Re-imagining Technology Enhanced Learning: Critical Perspectives on Disruptive Innovation [1st ed.] 9783030557843, 9783030557850

This book analyses technology enhanced learning through the lens of Disruptive Innovation theory. The author argues that

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Re-imagining Technology Enhanced Learning: Critical Perspectives on Disruptive Innovation [1st ed.]
 9783030557843, 9783030557850

Table of contents :
Front Matter ....Pages i-ix
Introduction (Michael Flavin)....Pages 1-8
Whatever Happened to Technology Enhanced Learning? (Michael Flavin)....Pages 9-42
Virtual Library Environment? VLEs in Practice (Michael Flavin)....Pages 43-58
This Chapter Is a Stub: Wikipedia as a Disruptive Innovation (Michael Flavin)....Pages 59-78
Putting a Brave Face on it: Social Media Technologies and Disruptive Innovation (Michael Flavin)....Pages 79-99
Cash in the Academic: Technology Enhanced Learning and the Monetisation of Higher Education (Michael Flavin)....Pages 101-119
Reboot the Messenger: A Narrative for Technology Enhanced Learning (Michael Flavin)....Pages 121-144
Conclusion: Switch It Off, Switch It on Again—Reimagining Technology-Enhanced Learning in Higher Education (Michael Flavin)....Pages 145-200

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Re-imagining Technology Enhanced Learning Critical Perspectives on Disruptive Innovation Michael Flavin

Digital Education and Learning

Series Editors Michael Thomas Liverpool John Moores University Liverpool, UK John Palfrey Phillips Academy Andover, MA, USA Mark Warschauer University of California, Irvine Irvine, USA

Much has been written during the first decade of the new millennium about the potential of digital technologies to produce a transformation of education. Digital technologies are portrayed as tools that will enhance learner collaboration and motivation and develop new multimodal literacy skills. Accompanying this has been the move from understanding literacy on the cognitive level to an appreciation of the sociocultural forces shaping learner development. Responding to these claims, the Digital Education and Learning Series explores the pedagogical potential and realities of digital technologies in a wide range of disciplinary contexts across the educational spectrum both in and outside of class. Focusing on local and global perspectives, the series responds to the shifting landscape of education, the way digital technologies are being used in different educational and cultural contexts, and examines the differences that lie behind the generalizations of the digital age. Incorporating cutting edge volumes with theoretical perspectives and case studies (single authored and edited collections), the series provides an accessible and valuable resource for academic researchers, teacher trainers, administrators and students interested in interdisciplinary studies of education and new and emerging technologies. More information about this series at

Michael Flavin

Re-imagining Technology Enhanced Learning Critical Perspectives on Disruptive Innovation

Michael Flavin King’s College London London, UK

Digital Education and Learning ISBN 978-3-030-55784-3    ISBN 978-3-030-55785-0 (eBook) © The Editor(s) (if applicable) and The Author(s), under exclusive licence to Springer Nature Switzerland AG 2020 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Cover illustration: © Stanislaw Pytel / Getty This Palgrave Macmillan imprint is published by the registered company Springer Nature Switzerland AG. The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

To Geraldine, Liam and Rosie.


I am grateful to my research assistants: Aditi Bhandari for work on virtual learning environments; Katerina Hulova for work on Wikipedia; and Ting Zhou Chen and Valentina Quintero for work on technology enhanced learning strategies.



1 Introduction  1 2 Whatever Happened to Technology Enhanced Learning?  9 3 Virtual Library Environment? VLEs in Practice 43 4 This Chapter Is a Stub: Wikipedia as a Disruptive Innovation 59 5 Putting a Brave Face on it: Social Media Technologies and Disruptive Innovation 79 6 Cash in the Academic: Technology Enhanced Learning and the Monetisation of Higher Education101 7 Reboot the Messenger: A Narrative for Technology Enhanced Learning121 8 Conclusion: Switch It Off, Switch It on Again— Reimagining Technology-­Enhanced Learning in Higher Education145 ix

1 Introduction

Viewed historically, Disruptive Innovation is a tautology. From the Renaissance onwards, uses of the word ‘innovation’ were accusatory rather than laudatory. Innovation was opposed to custom and order, and was disruptive by definition. As Godin (2013) argues, ‘Innovation was not the subject of inquiry, study or theory. It was a linguistic weapon used against an enemy: the revolutionary, the republican and, in the nineteenth century, the socialist’ (p. 19). The meaning of innovation changed. It became aligned with progress and utility. Instead of signifying chaos and disruption in the present, innovation offered progress in the future (Godin, 2013). The understanding of innovation further developed through the twentieth century; the phrase ‘technological innovation’ emerged after World War Two and was understood as commercialised invention (Godin & Vinck, 2017a). Understandings of innovation continued to shift in the second half of the twentieth century. Perren and Sapsed (2013) analyse the use of the word ‘innovation’ in UK parliamentary proceedings 1960–2005, finding a tenfold increase in its usage in parliamentary debates, as well as finding the term being used in an increasingly positive tone. Innovation has come to have invariably positive connotations, signifying something both © The Author(s) 2020 M. Flavin, Re-imagining Technology Enhanced Learning, Digital Education and Learning,



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inventive and aspirational. As Perren and Sapsed (2013) argue, ‘Thus, the successful introduction of novelty is seen as a worthy and important task in itself, and it has therefore become politically expedient to associate innovation with multiple agendas … providing solutions for the environment crisis, updating public services, educating children, governing health services, and for promoting economic growth and competitiveness’ (p. 1826). Innovation is now ubiquitous and an unalloyed good: ‘it seems as if all governmental functions must cater to the innovation discourse in order to appear economically defensible, politically legitimate, and modern’ (Pfotenhauer & Juhl, 2017, p. 82). The situation we have arrived at in respect of understanding innovation is such that, ‘Today, the concept of innovation is wedded to an economic ideology, so much so that we forget that innovation has been a mainly political—and contested—concept for most of history’ (Godin & Vinck, 2017a, p.  4). In the twenty-first century innovation is seen as good axiomatically, a signifier for progress and transformation, bringing benefits wherever it goes. Godin (2010) argues, ‘Innovation has shifted from being evil to being panacea’ (p. 38), while Godin and Vinck (2017b) add, ‘That innovation is good, always good, is the mantra in the study of innovation’ (p. 319). Other writers have noted the widespread applicability of innovation. Pfotenhauer and Juhl (2017) claim, ‘innovation is more than a mere vehicle for techno-economic development worthy of government attention: It is also a means of governing society through national projects, through the rationalization and legitimation of state action, and through national identity-formation’ (p. 83). We innovate, or we claim to innovate, in our economies, our societies, and our culture. Pfotenhauer and Juhl (2017) further argue, ‘The relationship between innovation and the state is without doubt one of the most important and challenging construction sites policy-makers face in highly technologized societies. Innovation has become a central arena for politics and societal self-­ imagination, perhaps the closest current-day equivalent we have to the promise of enlightenment of old’ (pp. 88–89). Moreover, innovation is one of the United Nation’s Sustainable Development Goals: ‘Build resilient infrastructure, promote inclusive and sustainable industrialization

1 Introduction 


and foster innovation’ (UN, 2019). You are nobody if you are not innovating. Resistance to innovation can be functional but it can also be psychological: innovations disrupt routines and humans can be attached to their routines (Laukkanen, Sinkkonen, & Laukkanen, 2009). Once a technology becomes embedded it can be hard to dislodge. Rivals to Microsoft can manufacture functional equivalents to the services offered by Microsoft Office, but users will tend to stay with convenient and easy to use technologies, and will often be tempted to stick with what they already know, leading to a form of lock-in. This book examines the specific theory of Disruptive Innovation and applies it to technology enhanced learning in higher education. The book identifies the kind of technologies that succeed, the technologies that fail, and uses Disruptive Innovation theory to evaluate the state of technology enhanced learning in higher education and where it might go hereafter. This is a necessary enquiry because of the extent to which technology usage pervades higher education practice. Selwyn (2014) argues, ‘you cannot hope to understand higher education without paying serious attention to the varied uses of digital technology across the sector’ (p. 110), and Weeks (2015) acknowledges, Disruptive Innovation theory is, ‘a powerful lens for examining certain technological advances’ (p. 426). The theory of Disruptive Innovation is closely associated with the work of Clayton Christensen (1952–2020). His original (1997) dualism was between sustaining and disruptive technologies. The former comprise incremental improvements of existing technologies; the latter prompt new practices. Subsequently, in a co-authored book (Christensen & Raynor, 2003), Christensen changed ‘technology’ to ‘Innovation,’ reflecting the argument that disruption is a matter of practice and not intrinsic to a technology. Disruptive Innovation is fundamentally a theory about goods and services. Godin and Vinck (2017c) argue, ‘Innovation theories are mainly developed in economics and management, which are partly geared towards industry’ (p.  111). However, Disruptive Innovation can be applied more widely and it is highly relevant to a sector in which technology usage is exceptionally rife, and in which the increasing privatisation of higher education blurs the boundaries between education, business,


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politics and economics. A range of examples of Disruptive Innovation are cited in this book, from bookselling to air travel to watchmaking. Illustrative comparisons are made between these practices and higher education, without forgetting higher education’s distinctiveness. Each individual chapter is briefly summarised in the paragraphs below. Chapter 2 summarises the theory of Disruptive Innovation. The chapter offers case studies to illustrate how Disruptive Innovation works in practice. The chapter argues Disruptive Innovation is a useful lens through which to consider technology enhanced learning in higher education, because it enables an understanding of which technologies succeed, and why they succeed. Chapter 3 looks at the virtual learning environment (VLE). The VLE is examined because it is an embedded, indeed ubiquitous technology in higher education. However, despite its transformative potential, the chapter argues the VLE is a sustaining innovation, offering marginal enhancements but not challenging established higher education practices. Chapter 4 examines Wikipedia as an example of a successful disruptive technology in higher education. Wikipedia conforms to Christensen’s (1997) core definition of a disruptive technology, being free, convenient and easy to use. It is also an example of Disruptive Innovation because of how it has changed practice. Wikipedia is often the first port of call for both students and lecturers when information is sought, despite the availability of institutional, and often costly, alternatives. However, Wikipedia is also commonly seen as academically inferior. The chapter therefore also evaluates Wikipedia as a resource to support learning and teaching in higher education. Chapter 5 examines social media technologies in higher education. They have the core characteristics of disruptive technologies, being free, convenient and easy to use. It is simple to join and use a social networking technology. However, social media technologies are not, in practice, a disruptive innovation. This is partly the result of demarcation; users opt to maintain distance between their social and learning personae. The chapter also examines social media technologies as an aspect of marketing in higher education; and as examples of communities of practice. The chapter analyses examples of the commercial and political usage of data

1 Introduction 


drawn from social media technologies, and how this fits within or conflicts with practice in higher education. Chapter 6 looks at the practice of Bring Your Own Device (BYOD); at user-owned technologies in higher education more generally; and at the monetisation of higher education. The practice of BYOD is of interest because it enables contrasting yet equally valid interpretations. On the one hand, BYOD can be seen in the context of the increasing privatisation and monetising of higher education. Having transferred the costs of tuition to students and their families, some higher education systems transfer the hardware costs, too. On the other hand, the use of technologies owned or rented by students is an expression of personal preference, in part because the affordances of user-owned technologies can exceed those offered by institutions. The practice of BYOD is simpler and more convenient for many than logging-on to an institution as a prior step to accessing and using resources, though the practice is also complicated as it expresses different economic and social influences on technology usage. Chapter 7 explores the narrative of technology enhanced learning in higher education. Disruption arises from practice more than design, but practice does not occur in a vacuum. Creating a narrative for what can be done with a technology is a significant spur to practice. The chapter therefore examines successful narratives for technology usage to see how narrative can provoke and enable Disruptive Innovation. The role of technology design in Disruptive Innovation is also considered as a factor shaping technology usage. The conclusion imagines what a future, Disruptive University might look like. The continued privatisation and monetisation of higher education can lead to a particular form of Disruptive Innovation. To describe, however, is not necessarily to approve. Instead, the purpose of the chapter is to suggest what could happen, not as a matter of inevitability but as a result of choices: political and economic choices, and social and technology choices. It is a question of considering what may happen if the current direction of travel is maintained. Another type of Disruptive University is also imagined in the conclusion, predicated on a different conception of higher education. The book as a whole argues higher education has not experienced Disruptive Innovation to date, but nor is higher education immunised


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against Disruptive Innovation. Moreover, Disruptive Innovation may be desirable in higher education because wider contexts change yet higher education serves up a largely unchanged product generation after generation, by unchanged means. As Selwyn (2016) argues, ‘the past 100 years show that education has been largely un-transformed and un-disrupted by successive waves of technological innovation’ (p. 439). This book therefore examines Disruptive Innovation in other practices and other types of institutions, to suggest how Disruptive Innovation might unfold in higher education. It argues that the technology innovation we have experienced and will experience is shaped by wider economic and social factors, yet it is not wholly determined by them. Innovation is not always easy, even when it is socially desirable. Replacing fossil fuels with renewable energy is desirable but powerful industry incumbents have economies of scale and the broader infrastructure and influence to possess economic and political advantages (Anadon et  al., 2016). Other factors shaping technology usage include technology design and the narratives we create for technologies. The future of technology enhanced learning in higher education is subject to factors outside higher education, but not wholly determined by them. We can still choose and direct the kind of technology enhanced learning in higher education that we want. Hellström (2004) argues ‘people make themselves through their labour; they can reshape themselves and society and, by extension, this is what makes them capable of eventually innovating for other purposes than those intended by the powers that be’ (p. 640). This book, underpinned by Disruptive Innovation theory, examines contrasting perspectives on technology enhanced learning in higher education and where they might take us.

References Anadon, L. D., Chan, G., Harley, A. G., Matus, K., Moon, S., Murthy, S. L., et al. (2016). Making technological innovation work for sustainable development. Proceedings of the National Academy of Sciences, 113(35), 9682–9690.

1 Introduction 


Christensen, C. M. (1997). The innovator’s dilemma: When new technologies cause great firms to fail. Harvard: Harvard Business School Press. Christensen, C. M., & Raynor, M. E. (2003). The innovator’s solution: Creating and sustaining successful growth. Boston: Harvard Business School Press. Godin, B. (2010). ‘Meddle not with them that are given to change’: Innovation as evil. Project on the intellectual history of innovation (Working Paper No. 6). Montreal, QC. Retrieved from VIKBB55/um/10_Godin.pdf Godin, B. (2013). Innovation after the French revolution, or, innovation transformed: From word to concept. Project on the intellectual history of innovation (Working Paper No. 14). Montreal, QC. Retrieved from http://www. Godin, B., & Vinck, D. (2017a). Introduction: Innovation—From the forbidden to a cliché. In B. Godin & D. Vinck (Eds.), Critical studies of innovation: Alternative approaches to the pro-innovation bias (pp.  1–16). Cheltenham: Edward Elgar. Godin, B., & Vinck, D. (2017b). Conclusion: Towards critical studies of innovation. In B.  Godin & D.  Vinck (Eds.), Critical studies of innovation: Alternative approaches to the pro-innovation bias (pp. 319–322). Cheltenham: Edward Elgar. Godin, B., & Vinck, D. (2017c). Moving towards innovation through withdrawal: The neglect of destruction. In B. Godin & D. Vinck (Eds.), Critical studies of innovation: Alternative approaches to the pro-innovation bias (pp. 97–114). Cheltenham: Edward Elgar. Hellström, T. (2004). Innovation as social action. Organization, 11(5), 631–649. Laukkanen, T., Sinkkonen, S., & Laukkanen, P. (2009). Communication strategies to overcome functional and psychological resistance to internet banking. International Journal of Information Management, 29(2), 111–118. Perren, L., & Sapsed, J. (2013). Innovation as politics: The rise and reshaping of innovation in UK parliamentary discourse 1960–2005. Research Policy, 42(10), 1815–1828. Pfotenhauer, S. M., & Juhl, J. (2017). Innovation and the political state: Beyond the myth of technologies and markets. In Critical studies of innovation: Alternative approaches to the pro-innovation bias (pp.  68–96). Cheltenham: Edward Elgar. Selwyn, N. (2014). Digital technology and the contemporary university. Abingdon: Routledge.


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Selwyn, N. (2016). Minding our language: Why education and technology is full of bullshit… and what might be done about it. Learning, Media and Technology, 41(3), 437–443. United Nations (2019). Sustainable Development Goals, Weeks, M. R. (2015). Is disruption theory wearing new clothes or just naked? Analyzing recent critiques of disruptive innovation theory. Innovations, 17(4), 417–428.

2 Whatever Happened to Technology Enhanced Learning?

This chapter introduces Disruptive Innovation theory. The chapter uses Disruptive Innovation to examine technology enhanced learning in higher education. It summarises a number of examples of Disruptive Innovation to illustrate aspects of the theory. Disruptive Innovation is a suitable lens through which to examine technology enhanced learning in higher education because it enables the identification of technologies and practices that have been genuinely transformative, or which have the potential to be transformative. Disruptive Innovation is a theory about goods and services, which emerged from Harvard Business School in the 1990s and is most closely associated with the work of Clayton Christensen. It describes a process whereby innovative goods or services enter and disrupt a market which has powerful incumbents. In some instances, disruptive innovations can render existing practices obsolete and completely unseat the incumbents. Nagy, Schuessler, and Dubinsky (2016) argue, ‘disruptive innovations cause a market to behave differently’ (p. 120), indicating the impact of Disruptive Innovation. The development of the railway network in the UK in the nineteenth century, for example, had consequences beyond transport, imposing a regulated, standardised system of time in the UK. © The Author(s) 2020 M. Flavin, Re-imagining Technology Enhanced Learning, Digital Education and Learning,



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In Christensen’s early books (Christensen, 1997; Christensen & Raynor, 2003), Disruptive Innovation is positioned against Sustaining Innovation. The latter process involves the incremental improvement of existing technologies. However, technologies developed along Sustaining Innovation lines can result in improvements which do not serve customers’ needs, producing, instead, product overshoot, whereby the measure of improvement exceeds customers’ requirements. Personal computers, for example, as they developed, often came with a plethora of software programmes, the majority of which were unused or underused by customers. The emergence of tablet computers and smartphones, perhaps most notably Apple’s iPad and iPhone, changed the landscape by selling a tabula rasa, which the customer modified through their own selection of apps, the product doubling-up as a platform. While the Blackberry looked like a miniaturised PC, with ‘Qwerty’ keyboard below the screen, iPads and iPhones had a screen on which a keyboard could be summoned, but purpose was determined by the user more than by design. The potential to innovate was built-in to the hardware. Christensen and Raynor (2003) argue technologies, in and of themselves, are not disruptive. They acquire a purpose through practice. Disruption is a process, not an event. Latterly, a third category has arisen, Efficiency Innovation, which enables us to do more with less (Christensen, Bartman, & van Bever, 2016). Montoya and Kita (2017) argue, efficiency innovations, ‘get rid of inefficient structures, unnecessary intermediaries, and rescue costs.’ Eliminating sales support, for example, is an efficiency innovation. However, at the same time as they threaten jobs, efficiency innovations can bring benefits. Handing a customer a cup and pointing them to the drinks dispenser does away with the job of a member of waiting staff, but it allows the customer to refill their drink, getting more for their money. The customer doubles up as waiter but may benefit from the transformation. A lot of early research on Disruptive Innovation started with variations on a question: ‘why it was that firms which at one point could be esteemed as aggressive, innovative, customer-sensitive organizations could ignore or attend belatedly to technological innovations with enormous strategic importance’ (Christensen & Bower, 1996)? Part of the answer was that firms concentrated on their most profitable customers and were

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vulnerable to an innovator coming in at the low end of the market, or creating a new market. In the short term, disruptive technologies are often non-disruptive (Schmidt & Druehl, 2008). They make limited impact, and such impact as they do make is on less profitable customers, or a modest number of new consumers. Schmidt and Druehl (2008) argue: ‘Preferences in this new market are so divergent (detached) from the current market that reducing the price of the current product a bit would not have enticed the detached market to buy it’ (p. 351). Incumbents may well be aware of disruptors at their periphery but the disruptor has no impact on the incumbent’s business model and so the incumbent ignores the disruptor, enhancing the disruptor’s opportunity. Yu and Hang (2010) ague, ‘entrants with inferior technology generally win because of innovative business models or a deep understanding of non-consumption’ (p. 441). Disruptions introduce new forms of practice and create and develop new markets. Furthermore, once they have a foothold, disruptive innovations progress along Sustaining Innovation lines, improving their standards, further encroaching on the incumbent’s territory. As Schmidt and Druehl (2008) argue, ‘over time the disruptive innovation improves on the primary dimension to the extent that it eventually appeals to the very mainstream customers that initially shunned it’ (p. 347). Disruptive innovations can be low end or new market. Low end disruptions emerge at the bottom of existing markets; new market disruptions make goods and services available to people who did not have access to them at all. Li (2013) argues that in low end disruption, the disruption is primarily the lower price, comprising market disruption. In new market disruption, the disruption is at the levels of both market and technology. Christensen (2002) argues disruptive innovations, ‘appeal to a new, small and initially unattractive (to established firms) set of customers, who use them in new or low-end applications’ (p.  34). For example, ‘many people loved the first personal computers, no matter how clunky the booting process and limited the software the machines could run, because the alternative … was no computer at all’ (p. 34). Furthermore, ‘By assaulting the low end of the market and then moving up, a new company attacks, tier by tier, the markets from which established competitors are motivated to exit’ (p. 36). Low-end disruptive innovations


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latch onto existing markets at the periphery but then move through the market. An example of low end disruption can be found in the car industry in the USA; Toyota entered it with economy cars which only generated low profit margins (Christensen, Grossman, & Hwang, 2009; Schmidt & Druehl, 2008). From this bridgehead, Toyota established itself as a notable player in the USA car market, improving along Sustaining Innovation lines and engaging in wider swathes of the market. It was both a low end disruption, appealing to customers at the bottom end of the existing market, and a new market disruption, appealing to people who could not afford cars previously: Montoya and Kita (2017) argue, ‘Intuition would tell us that disruptive technologies should not succeed in the market since they offer worse performance. However, performance has to be understood in relation to customers.’ Incumbents defend against rivals’ sustaining innovations but disregard disruptive innovations because disruptive innovations are not initially perceived as a threat. According to Raynor (2011), when new entrants to markets replicate the strategies of powerful incumbents, they tend to fail. However, if they pursue a relatively less attractive market they can gain a foothold from which they can progress. A powerful incumbent enhancing its existing provision is likely to succeed, unless the innovation overshoots the needs of its customers, offering marginal enhancements that the customer does not need or value. However, given that sustaining innovations are successful for lengthy periods until a disruptor appears, incumbents are unwilling to adopt a Disruptive Innovation strategy. Conversely, a new entrant to a market is likely to fail with a sustaining innovation, because powerful incumbents are already in place, but may succeed with a disruptive innovation. Technologies have a history of being displaced. Valve radios were disrupted by the transistor radio (Christensen & Raynor, 2003) which, in turn, was disrupted by radio over the internet. Adner and Zemsky (2005) argue, ‘the disruptive technology is … initially purchased by consumers in a secondary (niche) market segment, who place high value on the new technology’s attribute mix’ (p.  230). Rosenbloom and Christensen (1994) note that the first transistor radio was marketed in 1954, but the breakthrough was Sony entering the

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market in 1957, with Sony being a notable innovator in the post-World War Two economic revival in Japan: Markides (2012) argues, ‘Disruptive innovation has been credited as the strategy that led to Japan’s economic development after World War II.’ The incumbents in the radio industry understood the new technology but did not change their strategies. They had established business models and pursued their most profitable customers at the top end of the market. Meanwhile, the disruptor grew. A key feature of Disruptive Innovation is that purpose arises through practice, not design. The smartphone was not designed to disrupt road atlases or satnav devices, but the Google Maps navigation app did disrupt (Downes & Nunes, 2013). The smartphone was originally a disruptive innovation, in the sense of changing the means by which people accessed the internet, but it can now also be seen as a sustaining innovation through the introduction of lithium batteries and other changes that reduce the smartphone’s weight and increased its run-time (Brackin, Jackson, Leyshon, & Morley, 2019). High end disruption is also possible and occurs when a new product or service enters at the top end of a market before spreading downwards into mass markets. Carr (2005) gives the example of FedEx, which offered a premier document delivery service to high end customers. Having established a foothold and a market position, FedEx was able to grow. Another example of successful high end disruption is the calculator, as summarised by Schmidt and Druehl (2008): ‘The calculator’s attributes were exactly what high-end customers … wanted, and these high-end customers were the first to buy. As calculator prices came down, calculators relatively quickly diffused down-market to those customers with lower willingness to pay’ (p. 362). An advantage of high end disruption is that it tends to be visible from the outset and can create a brand to which mainstream customers aspire. Kostoff, Boylan, and Simons (2004) examine why incumbents often fail to engage with the possibilities of disruption despite being aware of it, given that, ‘Disruptive technologies offer a revolutionary change in the conduct of processes or operations’ (p. 141). However, disruptive innovations, at first, generally offer lower profit margins. In terms of organisational strategy, ‘A technology with the potential to radically reduce the cost of a product, but whose application is years in the future, and whose


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cost is being borne currently, is likely to reduce current profitability, and unlikely to enhance one’s upper management career’ (p. 144). Henderson (2006) argues, ‘senior teams are, in essence, captured by their largest, most profitable customers, making it exceedingly difficult to allocate resources to initiatives that serve new customers at lower margins’ (p. 5). When incumbents are disrupted, it is not solely a question of technology. It is also a question of the incumbent not changing its strategy because it has a consistent number of customers who value existing goods and services and maintain the prosperity of the organisation. Disruptive Innovation has critics. For example, while Disruptive Innovation argues innovation is a ground-up process, with purpose for technology arising through practice, Markides (2006) argues it can be consciously created, citing Amazon and Swatch as examples. Neither book selling nor watchmaking were innovations in themselves, but both companies changed customer perspectives and markets. Moreover, disruption is not axiomatically good. Cortez (2014) identifies novel securities instruments that contributed to the 2008 financial crisis as a disruptive innovation. In addition, Dutton, Cheong, and Park (2004) argue, ‘a new idea could be silly, have harmful unintended consequences, or just fail to diffuse and fade from sight’ (p.  132). A new product or service is not disruptive by definition but by practice. Many potential disruptors fail, and others have impact but can be economically and socially damaging. However, the fiercest criticism of Disruptive Innovation has come from Lepore (2014) who, in a New Yorker article, attacked Disruptive Innovation’s methodology, which is, primarily, the retrospective case study. The problem with the retrospective case study is that it enables cherry-picking, in the sense of only featuring case studies that validate the hypothesis. The internet has disrupted many areas of practice that seemed secure. The music industry has changed radically and so has the newspaper industry, but higher education is largely unchanged. Most students still attend campus universities; most students attend lectures as a primary teaching instrument; and most students submit written assignments and undertake examinations. Technology enhanced learning promised a digital revolution. Influential articles such as Prensky (2001) posited a digital generational divide and created the ‘digital natives/digital immigrants’

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dualism, but subsequent research (Jones, 2012) exposed fundamental flaws in the hypothesis, though other writers have argued for a continuing socio-economic divide in digital competence (Hargittai, 2010), analysing effective access (what people can utilise the internet for) as well as technical access (being able to get onto the net in the first place). Dutton et  al. (2004) argue technologies are, ‘inherently political innovations because they are anchored in choices that reconfigure access to information, people, services and technologies’ (p. 133). It appears there is no substantial generational technology divide and it further appears there is no digital revolution. Having summarised Disruptive Innovation theory, the next section looks in more detail at individual case studies of Disruptive Innovation and what can be learned from them.

Case Studies of Disruptive Innovation A number of examples are offered in this section to illustrate Disruptive Innovation. These range from the telephone, to the electric light bulb, through to retail businesses, air travel, video technology, and other goods and services. The President of Western Union, a major American telecommunications company, declined to buy the patent for Alexander Graham Bell’s telephone in the eighteen-seventies, describing it as an, ‘electric toy’ (Sultan, 2013, p. 162). The telephone began as a one-way device disruptive to telegraphy, but it developed along Sustaining Innovation lines into a two-way device. With Western Union declining to buy the patent, it was taken up by AT&T, a smaller company with a niche market (Latzer, 2009). Much later, in the nineteen-eighties, AT&T hired a consultancy firm to assess the commercial viability of cell phones. The firm concluded the worldwide market for cell phones would amount to around 900,000 (Govindarajan & Kopalle, 2006), and thus AT&T, too, was disrupted. The core technology for cell phones had long been possessed by companies such as AT&T in the USA and Ericsson in Sweden. However, an infrastructure was also necessary, including sales outlets and relationships


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with telecom providers (Vidal & Mitchell, 2013). Nokia built an infrastructure and maintained a position of market pre-eminence until the advents of smartphones. The telephone was a classic disruptive innovation, but cell phones are a good example of high end disruption, whereby goods and services enter at the top end of markets. Cell phones were originally bought by corporate executives before spreading down market (Yu & Hang, 2010). Classic Disruptive Innovation happens at the low end of existing markets or creates new markets. Schmidt and Druehl (2008) note, ‘Cell phone sales grew for roughly 25 years before beginning to encroach on land lines … As cell phones became a little less bulky and less costly and as coverage improved, the first significant direct encroachment on the land-line market was with lower-end land-line users such as college students and second lines in homes’ (p.  359). Having emerged initially as a disruptive innovation, the cell phone, too, developed along Sustaining Innovation lines. Akbar and Ozuem (2019) argue corporate executives welcomed cell phones, ‘since they offered convenience and portability … mainstream customers continued to favour landlines for their comparatively low prices, better coverage and reliability. Yet, over time, mobile technology caused disruption, as the progression of the technology made it possible to increase the coverage and reliability of the service at a cost that was acceptable and affordable to mainstream customers.’ The cell phone changed telephony but has also changed practices more widely. Cell phones enable work to take place outside the workplace and social activity to take place in the workplace, albeit surreptitiously at times. They blur the lines between the workplace and domestic space and the transit between the two. They can also extend the working day. Williamson and Zeng (2009) outline an example of how high end disruption changed an entire market over time: ‘although cellular telephones are commonplace in India today…, that didn’t seem likely when companies started offering mobile telephony services back in 1995 …. After 2002, leading mobile telephony companies such as Bharti Airtel and Reliance Telecom stated lowering prices to grow the market and consolidate the industry. What started as a premium business then quickly became a mass market’ (p. 72). Disruptive innovations gain a foothold before permeating an entire market through Sustaining Innovation. The

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telephone, primarily a disruptive innovation, then a sustaining innovation, revivified its disruptive potential through cell phones, then smart phones. In each phase, the typical trajectory is an original disruption followed by a period of Sustaining Innovation until the next disruption. Furthermore, the cell phone market has not remained static, as noted by Hagel, Eckenrode, and Srinivas (2016): ‘Android has emerged as a de facto operating system, inviting any mobile phone manufacturer to use its operating system’ (p. 12). The market for cell phones has continued to innovate, and the extent of smartphone usage has grown continuously, too. Hargadon and Douglas (2001) show how Edison developed the electric light bulb and accompanying infrastructure. The invention was disruptive to the gas companies, who, ‘had a capital investment of approximately 1.5  billion dollars. In New  York, these companies had integrated themselves deeply within the city’s social, economic, political, and physical infrastructure, from their many gas mains buried under the streets to their extensive corps of city-employed lamplighters, to their powerful influence over the aldermen and mayor of New York’ (p. 484). Edison’s system was successful because it closely resembled gas lighting at the user interface. The system of electric lighting, ‘exploited past understandings but also preserved the flexibility to evolve beyond them and build wholly new institutions’ (p. 477). It looked like the existing technology but was, in fact, a new technology. New entrants in markets are more likely to act entrepreneurially, aiming to transform markets and build new ecosystems. This capability is important, because new technologies often require users to behave differently (Berglund & Sandström, 2017). By imitating the features of gas lighting, Edison displaced the technology of gas lighting without requiring dramatic changes in the surrounding understandings and patterns of use. Technologies that are simple, convenient and easy to use require less behavioural modification on the part of users and are more likely to succeed. The electric lightbulb was disruptive but it took consumers with it because electric light bulbs appeared to be a technology and practice with which they were familiar (see Chap. 7). Markides and Sosa (2013) cite the example of Enterprise Rent-a-Car, which disrupted the car rental market, offering a new business model


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rather than a new technology: ‘Rather than target travellers as its customers (like Hertz and Avis did), Enterprise focused on the replacement market (i.e. customers who had an accident). Rather than operate out of airports, it located its offices in downtown areas. Rather than use travel agents to push its services to the end consumers, it uses insurance companies and body shop mechanics. Rather than wait for the customer to pick up the rental, it brings the customer to the car. In short, Enterprise built a business model that is fundamentally different from the ones utilised by its biggest competitors. This allowed it to start out in 1957 as a new start­up firm in the industry and grow into the biggest competitor in less than 50  years’ (p.  328). A disruptor does not have to take customers from other businesses, at least initially. Instead, it can comprise a new market disruption by having a new business model, which can be more important than having a new technology. Vriens and Søilen (2014) argue, ‘disruption always needs a change in business model’ (p. 69). The business model of Enterprise expanded the market then developed along Sustaining Innovation lines to challenge the incumbents. Christensen (2002) argues Sony was a particularly successful disruptor between 1950 and 1980, introducing, ‘everything from radios and televisions to VCRs and the Walkman.’ Thereafter, however, Sony was less innovative; products such as the PlayStation and Vaio notebook were entries into already-established markets. Christensen (2002) argues the introduction of market research into Sony’s practice in the nineteen-­ eighties curtailed innovation, directing the company’s focus away from the creation of new markets and towards the exploitation of existing markets. Disruptive Innovation flourishes in the absence of restrictions, including the restrictions produced inadvertently by market research, which can focus on expanding existing markets rather than on goods and services that create new practices, finding their purpose through usage. Paradoxically, market research can curtail innovation because innovation often arises through practice rather than design. It is more serendipitous than scheduled. Vidal and Mitchell (2013) show that a portable cassette player was patented in 1972 by a German-Brazilian inventor, but it was Sony who achieved commercial success with the Walkman, launched in 1980. Sony had access to manufacturing facilities and marketing expertise. They also

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had the means of accessing the mass market internationally. There were competitor products (Toshiba’s Walky and Panasonic’s MiJockey), but Sony improved its product along Sustaining Innovation lines and, having gained a market advantage, sustained it until, in time, the Walkman was disrupted by the MP3 player (Palacios-Fenech & Tellis, 2016), now itself disrupted as people listen to music through their cell phones. Ryanair was started by two brothers, Cathal and Declan Ryan, in 1986. Their strategy was to compete on the London–Dublin route. The two established players on the route, Aer Lingus and British Airways, dropped their prices to force out the newcomer and by 1991 Ryanair was on the verge of bankruptcy. At this point it recruited Michael O’Leary and changed its strategy. All inessential expenses were eliminated, right down to pens for headquarters staff, and by 1992 Ryanair was profitable (Yoffle & Kwak, 2002). The new Ryanair strategy was to replace a diverse fleet with one type of plane. Furthermore, bookings were not taken through travel agents. Instead, they were made through call centres and, later, the internet. In addition, Ryanair eliminated business class and seat assignment. Ryanair charged for everything beyond the basic. It realised, ‘success depended not on being 10% cheaper but on being 80% to 90% cheaper’ (Kumar, 2006, p. 112). Ryanair started operating from secondary cities. Some of the airports in the secondary cities paid Ryanair to fly to them because of the economic stimulus created by having a regular throughput of travellers. Ryanair did not serve meals, which meant fewer flight attendants were needed. In addition, it stopped carrying cargo, nearly halving turnaround times in the process. In the 1990s, all the major airlines started no-frills second carriers, but none of them survived. Kumar (2006) argues a business needs one strategy, and having more than one is rarely successful. Ryanair practised low end disruption, taking customers from the incumbents, though it may also have had an element of new market disruption, too, by making air travel more affordable. Disruptive Innovation does not have to be destructive innovation (Yu & Hang, 2010). The example of Ryanair shows how incumbents can be disrupted yet still survive. Budget airlines have impacted on the market, but established providers in other areas of the market still exist (Rasool,


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Koomsap, Afsar, & Panezai, 2018). While disruptive innovators are commonly understood as unseating established goods and services, they can also cohabit and even co-operate with competitors. It is commonplace for disruptive innovations to make markets bigger, benefiting all, or most, participants. However, disruption is feared because of its potential to bring about significant change, posing a threat to powerful incumbents. In finance, First Direct bank is an offshoot from HSBC, marketing itself as a specifically online bank. Markides and Charitou (2004) note, ‘First Direct customers … are more satisfied with their ATM [Automated Teller Machine] network than HSBC customers are even though both use the same machines. Whereas HSBC customers demand ATMs at every corner, First Direct customers, who don’t expect so many machines, are delighted to see them.’ Moore (2004) notes how fault-tolerant computers were applied to the banking market to create ATMs (p. 88). Fault-­ tolerant computers were not created to enable ATMs but found a valuable application in ATMs, showing how purpose arises through practice. The ATM itself was both a sustaining innovation and an efficiency innovation. It was sustaining in allowing access to money outside of the bank’s opening hours. It was an efficiency innovation in terms of doing away with the need for a bank clerk, thus impacting on jobs. The emergence of contactless payment as a further efficiency innovation lessens the need for ATM machines, as contactless payment via bank card allows easy access to low-cost goods and services, without cash. Markides and Charitou (2004) further note, of First Direct, ‘the decision was made early on to keep the new unit as separate from the established bank as possible so as to minimize conflicts and prevent the parent’s existing processes and culture from suffocating the new business model’ (p. 25). This is a classic case study of an incumbent managing Disruptive Innovation by establishing a separate, innovative unit as a business in its own right, a strategy recommended by Christensen (1997) and Christensen and Raynor (2003). Christensen and Tedlow (2000) argue, ‘A disruptive technology enables innovative companies to create new business models that alter the economics of their industry’ (p.  42). They give the example of retailing. Local traders were disrupted by department stores, the disruption being facilitated by another disruptive innovation, the railway, which mobilised customers. Furthermore, infrastructure changes continued to disrupt

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retailing. Effective mail delivery enabled catalogue shopping: widespread car ownership made shopping malls possible. Car ownership also opened the way for discount stores. In an example from retail, Kumar (2006) argues, ‘Aldi doesn’t pamper customers … Aldi was one of the first retailers to require customers to pay refundable deposits for grocery carts. Shoppers return the carts to designated areas, sparing employees the time and energy needed to round them up. At the same time, Aldi gets the basics right. There are several checkout lines, so wait times are short even during peak shopping hours. Its scanning machines are lightning fast, which allows clerks to deal quickly with each shopper … In 2006, Germans voted Aldi the country’s third most-trusted brand, behind only Siemens and BMW.’ This leads to the conclusion, ‘Most low-cost players alter customer behaviour permanently, getting people to accept fewer benefits at lower prices.’ Aldi analysed the market, identified the market’s core elements and subtracted the rest. In common with Ryanair, it identified the job customers wanted to do and targeted the job, foregrounding cost and simplicity to gain market advantage. Amazon initially gained a foothold in the bookselling market, appealing to customers who were willing to forego in-store service for price and convenience. Moreover, Amazon was able to offer a broader selection of books than bricks-and-mortar retailers, as it did not need High Street premises with limited floor space. Having gained a foothold, Amazon was disruptive not merely on the book trade but, through expansion, on the entire retail sector. Amazon has expanded its operations to the extent that it, ‘leases its core technologies to third-party resellers. It even offers its expertise in online retailing and cloud computing to unrelated businesses that outsource their hardware and software needs to Amazon’ (Downes & Nunes, 2013, p. 54). Amazon has expanded from customer retail to providing services, notably in the form of a platform for the products of other businesses. Amazon has experienced failure, including the Fire smartphone and Amazon auctions, but these do not matter because the business has sufficient successes. AirBnB was originally ignored by the hotel industry, which saw the newcomer as appealing to a new set of customers, not disrupting its traditional model and its profits. However, and in common with other disruptive innovations, AirBnB, having gained a foothold, moved up


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market, encroaching on hotels’ customers, including business travellers. One of the consequences of AirBnB’s success is that revenue lost by hotels reduces taxation revenue (Dogru, Mody, & Suess, 2019), and thus the innovation has economic and social consequences. Disruptive Innovation is a process not an event, but it does not follow that disruption cannot happen quickly. Road atlases were disrupted by satnavs within a short period of time, but they, too, were disrupted quickly, by navigation apps. Navigation apps are a sustaining innovation on satnavs, but they were disruptive to the manufacturers of satnavs. Satnav apps also make local road knowledge largely irrelevant, aiding other disruptive innovations, notably, in road transport, Uber. Moreover, the satnav entered all sections of the market at once. It was not a question of innovation from the ground up, with the technology appealing to a previously disenfranchised community. The innovation was applicable right across the spectrum and caught on because of cost, simplicity and convenience. A feature of Disruptive Innovation is the incumbent retreating towards the top end of its own market, to such an extent that it offers products and services beyond its own customers’ needs (Christensen, 1997). However, the overshoots may be valued in some markets. At least one no-frills airline, Easyjet, sought to branch out into cruises, but without success. Easycruise opened for business in 2004 but by 2010 the business had closed. The strategy of Easycruise was to lower the cost of a cruise and thus create a new market, though experts had argued the low-cost strategy would not work in the cruising business (Gross, 2009). Customers on cruises expect frills as an integral part of the package. A particular innovation practised by Easycruise was to cut down on service quality by changing the ratio of staff to customers. High standard of service was not an unnecessary add-on to a cruise but an integral aspect of the experience. The potential disruptor lost sight of the job the customer wanted to do. In the videogaming industry, the case study of Nintendo shows disruption happens by targeting previous non-consumers, in this case by producing social activities based on outdoor sports. The Nintendo Wii disrupted the traditional gaming industry, but both old and new industry models cohabit. Katila and Chen (2008) argue Nintendo succeeded

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through simple games and graphics, undercutting the sustaining innovation practices of games manufacturers. Norman and Verganti (2014) argue, ‘With the introduction of the Nintendo Wii, console games opened up outside the normal, small niche segment of skilled experts and let the entire family play sports, exercise and interact with one another without requiring expert skills … Microsoft and Sony invested significant resources to develop even more powerful processors. Nintendo, meanwhile, challenged the existing meaning of game’ (p. 86). Markides (2012) notes that the Wii outsold Sony’s PlayStation 3 by three-to-one in Japan and five-to-one in the USA. Atari, which was taken over by Warner in 1986, had introduced a video games console in 1972 and had a notable success with the launch of the Space Invaders game in 1980 (Ernkvist, 2008). Atari also developed a business model whereby independent game developers could develop games for Atari but had to pay a percentage of their royalties to Atari. However, Nintendo, which launched its own console in 1974, gained greater market share, in part by developing more games for its console (Vidal & Mitchell, 2013). A plethora of products on the platform comprised a market advantage, appealing to a wider audience. Downes and Nunes (2013) argue teenagers used to flock to arcades, but the release of the Sony PlayStation in 1994, PlayStation 2 in 2000 and Xbox in 2001, turned gaming into a primarily home-based activity by offering arcade production standards in a home context, offering disruption through a different channel, targeting video games aficionados rather than non-consumers. Various waves of disruption have happened in the video gaming industry, leading to a mass market, and the home as the setting for gaming. The idea of the home as a sequestered space is challenged, as teenagers can interact together without having to physically congregate together. Cusumano, Mylonadis, and Rosenbloom (1992) show how Betamax and VHS formats competed for the video recorder market. Attempts to market a video recorder dated back to the 1950s, and by the 1960s Sony had the U-Matic which, though too large and expensive for homes, attained a foothold through sales to schools and other institutions. Sony were first in selling to the home market with the Betamax and accounted for the majority share of the market in 1975–1977. From 1978, however,


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VHS had greater sales, and by the end of the 1980s Sony had stopped production of the Betamax. Gawer and Cusumano (2014) argue everyone with a television was a potential customer for the video recorder, and so there was huge market potential. The market for video recorders initially grew on blank tapes but the market for pre-recorded tapes grew in the 1980s (especially in Europe where there were fewer TV channels than in the USA) and the Disruptive Innovation prompted economic growth with the emergence of retail outlets for tape rental. Disruptive innovations need infrastructure and networks to grow. They need vendors to trade the goods or services. Christensen et al. (2009) note, ‘when color television was invented, nobody would buy color TVs because no network was broadcasting in color. And networks would not broadcast in color because nobody owned color televisions’ (p. xxx). Disruptive Innovation succeeds in a context not a vacuum. The emergence of the video recorder in mass markets created a fear that video piracy would destroy the filmmaking industry, but in fact home viewing created a new and lucrative market (Currah, 2007). The first-mover in the market, Sony, had a potential advantage but, as Cusumano et al. (1992) argue, ‘An early mover into the market had no guarantee of a sustainable advantage from simply being first, but needed an effective strategy to capitalize on its position’ (p. 63). Neither Betamax nor VHS had a notable advantage over the other in terms of features, price or quality. The manufacturers of VHS (the JVC corporation) aimed for the USA market as route to domination, and allocated seventy engineers to the task of extending recording time so that consumers could record an entire game of American Football. Digital photography disrupted its industry. Benner and Tripsas (2012) note the first digital camera for consumers was available in 1991. Sales overtook analogue cameras in 2003. Of the eighty-three entrants to the market, twenty-five came from the photography industry, nineteen from consumer electronics, and twenty-five from computing. Five came from unrelated industries (including Disney and Mattel) and nine were start-­ ups (p. 282). Gilbert and Bower (2002) argue Kodak, in response to digital photography, adopted a Sustaining Innovation approach, as they, ‘hastily installed 10,000 digital kiosks in Kodak’s partner stores …

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Hewlett-Packard, Canon and Sony—did a better job. They launched products based on home storage and home printing capabilities and, in the process, uncovered new demand for convenience, storage, and selectivity’ (pp. 95–96), though Latzer (2009) argues, ‘with digital photography the seat of power can be seen as having moved from Kodak and Fuji to consumers rather than to other companies’ (p. 608). The momentum lay with the disruptor and the movement to home printing was unstoppable. In common with video games, photography moved from commercial outlets to homes and in so doing increased the commercialisation of domestic space. With shopping being undertaken from home, too, and work practices via cell phones, the idea of domestic space being cleaved from commercial space is undermined through technology. Some innovations succeed by accident. The fax machine had minimal sales in the first fifteen years of its operation, with only doctors and architects seeing use value in being able to exchange information by this means. However, strikes by postal workers increased the usage of fax machines and the innovation took hold (Holtham & Courtney, 2005). Furthermore, Innovations can be created by users rather than entrepreneurs. Von Hippel, Ogawa, and Jong (2011) give the example of the skateboard, invented by children hammering wheels removed from roller skates onto boards. The commercial development and exploitation of the invention came later. In addition, Dew, Sarasvathy, Read, & Wiltbank (2008) state, ‘the founders of Starbucks opened their first shop only as an outlet for selling fresh roasted and ground coffee beans from around the world, mostly since they themselves were coffee aficionados. Only requests from walk-in prospects for trying out the coffee in the shop led them to the idea of a coffee shop such as the modern Starbucks Coffee shops’ (p. 321). The disruptive innovations considered in this section challenged established markets but sometimes created new markets. They also identified the jobs customers wanted technologies to do. Thinking about higher education, there is exceptional scope, globally, for expanding provision. There is also a case for examining the circumstances in which current non-consumers might access higher education. A disruptor with a clear sense of the technologies required to meet the need, and with a business


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model to direct its practices and form a strategy, could gain a beachhead from which huge expansion would be possible.

Disruptive Innovation and Higher Education This section of the chapter looks at both successful and unsuccessful technological innovations in higher education. Innovation can be push or pull: technological innovations can impel and push change, or consumer demand can pull innovation into an otherwise ossified system. However, in higher education the core product is established, tried and tested. Therefore, and despite the plethora of technological innovations over the last generation, there is no great pull because the status quo tends to satisfy. There is, however, practice, and, from a Disruptive Innovation perspective, practice with technology can produce innovation. Google is a successful Disruptive Innovation. It is simple and convenient. It is often the first port of call for information on any subject, from train times to the meaning of life. Founded in 1998, by 1999 Google Search was already fielding seven million requests per day. By 2001, Google was making a profit (Zuboff, 2019). In 2006, Google paid $1.6  billion for YouTube within two years of its launch, later buying WhatsApp for $19 billion (Jones, 2019), using mergers and acquisitions to expand its reach and power. Google is not infallible, having been slow to realise the potential of social networking (Gawer & Cusumano, 2014), but its successes outweigh its failures. Google Wave launched in 2009, combining email, instant messaging, collaborative working tools and the embedding of other media. However, it closed in 2010. Kaewkitipong (2012) argues users found the system too complicated. Google Wave was multi-functional, but Christensen and Raynor (2003) argued the important question to ask of a technology is, what job does it do? In the absence of a clear, lucid answer, any technology will, they argue, flounder. The proprietal technologies of universities can be seen as a step backwards, relative to Google, in terms of how they are experienced. If a student wishes to use an academic journal database they have to log on to their institution’s home page, find its library services, find its academic journal databases, select one, then enter search terms in a range of

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different boxes. Alternatively, they can use Google Scholar, a sustaining innovation built on the disruptive innovation of Google. Jones (2019) notes how Google is a universal infrastructure, with its own educational sub-sections evident in Google Scholar. In this specific instance, an initial, disruptive innovation has developed along Sustaining Innovation lines and has changed practice in higher education, serving the needs of time-poor students and lecturers. Disruption is commonly a process that occurs from the ground up. The disruptor enters a market at the low end, or creates a new market for people not served by existing goods or services. In technology enhanced learning in higher education, technologies that have taken firm hold, such as Google, are distinct from technologies designed to support learning and teaching, such as virtual learning environments. Students and lecturers use Google despite its not having been designed as a technology specifically to support formal learning in higher education, its purpose having arisen through practice. However, Google is not the passive servant of the queries entered into it. Klawitter and Hargittai (2018) argue, ‘there is little concern on the part of users that Google manipulates results in a way that may steer them to pages not necessarily optimal for their query’ (pp. 3492–3493). Users look for instant results and tend to accept the results provided. Google is a disruptive innovation but not a socially and politically neutral one if it steers users in particular directions. As Zuboff (2019) argues, ‘There was a time when you searched Google, but now Google searches you’ (p. 262). Users’ data enables targeted advertising, and targeted solicitations for political support. While Google is a core feature of internet usage, other technologies were designed for education, including the Massive Open Online Course (MOOC). Initially, the MOOC was a ground-up innovation practised by enthusiasts (Selwyn, 2014), but its growth resulted in commercialisation by for-profit companies, at which point innovation acquired different functions and served different purposes, as the commercial providers needed to make a profit. The technology was potentially disruptive but was redirected and constrained by a business model. MOOCs were touted as disruptive but poor completion rates deflated the hype. The autodidacticism required to steer successfully through a


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MOOC presupposed a skill set which was most likely to have been developed through formal study, hence successful completers of MOOCs featuring a disproportionate number of learners who had already attained degrees or other significant educational qualifications (Conole & Brown, 2018; Laurillard, 2014). The MOOC is still with us but it is a Sustaining rather than Disruptive Innovation, building on traditional learning and teaching rather than disrupting it. The MOOC comprises an online course, a form of learning that has been around since the 1990s (Flavin, 2016; Lawton & Katsomitros, 2012), albeit with some added technological sophistication. MOOCs are not disruptive because they sustain and develop an existing practice. They may even be an example of product overshoot (Christensen, 1997), technologically impressive but exceeding the needs of the market. There may be an enduring role for MOOCs in providing just-in-time training in work-based learning contexts, but in this instance the MOOC is neither massive nor open. It is an online course. MOOCs can also be used to market an institution; for open and lifelong learning; or for academic credits; but they have not disrupted higher education. That said, the hype around MOOCs is not fully extinguished: Jansen (2018) writes about MOOCs ‘providing new learning opportunities for millions of people’ and comprising, ‘a significant innovation in (higher) education, and a lever for innovation in mainstream degree education’ (p.  4), but the reality falls short of the hype. It is possible that commercialisation, the business model, has diluted innovation. Commercialisation in the form of an effective value proposition and strategy can be a stimulus to innovation, but if a product has been defined as commercial (and often Anglophone, for that matter), innovative possibilities can be curtailed. Laurillard and Kennedy (2017) outline MOOCs’ potential in the Global South, noting the consequences of MOOCs being established originally in the Global North, including the fact that most MOOCs are in English. From this perspective, MOOCs are problematic, nominally offering free access to higher education materials but privileging a language, pedagogy and mode of product design. Kalman (2014) also argues MOOCs are unlikely to assist students from developing countries, or with disadvantaged backgrounds. MOOCs are free to use and convenient to access, assuming basic net connectivity is

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assured, but they are not a Disruptive Innovation. They are ultimately obstructions to innovation because they offer an innovation impression while, in practice, offering more of the same. Some potentially disruptive innovations in technology enhanced learning in higher education have manifestly failed. Second Life is a virtual world. It is free for its users. Universities created their own Second Life virtual campuses. Furthermore, Second Life was the subject of academic journal articles, though these declined from around 2009 (Flavin & Hulova, 2018; Wang & Burton, 2012), suggesting diminishing interest by that stage. The question, therefore, is why did Second Life fail in higher education? It was free to use, like Google and Wikipedia. However, the level of effort required to use it exceeded the value to be drawn from it as a virtual campus. Second Life failed to meet all the Disruptive Innovation criteria (free, yes; easy to use, not always) and it failed in higher education. An interesting postscript to Second Life in academia may be found in Hogan (2015), in which the author’s Second Life avatar wanders through deserted Second Life campuses. In terms of how technology enhanced learning can be applied disruptively in higher education, one possibility is a platform model, mimicking the approach of Amazon. A higher education provider adopting the Amazon approach would have a core platform, accessible online, upon which a wide range of educational offerings, both in-house and third party, could be made available, wider than a bricks-and-mortar university, reaching the needs of students who are not served by the traditional campus. In case the business model seems far-fetched, the analysis of Hagel et al. (2016) is worth bearing in mind: ‘Many traditional retailers were initially very sceptical about customers’ willingness to buy books or rent/buy videos from online platforms. Look what happened’ (p.  11). Amazon uses customer data to tailor its services and there is no in-­ principle reason why universities cannot do the same, suggesting individually tailored resources, or recommending particular student support, or a specific course, which could be suitable for the learning needs of the student and the commercial needs of the provider. In the event of the two colliding it would be interesting to see if the student’s needs or the provider’s profits would be prioritised.


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There is a lot of hype around technology enhanced learning in higher education, hype which gets focused in specific instances such as Second Life and MOOCs. What we have in technology enhanced learning in higher education is not ‘digital hysteria’ (Selwyn, 2014, p. 9), but there is a tendency towards digital panacea. Technology is posited as a solution to amorphously framed questions, but technology is inert: Van Laar, Van Deursen, Van Dijk, and De Haan (2017) argue, ‘Innovation starts with people, making the human capital within the workforce decisive’ (p. 577). Furthermore, Hayes and Jandrić (2014) argue, ‘to repeatedly infer that technology actually performs our labour on our behalf … dis-empowers us as humans and closes many routes for learning’ (p.  202). It is only through practice that technologies acquire meaning. Ferreira, Rosado, Lemgruber, and Carvalho (2020) argue technological solutionism and innovation have supported marketisation of the education system in Brazil. Technological solutions are brought in by external parties, for a fee. As they are incentivised by profit, businesses may have a vested interest in proclaiming a problem, to which they alone have the solution. Within this discourse, technologies are framed as subjects with agency: ‘educators must assume the role of entrepreneurs and promote “innovative” actions with new digital tools created, predominantly, by companies based in the global North … “efficiency” needs to be increased …, a demand created by the assumed need to develop educational systems that are fit-for-purpose in the globalised twenty-first century’ (Ferreira et al., 2020, pp. 56–57). Wan, Williamson, and Yin (2015) argue, ‘Emerging economies can provide a particularly conducive environment for innovation opportunities to arise because they often act as a crucible where new customers with fluid needs and behaviours, a growing number of competitors, a flexible business and institutional context and newly introduced technologies come together’ (p.  95). In practice, technology enhanced learning in higher education has offered more of the same, adopting technology as a sustaining innovation or efficiency innovation, determined by economic and political interests, retaining existing hierarchies. Technology has not disrupted; it has consolidated. The failure of individual, educational technologies falling short of the hype may derive in part from a fear of missing out, an institutional fear of being left behind a huge technology wave. Confronted with

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participation or opting-out completely, many universities will opt for some form of engagement. This, however, is not a secure basis from which to form a technology enhanced learning strategy, not least as it could well fall victim to effective marketing of unsuitable goods and services from education technology vendors, rather than from a clear analysis of institutional need and the role technology can play in achieving wider institutional goals. Higher education is only available to a section of the population in many countries. Therefore, a new market entrant using technology in innovative ways could make higher education available to people who lack access to it. This is not to position technology as a panacea but to recognise how embedded digital technologies have become in higher education, and to further recognise that their potential has not been fully utilised to date because technologies have been configured to serve existing curricula and pedagogies which, themselves, are pre-digital in their design features, with the lecture as a pedagogical method predating the mass availability of printed books. Most organisations do not survive for long periods of time (O’Reilly & Tushman, 2011), yet universities endure. Why is this? In the UK, the Further and Higher Education Act of 1992 allowed former polytechnics to rebrand themselves as universities, yet a number of the older UK universities coalesced to form the Russell Group, distinctive by virtue of the research they undertook. In the years since, the Russell Group has consolidated and enhanced its position as the premier segment of UK higher education. In the stratified higher education sector, offering a premium service in a high-end niche might enable disruption but, in the UK, the New College of the Humanities (NCH), which began offering tuition in 2012, promoted the presence of well-known academics on its faculty but would appear, thus far, to have made little impact. The NCH was bought out by Northeastern University in the USA in 2019. Incumbency in the higher education sector is powerful enough to withstand top end disruption. Low end disruption, or new market disruption through a platform model, may be another matter. A new higher education institution is unlikely to threaten incumbents if it reproduces their approach but may gain a foothold from which it can move upmarket if it offers something disruptive. A disruptive university


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on the Ryanair model would not need a high initial enrolment to prosper. It need only appeal to a small fraction of the market to build a viable base from which it could expand. Being a new provider in higher education can easily be a liability. In a sector in which age is correlated with quality, being the new kid on the block is not an asset. A provider needs a clear value proposition to attract students, articulated in a lucid, synoptic narrative, and a clear business model. In higher education, the value proposition can focus on cost and quality. Traditional universities can differentiate themselves by cultivating an upmarket brand image, such as membership of the Russell Group of universities in the UK or the Ivy League in the USA, but if a low-cost provider can alter the expectations and behaviour of students, while offering a high-quality core product and service, it can effect a disruptive innovation over time. It may be the case that higher education mediated wholly through technology will always be perceived as a poor relation because of its stripping-­down of the student experience. Discount higher education might fail in the same way that discount cruise lines failed. In that case, the narrative for an entirely online university may need to stress other factors, such as affordability and convenience, and possibly speed, too, as a student can accumulate academic credits twelve months a year, rather than being limited by the traditional academic calendar. There are different tiers within education systems and elite providers are the ones least vulnerable to disruption. Disruptors more commonly come in at the bottom end of the market and work their way upwards. A new entrant in higher education attempting to come in at the top end of the market would lack the reputation that the incumbents hold, and would need to rapidly prove its credentials and standards. Innovation is a potentially double-edged sword, creating opportunity for some but comprising a threat to others. However, in practice, technologies have been used to support the existing pedagogical model in higher education (Flavin, 2016, 2017). Duvivier (2019) argues, ‘the rise of new technologies allows for and creates new ways to work with knowledge’ (p. 18), but, as a sector, higher education has stuck with the old ways.

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Conclusion Higher education in the twenty-first century relies substantially on technologies. However, technologies have not fundamentally altered the product of higher education (the degree, or other certification), nor has technology fundamentally altered how higher education is delivered, with a majority of students still attending campuses. That said, technology has disrupted other areas of practice, and higher education is not immune to the possibility of Disruptive Innovation. In society in general, the technologies we use and the jobs we get them to do have stripped away layers of mediation. We are accustomed to scanning the products we buy in shops, opting-in to an efficiency innovation. We use technology in higher education for greater efficiency, too, or to marginally enhance existing practices, but the digital mediation of higher education has left education fundamentally unaltered. In terms of establishing reasons why technology has not disrupted higher education to date, it needs to be recognised that, ‘renovation often prevails over innovation; everyone dreams of revolution but most firms end up working towards evolution’ (Garel, 2015, p. 34). Higher education works within regulatory systems. Technology works within institutions that are often large and embedded and inflexible. Technology has been looked to as a transforming agent but technology can do nothing without human agency. Higher education needs to be wary of, ‘the just-­ add-­technology-and-stir fallacy’ (Philip & Garcia, 2013, p. 316), which can lead to the purchasing of technology ‘solutions’ to amorphous or non-existent problems. Technologies can promise transformation in higher education, yet what they present in practice is more of the same. The question of where innovation comes from in organisations is also significant. Foss, Woll, and Moilanen (2013) show women’s ideas are not implemented to the same degree as men’s, in research conducted in the Norwegian energy industry. Remneland Wikhamn and Knights (2013) argue that, in western economies, ‘emphasis on market principles, competition and self-sufficiency has stimulated and legitimised an associated tough, macho-masculinity in the management of organisations’ (p. 278). Innovation does not exist in a vacuum but is implicated in a range of


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other practices. It can and often does replicate and express wider economic and social inequities. Lucas and Goh (2009) argue, ‘Culture defines what the organization does, but it also defines what it cannot do, and in this respect can be a disability when confronting a new innovation’ (p.  47). Organisational culture, the way things are done, puts borders around practice and militates against innovation. Culture is important for organisational identity but it can also ossify, and it can neglect to notice the innovation at its periphery, creating the disruptor’s opportunity. Many universities are long-established but this does not mean they cannot change, or that they cannot be threatened by a new provider. King and Baatartogtokh (2015) argue, ‘The theory of disruptive innovation provides a generally useful warning about managerial myopia’ (p. 85), and Tellis (2006) argues, ‘dominant incumbents that succumb to technological change are content with past successes, are disdainful of new entrants, focus on current products or current customers’ (p. 37). Many incumbents meet the criteria and could be vulnerable to a low end or new market disruptor. Hargadon and Douglas (2001) argue, ‘When innovations meet institutions, two social forces collide’ (p.  476). Universities are powerful institutions, producing large numbers of graduates for existing economic and social conditions. Disruptive Innovation represents change and is therefore a threat to existing higher education provision. Higher education can ignore Disruptive Innovation but Disruptive Innovation will not go away. When, as shown in the case studies in this chapter, so many areas of practice have been disrupted, it would be an error to assume higher education’s invulnerability. Technology enhanced learning has made research more simple and convenient for academics. It has made the dissemination of research more efficient and convenient and, moreover, the work of other researchers can be accessed within seconds. However, undergraduate degree programmes are largely unchanged. They are enhanced incrementally through technology, or institutional cost-savings are enabled through Efficiency Innovation, but the outcome and the mode of delivery often remain the same. Universities practise Sustaining Innovation or Efficiency Innovation in their teaching and, institutionally, in technology infrastructures and in their strategies (Flavin & Quintero, 2018). Disruptive Innovation offers the prospect and also the threat of cultural, transformational change.

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Hagel et al. (2016), write of ‘black swans,’ ‘disruptive events that may start small but quickly develop into something larger’ (p. 3). Their definition of disruption is severe: ‘Disruption requires the displacement of most incumbent leaders’ (p. 3). The key is to identify the circumstances in which disruption is likely, ‘digital infrastructure with rich connectivity that can be accessed by underserved customers’ (p.  10). If the underserved customers have internet access, they can be reached by goods and services. If those goods and services are affordable and easy to use, disruptors are in a position to succeed. Hargadon and Douglas (2001) argue, ‘research tends to treat innovations as abstract and indeterminate ideas—the automobile, the personal computer, the internet, and genetic engineering—while, in daily life, the public confronts them in specific and concrete forms—the Model T, the Apple II, Yahoo!, and Dolly the sheep’ (p. 477). Disruptive Innovation rarely enters with a bang. It enters at the low end of markets or it creates new markets. The incumbent is often not aware of the scale of the threat until it appears at the incumbent’s shoulder. Higher education systems have been remarkably resilient to date, using technologies to enhance what they do or to make practice more efficient. However, other, seemingly resilient goods and services were disrupted, a lesson higher education needs to learn. Higher education is resilient. It is not invulnerable. This chapter has analysed Disruptive Innovation theory, has summarised examples of Disruptive Innovation and has explored its applicability to higher education. The next chapter looks at a technology which has apparently succeeded in embedding itself in higher education, the Virtual Learning Environment.

References Adner, R., & Zemsky, P. (2005). Disruptive technologies and the emergence of competition. The Rand Journal of Economics, 36(2), 229–254. Akbar, M. F., & Ozuem, W. (2019, April 9–10). Disruptive innovation: The high end market perspective. In 24th UK Academy for Information Systems International Conference, University of Oxford. Retrieved from http://insight.


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Benner, M. J., & Tripsas, M. (2012). The influence of prior industry affiliation on framing in nascent industries: The evolution of digital cameras. Strategic Management Journal, 33(3), 277–302. Berglund, H., & Sandström, C. (2017). A new perspective on the innovator’s dilemma—Exploring the role of entrepreneurial incentives. International Journal of Technology Management, 75(1–4), 142–156. Brackin, R. C., Jackson, M. J., Leyshon, A., & Morley, J. G. (2019). Taming disruption? Pervasive data analytics, uncertainty and policy intervention in disruptive technology and its geographic spread. ISPRS International Journal of Geo-Information, 8(1), 34. Retrieved from https://www.mdpi. com/2220-9964/8/1/34/htm. Carr, N. G. (2005). Top-down disruption. Strategy and Business, 39. Retrieved from Christensen, C. M. (1997). The innovator’s dilemma: When new technologies cause great firms to fail. Harvard: Harvard Business School Press. Christensen, C.  M. (2002). The rules of innovation. Technology Review, 2002, 33–38. Christensen, C. M., Bartman, T., & van Bever, D. (2016, Fall). The hard truth about business model innovation. MIT Sloan Management Review. Retrieved from Christensen, C. M., & Bower, J. L. (1996). Customer power, strategic investment, and the failure of leading firms. Strategic Management Journal, 17, 197–218. Christensen, C. M., Grossman, J., & Hwang, J. (2009). The innovator’s prescription: A disruptive solution for health care. New York: McGraw-Hill. Christensen, C. M., & Raynor, M. E. (2003). The innovator’s solution: Creating and sustaining successful growth. Boston: Harvard Business School Press. Christensen, C. M., & Tedlow, R. S. (2000). Patterns of disruption in retailing. Harvard Business Review, 78(1), 42–45. Conole, G., & Brown, M. (2018). Reflecting on the impact of the open educational movement. Journal of Learning for Development, 5(3), 187–203. Cortez, N. (2014). Regulating disruptive innovation. Berkeley Technology Law Journal, 29(1), 175–228. Currah, A. (2007). Hollywood, the internet and the world: A geography of disruptive innovation. Industry and Innovation, 14(4), 359–384.

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Cusumano, M.  A., Mylonadis, Y., & Rosenbloom, R.  S. (1992). Strategic maneuvering and mass-market dynamics: The triumph of VHS over Beta. Business History Review, 66(1), 51–94. Dew, N., Sarasvathy, S. D., Read, S., & Wiltbank, R. (2008). Immortal firms in mortal markets? An entrepreneurial perspective on the ‘innovator’s dilemma’. European Journal of Innovation Management, 11(3), 313–329. Dogru, T., Mody, M., & Suess, C. (2019). Adding evidence to the debate: Quantifying Airbnb’s disruptive impact on ten key hotel markets. Tourism Management, 72, 27–38. Downes, L., & Nunes, P. (2013, March). Big-bang disruption. Harvard Business Review, 44–56. Dutton, W. H., Cheong, P. H., & Park, N. (2004). An ecology of constraints on e-learning in higher education: The case of a virtual learning environment. Prometheus, 22(2), 131–149. Duvivier, R. J. (2019). How to ‘future-proof ’ the use of space in universities by integrating new digital technologies. Perspectives: Policy and Practice in Higher Education, 23(1), 18–23. Ernkvist, M. (2008). Down many times, but still playing the game: Creative destruction and industry crashes in the early video game industry 1971–1986. In K. Gratzer & D. Stiefel (Eds.), History of insolvency and bankruptcy from an international perspective (pp. 161–191). Huddinge: Södertörns Högskola. Ferreira, G.  M. D.  S., Rosado, L.  A. D.  S., Lemgruber, M.  S., & Carvalho, J. D. S. (2020). Metaphors we’re colonised by? The case of data-driven educational technologies in Brazil. Learning, Media and Technology, 45(1), 46–60. Flavin, M. (2016). Technology enhanced learning and higher education. Oxford Review of Economic Policy, 32(4), 632–645. Flavin, M. (2017). Disruptive technology enhanced learning: The use and misuse of digital technologies in higher education. London: Palgrave Macmillan. Flavin, M., & Hulova, K. (2018). An inferior source? Quantitively analysing the production and revision of five, technology enhanced learning-related terms on Wikipedia. Research in Learning Technology, 26. rlt.v26.2103. Flavin, M., & Quintero, V. (2018). UK higher education institutions technology enhanced learning strategies from the perspective of disruptive innovation. Research in Learning Technology, 26. Retrieved from https://journal.alt.


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Foss, L., Woll, K., & Moilanen, M. (2013). Creativity and implementations of new ideas: Do organisational structure, work environment and gender matter? International Journal of Gender and Entrepreneurship, 5(3), 298–322. Garel, G. (2015). Lessons in creativity from the innovative design of the swatch. Technology Innovation Management Review, 5(7), 34–40. Gawer, A., & Cusumano, M.  A. (2014). Industry platforms and ecosystem innovation. Journal of Product Innovation Management, 31(3), 417–433. Gilbert, C., & Bower, J. L. (2002). Disruptive change: When trying harder is part of the problem. Harvard Business Review, 80(5), 94–101. Govindarajan, V., & Kopalle, P. K. (2006). The usefulness of measuring disruptiveness of innovations ex post in making ex ante predictions. The Journal of Product Innovation Management, 23(1), 12–18. Gross, S. (2009). Low-cost cruises: A business model analysis of easycruise. Tourism in Marine Environments, 6(1), 11–24. Hagel, J., Eckenrode, J., & Srinivas, V. (2016). Patterns of disruption: Impact on wholesale banking. Deloitte University Press. Retrieved from https://www2. Hargadon, A. B., & Douglas, Y. (2001). When innovations meet institutions: Edison and the design of the electric light. Administrative Science Quarterly, 46(3), 476–501. Hargittai, E. (2010). Digital na(t)ives? Variation in internet skills and uses among members of the ‘net generation’. Sociological Inquiry, 80(1), 92–113. Hayes, S., & Jandrić, P. (2014). Who is really in charge of contemporary education? People and technologies in, against and beyond the neoliberal university. Open Review of Educational Research, 1(1), 193–210. Henderson, R. (2006). The innovator’s dilemma as a problem of organizational competence. The Journal of Product Innovation Management, 23, 5–11. Hogan, P. (2015, March). We took a tour of the abandoned college campuses of Second Life. Splinter. Retrieved from we-took-a-tour-of-the-abandoned-college-campuses-of-sec-1793849944 Holtham, C., & Courtney, N. (2005). Virtual learning environments: Practitioner perspectives on good practice. London: The Observatory on Borderless Higher Education. Retrieved from details?id=48.

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Jansen, D. (2018). Foreword. In D.  Jansen & L.  Konings (Eds.), The 2018 OpenupEd trend report on MOOCs. Maastricht: EADTU.  Retrieved from Jones, C. (2012). Networked learning, stepping beyond the net generation and digital natives. In L. Dirckinck-Holmfield, V. Hodgson, & D. McConnell (Eds.), Exploring the theory, pedagogy and practice of networked learning (pp. 27–41). New York: Springer. Jones, C. (2019). Capital, neoliberalism and educational technology. Postdigital Science and Education, 1(2), 288–292. Kaewkitipong, L. (2012). Diffusion of an online collaboration tool: The case of Google wave adoption failure. In 45th Hawaii international conference on system sciences (pp.  3990–3999) Retrieved from stamp/stamp.jsp?arnumber=6149380. Kalman, Y. M. (2014). A race to the bottom: MOOCs and higher education business models. Open Learning: The Journal of Open, Distance and e-­Learning, 29(1), 5–14. Katila, R., & Chen, E. L. (2008). Effects of search timing on innovation: The value of not being in sync with rivals. Administrative Science Quarterly, 53, 593–625. King, A. A., & Baatartogtokh, B. (2015). How useful is the theory of disruptive innovation? MIT Sloan Management Review, 57(1), 77–90. Klawitter, E., & Hargittai, E. (2018). ‘It’s like learning a whole other language’: The role of algorithmic skills in the curation of creative goods. International Journal of Communication, 12, 3490–3510. Kostoff, R.  N., Boylan, R., & Simons, G.  R. (2004). Disruptive technology roadmaps. Technological Forecasting and Social Change, 71, 141–159. Kumar, N. (2006). Strategies to fight low-cost rivals. Harvard Business Review, 84(12), 104–112. Latzer, M. (2009). Information and communication technology innovations: Radical and disruptive? New Media & Society, 11(4), 599–619. Laurillard, D. (2014). ‘What is the problem for which MOOCs are the solution?’ #ALTC Blog: News and Views from the ALT Community. Retrieved from Laurillard, D., & Kennedy, E. (2017). The potential of MOOCs for learning at scale in the global south. London: Centre for Global Higher Education. Retrieved from


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Lawton, W., & Katsomitros, A. (2012). MOOCs and disruptive innovation: The challenge to HE business models. London: The Observatory on Borderless Higher Education. Retrieved from view_details?id=929. Lepore, J. (2014). The disruption machine: What the gospel of innovation gets wrong. The New Yorker, 90(17), 30–36. Li, P.  P. (2013). Introduction: Disruptive innovation from the bottom of the pyramid. In Disruptive innovation in Chinese and Indian businesses (Vol. 1, pp. 1–30). London: Routledge in Association with GSE Research. Lucas, H. C., & Goh, J. M. (2009). Disruptive technology: How Kodak missed the digital photography revolution. Journal of Strategic Information Systems, 18, 46–55. Markides, C. (2006). Disruptive innovation; in need of better theory. The Journal of Product Innovation Management, 23, 19–25. Markides, C. (2012). How disruptive will innovations from emerging markets be? MIT Sloan Management Review, 54(1). Retrieved from Markides, C., & Charitou, C. D. (2004). Competing with dual business models: A contingency approach. Academy of Management Executive, 18(3), 22–36. Markides, C., & Sosa, L. (2013). Pioneering and first mover advantages: The importance of business models. Long Range Planning, 46, 325–334. Montoya, J. S., & Kita, T. (2017). Towards an improved theory of disruptive innovation: Evidence from the personal and mobile computing industries. In The Asian conference on the social sciences 2017: Official conference proceedings (pp. 125–144) Retrieved from 4cb3c27efee6e3e5e670bb3c5a4d81d.pdf. Moore, G.  A. (2004). Darwin and the demon. Harvard Business Review, 82(7–8), 86–92. Nagy, D., Schuessler, J., & Dubinsky, A. (2016). Defining and identifying disruptive innovations. Industrial Marketing Management, 57, 119–126. Norman, D.  A., & Verganti, R. (2014). Incremental and radical innovation: Design research vs. technology and meaning change. Design Issues, 30(1), 78–96. O’Reilly, C., & Tushman, M. L. (2011). Organizational ambidexterity in action: How managers explore and exploit. California Management Review, 53(4), 5–22.

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Palacios-Fenech, J., & Tellis, G. J. (2016). The dive and disruption of successful current products: Measures, global patterns, and predictive model. Journal of Product Innovation Management, 33(1), 53–68. Philip, T., & Garcia, A. (2013). The importance of still teaching the iGeneration: New technologies and the centrality of pedagogy. Harvard Educational Review, 83(2), 300–319. Prensky, M. (2001). Digital natives, digital immigrants. On the Horizon, 9(5), 1–6. Rasool, F., Koomsap, P., Afsar, B., & Panezai, B. (2018). A framework for disruptive innovation. Foresight, 20(3), 252–270. Raynor, M. E. (2011). Disruption theory as a predictor of innovation success/ failure. Strategy and Leadership, 39(4), 27–30. Remneland Wikhamn, B., & Knights, D. (2013). Open innovation, gender and the infiltration of masculine discourses. International Journal of Gender and Entrepreneurship, 5(3), 275–297. Rosenbloom, R. S., & Christensen, C. M. (1994). Technological discontinuities, organizational capabilities, and strategic commitments. Industrial and Corporate Change, 3(3), 655–685. Schmidt, G. M., & Druehl, C. T. (2008). When is a disruptive innovation disruptive? The Journal of Product Innovation and Management, 25, 347–369. Selwyn, N. (2014). Digital technology and the contemporary university. Abingdon: Routledge. Sultan, N. (2013). Knowledge management in the age of cloud computing and web 2.0: Experiencing the power of disruptive innovations. International Journal of Information Management, 33(1), 160–165. Tellis, G. J. (2006). Disruptive technology or visionary leadership? The Journal of Product Innovation Management, 23, 34–38. Van Laar, E., Van Deursen, A. J., Van Dijk, J. A., & De Haan, J. (2017). The relation between 21st-century skills and digital skills: A systematic literature review. Computers in Human Behavior, 72, 577–588. Vidal, E., & Mitchell, W. (2013). When do first entrants become first survivors? Long Range Planning, 46, 335–347. Von Hippel, E., Ogawa, S., & Jong, J. P. J. (2011). The age of the consumer-­ innovator. MIT Sloan Management Review, 53(1) Retrieved from http:// Vriens, D., & Søilen, K. S. (2014). Disruptive intelligence-how to gather information to deal with disruptive innovations. Journal of Intelligence Studies in Business, 4(3), 63–78.


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Wan, F., Williamson, P. J., & Yin, E. (2015). Antecedents and implications of disruptive innovation: Evidence from China. Technovation, 39, 94–104. Wang, F., & Burton, J. K. (2012). Second life in education: A review of publications from its launch to 2011. British Journal of Educational Technology, 44(3), 357–371. Williamson, P. J., & Zeng, M. (2009). Value-for-money strategies for recessionary times. Harvard Business Review, 87(3), 66–74. Yoffle, D. B., & Kwak, M. (2002). Mastering balance: How to meet and beat a stronger opponent. California Management Review, 44(2), 8–24. Yu, D., & Hang, C.  C. (2010). A reflective review of disruptive innovation theory. International Journal of Management Reviews, 12, 435–452. Zuboff, S. (2019). The age of surveillance capitalism: The fight for a human future at the new frontier of power. New York: PublicAffairs.

3 Virtual Library Environment? VLEs in Practice

This chapter uses virtual learning environments (VLEs) as a case study of Sustaining Innovation. The chapter argues the VLE is a typical, institutional technology for learning and teaching because its transformative potential is subsumed to serve an existing pedagogical model. VLEs are more likely to be used as libraries than classrooms, storage facilities rather than spaces for innovative learning and teaching. The chapter examines how VLEs are used in practice and returns to Disruptive Innovation theory as a means of understanding VLEs. In addition, the chapter examines VLEs as products sold to universities by third party, educational technology (ed-tech) vendors, looks at how VLEs as homogenising platforms work in different cultural contexts, and examines data collection on VLEs. The VLE could, in theory, be regarded as one of technology enhanced learning’s greatest hits, because of its ubiquity. A 2005, UK-based survey (Browne, Jenkins, & Walker, 2006) showed sectorial growth in the use of VLEs, from 81% in 2001; to 86% in 2003; to 95% in 2005 (p.  8). Furthermore, Costello (2013) argues that as VLEs became embedded, they became, ‘as important to the identity of a university as a library’ (p. 188). In addition, VLEs are scalable and can be used to cater to a high volume of students at low cost. However, this chapter argues technology © The Author(s) 2020 M. Flavin, Re-imagining Technology Enhanced Learning, Digital Education and Learning,



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enhanced learning has been a disappointment if VLEs are a success story because of VLEs’ conservatism and risk aversion. VLEs may have lapsed into Sustaining Innovation, their design encouraging them to be used in practice as sustaining innovations. In addition, VLEs are an example of product overshoot, developing incremental enhancements which exceed users’ needs, creating a potential space for disruptors at the low end of markets. Examining why VLEs have developed into conservative tools for learning and teaching in higher education shows how institutions resist innovation and also shows how commercial businesses can stunt innovation by marketing products that offer smoother process and greater efficiency, rather than genuine innovation and transformation.

The VLE as a Sustaining Innovation VLEs offer convenience. They are easy to use, notwithstanding that users have to go through institutional log-on to access them. VLEs could, potentially, be disruptive innovations. That they are not is a result of decision-making in the design process, of cultural pressures towards homogenisation, and as a result of practice. VLEs relocate traditional, didactic modes of instruction to the digital realm. They are used primarily to store content and are more warehouse than classroom: Rienties, Giesbers, Lygo-Baker, and Ma (2016) argue many educators use only a small amount of VLEs’ capabilities. VLEs function effectively as storage facilities and message boards, but when VLEs are used solely as storage facilities they inhibit social interactions. VLEs become a well to draw from, not a forum in which to interact. VLEs are a sustaining innovation but this was not preordained. VLEs as sustaining innovations arise from practice, from the vendors of VLEs and from the pedagogical practices of universities. Dutton, Cheong, and Park (2004) argue: ‘VLE systems began to diffuse widely in the late-­1990s and quickly became a status symbol of innovation, with many higher-­ education institutions not wishing to be left without their own system. They were viewed as being of critical value as an organization-wide standard that could enable innovation in e-learning among non-technically proficient instructors and students’ (p.  135). The quote suggests VLEs

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would be transformative but VLEs have not disrupted. They have made aspects of learning more convenient, primarily by enabling any time, anywhere access to resources, but they have also supported and cemented a pre-existing pedagogical model. There is nothing necessarily wrong with a VLE being a sustaining innovation. Rodriguez-Ardura and Meseguer-Artola (2016) argue, ‘A clear, comprehensible, flexible, and pertinent virtual education environment helps users achieve their learning goals’ (p. 1046). In adopting this approach, however, it needs to be recognised that the VLE as a sustaining innovation constricts technology’s potential. The technology serves pedagogy; it does not change it, perhaps because pedagogy is not in need of change. Newman, Beetham, and Knight (2018), in a large-scale survey of UK students, showed 75% of students relying on their VLE to support their coursework. In the same study, 55% of students said their VLE was well designed. In another large-scale survey in the UK, 72% of higher education students stated they relied on their VLE to do their coursework (Langer-Crame, Newman, Beetham, Killen, & Knight, 2019). VLEs do a job in higher education and they do it efficiently. A study of survey responses from 521 staff in Irish Higher Education Institutions found the most common use of VLEs was as content repositories and as a channel for communication (Farrelly, Raftery, & Harding, 2018). In an earlier study, Fry and Love (2011) interviewed lecturers in Business, whose metaphors for VLEs included, ‘security blanket,’ ‘crutch,’ and ‘electronic filing cabinet’ (p. 54). The VLE does a particular job relating to the storage and transmission of information. If VLEs are effective as libraries and repositories, it may be best to recognise the fact, utilise them in that way and look for innovation elsewhere.

The Business of VLEs To understand why VLEs do not comprise disruptive innovations, it is necessary to recognise the embeddedness of established higher education pedagogy, which is deeply rooted and resistant to fundamental change. It is also important to recognise business and its tension, in this instance, with innovation. Castaneda and Selwyn (2018) argue, ‘the use of digital


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technology in higher education is now a multi-billion dollar business which sees global technology corporations exerting increasing influence on the affairs of local universities … the commercial design of educational systems and software increasingly shapes the forms of teaching and learning that take place in universities’ (p. 6). Commercial Ed-tech vendors compete to sell VLEs to universities. They offer a stable product in a pedagogical form which universities recognise as approximating their existing practice. The design of VLEs is an aspect of their conservatism, but so is language. Selwyn (2016) argues that terms such as virtual learning environment, ‘convey a clear sense of what will happen when these technologies are used in education’ (p.  438). Bayne (2015) argues that the phrase, technology enhanced learning, contains ‘deeply conservative assumptions’ (p. 7). Enhancement assumes, ‘a pre-existing set of practices which are not in need of radical shift or displacement, but are rather simply open to being made even “better”’ (p.  10). If this is true, Disruptive Innovation is technology enhanced learning’s antagonist because it pushes for transformation rather than steady, incremental progress. Technology enhanced learning as a phrase implies Sustaining Innovation. The virtual learning environment implies a relocation of traditional practice to the digital environment. A large-scale survey in the UK showed the virtual learning environment to be the technology receiving most institutional investment (Jenkins, Walker, & Voce, 2018). Leaders in higher education are wary of investing heavily in a new and unproven technology, and wary of investing in VLEs that deviate from the norm. Moccia (2016) argues, ‘Technologies are always expensive so leaders in higher education have to bet on where to invest their sometimes-rare resources’ (p. 32). The cost of technologies nurtures conservatism and risk-aversion. Universities are more likely to invest in technologies offering an enhanced form of existing practice than to invest in a technology with the potential to disrupt the university’s existing practices. VLEs are commercial products offered by rival vendors. Paradoxically, commercial competition militates against innovation in this instance because vendors sell products to universities predicated on the pedagogical design of VLEs closely resembling traditional, established learning

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practice, being predominantly teacher rather than learner-centred. The products sold by Ed-tech vendors veer towards a monoculture, a homogenised form of learning and an antithesis to innovation. Competition in the Ed-tech industry guarantees neither innovation nor high quality. VLEs from different providers are more conspicuous by their similarities than by their differences. The design of VLEs demonstrates risk-aversion, pursuing lowest common denominators rather than innovation as vendors seek to reproduce and relocate the components of traditional teaching online. Watters (2014) argues, ‘it is clear that the education-technology industry does have a powerful influence on the design and development of new tools’ (p.  17). Furthermore, Selwyn (2007) argues, ‘education technology is predicated upon the involvement of commercial IT firms and, it follows, that these private interests exert a profound shaping influence on education technology … university campuses represent a significant and potentially lucrative market within which the IT industry operates’ (p. 86). Watters (2017) also argues that as technologies become embedded, ‘we hand over a certain level of control—to the technologies themselves, sure, but just as importantly to the industries and the ideologies behind them’ (p. 38). Ed-tech vendors need to sell their products to the higher education sector. To that end, they have to be able to articulate the jobs their products do. Consequently, they sell products that do the existing jobs that universities do, transferred to the digital realm. Zeide and Nissenbaum (2018) argue, of VLE vendors, ‘by adopting commercial marketplace norms, these providers undermine core functions and values of education’ (p. 280). Vendors do not necessarily undermine education because they support the performance of a recognisable job, one that universities have already been doing. However, the norms of commerce can lead to inflated claims, including the claim that vendors’ products can solve perceived problems. These problems can be amorphous, described by the same vendors who have products to sell which can solve the perceived problems, in a circular argument which generates profits. Ferreira et al. (2020) argue technological solutionism and innovation have supported marketisation of the education system in Brazil, comprising a form of digital colonialism. Products created in affluent countries are sold to developing economies, drawing revenue back to


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already-wealthy locations and, moreover, imposing forms of learning and teaching which exclude the particularities of the local context. The idea of using technologies to transform learning and teaching is commercially hazardous, and the commercialisation of VLEs has played a significant role in their becoming sustaining innovations. It is easier to sell a product resembling a traditional classroom than it is to sell a transformation necessitating a new set of practices. Dutton et al. (2004) argue, ‘traditional teaching paradigms are designed into many e-learning products in order to facilitate their marketing, based on analogies to what teachers already know and understand’ (p. 132). A case study of IBM and Remington Rand in computer provision to the post-Second World War domestic insurance market in the USA argues that the company whose narrative stressed the ability to do existing jobs easier won market dominance (Kahl & Grodal, 2016). Both companies were selling computers with similar specifications, but Remington Rand stressed the technical aspects of their machines whereas IBM’s marketing reassured customers that computers would enable them to do what they were already doing, in enhanced and more efficient ways, but without disrupting their established modes of practice. IBM achieved market dominance (see Chap. 7). A further issue arising from universities purchasing VLEs is that of vendor lock-in (Pecori, 2018). Costello (2013) argues, ‘The process of moving from one VLE to another is more costly and difficult the more one has invested in it: teachers and students must be retrained, the VLE must be connected to other information technology systems, and existing content may have to be migrated to the new system’ (p. 192). The purchase of a VLE is not only a significant investment. It is a long-term commitment, and once a university has a relationship with a particular vendor it is difficult to dislodge that relationship. Far from innovating, technology, in this instance, entrenches.

One VLE: Many Contexts VLEs are customarily produced in affluent countries but exported worldwide. Jones (2014) argues, ‘the technologies deployed to enable networked learning are largely the outcome of design and development

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carried out by multi-national US based corporations’ (p. 170). Moodle’s head office is in Australia, but the other main VLE provider, Blackboard, is based in Washington DC. Sakai was developed by a group of universities in the USA. WebCT, a major player in the VLE market until it was taken over by Blackboard, also began in the USA. Paradoxically, as the number of universities using VLEs grew, the number of providers shrank (Costello, 2013) and a form of VLE orthodoxy was imposed. The core standardisation of VLEs as products imposes a digital hegemony and a standardised, reductive and culturally weighted mode of learning and teaching. Moodle, as a specific VLE brand, had a different genesis to other VLEs, being a ground-up innovation and open source project, yet over time it gravitated toward a similar kind of product architecture as other commercial VLEs, suggesting the conservative pedagogical practices of universities have been a determinant of the kind of technology enhanced learning made available. Universities encourage technologies that do existing jobs online. A ground-up innovation gets subsumed within a dominant pedagogical model. Alternatively, there may be good reasons for the general uniformity of VLE design, related to the job universities want VLEs to do, but that same uniformity means there is scant consideration of the cultural contexts of learning. Segooa and Kalema (2015) argue, ‘many VLEs are not contextualized to meets the needs of educational institutions in developing countries … elearning implementation should focus more on the social contexts rather than the technological solution’ (pp. 353–354). A one-size fits-all template cannot successfully be transferred wholesale because contexts are particular and not universal. As an educational imposition, the mainstream VLE from a market-­ leading provider is not necessarily suited to other contexts and reflects the pedagogy and priorities of the country within which it is produced. Tarhini, Hone, and Liu (2014) studied two universities in Lebanon, arguing, ‘it is futile to facilitate a technology which is implemented in a Western country … and then apply it in non-western countries that have substantial cultural differences’ (p.  161). Cultural considerations were also foregrounded in a study in Indonesia by Lee, Hsiao, and Purnomo (2014), who argued, ‘The cultural context of international students should be considered when presenting materials in an e-learning


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environment’ (p. 574). Similarly, a study in Pakistan (Farid et al., 2015) found a range of factors impeding the effective development of technology enhanced learning, including technical infrastructure and a lack of staff with the requisite technological expertise. The problems of implementing e-learning systems in developing countries (specifically, Pakistan) have also been identified by Kanwal and Rehman (2017). By selling a product designed in and for a specific cultural context as a one-size-fits-all solution, vendors reduce and misrepresent education. Studies tend to show that VLEs are used in similar ways, internationally. Dutton et al. (2004) undertook a case study of a VLE at a private university in the USA, finding its primary value to be ease of use: it was used, ‘most often as an alternative to the copy machine, by providing students with online access to assignments, readings, lecture notes and other class documents’ (p. 140). Risquez, Raftery, and Costello (2015) report on a survey of VLE use in Ireland (the survey has been taking place on a rolling basis since 2008). Students taking the survey want VLEs that are easy to navigate (p.  1071). Cobo, Rocha, and Rodriguez-Hoyos (2014), in a study at a university in Spain, found 84% of students having low or very low levels of interactivity with a VLE. Sanchez and Hueros (2010) undertook a survey of Business students at one university in Spain, finding technical support had a direct effect on students’ perceived ease of use and the perceived usefulness of Moodle. Oproiu (2015) found students in Romania using the VLE for downloading material, rather than using the VLE as a two-way communications tool. Ngai, Poon, and Chan (2007), in research conducted in Hong Kong, found ease of use and usefulness to be the dominant factors affecting the use of VLEs. Van Raaij and Schepers (2008) studied forty-five students on an Executive MBA programme in China, finding perceived usefulness had a direct effect on VLE use. Penjor and Zander (2015) undertook a study of VLE use in Higher Education Institutions in Bhutan, finding that the uploading of simple materials was the main activity, and a study in Malaysia found a VLE being used mainly to store learning materials (Zainuddin, Idrus, & Jamal, 2011). The tendency to use VLEs in similar ways in different contexts indicates the VLE is a limited tool. It may also signify the deterministic effect of standardised product architecture. Innovation is designed-out by commercial companies aiming to increase profit by

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offering a non-threatening product which replicates online the components of the traditional classroom, while also understanding the traditional classroom in culturally specific terms, comprising an imposition and a fetter as much as a means of supporting learning and teaching.

VLEs and Data Collection If a technology does a job conveniently and simply it is, in Disruptive Innovation terms, more likely to be used (Christensen & Raynor, 2003). Students are not loudly clamouring for their VLEs to change. VLEs are commonly perceived as technologies that do a specific if unremarkable job. From an administrative point of view, VLEs also enable the collection of data at minimal cost (Grech & Cassar, 2018). The VLE as an instrument of data collection is more innovative than the VLE as a tool for learning and teaching because it enables monitoring and support. Rather than wait for a post-course evaluation survey, education leaders can get data as the course is in progress. VLEs produce a constant data stream, showing which learning resources are used most frequently. VLEs allow data to be gathered and analysed in practically real time, and data monitoring in VLEs can be used to lessen the risk of student dropout (Pecori, 2018). Alves, Miranda, and Morais (2015) argue the data accrued in VLEs can be used to enable a deeper understanding of the learning process. Their study in Portugal of around 7000 students per year for five academic years showed the most frequently used tools within a VLE to be resources, messages and assignments, indicating passive learning but at least giving the authors a firm evidence base for their argument, evidence gained not through an explicit research intervention but arising from students’ day-to-day interactions with technology. Olivé, Huynh, Reynolds, Dougiamas, and Wiese (2019) developed a one-sits-fits-all predictive model for Moodle VLEs, designed to identify students unlikely to submit. The model provided its prediction two days before an assignment was due. Having a working model for highlighting how data gathering on VLEs can be used to support students is encouraging, though the authors acknowledged that the predictive power of the


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model varies, depending on how individual instructors use VLEs. Data accrued as a matter of course in online environments can have use value, identifying students who may be experiencing difficulties and reducing the risk of drop out. VLEs, because they have restricted access, can feel like safe spaces for communicating with and between students (Cronin, 2017). However, users’ interactions with VLEs are easily tracked: Knox, Williamson, and Bayne (2020) argue VLEs can be seen as, ‘devices for the harvesting of student data.’ Similarly, McCluskey and Winter (2014) argue, ‘in the digital classroom there is a physical record of every transaction that takes place’ (p. 142). Furthermore, Zeide and Nissenbaum (2018), linking the exclusivity of VLEs with the fact of their being produced by Ed-tech vendors, argue, ‘Because they collect information directly from learners without school mediation, independent Virtual Learning Environment providers fall outside the scope of student privacy regulation and can share information broadly without learner consent or consideration of educational purpose’ (p.  280). The accumulation of data can result in VLEs that are more efficient, but data can be used for a range of purposes. The routine recording of data may be one of the factors inhibiting VLE interaction. It may also be a component part of a wider process of data gathering in higher education and in day-to-day practice. The VLE may be a microcosm of the recording of online interactions, offering enhanced learning support but also accruing data which can have commercial and political, sell-on value. Users contribute data without knowing how the data may be used. Data accrual has become normalised at the site of collection, yet the usage of data can be characterised by opacity. Data gathering can support but it can also exploit, and the VLE can draw from students just as easily as it can give content to them.

Conclusion A VLE is a controlled space, containing the content with which it is populated. It is also an enclosed space, available only to those with approved access to it. Enclosure also means exclusion but the VLE does

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a job for students, academics and the university. It is a limited technology but it is also an efficient means of conveying content and instructions: Naveh, Tubin, and Pliskin (2010) argue, ‘instructors can maintain their conservative teaching habits except for posting their course content on the website. From an organizational perspective, this can be done at low cost, yielding relatively high student satisfaction’ (p. 132). Improvements in VLEs are incremental, comprising sustaining innovation, and efficiency innovation also ensues, enabling jobs to be done at reduced cost. VLEs are also scalable, allowing large numbers of students to be accommodated, well beyond the maximum capacity of a lecture theatre. VLEs also comprise an example of what Christensen (1997) calls product overshoot, with incremental enhancements being provided which do not match with or which exceed user’s needs. Product overshoot creates opportunities for disruption at the lower end of markets, as incumbents add sustaining innovations which exceed the needs of their customers. Montoya and Kita (2018) challenge Christensen’s concept of product overshoot, arguing customer response to innovation can be more elastic, especially in the early stages of a technology’s development, and Benner and Tripsas (2012) argue, ‘Firms entering a nascent product market face a context characterized by tremendous ambiguity and uncertainty, particularly when the market is sparked by radical technological change’ (p. 277). Once an understanding of a particular technology and the job it does has hardened, however, innovation becomes more difficult. Students use VLEs as, predominantly, course-specific libraries, which is only a partial feature of VLE design, making learning and teaching more efficient and enhancing it incrementally, but not disrupting it. Product overshoot creates opportunities for innovators (vendors prioritise their most profitable customers at the high end of markets), but there is scant evidence of innovators moving into this space as far as VLEs are concerned. VLEs are not disruptive innovations. The digital classroom is no more innovative than the traditional classroom. The identity and role of VLEs as sustaining innovations is established and embedded. If technology is to enable transformation in higher education, it will almost certainly be by


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another route. Technologies created for institutions will tend to be tailored to the institution’s existing practices. VLEs condense a university’s existing teaching model. In so doing they do not articulate a university in glowing terms, as they encourage passive learning, the imbibing of content to achieve assessment goals. This chapter has examined the VLE as an example of a sustaining innovation, which had, but which failed to live up to, its disruptive potential. The next chapter looks at a successful disruptive innovation, Wikipedia, and its impact on higher education.

References Alves, P., Miranda, L., & Morais, C. (2015). Record of undergraduates’ activities in virtual learning environments. In 14th European Conference on e-­Learning (pp. 25–33). Academic Conferences and Publishing International Limited. Retrieved from Activities%20in%20VLE.pdf Bayne, S. (2015). What’s the matter with ‘technology enhanced learning’? Learning, Media and Technology, 40(1), 5–20. Benner, M. J., & Tripsas, M. (2012). The influence of prior industry affiliation on framing in nascent industries: The evolution of digital cameras. Strategic Management Journal, 33(3), 277–302. Browne, T., Jenkins, M., & Walker, R. (2006). A longitudinal perspective regarding the use of VLEs by higher education institutions in the United Kingdom. Interactive Learning Environments, 14(2), 177–192. Castaneda, L., & Selwyn, N. (2018). More than tools? Making sense of the ongoing digitizations of higher education. International Journal of Educational Technology in Higher Education, 15, 22. Retrieved from https://link.springer. com/article/10.1186/s41239-018-0109-y. Christensen, C. M. (1997). The innovator’s dilemma: When new technologies cause great firms to fail. Boston: Harvard Business School Press. Christensen, C. M., & Raynor, M. E. (2003). The innovator’s solution: Creating and sustaining successful growth. Boston: Harvard Business School Press.

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Cobo, A., Rocha, R., & Rodriguez-Hoyos, C. (2014). Evaluation of the interactivity of students in virtual learning environments using a multicriteria approach and data mining. Behaviour and Information Technology, 33(10), 1000–1012. Costello, E. (2013). Opening up to open source: Looking at how Moodle was adopted in higher education. Open Learning: The Journal of Open, Distance and e-Learning, 28(3), 187–200. Cronin, C. (2017). Openness and praxis: Exploring the use of open educational practices in higher education. The International Review of Research in Open and Distance Learning, 18(5), 15–35. Retrieved from index.php/irrodl/article/view/3096. Dutton, W. H., Cheong, P. H., & Park, N. (2004). An ecology of constraints on e-learning in higher education: The case of a virtual learning environment. Prometheus, 22(2), 131–149. Farid, S., Ahmad, R., Niaz, I.  A., Arif, M., Shamshirband, S., & Khattak, M. D. (2015). Identification and prioritization of critical issues for the promotion of e-learning in Pakistan. Computers in Human Behavior, 51, 161–171. Farrelly, T., Raftery, D., & Harding, N. (2018). Exploring lecturer engagement with the VLE: Findings from a multi-college staff survey. Irish Journal of Technology Enhanced Learning, 3(2). Ferreira, G. M. D. S., Rosado, L. A. D. S., Lemgruber, M. S., & Carvalho, J. D. S. (2020). Metaphors we’re colonised by? The case of data-driven educational technologies in Brazil. Learning, Media and Technology, 45(1), 46–60. Fry, N., & Love, N. (2011). Business lecturers’ perceptions and interactions with the virtual learning environment. International Journal of Management Education, 9(4), 51–56. Grech, A., & Cassar, M. (2018). Can virtual learning environments be used as research platforms? Nurse Researcher, 26(3). nr.2018.e1568. Jenkins, M., Walker, R., & Voce, J. (2018). Building institutional cultures of innovation in technology enhanced learning: UCISA findings on current challenges and developments in UK higher education. In 35th International Conference of Innovation, Practice and Research in the Use of Educational Technologies in Tertiary Education (pp. 412–417) Retrieved from https://pure. Proceedings_Final.pdf#page=415.


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Jones, C. R. (2014). The politics of networked learning in an age of austerity. In Proceedings of the 9th International Conference on Networked Learning. Retrieved from Kahl, S. J., & Grodal, S. (2016). Discursive strategies and radical technological change: Multilevel discourse analysis of the early computer (1947–1958). Strategic Management Journal, 37, 149–166. Kanwal, F., & Rehman, M. (2017). Factors affecting e-learning adoption in developing countries—Empirical evidence from Pakistan’s higher education sector. IEEE Access, 5, 10968–10978. Knox, J., Williamson, B., & Bayne, S. (2020). Machine behaviourism: Future visions of ‘learnification’ and ‘datafication’ across humans and digital technologies. Learning, Media and Technology, 45(1), 31–45. Langer-Crame, M., Newman, T., Beetham, H., Killen, C., & Knight, S. (2019). Digital experience insights survey 2019: Findings from students in UK further and higher education. Bristol: JISC. Lee, Y. H., Hsiao, C., & Purnomo, S. H. (2014). An empirical examination of individual and system characteristics on enhancing e-learning acceptance. Australasian Journal of Educational Technology, 30(5), 562–578. McCluskey, F. B., & Winter, M. L. (2014). Academic freedom in the digital age. On the Horizon, 22(2), 136–146. Moccia, S. (2016). Managing educational reforms during times of transition: The role of leadership. Higher Education for the Future, 3(1), 26–37. Montoya, J. S., & Kita, T. (2018). Exponential growth in product performance and its implications for disruptive innovation theory. International Journal of Business and Information, 13(1) Retrieved from Naveh, G., Tubin, D., & Pliskin, N. (2010). Student LMS use and satisfaction in academic institutions: The organizational perspective. Internet and Higher Education, 13, 127–133. Newman, T., Beetham, H., & Knight, S. (2018). Digital experience insights survey 2018: Findings from students in UK further and higher education. Bristol: JISC. Ngai, E. W., Poon, J. K. L., & Chan, Y. H. (2007). Empirical examination of the adoption of WebCT using TAM. Computers and Education, 48(2), 250–267. Olivé, D.  M., Huynh, D.  Q., Reynolds, M., Dougiamas, M., & Wiese, D. (2019). A quest for a one-size-fits-all neural network: Early prediction of

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students at risk in online courses. IEEE Transactions on Learning Technologies, 12(2), 171–183. Oproiu, G.  C. (2015). A study about using e-learning platform (Moodle) in university teaching process. Procedia-Social and Behavioral Sciences, 180, 426–432. Pecori, R. (2018). A virtual learning architecture enhanced by fog computing and big data streams. Future Internet, 10(1) Retrieved from https://www. Penjor, S., & Zander, P. O. (2015). Predicting Virtual Learning Environment adoption: A case study. arXiv preprint arXiv:1503.02408. Rienties, B., Giesbers, B., Lygo-Baker, S., & Ma, H. W. S. (2016). Why some teachers easily learn to use a new virtual learning environment: A technology acceptance perspective. Interactive Learning Environments, 24(3), 539–552. Risquez, A., Raftery, D., & Costello, E. (2015). The open dataset on students’ perceptions of virtual learning environments in Ireland: Collaborating to listen to the student voice. British Journal of Educational Technology, 46(5), 1070–1074. Rodriguez-Ardura, I., & Meseguer-Artola, A. (2016). What leads people to keep on e-learning? An empirical analysis of users’ experiences and their effects on continuance intention. Interactive Learning Environments, 24(6), 1030–1053. Sanchez, R. A., & Hueros, A. D. (2010). Motivational factors that influence the acceptance of Moodle using TAM. Computers in Human Behavior, 26, 1632–1640. Segooa, M.  A., & Kalema, B.  M. (2015). Virtual learning environments for higher learning institutions in developing countries. In Fifth International Conference on e-Learning (pp. 353–359). Selwyn, N. (2007). The use of computer technology in university teaching and learning: A critical perspective. Journal of Computer Assisted Learning, 23(2), 83–94. Selwyn, N. (2016). Minding our language: Why education and technology is full of bullshit… and what might be done about it. Learning, Media and Technology, 41(3), 437–443. Tarhini, A., Hone, K., & Liu, X. (2014). The effects of individual differences on e-learning users’ behaviour in developing countries: A structural equation model. Computers in Human Behavior, 41, 153–163. Van Raaij, E. M., & Schepers, J. J. L. (2008). The acceptance and use of a virtual learning environment in China. Computers and Education, 50, 838–852.


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Watters, A. (2014). How will the ed-tech industry shape student reading? Knowledge Quest, 43(1), 16–22. Watters, A. (2017). Memory machines and collective memory: How we remember the history of the future of technological change. Educause Review, 2017, 37–50. Retrieved from 2017/10/erm17613.pdf. Zainuddin, N., Idrus, R., & Jamal, A. F. M. (2011). Moodle as an ODL teaching tool: A perspective of students and academics. Academic Conferences and Publishing International Limited. Retrieved from bitstream/123456789/13855/1/moodle%20as%20an%20ODL.pdf. Zeide, E., & Nissenbaum, H. (2018). Learner privacy in MOOCs and virtual education. Theory and Research in Education, 16(3), 280–307.

4 This Chapter Is a Stub: Wikipedia as a Disruptive Innovation

This chapter uses Wikipedia as a case study of successful Disruptive Innovation in technology enhanced learning in higher education. The chapter evaluates Wikipedia’s impact and its uneasy relationship with formal higher education. It examines how and by whom Wikipedia is used in higher education, and the implications of Wikipedia’s practices, especially its means of production. Wikipedia was launched in January 2001, originally in English, with the first edition in another language (German) appearing in March 2001 (Jemielniak, 2014). Since its inception, Wikipedia has become the world’s largest encyclopaedia and one of the world’s most popular websites, available in more than 250 languages (Mesgari, Okoli, Mehdi, Nielsen, & Lanamäki, 2015). Wikipedia was an offshoot of Nupedia, which began as an online encyclopaedia in the Encyclopaedia Britannica mould, with expert writers and peer reviewers. However, Wikipedia grew rapidly, ‘flourishing entirely independent of the site it was intended to serve, which simply couldn’t keep up with the sheer volume of content’ (McGrady, 2009). Bryant, Forte, and Bruckman (2005) argue, ‘Nupedia was stymied by a cumbersome editing process… The Wikipedia’s founders’ brilliance was in their © The Author(s) 2020 M. Flavin, Re-imagining Technology Enhanced Learning, Digital Education and Learning,



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ability to identify the shortcomings of the traditional model and adapt their project to new constraints’ (p. 9). Whether by design or practice, Wikipedia rapidly became disruptive, showing that the creation of knowledge was not the preserve of a formally educated elite but could be undertaken by anyone, and could be published at speed and with no cost to the end user. Wikipedia is not published, in the sense of being issued whole on a specific date. It is continually updated and checked; it is ‘precisely unlike anything in print’ (Gauntlett, 2008, p.  41, emphasis in original). Wikipedia is ongoing and constantly renewing whereas, in book or encyclopaedia production, editing occurs before publication and ends once the volume is published. Ideally, Wikipedia can be continually enhanced, too, as contributors and editors develop the entries (Jemielniak, 2014). By being a permanent work-in-progress, it aligns with definitions of Disruptive Innovation as a process rather than an event (Christensen, Raynor, & McDonald, 2015). Most researchers are not academics. They are people researching their holiday arrangements; their insurance policies; or the schools their children might attend. People also undertake research when they shop online, using the reviews of other customers to inform their decisions. The sites used by shoppers feature information volunteered by other users of the same goods or services. Wikipedia, similarly, relies on crowdsourcing and user-generated content, an approach which has also worked to boost commercial worth for organisations such as TripAdvisor and IMDb (Jemielniak, 2014). More content results in more revenue and credibility. Wikipedia also shares some of the features of a start-up, being entrepreneurial by soliciting donations, though it is a not-for-profit organisation run by the Wikipedia foundation registered in San Francisco, by-passing the need for investors expecting a return. It employs few staff and relies on volunteers for both funding and content (Greenstein & Zhu, 2012; Klapper & Reitzig, 2016). Wikipedia is an organisational as well as technological innovation, a business model innovation as well as a new technology, with innovation as part of its organisational DNA (Jemielniak, 2014). Wikipedia is a disruptive innovation but it has also branched out into, for example, Wikibooks, Wikiquote, Mediawiki, Wiktionary, Wikisource

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and Wikiversity. These are sustaining innovations, building incrementally from the original disruptive innovation.

Wikipedia as Disruptive Innovation Wikipedia is a classic disruptive innovation: free to use, simple and convenient. Furthermore, it disrupted a powerful incumbent in Encyclopaedia Britannica which, in 2012, announced it would stop publishing in printed form. Britannica was innovative in its own time, positing that authority could be placed in a brand rather than an individual, and aggregating experts’ work into one publication. Its success, however, was based on its ability to sell its product, maintain its means of production and produce a profit. It paid its experts whereas Wikipedia relies on volunteers. Wikipedia has already disrupted the printed encyclopaedia but, more subtly, it has the potential to disrupt deeply rooted aspects of academic practice because it can democratise how and by whom knowledge is produced, distributed and used. Wikipedia is arguably exploitative because the people who produce its content do not get paid for their labour, but it is at the same time potentially revolutionary because it detaches knowledge production from surplus labour. Contributors are not expected to create profit for publishers. They are expected to contribute to knowledge. Britannica has proscribed article lengths but there is no length restriction on Wikipedia articles, and no costs associated with the publication of longer articles. Greenstein and Zhu (2018) researched articles concerning aspects of US politics, finding the average length of a Wikipedia article was 4113 words, whereas the average length of a Britannica article was 1778 (p. 949). There is no necessary relationship between size and quality, but Wikipedia entries offer greater scope for development. Moreover, short Wikipedia articles, known as stubs, actively invite further contributions, encouraging more interactivity and user-generated content. In early research on Wikipedia, Giles (2005) compared it with Encyclopaedia Britannica, in a study of eighty-four articles, finding that each Wikipedia article had, on average, four errors, while each article in


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Britannica had three. Nonetheless, the article was important for showing Wikipedia could compete, in quality terms, with Britannica. Moreover, Wikipedia had only been in existence for four years at the time, whereas Britannica was 232  years old in 2005, indicating the rapid progress Wikipedia had made (Mesgari et  al., 2015). Rajagopalan et  al. (2011) compared information on cancer on Wikipedia with the Physician Data Query website, maintained by the National Cancer Institute in the USA, finding similar levels of accuracy, though with Wikipedia entries being less readable. Conversely, Hasty et al. (2014) studied Wikipedia articles for the ten most costly medical conditions in the USA, finding Wikipedia entries contained many errors, compared with peer-reviewed articles. Wikipedia articles are not perfect, but often bear comparison with more conventional printed sources. Other studies have critically analysed Wikipedia’s objectivity: Greenstein and Zhu (2018) compared articles on aspects of US politics published on Wikipedia and in Britannica, finding that Wikipedia articles were more likely to be slanted towards a Democrat position. Martin (2018), in a case study of his own Wikipedia entry, showed systematic bias could be present, despite surface commitment to Wikipedia’s guidelines. Moreover, Thompson (2016) showed how public relations (PR) companies had made alterations to Wikipedia entries, though the changes were identified and challenged by the Wikipedia community. The PR company, ‘interacted with Wikipedia using a mixture of traditional corporatist media relations and a view that they could edit and delete at will’ (p. 15), but Wikipedia’s community of editors amended their text, suggesting Wikipedia has integrity and a measure of objectivity. Clearly, neither Wikipedia nor Britannica is infallible but both can be useful. However, a key difference between the two is that the content of Britannica is fixed in each printed book whereas the content of Wikipedia is constantly evolving: hard copies of Britannica still list Pluto as a planet, but Wikipedia can respond to new knowledge instantly (Flavin & Hulova, 2018; Leitch, 2014). Wikipedia can have real-world impact. Xu and Zhang (2013) found Wikipedia improved the information environment in financial markets: while corporate websites control information content, Wikipedia enables independent expression. Moreover, given how frequently Wikipedia is

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updated, it allows information on companies to become public very quickly. Wikipedia can claim value by not being an arm of corporate communication, offering more authentic information with use value. As a disruptive innovation, Wikipedia disrupted the incumbent, the physical encyclopaedia, by drawing on the incumbent’s strengths and, at the same time, exploiting its weaknesses for the disruptor’s own advantage. It is parasitical on the incumbent but symbiotic with its users, who are the reason for its growth and influence. Through the breadth of its entries, including contemporary sportspeople and popular culture celebrities, it moved into a market space Britannica did not want to occupy and therefore ignored. Meanwhile, Wikipedia grew. Wikipedia is not a publishing utopia. It is, for example, a gendered space: only a small fraction of Wikipedia’s editors are women, and male editors are more active than female editors (Lam et al., 2011), despite the fact that there is not an imbalance between male and female in terms of Wikipedia readership (Collier & Bear, 2012). Reagle and Rhue (2011) argue both Wikipedia and Britannica demonstrate a gender bias in terms of their coverage of prominent figures, and Hinnosaar (2019) argues the gender gap among contributors results in unequal coverage of topics. Hinnosaar’s (2019) research also shows women are more likely to contribute to Wikipedia articles about women (three times more likely than men), while also showing that biographies of women on Wikipedia receive more views than biographies of men. Wikipedia also features underrepresentation of editors from the Global South (Jemielniak, 2014), as well as underrepresenting black history (Hinnosaar, 2019). Wikipedia aims for a neutral point of view in its articles but this is hard to achieve if the community of contributors is weighted towards men from the global north. Rubira and Gil-Egui (2019) analysed Wikipedia entries for the word ‘globalization’ in six Western languages, finding more similarities than differences between them, suggesting an acceptable level of reliability of Wikipedia, different language versions notwithstanding. However, the same study also showed an overreliance on English language sources, suggesting the influence of English across different languages and cultures and querying Wikipedia’s objectivity. Hara, Shachaf, and Hew (2010) argue, ‘over 75% of Wikipedia is written in languages other than English’ (p.  2098) but the English


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language can still dominate in terms of the sources used to validate entries, and Wikipedia can comprise a continuum of power imbalances evident in societies; Shaw and Hargittai (2018) identify, ‘the multidimensionality of digital inequalities’ (p. 143) as being present in Wikipedia. It has many advantages but it is part of society and reflects inequities inherent in the organisation of societies. Wikipedia relies on unpaid labour. As the content is generated by users rather than by paid employees, Wikipedia is a platform, or an aggregation point (Fallis, 2008). Wikipedia does not, strictly, provide content. It provides a space in which content is produced. In common with other sites, from Amazon to Ebay, it collects information but does not produce it directly. It facilitates the production, exchange and consumption of knowledge by a global community though its largest version is in English and the majority of its contributors are male. Firer-Blaess and Fuchs (2014) argue there is, ‘control of the platform by the users’ (p. 92), who create, enhance and sustain the entries, though the users are still products of societies and reflect, through Wikipedia’s contents, imbalances in global society. Wikipedia is an open educational resource but it does not follow that it is an unalloyed good. Jones (2019) argues open educational resources, ‘can also be in alignment with the contemporary needs of capital in which the learner has to constantly seek new and relevant knowledge, to make themselves a more desirable, educated and flexible labour commodity.’ Wikipedia, in common with other open educational resources and other disruptive innovations, finds its purpose through practice, though the user may not be in control of the purpose and may be reactive, acquiring knowledge to maintain or advance their socio-economic position. Wikipedia, as a resource freely available in the twenty-first century, serves the needs of its users but those needs may be linked to economic necessity as well as recreational preference. Open education has disruptive potential; the creation and sharing of resources opens up, ‘the possibility of lower cost education, efficiency and pedagogical innovation’ (Czerniewicz, Deacon, Glover, & Walji, 2017, p.  82). Stewart (2015) argues, ‘the word “open” signals a broad, de-­ centralized constellation of practices that skirt the institutional structure and roles by which formal learning has been organized for generations’

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(p. 287). Moreover, open source can turn privatised commodities into a public good and it also exposes previously untapped productive resources by opening-out knowledge production and consumption. However, the purposes for which it can be used can relocate the responsibility for continuing professional development from an employer to an individual. This is not to condemn the use of Wikipedia as an open educational resource to enhance employability, but to recognise that it can privatise the responsibility. Its meaning depends upon the purposes for which it is used. As a disruptive innovation, Wikipedia is free. However, in a monetised system quality can be correlated with cost. Therefore, it could be inferred that free means lower quality. In a marketised system you get what you pay for, and those doing the paying could reasonably expect that premium price means premium quality. Free resources may have to argue for and demonstrate their quality because of their paradoxical position within overall, monetised systems. Sundin (2011) identifies Wikipedia as a space where the already-­ published gets recycled but information provided on Wikipedia gets packaged in user-friendly ways, beginning with a synoptic paragraph and concluding with references. Time-poor users can get the information they want or need. By structurally foregrounding ease of use, simplicity and convenience, it underlines its status as a disruptive innovation. It has profoundly challenged a powerful incumbent through its technological affordances and its business model. Despite its social impact, however, its status in academia is unclear.

Wikipedia and Academia Wikipedia has disrupted the traditional encyclopaedia but it can also have a role in supporting academic work. A study of technology enhanced learning terms on Wikipedia showed it was potentially more useful than academic journal publications in the early phases of a technology because of the speed of its publication and the regularity with which Wikipedia’s contents are updated (Flavin & Hulova, 2018). Leitch (2014) argues, ‘many teachers categorically forbid their students to cite Wikipedia in


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their assignments, though this interdiction does not prevent students, or indeed the teachers themselves, from consulting Wikipedia without citing it’ (p.  4). Kim, Sin, and Tsai (2014) also argue Wikipedia is used widely by students. Selwyn and Gorard (2016) showed 87.5% of their sample of 1658 students in Australia used Wikipedia, albeit to a lesser extent than Facebook and YouTube, and for limited purposes. Wikipedia is used widely in higher education, despite not being produced in academia, and despite its being produced under terms eschewed by academia. Academia is hierarchical. It has qualified experts who state and audiences who listen. Academic hierarchies apply in a lecture theatre and in publication. Brailas, Koskinas, Dafermos, and Alexias (2015) argue, ‘formal schooling and academia has been established through centuries of educational tradition based on a binary pedagogical relationship between a group of students and their teacher’ (p. 62). Wikipedia is a challenge to academia because anyone can be a contributor, yet it has found a place in supporting academic work while at the same time challenging the conditions and relationships on which academic life is based, by extending the base of expertise. Wikipedia shows how technologies have the potential to transform education by democratising it and, more tellingly, by reframing the means by which knowledge is produced, distributed and consumed. In Wikipedia, the sole, academic expert gets challenged by visibly collaborative production (Bayliss, 2013). Wikipedia supports learning and teaching in higher education through its extensive usage in practice. Traditional academic practice has quality assurance. Novice participants undertake lengthy research degrees, having already gained higher education qualifications. They undertake research with their supervisors, submit their findings in a thesis and undergo an oral examination. Moreover, once the researcher begins submitting work to journals, they are subject to anonymous peer review. Wikipedia is radically different, the antithesis to conventional academic practice. It is easy to write for and easy to use. It democratises academic practice. As Medelyan, Milne, Legg, and Witten (2009) note, ‘It has effectively enabled the entire world to become a panel of experts, authors and reviewers’ (p. 717). Users on Wikipedia can call themselves anything they want, from their own names to elaborate aliases. The anonymity of contributors means that, in many instances, their expertise and status in the subject area is not known,

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opening the way for contributions not determined by academic hierarchies. Wikipedia is an equalising space for writing, in a wider academic publishing environment dominated by formal attainments. The fact of Wikipedia being a Disruptive Innovation, and the fact of its being published in conditions that potentially unseat traditional academic practices, does not mean that Wikipedia has to be excluded from academia. Wikipedia has produced a lot of content which supports learning and teaching in higher education (together with a lot of extraneous content), but at the same time Wikipedia still gets absorbed within existing pedagogy as a source used regularly to support academic work. Exhortations from institutions or individual academics not to use Wikipedia get routinely ignored, but while Wikipedia may have disrupted encyclopaedia production and offers a different mode of academic production, it has not fundamentally disturbed or disrupted higher education itself, primarily because it has not been actively included in higher education. Grudging tolerance does not make for constructive engagement. Wikipedia is often an irksome presence at the margin, used but not celebrated. In a classic Disruptive Innovation pattern, it gets disregarded because it does not fit the established mode of production, but it grows in a community of users who find it suitable for their needs. Mollifying attempts to engage with Wikipedia are not the answer. Leitch (2014) argues, ‘teachers forbidding their students from citing Wikipedia often describe it as a good place to begin research, implicitly distinguishing its authority from the final sources that are presumably a good place to end research’ (p. 11). An engaged rather than acquiescent approach to Wikipedia might well be preferable, and more usefully related to students’ actual practice. Students could be set the task of writing or editing a Wikipedia entry in a group. Such a task could encourage a critical approach towards sources and would encourage collaborative production. It could illuminate how academic work is produced through labour, not handed over from expert to novice. Soler-Adillon, Pavlovic, and Freixa (2018) undertook a case study in universities in Spain and Serbia, producing favourable responses from students who had written or edited Wikipedia entries relevant to their courses (and, in so doing, benefitting future cohorts of students). Wikipedia could be an asset to higher education because it encourages active learning, but it would require


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more widespread academic recognition to do so. Reilly (2011) argues Wikipedia is, ‘a pedagogical tool with which students can improve their research practices and writing proficiency… By writing for Wikipedia, students … develop rhetorical and technological proficiency, and generate texts that prompt real-world response and provide potentially useful information for fellow users… By participating in this community, students can exchange ideas with other writer-editors and receive feedback about their contributions, providing them with a material response to their writing not often experienced in classroom settings.’ Wikipedia can benefit academia but it requires the recognition that academia’s status as a specialist and expert community for the production and distribution of knowledge gets redefined and extended, making knowledge production a more widely distributed process, diluting the current boundaries of knowledge communities. Fallis (2008) argues people are more likely to be sceptical of Wikipedia entries than of traditional encyclopaedias, but scepticism of knowledge claims is a good thing and can prompt a rigorous, questioning response from students. Wikipedia can encourage students to be intellectually sceptical and autonomous. Moreover, Wikipedia users can see any entry’s edit history, thus seeing how knowledge is constructed, and considering alternative claims to those published. Wikipedia can pave the way for more digitally enabled, user-generated content, positioning students as co-producers of knowledge and academic partners. Furthermore, Wikipedia shows how innovative learning can take place outside the academy. Practice by contributors on Wikipedia, none of whom need an orthodox academic affiliation, can outflank academic production, as Wikipedia produces and updates content much more rapidly than academic journals (Flavin & Hulova, 2018). Universities have never monopolised learning but they comprise sites of concentrated academic production, distribution and usage. Wikipedia offers an alternative, a diffused model for the production, distribution and use of knowledge. Wikipedia does not come with a pedagogy or support, unlike content in the context of an academic programme, but is still useful in higher education because it gets a job done, offering core information on demand. Wikipedia is effective in higher education despite the absence of pedagogy and support because it is an encyclopaedia, a form of

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publication with which people are familiar and which they know how to use. Its generic description of encyclopaedia means users know how to engage with it without instruction. It does not ask for behavioural modification on the part of users. Instead, it meets their needs. Whilst radical in conception, it is designed to look like a product with which users are already familiar. Its skeuomorphic design is an aspect of its success. Wikipedia has disrupted the encyclopaedia but it can also disrupt the economic base for the production of knowledge. Von Hippel and Von Krogh (2003) argue, ‘free revealing does not make sense from the point of view of the private investment model of innovation’ (p. 214). By voluntarily co-creating knowledge, Wikipedia contributors destabilise traditional academic forms of publication and sidestep the gatekeepers of academic institutions. Wikipedia does not offer assessment or certification but it does offer open access educational resources.

The Wikipedia Community Wikipedia’s popularity is due in part to its community, the writers, editors and reviewers who produce it and its users. As Gauntlett (2008) notes, ‘Wikipedia embodies an optimistic ethos which, to the dismay of committed cynics, actually seems to work’ (p. 42, emphasis in original). Moreover, its methodology is not without precedent: in the nineteenth century, the Oxford English Dictionary relied on assistance with its content from the general public (Winchester, 1998). Wikipedia can be seen as a community of practice (Lave & Wenger, 1991; Wenger, 1998), in which users move from the periphery to the centre of organisations, developing a distinctive identity. Bryant et  al. (2005) argue, ‘At the periphery of Wikipedia, novice users contribute by reading articles out of interest, noting mistakes or omissions, and correcting them. For the novice, the goal of participating in Wikipedia is often information gathering (using the site as an Encyclopaedia). In passing, they identify problems and mistakes and fix them’ (p. 4). A community of practice understands learning as centripetal, whereby newcomers travel from the periphery to the centre of communities. However, progress from the periphery to the centre is not assured; trolls can be a destructive


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presence in online communities (Shachaf & Hara, 2010). Moreover, the vast majority of people who engage with Wikipedia opt to remain at the periphery as readers. A small minority may contribute some content but are unlikely to become part of the Wikipedia core community. Relatively few users contribute a large percentage of the overall editing activity on Wikipedia, with a long tail of users providing the rest (Suh, Convertino, Chi, & Pirollo, 2009). Lampel and Bhalla (2007) argue status seeking is a notable feature of participation in online communities, ‘a scarce social resource that is intimately linked to competition for attention and approval’ (p. 449). Given a practical hierarchy in online communities, there is a risk that they take on, ‘the characteristics of exclusive golf clubs rather than open, democratic forums’ (p. 451). Lampel and Bhalla’s (2007) also point out that virtual communities are not horizontal but have peaks and troughs of influence, as argued for from a Community of Practice perspective by Wenger (1998; see also Lave & Wenger, 1991, p. 123). Wikipedians gain status and reputation through participation (Xu & Li, 2015). Novice users have to serve their apprenticeships to reach core status, and in this sense Wikipedia reflects traditional academic and organisational hierarchies. It is open-entry but organisational reputation is earned over time, established through practice and accomplishments. Hara et al. (2010) argue Wikipedia is a distinct community of practice because it goes beyond formal organisational boundaries. Unlike a workplace, the Wikipedia workforce is fluid and open-entry because it is unpaid. However, Wikipedia retains the core structure of a community of practice and offers the community of practice’s conventional pathway to core membership, moving from the periphery to the centre. Wikipedia’s fundamental principles are expressed as ‘five pillars’ (Wikipedia, 2020), one of which is that it propounds a neutral point of view. Wikipedia also has a ‘Don’t Bite the Newcomer’ policy, but the policy may not have permeated the entire Wikipedia culture and community (Collier & Bear, 2012). However, Wikipedia additionally opens­up the question of surveillance and data collection in online environments. Contributors’ and editors’ actions are recorded. Users may have anonymity, but they also leave data trails and an IP address (Arazy, Ortega, Nov, Yeo, & Balila, 2015). As Engeström (2009) notes, ‘every alteration of an

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entry is automatically stored and retrievable for anyone as a cumulative record of previous versions and alterations’ (p. 4). Moreover, Haider and Sundin (2010) argue, ‘In Wikipedia, all versions of all articles are always accessible for all. Everything is constantly changing at the same time as it is always saved and stable, archived.’ In addition, Fallis (2008) argues, ‘Wikipedia is not a “black box.” Readers of Wikipedia have easy access to the entire editing history of every entry’ (p. 1668). Wikipedia is a palimpsest, with each stroke of its development and editing left on record. This is a strength of Wikipedia because the process of co-composition is visible. Wikipedia could also be used as a learning aid, showing how writing is an incremental process, characterised by revision and editing. However, it also shows how digital data trails are left, comprising a digital cautionary tale in this respect, illustrating how online engagement leaves traces. Wikipedia, like Google, is virtually ubiquitous. Wikipedia has changed aspects of knowledge production, distribution and consumption. Moreover, it relocates, in part, the production and distribution of knowledge away from the academy, provoking a frequently defensive response from universities, underlining its disruptiveness. Wikipedia entries commonly appear on the first page of results provided by search engines, giving Wikipedia de facto authority. Thompson (2016) argues, ‘any Google search on a topic will often display Wikipedia at the top of the suggested pages. So rather than diversity and plurality in online media, the top-­ ranked search engine Google recommends the top-rated information site, Wikipedia. In effect, this turns the web into a feedback loop between the two’ (p. 5). If Google determines the options users see, and Wikipedia offers instant, synoptic knowledge on virtually any topic, there is not only a feedback loop but also a virtual centre of gravity, through the combination of Google and Wikipedia’s organisation and presentation of information. Wikipedia can thus run the risk of, in practice, corralling knowledge, though the constant updating of Wikipedia implies the flexibility and contestation of knowledge. Perhaps the more telling practice exposed by the Google-Wikipedia feedback loop is the time pressures experienced in higher education, and in society more widely. If the first source of information offered to users does the job, that source will be used.


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Wikipedia is bureaucratic. Bureaucracy in all its forms enables control but it is also conservative by nature, resisting deviation from established procedure. Wikipedia’s bureaucracy is a by-product of its growth. It has changed, ‘from the encyclopaedia that anyone can edit to the encyclopaedia that anyone who understands the norms, socializes himself or herself … and still wants to voluntarily contribute his or her time and energy can edit’ (Halfaker, Geiger, Morgan, & Riedl, 2012, p. 683), and Shaw and Hargittai (2018) argue, ‘Wikipedia contribution remains vanishingly rare at the low end of the Internet skills spectrum’ (p. 163). However, bureaucracy is necessary on Wikipedia to manage and curate the increasing number of contributions (Arazy et al., 2015). Alongside its expansion, Wikipedia has developed policies and guidelines and a code of recommended good manners (Medelyan et al., 2009), and has also sought to protect the quality of its entries. Geiger and Ribes (2010) claim vandalism on Wikipedia is a routine activity occurring hundreds of times a day, but vandalism repair bots emerged in 2006 (Priedhorsky et  al., 2007), software that automatically edits the site, protecting Wikipedia’s quality. As an example of Wikipedia’s procedure and effectiveness, Magnus (2008) set up an experiment whereby thirty-six false facts were inserted into the Wikipedia entries of philosophers for a forty-eight-hour period. Fifteen of the errors were removed within the forty-eight hours and, of these, fourteen were removed in the first twenty-four. Three other entries were flagged-up as needing a citation.

Conclusion Wikipedia is a successful disruptive innovation in higher education. It is free, simple, easy to use and convenient. It removes the need to consult a printed encyclopaedia, disrupting a formerly powerful incumbent. Wikipedia both challenges the capitalist mode of production and serves it. Firer-Blaess and Fuchs (2014) argue Wikipedia is based on, ‘common ownership of the means of production and collaborative work’ (p.  90). Contributors volunteer their labour, producing because they want to, but they can also contribute to boost their employability. Users on Wikipedia can engage with the site because they want to, or because

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they need to acquire knowledge or skills to enhance or retain socio-­ economic status. Firer-Blaess and Fuchs (2014) argue, ‘Wikipedia is to a certain degree entangled into the capitalist relations of production’ (p. 97), which recognises that Wikipedia is a part of society, not a revolutionary departure from it, though Wikipedia also does things differently and shows how other knowledge-creation activities can be done differently. As with many other disruptive innovations, its disruptiveness arises from practice, from the purposes, the jobs, that Wikipedians get the technology to do. Contributors work for free on Wikipedia, which allows for the possibility of calling its business model exploitative. Volunteers create surplus value for the site. Haider and Sundin (2010) argue, Wikipedia has an, ‘actually very un-modern approach… It is somewhat of a knowledge sweatshop… Wikipedia is based entirely on free labour and that in an age in which knowledge is supposed to be the most important economical resource.’ By providing free content which can be used in increasingly monetised higher education systems, Wikipedia is both disruptive and potentially subversive. By not paying its contributors, however, Wikipedia exemplifies unequal power relations. Wikipedians can put their work on the site onto their curriculum vitae and job applications, potentially boosting their employability. Wikipedia competence and participation can be another skill set on employment’s digital waterfront. Wikipedia is thus both subversive and highly conventional. It disrupts the printed encyclopaedia on one hand but it mobilises and enables unpaid labour on the other. Wikipedia, as an open-source, constantly evolving encyclopaedia, can have liberating potential. Kwet (2019) argues, of open-source resources, ‘Free access to digital publications for all people on planet earth, irrespective of their wealth, could improve education, culture, equality, democracy, and innovation’ (p.  11). However, information in itself will not achieve these ends. It is a question of how the information is used, which opens up an ongoing role for universities in framing knowledge, creating narratives and pathways in the context of certified programmes. Wikipedia can play a role in democratising the academy globally, if the academy will let it.


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Wikipedia has disrupted the means by which knowledge is produced, distributed and used. It operates in a space academia largely disregards yet it gets used to support academic work. It has found a role in higher education without official encouragement. It has disrupted how the construction of knowledge is conceived of, through the removal of formal editorship. This chapter has analysed Wikipedia as a successful disruptive innovation in higher education. The next chapter examines social media technologies, which have the potential to be disruptive innovations, being free to use, simple and convenient, but which may not, in practice, be disruptive, and which may have an, at best, limited applicability to higher education.

References Arazy, O., Ortega, F., Nov, O., Yeo, L., & Balila, A. (2015). Functional roles and career paths in Wikipedia. Proceedings of the 18th ACM conference on computer supported cooperative work & social computing, 1092–1105. Retrieved from Bayliss, G. (2013). Exploring the cautionary attitude toward Wikipedia in higher education: Implications for higher education institutions. New Review of Academic Librarianship, 19(1), 36–57. Brailas, A., Koskinas, K., Dafermos, M., & Alexias, G. (2015). Wikipedia in education: Acculturation and learning in virtual communities. Learning, Culture and Social Interaction, 7, 59–70. Bryant, S.  L., Forte, A., & Bruckman, A. (2005). Becoming Wikipedian: Transformation of participation in a collaborative online encyclopedia. Proceedings of the 2005 international ACM SIGGROUP conference on supporting group work, 1–10. Retrieved from cfm?id=1099205. Christensen, C. M., Raynor, M. E., & McDonald, R. (2015). What is disruptive innovation? Harvard Business Review, 93(12), 44–53. Collier, B., & Bear, J. (2012). Conflict, criticism, or confidence: An empirical examination of the gender gap in Wikipedia contributions. Proceedings of the ACM 2012 conference on computer supported cooperative work, 383–392. Retrieved from

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Czerniewicz, L., Deacon, A., Glover, M., & Walji, S. (2017). MOOC-making and open educational practices. Journal of Computing in Higher Education, 29, 81–97. Engeström, Y. (2009). Wildfire activities: New patterns of mobility and learning. International Journal of Mobile and Blended Learning, 1(2), 1–18. Fallis, D. (2008). Toward an epistemology of Wikipedia. Journal of the American Society for Information Science and Technology, 59(10), 1662–1674. Firer-Blaess, S., & Fuchs, C. (2014). Wikipedia: An info-communist manifesto. Television & New Media, 15(2), 87–103. Flavin, M., & Hulova, K. (2018). An inferior source? Quantitively analysing the production and revision of five, technology enhanced learning-related terms on Wikipedia. Research in Learning Technology, 26. rlt.v26.2103. Gauntlett, D. (2008). Case study: Wikipedia. In G.  Creeber & M.  Royston (Eds.), Digital cultures: Understanding new media (pp.  39–45). New  York: McGraw-Hill. Geiger, R.S. & Ribes, D. (2010, February 6–10). The work of sustaining order in Wikipedia: The banning of a vandal, CSCW 2010. In Proceedings of the 2010 ACM conference on computer supported cooperative work (pp. 117–126). Savannah, GA. Giles, J. (2005). Intent encyclopaedias go head to head. Nature, 438, 900–901. Greenstein, S., & Zhu, F. (2012). Is Wikipedia biased? American Economic Review: Papers and Proceedings, 102(3), 343–348. Greenstein, S., & Zhu, F. (2018). Do experts or crowd-based models produce more bias? Evidence from encyclopedia britannica and wikipedia. MIS Quarterly, 42(3), 945–959. Haider, J., & Sundin, O. (2010). Beyond the legacy of the enlightenment? Online encyclopaedias as digital heterotopias. First Monday, 15(1). https:// Halfaker, A., Geiger, R.  S., Morgan, J.  T., & Riedl, J. (2012). The rise and decline of an open collaboration system: How Wikipedia’s reaction to popularity is causing its decline. American Behavioral Scientist, 57(5), 664–688. Hara, N., Shachaf, P., & Hew, K.  F. (2010). Cross-cultural analysis of the Wikipedia community. Journal of the American Society for Information Science and Technology, 61(10), 2097–2108. Hasty, R.  T., Garbalosa, R.  C., Barbato, V.  A., Valdes, P.  J., Powers, D.  W., Hernandez, E., et al. (2014). Wikipedia vs. peer-reviewed medical literature


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for information about the 10 most costly medical conditions. Journal of the American Osteopathic Association, 114(5), 368–373. Hinnosaar, M. (2019). Gender inequality in new media: Evidence from Wikipedia. Journal of Economic Behavior and Organization, 163, 262–276. Jemielniak, D. (2014). Common knowledge: An ethnography of Wikipedia. Redwood City, CA: Stanford University Press. Jones, C. (2019). Capital, neoliberalism and educational technology. Postdigital Science and Education, 1, 288–292. s42438-019-00042-1. Kim, K. S., Sin, S. C. J., & Tsai, T. I. (2014). Individual differences in social media use for information seeking. The Journal of Academic Librarianship, 40(2), 171–178. Klapper, H., & Reitzig, M. (2016). On the effects of authority on peer motivation: Learning from Wikipedia. Strategic Management Journal, 39(8), 2178–2203. Kwet, M. (2019). Digital colonialism: US empire and the new imperialism in the global south. Race & Class, 60(4), 3–26. Lam, S. T. K., Uduwage, A., Dong, Z., Sen, S., Musicant, D. R., & Terveen, L. (2011). WP: Clubhouse? An exploration of Wikipedia’s gender imbalance. Proceedings of the 7th international symposium on Wikis and open collaboration, 1–10. Lampel, J., & Bhalla, A. (2007). The role of status seeking in online communities: Giving the gift of experience. Journal of Computer-Mediated Communication, 12, 434–455. Lave, J., & Wenger, E. (1991). Situated learning: Legitimate peripheral participation. Cambridge: Cambridge University Press. Leitch, T. (2014). Knowledge, authority and liberal education in the digital age. Baltimore: Johns Hopkins University Press. Magnus, P. D. (2008). Early response to false claims in Wikipedia. First Monday, 9(1) Retrieved from Martin, B. (2018). Persistent bias on Wikipedia: Methods and responses. Social Science Computer Review, 36(3), 379–388. McGrady, R. (2009). Gaming against the greater good. First Monday, 14(2). Medelyan, O., Milne, D., Legg, C., & Witten, I. H. (2009). Mining meaning from Wikipedia. International Journal of Human-Computer Studies, 67, 716–754.

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Mesgari, M., Okoli, C., Mehdi, M., Nielsen, F. Å., & Lanamäki, A. (2015). The sum of all human knowledge: A systematic review of scholarly research on the content of Wikipedia. Journal of the Association for Information Science and Technology, 66(2), 219–245. Priedhorsky, R., Chen, J., Lam, S.  K., Panciera, K.  Terveen, L., & Riedl, J. (2007). Creating, destroying, and restoring value in Wikipedia. In Proceedings of the 2007 international ACM conference on supporting group work (pp. 259–268). Rajagopalan, M. S., Khanna, V. K., Leiter, Y., Stott, M., Showalter, T. N., & Dicker, A. P. (2011). Patient-oriented cancer information on the internet: A comparison of Wikipedia and a professionally maintained database. Journal of Oncology Practice, 7(5), 319–323. Reagle, J., & Rhue, L. (2011). Gender bias in Wikipedia and Britannica. International Journal of Communication, 5, 1138–1158. Reilly, C. (2011). Teaching Wikipedia as a mirrored technology. First Monday, 16(1). Rubira, R., & Gil-Egui, G. (2019). Wikipedia as a space for discursive constructions of globalization. International Communication Gazette, 81(1), 3–19. Selwyn, N., & Gorard, S. (2016). Students’ use of Wikipedia as an academic resource—Patterns of use and perceptions of usefulness. The Internet and Higher Education, 28, 28–34. Shachaf, P., & Hara, N. (2010). Beyond vandalism: Wikipedia trolls. Journal of Information Science, 36(3), 357–370. Shaw, A., & Hargittai, E. (2018). The pipeline of online participation inequalities: The case of Wikipedia editing. Journal of Communication, 68(1), 143–168. Soler-Adillon, J., Pavlovic, D., & Freixa, P. (2018). Wikipedia in higher education: Changes in perceived value through content contribution. Comunicar, 26(54), 39–48. Stewart, B. (2015). Open to influence: What counts as academic influence in scholarly networked twitter participation. Learning, Media and Technology, 40(3), 287–309. Suh, B., Convertino, G., Chi, E. H., & Pirollo, P. (2009, October 25–27). The singularly is not near: Slowing growth of Wikipedia. In WikiSym’09: Proceedings of the 5th international symposium on wikis and open collaboration. Orlando, FL. Sundin, O. (2011). Janitors of knowledge: Constructing knowledge in the everyday life of Wikipedia. Journal of Documentation, 67(5), 840–862.


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Thompson, G. (2016). Public relations interactions with Wikipedia. Journal of Communication Management, 20(1), 4–20. Von Hippel, E., & Von Krogh, G. (2003). Open source software and the ‘private-­ collective’ innovation model: Issues for organization science. Organization Science, 14(2), 209–223. Wenger, E. (1998). Communities of practice: Learning, meaning and identity. Cambridge: Cambridge University Press. Wikipedia. (2020). Five pillars. Retrieved from Wikipedia:Five_pillars Winchester, S. (1998). The professor and the madman: A tale of murder, insanity, and the making of the Oxford English dictionary. New York: Harper Collins. Xu, B., & Li, D. (2015). An empirical study of the motivations for content contribution and community participation in Wikipedia. Information and Management, 52, 275–286. Xu, S. X., & Zhang, X. (2013). Impact of Wikipedia on market information environment: Evidence on management disclosure and investor reaction. MIS Quarterly, 37(4), 1043–1068.

5 Putting a Brave Face on it: Social Media Technologies and Disruptive Innovation

Introduction This chapter examines social media technologies in higher education from a Disruptive Innovation perspective. The chapter argues social media technologies are a poor fit for higher education but retain the potential for a role, if only at the level of a Sustaining or Efficiency Innovation, given that they can enhance connections between people regardless of temporal or spatial boundaries. By using the term social media technologies, there is a risk of seeing a diverse range of services and practices as monolithic (Fenwick, 2016). However, it remains a useful, umbrella term. Tess (2013) argues, ‘social media is often described by example’ (p. A60) but, for the purposes of this chapter, the term, ‘social media’ encompasses a range of online services, applications and practices. Social media technologies are digital tools enabling the production, exchange and consumption of content through various modalities (including text, images and videos) and the formation of networks. Social media technologies also enable the construction and curation of digital identities and personal branding (McCorkle & Payan, 2017). Moreover, social media technologies enable © The Author(s) 2020 M. Flavin, Re-imagining Technology Enhanced Learning, Digital Education and Learning,



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active participation, both synchronous and asynchronous. They also enable publishing, remixing and repurposing. Social media technologies have the power to mobilise people in fields as diverse as political revolutions and supermarket discounts. In higher education, social media technologies provide universities with the possibility of digitally mediated, high-quality relationships with their students (Clark, Fine, & Scheuer, 2017): Doleck, Lajoie, and Bazelais (2019) argue social media technologies, ‘arguably represent one of the most consequential technological developments in recent history’ (p.  1545). Universities with an extensive social media profile can engage effectively with students, potential students and alumni. However, and while social media technologies have the capacity to support learning and teaching in higher education, actual practice suggests social media technologies do not make learning and teaching in higher education simpler and are not, in practice, a Disruptive Innovation, in part because social media technologies can mask their own, commercial practices. Newman, Beetham, and Knight (2018), in a UK study, asked students how often they used digital technologies to undertake seven named activities. The use of social media was the lowest scoring activity (46%, as opposed to 84% of students accessing lecture notes or recorded lectures). Social media technologies can be used as a curriculum bolt-on, with potential for added value, but they are not, in general, a successfully embedded part of the curriculum. That said, social media technologies can help students develop skills which are transferable to the academic realm: students might become acquainted with the uses of a hashtag via Facebook or Twitter, but the hashtag can also be a valuable tool when navigating a database. This chapter examines Facebook as both an innovation and as a community of practice. It also looks, less extensively, at other, selected social media technologies. In addition, the chapter looks at social media technologies as a means of marketing higher education, and examines the tension between the free services offered by social media technologies, and how data submitted to social media technologies gets used.

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Facebook Etc. This section of the chapter looks at a number of social media technologies, including Facebook, Twitter, WhatsApp and YouTube. Facebook is an exemplar of social media technologies. It conforms to the core criteria for a disruptive innovation. Facebook is simple, convenient, free and easy-to-use. Does it follow that it is a disruptive innovation? Not necessarily, because it depends on how Facebook is deployed in higher education. In line with Christensen and Raynor (2003), the key is how Facebook is used, the jobs it does for students and lecturers. In Disruptive Innovation, people create meanings for technologies through their usage of them (Christensen & Raynor, 2003) and social media technologies are only disruptive if they are used disruptively. The user exerts control over how they use social media, creating purpose through practice, but, in general, social media technologies in higher education are used to undertake tasks which are, in essence, predigital. Moreover, social media technologies can be used for straightforward delivery. They are only interactive if they are used interactively. They can just be digital megaphones. Facebook is, ‘the face of online social networks’ (Tess, 2013, p. A61). Ezumah (2013) surveyed 289 students in the USA, arguing ease of use and the potential to undertake different tasks drew students to Facebook. From this perspective, Facebook can be seen as a disruptive innovation. Social media technologies require only minimal information to register an account and get started. However, Selwyn (2009, 2014) shows how students’ Facebook postings continue informal exchanges of the kind that have characterised student life for generations. These exchanges and practices do not add to learning and teaching, merely communicate it informally through a digital channel. They may cement relationships between students but the practice of relationship-building itself is predigital. Social media technologies are a sustaining innovation or an efficiency innovation, facilitating an existing process through digital means. Michikyan, Subrahmanyam, and Dennis (2015) surveyed 261 students, finding 14% of their Facebook postings were academically related, albeit more than in a study of Facebook postings in an earlier study (Selwyn,


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2009). Both studies found students using Facebook to vent feelings about their studies and their lecturers, and in this sense social media technologies relocate a pre-existing practice. Moore-Russo, Radosta, Martin, and Hamilton (2017) studied a sample of postgraduate students and found Facebook was used primarily for entertainment and socialising. Social media technologies do not change practice; they merely comprise an efficient channel for increasingly time-poor students to do things they have always done. Some studies have found students responding positively to the use of social media in education (Samuels-Peretz, Camiel, Teeley, & Banerjee, 2017), but Skiera, Hinz, and Spann (2015) argue, ‘most studies find a negative relation between time spent on Facebook and academic performance’ (p. 67), and Kuznekoff, Munz, and Titsworth (2015) show how social media technologies can be a distraction in classrooms. Doleck et al. (2019) argue there is no statistically significant relationship between use of social media technologies and academic performance, and Smith (2016) identified social media technologies as a ‘double-edged sword’ (p.  44) with the potential to both help and hinder academic progress. Christensen and Raynor (2003) argue disruption arises from practice rather than design but social media technologies lend themselves to numerous purposes. There is no straightforward, causal relationship between the use of Facebook and other social media technologies and academic performance. Their educational outcomes depend on how they are used in each individual context. Hickerson and Kothari (2017), looking at Facebook from the perspective of lecturers rather than students, state, ‘Faculty overwhelmingly reported using social media for sharing classroom announcements and fielding student questions as they would in a more traditional course management system’ (p. 404). Social media technologies are a sustaining innovation for lecturers, too, building on the virtual learning environment as a communication channel which, itself, is a sustaining innovation building on the traditional higher education classroom. Manca and Ranieri (2016a), in a study undertaken in Italy, found academics were more likely to use social media for social purposes than for teaching, and that personal use was not a predictive factor of teaching usage. In a further study, Manca and Ranieri (2016b) found the use of social media

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technologies was limited due to, ‘cultural resistance, pedagogical issues or institutional constraints’ (p. 216), and Veletsianos and Kimmons (2013) interviewed three faculty members who experienced a tension between personal connections and professional responsibilities when using social media technologies, while recognising that the technologies could help them to use their time more efficiently. Lecturers, like students, use social media technologies to get pre-existing jobs done, not to disrupt their practice. Social media technologies can also be understood as a sustaining innovation for exchanging messages (Gikas & Grant, 2013), in or out of class. Social media technologies offer an enhancement of existing practice, or a more efficient means of communication (comprising an efficiency innovation), but they do not transform practice. Barczyk and Duncan (2013) examined a sample of 106 students who did not find Facebook to be more effective than their institutional virtual learning environment. Facebook can do jobs that other technologies can do, and it can do them to an equivalent and even higher level, but it does not create new forms of practice and is not a disruptive innovation. There is a potential novelty value in using social media technologies to support learning and teaching but novelty value decreases over time (Janoske, Byrd, & Madden, 2019). Adams, Raes, Montrieux, and Schellens (2018), in a study at Ghent University, found students had high expectations of using Twitter to support their learning and teaching but became sceptical about it, and Welch and Bonnan-White (2012) found Twitter did not increase student engagement in introductory sociology and anthropology courses. These studies may be indicative of the novelty wearing off, or it may highlight a structural unsuitability of Twitter to support learning and teaching. In focus groups, the students researched by Adams et al. (2018) did not like the way Twitter blurred boundaries between their education and other areas of their lives. Similarly, Waycott, Thompson, Sheard, and Clerehan (2017) found some students maintaining separate Twitter accounts to support their personal lives on one hand, and their learning lives on the other, arguing students curated different digital identities. Demarcation in technology usage has also been noted by Wang, Woo, Quek, Yang, and Liu (2012) and Salmon, Ross, Pechenkina, and Chase (2015). More positively, Janoske et  al.


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(2019) show how students who engage with Twitter can gain both formal and informal knowledge. Moreover, Kuznekoff et  al. (2015) and Menkhoff, Chay, Bengtsson, Woodard, and Gan (2015) argue Twitter enables less vocal students to engage. In addition, a study by Luo, Shah, and Cromptom (2019) found Twitter to be more popular than a discussion forum on a virtual learning environment for maintaining student engagement, and Carpenter and Krutka (2015) sampled educators who found Twitter to be, ‘efficient, accessible and interactive’ (p. 707), though their specific study looked at schoolteachers rather than higher education lecturers. Shah and Cox (2018) studied academics’ use of Twitter, seeing it as, primarily, a professional practice. Most Tweets were sent during work hours, in the context of mini-breaks, enabling some symbiosis between social media and professional practice. Tang and Hew (2017) argue Twitter is a useful ‘push’ technology for getting information across to students. Twitter, like Facebook, comprises a sustaining innovation, enhancing some aspects of students’ and lecturers’ practice, but not transforming it. Bélanger, Bali, and Longden (2014) point out a hazard of academics’ tweets: ‘the message is not controlled any more by central administration. Anybody can tweet and re-tweet in any direction they want with virtually total impunity; if faculty in particular are not in sync and bought-in with current branding directions, they can do serious damage to an institution without much consequence to themselves’ (p. 27). Social media technologies can compromise a university’s brand because they elude total control from the institution’s centre. Moreover, a Tweet or other social media comment can be taken out of context, inflicting reputational damage. Arceneaux and Dinu (2018) compared Instagram and Twitter in terms of how well a sample of students in the USA recalled information transmitted through the two social media technologies, finding the visual platform of Instagram to be more effective than the text-based technology of Twitter. Similarly, Doiron (2018) argues visual communication takes centre stage in social media settings, hence the proliferation of emojis. Perhaps social media technologies are well-suited to snapshots of information but are less suitable for sustained argument. The instantaneous nature of social media technologies, their ease of access, is conducive to

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condensed exchanges but less suitable to the conditions of academic work, including the hour-long lecture (from which social media technologies can provide a welcome diversion) and the academic essay. A study of distance education in Africa found WhatsApp to be the most significant social media technology for connecting students, overtaking Facebook (Madge et  al., 2019). Furthermore, a case study in Ireland showed WhatsApp being used widely (Stone & Logan, 2018). In addition, a small-scale study by Church and Oliveira (2013) found exchanging messages on WhatsApp to be more conversational than standard texting. In this sense, WhatsApp represents a sustaining innovation on texting. More notably, social media technologies are a shifting landscape. shut down. It initially attracted millions of users but failed to become a sustainable business and closed in 2000. Boyd and Ellison (2007) argue: ‘Early adopters complained that there was little to do after accepting Friend requests, and most users were not interested in meeting strangers’ (p. 214). Users could only join by invitation. Myspace also fell from market dominance to practical obsolescence: Torkjazi, Rejaie, and Willinger (2009) show that the growth of user identities in MySpace was exponential, followed by a sudden and significant slow-­ down in April 2008 due to an increase in the popularity of Facebook, which offered an easier route through which to undertake online social networking (Ezumah, 2013), its ease of use being a factor in its success. WhatsApp (launched in 2009) and Instagram (launched in 2010 and bought by Facebook in 2012) have both come to prominence, but both may fade. Vonderau (2016) notes that YouTube has broadened the category of video to include both professional and amateur output, with content encompassing education, music, comedy and a range of other forms. The extension of broadband home internet was itself an innovation (arguably a disruptive one) as it changed the type and scale of content that could be easily consumed in people’s homes, and fed the growth of YouTube. Having been launched in 2005, YouTube was acquired by Google in 2006, aiding Google’s expansion. Langley and Leyshon (2017) argue, ‘The ease and flexibility of the act of uploading ensured that the YouTube platform filled up with content, which in turn attracted audiences, and then advertisers’ (p. 21). YouTube has disrupted consumption of video


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content but it has not disrupted higher education. Watching an educational video on YouTube is not radically different to watching a video on a university web page. Lee and Lehto (2013) argue YouTube can be suitable for procedural, step-by-step learning, but this is a sustaining innovation on the printed manual, not a disruptive innovation. Facebook and other social media technologies are ultimately an awkward fit for learning and teaching in higher education. More broadly, a range of social media technologies can be used to support higher education, but not all initiatives are successful. Moreover, when social media technologies do work in higher education, they do so at the level of Efficiency Innovation or Sustaining Innovation. They have not disrupted, despite having the potential to be disruptive.

Facebook as a Community of Practice Facebook may have value in higher education from a Community of Practice perspective (Lave & Wenger, 1991; Wenger, 1998). The Community of Practice theory argues learning is a centripetal process, as newcomers to a learning community move from the periphery to the centre. Learning is about the construction of an effective identity for the learning community, rather than being about the acquisition of a product called knowledge. Facebook and other social media technologies can be used as an aspect of becoming a student, of developing and curating a distinct identity in the context of higher education study, moving inwards from the periphery of a community as the student identity becomes more developed, and Barczyk and Duncan (2013) argue Facebook facilitates the development of a community of practice. However, while the development of an identity accompanies and can enhance the experience of a curriculum, it is not an embedded part of it, though new students can feel more at ease on Facebook than in the new physical environment of the university. They can begin to construct their identity of student in what feels to them to be a digital safe space, maintaining links with their former network while constructing a new one. Other researchers have identified digital stewardship, whereby users can promote the usage of technologies to others,

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strengthening the newcomer’s progress from the periphery to the centre (Lewis & Rush, 2013; Wenger, White, & Smith, 2009). Kimmons (2014) argues, ‘a participation gap exists between those who know how to participate fully via such media and those who do not’ (p. 93), but apprentice status and legitimate peripheral participation are acceptable sites and phases for learning in the community of practice model. Social media technologies can help to smooth passage into a higher education community. Junco (2015), however, found Facebook had a negative effect on the performance of first-year undergraduates, hypothesising that the students were transitioning from one mode of life to another, maintaining contact with pre-university friends while building new relationships. In this specific instance Facebook retarded academic progress (obstructing the creation of a new, academic identity) while facilitating social progress. The development of a new identity can involve the casting off of an old one. People create identities on Facebook and other social media technologies, in which they are the central node. Moreover, the identity they construct is often aspirational more than authentic. Zuboff (2019) notes, ‘the maximization of “likes” as the signal of one’s value in this existential marketplace’ (p.  472), indicating social media technologies can comprise competitive social and technological spaces, in which digital identities compete for notice and prominence. Couldry and Mejias (2019) argue, ‘the purpose of “social” media platforms is to encourage ever more of our activities and inner thoughts to occur on platforms’ (p.  341). A social media identity is curated but it can comprise a reputational risk as more of a life is made present online. Self-exposure online can lead to the dissemination of an unreflective posting or Tweet, directing content beyond the user’s control. The pressure to be present online can put digital identity at risk at the same time as it curates it. Brech, Messer, Vander Schee, Rauschnabel, and Ivens (2017), in a study of university Facebook pages, found the reputation of a university was the main determinant of the number of fans it had, more than the university’s size. It is possible that the fans of the pages wanted to be associated with the university’s reputation. It became part of the construction of an aspirational identity, established through followers, tags and likes.


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Facebook can be a community of practice but this does not make it a disruptive innovation. Facebook can facilitate and smooth a process which customarily occurs as part of higher education in any case. It can make the process of acculturation more efficient, and it can enhance it by comprising a bridge between prior and new forms of living, but the technology consolidates and enhances. It does not disrupt. Progress in a community of practice happens over time. Like Disruptive Innovation, it is a process not an event, but Facebook is not a disruptive innovation in itself, and social media technologies seen through a community of practice lens are still sustaining or efficiency innovations, though the perspective enables a clear sense of how social media technologies can be used to construct and curate a digital identity.

Marketing Interactions with a university’s social media channels can be functional or social but both can build relationships. A study of social media technologies in the marketing of universities by Le, Dobele, and Robinson (2019) showed prospective students were most interested in finding out about the institution’s reputation; its career prospects; learning and teaching; administration; and student life. Peruta and Shields (2018) studied Facebook posts from top universities in the USA. Certain topics, such as athletics, increased the level of engagement. A study in Canada (Bélanger et al., 2014) showed a university’s Happy New Year posting on Facebook gaining a significantly above average number of ‘Likes.’ Universities use social media in ways which are not strictly functional, to promote their institutions and their brands. Students and potential students enjoy the association with a brand’s success and can aspire to align with a successful brand. Social media technologies are effective for opening and developing different channels of communication, and can have value before university study begins. Fagerstrøm and Ghinea (2013) undertook a case study at a university in Norway, finding that Facebook pages for prospective students on specific courses produced a notable improvement in converting applicants to registered students, from 43.3% to 88.8%. Fagerstrøm and

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Ghinea (2013) further argue, ‘Social networks … challenge established marketing strategies based on conventional perspectives on how the marketplace works’ (p. 46). In the context of their study, ‘Some applicants started to share information about their interests and technological skills, their experience as an applicant and how complex it was to decide what and where to study’ (p. 48). Prospective students were building a connection with other students and with the university, developing new relationships at the pre-arrival stage. Similarly, Galan, Lawley, and Clements (2015) interviewed twelve postgraduate students. Facebook and YouTube were both used in the students’ searches, to find out about the institution and to find out former students’ views. Social media technologies have greater credibility if some of the content does not come officially from the university but from current or former students. The social media technology comprises, in effect, a customer review platform. Ribchester, Wakefield, and Miller (2012), in a case study, set up a bespoke online social network for new students coming to university, finding it an effective means of bridging the transition to higher education, providing introductions to both faculty and fellow students. Usage of the system tailed-off dramatically following the induction week, but this was because the network had done its job. Engaging with a social media technology does not feel like marketing in a conventional, passive sense. The presence of student reviews gives the technology enhanced credibility. A prospective student uses the social media technology to find out about the institution but the presence of student feedback means the university is not in clear and obvious control of all the content. Social media technologies are clearly an important marketing tool for universities but they are a more enhanced form of marketing by being interactive, encouraging students to join communities relevant to their studies, and by distributing the sources of information, from a university’s marketing department to its wider community. Social media technologies are useful for marketing higher education, perhaps more so than for learning and teaching, as social media technologies lend themselves to quick and impactful, abbreviated messages.


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Data and Profit Prior to Facebook (and, before Facebook, Myspace), (1997–2000) offered social networking but Facebook was the technology that succeeded, in part through generating income from online advertising (Vidal & Mitchell, 2013). Social media technologies need to be sustainable economically which, in practice, means they need to take the data garnered from their users to attract targeted advertising. Social media technologies are big businesses. Fenwick (2016) argues they are, ‘multinational corporations, whose commercial profits depend upon content sharing contributed by its users through their free labour … user connectivity is continuously trawled, hauled and aggregated in data mining … social media participants are caught in a central tension, becoming simultaneously both empowered agents supposing themselves to be acting beyond conventional institutional structures, and targets for exploitation by global capitalist networks’ (p. 672). Facebook’s mission statement is, ‘To give people the power to build community and bring the world closer together’ (Zuckerberg, 2017), but the statement suppresses the commercial imperative fuelling Facebook. The message foregrounds Facebook as a networking tool but conceals how users’ data is collated and sold on. Social media technologies need to make money and they do so by selling the data they collect. Users of social media technologies appear to accept the trade off, the exchange of their personal data in return for online services. They take the advantages of social media and trade-in their personal data which is used by firms selling products and political groups seeking support. Facebook gets money for selling-on the data it harnesses. It offers services to its users but its services also entail loss of data control (Anderson, 2019). The practice of gathering and selling data may make social media technologies unsuitable for higher education. Anderson (2019) argues, ‘the inherent commercial bias of social media, with a business model based upon promoting the consumption of advertised goods and services, is anathema to educational use … On the other hand, we may find the exchange of our time and our data is a small cost for an obvious educational benefit … We give our attention to promoted goods or services

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and in return we receive some value’ (p. 8). However, the data, ‘is used for multiple purposes—none of which are transparent to those who have contributed the data’ (p. 12). The data contributed through social media technologies creates profit: ‘This surplus data is aggregated and analysed, then sold to a host of purchasers wishing to influence our behaviour— and especially our purchasing, consumption and political decision-­ making’ (p. 13). The surplus data generated by interactions with social media equates to surplus value, the tier of engagement that creates economic value for others. The commercial imperative of social media technologies collides with their use value and with their suitability to higher education. Higher education via social media technologies comprises a trade between content and personal data, but the personal data is sold on for commercial and political appropriation. The firm Cambridge Analytica, which was working with Donald Trump’s election team, obtained data from up to eighty-seven million Facebook users, and academics were involved in retrieving the data (Manokha, 2018; Richterich, 2018). Cambridge Analytica were also active during the Brexit referendum. The data collected on social media technologies can be used to nudge people towards desired outcomes, in some instances by advocating the virtues of a political candidate or denigrating their opponent. Being influenced by advertising in this way is contrary to the open-ended nature of educational enquiry but, alternatively, it may align conformably with educational programmes framed by aims and learning outcomes. Curriculum design nudges students towards fore-ordained states. Social media technologies are arguably of a type with the practices of twenty-­ first century higher education. In this sense there is less of a collision between use value in higher education and commercial imperatives because of increasingly schematic curriculum design with outcomes defined in advance, underpinned by monetised systems in which students can define themselves as customers purchasing goods and services. The practice of using higher education to advertise is not limited to Facebook or other social media technologies. Newspapers, magazines and journals for the higher education community feature advertising, without its being seen as a major threat to scholarly integrity. Perhaps the issue with social media technologies is their opacity when it comes to students’


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data and what social media technologies do with it. Using social media technologies to support learning and teaching implicates students in other practices, without students being fully aware of how their data is used: Zuboff (2019) notes, ‘the artful manipulation of Facebook’s culture of intimacy and sharing’ (p. 92). Users may well not be fully conscious of how their data is being used, or by whom. Moreover, Manokha (2018) argues, ‘the tendency to invade or violate individual privacy is structural’ (p. 895, emphasis in original). Social media technologies have data extraction as a design feature, though not an explicit one. Terms and conditions are rarely read and require prodigious effort to do so: the extraction and selling-on of user data creates profit for the service provider but implicates the user in commercial and political processes that the user did not consciously sign up for.

Conclusion There has been no social media revolution in higher education. Social media technologies enhance contacts between students, and between students and their universities, but they do not challenge existing pedagogical models. They help sustain existing practices in higher education, relocating many social features of higher education, but they do not disrupt higher education. Siemens and Weller (2011) identify, ‘the one-way information flow model of many lecture halls and classrooms slows innovation’ (p. 165), but social media technologies have not changed the flow. Students in a lecture hall can use Facebook to do other things, especially if the lecture is boring, but this is not disruptive (at least not in the sense of Disruptive Innovation), as it is only the digitalisation of the note passed around or the whispered conversation. It is, in fact, less disruptive because it is mediated silently through a screen and keyboard. Social media technologies are also not a Disruptive Innovation because they are primarily targeted towards social rather than learning activities. Users deploy social media technologies to support their social lives more than their learning lives. That said, there is not always a clear distinction between the two. Amador and Amador (2017) conducted a study with trainee teachers, who viewed their Facebook interactions as social but

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which were, in practice, academically related, if only at the level of seeking solace in the face of a sizeable study burden. The fact that the students in the sample perceived those with whom they were interacting as friends influenced their tendency to think of themselves as engaging in a social rather than educational practice. Social media technologies can blur boundaries between practices but they do not transform practices. Boundary blurring (Fenwick, 2016) can ensue because social media technologies can be used for both social and learning purposes, but social media technologies are primarily a sustaining innovation. Social media technologies can also be efficiency innovations, enabling swift, effective communication with and between students on widely used platforms, at no direct monetary cost to the user. Social media technologies enable students to get social and educational tasks done, without direct cost and with minimal inconvenience, effectively self-serving information. They do not, however, create new forms of practice. They relocate practice that already takes place. Social media technologies are still looked to in order to provide technology solutions that disrupt higher education. Selwyn and Stirling (2016) argue, ‘Social media continues to be a topic where education researchers want to remain hopeful that this technology might provide the “Killer App” capable of initiating significant shift in how people learn and engage with education’ (p. 3). Social media technologies do retain potential as a pedagogical tool but they are not new anymore. Facebook was created in 2003 at Harvard University and within four years it was available to anyone aged thirteen or over with an email address. The term social media was coined in 2005 (Gikas & Grant, 2013). Twitter was launched in 2006. If social media technologies were truly going to disrupt higher education, they would have got around to it by now. This chapter has analysed social media technologies in higher education, arguing social media technologies are sustaining innovations or efficiency innovations, despite their disruptive potential. They have not changed practice though they do produce high revenue streams for third parties, and they can influence commercial practices and, worryingly, political affiliation. They may disrupt in areas other than higher education, though not always by explicit means. The next chapter examines the


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increasing monetisation of higher education and what this means for technology enhanced learning.

References Adams, B., Raes, A., Montrieux, H., & Schellens, T. (2018). ‘Pedagogical tweeting’ in higher education: Boon or bane? International Journal of Educational Technology in Higher Education, 15(1), 19. Retrieved from s41239-018-0102-5. Amador, P. V., & Amador, J. M. (2017). Academic help seeking: A framework for conceptualizing facebook use for higher education support. Tech Trends, 61, 195–202. Anderson, T. (2019). Challenges and opportunities for use of social media in higher education. Journal of Learning for Development, 6(1), 6–19. Arceneaux, P. C., & Dinu, L. F. (2018). The social mediated age of information: Twitter and Instagram as tools for information dissemination in higher education. New Media and Society, 20(11), 4155–4176. Barczyk, C. C., & Duncan, D. G. (2013). Facebook in higher education courses: An analysis of students’ attitudes, community of practice, and classroom community. International Business and Management, 6(1), 1–11. Bélanger, C. H., Bali, S., & Longden, B. (2014). How Canadian universities use social media to brand themselves. Tertiary Education and Management, 20(1), 14–29. Boyd, D. M., & Ellison, N. B. (2007). Social network sites: Definition, history, and scholarship. Journal of Computer-Mediated Communication, 13(1), 210–230. Brech, F.  M., Messer, U., Vander Schee, B.  A., Rauschnabel, P.  A., & Ivens, B. S. (2017). Engaging fans and the community in social media: Interaction with institutions of higher education on Facebook. Journal of Marketing for Higher Education, 27(1), 112–130. Carpenter, J. P., & Krutka, D. G. (2015). Engagement through microblogging: Educator professional development via twitter. Professional Development in Education, 41(4), 707–728. Christensen, C. M., & Raynor, M. E. (2003). The innovator’s solution: Creating and sustaining successful growth. Boston: Harvard Business School Press.

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Church, K., & De Oliveira, R. (2013, August). What’s up with whatsapp?: Comparing mobile instant messaging behaviors with traditional SMS.  In Proceedings of the 15th international conference on human-computer interaction with mobile devices and services (pp. 352–361). Clark, M., Fine, M. B., & Scheuer, C. L. (2017). Relationship quality in higher education marketing: The role of social media engagement. Journal of Marketing for Higher Education, 27(1), 4–58. Couldry, N., & Mejias, U. A. (2019). Data colonialism: Rethinking big data’s relation to the contemporary subject. Television & New Media, 20(4), 336–349. Doiron, J.  G. (2018). Emojis: Visual communication in higher education. PUPIL: International Journal of Teaching, Education and Learning, 2(2) Retrieved from view/1370. Doleck, T., Lajoie, S. P., & Bazelais, P. (2019). Social networking and academic performance: A longitudinal perspective. Education and Information Technologies, 24(2), 1545–1561. Ezumah, B. A. (2013). College students’ use of social media: Site preferences, uses and gratifications theory revisited. International Journal of Business and Social Science, 4(5), 27–34. Fagerstrøm, A., & Ghinea, G. (2013). Co-creation of value in higher education: Using social network marketing in the recruitment of students. Journal of Higher Education Policy and Management, 35(1), 45–53. Fenwick, T. (2016). Social media, professionalism and higher education: A sociomaterial consideration. Studies in Higher Education, 41(4), 664–677. Galan, M., Lawley, M., & Clements, M. (2015). Social media’s use in postgraduate students’ decision-making journey: An exploratory study. Journal of Marketing for Higher Education, 25(2), 287–312. Gikas, J., & Grant, M. M. (2013). Mobile computing devices in higher education: Student perspectives on learning with cellphones, smartphones & social media. The Internet and Higher Education, 19, 18–26. Hickerson, A., & Kothari, A. (2017). Learning in public: Faculty and student opinions about social media in the classroom. Journalism and Mass Communication Educator, 72(4), 397–409. Janoske, M., Byrd, R., & Madden, S. (2019). One liners and catchy hashtags: Building a graduate student community through twitter chats. Public Relations Education, 5(1), 70–100. Junco, R. (2015). Student class standing, Facebook use, and academic performance. Journal of Applied Developmental Psychology, 36, 18–29.


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Kimmons, R. (2014). Social networking sites, literacy, and the authentic identity problem. TechTrends, 58(2), 93–98. Kuznekoff, J. H., Munz, S., & Titsworth, S. (2015). Mobile phones in the classroom: Examining the effects of texting, twitter, and message content on student learning. Communication Education, 64(3), 344–365. Langley, P., & Leyshon, A. (2017). Platform capitalism: The intermediation and capitalisation of digital economic circulation. Finance and Society, 3(1), 11–31. Lave, J., & Wenger, E. (1991). Situated learning: Legitimate peripheral participation. Cambridge: Cambridge University Press. Le, T. D., Dobele, A. R., & Robinson, L. J. (2019). Information sought by prospective students from social media electronic word-of-mouth during the university choice process. Journal of Higher Education Policy and Management, 41(1), 18–34. Lee, D. Y., & Lehto, M. R. (2013). User acceptance of YouTube for procedural learning: An extension of the technology acceptance model. Computers & Education, 61, 193–208. Lewis, B., & Rush, D. (2013). Experience of developing twitter-based communities of practice in higher education. Research in Learning Technology, 21. Retrieved from Luo, T., Shah, S. J., & Cromptom, H. (2019). Using twitter to support reflective learning in an asynchronous online course. Australasian Journal of Educational Technology, 35(3) Retrieved from AJET/article/view/4124. Madge, C., Breines, M. R., Dalu, M. T. B., Gunter, A., Mittelmeier, J., Prinsloo, P., et al. (2019). Whatsapp use among African international distance education (IDE) students: Transferring, translating and transforming educational experiences. Learning, Media and Technology, 44(3), 267–282. Manca, S., & Ranieri, M. (2016a). ‘Yes for sharing, no for teaching!’: Social media in academic practices. Internet and Higher Education, 29, 63–74. Manca, S., & Ranieri, M. (2016b). Facebook and the others. Potentials and obstacles of Social Media for teaching in higher education. Computers and Education, 95, 216–230. Manokha, I. (2018). Surveillance: The DNA of platform capital—The case of Cambridge analytica put into perspective. Theory & Event, 21(4), 891–913. McCorkle, D., & Payan, J. (2017). Using twitter in the marketing and advertising classroom to develop skills for social media marketing and personal branding. Journal of Advertising Education, 21(1), 33–43.

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Menkhoff, T., Chay, Y. W., Bengtsson, M. L., Woodard, C. J., & Gan, B. (2015). Incorporating microblogging (“tweeting”) in higher education: Lessons learnt in a knowledge management course. Computers in Human Behavior, 51, 1295–1302. Michikyan, M., Subrahmanyam, K., & Dennis, J. (2015). Facebook use and academic performance among college students: A mixed-methods study with a multi-ethnic sample. Computers in Human Behavior, 45, 265–272. Moore-Russo, D., Radosta, M., Martin, K., & Hamilton, S. (2017). Content in context: Analyzing interactions in a graduate-level academic Facebook group. International Journal of Educational Technology in Higher Education, 14(1), 1–15. Retrieved from https://educationaltechnologyjournal.springeropen. com/articles/10.1186/s41239-017-0057-y. Newman, T., Beetham, H., & Knight, S. (2018). Digital experience insights survey 2018: Findings from students in UK further and higher education. Bristol: JISC. Peruta, A., & Shields, A. B. (2018). Marketing your university on social media: A content analysis of Facebook post types and formats. Journal of Marketing for Higher Education, 28(2), 175–191. Ribchester, C., Wakefield, K., & Miller, G. (2012). Creating a transitional space for new students through pre-induction social networking. Journal of Geography in Higher Education, 36(3), 455–467. Richterich, A. (2018). How data-driven research fuelled the Cambridge Analytica controversy. Partecipazione e conflitto, 11(2), 528–543. Salmon, G., Ross, B., Pechenkina, E., & Chase, A. M. (2015). The space for social media in structured online learning. Research in Learning Technology, 23, 1–14. Samuels-Peretz, D., Camiel, L. D., Teeley, K., & Banerjee, G. (2017). Digitally inspired thinking: Can social media lead to deep learning in higher education? College Teaching, 65(1), 32–39. Selwyn, N. (2009). Faceworking: Exploring students’ education-related use of Facebook. Learning, Media and Technology, 34(2), 157–174. Selwyn, N. (2014). Digital technology and the contemporary university. Abingdon: Routledge. Selwyn, N., & Stirling, E. (2016). Social media and education… now the dust has settled. Learning, Media and Technology, 41(1), 1–5. Shah, N. A. K., & Cox, A. M. (2018). Analysing the pattern of twitter activities among academics in a UK higher education institution. In G. Chowdhury, J.  McLeod, V.  Gillet, & P.  Willett (Eds.), Transforming digital worlds:


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­iConference 2018 (Lecture Notes in Computer Science, 10766). Springer. Retrieved from Siemens, G., & Weller, M. (2011). Higher education and the promises and perils of social network. Revista de Universidad y Sociedad del Conocimiento, 8(1), 164–170. Skiera, B., Hinz, O., & Spann, M. (2015). Social media and academic performance: Does the intensity of Facebook activity relate to good grades? Schmalenbach Business Review, 67(1), 54–72. Smith, E. E. (2016). ‘A real double-edged sword:’ Undergraduate perceptions of social media in their learning. Computers & Education, 103, 44–58. Stone, S., & Logan, A. (2018). Exploring students’ use of the social networking site Whatsapp to foster connectedness in the online learning experience. Irish Journal of Technology Enhanced Learning Ireland, 3(1), 42–55. Tang, Y., & Hew, K. F. (2017). Using twitter for education: Beneficial or simply a waste of time? Computers & Education, 106, 97–118. Tess, P. A. (2013). The role of social media in higher education classes (real and virtual)—A literature review. Computers in Human Behavior, 29, A60–A68. Torkjazi, M., Rejaie, R., & Willinger, W. (2009). Hot today, gone tomorrow: On the migration of MySpace users. In Proceedings of the 2nd ACM workshop on online social networks (pp. 43–48). Retrieved from Veletsianos, G., & Kimmons, R. (2013). Scholars and faculty members’ lived experiences in online social networks. The Internet and Higher Education, 16, 43–50. Vidal, E., & Mitchell, W. (2013). When do first entrants become first survivors? Long Range Planning, 46, 335–347. Vonderau, P. (2016). The video bubble: Multichannel networks and the transformation of YouTube. Convergence, 22(4), 361–375. Wang, Q., Woo, H. L., Quek, C. L., Yang, Y., & Liu, M. (2012). Using the Facebook group as a learning management system: An exploratory study. British Journal of Educational Technology, 43(3), 428–438. Waycott, J., Thompson, C., Sheard, J., & Clerehan, R. (2017). A virtual panopticon in the community of practice: Students’ experiences of being visible on social media. The Internet and Higher Education, 35, 12–20. Welch, B.  K., & Bonnan-White, J. (2012). Twittering to increase student engagement in the university classroom. Knowledge Management & E-Learning: An International Journal, 4(3), 325–345.

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Wenger, E. (1998). Communities of practice: Learning, meaning, and identity. Cambridge: Cambridge University Press. Wenger, E., White, N., & Smith, J. D. (2009). Digital habitats: Stewarding technology for communities. Portland, OR: CPsquare. Zuboff, S. (2019). The age of surveillance capitalism: The fight for a human future at the new frontier of power. New York: PublicAffairs. Zuckerberg, M. (2017). Bringing the world closer together. Facebook. Retrieved from

6 Cash in the Academic: Technology Enhanced Learning and the Monetisation of Higher Education

This chapter relates technology enhanced learning to the monetisation of higher education. The chapter examines the practice of bring your own device (BYOD), seeing it as an exemplar of the transfer of the costs of higher education from the state to the individual. At the same time, however, BYOD can be seen as an act of agency, with students and lecturers using technologies they own in preference to institutional technologies. The chapter analyses the implications of BYOD, including fewer computer facilities being supplied by universities, and the possibility of smaller Information Technology (IT) support departments. The chapter also analyses learning analytics in higher education and how they can be used to support students or, alternatively, how learning analytics can be used for surveillance, or as a way to produce profit. Students are the fundamental revenue stream for universities in privatised higher education systems, and universities have a vested interest in having satisfied students who graduate. Data and learning analytics can serve this need, as they record each interaction. It does not follow, however, that students derive no benefit from having their data extracted, if it enhances student support and is used to inform strategic decisions around library services and the curriculum. This chapter therefore examines the © The Author(s) 2020 M. Flavin, Re-imagining Technology Enhanced Learning, Digital Education and Learning,



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conflicting aspects of data gathering and learning analytics in higher education. The chapter also examines the metaphor, common in privatised higher education systems, of the student as customer. Any relationship, once monetised, changes fundamentally. Pohjola and Puusa (2016) undertook a case study of a community of enthusiasts sharing plans for converting petrol and diesel cars to electric. Once the project attracted an outside investor, processes became more closely audited and there was increased pressure to attain results. A privatised higher education system creates changes too. Bates and Kaye (2014) studied the effects of a new fees regime for higher education in the UK, with students paying £9000 per annuum instead of £3000. Students in their sample did not, on the whole, have increased expectations of the process of their higher education, but their expectations of what their degree would do for them, in terms of employability, did increase. Monetisation leads to changes in perception and expectation, of technology and of higher education. Monetisation also leads to changes in practice.

Bring Your Own Device (BYOD) Students pay tuition fees in many countries. They buy expensive textbooks and they also buy tablets, computers and smartphones. However, the latter are more complex than text books because they integrate students’ learning and social lives, and their lives as consumers. Moreover, students’ IT contracts and service user agreements are no longer solely with universities. They are with large IT organisations, to whom students pay fees, separate to fees for their tuition. The money they pay gives them access to goods and services unrelated to their studies. The practice of BYOD (which dates from 2007, according to Walton (2014)) is not simply a transfer of costs from the university to the individual. It disrupts practice but is also potentially disruptive of the relationship between a university and its students. As a technological practice it offers affordable, convenient and easy to use technologies. Its cost, ease of use and convenience identify it as a disruptive innovation. The

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university charges for tuition in monetised systems, and the practice of BYOD means it is in a position to provide less and less hardware, effecting an efficiency innovation for its own benefit. The university, through issuing certificates of attainment, provides its imprimatur and links the student with its brand, but both the cost of tuition and the costs of hardware for learning are moved away from the institution and towards the individual, who is monetised whether they want to be or not, requiring the university to legitimise and endorse their achievements. A student does not have to buy a smartphone or tablet. They can use their university’s IT facilities. To do so, however, determines where they can be at any one time. Hardware at universities assumes students undertake academic tasks for designated periods of time in designated spaces. Furthermore, static computers are unusable when universities are closed. It is difficult to sustain the assumption that students will undertake their work in an IT lab when many of them are in paid employment as well as studying, and when they possess devices of comparable or superior quality to those made available by their universities. In addition, while desktop computers are bulky apparatuses, necessitating students making a journey to a campus, many students own or rent devices which can be stored in a bag or a pocket. However, students may prefer not to bring user-owned technologies to university for a range of reasons, including personal security, an anxiety which can be offset by having secure storage facilities on campus. More subtle barriers to BYOD may be present, too, such as a consciousness of others’ devices and their technical superiority or perceived brand superiority. BYOD offers students ease of use and convenience in line with Christensen’s original definition of Disruption (Christensen, 1997, p. xv). Hung (2017) found students appreciated using clickers to participate in class content but their preference was for clicker apps they could download onto their own devices, rather than clickers as a stand-alone piece of apparatus, the students citing convenience and ease of use as reasons for their views. The smartphone or tablet is the hub, to which a range of practices can be appended. Kong and Song (2015) also argue for BYOD as a personalised learning hub. In addition, Bass and Movahed (2018) argue BYOD can support widening participation in higher


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education, enabling students to use their own devices for study as well as a range of other tasks. Learning can take place in breaks from work or domestic commitments. The student does not have to attend a campus to learn. BYOD can comprise and evidence a digital divide, but some divides are more divisive than others. Originally framed as a question of who had access to the internet, the notion of a digital divide extended to the question of effective usage rather than the bare fact of access. Duvivier (2019) argues, ‘increasing reliance on IT for delivery of education or access to learning resources has the potential to increase the financial burden on students to purchase laptops, and mobile devices’ (p. 21), but technologies are increasingly affordable, having improved incrementally along Sustaining Innovation lines since their introduction: a study by Kobus, Rietveld, and Van Ommeren (2013) showed 96% of a sample of over 3000 students in Holland having a portable device, with socioeconomic status not being a decisive factor (though a later study of the general Dutch population did suggest the persistence of a digital divide (van Deursen & van Dijk, 2019)). A large-scale survey of 2018 showed 94% of UK students owning a laptop, and 83.6% using a smartphone to support their learning (Newman, Beetham, & Knight, 2018, p.  25), and other studies have noted that devices can be inexpensive (Campbell et al., 2013). The increasing affordability of digital devices has also been noted by Pecori (2018). The laptop computer itself was a high end, top down innovation, initially used in organisations before percolating down to domestic usage as its price dropped (Köffer, Ortbach, Junglas, Niehaves, & Harris, 2015), lessening a digital divide. Studies on the digital divide customarily examine how different social groups access and use technology (see, e.g. Van Deursen & Mossberger, 2018), but the increasing affordability of technologies means money is not necessarily a key determinant per se of digital engagement in many contexts. However, Robinson et al. (2015) argue, ‘digital inequality and exclusion cannot be analysed apart from the offline circumstances of individuals and groups … specific forms of digital exclusion map onto particular kinds of offline disadvantage’ (p. 570). From this perspective, a digital divide is expressive of other forms of socioeconomic inequality. Park and Humphry (2019) argue social disadvantage compounds digital

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exclusion, and Mihelj Leguina, and Downey (2019) argue the online environment reproduces or even increases existing inequalities, stating digital technologies, ‘act as engines of inequality’ (p. 1471). In addition, Van Deursen, Helsper, Eynon, and Van Dijk (2017) argue, ‘Those who are marginalized in important domains are likely to also be marginalized in their digital skills and uses of technology, creating a vicious cycle where historically marginalized groups are further marginalized by technology’ (p. 470). Technology can amplify or exacerbate divides, equalising access and participation in theory but not necessarily in practice. BYOD is popular in business as well as universities, and for similar reasons. It reduces costs and can foster innovation through the emergence of new practices driven by users, who are more willing to experiment with their own devices than with their employer’s property. Employees can prefer the convenience of using personally owned devices with which they are fully familiar. They can be willing to spend their own money for this convenience (Shumate & Ketel, 2014). Businesses, meanwhile, experience the benefit of reduced overheads and maintenance. They cut their costs and they also improve their productivity because employees are using technologies with which they are comfortable (Afreen, 2014). Köffer et al. (2015) argue employees are more innovative with technologies they own and that the flow of innovation has been reversed: ‘The innovation process of the twentieth century was first deployed in organizations and only afterwards diffused into the consumer realm … the flow of innovation is now a bottom-up rather than a top-down process and requires a fundamental rethinking of IT strategy’ (p. 364). BYOD is disruptive because it brings new technologies and practices into institutions, altering those institutions in the process. Practice with user-owned technologies creates innovation. The organisation gains innovation (which can be disruptive, sustaining or efficiency innovation) and loses a hardware cost in the process, which is transferred to the employee. Köffer et al. (2015) also argue, ‘consumer IT and the permission to use privately owned IT exert positive effects on employees’ innovation behaviors’ (p. 363). BYOD can potentially liberate practice and catalyse innovation, and it can certainly offer cost savings, efficiency innovations, to businesses. BYOD is a disruptive innovation for students but it may be an efficiency innovation for universities, allowing them to provide education at


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reduced cost. It may also diversify as a practice: Campbell et al. (2013) offer the alternative definitions of bring your own everything (BYOE) and BYO* (substitute nearly anything for the asterisk). The fluidity of the definitions suggests that the innovation is still in progress but it is changing practice and it is a disruptive innovation. It serves students’ needs for anytime, anywhere access, offering cost savings to universities at the same time and, as Marginson (2018) notes, universities cannot disregard the means by which they are funded.

Learning Analytics The data accrued by students has the potential to open up education but it can also create a regime of surveillance and a climate of mistrust. Hagel, Eckenrode, and Srinivas (2016) recognise, ‘the opportunity to aggregate data about highly distributed transactions and apply sophisticated analytical software to identify and understand patterns emerging from these transactions’ (p. 15), but the more important questions relate to how the data is used and the purposes for which it is used. Žižek (2004) sees data in more sinister terms: ‘while in feudalism the key to social power was the ownership of the land … and in capitalism the key to power is the ownership of capital…, in the newly emerging netocracy the measure of power and social status is the access to key pieces of information’ (p.  303). Similarly, West (2019) argues that, in the nineteen-nineties, ‘companies turned from an understanding of the Internet primarily as a marketplace for the sale of goods to one that placed primacy on the role of technology in the production and harvest of users’ data’ (p. 21). Learning analytics presupposes that learning and teaching can be better understood and enhanced by analysing data accrued in the course of a student’s interactions with the university. The use of technology for everything from recording entry into buildings and classrooms, to library loans, through to recording module and programme performance, means there is an abundance of data on students accumulated as a matter of course. There is the potential for the data to be analysed in order to enhance processes and to identify, and potentially meet, student need.

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Large-scale data can be used to better understand students and the contexts in which they learn. Technology can also identify a student who might be struggling, if they are not attending classes or missing deadlines. Students generate a lot of data. The problem is what universities do with the data, or what they can do with it. Learning analytics offers different attributes to different constituencies. For university leaders, data can enhance institutional performance by providing the information to enhance student retention and outcomes. Learning analytics can also identify aspects of a curriculum that are not working, enabling data-­ informed redesign. For students, learning analytics can enhance personalised support. Technology, however, has another face. Learning analytics can be about control as well as convenience. It can enable surveillance as well as support. Data enables predictions: past online activities can be used to predict future activities, but data can also be used to induce in the form of advertising. According to Zuboff (2015), ‘new markets of behavioural prediction and modification’ with the aim of producing ‘revenue and market control’ (p.  75) are a product and feature of data collection. Zuboff (2015, 2019) writes about surveillance capitalism, arguing data accrual enables both profit and control: ‘the Faustian pact required to “get something in return” eliminates the older entanglements of reciprocity and trust’ (Zuboff, 2015, p. 84). Learning analytics is not a neutral practice. We may have grown accustomed to having our data mined. We are accustomed to seeing banner adverts on web pages based on our search history. We use social media technologies in which the information we provide and the interactions we undertake are used for targeted advertising and the elicitation of our support for politicians. In this climate, it is possible that students are sanguine about having their data mined in education, as in every other aspects of their lives. The gathering and analysis of users’ data may be nothing more sinister than an accepted part of twenty-first century digital practice. However, rendition has become common practice. Data is transacted in ways that reduces individuals’ agency, as individuals are not active participants in the transaction. Instead, individuals are passive donors. Zuboff (2019) argues for, ‘the


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rendering of our lives as behavioural data for the sake of others’ improved control of us … ignorance is a condition of this ubiquitous rendition’ (p. 94). Online surveillance was initially undertaken by businesses monitoring customers’ behaviour on websites, before moving into the political realm: ‘commercial surveillance in the 1990s and 2000s in many ways made government surveillance possible’ (West, 2019, p. 22). The economic practice came first; the political and ideological practices came after. Google has made exceptional profits from the traces generated by online actions, through advertising revenue: ‘Google discovered that while ostensibly a search company, it was really in the advertising business, selling its users’ data to advertisers’ (West, 2019, p. 32). Moreover, Google’s use of surveillance extends to its email service, Gmail: ‘Google has the capability to scan the content of users’ emails to serve up ads relevant to the text they contain’ (West, 2019, p. 34). Zuboff (2019) also notes, ‘Google maintains our search histories indefinitely’ (p. 15) and that, effectively, users of the internet are subjected to digital strip searches (pp. 172, 521). Learning analytics therefore raises questions relating to ethics, if students are not contributing data consciously and willingly: Zuboff (2015) argues, ‘The extractive processes that make big data possible typically occur in the absence of dialogue or consent’ (p. 79). Students may not be aware they are contributing data. Moreover, they may not care. Extensive data is accrued in daily interactions with Google, Facebook and other technologies. Students may accept the harvesting of their data, possibly seeing it as, in effect, a cost levied for online engagement. Digital technologies offer plentiful affordances but this creates problems as well as opportunities. Zuboff (2015) argues, ‘Nothing in past experience prepared people for these new practices …. Individuals quickly came to depend upon the new information and communication tools as necessary resources in the increasingly stressful, competitive, and stratified struggle for effective life’ (p.  85). The speed with which the new technologies infiltrated daily practice militated against the production of codes of conduct or ethical frameworks for the devices’ and services’ usage. In practice, we had the tools but not the instructions, creating positive conditions for Disruptive Innovation, but also for potential exploitation. Practice created innovation but also dependency which, in turn, created vulnerability.

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It is easy to see data gathering in an unfavourable, Orwellian light; ‘Instead of many people having some privacy rights, these rights have been concentrated within the surveillance regime’ (Zuboff, 2015, p. 83). However, in higher education, it has to be recognised that data can enhance the student experience, producing rapid and reliable evidence of whether the university needs to buy more copies of certain books, or whether ebooks are rising in popularity, or if a student might be struggling. Johnson (2014) argues data can be used to make ‘Netflix-style course recommendations’ (p. 5), which may over-simplify the composition and purpose of academic programmes, but the process also offers simplicity and convenience, using prior attainments to support future choices. The gathering of data can enable intervention for the student’s benefit. It seems, therefore, that data, in a digital age, simply is. Students and lecturers produce it in their daily interactions with university resources and it is intrinsically neither good nor bad. Its beneficence or malevolence depends on its usage by individuals and, importantly, by service providers. Couldry and Mejias (2019) argue we have, ‘a new social order, based on continuous tracking,’ resulting in, ‘a new form of data colonialism, normalizing the exploitation of human beings through data …. Data colonialism paves the way for a new stage of capitalism whose outlines we only glimpse: the capitalization of life without limit’ (p. 336). The form to be taken by this new colonialism is not always clear but the argument recognises that those in possession of data have power to monitor individual’s present practices, to predict future practices and to influence those practices. Couldry and Mejias (2019) further note data colonialism’s ‘normalization of resource appropriation, and its redefinition of social relations so that dispossession came to seem natural’ (p. 339). This point may already have been reached, as many users know their interactions with online environments are routinely tracked. What happens to the data, however, varies, and, in the case of higher education, data analysis can be used to analyse and to help students in need. Thatcher, O’Sullivan, and Mahmoudi (2016) argue, ‘As users of technology enter into tacit data licence agreements with the firms that create and control the technology, they are dispossessed of the right to control those data’ (p.  994), which presupposes a fundamental vulnerability in online


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engagement, as data are exposed, creating the potential for exploitation, or (more benignly) enhanced support. Kwet (2019) also argues there is digital colonialism, ‘foreign corporations undermine local development, dominate the market, and extract revenue from the Global South, with power obtained primarily through the structural domination of digital architecture, which leads to more general forms of imperial control’ (p.  7, emphasis in original). Kwet (2019) further argues, ‘Big data is the central component of surveillance capitalism. Corporations and states are collecting, storing and processing enormous centralised databases of information about the world’s netizens. This enables them to infer traits about people … that individuals do not disclose themselves’ (p. 13). Data gathering and analysis can undermine the consciously constructed public self and can be used to expose individuals. Furthermore, as long as data is gathered by private companies rather than institutions controlled by elected representatives, oversight of data gathering is difficult, and misappropriation of data is more likely. One of the problems with online data gathering is its aggregation and dissemination. Couldry and Mejias (2019) argue it is a largely unregulated area of the economy which specialises in, ‘collecting information from medical, financial, criminal, and other records for categorizing individuals through algorithmic means. Data brokers package and sell those lists to advertisers and other users such as governments and law enforcement agencies’ (p. 340). In addition, the purpose, for Couldry and Mejias (2019) is malign: ‘The goal is clear: to install into every tool for human living the capacity to continuously and autonomously collect and transmit data within privately controlled systems of uncertain security’ (p.  344). However, online data gathering is not solely a sinister and opaque external imposition. We have self-tracking on platforms, ‘we count our followers or likes’ (Couldry & Mejias, 2019, p. 344) and we use the information, rightly or wrongly, to self-evaluate. The gathering of data is a by-product of digitisation. The usage of data can be personalised, but data can also be appropriated and used for economic and political purposes. Couldry and Mejias (2019) may be correct in arguing, ‘a vast and varied social quantification sector operating within a complex web of data

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processing functions extract data from everyday life at a depth far exceeding that found in earlier forms of social organization’ (p. 344), but the potentially enhancing aspects of learning analytics should not be overlooked, either. Data protection regulations in higher education may shield students’ data from misappropriation, and can lead to individually tailored student support. Moreover, in the European Union, the General Data Protection Regulation, implemented in 2018, aims to give individuals greater control of their data.

The Information Technology Department Some time ago, Walton (2014) posed the question, ‘Does the library need to continue providing access to fixed PCs for students?’ (p.  1). Hardware is a notable cost for universities, and computer laboratories occupy space that could be profitably deployed for other purposes. In a large-scale survey in the UK, fewer than 1% of higher education students said they did not own a personal device (Langer-Crame, Newman, Beetham, Killen, & Knight, 2019). In the same survey, 93% of higher education students said they owned and used a laptop to support their learning, 86% said they owned and used a smartphone, but only 28% said they owned and used a desktop computer. Patterns of IT usage are changing and the use of personal devices is widespread. The university’s role as provider of IT services is radically diminished, offering a clear efficiency innovation. The increasing portability of personally owned devices comprises a sustaining innovation, leading to the near-ubiquity of personal devices on campus. Increasingly, students do not need a university’s IT department, instead making their own arrangements with third party vendors, which raises the question of why universities pay huge amounts to maintain large IT departments. The increasing prevalence of BYOD challenges IT departments and it can also change practice and strategy regarding technology, offering notable cost savings to universities in the process. If a computer at a university breaks, the university is responsible for its repair. If a student’s personally owned device breaks, it is their responsibility to get it repaired or replaced. They can go to the provider with whom they have a


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contract or the shop where they bought the product. They are less likely to go to an IT service desk. The university is commonly excluded from the process and achieves a cost saving. IT departments can, in practice, restrain innovation. Bygstad (2017) argues, ‘By definition innovation processes are hard to plan but also hard to envision, and emerge through interactions of diverse actors. That is why a third-party ecology is more innovative than a heavyweight IT department’ (p. 191). Technologies offered by an institutional IT department exist to support the work of the institution. Technologies outside of an institutional framework have greater potential to be disruptive innovations, with purpose arising through practice (Christensen & Raynor, 2003). Play and experimentation with technologies takes place outside rigidly structured frameworks. Students regularly have IT about their person which can be superior to the technology made available by the university, so it is not surprising if students prefer BYOD. It is more surprising that universities continue to fund large-scale IT provision. Smaller IT departments and fewer rooms on campus filled with desktop computers would free-up space and offer savings. University leaders can achieve an efficiency innovation by scaling back inessential IT provision. Having transferred the costs of tuition in monetised systems, universities can now transfer the costs of technology hardware onto students, too. The possibility of the efficiency innovation of universities having smaller IT departments arises from the Disruptive Innovation of BYOD.  Bygstad (2017) argues, ‘there is a parallel to earlier paradigm shifts in IT; in the 1980s the PCs fundamentally changed the user experience, but still relied heavily on central computers; in the 1990s the World Wide Web revolutionised the linking of information, but still relied heavily on the installed base of networked PCs’ (p. 183). BYOD ends the university’s dominance over the possession and distribution of resources for learning. It may also question the university’s responsibility to provide extensive IT facilities. Students do not need to attend a physical library and they do not need to attend rooms on campuses populated by computers. They can rely on the resources they can access any time from any place.

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Raghunath, Anker, and Nortcliffe (2018) identify a problem arising from the introduction of new technologies in universities: ‘Academics begin by trying to map existing manual or PC tasks to their devices. It takes time to innovate and see the potential to develop new ways of working using smart devices’ (p. 183). Academics attempt to use mobile technologies as a sustaining innovation but less utilitarian and more open-ended usage of devices may cause disruptive innovation to happen over time. When we get new digital tools we commonly attempt to map them across to our existing practices, looking for familiar features in new devices. It takes time and experimentation and play to discover other purposes. The university’s infrastructure, both technical (the IT department) and pedagogical (the curriculum) frames usage and makes innovation more difficult. More BYOD and smaller IT departments with fewer edicts may help to make innovation more plentiful. IT departments can argue for their continuing relevance by producing policies for BYOD but these policies can be irrelevant in practice if students are using their devices away from the institution and on different networks. Any suggestion of the IT department as technological in  loco parentis is flawed (DiFilipo, 2013). Innovation in technology enhanced learning diminishes the IT department and may, in time, reduce it to a minor support function. Students may appreciate computers on campus as a back-up but they may be more appreciative of facilities to charge-up their own devices. It may be more important for a university to maintain and enhance an excellent IT infrastructure, a network enabling fast access to and downloading of study materials, and the support of BYOD.

The Student as Customer Customers in monetised systems expect value. In higher education the extraction of value can be focused on outcomes, specifically the degree classification, but it can also be focused on process. Guilbault (2016) writes, ‘Many factors have led to this approach including increased competition, decreased government funding, and the increased cost of education …. Since marketing in HE is well established, it would follow that this means that there its a customer focus’ (p. 132). Marginson (2013)


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identifies the constituents of markets, including producers, who ‘want to generate profits—revenues surplus to costs. They want to maximise the price they obtain and minimise the material value embodied in each product …’ Markets also include customers, ‘who engage in price-based shopping’ (p. 356). Higher education is not a product in the orthodox commercial sense, though it is increasingly implicated in commercial frameworks in some countries, given the transfer of costs to the individual undertaking the process of higher education. The customer metaphor in higher education is pervasive: ‘relationship marketing emphasizes customer retention and satisfaction, and focuses on customer loyalty and long-term customer engagement. Many schools are recognizing the need to implement marketing concepts which other industries have recognized as necessary for success’ (Guilbault, 2016, p. 133). One of the means by which customers are retained is brand loyalty. Students need to believe in the product. One of the means by which belief can be structured is effective communication, which begins long before the student has even registered. Universities increasingly sell themselves to prospective students through open days, websites and their social media presence. Marginson (2018) argues, ‘whenever university places confer value in comparison with non-participation, there is rivalry; and in HEIs with a surplus of applications over places, participation is excludable. A market in tuition becomes possible’ (p. 327). Universities petition for applications but, with rare exceptions, do not have open entry. Status and reputation are enhanced by exclusivity. Not everyone has the actual or social capital to access the brand. Higher education can sceptically be redefined as eBay’s academic relation, comprising a market where customers (students) and products (certified achievements) interact, mediated through the university’s employees as de facto sellers. The problem is the marketplace model limits students’ agency, implying the product is stable and the student is the product’s passive recipient. However, in education the quality of the product is, or should be, closely related to the input of the purchaser. The customer metaphor in higher education is therefore less illuminating than thinking of the university metaphorically as a gym, with employees cast as personal trainers (Guilbault, 2016). They can provide guidance and support but the quality of the outcome depends on the student’s input. As Laing and

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Laing (2016) argue, ‘to rely on the notion of the student-as-customer is an oversimplification of an otherwise complex set of relationships’ (p. 44). The monetisation of higher education underpins the student as customer metaphor. The practice of BYOD does not necessarily impact on the perception of student as customer but the practical integration of learning with social and retail transactions undertaken through personally owned devices affiliates learning with social interaction and with consumer practices. BYOD can enhance the perception of higher education as being another product, another feature of marketisation. Greater alignment between different areas of practice blurs boundaries. Students may not be customers in the orthodox sense but that does not prevent them from conceiving of themselves as customers, with implications for their interactions with universities, from on-campus and digital services through to degree classifications. BYOD lessens the student’s affiliation with the university and can lead to the student conceiving of the university as the provider of goods and services. The student may no longer self-identify as a member of a community pursuing a common goal.

Conclusion BYOD changes the student’s relationship with the university. Learning is not contained within teaching hours but is distributed, to be managed whenever the increasingly time-poor student has time. Learning has never been wholly fettered by a timetable but it is certainly the case that technology has diffused learning. Access to learning materials is not constrained by a university library’s opening hours. As Duvivier (2019) argues, ‘study is no longer strictly confined to the library or computer rooms; indoor and outdoor areas can become spaces for learning … Ensuring students can access course information and library resources from off-campus locations, and from mobile devices, allows any space to become a learning space—bus, beach or bedroom’ (p. 21). As long as a student or lecturer has a networked device, they can access the information they want, when they want. BYOD enhances the convenience of technology. Devices are often small and, for many users, simple and easy to use. They are disruptive


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innovations, leading to the diminution of the campus as the hub for learning and the IT department as the backbone of technology provision in universities. However, Disruptive Innovation is a process and not an event. We may be living and working through the process, leading to campuses with radically scaled-down IT departments but with fast and reliable broadband enabling optimum use of devices owned by students, and with resources and services to support more learning at a distance. Universities can offer all they need to at significantly lower cost, achieving Efficiency Innovation in the process, enabled by the simple and convenient practice of BYOD which disrupts by repositioning the physical university from universal hub to one more node in a student’s plethora of responsibilities and practices. Through its simplicity and convenience, BYOD diminishes the campus as a learning hub, which relocates to the student’s pocket or bag. The campus still has a role but, increasingly, the campus is a retail and social hub, a members’ club for students. Online interactions are routinely monitored, creating the possibility of individually tailored support yet, in the context of personally owned devices used for a plethora of purposes on university networks, personal as well as learning data are potentially exposed. Moreover, personal data are at ongoing risk of being appropriated for commercial and political as well as learning purposes. Higher education is part of a wider social problem in this regard, which is recognised but which can feed contrasting analyses of support or surveillance, and which offers no easy answers. BYOD exemplifies a wider process in higher education. In many countries, costs for higher education are transferred from the state to the individual. Higher education is expressed as a private gain rather than a public good. Technology can aid the privatisation of higher education but this is challenged by technology’s potential to connect and socialise. Technology can mobilise a campaign or create a flash mob just as effectively as it can absolve a university of IT expenditure. Innovation can support an economic or political imperative through the more or less covert gathering and analysis of data, but innovation is also produced through practice, and practice can be less fettered and less subject to external pressure. Innovation is not a question of following a map. Instead, innovation forges a new route, holding the potential to elude market relations as well as conform to them.

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References Afreen, R. (2014). Bring your own device (BYOD) in higher education: Opportunities and challenges. International Journal of Emerging Trends & Technology in Computer Science, 3(1), 233–236. Bass, M., & Movahed, S. H. (2018). To what extent can ‘bring your own device’ be an enabler to widening participation in higher education for the socially disadvantaged? Journal of Perspectives in Applied Academic Practices, 6(1), 3–11. Bates, E.  A., & Kaye, L.  K. (2014). ‘I’d be expecting caviar in lectures’: The impact of the new fee regime on undergraduate students’ expectations of higher education. Higher Education, 67(5), 655–673. Bygstad, B. (2017). Generative innovation: A comparison of lightweight and heavyweight IT. Journal of Information Technology, 32, 180–193. Campbell, W.  G., Fitch, M., German, R.  F., Hulvey, D., McIntosh, K., McPherson, M.  R., et  al. (2013). The wild-card character of “bring your own”: A panel discussion. Educause Review, 48(2), 10–12. Christensen, C. M. (1997). The innovator’s dilemma: When new technologies cause great firms to fail. Harvard: Harvard Business School Press. Christensen, C. M., & Raynor, M. E. (2003). The innovator’s solution: Creating and sustaining successful growth. Boston: Harvard Business School Press. Couldry, N., & Mejias, U. A. (2019). Data colonialism: Rethinking big data’s relation to the contemporary subject. Television & New Media, 20(4), 336–349. DiFilipo, S. (2013). The policy of BYOD: Considerations for higher education. Educause Review, 48(2), 60–61. Duvivier, R. J. (2019). How to ‘future-proof ’ the use of space in universities by integrating new digital technologies. Perspectives: Policy and Practice in Higher Education, 23(1), 18–23. Guilbault, M. (2016). Students as customers in higher education: Reframing the debate. Journal of Marketing for Higher Education, 26(2), 132–142. Hagel, J., Eckenrode, J., & Srinivas, V. (2016). Patterns of disruption: Impact on wholesale banking. Deloitte University Press. Retrieved from https://www2. Hung, H. T. (2017). Clickers in the flipped classroom: Bring your own device (BYOD) to promote student learning. Interactive Learning Environments, 25(8), 983–995.


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Johnson, J. A. (2014). The ethics of big data in higher education. International Review of Information Ethics, 21(21), 3–10. Kobus, M. B. W., Rietveld, P., & Van Ommeren, J. N. (2013). Ownership versus on-campus use of mobile IT devices by university students. Computers and Education, 68, 29–41. Köffer, S., Ortbach, K., Junglas, I., Niehaves, B., & Harris, J. (2015). Innovation through BYOD? Business & Information Systems Engineering, 57(6), 363–375. Kong, S.  C., & Song, Y. (2015). An experience of personalized learning hub initiative embedding BYOD for reflective engagement in higher education. Computers and Education, 88, 227–240. Kwet, M. (2019). Digital colonialism: US empire and the new imperialism in the global south. Race & Class, 60(4), 3–26. Laing, C.  L., & Laing, G.  K. (2016). The student-as-customer metaphor: A deconstruction using Foucauldian constructs. Australasian Accounting, Business and Finance Journal, 10(1), 40–54. Langer-Crame, M., Newman, T., Beetham, H., Killen, C., & Knight, S. (2019). Digital experience insights survey 2019: Findings from students in UK further and higher education. Bristol: JISC. Marginson, S. (2013). The impossibility of capitalist markets in higher education. Journal of Education Policy, 28(3), 353–370. Marginson, S. (2018). Public/private in higher education: A synthesis of economic and political approaches. Studies in Higher Education, 43(2), 322–337. Mihelj, S., Leguina, A., & Downey, J. (2019). Culture is digital: Cultural participation, diversity and the digital divide. New Media & Society, 21(7), 1465–1485. Newman, T., Beetham, H., & Knight, S. (2018). Digital experience insights surve 2018: Findings from students in UK further and higher education. Bristol: JISC. Park, S., & Humphry, J. (2019). Exclusion by design: Intersections of social, digital and data exclusion. Information, Communication & Society, 22(7), 934–953. Pecori, R. (2018). A virtual learning architecture enhanced by fog computing and big data streams. Future Internet, 10(1) Retrieved from https://www. Pohjola, I., & Puusa, A. (2016). Group dynamics and the role of ICT in the life cycle analysis of community of practice-based product development: A case study. Journal of Knowledge Management, 20(3), 465–483. Raghunath, R., Anker, C., & Nortcliffe, A. (2018). Are academics ready for smart learning? British Journal of Educational Technology, 49(1), 182–197.

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Robinson, L., Cotten, S. R., Ono, H., Quan-Haase, A., Mesch, G., Chen, W., et  al. (2015). Digital inequalities and why they matter. Information, Communication and Society, 18(5), 569–582. Shumate, T., & Ketel, M. (2014, March). Bring your own device: Benefits, risks and control techniques. In IEEE Southeastcon 2014 (pp. 1–6). Thatcher, J., O’Sullivan, D., & Mahmoudi, D. (2016). Data colonialism through accumulation by dispossession: New metaphors for daily data. Environment and Planning D: Society and Space, 34(6), 990–1006. Van Deursen, A. J., Helsper, E., Eynon, R., & Van Dijk, J. A. (2017). The compoundness and sequentiality of digital inequality. International Journal of Communication, 11, 452–473. Van Deursen, A. J., & Mossberger, K. (2018). Any thing for anyone? A new digital divide in internet-of-things skills. Policy & Internet, 10(2), 122–140. Van Deursen, A. J., & van Dijk, J. A. (2019). The first-level digital divide shifts from inequalities in physical access to inequalities in material access. New Media and Society, 21(2), 354–375. Walton, G. (2014). Will smart phones and other bring your own devices (BYOD) dominate how academic library services are developed and delivered for the foreseeable future? New Review of Academic Librarianship, 20, 1–3. West, S. M. (2019). Data capitalism: Redefining the logics of surveillance and privacy. Business and Society, 58(1), 20–41. Žižek, S. (2004). The ongoing ‘soft revolution’. Critical Inquiry, 30(2), 292–323. Zuboff, S. (2015). Big other: Surveillance capitalism and the prospects of an information civilization. Journal of Information Technology, 30, 75–89. Zuboff, S. (2019). The age of surveillance capitalism: The fight for a human future at the new frontier of power. New York: PublicAffairs.

7 Reboot the Messenger: A Narrative for Technology Enhanced Learning

Kleenex tissues were first introduced in 1924 as a product for removing cold cream. Customers started using them instead of handkerchiefs when they had a cold. Kleenex repositioned their product by marketing it as, ‘the handkerchiefs you can throw away’ (Lindsay & Hopkins, 2010, p.  283). The disruptive usage occurred from the ground up, and the revised narrative bridged design and innovative practice. This chapter looks at the role of narrative in technology enhanced learning, analysing how narrative can articulate innovation, or restrict it, or align with current practice while also gesturing towards future practice. The chapter argues universities’ strategies and other forms of communication present technology enhanced learning in Sustaining Innovation or Efficiency Innovation terms, supporting and enhancing existing practice. A surface level of hype around innovation is undermined by conservatism, neglecting technology’s transformative potential and, instead, using technology to bolster existing practice. Case studies from a range of industries are cited, to show means by which innovation can be enacted or restrained. Higher education is good at resisting innovation. It is an established market with established leaders. Marginson (2013) argues, ‘elite status © The Author(s) 2020 M. Flavin, Re-imagining Technology Enhanced Learning, Digital Education and Learning,



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competition is largely closed to new entrants. The list of leading American universities has little changed since the First World War, inconceivable in markets for cars, household goods or banking’ (p. 364). Age is correlated with quality in higher education but digital technologies typify modernity. Strategies try to encompass both history and modernity, and the tension between the two may be a contributory factor to the status of technology in higher education as, predominantly, a sustaining innovation, with modernity frequently getting relegated below history, innovation suborned to the familiar. Universities are potentially vulnerable to Disruptive Innovation, which happens when a participant in a market offers something new, typically appealing to those who have previously not had access to the goods or services: Kumar (2006) argues that obsession with traditional rivals can blind incumbents to the threat from disruptive competitors offering lower costs, and Christensen, Grossman, and Hwang (2009) argue, ‘Disruptions are rarely plug-compatible’ (p. xxviii) with the practices of the industries they end up disrupting. However, universities also have the formidable shields of their brands as a notable aspect of their overall narrative. Moreover, universities have mission statements and mission groups, such as the Russell Group in the UK (an association of twenty-­ four, research led universities, formed in 1994). Universities are well-­ placed to resist disruption through the narratives they create but they may ignore activity at their periphery and at their peril. As well as analysing technology enhanced learning strategies and branding as a practice, the chapter also examines broader communication strategies in higher education. Narratives have a wide range of audiences and it is challenging to cater to them all at the same time. The chapter evaluates how a narrative for technology enhanced learning can support or transform an institution. Examples from outside education are presented to show how the articulation of innovations is an important factor in influencing their adoption. Innovative technologies become intelligible through practice but also through narrative. Hayes and Jandrić (2014) argue, ‘the relationships between technology, human beings and society are complex and dialectically intertwined in the language we use to negotiate them … This fabrication that technology is a “neutral” tool to harness and use to make

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improvements de-humanizes our relationships with technology within language’ (p. 198; pp. 202–203). Technology is contextualised through institutions, sectors, and through society and the economy. Technology navigates its contexts through the stories it creates.

Technology Enhanced Learning Strategies Strategy can produce innovation but it can also restrict it. Moreover, there can be a gap between strategy and practice. The music company Steinway was founded in New York City in 1853. It loaned pianos to New York’s thought leaders and to musicians. It built a concert hall in 1866. Through its actions, it became a market leader. From the 1960s, the importing of Japanese pianos threatened Steinway’s market position but its ‘high cultural status embodies long-term resilience’ (Cattani, Dunbar, & Shapira, 2017, p. 31). It withstood disruption by having a strong differentiation strategy, an example and approach applicable to universities in the face of potential Disruptive Innovation. An elite reputation is helpfully self-perpetuating. Strategy can start with the question; what business are we in, and why? (Venkatraman, 1994, p. 83). Technologies can create new possibilities to both underpin existing strategies and to challenge convention by creating new strategies. Venkatraman (1994) argues technologies are, ‘a fundamental source of business scope reconfiguration to redefine the “rules of the game”’ (p. 84). Technology can enable new answers to the fundamental questions of strategy but in so doing it can disrupt. In higher education, technology can enhance and even transform student experiences and outcomes. However, in practice, technology enhanced learning strategies tend to be far less adventurous, supporting existing practices (Flavin & Quintero, 2018). Getting a strategy right is difficult: condensing features of an entire institution into one narrative is challenging. Universities have institutional strategies and many universities have more than one. A large-scale survey in the UK showed 34% of higher education institutions having technology enhanced learning strategies (Jenkins, Walker, & Voce, 2018). A technology needs a narrative if it is to fully succeed. Practice is primary


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but practice needs to be articulated to others, too. Accommodating technology enhanced learning within an overall institutional narrative is challenging because it affects the overall tone and balance of strategies, foregrounding innovation and modernity in the context of a sector in which longevity and continuity are regarded as good qualities and guarantors of quality. The differentiation strategies of established universities stress history and longevity but technology typifies modernity. The narrative of technology is a determinant of its usage and a conservative narrative is likely to lead to conservative practice. According to Samra-Fredericks (2003), ‘a strategy tells you where “you’re going to end up” and like a ship’s rudder, steers the organization to some future destination’ (p. 142), defining outcomes to which the organisation is directed. Sillince, Jarzabkowski, and Shaw (2012) argue, ‘strategy involves persuasion of various audiences that particular actions have a significant and long-term impact on the organization’ (p. 630). Vaara (2010) draws attention to the aura of spiritualty in strategies, when they use terms such as ‘vision’ or ‘mission,’ while Wikhamn and Knights (2013) draw attention to the, ‘preoccupation with control and conquest’ (p. 275) in narratives of innovation, privileging masculinity. The use of the pronoun ‘we’ in strategies implies consensus (Vaara, 2010) but can mask internal contradictions and conflicts. Czerniewicz and Rother (2018), in a study of policy and strategy documents, show low levels of engagement with issues of inequality, indicating that the documents published by universities practise a selective gaze, foregrounding some aspects of an institution and ignoring others. For Hüsig, Hipp, and Dowling (2005), a disruptive innovation can gain a foothold, but to challenge a powerful incumbent it needs to be linked to a strategy. The disruptive innovation’s profitability is hindered until a business model is found (see also Hagel, Eckenrode, & Srinivas, 2016). One way or another, the narrative of technology is an important aspect of its adoption, and the suborning of technology’s potential to a narrative in which a university’s age and continuity are stressed can stunt technology’s growth. Technology can feature in strategies as a sustaining innovation or efficiency innovation but it is challenging for it to feature as a disruptive innovation.

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Higher education has an established product (the degree, or other certification) and an established means of delivering it (the curriculum, focused on and hallmarked by assessment). Christensen, Suarez, and Utterback (1998) argue market risk is less hazardous than technological risk. Technological disruptions are threatening, producing change on the fundamental level of practice. Technological strategies pose more challenges than marketing strategies because they are more closely linked with disruption, given that they involve new products or services, necessitating change. Universities can focus on their market strategy, have a less prominent technology enhanced learning strategy but respond to innovation without taking responsibility for it. Market strategies propose that existing technologies can be used to increase market share and revenue. They are more likely to sustain and enhance than disrupt. Practice and narrative can come into conflict. Flavin and Quintero (2018), in a study of forty-four technology enhanced learning strategies in UK higher education, found strategies to be conservative documents, advocating greater efficiency or incremental improvement but not offering anything different or transformative, despite the potential of technology. The strategies mentioned innovation repeatedly but what they meant by innovation gravitated towards modest, incremental improvement, or more efficient operation: there was, ‘a willingness to adapt on the part of universities but a disinclination to disrupt. Universities can describe themselves in their strategies as innovative yet, in practice, they are often ameliorative, more likely to pursue sustaining or efficiency than disruptive innovation’ (Flavin & Quintero, 2018). The strategies indicated universities mainly adopt a Sustaining Innovation approach to technology enhanced learning, aiming to enhance existing provision incrementally. By stating outcomes in advance, strategies militate against Disruptive Innovation, which is commonly a ground-up practice resisting a top-­ down strategy. Well-honed strategies can cement relationships between institutions and individuals. Reinhardt and Gurtner (2018) argue for embeddedness, ‘the degree to which a product is anchored in the social, market and technological system of the user’ (p. 268). Businesses can achieve embeddedness through technologies by offering use value. Reinhardt and Gurtner (2018) further argue, ‘managers should develop strategies to encourage


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the embedding process’ (p. 280). A student has, typically, a three- or four-­ year relationship with a university. A technology enhanced learning strategy that included alumni would extend the relationship further, perhaps by offering continued access to services once the student’s registration has expired. Marketing departments can also construct relationships with potential students. The curriculum is the backbone of the relationship but the relationship can be embedded through evolving narratives for different stages of the relationship, from pre-registration through to postgraduation. The university website is the first port of call for a prospective student seeking information. As a representation of the university in digital form it has considerable responsibility in conveying a strong first impression. Rose, Clark, Samouel, and Hair (2012) argue, ‘The customer engages in cognitive and affective processing of incoming sensory information from the website, the result of which is the formation of an impression in memory’ (p. 309). Saichaie and Morphew (2014) argue, ‘because the text and images that appear on these sites provide many prospective students with their first and only institutional impressions, the messages websites convey are incredibly important’ (p. 500). The home page is primary, the opening to the narrative. Nguyen and Rosetti (2013) argue, ‘we propose that students be treated as customers who can and must be guided to appreciate the real benefits of the product that they purchase’ (p. 172). The website is important in establishing a narrative. Strategies are secondary, less immediate in their impact, but they remain important because there needs to be consistency between strategy and practice to avoid accusation of mis-selling in monetised systems and to create a coherent, overall institutional narrative. Bingham and Kahl (2013) studied the adoption of the computer in the insurance business in the USA in the period 1945–1975. A combination of a post-war boom in insurance and a shortage of clerical workers created an imperative for a technological solution. The unfamiliar technology, the computer, was made familiar by co-opting the technology to do existing jobs. The disruptive potential of the technology was largely disregarded, at least in narrative terms. Over the period 1947–1958, IBM gained 76% market share in insurance, compared to Remington Rand’s

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10% (Kahl & Grodal, 2016, p. 150). The key was IBM’s discursive strategy, the narrative it created to frame its products: IBM engaged with insurance companies to develop a familiar understanding of the computer that fit with how insurance companies had begun to understand it. In contrast, Remington Rand acted as an authority on the computer and developed an interpretation of the computer that emphasized its novelty. Insurance companies came to view IBM as more accessible, their computers as more familiar and more aligned with their own understanding of the role of the computer in the workplace. (Kahl & Grodal, 2016, p. 155)

IBM found it easier to connect with its customers by not intimidating them. It offered Sustaining Innovation, a bridge between established practice and an enhanced future state, but one that ran along a performance trajectory with which their customers were familiar and comfortable. Sustaining Innovation often seems more attractive than Disruptive Innovation. The former offers better ways of undertaking existing process; the latter requires behavioural change. Both IBM and Remington Rand had a similar product range; both marketed at the same industry conferences. However, IBM’s marketing stressed how the computer would fit-in with, complement and enhance existing processes: ‘IBM engaged in a dialogue with insurance companies in order to make sure that its representation of the computer was aligned with the customers’ evolving understandings. In contrast, Remington Rand tried to construct a new understanding of the computer’ (Kahl & Grodal, 2016, p.  163, emphasis in original). Sustaining Innovation reassures while Disruptive Innovation disturbs. IBM, in its communications with customers, ‘used a mix of declarative and interrogative sentences to engage in dialogue’ (Kahl & Grodal, 2016, p. 157), whereas Remington Rand used far more declarative sentences. By creating horizontal dialogue rather than imposing a vertical power relationship rooted in authority, IBM appealed to more customers. Remington Rand, in its communications, talked of studies it had undertaken. The use of the word ‘studies’ suggested it had specialist knowledge


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to pass on. Unlike IBM, ‘Remington Rand let insurance companies know that it had the answers; no conversation was required’ (p. 161). The IBM/ Remington Rand case study is illuminating because it stresses the importance of the narrative in terms of both content and tone. An effective discursive strategy needs to connect with existing practice, which makes Disruptive Innovation difficult in strategic terms. Christensen (2002) argues, ‘innovators should try to disrupt their competitors, never their customers’ (p. 38). Innovation needs a narrative rooted in existing practice. Familiarity encourages recognition: IBM used a strategy focused on making the new technology seem familiar whereas Remington Rand focused on making the new technology seem novel. Bingham and Kahl (2013) argue, ‘innovations are assessed by applying existing cognitive constructs of a preceding technology, often by invoking analogies’ (p. 14). IBM adopted the label ‘electronic data processing machine’ (p. 21) to describe their computer. According to Kwet (2019), IBM went on to supply the punch-card system used by Apartheid-era South Africa to register the population under a racial system of African, Coloured, Indian and White. Anti-Apartheid activists in the 1970s and 1980s protested against IBM and other corporations for supplying computers for apartheid. Strategies and brands are invariably selective and an organisation’s narrative is a political act, foregrounding values of the organisation’s choice, relegating other practices within the narrative or removing them altogether, and all modulated by the market in which the institution needs to make impact. Innovation is controlled through language and also through design. Heidenreich and Handrich (2015) argue, ‘very high degrees of innovativeness may impose too much change and discontinuity on the individual, endanger the actual status quo, and likely provoke initial resistance … companies need to develop highly innovative products that stay below a critical threshold of change and discontinuity entailed to the adoption’ (p.  894). Successful innovators operate in a zone of proximal development (Chaiklin, 2003; Vygotsky, 1978), offering change but in terms that are intelligible in relation to current practice. Disruptive innovations are uncommon because they disrupt the incremental progress sought by both producers and consumers. Disruptive innovations emerge through ground-up practice, thwarting expectations and steering goods and

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services in new directions. Innovation does not occur in a vacuum but in a context. It needs some form of core intelligibility within that context in order to be adopted. Strategies in higher education vary, depending on the market position of the individual university. They offer enhancement and greater efficiency but rarely if ever disruption and transformation. Universities are geared towards Sustaining Innovation and Efficiency Innovation. They use technologies to consolidate and advance, modestly, existing practice. At the same time, they create a public image through their brand.

Design, Brands and Universities This section looks at how technologies feature in relation to university branding, showing overlaps between universities and commercial organisations in terms of how branding is used. Brands are important to universities. Byrne and Clarke (2020) argue ambitious students want to graduate from a university with a global brand (p. 65). Brands facilitate comprehension and can also be used to justify high prices. Nevzat, Amca, Tanova, and Amca (2016) argue, ‘individuals identify themselves with a well-regarded brand … when a student identifies himself/herself with the university brand, they will develop higher levels of trust towards that brand.’ Nevzat et al. (2016) also argue, ‘where the customer is not in a position to fully understand the many details of what makes the product or service better in terms of quality, they rely on the brand to simplify their choice. In terms of higher education, the universities have an intangible and complex offering which requires a brand,’ adding, ‘The customer commitment towards the brand also brings higher price tolerance’ (pp. 552–553). Brands need to be clear and consistent, conveying top-line messages to stakeholders. Williams Jr. and Omar (2014) argue, ‘In the current period of marketization, successful HEIs cannot maintain long periods of flux without negatively affecting brand equity’ (p. 5). Universities describing themselves as innovative need technology enhanced learning strategies and practices to reflect their brands but many universities lag behind in this respect, publishing conservative strategy documents which are


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conducive to clear and consistent messaging but militate against innovation. Strategies are used to shield brands. They may cite innovation as a symbol of modernity but the core of the brand is often longevity and, in the resolution of the tension between the two, innovation gets reduced to an empty signifier. Du Gay et al. (2013) undertook a case study of the Sony Walkman, which was launched in 1979. The Walkman’s invention was serendipitous; it came from the tape recorder division of Sony, whose existing products were being transferred to the radio division. The tape recorder division created the Walkman from existing practices and developments across Sony. In narrative terms, the Walkman had to be described to its market; American dealerships were unimpressed because the new product did not record. Du Gay et al. (2013) argue, ‘One way of trying to fix its meaning was to use a familiar language to describe or “represent” the device … We map new things in terms of, or by extension or analogy from, things we already know … Every time you trace a meaning back to what preceded it—from “headphone” to “wireless”, for example—it refers back to something which went before it’ (p. 14). The name of the new product implied portability, coaxing innovation out of the market. The Walkman was targeted at teenagers which meant reducing its cost to the extent that it initially lost money, but profits came with high sales and high volume manufacture (p. 132). Hargadon and Douglas (2001) undertook a case study of Thomas Edison’s electric lighting, arguing Edison, ‘strove to wrap his lighting system as tightly as possible in the trappings of the existing system’ (p. 489). Design tempered innovation by offering a product and service which resembled the existing technology of gas lighting: ‘Edison triumphed over the gas industry not by clearly distinguishing his new system from but, rather, by initially cloaking it in the mantle of these established institutions’ (Hargadon & Douglas, 2001, p.  479). They further argue, ‘Edison ensured his users would both recognize the purpose of his innovation at the outset and know without reflection how to use it in their everyday lives’ (p. 498). While Kahl and Grodal (2016) show how language can enable the acceptance of technology through reassuring content and tone, Hargadon and Douglas (2001) argue practical, physical design can achieve the same ends: ‘The role of design is then to arrange

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the concrete details that embody an innovation in ways that construct people’s interpretations of novelty from pieces of what are old and familiar to them … Innovations that distinguish themselves too much from the existing institutions are susceptible to blind spots in the public’s comprehension and acceptance, particularly those innovations viewed as radical or discontinuous’ (p. 493). Innovation needs articulation. It needs to be framed in terms of the job it does for users. If it articulates its innovativeness in overambitious terms it can confuse and alienate its potential users. The story of innovation, and is design, needs to reassure. It needs, in instances, to mask innovation, not foreground it. Norman and Verganti (2014) argue, ‘a completely novel innovation is impossible: All ideas have predecessors and are always based on previous work’ (p. 83). Innovation needs to move into the new from the basis of the familiar. Idris and Whitfield (2014) highlight the importance of corporate visual identity in university branding. They argue heraldic images are particularly effective in conveying an academic brand. As a form of symbolic representation it is both simple and cost-effective: ‘universities are a lucrative global market, and heraldry is freely available without requiring the expensive skills of brand designers. The city coat of arms may suffice when a new university is established or a new visual identity is sought’ (p. 55). Brands can be conveyed symbolically as well as through language or design, conveying images of historical longevity, or civic affiliation, or, if preferred, technological modernity. Some commercial organisations are highly adept at communication, cementing their place in their customers’ daily practices. Doiron (2018) shows how Pepsi, MTV and Burger King designed emojis which were used between their customers in social communications, as well as between the companies and their customers for purchases. Emojis were historically preceded by emoticons, but whereas emoticons arranged punctuation and alphanumerical marks to convey moods and feelings, emojis, which emerged in Japan in the late-1990s, offer a wider spectrum of representation including brands (Ljubešić & Fišer, 2016), and are especially popular for smartphone use (Lu et  al., 2016). Other brands that have created successful bespoke emojis include Bud Light, Starbucks and Dunkin Donuts (Doiron, 2018). Moreover, Coco Cola deployed emojis conveying happy images on the home page of its website (Lu


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et  al., 2016), expressing pleasure, modernity and a youthful image. Emojis can also make it easier to communicate across cultures, comprising, in effect, bridges (Lu et al., 2016), though there is potential for miscommunication: Miller et al. (2016) show how the same emoji could be interpreted as both ‘blissfully happy’ and ‘ready for a fight.’ Branding can take different forms and the use of bespoke emojis has travelled from commerce to higher education. In 2015, the University of Tennessee, Knoxville, introduced its own, bespoke emojis, as did Brown University in 2016. Universities are at least as likely to replicate the practices of large corporations as they are to deviate from them, and are as careful in their attention to branding. A study of mission statements in UK higher education (Flavin, Zhou Chen, & Quintero, 2019) shows a connection, both structurally and linguistically, between the mission statement of a Russell Group university (the University of Southampton (2018)), ‘To change the world for the better,’ and Virgin, a multinational venture capital conglomerate: ‘If we can change business for good, we should also make an effort to change the world for the better’ (Branson, 2018). Russell Group universities in the study tended to have shorter mission statements, whereas newer universities went to greater lengths to promote their brand, mentioning features of their provision such as local community links. Specialist institutions operating in one area of the curriculum were more likely to stress employability. Universities pitch their offering to different sections of the market in a stratified system, foregrounding intrinsic qualities (history or reputation) or extrinsic qualities (employability or community links) which are likely to appeal to students. The brand can move beyond the commercial and into the social. When a brand becomes all-pervasive it can become part of a customer’s identity. Rutter, Roper, and Lettice (2016) argue, ‘Unlike other purchase decisions, a student signing up for a degree is effectively singing up for a lifelong relationship with the university, as they will always have that university’s name linked with their own’ (p. 3097). A student’s relationship with a university begins before enrolment and can end long after graduation. Effective communication is central to the full duration of the relationship. Therefore, questions of brand become even more pronounced because a loss of a university’s reputation affects previous, current and future students. Universities need to articulate technologies in

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familiar terms. Technology design, too, benefits from built-in elements of familiarity. Ritzer and Jurgenson (2010) argue, ‘in earlier production-oriented capitalism the goal was to create a profitable product with the hope that it, in turn, would generate a successful brand. Now, the situation is largely reversed, and it is the brand that comes first, the profitable product will follow … once the brand is institutionalized’ (pp. 29–30). Holmberg and Strannegård (2015), in a case study of a Swedish Business School, show students did not know a lot about the programmes on offer. Instead, ‘they relied on impressions about reputation, brand, and image when they applied to the School’ (p. 187). If a university gets its narrative and brand right it is well placed to succeed in terms of volume of student applications. Its reputation may also shape student satisfaction ratings, influencing how students feel at postgraduation as well as pre-registration. The sell-on value of a qualification in the jobs market is enhanced if the university has a strong brand: Shields (2016) argues, ‘“world-class” institutions are talked into being through global rankings’ (p.  266). League tables establish reputation but in many instances league tables consolidate. They calculate and publicly declare a hierarchy which was evident in any case, established in part through longevity. Tapper and Filippakou (2009) argue, ‘the emergence of the league tables has changed the discourse of higher education’ (p. 57), as universities vie for higher league table placings and foreground, on their websites, the rankings table that gives them the highest position, with league tables themselves having become a competitive market as a number of league tables compete for authoritative status. Amsler and Bolsmann (2012) argue university rankings are a global business: rankings have value, ‘as consumer product ratings—a kind of corporate social capital, akin to that produced by winning sporting tournaments’ (p. 285). They conclude, ‘the practice of ranking universities can alternatively be theorised as a politico-­ ideological technology that serves not the educational needs of students or teachers, but rather the interests of the global elite’ (p. 288). Narrative, brand and league table can work symbiotically to enhance reputation, a practice which isolates Disruptive Innovation because it is a threat to continuity.


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Reputation and status become self-fulfilling. The numerical order of a league table implies mathematical calculation but league tables are, ‘a highly political—and likely contentious—representation of reality … policy instruments and management tools deployed within the sector to transform universities into more strategic corporations for economic purposes’ (Robertson, 2012, p. 241). League tables may have a role in influencing students’ applications but the influence of league tables does not stop there, as, ‘they can provide information to particular stakeholders, who view rankings as a proxy for the return on their investment in the institution, or for rating agencies that wrap rankings into calculations around the financial viability of the institution’ (Robertson, 2012, p. 241). As a means of conveying a narrative, rankings consolidate and enhance strategies and hierarchies within educational systems. A university is unlikely to risk its reputation and league table ranking with a new and untested technology. Hall and Bowles (2016) argue, ‘Universities deliver return on investment through brand, portfolio and product; and with other large corporations they have refocused their strategic planning on market share and capitalisation’ (p. 31), adding, ‘The modern university is curated by a formidable inventory of policies to contain reputational risk or brand disparagement’ (p.  38). Technology is part of the armoury: it has policies and narratives that do not compromise the brand. Disruptive Innovation in technology enhanced learning does not fit within the brand but asserts itself through ground up practice. Flavin and Quintero (2018) show how surface commitments to technological innovation are subverted by, in practice, modest enhancements or improved efficiency. The branding of technology in higher education practises the rhetoric of innovation but the rhetoric is undermined by conservative practice. When there is a gap between what universities preach and what they practice, or when there is incoherence within a strategy, confusion can ensue. Universities can be open to accusations of mis-selling in privatised higher education systems if their public face is inconsistent with their day-to-day practice. A university needs consistency between its message and its practices over a period of time for strategic, ethical and financial reasons. Hayes and Jandrić (2014) argue, ‘Policy documents often circulate claims about improving the quality of learning through technology, but this becomes

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an oppressive discourse if it only perpetuates simplified ideologies’ (p. 198). Technology enhanced learning can be problematic in strategic terms precisely because of its potential to transform. University reputations are consolidated and enhanced by continuity. The narrative and design of technology enhanced learning can limit technology enhanced learning’s potential and virtually ensure that genuine innovation with technologies will only happen outside of the institution’s strategies. Students were not told to use Google and Wikipedia (they were far more likely to be told not to). They just did, regardless of institutional discouragement. Practice is the breeding ground for innovation. The narrative of innovation is often retrospective (Christensen’s methodology is the retrospective case study) and a forward-looking strategy will always struggle to satisfactorily articulate innovation and may stand in its way, articulating the institution’s interests and protecting its brand.

Conclusion The potential for new and emerging markets in higher education worldwide is considerable. Technology can play a central part in providing for those markets but it is not a question of technology imposition from the outside. Instead, the key will be to be attuned to the local contexts of technology practice and to create a new, contextualised narrative for technology enhanced learning. A one-size-fits-all technology enhanced learning strategy will not work. Ringel et al. (2019) define a small number of companies, including Google and Amazon, as ‘serial reinventors’ (p. 7). Long-established universities are the opposite of serial reinventors yet they dominate the higher education sector: Kyriakopoulos, Hughes, and Hughes (2016) argue, ‘Strong reputation resources exhibit inertial properties’ (p. 414). The sector has constantly absorbed innovations (or ignored them), yet wider social contexts have changed. There is a global market for higher education. There is a global need for more higher education. However, established universities will need alternative forms of delivery and curriculum content to engage with these markets and meet their needs, which will


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mean the kind of reinvention to which they are averse. The opportunity for innovators is there. The language of strategies and other documents is ideologically loaded, stressing the positive aspects of technologies yet also stressing how technologies are contained within institutions, largely ignoring the potential of technologies to disrupt. The design of technologies is also frequently organised to cloak innovation. Hayes and Jandrić (2014) note, technology is, ‘a dialectical process of material and linguistic negotiation between competing social forces’ (pp.  194–195), and Hargadon and Douglas (2001) argue, ‘Understanding the role of design in mediating between innovations and institutions requires recognizing the interdependent relationship between the technical and social aspects that constitute an innovation’ (p. 492). Technology offers the new but universities thrive on the familiar: the global elite of universities is a largely unaltered community, closed to new entrants. Hayes and Jandrić (2014) argue, ‘we need to seek ways to input into policy using honest language that accounts for human labour and not simply allow university strategies to emerge as things we only react to … we will then be in a better position to disrupt a flow of text that spreads a key myth about technology’ (p.  202). However, technology often is, in practice, incorporated within a wider narrative in which its modernity and potential for innovation are, paradoxically, a drawback rather than an asset, because of the higher education sector’s correlation between age and quality. It is possible to create a new narrative for technology enhanced learning. Ferreira, Rosado, Lemgruber, and Carvalho (2020) argue, in the context of an increasingly marketised education system in Brazil, that resistance to marketisation entails finding new metaphors to articulate education. Moreover, Thibodeau and Boroditsky (2011) argue, ‘even minimal (one-word) metaphors can significantly shift people’s representations and reasoning about important real-world domains.’ A narrative could work hand-in-hand with innovation or even, unusually, precede it, by creating new metaphors for education, within which technology would occupy a significant role, postulating a different kind of higher education. Technology can be a transformer in preference to being an

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enhancer or a cost saver, a source of disruption not continuity, an attractive proposition for universities excluded from the global elite. Disruptive Innovation in higher education is problematic because it foregrounds the new: new technologies, new practices and, potentially, new institutions. As long as the correlation between age and quality endures (and there is no sign of it waning), Disruptive Innovation is the annoyance at the margins. It comprises the technologies and practices that subvert orthodox academic practice but may actually benefit higher education if universities are willing to engage. It is also the threat of new providers with radically new business models, including the potential to disrupt the higher education sector as other sectors have been disrupted. The perpetuation of similar technology enhanced learning narratives helps sustain higher education in its existing form but it also leaves the sector vulnerable to new, potentially disruptive narratives. Carroll (2015) argues, in many instances, ‘authenticity carries great appeal only in advanced market economies, often only in the West, and often primarily among affluent or education customers’ (p.  4). The correlation of age with quality is context specific. Other contexts may be better placed to reimagine technology enhanced learning and its role in higher education. Strategies are problematic from a Disruptive Innovation perspective because they are customarily top-down. Disruptive Innovation is anti-­ strategy because it is a ground-up process, thriving on users and the purposes they create through practice. Strategies with fixed outcomes are the antithesis to Disruptive Innovation but broad, less restrictive strategies enable flexibility of means, if not of outcomes. The more detailed a strategy, with pre-ordained targets, the more restrictive it is. It may be easier to align Disruptive Innovation with a university’s mission statement than its strategies, if only because the structurally synoptic nature of mission statements and their thematic breadth creates space for innovative practice. However, mission statements can be characterised by vacuity: Sauntson and Morrish (2011), in a UK study, argue mission statements are, ‘designed to propound a managerialist institutional narrative designed to forestall challenge, precisely because it is impossible to contest the positive images they invoke. In this way, universities construct themselves, their students and graduates in the desired corporate image’ (p.  83). Ultimately, it will always be difficult to align Disruptive


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Innovation with mission statements and strategies because, by its nature, Disruptive Innovation is the thing that happens despite institutional edict, not because of it. Auvinen et al. (2019) argue, ‘strategising always involves fictional narration’ (p. 205) and that, ‘Because strategy is fundamentally future oriented, it inescapably contains fictive elements related to forthcoming events’ (p. 221). Perhaps universities should promote the fictive aspects of strategy, using metaphor to imagine a different kind of university, liberating the conception of technology enhanced learning. Sajasalo, Auvinen, Takala, Järvenpää, and Sintonen (2016) argue metaphors can, ‘carry more powerful messages regarding the aspired future than numbers … making sense of something that is not real in the present requires imagination’ (pp. 320–321). At present, imagination is constrained by a conception of higher education in which longevity comprises quality. Technology can threaten this fundamental conception but technology tends to get suborned to a narrative in which it smooths process and enhances experience, offering more of the same in non-threatening terms. A key point to recognise in the creation of new narratives for technology enhanced learning is the current mismatch between practice and proclamation: students and lecturers make use of disruptive innovations (Henderson, Selwyn, Finger, & Aston, 2015; Littlejohn, Beetham, & McGill, 2012), but universities supply a set of tools and advocate practices which are misaligned with what users actually do. There is Disruptive Innovation, evident, for example, in the use of Google and Wikipedia in preference to institutional resources, but the rhetoric of university strategies emphasises Sustaining Innovation. A new, authentic narrative for technology enhanced learning can begin with a recognition and analysis of actual practice, and imagine a future from there. In creating narratives for technology enhanced learning, universities need to be aware of the trade-off between conformity and competitive differentiation (Zhao, Fisher, Lounsbury, & Miller, 2017). Universities in specific mission groups have mission statements and strategies that broadly resemble each other (Flavin et  al., 2019; Flavin & Quintero, 2018). They have no incentive to innovate as long as the existing higher education sector serves their interests because it enables them to attract and retain students. Their reputation, their brand, is effective, and their

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place in the system seemingly secure. Kahl and Grodal’s (2016) case study of IBM versus Remington Rand in the domestic insurance market in post-World War Two America is instructive for stressing the importance of an effective narrative: ‘To gain a competitive advantage, firms must use discursive strategies that effectively bridge their own interpretations of new technologies with those of their customers’ (p. 163). A new narrative for technology enhanced learning needs to start from existing practice, the technologies we use and what we use them for. A new narrative for technology enhanced learning also needs to work with its stakeholders, not dictate to them. The case study of IBM and Remington Rand also shows how the existing language of technology is better suited to Sustaining Innovation than Disruptive Innovation. Audiences are reassured by the familiar. Disruptive Innovation begins as an act of practice rather than as a statement of intent. The narrative customarily follows innovation; it does not conjure innovation into existence. This chapter has examined narratives for technology enhanced learning. Strategies for technology enhanced learning have been shown to be conservative. Innovation is less likely to happen by decree than by practice, with users creating purposes for technologies through their usage of them. There is a potential for radically new narratives (Ferreira et  al., 2020), but as these would challenge entrenched orthodoxies they are an uphill task, requiring the imaginative postulation of a different type of higher education. The next, and final, chapter revisits Disruptive Innovation theory and suggests what the disruptive university might look like.

References Amsler, S. S., & Bolsmann, C. (2012). University ranking as social exclusion. British Journal of Sociology of Education, 33(2), 283–301. Auvinen, T., Sajasalo, P., Sintonen, T., Pekkala, K., Takala, T., & Luoma-aho, V. (2019). Evolution of strategy narration and leadership work in the digital era. Leadership, 15(2), 205–225.


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Bingham, C.  B., & Kahl, S.  J. (2013). The process of schema emergence: Assimilation, deconstruction, unitization and the plurality of analogies. Academy of Management Journal, 56(1), 14–34. Branson, R. (2018). Retrieved from Byrne, E., & Clarke, C. (2020). The university challenge: Changing universities in a changing world. Harlow: Pearson. Carroll, G.  R. (2015). Authenticity: Attribution, value, and meaning. In Emerging trends in the social and behavioral sciences: An interdisciplinary, searchable, and linkable resource (pp. 1–13). Wiley. Cattani, G., Dunbar, R. L., & Shapira, Z. (2017). How commitment to craftsmanship leads to unique value: Steinway & Sons’ differentiation strategy. Strategy Science, 2(1), 13–38. Chaiklin, S. (2003). The zone of proximal development in Vygotsky’s analysis of learning and instruction. In A. Kozulin, B. Gindis, V. Ageyev, & S. Miller (Eds.), Vygotsky’s educational theory in cultural context (pp. 39–64). Cambridge: Cambridge University Press. Christensen, C.  M. (2002). The rules of innovation. Technology Review, 105(5), 33–38. Christensen, C. M., Grossman, J., & Hwang, J. (2009). The innovator’s prescription: A disruptive solution for health care. New York: McGraw-Hill. Christensen, C. M., Suarez, F. F., & Utterback, J. M. (1998). Strategies for survival in fast-changing industries. Management Science, 44(12), S207–S220. Czerniewicz, L., & Rother, K. (2018). Institutional educational technology policy and strategy documents: An inequality gaze. Research in Comparative and International Education, 13(1), 27–45. Doiron, J.  G. (2018). Emojis: Visual communication in higher education. PUPIL: International Journal of Teaching, Education and Learning, 2(2) Retrieved from view/1370. Du Gay, P., Hall, S., Janes, L., Madsen, A. K., Mackay, H., & Negus, K. (2013). Doing cultural studies: The story of the Sony Walkman (2nd ed.). London: Sage. Ferreira, G.  M. D.  S., Rosado, L.  A. D.  S., Lemgruber, M.  S., & Carvalho, J. D. S. (2020). Metaphors we’re colonised by? The case of data-driven educational technologies in Brazil. Learning, Media and Technology, 45(1), 46–60.

7  Reboot the Messenger: A Narrative for Technology Enhanced… 


Flavin, M., & Quintero, V. (2018). UK higher education institutions technology enhanced learning strategies from the perspective of disruptive innovation. Research in Learning Technology, 26. Retrieved from https://journal.alt. Flavin, M., Zhou Chen, T., & Quintero, V. (2019). Size matters: An analysis of UK higher education institution mission statements. Journal of Higher Education Policy and Management, 1–15. Retrieved from Hagel, J., Eckenrode, J., & Srinivas, V. (2016). Patterns of disruption: Impact on wholesale banking. Deloitte University Press. Retrieved from https://www2. Hall, R., & Bowles, K. (2016). Re-engineering higher education: The subsumption of academic labour and the exploitation of anxiety. Workplace: A Journal for Academic Labor, 28, 30–47. Hargadon, A. B., & Douglas, Y. (2001). When innovations meet institutions: Edison and the design of the electric light. Administrative Science Quarterly, 46(3), 476–501. Hayes, S., & Jandrić, P. (2014). Who is really in charge of contemporary education? People and technologies in, against and beyond the neoliberal university. Open Review of Educational Research, 1(1), 193–210. Heidenreich, S., & Handrich, M. (2015). What about passive innovation resistance? Investigating adoption-related behavior from a resistance perspective. Journal of Product Innovation Management, 32(6), 878–903. Henderson, M., Selwyn, N., Finger, G., & Aston, R. (2015). Students’ everyday engagement with digital technology in university: Exploring patterns of use and ‘usefulness’. Journal of Higher Education Policy and Management, 37(3), 308–319. Holmberg, I., & Strannegård, L. (2015). Students’ self-branding in a Swedish business school. International Studies of Management & Organization, 45(2), 180–192. Hüsig, S., Hipp, C., & Dowling, M. (2005). Analysing disruptive potential: The case of wireless local area network and mobile communications network companies. R&D Management, 35(1), 17–35. Idris, M. Z., & Whitfield, T. A. (2014). Swayed by the logo and name: Does university branding work? Journal of Marketing for Higher Education, 24(1), 41–58.


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Jenkins, M., Walker, R., & Voce, J. (2018). Building institutional cultures of innovation in technology enhanced learning: UCISA findings on current challenges and developments in UK higher education. In 35th international conference of innovation, practice and research in the use of educational technologies in tertiary education (pp. 412–417). Retrieved from Final.pdf#page=415 Kahl, S. J., & Grodal, S. (2016). Discursive strategies and radical technological change: Multilevel discourse analysis of the early computer (1947–1958). Strategic Management Journal, 37, 149–166. Kumar, N. (2006). Strategies to fight low-cost rivals. Harvard Business Review, 84, 104–112. Kwet, M. (2019). Digital colonialism: US empire and the new imperialism in the global south. Race & Class, 60(4), 3–26. Kyriakopoulos, K., Hughes, M., & Hughes, P. (2016). The role of marketing resources in radical innovation activity: Antecedents and payoffs. Journal of Product Innovation Management, 33(4), 398–417. Lindsay, J., & Hopkins, M. (2010). From experience: Disruptive innovation and the need for disruptive intellectual asset strategy. Journal of Product Innovation Management, 27(2), 283–290. Littlejohn, A., Beetham, H., & McGill, L. (2012). Learning at the digital frontier: A review of digital literacies in theory and practice. Journal of Computer Assisted Learning, 28(6), 547–556. Ljubešić, N., & Fišer, D. (2016). A global analysis of emoji usage. In Proceedings of the 10th web as corpus workshop, August, 82–89. Lu, X., Ai, W., Liu, X., Li, Q., Wang, N., Huang, G., et al. (2016). Learning from the ubiquitous language: An empirical analysis of emoji usage of smartphone users. In Proceedings of the 2016 ACM international joint conference on pervasive and ubiquitous computing, September 2016, 770–780. Marginson, S. (2013). The impossibility of capitalist markets in higher education. Journal of Education Policy, 28(3), 353–370. Miller, H. J., Thebault-Spieker, J., Chang, S., Johnson, I., Terveen, L., & Hecht, B. (2016). “Blissfully happy” or “ready to fight”: Varying interpretations of emoji. In Tenth international AAAI conference on web and social media, March. Retrieved from paper/viewPaper/13167 Nevzat, R., Amca, Y., Tanova, C., & Amca, H. (2016). Role of social media community in strengthening trust and loyalty for a university. Computers in Human Behavior, 65, 550–559.

7  Reboot the Messenger: A Narrative for Technology Enhanced… 


Nguyen, A., & Rosetti, J. (2013). Overcoming potential negative consequences of customer orientation in higher education: Closing the ideological gap. Journal of Marketing for Higher Education, 23(2), 155–174. Norman, D.  A., & Verganti, R. (2014). Incremental and radical innovation: Design research vs. technology and meaning change. Design Issues, 30(1), 78–96. Reinhardt, R., & Gurtner, S. (2018). The overlooked role of embeddedness in disruptive innovation theory. Technological Forecasting and Social Change, 132, 268–283. Ringel, M., Grassl, F., Baeza, R., Kennedy, D., Spira, M., & Manly, J. (2019). The most innovative companies 2019: The rise of AI, platforms, and ecosystems. Boston: Boston Consultancy Group. Retrieved from com/Images/BCG-Most-Innovative-Companies-Mar-2019-R2_ tcm9-215836.pdf. Ritzer, G., & Jurgenson, N. (2010). Production, consumption, prosumption: The nature of capitalism in the age of the digital ‘prosumer’. Journal of Consumer Culture, 10(1), 13–36. Robertson, S. L. (2012). World-class higher education (for whom?). Prospects, 42(3), 237–245. Rose, S., Clark, M., Samouel, P., & Hair, N. (2012). Online customer experience in e-retailing: An empirical model of antecedents and outcomes. Journal of Retailing, 88(2), 308–322. Rutter, R., Roper, S., & Lettice, F. (2016). Social media interaction, the university brand and recruitment performance. Journal of Business Research, 69, 3096–3104. Saichaie, K., & Morphew, C. C. (2014). What college and university websites reveal about the purposes of higher education. The Journal of Higher Education, 85(4), 499–530. Sajasalo, P., Auvinen, T., Takala, T., Järvenpää, M., & Sintonen, T. (2016). Strategy implementation as fantasising–becoming the leading bank. Accounting and Business Research, 46(3), 303–325. Samra-Fredericks, D. (2003). Strategizing as lived experience and strategists’ everyday efforts to shape strategic direction. Journal of Management Studies, 40(1), 141–174. Sauntson, H., & Morrish, L. (2011). Vision, values and international excellence: The ‘products’ that university mission statements sell to students. In M.  Molesworth et  al. (Eds.), The marketisation of higher education and the student as consumer (pp. 73–85). Abingdon: Routledge.


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Shields, R. (2016). Following the leader? Network models of “world-class” universities on twitter. Higher Education, 71(2), 253–268. Sillince, J., Jarzabkowski, P., & Shaw, D. (2012). Shaping strategic action through the rhetorical construction and exploitation of ambiguity. Organization Science, 23(3), 630–650. Tapper, T., & Filippakou, O. (2009). The world-class league tables and the sustaining of international reputations in higher education. Journal of Higher Education Policy and Management, 31(1), 55–66. Thibodeau, P. H., & Boroditsky, L. (2011). Metaphors we think with: The role of metaphor in reasoning. PLoS One, 6(2), e16782. Retrieved from https:// University of Southampton. (2018). Simply better: The university strategy. Retrieved from Vaara, E. (2010). Taking the linguistic turn seriously: Strategy as a multifaceted and interdiscursive phenomenon. In A. C. B. Joel & J. Lampel (Eds.), The globalization of strategy research (pp.  29–50). Bingley: Emerald Group Publishing Limited. Venkatraman, N. (1994). IT-enabled business transformation: From automation to business scope redefinition. Sloan Management Review, 35, 73–87. Vygotsky, L. S. (1978). Mind in society. In M. Cole, V. John-Steiner, S. Scribner, & E.  Souberman (Eds.), The development of higher psychological processes. London: Harvard University Press. Wikhamn, B. R., & Knights, D. (2013). Open innovation, gender and the infiltration of masculine discourses. International Journal of Gender and Entrepreneurship, 5(3), 275–297. Williams, R.  L., Jr., & Omar, M. (2014). How branding process activities impact brand equity within higher education institutions. Journal of Marketing for Higher Education, 24(1), 1–10. Zhao, E. Y., Fisher, G., Lounsbury, M., & Miller, D. (2017). Optimal distinctiveness: Broadening the interface between institutional theory and strategic management. Strategic Management Journal, 38, 93–113.

8 Conclusion: Switch It Off, Switch It on Again—Reimagining Technology-­ Enhanced Learning in Higher Education

There has been no digital revolution in higher education. Instead, technology has made learning and teaching more efficient and has supported incremental enhancement within a consistent and enduring pedagogy. However, technology retains the potential to be transformative and it is surprising that higher education has not been transformed by technology, as many other goods and services have been. This book has shown that virtual learning environments exemplify Sustaining Innovation and Efficiency Innovation. It has also shown how Wikipedia is a successful disruptive innovation in higher education, and challenges claims that social media technologies are disruptive. The book has also examined the consequences of privatising and monetising higher education, recognising the complexity of changing the economics of higher education through an examination of Bring Your Own Device. In addition, the book has shown the importance of creating an effective narrative for technology-enhanced learning. The digital world has not created utopia. It has not made life easier universally, and in some respects technology has amplified inequalities. iPhones are premier products, but the working conditions of the people who make the iPhone can be deplorable (Clarke & Boersma, 2017), © The Author(s) 2020 M. Flavin, Re-imagining Technology Enhanced Learning, Digital Education and Learning,



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determined by the imperatives of reducing costs and increasing efficiencies (Pun & Chan, 2013; Srnicek, 2016). As far as higher education goes, technologies are used to support and sustain existing pedagogy and practices. Embedded hierarchies remain untroubled in higher education. The digital world has created enhanced surveillance (Zuboff, 2019) as students’ digital interactions with their universities are monitored constantly, but technology has not revolutionised higher education in terms of how universities organise the curriculum and how students experience it. Digital technologies have failed to live up to their disruptive potential. The solution to technology-enhanced learning’s inertia, offered by this chapter, is a standard prescription: switch it off, switch it on again. The chapter aims to reimagine technology-enhanced learning in higher education and, to that end, explores what disruptive universities might look like. A disruptive university is proposed in this chapter, shaped by existing and increasingly privatised education systems. An alternative disruptive university is also considered.

Higher Education: The State of Play Higher education in countries such as the United Kingdom is hierarchical and stratified, but as higher education has moved from a state to a privatised system it has become more like a market, with paying customers pursuing value. There is an opportunity for disruptive providers who can analyse and define the job that students want higher education to do and offer provision to suit students’ needs. There is a mismatch in higher education between institutional provision, strategy and rhetoric on the one hand; and actual practice on the other. The contradiction between the two can lead to fundamental changes in learning and teaching in higher education. Rutter, Roper, and Lettice (2016) argue, of universities, ‘the language of the market frames and describes the sector’ (p. 3096), but this is inevitable in the context of the privatisation of higher education. As market practices are brought in, market terminology follows. Established universities have many advantages. They are well-­ networked. Their qualifications are sanctioned by official bodies. They

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have access to outstanding resources for learning and teaching. They have resources and they have brands. Universities are better placed than many industries to survive threats from disruptive entrants. However, they are not immune to change and they are not unassailable, and many powerful incumbents in other fields have been disrupted. Traditional universities pursue traditional models because traditional models are successful. However, by limiting their development to Sustaining Innovation and Efficiency Innovation, universities are leaving themselves vulnerable to a disruptor. Universities have used technologies to do what they have always done a little better and little more efficiently than before, disregarding the potential of technology to transform. Technology has altered how we engage with education (accessing material online and at any time rather than via a library with closing hours), but technology has not radically altered the kind of qualifications we produce, nor has it radically affected how higher education is experienced. A clear majority of students still physically attend an institution. Technologies need to be appropriate to their contexts and this may be one of the reasons why higher education institutions are geared towards Sustaining Innovation and Efficiency Innovation. Higher education providers look for technologies that enable them to do what they have been doing with greater efficiency, and with improvement along a performance trajectory with which they are familiar. Nair and Ahlstrom (2003) argue, ‘managers making technology investment decisions need to more completely understand the competing technologies, and the institutional and ecological dynamics surrounding the technologies’ (p.  360). Potential innovators, too, need to understand both the technologies they deploy and the contexts in which those technologies are deployed. If their understanding is better than the incumbents’ understanding, they can make inroads. Established universities have a vested interest in not staking their reputations because their reputations serve them well. Universities are structurally and strategically positioned against Disruptive Innovation. However, there is scope for a disruptive innovator to gain a foothold. Disruptive Innovation argues incumbents often do not notice the new entrant as a serious competitor until the momentum is already with the disruptor (Christensen, 1997; Sood & Tellis, 2011). At the same time,


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and through repeated sustaining innovations, the incumbent arrives at product overshoot (Christensen, 1997), providing goods and services its users do not need. Universities provide a plethora of non-curricular goods and services, from well-appointed cafes to opportunities to build soft skills through to careers departments and other small units within universities. A disruptive provider could argue these add-ons are not necessary and that pared-down and substantially cheaper provision can find a viable market. It can be argued that we do not want to change long-standing and generally efficient practices in higher education and therefore we will not; a study in the UK showed 88% of students rating digital provision at their HEI as good or higher (Newman, Beetham, & Knight, 2018). However, doing nothing ignores the fact that wider contexts do change, recognised over eighty years ago in The Saber-Toothed Curriculum (Peddiwell, 1939). Curricula cannot remain entirely static because economies and societies do not remain static. Technology can change the content we produce and how we produce it, technology can be better aligned with our changing economies and societies and it has clear, disruptive potential. Disruptive technologies tend to be cheap but disruption is not solely a matter of price competition. It is also centred on the convenience and ease of use of a technology and its ability to get jobs done, jobs that the buyer needs to get done. Students need affordable higher education of good quality. Technology can, in theory, provide it. The disruptive innovation of the higher education sector is therefore possible. However, it has not happened. It may be present at the periphery but it is not moving into the mainstream to an extent that threatens incumbent providers. Technologies can enable transformation in the production, distribution and consumption of higher education, but embedded pedagogies create expectation on students’ part and anything that deviates from the norm, that does not belong in the ecosystem, runs the risk of not being regarded as credible or proper higher education. Private, commercial providers in a range of sectors can often be innovative to help ensure their survival: Holtham and Courtney (2005) note, ‘For much of the 1990s, eLearning development was focused in the for-­ profit training sector’ (p. 7). Established higher education providers will

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not undergo fundamental change if they have no motive for doing so. As Rosenbloom and Christensen (1994) argue, ‘The incumbent’s disadvantage, hence, seems to be associated with an inability to change strategies, not technologies’ (p. 655). Universities will keep doing what they have always done while it is in their interests to do so. Esposito (2013) undertook research at an Italian university, arguing technology usage, ‘underlies a functional and efficiency-driven approach to digital tools and environments.’ It makes sense to use technologies to achieve efficiencies. It makes less sense to limit technologies in this way, especially if their usage can enable more people to access higher education and be supported through it. Markides and Sosa (2013) argue, ‘winning the market is not a matter of luck or good intentions. It is the by-product of an innovative business model’ (p. 327), yet many universities’ strategies seem inimical, in practice, to substantial innovation. New providers need to establish reputation but this is challenging without replicating the methods of established providers, including having a campus as a social as well as learning hub. Were emerging providers to take this route they would lose a core feature of their price advantage and essentially replicate the incumbents, without the advantages of age and reputation. There is an impasse and incumbents are powerful: as Wessel and Christensen (2012) note, in a USA context, ‘Ivy league universities are still better positioned than online institutions to confer elite status on aspiring high school seniors.’ The elite has remained unchanged in higher education, a claim it would be difficult to sustain in many other areas of practice (Marginson, 2013). However, technology retains the potential to offer a high-quality and low-cost higher education.

Designing Disruptive Innovation Technologies are constantly evolving, which makes it difficult to design technology-enhanced learning. However, Hargadon and Douglas (2001) argue for the importance of design, ‘the emergent arrangement of concrete details that embodies a new idea’ (p. 476). From this perspective, design can facilitate Disruptive Innovation, encouraging innovation by creating new possibilities. Whereas Christensen (1997) sees innovation as


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emerging from ground up practice, Hargadon and Douglas (2001) argue it can be created: design, ‘allows entrepreneurs to exploit the established institutions while simultaneously retaining the flexibility to displace them … entrepreneurs must locate their ideas within the set of existing understandings and actions that constitute the institutional environment yet set their innovations apart from what already exists’ (p.  476). Innovation should start from the known in order not to alienate or intimidate, but design can catalyse innovation. The new product, the innovation, needs to significantly resemble an existing product but it also needs the potential to move beyond the existing product’s capabilities. Similarly, a disruptor in higher education will need to start by offering goods and services resembling those already current and established in the sector, but offer something new, too. Hargadon and Douglas (2001) conclude, ‘prospective innovators must carefully choose designs that couch some features in the familiar, present others as new, and keep still others hidden from view’ (p.  480). The proposition confronts innovators with challenges, including the ability to imagine forms of usage that go beyond existing practices. However, the argument also implies innovation can be built-in. While this differs notably from Christensen (1997), it opens a framework for understanding why some goods and services prove to be disruptive and others do not. While Kahl and Grodal (2016) write about a narrative for new products that succeeds because it begins in the familiar, Hargadon and Douglas (2001) write about innovative design beginning with the familiar. Applying the argument to higher education, disruption does not need to be obviously disruptive initially. It can appear familiar but use technology to open up new practices and new possibilities. The innovations with the greatest potential to disrupt can be seen as skeuomorphs, which retain features of earlier iterations of the same or similar goods and services. One example of a skeuomorph is the icon of the dustbin on computer screens (Hargadon & Douglas, 2001), which represented, figuratively, a use for a new application, and drew out a specific practice on the part of the user. Skeuomorphic design can enable and support technology adoption: Ellis and Marshall (2019) argue, ‘skeuomorphs allow users to leverage their existing knowledge of physical artifacts to interact with digital artifacts’. Skeuomorphs are conducive to

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innovation because they enable interaction without training. They allow an encounter with a technology to feel intuitive, though the usage is directed by the design. They enable disruption by bridging present and future practice. Technologies can have entry-level functions that appeal to users but that do not circumscribe the range of possible usage. Design, therefore, has to enable pliability and repurposing in order to be disruptive: ‘our understandings and patterns of use are changing, and those systems that retain the flexibility to change with us will persist. Ultimately, these will be the innovations we look back on as radical and discontinuous’ (Hargadon & Douglas, 2001, p. 49). The Honda motorcycle in the USA, especially Honda’s Supercub bike, with its walk-through design more reminiscent of a woman’s bicycle, and its marketing slogan (‘You meet the nicest people on a Honda’) nullified the less savoury, Hell’s Angels image of motorcycles, and created a new market around socialising (Christensen, 1997; Pascale, 1984). It is a prime example of a design that looks familiar but enables new and innovative practices. A disruptor in higher education could offer the established product of undergraduate and postgraduate qualifications but could make them available to new markets. It need not have entry requirements. It need not have peripheral services. It need not have premises. It can decide upon its curricular offering and make it available at a pared-down cost without compromising on core questions of academic quality. It can aim for Ryanair’s proposition of 80–90% reduction in costs to the customer (Kumar, 2006). Skeuomorphic design can make the goods and services familiar yet at the same time enable new forms of practice by extending the higher education market, practising both low end and new market disruption. Ferreira, Rosado, Lemgruber, and Carvalho (2020) seek new metaphors for higher education. They argue against perceived, often amorphous problems in higher education, problems for which commercial ed-tech providers offer solutions. However, the new metaphors for technology-­enhanced learning in higher education are, as yet, unknown. Perhaps new metaphors can be produced, drawing, in this study, on the work of Hargadon and Douglas (2001) and Kahl and Grodal (2016). If new metaphors can be constructed, we can begin to imagine different,


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even transformative forms of academic practice, using technology to make higher education more open and accessible. If new metaphors are absent, and in the context of increasingly privatised and monetised systems, technology-enhanced learning will continue to be suborned to discourses of efficiency while it continues to make false promises of transformation.

The Disruptive University What would the Disruptive University look like? Would it have employer input from the outset? If employability was built-in to the curriculum in the design stage there would be no need for a separate careers service, a measure offering an immediate and substantial cost saving. The Disruptive University could argue that students can find gainful, graduate employment by themselves, using jobs websites. A relationship between a student and a university is high-risk because of how much depends on it, most notably the student’s future earnings. A curriculum that embraced employability would be working consciously to offset the risk. In a large-­ scale survey in the UK, 70% of higher education students said digital skills were important for their chosen career but only 42% said their course prepared them for the digital workplace (Langer-Crame, Newman, Beetham, Killen, & Knight, 2019). A disruptive provider, entirely online, could develop students’ IT skills, whether explicitly as part of the curriculum or implicitly through the practice of studying online. In acquiring these skills, students could make themselves more employable (Jones, 2014). The Disruptive University, as an online provider, would enhance employability by putting digital skills at its core. Markides and Sosa (2013) identify a problem in markets, namely that, ‘most entrants imitate the incumbents’ (p. 327), but what would happen if a higher education provider came along with a radically different model, centring on the Ryanair proposition (Kumar, 2006)? Hopp et al. (2018) argue, ‘rarely is the technology inherently disruptive, but rather the business model (enabled by the new technologies) has a disruptive impact on incumbents’ value creation and market position’ (p.  446), and Hagel, Eckenrode, and Srinivas (2016) argue, ‘technology is often a significant

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enabler of disruption, but unless it is coupled with a powerful business value proposition, it is unlikely to have a disruptive impact’ (p. 3). The Disruptive University would only need a small market share to survive and to build. Powerful incumbents would ignore it, giving the new provider more opportunities for market growth. The Disruptive University would not need high enrolments at first, just enough to claim a foothold, a modicum of brand recognition and effective validation through evidence of enhanced employability, and it could build from its foothold along Sustaining Innovation lines. Zeide and Nissenbaum (2018) argue, ‘Despite rhetoric extolling education as a means to promote democracy, equality, and self-actualization, most online education providers offer educational experiences focused on the economic value of acquiring marketable skills and credentials’ (p. 296), so perhaps the Disruptive University would risk being a sustaining innovation, offering an employability-focused add-on to existing provision. However, the Disruptive University could offer socioeconomic as well as economic value by using Efficiency Innovation savings to drive down fees, encouraging wider participation. The Disruptive University would not have to be an educational ghetto for the economically disadvantaged. Instead, it could provide increased access to higher education and provide clearly enhanced employability, too. If the Disruptive University dedicated its marketing budget as much to employers as to prospective students, it could make both sides of the employment contract aware of its value proposition and gain a foothold from which it could progress incrementally. Disruptors need credibility and reputation, which are best purchased within the existing higher education ecosystem. The Disruptive University’s core products should continue to be certificates, diplomas and degrees. The Disruptive University would also need to establish reputation outside the immediate ecosystem of the higher education sector by having credibility with employers. This might lead to a narrow curriculum focused solely on employability but the Disruptive University would stand a fair chance of success if it was priced significantly below the mainstream sector. Moreover, the Disruptive University could argue there is no necessary antagonism between education for employability and a satisfying educational experience. It would just be a question of the


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Disruptive University building a good narrative, of getting the message right, foregrounding quality as well as relevance. The Disruptive University could pose a challenge to existing scholarship practices. Lecturers expect research time to be built into their contracts. Lecturers at the Disruptive University will be expected to conduct research in their own time and at their own expense. Byrne and Clarke (2020) note, ‘The massive and economically important strength of the UK’s research … is concentrated in about a third of our universities. If no research were to take place in the other two thirds, the overall damage would be quite limited’ (p. 17), the authors being a Russell Group university principal and a former Secretary of State for Education in the UK. According to Salter (2005), the financial community has a, ‘You eat what you kill’ system of reward (p. 19), and Metcalf and Moss (2019) argue, ‘In Silicon Valley, a common motto is “fail fast, fail often.” The industry rewards breaking rules and ignoring guardrails’ (p.  468). The Disruptive University can function similarly in the higher education community, rewarding its lecturers recruited on gig economy principles by student outcomes and student satisfaction, ratified in the former case by exam boards; in the latter by marketing departments. Acs and Audretsch (1988) argue innovation is negatively correlated with unionisation, so the Disruptive University need not recognise trade unions. The positive aspects of gig economy lecturers’ contracts can be emphasised because some academics may appreciate the flexibility. Already, some lecturers undertake sessional work in more than one institution (Richardson, Wardale, & Lord, 2019), and around a third of UK academic employees are on fixed-term contracts (Loveday, 2018). The Disruptive University will build upon existing developments, being more of a Sustaining Innovation than a Disruptive Innovation it its approach to labour relations, but will differ by passing on the cost savings to students. Some employers have online, just-in-time training, enabling employees to retain currency in their practice. Why can’t the Disruptive University do the same with its academics, support and develop them as teachers but let them manage their own careers as researchers? By these means, academic practice can be re-engineered to produce surplus value and therefore profit (Hall & Bowles, 2016, p. 34).

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The Disruptive University will have low or no barriers to student entry. The harvesting of data will enable students to be constantly aware of their progress and will tailor, through curriculum design, learning materials to student need, perhaps by foregrounding a particular e-book, or article, or video resource. E-books not already owned by the university can be sold to students, with a link directly from the Disruptive University’s pages to the seller’s pages, with the Disruptive University taking a small percentage of the transaction. The Disruptive University’s library can be excluded from the process, producing further cost savings. Technology is very useful for gaining knowledge of customers. Amazon began as an online bookshop in 1994 but by 2001 was allocating a third of its budget to technological developments (Kimble & Bourdon, 2013). An early online bookseller, Book Stacks Unlimited, had opened in 1992 but was overpowered by Amazon (Vidal & Mitchell, 2013), which used data to tailor what the customer saw each time, offering future purchases based on past behaviour. Amazon sought out innovation and changed the retail sector in the process. As Kimble and Bourdon (2013) argue, ‘If a company is able to pioneer some form of innovation that is so deep-­ seated that it disrupts the way an existing market operates, it creates a completely new set of rules that only it understands and can follow’ (p. 58). Amazon did not invent retail trade but changed how it was experienced. It bridged the gap between existing and future practice, offering customers convenience and a simple to use interface while also offering lower prices and, initially, free delivery on all purchases. Kimble and Bourdon (2013) argue, of Amazon, and its founder, Jeff Bezos, ‘The key to Bezos’s business model was to concentrate on attracting and retaining customers … while leaving the responsibility for the logistics of distribution … to the publishers and wholesalers’ (p.  60). The Disruptive University, focused on attracting and retaining students, could leave both content and its provision to subject experts hired for their knowledge in a gig economy model. It could also offer students Continuing Professional Development courses beyond its degrees, to prolong its relationship with its customers indefinitely, using data to anticipate its customers’ needs. Universities already have associate lecturers and teaching fellows, many of whom have no job security and are hired per academic year depending on student numbers. This business model leaves no time for supported


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research, which is undertaken autonomously by academics as self-­ employment. To think of a business model in relation to higher education need not be problematic, partly because it is a predictable outcome of a monetised system and also because the term business model has been extended to cover a range of organisations, the business model comprising the customer value proposition, the infrastructure and the financial components (Kalman, 2014). Traditional universities invest heavily in infrastructure; a university mediated primarily or entirely through technology would not be so burdened. If careers support for academics is no longer their employer’s responsibility, a notable cost saving ensues. Moreover, given that academics often change employers more than once in the course of the careers, employers can argue their own interests are not served by enabling their employees to move on because the investment achieves no return. Gig economy employers are unlikely to have to face unfair dismissal litigation (Friedman, 2014). Furthermore, using gig economy contracts in universities is not revolutionary: Friedman (2014) notes, ‘Gig economy workers are employed in coffee shops and university lecture halls, farms, factories, and as janitors, cleaning offices at night’ and can be relaxed about their contracts; ‘Young people especially are said to want to break free of the confining restraints of traditional jobs’ (Friedman, 2014, pp. 172–173). However, in the event of gig economy employment being resisted, employers are well armed: ‘fear of unions and labor unrest no longer drives employers to establish internal labor markets; they have developed an arsenal of other tools—legal and other—to defeat labor militancy … their [gig economy workers] precarious employment situation makes them reluctant to bring complaints to their supervisors and employers’ (pp.  181 and 184). The Disruptive University can grow through the kind of employment contracts it provides and the likelihood of a substantial pool of willing, or at least acquiescent, labour to draw upon. Why does a university need a physical library when an incalculable number of scholarly resources are available online? Self-service terminals for checking-out and returning books already enable university libraries to make savings, comprising an efficiency innovation, but if every university is doing the same, no one gains an advantage. For that to happen, a

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more radical rethink is required. A university can buy nearly all its new titles in electronic form and phase out old, unused books, recycling paper in the process, highlighting the Disruptive University’s environmental credentials. Moreover, and again from an environmental perspective, being an online provider the Disruptive University will not require students to travel to a campus. Mohan, Ramesh, Cao, and Sarkar (2012) argue innovation, in the sense understood by Christensen, could create benefits for the environment through both efficiencies and imaginative solutions to problems of resources and infrastructure: the Disruptive University will exemplify this argument with an environmental impact strategy. Fewer library staff will be needed at the Disruptive University. The library can produce short videos on using academic databases and as a result the library will need fewer information specialists. Furthermore, as Leitch (2014) argues, ‘the ability of university libraries to subscribe to online journals instead of procuring hard copies has freed sorely needed shelf space’ (p. 3). As a result of all these changes the library will need less space, and the space vacated can be repurposed, rented, or sold. Digital libraries enable and support independent research, a skill undergraduate students should have, and thus the Disruptive University aids students’ academic development and employability skills. As long as the Disruptive University has online resources to support the acquisition and development of the skills, perhaps by following the Community of Practice model (Lave & Wenger, 1991; Wenger, 1998) for how the resources are prepared and presented, enabling novices to develop competence and confidence, bridging the gap between established and innovative practice, students and the university both benefit. Why do universities need accommodation departments when students and their families can find accommodation online? Why should a university subsidise sports clubs and make costly sports facilities available? The Disruptive University, not compromising on academic quality, can dispense of peripheral services, passing-on the cost savings to students. Hagel, Eckenrode, et  al. (2016) argue, ‘Infrastructure services involve scale-intensive, high-volume, routine processing activities’ (p.  16). If a university strips back its infrastructure it generates considerable savings on administration as well as buildings. Moreover, by removing inessential


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posts right across its provision, the Disruptive University will save substantial costs. Temple (2009) argues, ‘almost all writing about the university as a physical entity examines it as a site of teaching and learning, and/ or of research. The majority of people working regularly in a university, though, are support staff of various kinds, not directly engaged in any of these tasks, though their contributions are essential to them happening at all’ (p. 211). The Disruptive University could make drastic savings across its provision, passing the savings on to students. Are in-house student counsellors necessary or can the service be outsourced? Can digital resources be provided to support mental health? The Disruptive University needs to think about what digital support looks like and this may be one space in which technology is at a permanent disadvantage compared to face-to-face provision. Laurillard and Kennedy (2017) argue, ‘Education is no more a mass delivery industry than is parenthood. Whatever techniques we use to reduce the personal tutor support in order to keep costs down, there is the likelihood that we reduce quality, and therefore equity’ (p. 25). Perhaps, therefore, the Disruptive University needs a kernel of full-time lecturers who have personal tutor duties as part of their contracts, facilitated by video at a distance where necessary. Academics’ research time can be redefined as student support time and research can be an extra-curricular activity, with the Disruptive University providing nominal support in the form of access to a full range of scholarly materials. Nominal training can be provided to support the personal tutor function, and a nominal additional payment to recognise the additional commitment. Do universities need extensive premises if they are supporting programmes not necessitating laboratory work, or other programmes demanding designated space? Degrees in Literature or History, for example, could be supported without classrooms to attend. How much capital will universities free-up with fewer buildings and the attendant costs benefits of fewer staff and lower utilities bills? The Disruptive University will not need a large campus and possibly might not need a campus at all, and its online core means its reach can be practically global. Christensen and Tedlow (2000) argue, ‘the internet negates the importance of location’ (p. 44), and Kumar (2014) writes of, ‘Mobile-centric use of the Internet’ (p. 1122) and, ‘the rapid penetration of affordable mobile technology in

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remote regions of the global south’ (p. 1124). Zuboff (2015) states, ‘three of the world’s seven billion people are now computer-mediated in a wide range of their daily activities’ (p. 77). With digital infrastructure in place, and more extensive higher education provision highly desirable, there is exceptional market potential for the global expansion of higher education. Piketty (2017) shows how 70–80% of the production of goods and services, worldwide, used to be concentrated in Europe and America, but this figure had fallen to 50% by 2010 (p. 59). Europe attained its peak economic weight just before the outbreak of World War One whereas America peaked in the 1950s, but both Europe and America are characterised by a, ‘hyperdeveloped core and a less developed periphery’ (Piketty, 2017, pp. 61–62). Piketty (2017) further argues, ‘the poor catch up with the rich to the extent that they achieve the same level of technological know-how, skill, and education’ (p. 71). The foundational conditions are in place for a worldwide higher education revolution. Accelerating economic activity in previously underdeveloped regions of the world stimulates the demand for more higher education. Through skilful curriculum design, the Disruptive University can help to ensure that the new markets for higher education foreground the acquisition of skills most in demand by the globalised economy. Piketty (2017) argues, ‘Capital is never quiet: it is always risk-oriented and entrepreneurial’ (p.  115), and the global higher education market can keep capital occupied and profitable. The Disruptive University, designing its learning materials with a mobile-first strategy, can access hitherto underserved markets. In addition, if the Disruptive University has little or no physical location in the form of a campus, how can it be compelled to make a notable contribution to a nation’s taxation revenue? It can register itself in a business-­friendly country with little or no corporation tax. Tang and Bussink (2017) argue, ‘the current international tax rules only create a taxing right for a jurisdiction when the business has a physical presence in that jurisdiction … it is urgent to close the gap in the tax rules in order to ensure the fair and efficient taxation of corporate income in a digitized economy’ (p. 7). That said, for as long as existing rules are in place the Disruptive University has a vested interest in seeking a home within a business-friendly taxation system, in order to drive down costs for its customers. Jones (2014) argues, ‘Multi-national corporations, often


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engaged directly or indirectly in higher education, can move their profits from one national system to another … thus avoiding taxation’ (p. 175). The Disruptive University can do this, too, citing defence of its customers’ interests and deepening an alliance with its customers by defending low prices. If costs are kept drastically low, students are arguably as least as likely to side with the Disruptive University as they are with a tax regime. The Disruptive University can have a democratising influence on higher education. Tapper and Filippakou (2009) argue, ‘access to institutional status, income and power is greatly enhanced by academic success at the right universities. There is nothing conspiratorial about this: … they are establishing potentially very fruitful social networks, and over the years their universities have formed excellent working relationships with all the prestigious segments of the occupational structure … Symbiotic relationships are at work: the universities, the institutions that make up the commanding heights of public and private life, and talented students are all part of a mutually reinforcing web’ (p. 61). If the traditional university reinforces social stratification, the Disruptive University can be the great democratiser in higher education. Fosnacht, McCormick, and Lerma (2018) argue, ‘students who work full-time will typically be attracted to institutions that prioritize flexibility in scheduling’ (p. 965). The Disruptive University will have flexibility informing all aspects of its provision, will make higher education more widely available and will deliver wider social benefit. By increasing, globally, the number of students in higher education it will swell the talent pool, creating, worldwide, the kind of education only available historically to the elite. Most students in the UK accept a fully or partly privatised system. Neves and Hillman (2019), in a survey of over 14,000 students in the UK, found only 22% of respondents stated the government should pay all the cost of teaching undergraduates. The Disruptive University will not be a total culture shock. It will just be much cheaper.

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The Disruptive University as Platform What would the Disruptive University look like in practice? One possibility is that it could be a platform. Zhu and Furr (2016) define a platform as, ‘intermediaries that connect two or more distinct groups of users and enable their direct interaction’ (p. 74); Zysman and Kenney (2016) define platforms as, ‘multisided digital frameworks that shape or intermediate the terms on which participants … interact with one another’ (p. 6); and Thelen (2018) argues, ‘Whereas traditional business models are premised on firms organizing the production and distribution of goods and services to consumers, platform business models create value by linking service providers directly with clients’ (pp. 941–942). If we think of one group of users as the provider of the curriculum, and the other group of users as students, lecturers for the Disruptive University can be hired under the same principle as other participants in the gig economy and the platform can be a profitable means of distributing higher education. A number of successful disruptive innovations are platforms, including Uber, AirBnB, Facebook and Instagram. In each case, the technology only has value if users are actively engaging (Hopp, Antons, Kaminski, & Salge, 2018). The platform model attracts both consumers and producers, encouraging engagement and increasing value (Gawer & Cusumano, 2014). Gillespie (2010), analysing the term ‘platform’ in a digital context, argues, ‘the material “platform” for physical industry becomes a metaphysical one for opportunity, action and insight’ (p. 350), and, ‘A term like “platform” does not drop from the sky, or emerge in some organic, unfettered way from the public discussion. It is drawn from the available cultural vocabulary by stakeholders with specific aims’ (p.  359). The term, the metaphor, supports usage; skeuomorphic design makes the technology intelligible. It implies an equal meeting place but, in practice, the space is commercialised, either directly through fees charged or indirectly through data gathering. Rahman and Thelen (2019) read further significance into the platform as a means of describing this kind of digital interaction: ‘the very idea of the “platform” reflects an aspiration to be the foundational infrastructure of a sector—whether it is Uber’s attempt to dominate transportation services … or Amazon’s dominance of the online


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retail sector as a whole’ (p. 180). As Manokha (2018) points out, Facebook does not produce content and Uber does not own a car. The platform is essential, the foundational base on which everything else is superstructure. Platform implies indispensability and strengthens the provider. The metaphor makes the innovation seem an architectural necessity. A platform model could work in higher education. Buyers and sellers of educational goods and services could meet in an online marketplace. Part of the attractiveness of this proposition is that it could potentially offer open-entry to students. Furthermore, peer-to-peer transactions could be conducted swiftly and at low cost. A key problem facing peer-­ to-­peer transactions in education, however, is quality assurance. The platform could counter this problem by either partnering with an established higher education brand or investing sufficiently to create its own brand, producing and purchasing trust in the goods and services. If not originally a platform, the Disruptive University, once operational as a higher education provider, could create a platform as a sustaining innovation on its original disruptive proposition, and could rent space to third-party providers, increasing choice and revenue. An architecture to develop the Disruptive University as platform is already available: Eaton, Elaluf-Calderwood, Sørensen, and Yoo (2011) argue, ‘A digital system includes a platform that serves as a core on which others can build modules that are designed to extend the service possibilities of the platform’ (p. 2, emphasis in original). Furthermore, Denning (2016) argues for, ‘taking something that was previously a standalone product and creating a platform with shared infrastructure and base level of functionality, then inviting investors to create extensions and adaptations on top of that platform’ (p. 5). The innovators would create the value, for the benefit (at a price) of customers. There is a possibility of a global higher education platform on which individual offerings can be made available, connecting sellers and buyers, while the platform owners issue certification when a set number of academic credits have been accrued, or depute the accreditation process to the providers on the platform. The platform model for the Disruptive University may even be one means of providing an individualised curriculum (potential quality assurance problems notwithstanding), with students accessing a shopping list of modules via the platform like a supermarket, all under the banner of consumer choice.

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Hagel, Eckenrode, et al. (2016) argues, ‘the disruptors define and deliver a foundation of core functionality upon which third parties can build to tailor products and services to meet the needs of smaller segments of customers or individual customers’ (p.  12). The Disruptive University as platform offers a full market solution. Platforms offer convenience and ease of access, and platform products and services are popular: Culpepper and Thelen (2020) ask, ‘Who wants to be the politician who shuts down my access to cheap consumer goods … or the information gateway that connects me to the world through Facebook?’ (p.  293). Therefore, because of their success, platforms are powerful: ‘The power these companies wield operates not through politician’s fear of the pain these firms can visit upon the economy so much as the anticipated political fallout to which overeager regulators would expose themselves by messing with the infrastructure of people’s lives’ (p. 293), leading to the conclusion, ‘“What would we do without Amazon?” may not excite the revolutionary fervor of class warriors, but it is an effective statement of a distinctive source of the power that Amazon enjoys in today’s politics’ (p. 311). Culpepper and Thelen (2020) further argue, ‘the power of these companies … is clearly exercised not against the public but in a close and symbiotic alliance with a public that has come to depend on them … platform firms have succeeded in getting what they want because the public wants it too’ (p. 295, emphasis in original). People interact with platforms socially and commercially. There is no in-principle reason why they cannot interact with them educationally, too. Platforms are easy to use and convenient, and there is no cost for accessing the platform itself, only for goods and services supplied through the platform. As a digital marketplace, platforms are a secure and recognisable base, supporting users in engaging with them by means which feel intuitive. Higher education via a platform need not feel intimidating, as a traditional university might to a new entrant from a minority community with no previous experience of university study. Zysman and Kenney (2016) argue, ‘Advice often given in Silicon Valley is: “Don’t ask permission, ask forgiveness”’ (p.  19). The economic and political power of high profile digital corporations operating via platforms is exceptional. Based on the experience of other industries, it would


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be for higher education regulatory regimes to respond, not dictate. If the Disruptive University as a platform offered low cost and convenience in an easy to access form, it would be hard to counteract once it had proven popular with its customers, namely students. Moreover, once established, the Disruptive University could increase its fees incrementally to maximise profit: as Hagel, Eckenrode, et al. (2016) argue, ‘owners can often become greedy, charging higher fees for transactions’ (p. 14). It would be a question of finding optimum market price tolerance, monitoring student registrations through data gathering as prices increase. Srnicek (2017) argues, ‘Essential to all of these platform businesses … is the centrality of data … by providing the infrastructure and intermediation between different groups, platforms place themselves in a position in which they can monitor and extract all the interactions between these groups. This positioning is the source of their economic and political power’ (pp. 254–55). Consequently, ‘there is an intrinsic drive for these companies to be pushing up against the limits of what we presently consider the private realm’ (p.  255). Furthermore, platforms are often an attractive long term investment because of the profit opportunities they offer: ‘Funding from Silicon Valley (and elsewhere) flows into these companies, enabling them to continue operating at a loss for years at a time’ (p.  257). Moreover, Rahman and Thelen (2019) argue, ‘the business strategies of platform firms … depend heavily on a particular type of investor, one willing to underwrite massive losses in the short and medium term in pursuit of winner-take-all gains’ (p. 193). The platform model is efficient and potentially very profitable, and it could be a means of providing higher education irrespective of national borders and socio-­ economic boundaries. The potential profits are substantial enough to attract providers with the resources to dig in for the long term. The power of platforms is not to be underestimated, as evidenced by the success of some of the most well-known digital corporations. Rahman and Thelen (2019) argue Amazon, ‘has a vast share of the retail market-­ place: but even more important, it occupies a structural position that enables it to control market flows in both directions’ (p. 179). Moreover, the platform can serve the perceived interests of both providers and users, especially if the platform asserts itself as a dominant provider in the digital realm: ‘Once achieved, this “winner takes all” market dominance

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offers many avenues for generating returns through rents while also multiplying the number of stakeholders whose dependence on the platform makes them potential allies in efforts to defend it against unwelcome regulation’ (p.  180). Platforms are attractive to entrepreneurs, drawing investment from a range of sources: ‘venture capital, private equity firms, and even international sovereign wealth funds … Moreover, as platform firms become more dominant, they became stable, reliable investments for other sources of capital such as pension funds’ (p. 184). Hence, ‘the combination of investor and consumer interests around a business model that seeks market dominance and cuts labor out of the modern social contract is politically and rhetorically powerful. It allows platform firms to portray themselves as defending consumers against “stifling” regulation in the interest of efficiency, innovation, and consumer choice’ (p. 187). Platforms are established and popular. They accumulate influence through the data they collect as a matter of course. They have the economic backing to support them through lengthy development phases. The platform is not simply an inert technology for commercial purposes. It also changes practice and can start with a product before bridging to the platform. Brackin, Jackson, Leyshon, and Morley (2019) argue the smartphone, ‘provides a full cycle model, from original technology through to the development of a platform and the subsequent development of technologies using that platform in the explosion of Apps we see today.’ More precisely, ‘Early smartphones were limited to basic web browsing and navigation, but after series of iterations of the platform and business models, more complex apps such as AirBnB and Uber developed.’ The disruptive innovation of the smartphone was enhanced by the sustaining innovation of apps to enable commerce and socialising, and the possibilities of apps are far from exhausted. The creative practice of hackathons results in new apps being developed at speed, in this case without market testing or commercial strategy. When these succeed, as Downes and Nunes (2013) note, ‘The innovators are not even trying to disrupt your business. You’re just collateral damage’ (p.  48). Apps are cheap to produce and hence there is a low barrier to market entry. Muller (2019) argues, ‘we download a lot and use a little … the few apps that we do keep and use, such as online banking or satellite navigation systems such as Google Maps, have considerably changed our behaviour.’ A


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technological innovation does not have to begin as a platform but can evolve into one along Sustaining Innovation lines once it has an established core. The Disruptive University could design its own programmes until it built sufficient reputation, then open up the market to other providers, charging for a presence on the platform. Apple entered the mobile industry in 2007; Google introduced its Android operating system in 2008 and powerful incumbents in the industry were disrupted. Motorola sold its mobile division to Google in 2011 and Nokia sold its core handset business to Microsoft in 2013 (Kushida, 2015). Montoya and Kita (2017) argue the iPhone ‘helped define a dominant design for smartphones in 2007. This dominant design established multi-touch as the default interface of smartphones.’ Reinhardt and Gurtner (2018) argue, ‘Blackberry did not invest in touchscreens and smartphones … consumers later switched to this new technology and Apple and other competitors displaced BlackBerry’ (p.  137). Having established a dominant design, Apple was able to dominate the market. Its platform model attracts more participants and generates more profit. The platform’s agility and market sensitivity (the latter underpinned by constant data gathering) can give it competitive advantage. Hagel, Seely Brown, Wooll, and de Maar (2016) argue, ‘the incumbent’s standardized product may not be able to compete with the more innovative and more targeted products being rapidly created by the platform’s network of producers’ (p. 6). Furthermore, platform-based higher education can comprise both low end and new market disruption: ‘because new variants may span the quality and price spectrum, less expensive variants may unlock pent-up demand from the low end of the customer pool’ (p. 6). The platform model in higher education could comprise a classic disruptive innovation, catering to the low end of existing markets, opening up new markets, using technology to challenge the incumbents. On a higher education platform, the razor/razor blade profit model could be effective (Benner, 2007), in which the core hardware is not sold at a big profit but the necessary add-ons are. The platform itself would be free to access, and so would some content, but there would be additional costs for access to extensive materials, and more significant costs for undertaking assessment leading to accreditation. Additional costs can be levied for specialist learning materials, or one-to-one video support,

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possibly charged by a meter, with the lecturer getting a percentage of the revenue produced, like an academic taxi driver.

Uber U Successful disruptive innovations in the digital age have already used the platform model. Muller (2019) notes, ‘Uber entered New York City in mid-2011, and within seven years … overtook the existing taxi service in terms of rides per day.’ Offering a taxi service has low barriers to entry, unlike higher education provision, but the principle of a digital platform as a mode of disruption is established. Christensen, Raynor, and McDonald (2015) argue Uber is not a disruptive innovation because it did not begin as a low end or new market disruption. However, some disruptions, such as cell phones, began at the high end of the market. Moreover, Brackin et al. (2019) argue Uber is disruptive: as a technology, its approach is to be cheap, simple and convenient. Laurell and Sandström (2016) analysed over 6500 social media posts and found Uber was perceived as both an institutional disruption and a disruptive technology. Rahman and Thelen (2019) argue, ‘Perhaps more than any other company, Uber has come to stand in for the excesses and promise of twenty-­ first-­century capitalism. Under drivers are the paragon of the new “gig economy,” in which work is increasingly precarious, insecure, and yet highly optimised for both firms and end users’ (p. 178). Uber shows how the platform works and also shows how disruptive innovations change practice. Platforms create a bond between provider and consumer, with the labourer in between them having to adjust to suit the demands of the other elements in the system. Innovative firms and their customers work conspiratorially to sidestep rules and set new parameters for acceptable practice. Muller (2019) argues, ‘Uber and Airbnb can be thought of as modern-day pirates, as they have sustained a continued struggle, often illegal at first, against inefficient regulators while gradually succeeding in changing the industries and regulations in which they operate.’ Thelen (2018) argues, ‘fast-moving technology allows firms like Uber to exploit gaps in existing regulatory frameworks … flat-footed government


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regulators often find themselves a step behind these agile companies … so that by the time lawmakers begin to consider new legislation, they face intense political pressure to devise rules that retroactively render these practices legal’ (p.  940). Moreover, innovations can work on different sides of a political divide. Thelen (2018), in the context of the USA, argues, ‘At the national level, prominent Republicans heralded Uber as a champion of free markets, while Democrats (with an eye toward their millennial base) embraced it as urban, progressive, and innovative’ (p. 945). However, in Germany, ‘national associations representing local taxi operators mounted a quick, coordinated response. Cementing a national-level alliance with transportation authorities and leaders from both sides of the aisle, they mounted a spirited defence of the existing regulatory framework’ (p. 947). It has been possible to resist the disruption posed by Uber but higher education is stratified in many countries which makes it more difficult to counter a disruption by creating a united front. If a low end disruptor was drawing students away from universities in the bottom section of league tables, elite universities may not be especially motivated to join the resistance. They would be unlikely to mobilise until and unless their own student base and business model was threatened. Uber employs no drivers. Any driver with a car can potentially work for it. Instead, drivers are independent contractors, bearing the responsibility to maintain and repair their vehicles. The Disruptive University could follow the same model. Uber drivers have cars: would-be lecturers have PhDs and can manage their own assets (their research and publications). The Disruptive University would be creating opportunity. Whereas incumbents in the taxi industry have to invest in vehicles, staff and overheads, passing these expenses onto customers in the fares charged, Uber can cut out layers of mediation and pass the savings on. The Disruptive University could similarly target layers of mediation and offer a drastic reduction in student fees. The fact that the Uber app is a bidirectional rating system and ensures accountability means the service is conducive to quality control, exposing bad drivers. Uber’s practice of drivers and customers rating each other also ensures surveillance is built into the business model. At the Disruptive University, lecturers with bad ratings could be similarly flushed out by poor student ratings. Uber can claim

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environmental responsibility by offering a service which means fewer people need to own cars, reducing air pollution and traffic jams, and moreover, in Norway, ordering UberEL provides the customer with an electric car (Thelen, 2018). An entirely online Disruptive University could make a comparable claim by not having a campus. If the Disruptive University identified and expunged all its layers of mediation between educational content and students, passing its cost savings on in terms of massively reduced fees, it could appeal to a sizeable number of students. The neo-Liberal era, which we can roughly define as having been inaugurated in the USA and the UK in the early-1980s, is characterised by deregulation. Uber practises, ‘disrupted regulation’ (Collier, Dubal, & Carter, 2018, p. 920). Uber successfully disregards regulations, describing itself as a technology company rather than a taxi company and thus not being subject to the regulations normally applying to taxis, leading to duel regulatory regimes applying in the same industry, characterised by weaker regulations for the disruptor. Uber offers low prices and high driver supply. The service is reliable and popular with consumers; Uber, ‘forces local or state governments to respond reactively to a fait accompli, after Uber has established a base of customers and drivers’ (Collier et al., 2018, p.  923). Regulation can inhibit innovation because it protects some terms and conditions of employees: ‘work laws, such as the minimum wage, social security, right to unionize, and overtime pay’ (p. 921). Deregulation seemingly creates a free trade area but in reality power is weighted towards those offering employment in conditions where there is a surplus of available labour. Uber has a low fixed cost model (Isaac, 2014). By classifying itself as a technology company it sidesteps regulations pertaining to transport companies. By classing its drivers as independent contractors it evades workers’ protection and benefits (Qiu, Gregg, and Crawford (2014) pose the question, ‘This is the best of times for capital. Is it the worst of times for labour?’ (p. 568)). By shifting its costs it increases its profitability. From a customer’s point of view, Uber has made transport cheaper and more convenient. Uber can argue that it has, ‘stepped into the vacuum of the taxi service industry that, guarded by entry controls and sheltered from competition, has been unresponsive to consumer demands and unwilling to innovate’ (Isaac, 2014, p.  10). Universities have been similarly


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sheltered by their reputations established over time but they are not unassailable. A disruptor with a low fixed cost business model could be attractive. Uber is backed by global investors including Google Ventures (Elbanna & Newman, 2016). Hang and Garnsey (2011) argue, ‘Venture capital is well known for enlarging the scope of enterprise’ (p. 21). The Disruptive University, backed by international capital, could become globally significant in higher education, undeterred by national boundaries. It could act first and apologise later. It could build participation to the extent that regulators are compelled to accommodate it. The Disruptive University could become the World’s first truly global university. The Economist (2015) argues, ‘Both Netflix and Uber have prospered by dealing with the “pain points” of core customers: in Netflix’s case, Blockbuster’s limited range and punishing late-return fees; and in Uber’s case, the manifold inefficiencies of the established taxi industry.’ Efficiency Innovation and Disruptive Innovation can work hand-in-hand to transform a range of practices, including higher education.

Apple Corps A major hurdle facing the Disruptive University is credibility and recognition. It would benefit from a strong brand to bestow trust. The Disruptive University could combat its credibility and recognition drawback by connecting with a globally recognised brand such as Apple. Hagel, Eckenrode, et al. (2016) note Apple, ‘started in the PC business but then focused on scaling an edge in the digital music player business, then the mobile phone business, and then the tablet computer business. Each time, Apple was able to scale a promising edge to build an entirely new business, leveraging its core expertise in product design’ (p.  18). Apple has already shown its capacity to diversify, and Qiu et al. (2014) argue, ‘Apple can be seen as an emblem of contemporary capitalist world order’ (p. 572). It is a dominant and globally recognised brand, attractive to customers. Apple has a track record of innovation and taking risks. Paap and Katz (2004) state, ‘When Apple launched the iMAC it was met with surprise

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(and in some cases anger) by many users because it did not come with a 3½ inch floppy drive. Apple had predicted …. that the 3½ inch floppy technology used for file transfer would soon be irrelevant with the emergence of newer technologies …. Apple knew more about its customers’ needs than most of its customers did’ (p. 20). One of Apple’s innovations was a chain of its own shops offering both products and support (Brackin et al., 2019). Is there any reason, therefore, why established brands such as Apple should not lend their brand to higher education, when the potential rewards, worldwide, are enormous? The mission statements of higher education institutions can already align with those of major corporations, as shown in a UK context by Flavin, Zhou Chen, and Quintero (2019). There is no in-principle reason why Apple could not enter the higher education market given its design strengths, track record in innovation, its presence and global brand. Moreover, Apple has shown it can build on others’ initial forays into markets with new technologies: Napster was the first to offer a music file sharing service but encountered legal problems regarding copyright. Conversely, Apple cooperated by negotiating with record labels, and offered its own service from its iTunes platform modelled on closely on Napster (Söderberg, 2017; Vidal & Mitchell, 2013). Apple’s brand is global and well received. Ashill, Semaan, and Williams (2019) interviewed consumers in the United Arab Emirates, who said, ‘Apple always has a story to tell …. I feel inspired by those stories’ (p. 12). Consumers also stated, ‘Apple has a vision for the future and is innovative, which by default makes it unique and ambitious and risky’ (p. 13). However, Knox (2019) argues, ‘the digital requires bodies … efficiency in one context is dependent on manual labour in another … there is a social cost to the availability of digital technologies,… they do not exclusively derive from clever “disruptions” or “innovations” in Silicon Valley’ (p. 366). Emejulu and McGregor (2019) argue, ‘Constructing technology as innocent or neutral misunderstands the social relations of technology and its very real material consequences in our social world’ (p. 133), and the treatment of workers who make Apple’s products has been criticised. Many of Apple’s products are manufactured in China, where independent trade unions are forbidden and labour strikes illegal (Clarke & Boersma, 2017). There were, moreover, a spate of suicides at Foxconn


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factories in China (Apple’s contract manufacturers in China) in 2010 (Chan, 2013; Emejulu & McGregor, 2019; Litzinger, 2013; Pun & Chan, 2013), and workers are prone to hand injuries, working long hours with heavy machinery (Qiu et al., 2014). Sandoval (2013) argues, ‘The conditions under which these products are produced … resembles the early days of industrial capitalism … Apple’s marketing slogans present its products as technological marvels without history. They divert attention away from the fact that underpaid Chinese workers are producing these products during 10–12  hour shifts at least 6  days a week’ (pp. 338–339). Moreover, the minerals necessary for Apple products are excavated in mining, with a labour force that has included children (Sandoval, 2013). However, concerns over production methods have not damaged the Apple brand, which has used the imagery of cultural icons and progressive activists, from Miles Davis, to John Lennon and Yoko Ono, to Gandhi (Clarke & Boersma, 2017, p. 112). A Foxconn recruitment slogan treads, ‘There’s no choosing your birth, but here, you will reach your destiny. Here you need only dream, and you will soar!’ (Chan, 2013, p. 91). The skilful creation of a narrative, either by producers or brands, can encourage innovation, foregrounding some aspects of a product’s features and concealing others, creating an image which is well received if inauthentic. Litzinger (2013) argues Steve Jobs, ‘silently outsourced much if not all of Apple’s production to China, Apple honed an image of itself as a pedagogical innovator’ (p. 173). Apple has experienced success as both an innovator and a communicator, and concerns over its mode of production have not obviously damaged sales and reputation. Moreover, its mode of production may well be typical of technology companies as a whole, and the shift of the computer supply chain to Asia can be seen as an efficiency innovation (Chan, Pun, & Selden, 2013; Montoya & Kita, 2017). Hang and Garnsey (2011) argue Chinese companies serve as, ‘manufacturing contractors for foreign companies exporting Chinese-made products back to developed countries’ (p. 15), and a brand can be robust if its core narrative is impactful and reiterated. The Apple brand is intact and continues to be popular with customers. Disruptive innovations can be supported in their pursuit of profit by nations whose labour costs are low and where protest is suppressed: ‘A neoliberal state collaborates with private entrepreneurial elites by

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providing infrastructural support and ensuring law and order, thereby facilitating capital accumulation and economic growth’ (Chan et  al., 2013, p. 102). Moreover, Apple’s practices are not without precedent in technology: in the 1960s, IBM shifted production to Europe and Asia to cut costs, but Apple’s profitability relies on a mainly Asian production base (Chan et al., 2013, pp. 103–104). Perhaps the production processes of modern technologies are typical of a global system of production, distribution and consumption. Apple and other brands use their innovative track records to optimise customer satisfaction and firms’ profits, creating narratives that diminish aspects of the production process and promote association with politically and culturally prominent figures, continually nurturing the brand. Apple launched its app store in July 2008. In the Apple App Store in the USA, Education was the category with the second-highest number of apps in 2015, Games being the highest (Brockmann, Stieglitz, & Cvetkovic, 2015). The statistics indicate an interest in accessing education through apps. Google and Microsoft also have their own app markets, extending provision. Brockmann et al. (2015) argue there are three means by which to generate revenue in app stores: direct purchase; in-app purchase; and advertisements (p. 1212). The Disruptive University can take advantage of all of these. A global brand creates interest; a platform creates a user-friendly marketplace; apps enable swift and convenient consumer choice; specialists provide academic content of due quality and the means to assess student performance. Disruption in higher education, therefore, could come via a well-­ known name. There might be a new higher education provider involved but their name would not be the public-facing brand. The Economist (2015) argues, of Christensen’s Disruptive Innovation theory, ‘Christensen struck fear into executives by warning them that they could be put out of their jobs by companies they had never heard of. Today the biggest threats may come from people they talk about every day.’


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Opposing the Disruptive University The core strategy for contending with disruption is for an incumbent to set up a separate business to identify and develop innovations of its own (Christensen, 1997; Christensen & Raynor, 2003). Setting up a separate business can encourage constructive competition between the two, to the benefit of both. The offshoot is free of the ossifying effects of the organisation’s culture and is free to innovate. Gobble (2018) argues that, in instances where a parent company sets up a separate unit, ‘At some point, if it’s to become something more than a novelty, the carefully nurtured innovation will have to leave the protection of the incubator and cross over to the operational side of the company, which will have to figure out how to assimilate it without gutting it’ (p.  54). Relationships between parent companies and offshoots can be fraught but if commercial momentum is with the disruptor it may be best placed to succeed. It may need to take priority over the incumbent. Existing universities may need to demonstrate ‘organizational ambidexterity’ (O’Reilly & Tushman, 2011), maintaining their current operations while also exploring innovative possibilities within higher education. Moreover, an offshoot from a parent company is a commitment which may require protracted, financial support. O’Reilly and Binns (2019) argue new ventures need, ‘to add customers, capacity, and capability fast enough to maximize the market opportunity’ (p.  10). Consequently, ‘Unless the new venture has active senior-level sponsorship, the internal dynamics of the core business are likely to slow down or smother the new business’ (p. 13). The strategy is a risk because the parent company has to commit substantial resources to give the new organisation a chance of success and, moreover, success might compromise the profitability of the parent. Markides and Charitou (2004) argue, ‘Perhaps the biggest cost of keeping the two businesses separate is a failure to exploit synergies between the two’ (p. 24) and therefore ‘firms that assigned an insider to be the CEO of the new unit were more effective in their response than firms that used outsiders’ (p. 26). One outcome of this approach is that the new business has lower profit margins but this is acceptable, especially if the new unit can build capacity. Instead of retreating from the

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lower, less profitable end of the market, the incumbent caters for it through its offshoot. At the same time, it dilutes the threat of Disruptive Innovation. In this way, incumbents counter Disruptive Innovation by creating and incubating it. A university could set up its own offshoot to cater to new markets. A number of universities in the USA and UK set up overseas campuses but these can have high overheads, lessening their potential profitability. Online offshoots tailored for specific markets would not have this problem and do have the potential to build new markets, using the parent company as a brand if the brand is well known and reputable. An offshoot from a parent company is not the only strategy for responding to Disruptive Innovation. King and Baatartogtokh (2015) argue, ‘managers … should find ways to leverage existing capabilities. And … where practicable, they should work collaboratively with other companies’ (p. 87). Higher education is a large and expanding market but static universities may not be best placed to capitalise on global markets unless they have the brand and reputation to attract sizeable numbers of students, particularly high fee paying international students. Incumbents can identify the disruptors who have acquired momentum and look at ways of working with them, including mergers and acquisition, consolidating their own position. There are advantages to having, ‘a “fast second strategy”, letting smaller firms take the risk and then quickly imitate and catch up’ (Leitner, 2017, p. 203). Wessel and Christensen (2012) recommend the following course of action to incumbents in the face of disruptive innovations: ‘Identify the strengths of your disrupter’s business model; Identify your own relative advantages; Evaluate the conditions that would help or hinder the disrupter from co-opting your current advantages in the future.’ The incumbent can counter Disruptive Innovation by watchfulness and by strategy. Yoffle and Kwak (2002) argue, ‘If you want to avoid future combat, give potential competitors a stake in your success through partnerships, joint ventures or equity deals … keep in mind that the true goal of this tactic isn’t to make all sides better off; it’s to defend and strengthen your competitive position’ (p. 11). They further argue, ‘Sell your services to opponents in order to stop them from developing competing capabilities on their own’ (p. 15). An innovator in higher education, partnering with an


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incumbent, could use the incumbent’s brand and quality assurance processes to ensure and enhance reputation. Following the recommendation for incumbents to establish separate businesses to identify and develop innovation, and to limit the impact of competitors doing it, innovation can be used to bolster incumbency, not unseat it. Incumbents can also buy disruptors: Walt Disney bought Pixar in 2006 instead of trying to compete with it (Currah, 2007; King & Baatartogtokh, 2015). Disruptive innovations pose a threat but incumbents have resources at their disposal. However, ‘incumbent leaders must find ways to create a sense of urgency within their leadership groups’ (Hagel, Eckenrode, et al., 2016, p. 16), which can pose a cultural challenge to many existing and arguably inertia-prone universities as, ‘a profit-maximizing firm lacks incentives to invent technologies for people who cannot afford its products’ (Anadon et  al., 2016, p.  9687). Garrison (2009), in a survey of seventy-three executives, found larger companies had an inferior response capability, being able to perceive potential technology threats but being organisationally geared in ways that made it difficult to respond to emerging technologies. Moreover, Currah (2007) spoke to Hollywood executives, whose jobs and resultant lifestyle privileges were precarious, leading to conservative practices relating to new technologies, because the risks were perceived as too high. Incumbents in higher education can also create a narrative to combat Disruptive Innovation, as happened in the razor industry in a case study of Bic and Gillette: ‘After seeing a quarter of the market being won over by Bic (in less than ten years), Gillette set about to change people’s perceptions on what to expect from their razor … By successfully raising the bar in this market, Gillette managed to convince consumers that they should expect more from their razor and that Bic was not really “good enough” for them’ (Markides & Sosa, 2013, p.  331). Incumbents in higher education have a strong narrative of quality and continuity which they can use to argue that a new provider will always be second best. The two industries are very different but universities are preoccupied with narratives, as shown in their strategies, mission statements and websites. Narrative can be used to counter disruption, or in an attempt to nullify it, trying to prevent it gaining a foothold in the first place.

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 efeating Disruption: The Swiss D Watchmaking Industry Markides and Charitou (2004) present a case study for showing how an incumbent can respond to disruption by creating an effective narrative. The Swiss watchmaking industry enjoyed global dominance but this was threatened in the 1970s when quartz technology enabling watches to have additional features was taken up by manufactures such as Seiko in Japan and Times in the USA: ‘The Swiss share of global world production declined from 48 per cent in 1965 to 15 per cent by 1980’ (p. 29) and the industry lost two thirds of its workforce between 1970 and 1980 (Garel, 2015, pp. 35–36). In response, the Swiss introduced the Swatch in 1983: ‘what the Swiss did was to produce something that delivered low cost and differentiation at the same time—managing two conflicting strategies simultaneously’ (p. 29). Low cost is commonly associated with lower standards but effective marketing enabled the Swatch to claim differentiation. The incumbent redefined itself in the face of the disruptor, launching an additional, affordable product that still benefited from the well-established brand. The Swatch was launched in the Swiss market in 1983, but it is important to note that the Swatch did not start from a vision but from necessity within an industry under threat. A threat from the disruptor forced the incumbent to innovate and offer new, affordable products. Swiss watches had dominated the industry worldwide since the early-­ twentieth century, with the watch itself having been a largely static technology since the seventeenth century (Glasmeier, 1991). A state system, Statut de l’Horlogerie, introduced in the 1930s, ensured, ‘Swiss manufacturers could only buy from Swiss producers, and component producers could sell only to Swiss firms’ (Glasmeier, 1991, p. 472). The system of export permits ensured supply remained below demand, ensuring profit levels, and, ‘High profits earned in this period allowed firms to develop a mechanical watch manufacturing system unparalleled in efficiency’ (Glasmeier, 1991, p. 472). However, rivalry to Swiss domination from the Japanese industry was supported by low labour costs in Japan and a protected home market. American firms were also able to enter the


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worldwide watch market through off-shore watch assembly by poorly paid workers (Glasmeier, 1991). In addition, Timex watches were sold in drug stores with a low margin, rather than in jewellers with a high margin (Abernathy & Clark, 1985; Linton, 2009), making the disruptive technology more affordable. A key design feature of the Swatch was that it was welded and therefore could not be repaired, only replaced. Moreover, the Swatch was simplified, comprising 51 parts rather than the 150 required to make a traditional watch (Garel, 2015, p.  38) and was assembled at automated factories (Norman & Verganti, 2014, p. 88). Given the Swatch’s cheapness and simplicity, it comprised a disruptive innovation responding to the preceding disruptive innovation of quartz technology. However, it was clearly still, recognisably, a watch. Therefore, and building on the work on design by Hargadon and Douglas (2001), and the work on strategy by Kahl and Grodal (2016), the Swatch offered familiarity while still achieving innovation. In marketing terms, through the variety of its designs, the Swatch became a fashion accessory and people could own more than one Swatch in the same way that they might own more than one pair of earrings. Raffaelli (2019) argues a legacy technology can re-emerge, and the traditional Swiss watchmaking industry made a comeback. In order for a comeback to happen, the meanings and values of the legacy technology needed to be redefined. Relating the experience of the Swiss watchmaking industry back to higher education, a university could assert its intention to have face-to-face provision in preference to learning and teaching mediated through technology, in the interests of traditional academic quality. It could stress its longevity; its history; its notable alumni. In Raffaelli’s (2019) case study, Swiss watchmakers stressed the values of craftsmanship, luxury and precision. The technology was disrupted and risked being displaced by quartz watches, but because of the industry’s capacity to redefine itself Swiss watches experienced market growth by 2000, superseding quartz watch sales by 2008. The industry achieved revitalisation by redefining itself, foregrounding its values, including status. Moreover, it was able to communicate its values effectively, in part through the recruitment of brand historians. While watchmaking and higher education are very different areas of practice, universities stress

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their quality, status and longevity in their mission statements and strategy documents, and have symbolic capital to draw upon in the face of a disruptor. Ultimately, effective leadership is the best bulwark against disruptive Innovation. University leaders should identify areas, both geographical and socio-economic, of under-provision, and use their assets, both economic and symbolic, to meet the opportunity and extend higher education. Tellis (2006) argues, ‘some firms last for decades and even a century. Other highly successful and established incumbents self-destruct or decline into oblivion. Long-term market leaders focus intently on future emerging mass markets. They innovate relentlessly to cater to that emerging market … they are willing to cannibalize their current assets to realize that future potential’ (p. 37). The Swiss watchmaking industry faced a disruptor, one that came with an excellent technology. Watchmaking fought back with its age and quality, features available to some universities, too. The industry also fought back with a new product of its own, offering quality and affordability at the same time. Perhaps an EduSwatch has a future, providing a lean product but within a brand that generates customer confidence.

The Other Disruptive University There is the possibility of another type of Disruptive University, one that could use technology to disrupt higher education. This university might have premises, such as units on high streets helping urban renewal. Unlike most university premises, identity cards are not necessary to gain entrance. Visitors can use terminals or their own devices to find out more about the programmes on offer and to access content. They can talk to a student support officer who is not a salesperson and has no targets to achieve in terms of students enrolled. However, it is also possible that the Other Disruptive University does not have premises and is entirely online. It still has student support officers but they visit community centres, job centres, parent and baby clubs, and prisons, making people aware of the courses on offer.


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The Other Disruptive University is owned by the state and exists to provide goods and services for community benefit. It is not a profit-­ making business, any surplus produced being reinvested with the aim of expanding participation. Moreover, students are encouraged to develop and share their own digital practices at the Other Disruptive University, co-constructing digital literacies. Content is freely available at the Other Disruptive University. Once registered, students are not limited in terms of the course materials they can view. One registration enables total access. Hence, though they may be registered on a Physics programme they can access the materials from the History of Art programme. Content is accessible from a range of devices, and design takes account of a range of screen sizes. Interactivity and peer-to-peer support is enabled by forums supplied through a virtual learning environment but also through social media accounts run by the Other Disruptive University. The core consideration in the design of all material is ease of use, simplicity and convenience, in line with Disruptive Innovation principles (Christensen, 1997). Courses can be taken to enhance employability, or for personal enjoyment. The Other Disruptive University does not make judgements about what the content is for; it simply makes it available. Courses can be taken for academic credits and qualifications but at a pared-down cost which contributes to the wages of the employees, and hires premises if applicable. Union recognition protects the terms and conditions of employees and promotes constructive dialogue with the Other Disruptive University’s leaders. Academics are encouraged to research and publish, both to maintain their currency and to promote the academic strengths of the Other Disruptive University. They are encouraged to host webinars for the benefit of all students. Many if not all of these are publicly available, too. The Other Disruptive University maintains meaningful relationships with employers’ organisations and reminds them of the generic and transferable skills students are acquiring at the Other Disruptive University, including communication skills and self-management. The Other Disruptive University is similarly engaged with local councils and the third sector. The Other Disruptive University requires state support to launch, operate and develop. This, in turn, requires a political understanding of

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higher education as a social good and presupposes a government which has made its case to the electorate and has secured a democratic mandate. A number of European countries already offer higher education free or at a very low cost, including Germany, France and Norway. That said, other countries including the UK accept the existence of higher education fees (Neves & Hillman, 2019). The Other Disruptive University will need to make its case for education as a public good, to be underpinned by public funding. In its strategy, it can aim for a measure of financial self-­sufficiency within a given period of time. The Other Disruptive University partners symbiotically with public libraries, enhancing the materials available to library members while the library makes its members aware of the Other Disruptive University’s provision. The Other Disruptive University also partners with community organisations, so students can gain experience of field work and the organisations can benefit from students’ input. Maybe, in its early stages, the Other Disruptive University partners with an existing university, comprising an offshoot. The existing university gets additional state support in exchange for incubating the new provider. The Other Disruptive University is simple and convenient to access. It has state support and is affordable, as its courses are subsidised, at least initially. It is innovative in practice by positively encouraging mass participation in higher education, beyond traditional higher education demographics. Its graduates are confident communicators. They are digitally competent and confident. Cohorts are not restricted by national borders and thus students can gain intercultural competence, too, through peer-to-peer interaction. Programmes allow and encourage interdisciplinarity by making introductory modules available across a range of subjects and publishing extensive content. The modules are credit bearing and do not slow down a student’s progress. Students are not removed from the Other Disruptive University’s register at the end of their programmes and can continue to access material for self and professional development at a nominal fee, effectively attaining permanent membership of the learning community. The Other Disruptive university is a lifelong, life-enhancing, social resource. Innovation is built into its provision and into its narrative, which is carried proactively into the public domain and into markets where higher


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education participation is traditionally low. The Other Disruptive University aims for the low end of the existing market and aims to create new higher education markets from which it can build incrementally. Its scope is global. Selwyn (2013) argues, ‘a genuine grassroots interest needs to be developed in the co-creation of alternative educational technologies’ (p.  3). A genuine grassroots interest can start with practice, with users creating new technologies and repurposing existing technologies. A genuine grassroots interest means not being fettered by conservative strategies or other forms of management edict. It means being open to the possibility of disruption. It means disruption being defined socially more than commercially. The Other Disruptive University could encourage students to share technologies and practices and to use them in assessments. The strategy for technology-enhanced learning could be compiled from the ground up, leading to an authentic approach in which rhetoric is aligned with practice, achieving a notable innovation in higher education.

Conclusion New technologies arise; continuously so. Wider contexts also change as economies demand different skills. In higher education, fee-paying students demand high quality and relevant programmes. Yet, despite these changes, higher education remains fundamentally unchanged. Technology has not disrupted higher education. That said, the biggest risk of all is for higher education institutions to do nothing with or about Disruptive Innovation and to rely on the perpetuity of the status quo. Byrne and Clarke (2020) argue, ‘the number of tertiary level students around the world is expanding rapidly and all the projections are for this number to continue increasing’ (p.  229). Can existing universities allow the challenge of global higher education provision to be unmet? The universities that will thrive in a rapidly-changing world will be flexible and responsive and will use technologies to attract and retain students. By not changing their existing practices to meet the growing market, established universities will cede ground to a disruptor.

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One way to approach the potential of technologies to disrupt higher education is to identify those market segments to whom higher education is not readily available. Clearly, there is scope for a disruptive entrant. However, the disruptor’s value proposition will need to be both strong in terms of academic quality and lucid in terms of narrative. Furthermore, the goods and services provided will need to be seen to be robust in areas where higher education qualifications are evaluated, most notably the jobs market. Disruptive Innovation arises initially within small constituencies, often at the low end of markets. These are spaces that higher education cannot afford to ignore. Higher education cannot afford to ignore them socially because education should be available to anyone who wants to take advantage of it. Higher education cannot afford to ignore the low end of the market commercially either, because of the opportunity it affords to a disruptor. However, large organisations are prone to inertia. Established practices become entrenched practices. A disruptor in higher education would have an opportunity to build market share because incumbents would be slow to respond and would be unlikely to fundamentally change their marketing strategies to attack a provider targeting the low end of the market, or catering for a market segment previously ignored by higher education. Shang, Miao, and Abdul (2019) undertook a survey of research on Disruptive Innovation during the period 1997–2016 and found its strongest geographical concentration was in the USA, which published 44.27% of research papers concerning Disruptive Innovation. The UK and Germany were second and third, with China fourth. It may be the case, therefore, that Disruptive Innovation is more likely to happen in advanced and advancing industrial and post-industrial nations where the practice has been experienced, recorded and researched most frequently. However, Rahman and Thelen (2019) argue diminished regulations and the weakness of trades unions create the permissive contexts that aid disruption, and venture capitalists and other investors are attracted to disruptive business models. Leitner (2017) argues, ‘Traditionally, industrialized countries are said to innovate and sell their products globally, whereas catching up economies mainly imitate and only slowly develop the capacities to innovate. While the USA, Europe and Japan are considered to be leading innovation nations, many other


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countries have caught up in recent years …. If the innovation pace on a global level increases and countries such as India and China catch up and develop high innovation capacities, innovation competition will become even more fierce, and firms, particularly in western countries, may more often pursue imitation strategies’ (p. 208). Hellström (2004) argues, ‘economic structure in some way is the foundation of society, since it is only after people have taken care of their sustenance that they can innovate and create. Hence, in the big picture of innovation and technological change, “economics” will always come first, not in a linear manner but as a continuously present basic condition for ideation and innovation’ (p. 641). Linton (2009) argues, ‘In many cases social innovations must arise so that the full value of a technological advance can be obtained’ (p. 729). Innovation presupposes the conditions in which it can happen. Higher education offers a growing, global market (Moccia, 2016), but high fees in some countries comprise a barrier. An affordable, convenient and reputable alternative to current provision will be attractive. Anadon et  al. (2016) argue, ‘impoverished, marginalized, and unborn populations too often lack the economic and political power to shape innovation systems to meet their needs’ (p.  9682). At present, therefore, the potential to innovate is inequitably weighted towards those with wealth and power already, but Disruptive Innovation is a ground up practice. If it is detached from existing business structures it can gain a foothold, which does not prevent the innovation being adopted by a major stakeholder later on, or being developed commercially, but it does imbue the innovation with authenticity. One risk of low end disruption in countries like the UK is that it could initially lead to further stratification in higher education. The formation of the Russell Group in 1994 was instrumental in creating and consolidating a stratified sector. A low end disruptor would be at the bottom of the market. However, if the qualifications provided by the disruptor had sell-on value in the jobs market, students might be willing to trade the qualification for the status, especially if they were priced-out of the mainstream sector. A disruptive innovator offering drastic reductions in fees could gain a foothold from which it could progress, raising fees moderately as its credibility increases.

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Higher education is not solely about the product. It is also about the service and the social opportunities. But, for some students, the product may be all-important. A higher education product mediated by technology could gain substantial interest, especially if content was available any time and not fixed by a timetable. Entirely online universities could trade at a vastly reduced price given their relatively low overheads. Selwyn (2014) positions technology as, ‘an extension of the politics of higher education’ (p. ix), but what are the politics of higher education? On the one hand, students are potentially empowered because of the significant revenue they bring to the sector and are thus in a position to effect their education as a whole and the use of technologies in particular. However, digital technology practice in universities does not reflect the day-to-day practice of students (or lecturers, for that matter). Slater, Mohr, and Sengupta (2014) argue, ‘product innovation is the lifeblood of firms competing in dynamic environments’ (p. 552) but universities are often conservative environments, delivering the same product by the same means. Maybe this is not important. The degree continues to be a well-­ regarded qualification and technology practices within higher education need not be a continuum of the practice outside it, so perhaps the politics of higher education are largely untroubled: Marginson (2013) argues, ‘Graduates are not rewarded in labour markets for knowledge but for private goods: vocationally specific skills and the brand of the degree certificate’ (p. 362). As long as universities continue to issue the branded certificates they can do a job satisfactorily for their stakeholders. Universities prepare students for employability and also enhance their skills. Employers state they want students who can think for themselves but if that were to happen across the board in western societies they would get warehouse workers for online retailers who might start to think about why their toilet breaks get monitored. Powerful, incumbent universities will withstand disruption because of their reputation and resources. High-end universities will continue to serve premium, niche markets, as expensive sports cars do. Less established universities are vulnerable to the first waves of disruption. Moreover, their current assets, large buildings in urban centres, could turn out to be future liabilities: Byrne and Clarke (2020) argue, ‘as online learning becomes more prevalent, there will probably be a reducing correlation


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between success and size’ (p. 227), a process which could be accelerated if health pandemics or other unforeseen crises curtail student mobility. The 2020 Corona virus pandemic highlights how seemingly entrenched and secure practices and business models are inherently vulnerable. A contextual lurch can force change. Face-to-face university tuition may have to be scaled down. Online provision may become the norm, not an add-on. The challenge is to reimagine technology-enhanced learning to reflect the dominance of the online medium in a sector prone to inertia. If the pedagogy does not change, fault lines in traditional provision may be opened as technology gets used to prop up an entrenched mode of higher education learning and teaching, a mode which predates technology-­enhanced learning. The soporific experience of sitting in front of a screen for an hour long lecture will not inspire students’ enthusiasm and engagement. Traditional higher education pedagogy thwarts innovation but practice with technologies can cause innovation, and if more technology-enhanced learning is happening the opportunities for innovation increase. A crisis is also an opportunity and invitation to change and innovate, catalysing and incubating new practices and new technologies. If a disruptor did not attempt to immediately attack powerful incumbents but established itself at the lower end of higher education provision, it could grow to such an extent that it would come to the attention of the well-established universities. If, by that stage, the momentum lay with the disruptor, the incumbents would have a problem. Universities often see themselves in competition with providers in the same sector of the higher education market and are unlikely to be alert to the emergence of a low-cost, disruptive competitor. Kumar (2006) argues this is an error because low-cost rivals can force incumbents to vacate entire market segments. This is the classic dilemma of disruptive innovation (Christensen, 1997). The presence of disruption steers incumbents to the most profitable areas of its business at the high end, but in so doing the incumbent cedes further ground and the disruptor grows. A disruptive provider could cater to people who would not ordinarily access higher education at all. It would not have to aim for international students paying the highest fees. Established universities might simply ignore such a provider and meanwhile the disruptor would grow.

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Many universities adopt a supermarket model, offering exhaustive selection and high volume. If market competition intensified because of a disruptive entrant it would not be possible for universities to subsidise loss-making programmes, which would lead to more specialisation in the higher education market. In this way, a disruptor could change the entire higher education market over time, achieving Disruptive Innovation. A consequence of Disruptive Innovation in higher education is that, ‘concepts like merger and acquisition … will be part of our ordinary lives’ (Moccia, 2016, p. 29), as established providers respond and attempt to consolidate their strength. Mergers and acquisitions enable incumbents to buy innovation. However, if established providers retreat upmarket they will vacate other sections of the market, creating more opportunity for disruptions. Moccia (2016) further argues, ‘the next battles will be fought with financial officers in the frontline’ (p. 30), the unavoidable outcome of privatised, monetised systems. Moccia (2016) predicts the future for higher education: ‘The next battle will be with new players, the majority of them previously unknown. New companies/universities are coming out every day, thanks to the fact they do not need facilities’ (p. 34). In response, incumbents will have the option of collaboration or of acquisition, but in so doing they will simply be reflecting the fact that the Disruptive University has changed higher education. From a more sceptical perspective, Ferreira et al. (2020) write of, ‘an inevitable “innovative” future that will only reproduce the past, albeit in a different guise’ (p. 56). The label of innovation can be applied to any number of goods and services but actual innovation is a question of practice. Goods and services can market themselves as innovative in order to solve perceived (not necessarily authentic) problems in higher education but calling something innovative does not make it so. Innovation, specifically Disruptive Innovation, is measurable in ground-up practice and in wider market consequences. Established universities are a barrier to innovation because they have long-established values and practices. Significant Disruptive Innovation in higher education is more likely to take place in a less-established or new higher education provider where it can be hardwired into organisational culture. Tapper and Filippakou (2009) argue powerful incumbents in higher education, ‘have to offer an appealing product … a carefully


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landscaped campus, elegant buildings with upmarket facilities, support for an extensive range of cultural and sporting activities, well-paid faculty … and all kept going by a well-functioning, and inevitably expensive, administrative apparatus’ (p. 61). Disruptive innovations in higher education will need to think differently about how higher education can be experienced, turning opponents’ assets into cost liabilities: Byrne and Clarke (2020) note the existence of, ‘university facilities that are wasted and empty for half the year’ (p. 59). An innovator without facilities to build and maintain could achieve an immediate and substantial cost saving. Vriens and Søilen (2014) argue, ‘a business may be disrupted if its existing products or services are expensive, difficult to access and/or may not be convenient … a first indicator is the degree to which a business provides expensive and inaccessible products/services’ (p. 72). Perhaps, in order to be attractive to fee-paying students, universities are already starting to practise product overshoot, making themselves vulnerable to a disruptor in the low end of the market. The organisational design of the traditional university includes physical spaces, timetabled classes and academic staff whose expertise is evident in qualifications and research output. A remote provider with no premises could supply higher education at a fraction of the cost. Because classes would not be timetabled, with all necessary learning materials available on demand, the offer may well be attractive to individuals who can match neither their lifestyles nor their prior educational attainments (nor their finances, for that matter) to the demands of the existing higher education system. Allen and Farber (2018) argue success in higher education is related to time spent on campus, but technology means a student does not have to be on campus to learn. Academic success does not have to depend on physical space. Higher education providers can conceive of the disruptive use of technology as a threat or an opportunity. For established universities in expensive premises, the prospect of a competitor undercutting their business model through technology is threatening. However, the use of technologies in education is a fact that needs to be recognised, and it further needs to be recognised that technology usage has become all-pervasive. Students and lecturers mediate aspects of their experience through technologies, be that through finding resources, accessing class materials, or

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submitting assignments. Many students also rely on technologies to mediate their social lives. Ultimately, for universities’ business models, Disruptive Innovation should not be feared, not least because most disruptions create economic growth, starting new markets and attracting new customers (Gilbert & Bower, 2002). Higher education is a longstanding ecosystem characterised by providers of established reputation and esteem. In order for a disruptive innovator to succeed in higher education it may need to cooperate with the status quo at least as much as it disrupts it, achieving a market share rather than posing an existential threat. Universities’ entrenched perceptions will shape their responses to Disruptive Innovation but if they recognise opportunity as much as threat they will be better placed to engage constructively with technologies and use them to enhance their provision, be that in disruptive or sustaining terms. The presence of a successful disruptive provider in the higher education market could compel universities to raise their game through the reformulation of threat as an opportunity to improve performance, building on their incumbent assets including substantial premises and services beyond the qualification. Kim and Min (2015) argue, ‘incumbent assets provide potential for better performance, but translating it into improved performance also requires a certain opportunity to realize that potential, which managerial choices provide’ (p. 52, emphasis in original). For an established university to raise its game without increasing costs, however, would be challenging, especially if a disruptor was offering significantly cheaper provision. Zhao, Fisher, Lounsbury, and Miller (2017) argue, ‘institutional legacies can provide resources for incumbents that compensate for their technical inefficiency or lack of adaptability, enabling them to survive threats from new entrants’ (p. 103). The Swiss watchmaking industry was able to use the symbolic capital of its history and reputation to counter quartz watches. Older universities have strong institutional legacies which strengthen their market position, but not to the point of unassailability. A truly technology enhanced curriculum can position students as producers, using technologies to construct their own arguments and artefacts, based on their own findings and rooted in existing scholarship. However, transformation on this scale requires a technology-informed


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rethink of assessment, which means rethinking teaching practices, too. This will be difficult, not least because of misalignment between different members of academic communities. Governing councils and other sovereign bodies at institutions want universities to produce a surplus and climb league tables. It can, therefore, be difficult to persuade senior management at universities to invest in innovation because an innovation that goes wrong is a threat to both revenue and reputation. However, students do use non-institutional, disruptive technologies to get jobs done. They use Google and Wikipedia in preference to costly institutional resources such as academic databases. Furthermore, students are increasingly time-­ poor; more and more students are having to work as well as study in order to buy their higher education in privatised systems and they will use technologies that save time. It may be going too far to suggest, as Hayes (2015) does, ‘Universities are now non-places that simply act like transit points’ (p. 276), but time-poor students in part-time or full-time employment cannot take full advantage of the social facilities on campus. Lecturers are also under time pressures and have to support large numbers of students. Innovation happens but at senior levels it may be ignored, or subsumed under impressive-sounding strategies which, themselves, creak under examination, their internal contradictions exposed. The gap between official proclamation and day-to-day practice deepens the fracture between different strata within academic communities. Google and Wikipedia are established technologies in higher education, if not always officially sanctioned, but new technologies are constantly arising, and practice with them creates the ongoing potential for innovation, notwithstanding the seeming indomitability of the existing, hierarchical higher education sector. If we want relevant twenty-first century curricula we have to accept the centrality of technologies in learning and teaching, including the widespread use of Google and Wikipedia and the widespread use of Bring Your Own Device, the latter a complex practice illustrating both self-­ determination on the part of students and the transfer of costs to the individual in an increasingly privatised system. Google and Wikipedia both work as technologies in higher education because of their ease of use, convenience, simplicity, and because they are free to use. Similar technologies will meet with similar success.

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As well as the question of how Disruptive Innovation in higher education takes place, there is a related question: who are the change makers? Patterns of Disruptive Innovation indicate the innovators are a small cohort at first, whose practices spread as they are shown to be useful to a wider constituency. Disruptive Innovation starts small but ends up transforming practices and sweeping away incumbents who fail to see and act upon changing conditions. Technology has not disrupted higher education. Not yet. Switch it off. Switch it on again.

References Abernathy, W. J., & Clark, K. B. (1985). Innovation: Mapping the winds of creative destruction. Research Policy, 14(1), 3–22. Acs, Z. J., & Audretsch, D. B. (1988). Innovation in large and small firms: An empirical analysis. The American Economic Review, 78(4), 678–690. Allen, J., & Farber, S. (2018). How time-use and transportation barriers limit on-campus participation of university students. Travel Behaviour and Society, 13, 174–182. Anadon, L. D., Chan, G., Harley, A. G., Matus, K., Moon, S., Murthy, S. L., & Clark, W. C. (2016). Making technological innovation work for sustainable development. Proceedings of the National Academy of Sciences, 113(35), 9682–9690. Ashill, N., Semaan, R. W., & Williams, P. (2019). Measuring brand charisma: An exploratory study of luxury brand consumers. In 2018 Annual Meeting of the Decision Sciences Institute Proceedings, March, 1074–1093. Retrieved from Benner, M.  J. (2007). The incumbent discount: Stock market categories and response to radical technological change. Academy of Management Review, 32(3), 703–720. Brackin, R. C., Jackson, M. J., Leyshon, A., & Morley, J. G. (2019). Taming disruption? Pervasive data analytics, uncertainty and policy intervention in disruptive technology and its geographic spread. ISPRS International Journal of Geo-Information, 8(1), 34. Retrieved from https://www.mdpi. com/2220-9964/8/1/34.


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Brockmann, T., Stieglitz, S., & Cvetkovic, A. (2015). Prevalent business models for the apple app store. In 12th International Conference on Wirtscha ftsinformatik, 4–6 March, 1206–1221, Osnabrück, Germany. Retrieved from wi2015 Byrne, E., & Clarke, C. (2020). The university challenge: Changing universities in a changing world. Harlow: Pearson. Chan, J. (2013). A suicide survivor: The life of a Chinese worker. New Technology, Work and Employment, 28(2), 84–99. Chan, J., Pun, N., & Selden, M. (2013). The politics of global production: Apple, Foxconn and China’s new working class. New Technology, Work and Employment, 28(2), 100–115. Christensen, C. M. (1997). The innovator’s dilemma: When new technologies cause great firms to fail. Harvard: Harvard Business School Press. Christensen, C. M., & Raynor, M. E. (2003). The innovator’s solution: Creating and sustaining successful growth. Boston: Harvard Business School Press. Christensen, C. M., Raynor, M., & McDonald, R. (2015). What is disruptive innovation? Harvard Business Review, 93(12), 44–53. Christensen, C. M., & Tedlow, R. S. (2000). Patterns of disruption in retailing. Harvard Business Review, 78(1), 42–45. Clarke, T., & Boersma, M. (2017). The governance of global value chains: Unresolved human rights, environmental and ethical dilemmas in the apple supply chain. Journal of Business Ethics, 143(1), 111–131. Collier, R.  B., Dubal, V.  B., & Carter, C.  L. (2018). Disrupting regulation, regulating disruption: The politics of Uber in the United States. Perspectives on Politics, 16(4), 919–937. Culpepper, P. D., & Thelen, K. (2020). Are we all Amazon primed? Consumers and the politics of platform power. Comparative Political Studies, 53(2), 288–318. Currah, A. (2007). Hollywood, the Internet and the world: A geography of disruptive innovation. Industry and Innovation, 14(4), 359–384. Denning, S. (2016). Can new disruption research suggest defenses against threats and opportunities for innovators? Strategy and Leadership, 44(3), 3–8. Downes, L., & Nunes, P. (2013, March). Big-Bang Disruption. Harvard Business Review, pp. 44–56. Eaton, B., Elaluf-Calderwood, S., Sørensen, C., & Yoo, Y. (2011). Dynamic structures of control and generativity in digital ecosystem service innovation: The

8  Conclusion: Switch It Off, Switch It on Again—Reimagining… 


cases of the Apple and Google mobile app stores (Vol. 44, pp. 1–25). London: London School of Economics and Political Science. Elbanna, A., & Newman, M. (2016). Disrupt the disruptor: Rethinking ‘disruption’ in digital innovation. In MCIS 2016 Proceedings, 58. Retrieved from Ellis, A., & Marshall, M. T. (2019). Can skeuomorphic design provide a better online banking user experience for older adults? Multimodal Technologies and Interaction, 3(3), 63. Retrieved from https://www.mdpi. com/2414-4088/3/3/63/htm. Emejulu, A., & McGregor, C. (2019). Towards a radical digital citizenship in digital education. Critical Studies in Education, 60(1), 131–147. Esposito, A. (2013). Neither digital or open. Just researchers: Views on digital/ open scholarship practices in an Italian university. First Monday, 18(1) Retrieved from view/3881/3404. Ferreira, G.  M. D.  S., Rosado, L.  A. D.  S., Lemgruber, M.  S., & Carvalho, J. D. S. (2020). Metaphors we’re colonised by? The case of data-driven educational technologies in Brazil. Learning, Media and Technology, 45(1), 46–60. Flavin, M., Zhou Chen, T., & Quintero, V. (2019). Size matters: An analysis of UK higher education institution mission statements. Journal of Higher Education Policy and Management, 42, 1–15. Retrieved from https://www. Fosnacht, K., McCormick, A. C., & Lerma, R. (2018). First-year students’ time use in college: A latent profile analysis. Research in Higher Education, 59(7), 958–978. Friedman, G. (2014). Workers without employers: Shadow corporations and the rise of the gig economy. Review of Keynesian Economics, 2(2), 171–188. Garel, G. (2015). Lessons in creativity from the innovative design of the swatch. Technology Innovation Management Review, 5(7), 34–40. Garrison, G. (2009). An assessment of organizational size and sense and response capability on the early adoption of disruptive technology. Computers in Human Behavior, 25(2), 444–449. Gawer, A., & Cusumano, M.  A. (2014). Industry platforms and ecosystem innovation. Journal of Product Innovation Management, 31(3), 417–433. Gilbert, C., & Bower, J. L. (2002). Disruptive change: When trying harder is part of the problem. Harvard Business Review, 80(5), 94–101. Gillespie, T. (2010). The politics of ‘platforms’. New Media & Society, 12(3), 347–364.


M. Flavin

Glasmeier, A. (1991). Technological discontinuities and flexible production networks: The case of Switzerland and the world watch industry. Research Policy, 20(5), 469–485. Gobble, M. M. (2018). The importance of management innovation. Research-­ Technology Management, 61(6), 54–58. Hagel, J., Eckenrode, J., & Srinivas, V. (2016). Patterns of disruption: Impact on wholesale banking. Deloitte University Press. Retrieved from https://www2. Hagel, J., Seely Brown, J., Wooll, M., & de Maar, A. (2016). Turn products into product platforms; providing a foundation for others to build upon. Deloitte University Press. Retrieved from focus/disruptive-strategy-patterns-case-studies/disruptive-strategy-productplatforms.html. Hall, R., & Bowles, K. (2016). Re-engineering higher education: The subsumption of academic labour and the exploitation of anxiety. Workplace: A Journal for Academic Labor, 28, 30–47. Hang, C. C., & Garnsey, E. W. (2011, March). Opportunities and resources for disruptive technological innovation (Working Paper). Centre for Technology Management. Retrieved from papers.cfm?abstract_id=1923036 Hargadon, A. B., & Douglas, Y. (2001). When innovations meet institutions: Edison and the design of the electric light. Administrative Science Quarterly, 46(3), 476–501. Hayes, S. (2015). A sphere of resonance for networked learning in the ‘non-­ places’ of our universities. E-Learning and Digital Media, 12(3–4), 265–278. Hellström, T. (2004). Innovation as social action. Organization, 11(5), 631–649. Holtham, C., & Courtney, N. (2005). Virtual learning environments: Practitioner perspectives on good practice. London: The Observatory on Borderless Higher Education. Retrieved from details?id=48. Hopp, C., Antons, D., Kaminski, J., & Oliver Salge, T. (2018). Disruptive innovation: Conceptual foundations, empirical evidence, and research opportunities in the digital age. Journal of Product Innovation Management, 35(3), 446–457. Isaac, E. (2014). Disruptive innovation: Risk-shifting and precarity in the age of Uber, Berkeley Roundtable on the International Economy (Working Paper No. 2014–7). Retrieved from

8  Conclusion: Switch It Off, Switch It on Again—Reimagining… 


Jones, C. R. (2014). The politics of networked learning in an age of austerity. In Proceedings of the 9th international conference on networked learning. Retrieved from Kahl, S. J., & Grodal, S. (2016). Discursive strategies and radical technological change: Multilevel discourse analysis of the early computer (1947–1958). Strategic Management Journal, 37, 149–166. Kalman, Y. M. (2014). A race to the bottom: MOOCs and higher education business models. Open Learning: The Journal of Open, Distance and e-­Learning, 29(1), 5–14. Kim, S. K., & Min, S. (2015). Business model innovation performance: When does adding a new business model benefit an incumbent. Strategic Entrepreneurship Journal, 9(1), 34–57. Kimble, C., & Bourdon, I. (2013). The link among information technology, business models, and strategic breakthroughs: Examples from Amazon, Dell, and eBay. Global Business and Organizational Excellence, 33(1), 58–68. King, A. A., & Baatartogtokh, B. (2015). How useful is the theory of disruptive innovation? MIT Sloan Management Review, 57(1), 77–90. Knox, J. (2019). What does the ‘postdigital’ mean for education? Three critical perspectives on the digital, with implications for educational research and practice. Postdigital Science and Education, 1(2), 357–370. Kumar, N. (2006). Strategies to fight low-cost rivals. Harvard Business Review, 84(12), 104–112. Kumar, N. (2014). Facebook for self-empowerment? A study of Facebook adoption in urban India. New Media & Society, 16(7), 1122–1137. Kushida, K. E. (2015). The politics of commoditization in global ICT industries: A political economy explanation of the rise of Apple, Google, and industry disruptors. Journal of Industry, Competition and Trade, 15(1), 49–67. Langer-Crame, M., Newman, T., Beetham, H., Killen, C., & Knight, S. (2019). Digital experience insights survey 2019: Findings from students in UK further and higher education. Bristol: JISC. Laurell, C., & Sandström, C. (2016). Analysing Uber in social media— Disruptive technology or institutional disruption? International Journal of Innovation Management, 20(5), 1640013. Retrieved from https://www. Laurillard, D., & Kennedy, E. (2017). The potential of MOOCs for learning at scale in the global south. London: Centre for Global Higher Education. Retrieved from


M. Flavin

Lave, J., & Wenger, E. (1991). Situated learning: Legitimate peripheral participation. Cambridge: Cambridge University Press. Leitch, T. (2014). Knowledge, authority and liberal education in the digital age. Baltimore: Johns Hopkins University Press. Leitner, K.  H. (2017). ‘No’ and ‘slow’ innovation strategies as a response to increased innovation speed. In B. Godin & D. Vinck (Eds.), Critical studies of innovation: Alternative approaches to the pro-innovation Bias (pp. 201–217). Cheltenham: Edward Elgar. Linton, J. D. (2009). De-babelizing the language of innovation. Technovation, 29(11), 729–737. Litzinger, R. (2013). Labor in China: A new politics of struggle. Special Issue of South Atlantic Quarterly, 112, 172–212. Loveday, V. (2018). The neurotic academic: Anxiety, casualisation, and governance in the neoliberalising university. Journal of Cultural Economy, 11(2), 154–166. Manokha, I. (2018). Surveillance: The DNA of platform capital—The case of Cambridge analytica put into perspective. Theory & Event, 21(4), 891–913. Marginson, S. (2013). The impossibility of capitalist markets in higher education. Journal of Education Policy, 28(3), 353–370. Markides, C., & Charitou, C. D. (2004). Competing with dual business models: A contingency approach. Academy of Management Executive, 18(3), 22–36. Markides, C., & Sosa, L. (2013). Pioneering and first mover advantages: The importance of business models. Long Range Planning, 46, 325–334. Metcalf, J., & Moss, E. (2019). Owning ethics: Corporate logics, silicon valley, and the institutionalization of ethics. Social Research: An International Quarterly, 86(2), 449–476. Moccia, S. (2016). Managing educational reforms during times of transition: The role of leadership. Higher Education for the Future, 3(1), 26–37. Mohan, K., Ramesh, B., Cao, L., & Sarkar, S. (2012). Managing disruptive and sustaining innovations in green IT. IT Professional, 14(6), 22–29. Montoya, J. S., & Kita, T. (2017). Towards an improved theory of disruptive innovation: Evidence from the personal and mobile computing industries. In The Asian Conference on the Social Sciences 2017: Official Conference Proceedings, 125–144. Retrieved from 4/223404cb3c27efee6e3e5e670bb3c5a4d81d.pdf Muller, E. (2019). Delimiting disruption: Why Uber is disruptive, but Airbnb is not. International Journal of Research in Marketing, 37(1), 43–55. https://

8  Conclusion: Switch It Off, Switch It on Again—Reimagining… 


Nair, A., & Ahlstrom, D. (2003). Delayed creative destruction and the coexistence of technologies. Journal of Engineering and Technology Management, 20, 345–365. Neves, J., & Hillman, N. (2019). Student academic experience survey 2019, advance HE and higher education policy Institute. New  York and Oxford. Retrieved from Student-Academic-Experience-Survey-2019.pdf Newman, T., Beetham, H., & Knight, S. (2018). Digital experience insights survey 2018: Findings from students in UK further and higher education. Bristol: JISC. Norman, D.  A., & Verganti, R. (2014). Incremental and radical innovation: Design research vs. technology and meaning change. Design Issues, 30(1), 78–96. O’Reilly, C., & Binns, A. J. M. (2019). The three stages of disruptive innovation: Idea generation, incubation, and scaling. California Management Review, 61(3), 49–71. O’Reilly, C., & Tushman, M. L. (2011). Organizational ambidexterity in action: How managers explore and exploit. California Management Review, 53(4), 5–22. Paap, J., & Katz, R. (2004). Anticipating disruptive innovation. Research-­ Technology Management, 47(5), 13–22. Pascale, R. T. (1984). Perspectives on strategy: The real story behind Honda’s success. California Management Review, 26(3), 47–72. Peddiwell, J.  A. (2004 [1939]). The Saber-tooth curriculum. New  York: McGraw Hill. Piketty, T. (2017). Capital in the twenty-first century (A. Goldhammer, Trans.). Cambridge, MA: Harvard University Press. Pun, N., & Chan, J. (2013). The spatial politics of labor in China: Life, labor, and a new generation of migrant workers. South Atlantic Quarterly, 112(1), 179–190. Qiu, J.  L., Gregg, M., & Crawford, K. (2014). Circuits of labour: A labour theory of the iPhone era. tripleC: Communication, Capitalism & Critique. Open Access Journal for a Global Sustainable Information Society, 12(2), 564–581. Raffaelli, R. (2019). Technology reemergence: Creating new value for old technologies in Swiss mechanical watchmaking, 1970–2008. Administrative Science Quarterly, 64(3), 576–618.


M. Flavin

Rahman, K. S., & Thelen, K. (2019). The rise of the platform business model and the transformation of twenty-first-century capitalism. Politics and Society, 47(2), 177–204. Reinhardt, R., & Gurtner, S. (2018). The overlooked role of embeddedness in disruptive innovation theory. Technological Forecasting and Social Change, 132, 268–283. Richardson, J., Wardale, D., & Lord, L. (2019). The ‘double-edged sword’ of a sessional academic career. Higher Education Research and Development, 38(3), 623–637. Rosenbloom, R. S., & Christensen, C. M. (1994). Technological discontinuities, organizational capabilities, and strategic commitments. Industrial and Corporate Change, 3(3), 655–685. Rutter, R., Roper, S., & Lettice, F. (2016). Social media interaction, the university brand and recruitment performance. Journal of Business Research, 69, 3096–3104. Salter, M.  S. (2005). Innovation corrupted: The rise and fall of Enron (A). Harvard Business School case 905–048, December 2004 (revised October 2005). Retrieved from aspx?num=31813 Sandoval, M. (2013). Foxconned labour as the dark side of the information age: Working conditions at Apple’s contract manufacturers in China. TripleC: Communication, Capitalism & Critique, 11(2), 318–347. Selwyn, N. (2013). Digital technologies in universities: Problems posing as solutions? Learning, Media and Technology, 38(1), 1–3. Selwyn, N. (2014). Digital technology and the contemporary university. Abingdon: Routledge. Shang, T., Miao, X., & Abdul, W. (2019). A historical review and bibliometric analysis of disruptive innovation. International Journal of Innovation Science, 11(2), 208–226. Slater, S.  F., Mohr, J.  J., & Sengupta, S. (2014). Radical product innovation capability: Literature review, synthesis, and illustrative research propositions. Journal of Product Innovation Management, 31(3), 552–566. Söderberg, J. (2017). Comparing two cases of outlaw innovation: File sharing and legal highs. In B. Godin & D. Vinck (Eds.), Critical studies of innovation: Alternative approaches to the pro-innovation bias (pp. 115–132). Cheltenham: Edward Elgar.

8  Conclusion: Switch It Off, Switch It on Again—Reimagining… 


Sood, A., & Tellis, G.  J. (2011). Demystifying disruption: A new model for understanding and predicting disruptive technologies. Marketing Science, 30(2), 339–354. Srnicek, N. (2016). Platform capitalism. Cambridge: Polity. Srnicek, N. (2017). The challenges of platform capitalism: Understanding the logic of a new business model. Juncture, 23(4), 254–257. Tang, P., & Bussink, H. (2017). EU tax revenue loss from Google and Facebook. PvdA, S&D.  Retrived from uploads/2018/03/EU-Tax-Revenue-Loss-from-Google-and-Facebook-2.pdf Tapper, T., & Filippakou, O. (2009). The world-class league tables and the sustaining of international reputations in higher education. Journal of Higher Education Policy and Management, 31(1), 55–66. Tellis, G. J. (2006). Disruptive technology or visionary leadership? The Journal of Product Innovation Management, 23, 34–38. Temple, P. (2009). From space to place: University performance and its built environment. Higher Education Policy, 22(2), 209–223. The Economist. (2015, November 26). Disrupting Mr disrupter. Retrieved from disrupting-mr-disrupter Thelen, K. (2018). Regulating Uber: The politics of the platform economy in Europe and the United States. Perspectives on Politics, 16(4), 938–953. Vidal, E., & Mitchell, W. (2013). When do first entrants become first survivors? Long Range Planning, 46, 335–347. Vriens, D., & Søilen, K. S. (2014). Disruptive intelligence: How to gather information to deal with disruptive innovations. Journal of Intelligence Studies in Business, 4(3), 63–78. Wenger, E. (1998). Communities of practice: Learning, meaning, and identity. Cambridge: Cambridge University Press. Wessel, M., & Christensen, C.  M. (2012, December). Surviving disruption. Harvard Business Review. Retrieved from surviving-disruption Yoffle, D. B., & Kwak, M. (2002). Mastering balance: How to meet and beat a stronger opponent. California Management Review, 44(2), 8–24. Zeide, E., & Nissenbaum, H. (2018). Learner privacy in MOOCs and virtual education. Theory and Research in Education, 16(3), 280–307. Zhao, E. Y., Fisher, G., Lounsbury, M., & Miller, D. (2017). Optimal distinctiveness: Broadening the interface between institutional theory and strategic management. Strategic Management Journal, 38, 93–113.


M. Flavin

Zhu, F., & Furr, N. (2016, April). Products to Platforms: Making the Leap. Harvard Business Review, pp. 72–78. Zuboff, S. (2015). Big other: surveillance capitalism and the prospects of an information civilization. Journal of Information Technology, 30(1), 75–89. Zuboff, S. (2019). The age of surveillance capitalism: The fight for a human future at the new frontier of power. New York: PublicAffairs. Zysman, J., & Kenney, M. (2016). The next phase in the digital revolution: Platforms, abundant computing, growth and employment. The Research Institute of the Finnish Economy. Retrieved from sites/default/files/brie-working-paper-2016-35.pdf