in total life experience to date) None

Understanding of stories and shared knowledge

Understanding of discussions Learning from problem solving Team innovations Understanding of discussions Understanding of shared knowledge

Discussing and exploring Problem solving and innovating Reporting Discussing and exploring Sharing knowledge

Study materials Teacher interactions Learning from hands-on practices Automatized work processes Own work discoveries and innovations

Tacit knowledge built by internalizing

Solving problems Working in laboratory Working in the field Collaborating Performing job tasks Innovating Preparing report

Knowledge forms Knowledge-as-process developed when

Table II Examples of knowledge transfers for different modes and knowledge forms

Embedded in the person’s perspectives, mentality, etc. None

Tacit understanding of role models

Tacit understanding of role models

Tacit and conscious reflections about work and associated experiences

Reflections on approaches and results for critical thinking, Mathematical proofs, etc. Tacit and conscious reflections about work and associated experiences

Metastrategic knowledge generated from

of mental reference models (Wiig, 2004) and should cover science, job-specific, and world-understanding knowledge domains with practical routines, scripts, schema, and metastrategic knowledge. Effective cities and districts The contribution of cities and districts to societal success is crucial. Cities are where people from the region come to find work, education, social and cultural life, and improved QoL. Cities are where industries come to find workforces and suppliers. Cities are where economic and commercial establishments come to find customers and other opportunities. Cities are where institutions of all kinds congregate to exchange ideas and learn what others do. Cities, in other words, are where all kinds of modern economic and societal activities come together, often congregating in specialized neighborhoods. Extensive networking in cities with good infrastructure make them become major generators of ideas – of new understandings, knowledge, and innovations. For cities to be effective, they must be diversified with a variety of complementary establishments that foster outsourcing, learning, and provide business opportunities. Diversity drives the city’s industries and commercial establishments in new directions when to deal with changes in technology and the economy. Cities provide the capabilities and resources that make it possible for societies to grow and progress – socially economically, industrially, and scientifically (Jacobs, 1970, 1985; Komninos, 2002). Cities must be attractive to draw people and institutions. They need a variety of highly competent people. They need ubiquitously available infrastructures – technical ICT, logistics and transportation, and municipal services. They must provide environments for exchange of ideas through networks of practice (NoP) that allow professionals from many areas to socialize and meet professionally (Brown and Duguid, 2000). They need advanced educational and research institutions to collaborate with local enterprises. City dwellers must be motivated to seek education, on-the-job learning opportunities, and collaboration. They must participate in communities-of-practice (CoP) to exchange experiences, personal knowledge, and knowledge-as-objects (Wenger, 1998). Unfortunately, most cities attract more people than can be employed and that infrastructures can handle, with the result that large slums develop.

A multi-tier societal knowledge-focused framework Effective strategies are required to build the broadly distributed knowledge and focus needed to drive society forward. Numerous areas warrant attention to build capabilities to participate successfully in the global knowledge economy. Societal, enterprise, and personal activities must be supported. Many educational systems are based on hundred year-old models and practices and need to be changed (Benner and English, 2006). The fundamental role of knowledge and KM for growth and progress is foreign to most, both ordinary individuals and leaders of enterprises, but must be understood. The understanding of how knowledge and SKM affect personal, enterprise, and societal functions is emerging but is in its infancy and focused more on discussions and plans than on actions. Targeted actions are required for societies to pursue participative global roles. Actions include direct investment in capabilities and services to provide incentives and reference models for society-wide, local, and personal actions. In most societies, the areas that need central and top-down knowledge-focused intervention include: 1. National plans. Long-term plans with short-term action-candidates are needed to strengthen IC for support of societal growth and progress. Many nations have already created such plans (Science, 2007). 2. Broad-based knowledge awareness. Enterprise managers and the general public need to understand and appreciate the role of knowledge and its active management for personal, institutional and societal success. Public initiatives like media campaigns and general informational efforts need to generate widespread insights.

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‘‘ The global knowledge economy changes the rules for national progress. ’’

3. Societal incentives. Knowledge building must be priority for organizations and individuals. Incentives need to accelerate these activities by introducing tax incentives for educational activities and grants. Other incentives include certifications of craft competence and other proofs of proficiency. 4. Reference role models and best practices. Targeted SKM must be shaped to support new contexts. Specific reference examples, stories, role models, and benefit illustrations help organizations and individuals determine how to proceed and act. Representative examples must be assembled in easy-to-access repositories and publications. Materials must cover applications and advantages for society, organizations, and individuals. 5. Infrastructures. Knowledge-empowered societies require knowledge-related infrastructures ranging from technology-based communications capabilities, to educational institutions, to legal mechanisms to protect intellectual property and promote intellectual freedom. Infrastructure capabilities motivate and facilitate enterprises to adopt effective business practices and operations and help individuals engage in knowledge-building activities otherwise not possible (Komninos, 2002; Reinslau, 2006). 6. Public services. Society cannot rely on local or private initiatives to provide every knowledge-related capability required. Long-term needs require investments for decades. Examples of initiatives are: B

Public R&D programs. Most enterprises have limited capabilities to undertake R&D with long-term, industry-wide or national implications. Public funding and institutions are needed to provide scientific foundations and spawn smaller, often private, enterprises.

B

Public educational system. A durable society needs continuous development of its competent workforce. Strong systems maximize individual learning from young age to late life. Educational opportunities must provide people with capabilities to pursue areas of personal strengths and interests (Gardner, 1993, 2006). Educational principles vary greatly, even within cities, and many are outdated. New curricula, modern technology and advanced practices are increasingly available and require infrastructure support and educator reeducation.

In addition, conventional public functions such as national governance, national defense, social services and health care, local law and order, and local infrastructure management functions are needed.

Societal knowledge management Effective SKM is required to build, maintain, and make the best use of the country’s broad knowledge assets. SKM helps to foster knowledge-related initiatives at all levels of society. SKM employs a mix of proactive and voluntary actions governed by personal and local contexts and knowledge-related infrastructures like apprenticeships, public education, basic research programs, and efficient ICT. SKM needs long planning horizons, consider broad implications, and pursue different approaches while also focusing deliberately on short-term results (Wiig, 2006). Management of knowledge from societal perspectives is not new. It has been a concern for societal progress for several thousand years – in China, India, Egypt, the Middle East, and in early societies in the Americas. Recent developments of practical approaches provide effective deliberate, systematic, and practical SKM. These approaches are based on

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understanding of human and social mechanisms and make SKM practices able to provide good results in the short and long term. Many countries have extensive experiences with SKM, broadly within their nations, districts and cities, targeted for industry and commerce, and detailed for individuals (Nordic Council of Ministers, 1998; Reinslau, 2006). SKM’s purpose is to build, safeguard, and utilize all important knowledge and other intellectual capital assets in every area of society to support and advance societal and private intents and objectives. This scope includes management of personal, industrial, commercial, and public and national knowledge assets. Intents and objectives are aimed to achieve durable long-term viability and success by fostering balanced, stable, and capable societies with good conditions for its enterprises and citizens. Goals include society’s overall welfare with effective cities, districts and regions and their institutions, profitable commercial and industrial enterprises, and personal success. Principles for effective SKM are that it must: B

Provide societal leadership to promote local and private KM initiatives without autocratic bureaucracy.

B

Govern and facilitate building, maintaining, safeguarding, and utilization of IC assets to support broad societal goals and intents.

B

Provide societal resources and support priority setting to achieve desired goals.

B

Pursue initiatives and practices that employ technology and rely on human and social mechanisms, which must be understood for initiatives and practices to be effective.

B

Rely extensively on educational institutions and infrastructure support such as ICT.

B

Obtain support by public opinion and voluntary action for best effectiveness.

B

Support development of higher-order learning and reasoning in addition to widespread literacy as fundamental goals for effective behaviors.

Premises for SKM include: 1. Citizens throughout society must be knowledgeable and responsible partners who can understand and judge societal issues independently to participate objectively in the public process. 2. An effective society requires competent public administration to perform normal work and with additional insights and perspectives to apply contextual judgment in non-routine situations. 3. A globally competitive society requires a variety of quality IC assets to build: B

Competent and well-educated workforces.

B

State-of-the-art government and industrial programs for basic and applied R&D.

B

Effective and innovative industrial and commercial establishments.

B

Effective and justly enforced laws and regulations.

4. Modern technology continually changes society’s culture, systems, procedures, and infrastructures. The changes affect personal proficiencies and how organizations and citizens interact with public services, enterprises, and other citizens. Widespread understandings must be built to work with and navigate the new environment. In general, SKM shares the same foundation as private sector KM. Hence SKM uses approaches developed and perfected in the private sector. Most management, organizational, and operational principles are similar. KM-related technology is also the same. Beyond private sector KM, SKM introduces additional objectives that require different approaches. For example, SKM’s broader scope includes helping people of all ages learn and reason at world-class levels. As part of their SKM some nations support pre-natal and infant care to increase children’s learning capabilities with the intent to facilitate their

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‘‘ Strong societal intellectual capital is required to create and maintain acceptable internal domestic and local conditions and to participate effectively in the global knowledge economy. ’’

educational achievements through school and college (Coffey and McCain, 2002; Saugstad, 1999). The nature of SKM is multifaceted. Some initiatives require management of publicly-funded programs such as support for R&D. Others set standards and policies for educational contents, achievement test principles, and how to deal with patents and intellectual property. Yet others involve international treaties and different approaches to safeguard and exploit ICs globally. Some involve creating public awareness of how to navigate, prepare for, and survive best possibly as their world changes by building awareness, shaping public opinion, citizen attitudes, and the general culture. Still others assist individual citizens understand how to manage personal knowledge-initiatives and help family members, children, and students make effective decisions. Table III provides examples of SKM activities as they relate to selected strategic and operational purposes.

Final thoughts The global knowledge economy places requirements on countries to build competent people, profitable enterprises, effective cities and regions, and desirable societies. These requirements are important and they are not simple and lead to significant challenges. Some of these challenges are: B

Fostering the political and public resolve to pursue successful knowledge-driven participation in the global knowledge economy require major efforts.

B

Building a multi-tier knowledge-focused planning and action framework and the associated culture involves many new perspectives and professional areas – but needs to transcend the whole society and be undertaken swiftly with long-term perspectives.

B

Upgrading cities and districts to become national growth-node knowledge cities with competitive enterprises, competent workforces, technical, educational, and social infrastructures requires political will, extensive – but rapid – planning, and considerable public and private resources.

B

Creating national R&D programs and facilities that complement and support industrial and national economic directions requires significant advanced professional resources.

B

Educating competent knowledge workers for all levels – professionals, paraprofessionals, craft workers will for most nations require significant changes in educational systems and practices. In many cases it will also require changes in educational philosophy and principles.

B

As observed by Peter Drucker: ‘‘The productivity of the newly dominant groups in the workforce, knowledge workers and service workers, will be the biggest and toughest challenge facing managers in the developed countries for decades to come. And serious work on this daunting task has only begun’’ (Drucker, 1992).

The world’s challenges are formidable, as can be seen by examining the map of world literacy rates presented in Figure 3. The challenges must be confronted and tackled by any country that intends to be successful – that wishes to provide its citizens good conditions, its industries and commercial establishments success and growth opportunities, its cities and regions viability, and its society stability and security while changing gradually to adapt to

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VOL. 11 NO. 5 2007 JOURNAL OF KNOWLEDGE MANAGEMENT PAGE 153

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Develop capable workforce

Build and leverage public and private knowledge

Prepare effective policy partners

Assure effective public service

Examples of purposes for managing knowledge Build SKM infrastructures Build communities of practice Build SKM core staff of KM professionals

Create web sites and public actions portals Create information repositories and libraries Create state-of-the-art public interfaces Create strategy, tactics, and Conduct extensive education – short-term plans infants to adult LLL Obtain legislative support and Build public R&D, technology and funding innovation parks Govern Build libraries and knowledge repositories Create vision for workforce Develop curricula, tests, educational materials development Develop guidelines and standards Provide ICT infrastructures for mainstream educational tracks Educate and reeducate teachers Obtain legislative support and and administrators funding

Create societal vision Survey and map current state of knowledge and IC Provide incentives, guidelines and policies to upgrade knowledge Create visions for how knowledge can assist better government Obtain fundings and legislative support Govern SKM

Examples of governance activities

Undertake publicly supported knowledge-sharing programs Award contracts and conduct public R&D Conduct knowledge exchanging conferences Educate, collaborate, share knowledge Develop and communicate educational role models Transfer topic knowledge, metaknowledge, and critical thinking

Provide deep communications of proposed actions Maintain publicly accessible data bases Create learning materials

Educate public servants Capture innovations, lessons learned, other knowledge Transfer expertise through CoPs

Examples of knowledge-related activity areas Examples of infrastructure activities Examples of operational activities

Table III Examples of SKM activities for some knowledge-related purposes

Support industry growth by developing competent workforce Deliver world-competitive products and services Provide incentives to decrease unemployment and increase QoL

Export products and services from high technology firms Export basic industry products with maximum value-added by using world-class expertise

Collaborate extensively Practice ‘‘always use best knowledge’’ Allow public servants to use their expertise Engage citizens and interest groups Obtain feedback to understand Encourage citizen participation in public decision making

Examples of general SKM activities

Figure 3 World adult literacy rates in 2000

the rest of the world. That does not only apply to the developing world but equally to advanced industrialized nations that plan to continue to thrive.

Note 1. In this article, knowledge is considered to be part of the broader concept of intellectual capital. The two terms will be used interchangeably.

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Fauconnier, G. and Turner, M. (2003), The Way We Think: Conceptual Blending and the Mind’s Hidden Complexities, Basic Books, New York, NY. Galbraith, J.K. (1996), The Good Society: The Humane Agenda, Houghton Mifflin, Boston, MA. Gardner, H. (1993), Multiple Intelligences: The Theory in Practice, Basic Books, New York, NY. Gardner, H. (2006), Multiple Intelligences: New Horizons, Perseus, New York, NY. Gardner, H. (2007), Five Minds for the Future, Harvard Business, Boston, MA. Gazzaniga, M.S. (Ed.) (2004), The Cognitive Neurosciences III, 3rd ed., MIT Press, Cambridge, MA. Gordon, E.E. and Gordon, E.H. (2002), Literacy in America: Historic Journey and Contemporary Solutions, Praeger, New York, NY. Harrison, L.E. (2000), Underdevelopment is a State of Mind, Madison, New York, NY. Hayek, F.A. (1945), ‘‘The use of knowledge in society’’, The American Economic Review, Vol. 35 No. 4, pp. 519-30. Hazen, R.M. (2002), ‘‘Why should you be scientifically literate?’’, an ActionBioscience.org original article, available at: www.actionbioscience.org/newfrontiers/hazen.html Jacobs, J. (1970), The Economy of Cities, Vintage, New York, NY. Jacobs, J. (1985), Cities and the Wealth of Nations, Vintage, New York, NY. Johnson-Laird, P.N. (2006), How We Reason, Oxford University Press, New York, NY. Katz, L. (2000), ‘‘The importance of investing in literacy’’, Children’s Literacy Initiative, available at: www.cliontheweb.org/investing1.html Komninos, N. (2002), Intelligent Cities: Innovation, Knowledge Systems and Digital Spaces, Spon Press, New York, NY. Kuhn, D. (2000), ‘‘Metacognitive development’’, Current Directions in Psychological Science, Vol. 9 No. 5, pp. 178-81. Malhotra, Y. (2002), Measuring knowledge assets of a nation: knowledge systems for development’’, Keynote Presentation at United Nations, Advisory Meeting of the Department of Economic and Social Affairs, New York. Mintzberg, H. (2001), ‘‘A Dialog with Dr Henry Mintzberg’’, Monograph 7: Philia Dialogue Series Creative Responses to Social Obligations, available at: www.philia.ca/actions/dialogue%20seven.htm Mintzberg, H. (2002), ‘‘Heretic in the Ranks’’, Scotland on Sunday, 9 June, available at: http:// scotlandonsunday.scotsman.com/business.cfm?id ¼ 626272002 NEFE (2002), Financial Literacy in America: Individual Choices, National Consequences, National Endowment for Financial Education, Greenwood Village, CO, available at: www.nefe.org/pages/ whitepaper2002symposium.html Nordic Council of Ministers (1998), Sustainable Development – New Bearings for the Nordic Countries, available at: www.norden.org/miljoe/sk/uk-pop.pdf Ntoso, A. (2006), Africa i-Parlaments: Gap Analysis, available at: www.parliaments.info/ 05_problem_statement/02_gap_analysis O’Brien, C. (2000), ‘‘We’re six, therefore we think – expanding children’s minds’’, The Times, 4 May, pp. 3-4. Polany Levitt, K. (2006), ‘‘Reclaiming policy space for equitable economic development’’, Post-autistic Economics Review, Vol. 38, 1 July. Prescott Allen, R. (2001), The Wellbeing of Nations: A Country-by-Country Index of Quality of Life and the Environment, Island Press, Washington, DC. Reinslau, K. (2006), ‘‘Knowledge management in Estonian regional administration: background, outputs, and unused resources’’, Information Technology for Development, Vol. 12 No. 1, pp. 63-76. Riege, A. and Lindsay, N. (2006), ‘‘Knowledge management in the public sector: stakeholder partnership in the public policy development’’, Journal of Knowledge Management, Vol. 10 No. 3, pp. 24-39. Romer, P. (1986), ‘‘Increasing returns and long-run growth’’, Journal of Political Economy, Vol. 94 No. 5, pp. 1002-37.

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Romer, P. (1990), ‘‘Endogenous technological change’’, Journal of Political Economy, Vol. 98 No. 5, pp. S71-S102. Romer, P. (2007), ‘‘Economic growth’’, in Henderson, D.R. (Ed.), The Concise Encyclopedia of Economics, Liberty Fund, Indianapolis, IN, available at: www.stanford.edu/,promer/EconomicGrowth. pdf Rose, J.R. (2006), ‘‘Condition critical: American hospitals face a severe undersupply of allied health professionals’’, Schmidt Labor Research Center Seminar Research Series, University of Rhode Island, Kingston, RI, available at: www.uri.edu/research/lrc/Papers/Rose_Healthcare.pdf Saugstad, L.F. (1999), ‘‘Optimality of the birth population reduces learning and behavior disorders and sudden infant death after the first month’’, Acta Paediatrica, Vol. 88, Supplement 429, pp. 9-28. Science (2007), ‘‘Science Japan picks up the ‘innovation’ mantra’’, 13 April, p. 186. Skapinker, M. (2003), ‘‘In search of a balanced society: interview with Henry Mintzberg’’, Financial Times, 16 September. UN-Habitat (2006), ‘‘Mumbai’s quest for ‘world city’ status’’, State of the World’s Cities 2006/7, UN-Habitat, Nairobi, Kenya, available at: ww2.unhabitat.org/mediacentre/documents/sowcr2006/ SOWCR%2012.pdf UNESCO (2001), International Literacy Day 2001, available at: www.sil.org/literacy/LitFacts.htm UNESCO (2002), International Literacy Day 2002, available at: www.uis.unesco.org/en/stats/statistics/ ed/map_illit_monde2000.jpg Warsh, D. (2006), Knowledge and the Wealth of Nations: A Story of Economic Discovery, Norton, New York, NY. Wenger, E. (1998), Communities of Practice: Learning, Meaning, and Identity, Cambridge University Press, New York, NY. Wiig, K.M. (2002), ‘‘Knowledge management in public administration’’, Journal of Knowledge Management, Vol. 6 No. 3, pp. 224-39. Wiig, K.M. (2004), People-focused Knowledge Management: How Effective Decision Making Leads to Corporate Success, Butterworth-Heinemann, Boston, MA. Wiig, K.M. (2006), ‘‘Societal knowledge management in the globalised economy’’, International Journal of Advanced Media and Communication, Vol. 1 No. 2, pp. 172-91. Wikipedia (2007), ‘‘The International Baccalaureate (IB) Programme’’, Wikipedia, available at: http://en. wikipedia.org/wiki/IB_Diploma_Programme

Further reading Drucker, P.F. (1999), Management Challenges for the 21st Century, Harper Business, New York, NY.

About the author Karl M. Wiig is chairman and CEO of Knowledge Research Institute, Inc. and Knowledge Management Adjunct Professor at The Hong Kong Polytechnic University. As technical and management consultant for more than 45 years, he helps organizations develop systematic approaches to manage intellectual capital and effective decision making. His present concerns are societal knowledge management and people-focused knowledge management. He has international reputation for his work in Knowledge Management, applied artificial intelligence and management science and has published over 70 textbook chapters and research articles and five KM books.

To purchase reprints of this article please e-mail: [email protected] Or visit our web site for further details: www.emeraldinsight.com/reprints

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Call for papers Journal of Knowledge Management Annual special issue on

Knowledge-based development Guest Editor: Francisco Javier Carrillo The Journal of Knowledge Management Special Issue on Knowledge-based Development is published annually. This is the call for papers for the 2008 special issue. Each issue includes both commissioned and submitted papers. Submissions for publication of original research, case studies, strategies, tools and techniques on urban, regional, national and supranational Knowledge-based Development are welcomed. Some of the topics of interest are: . Dynamics of social knowledge-based value creation . . . . . . .

Identification, measurement and strategic development of social intellectual capital National, regional and urban KBD planning and development Knowledge cities concepts and models Descriptions and assessments of implementation cases Metrics, benchmarkings and comparative analyses Social accounting and strategy deployment Social learning networks and social knowledge bases

Knowledge citizenship, access to information and distributed participation . ITCs and social bases of instrumental capital . KBD policy and cultural issues .

Global marginalization and the knowledge divide Systems perspectives on KBD . Radical KBD as a strategic and disruptive paradigm . .

Please indicate your intention to contribute at your earliest convenience to: Professor Francisco J. Carrillo E-mail: [email protected] Submission deadline is February 1, 2008. All commissioned and submitted papers are expected to fully comply with JKM standards and are subject to regular review procedures. An early compliance with format, style and readability guidelines significantly alleviates the review process by allowing it to concentrate on content. Emerald submission guidelines are available at: www.emeraldinsight.com/info/ journals/jkm/notes.jsp

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