Doing Business In A Digital World 9781845443269, 9781845443252

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19/07/2005

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ISBN 1-84544-325-X

ISSN 0885-8624

Volume 20 Number 4/5 2005

Journal of

Business & Industrial Marketing Doing business in a digital world Guest Editor: Angela Hausman

www.emeraldinsight.com

Journal of Business & Industrial Marketing Volume 20, Number 4/5, 2005 ISSN 0885-8624

Doing business in a digital world Guest Editor: Angela Hausman

Contents 158

Access this journal online

159

Guest editorial

160

Capitalizing on the internet opportunity George S. Day and Katrina J. Bens

169

179

The role of information technology in supply-chain relationships: does partner criticality matter? Daekwan Kim, S. Tamer Cavusgil and Roger J. Calantone Collaborative supply-chain partnerships built upon trust and electronically mediated exchange Niklas Myhr and Robert E. Spekman

187

Critical factors affecting intermediary web site adoption: understanding how to extend e-participation Tina Harrison and Kathryn Waite

200

Cooperative adoption of complex systems: a comprehensive model within and across networks Angela Hausman, Wesley J. Johnston and Adesegun Oyedele

211

Inter-organisational collaboration for the digital economy Elizabeth Houldsworth and Gillian Alexander

218

An empirical framework developed for selecting B2B e-business models: the case of Australian agribusiness firms Eric Ng

226

A decision-support system for business-to-business marketing Behrooz Noori and Mohammad Hossein Salimi

237

Why doesn’t marketing use the corporate data warehouse? The role of trust and quality in adoption of data-warehousing technology for CRM applications Fay Cobb Payton and Debra Zahay

245

Creating digital value: at the heart of the I-E-I framework Tim Foster

253

Executive summary and implications for managers and executives

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and Spekman then discuss the role of electronic communication in mediating supply chain relationships to create value for the chain. The article by Dr Tina Harrison and Ms Kathryn Waite looks at adoption of website technology within a supply chain context. Combining both qualitative and quantitative approaches, the study provides guidance for firms in their efforts to increase the use of websites by financial services supply chains. The final paper in this section was written by Drs Hausman and Johnston, and Mr Oyedele. This paper looks at coordination between firms in a network using the adoption of inter-organizational systems, such as electronic data interchange, as an exemplar. The next set of articles looks at different digital technologies and explores how these technologies have been used to improve firm effectiveness. Drs Houldsworth and Alexander explore the role digital communication plays in facilitating collaboration between virtual teams. Drawing on the learning literature, the study takes a qualitative approach with the interesting finding that teams prefer face-to-face encounters over those that are electronically mediated. Dr Ng next provides tools for selecting e-business models in the context of Australian agribusinesses. The use of decision support systems in business-to-business markets was the topic of the study by Drs Noori and Salimi. This study integrates the important areas of decision support systems with customer relationship management. This dovetails well with the paper written by Drs Payton and Zahay. Their study also explores customer relationship management from the perspective of identifying factors contributing to its under-utilization by the marketing group despite frequent use of the data warehouse by finance and other functional groups. The final paper, by Dr Tim Foster, looks at the use of extranets to create value for business-tobusiness firms. The primary driver of value in this context is not only the value taken out by the firms, but the value put into the extranet by member firms. In sum, these articles provide both theoretical and practical perspectives on the use and utility of various digital technologies in creating business value. I hope you find the articles as insightful and useful as I did. Angela Hausman

Guest editorial About the Guest Editor Angela Hausman is currently an Assistant Professor of Marketing at the University of Texas-Pan American. She holds a PhD from the University of South Florida and an MBA from the University of Pittsburgh. Her publications span both consumer behavior and business-to-business marketing and have appeared in a number of scholarly journals, including the Journal of the Academy of Marketing Science, Industrial Marketing Management, Journal of Business Research, Journal of Services Marketing, and Journal of Consumer Marketing. In addition, she has made presentations at national and international conferences, such as AMA, ACR, and AMS. She is currently working predominantly in the areas of the internet, health care, and international marketing.

I am very happy to have been asked to act as guest editor for this special issue dealing with digital technologies in businessto-business markets. It was a pleasure to see the variety of approaches researchers are taking to understand factors impinging on the rapidly changing landscape of technology. The multi-national perspective provided by these researchers makes this issue particularly valuable. I am confident their findings will provide guidance for industrial firms as they move forward. The first set of articles in this series dealt with utilization of information technology by firms as both a marketing tool and a means to manage their supply chains effectively. The first, by Dr George Day and Ms. Katrina Bens, reports the value business-to-business firms find in using the Internet to help achieve their goals. Not only have firms been able to avoid adverse consequences, such as channel conflict, they have seen the Internet help them leverage existing competencies. Echoing this, Drs Kim, Cavusgil, and Calantone discuss the benefits information technology has on firm performance within the context of supply chain relationships. Drs Myhr

Journal of Business & Industrial Marketing 20/4/5 (2005) 159 q Emerald Group Publishing Limited [ISSN 0885-8624]

159

Capitalizing on the internet opportunity George S. Day Mack Center of Technological Innovation and Emerging Technologies Management Research Program, The Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania, USA, and

Katrina J. Bens Department of Business Administration, University of Illinois, Urbana Champaign, Illinois, USA Abstract Purpose – To investigate how business-to-business (B2B) firms view the opportunities and threats of the internet and determine which firms are most likely to gain from the internet. Design/methodology/approach – A nation-wide survey of marketing, sales and MIS managers in B2B firms provides the data necessary to explore the impact of the internet. Findings – Managers view the internet positively as it will reduce customer service costs and allow firms to tighten relationships with customers. The positive potential outweighs the negative potential of increased competition and new pricing models. However, not all will benefit. Practical implications – While there is much optimism about the internet, those most likely to benefit are those firms already proficient at forging close customer relationships. Originality/value – This paper provides lessons about who will benefit from the internet. Keywords Customer relations, Internet, Business-to-business marketing Paper type Research paper

a threat nor an opportunity. To better understand these overall judgments we also asked them about 15 possible consequences of the internet for customer relationships. Overall the internet was judged to offer opportunities to reduce customer service costs, while tightening customer relationships by encouraging dialogue, linking more parts of customer contact and enabling the personalization of communications. Fears of channel conflict, price wars and new business models disrupting their markets have been overshadowed by these opportunities. However, a closer look at the results reveals that this optimistic interpretation is potentially misleading, and that most firms won’t realize the expected benefits. Instead the gains will likely go to the firms that were already proficient at forging close customer relationships.

An executive summary for managers and executive readers can be found at the end of this issue.

Capitalizing on the internet opportunity Opinions about the impact of the internet on customer relationships have evolved along three lines. Some firms still hold to the view that prevailed in the 1990s, that the resulting market transparency would cause margins to shrink and loyalty to become even more transient (Porter, 2001). As firms gained experience with the internet, some replaced their anxiety with enthusiasm over the possibilities for cutting customer service costs while tightening connections with customers. More recently, a revisionist argument has been made that digital technologies – and especially the internet – offer only limited advantages because the applications are readily copied (Carr, 2003). Persuasive evidence that most business-to-business (B2B) firms have been able to use the internet to leverage existing advantages and avoid the adverse consequences of increasing market transparency come from our survey of 165 senior managers on the impact of the internet on their ability to manage customer relationships. We found that 25 percent saw the internet as a major opportunity whereas only one percent saw it as a major threat. A further 57 percent saw the internet as a minor opportunity and only 13 percent said it was neither

How the data were collected A representative sample of senior marketing, sales, and MIS managers and executives was drawn using a database combining information from Dun & Bradstreet and Market Place. SIC codes were selected from the manufacturing, transportation, public utilities, wholesale and retail trade, finance, insurance and real estate sectors. Companies located in all 50 states with more than 500 employees were included in the sample. The questionnaire was mailed to the most senior person responsible for customer relationship management (CRM) initiatives who was also knowledgeable about the competitive strategy and performance of the firm. The cover letter explained how to access the questionnaire on the web if the participant preferred. The web survey was password protected and designed to look as similar as possible to the paper survey. Two weeks after the mailing, follow-up telephone calls were used to remind people to complete the survey and surveys were remailed if requested. 1,100 surveys were sent out in the first mailing, and a second wave was sent out about four weeks later to 900 new contacts. The two mailings had similar response rates and the final response rate was 17 percent with 24 percent of respondents choosing to complete the survey via the internet. Data collection was completed in March 2001. There were no significant differences between the firms that responded compared to the sample frame in their industry, number of employees and geographic location. The majority of businesses were B2B (at 54 percent) while 24 percent were business to consumer (B2C) and 22 percent sold to both B2B and B2C markets. This paper is based on the 165 respondents from the B2B portion of the sample. Early respondents were compared to late respondents. Of the 100 variables in the survey, only two showed a statistically significant difference for early and late respondents, less than

The Emerald Research Register for this journal is available at www.emeraldinsight.com/researchregister The current issue and full text archive of this journal is available at www.emeraldinsight.com/0885-8624.htm

Journal of Business & Industrial Marketing 20/4/5 (2005) 160–168 q Emerald Group Publishing Limited [ISSN 0885-8624] [DOI 10.1108/08858620510603837]

160

Capitalizing on the internet opportunity

Journal of Business & Industrial Marketing

George S. Day and Katrina J. Bens

Volume 20 · Number 4/5 · 2005 · 160 –168

threat,” and the other end with “major opportunity,” with the middle point being “no impact.”

what one would expect by chance at the 5 percent level. There were no statistically significant differences between the internet and paper forms of the survey. Although the firms in the sample all had more than 500 employees, we asked respondents to answer from the perspective of a specific business unit or division competing in a distinct market. Thus 20 percent of these businesses had less than 500 employees, 67 percent had between 500 and 4,999 employees and 12 percent had more than 5000 employees. The selection criteria tilted the respondents toward marketing and/or sales management so they made up 78 percent of the sample. Another 8 percent were in general management and the majority of the remainder were in technology management.

Opportunities and threats from the internet To address this issue we first asked how closely the 15 specific consequences were correlated with the overall judgment of the managers about the impact of the internet on customer relationships. These multiple regression results with standardized coefficients are reported in Table II[3]. The main conclusion is that the threats had very little influence on the overall judgment of the impact of the internet on customer relationships. Conversely the perceived opportunities to reduce service costs, link customer contact points within the firms, and encourage feedback and dialogue with customers were very influential.

Because the strategies of these relationship leaders emphasize connecting with customers, and their organizations are already aligned to this priority, they will use the internet to enhance their advantage. To help B2B companies assess whether they are likely to gain, stay where they are, or fall behind in the competition for customer relationships, we have extracted three lessons: 1 relationship leaders will leverage the internet to stretch their lead; 2 the transformative impact of new market models has been modest; and 3 the internet will complement the existing channels.

Reducing customer search costs Just because customers can search more widely, compare more readily and eliminate some of their transaction costs on the internet doesn’t mean they will actually defect. Indeed only four percent of B2B firms saw this factor as a major threat, while 10 percent said it was a major opportunity. More than a third saw neither threat not opportunity – in deference to the reality that most customers don’t actually search very much. Firms in B2B markets appear to believe they can turn the reduction in customer search costs to their advantage. These suppliers appear to believe that customers they don’t currently serve will be able to find them more readily, and then they have a good chance of being chosen on their merits. At the same time they have confidence their current customers will stay with them even after they have considered new sources.

Identifying the consequences of the internet This study began with a content analysis of 90 articles and 12 books[1] on the internet; paying particular attention to forecasts and expectations about how the internet would influence the ability of firms to manage their customer relationships. For our purposes CRM was defined as a crossfunctional process for achieving a continuing dialogue with customers, across all their points of contact and access with the business, with personalized treatment of the most valuable customers, to increase customer retention and the effectiveness of marketing initiatives. This definition recognizes that the ability to have a dialogue with customers is an essential ingredient of all CRM initiatives. The intent is to integrate information from diverse sources such as direct sales, telesales, websites, customer service, resellers and channel partners, to arrive at a coherent picture of the customer and to be able to better serve that customer[2]. The internet could be either a threat or opportunity, depending on whether it disrupted or facilitated: the process of understanding customers, engaging in a dialogue with them, and improving the service offering; the balance of information and bargaining power between buyers and sellers; or the ability of present and prospective competitors to improve their position and increase the rate of defection. We coded over 25 ostensibly different consequences of the internet. Our preliminary list of hypothesized consequences of the internet was refined in five stages. First, we interviewed senior managers in 12 large companies including GE Capital, Dow Chemical, and Verizon Information Services, to learn how they were using the internet and how they viewed its disruptive potential. Second, we conducted three separate pretests with 90 representative managers to identify ambiguities, and eliminate overlaps in the items. This latter step was facilitated by an orthogonal factor analysis to identify consequences that were highly correlated. In such cases we combined and rewrote the items. The final set of 15 items is shown in Table I, along with a comparison of the results for the B2B sample and a smaller group of B2C companies. We used a five-point scale, anchored at one end with “major

Prospects for connecting and personalizing There was a considerable enthusiasm for using the internet to tighten customer relationships. Between 32 and 43 percent of all B2B respondents saw major opportunities to: . encourage customer feedback and dialogue; . facilitate linking more points of customer contact (which is the central appeal of CRM); and . permit the personalization of marketing messages. These results are at odds with criticisms that efforts to use the internet to personalize customer relationships are misguided, because nothing can match person-to-person communications. In this jaundiced view, the efforts to extract patterns in clickstream data, then make predictions based on past behavior, and construct deep customer profiles to guide personalized marketing messages will continue to stumble over software problems, consumer indifference and privacy concerns (Usborne, 2001). While these criticisms do sting, they overlook the experience of best practice companies who have learned how to use the internet. For example, the internet has already pushed deeply into business markets ranging from commodity chemicals (see the indented text below on Myaccount@dow) to expensive, mission-critical items like power transformers and diagnostic-imaging devices. Radiologists using GE’s CT scanners and MRI machines can go to the internet and try out new GE software that increases the efficiency of spinal exams. If they like what they see they can order the software for $65,000 (Colvin, 2001). They are likely to make the purchase 161

Capitalizing on the internet opportunity

Journal of Business & Industrial Marketing

George S. Day and Katrina J. Bens

Volume 20 · Number 4/5 · 2005 · 160 –168

Table I Judging the impact of the internet on customer relationships Major threat (%)

Minor threat (%)

No impact (%)

Minor opportunity (%)

Expands set of competitors B2B 9 50 29 10 B2C 8 37 29 20 Increases channel conflict B2B 7 33 54 4 B2C 6 6 77 11 Facilitates customers switching B2B 6 38 41 13 B2C 3 35 30 30 Enables customers to conduct reverse auctions B2B 7 31 46 14 B2C 0 11 86 3 Customers can form buying groups to get quantity discounts B2B 6 27 55 12 B2C 1 8 84 5 Prices can be changed rapidly B2B 7 19 55 17 B2C 1 9 72 12 Customers are able to propose prices B2B 4 14 67 13 B2C 3 14 78 5 Customers can learn what other customers are thinking B2B 2 18 47 28 B2C 3 12 36 38 Increases “stickiness” – makes it harder for customers to switch B2B 1 11 55 22 B2C 0 11 58 23 Reduces customers’ search costs B2B 4 10 34 41 B2C 1 11 39 28 Customers can design products to their specific requirements B2B 0 1 49 35 B2C 0 4 57 28 Reduces customer service costs because customers can self-serve B2B 0 1 36 38 B2C 0 7 44 32 Permits the customization of marketing messages B2B 0 3 16 49 B2C 1 7 8 32 Encourages customer feedback and dialogue B2B 0 2 12 47 B2C 0 5 7 35 Facilitates linking more points of customer contact B2B 0 2 13 42 B2C 1 5 4 36 Overall, what is the effect of the internet on your ability to manage customer relationships? B2B 1 4 13 57 B2C 1 4 13 49

Major opportunity (%)

Average scorea

2 7

2.47 2.80


1 0

2.59 2.94


1 3

2.64 2.85


1 0

2.71 2.92


1 1

2.76 2.97


2 5

2.88 3.11


1 0

2.93 2.86

5 11

3.16 3.42


10 8

3.29 3.28

10 20

3.45 3.55

14 11

3.62 3.45

25 17

3.87 3.60


32 52

4.10 4.27

38 53

4.21 4.36

43 53

4.25 4.35

25 33

4.01 4.08

Notes: Number of responses and percent of responses by question. Totals may not equal 100 percent due to rounding error. a “Average score” was computed by averaging the responses where major threat ¼ 1, minor threat ¼ 2, no impact ¼ 3, minor opportunity ¼ 4, major opportunity ¼ 5.
Mean difference at 0.05 (using a two-tailed t-test)

about 65 percent of the time without ever talking to a salesperson.

was organized; rigid and siloed. But customers really wanted an easy one stop source of information, assistance and ordering. For example; to get spec sheets on products, customers had to call Dow and request specific specification sheets. These were then mailed to the customers. A few days later, upon receiving the spec sheets, the customer might realize the products

Myaccount@dow Before the internet, customers had to deal with Dow Chemical the way Dow

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Capitalizing on the internet opportunity

Journal of Business & Industrial Marketing

George S. Day and Katrina J. Bens

Volume 20 · Number 4/5 · 2005 · 160 –168

Table II Explaining the overall influence of the internet on the firm’s ability to manage customer relationships

with “Congratulations! You’ve been pre-approved.” In the paper world, the prescreen process involves departments such as credit screening, marketing, creative agencies, fulfillment, plastic embossing and so on, with abundant places for delay and error. This paper process has been converted to a very fast and low cost, web-enabled sequence of activities so a customer can connect via a modem to make a purchase and establish credit in one seamless process. Skeptics about the internet believe that most of the prospective cost savings will be captured by customers because their bargaining power has been enhanced (Porter, 2001). Indeed, in the respondents view two of the biggest threats were “expanding the competitive set” and “facilitates customers switching,” both of which are accepted indicia of customer bargaining power. Nine percent of the B2B respondents said their firms were seriously threatened because there were more competitors who would undermine longstanding relationships or be used by their customers as bargaining chips to push down the price level. But when we put these two threats into the broader context of all threats and opportunities we found they had little relationship with the overall judgment of the consequences of the internet. As shown in Table II, the coefficients of these variables in the regression equation are not significant, which means that while the threat from more competitors and easier switching can be ignored, the prospects of price pressure are far outweighed by the other benefits. Similarly, the potential threats from auctions and buying groups were found to be symptoms of deeper underlying problems. For example, the seven percent who were seriously threatened by customers initiating reverse auctions were invariably in mature markets with few differences among competitors, or lacking close relationships with their key customers. One manager at a large detergent chemical maker shared the poignant tale of a long-standing and seemingly loyal customer who abruptly announced they were preparing a reverse auction to open up the business to more suppliers. This supplier was assured they would be invited to bid and would be favorably considered – so long as they were price competitive! Perhaps an auction was inevitable, but the fact they were taken by surprise suggests they weren’t very close to their customer, nor were they perceived as a supply partner.

Independent variables (listed in order of importance) Intercept Encourages customer feedback and dialogue Customers can propose prices Reduces customer service costs Customers’ search costs are reduced Permits customization of marketing messages Prices can be changed quickly Enables customers to conduct auctions Expands set of competitors Increases channel conflict Increases “stickiness” Customers can form buying groups Facilitates customers switching Customers can custom-design products Facilitates linking customer contact points Customers can learn from one another

Parameter estimates (t-value) 0.002 0.378 0.256 0.243 0.237 0.111 0.065 0.056 0.029 0.007 20.001 20.013 20.017 20.021 20.024 20.074

(0.038) (3.93)
(3.59)
(3.46)
(3.4)
(1.2) (0.96) (0.85) (0.44) (0.11) (2 0.02) (2 0.17) (2 0.25) (2 0.3) (2 0.24) (2 1.05)

Notes: R2ADJ ¼ 0:473;
¼ p , 0:001

weren’t exactly what they needed. Then, they would have to call back (during business hours, of course) to request more sheets. Now, with Dow.com, 24 hours a day, customers can log onto the site, search spec sheets and print and/or download all those that interest them. No longer is the information gathering process a multi-day task which may involve several iterations. Instead, when a customer needs information, it is immediately available and accessible. During 2000, Dow estimated that they were saving approximately $1 million per month in printing and mailing costs by having customers serve themselves. Myaccount@dow provides more personalized account servicing and is being piloted and developed with a subset of customers. The account allows customer specific information to be accessed by the customer and Dow. For instance, myaccount@dow allows secure internet monitoring of customer chemical tank levels. When tanks reach predetermined levels, reordering can be automatically triggered.

For some firms the personalization of interactions and communications is a step on the road to using the internet to help customers to custom design products to their specific requirements (Wind et al., 2001; Pine, 1992). Despite the appeal of “mass customization,” only 14 percent of the respondents saw this as a major opportunity, while 35 percent viewed it as a minor opportunity. What explains this hesitancy? Another question in the survey found that 57 percent of B2B respondents thought it was very or somewhat difficult to tailor or mass customize the product or service offer in their market. Perhaps this is a reflection of the difficulties of designing a manufacturing or service operation with highly flexible processes that can cost-effectively produce individualized offerings.

When and why is the internet an opportunity? What explains the varying levels of enthusiasm for the internet? In particular, what distinguishes the firms that saw the internet as a major opportunity from the others? Was it because their market environments were especially conducive, or were they better equipped to exploit the opportunities than their rivals? In fact we found both factors were at work. The following sets of variables were used in the multiple regression equation in Table III[4], where the dependent variable was the overall judgment about the internet: 1 Attributes of the market: . growth rate of the total market; . loyalty of customers in the market; . customer perceptions of differences among competitive alternatives; and . ability of customers to judge the quality of the product or service on the web. 2 Attributes of the firm. These were grouped into three categories:

The promise of efficiency gains The size of the opportunity to reduce customer service costs (because customers could self-serve) was the third most important determinant of the overall judgment about the internet. This reflects a noticeable shift of the goals of CRM projects from revenue enhancement to cost containment. GE Capital’s Card Services division has harnessed the internet to improve the efficiency of pre-approved direct mail, one of the core customer acquisition processes it offers to its retail clients. These are the credit offers that try to entice you 163

Capitalizing on the internet opportunity

Journal of Business & Industrial Marketing

George S. Day and Katrina J. Bens

Volume 20 · Number 4/5 · 2005 · 160 –168

broader channel systems. These results were especially valuable in extracting useful lessons for managers.

Table III When and why is the internet an opportunity? Independent variables Intercept Market share rank Total number of channels Loyalty of customers Customer-relating capability Focus of strategy Number of customers Customer perceptions of differences Market growth rate Number of employees Ability to judge quality on net Use of CRM software CRM initiatives

Parameter estimates (t-values) 2 0.015 0.212 0.200 0.168 2 0.166 2 0.124 0.109 2 0.098 0.072 2 0.046 0.036 0.018 0.012

(20.20) (2.52)

(2.36)

(2.07)
(21.78)
(21.35) (1.31) (21.2) (0.89) (20.57) (0.47) (0.02) (0.13)

Lesson 1: relationship leaders will leverage the internet to extend their lead Who is going to gain and sustain an advantage in the customer-empowered, competitive markets that are being reshaped by the internet? The message from our study is that those who already excel at managing customer relationships were best equipped to capitalize on the opportunities of the internet[5]. These leaders were able to anticipate earlier how to use the internet to connect with their customers, exploited it faster and implemented the initiative better. Relationship leaders are the 17 percent of firms who judged themselves to have a significant advantage over their rivals in their ability to manage customer relationships. In summary, the internet offers the best opportunities for firms that have the necessary conditions in place. If the culture condones a transactional mind-set and is not equipped to treat different customers differently, the systems and databases are incomplete, incompatible and out-of-date, and the organization is balkanized along hierarchical lines so teams struggle to collaborate, and the incentives don’t reward retention, then the internet should deservedly be feared. These transactional firms don’t have any strategic degrees of freedom, and the internet means they will lose further control. Conversely, best-of-breed relationship builders like Dell, FedEx, Schwab, Fidelity, Singapore Airlines, L.L. Bean, Recreational Equipment Inc., and Pioneer Hi-Bred Seeds relish the prospects presented by the internet.

Notes: Dependent variable ¼ Overall, what is the effect of the internet on your ability to manage customer relationships? R2ADJ ¼ 0:10;
¼ p , 0:05;

¼ p , 0:01

.

.

.

Strategy and capabilities: – focus of strategy on delivering superior value through close customer relationships; and – capability in developing and managing customer relationships relative to competitors. Prowess with CRM technology: – utilization of CRM software to coordinate customer communications, interactions and service support activities; and – progress with CRM initiative compared to direct competitors. Demographics: – market share; and – number of employees.

Lesson 2: the transformative impact of new market models is modest At the peak of internet enthusiasm it seemed anything was possible, and that the old rules for reaching and serving markets were about to be overturned. Extravagant pronouncements about the possibilities for reverse auctions, open exchanges, buying groups, infomediaries and nameyour-own price models captured the collective imagination. One reason these forecasts had credence was that no one had any meaningful experience they would use to appraise the claims. Now we have the experience and the myths have been dispelled. Our results confirm what others have found; these models have limited or negligible roles in most markets. None of the new market models was judged to be a major threat by more than seven percent of the B2B respondents. The reasons the fears of established firms have abated differ for each of the internet market models, but the net effect is that they are having little impact on customer-supplier relationships.

A further correlate was the total number of channels used by the firm because the number available is an attribute of the market and the number used is a strategic choice. The main story from the multiple regression analysis, using all these variables, is that the overall judgment about the impact of the internet on customer relationships mainly depends on the number of channels, the market share rank, whether the customers are loyal, and the customer relating capability. The assessment of the customer relating capability was based on a reverse coded questions asking “Overall, how does your business compare with your competitors in developing and managing relationships with valuable customers” on a scale where 1 ¼ significant advantage and 5 ¼ significant disadvantage. To learn what set apart the 25 percent of firms that saw the internet as a major opportunity for strengthening customer relationships we next used a continuous ratio logit model to compare this group with the rest of the sample, using a reduced set of variables. The results in Table IV show that those who see the greatest opportunity are: much better at managing customer relationships than their rivals; and have a lower market share rank which suggests that smaller firms see the internet as a way to easily add another channel to reach their customers and close the gap with larger rivals with

Infomediaries Many have been disabled by unexpected barriers that incumbents had long learned to live with. These constraints serve as isolating mechanisms that impede competitive moves. Protected niches within a market – stemming from longstanding relationships or regulations designed to protect some players in a value chain – are among the signals of these killer constraints. These signals were frequently downplayed by ecommerce challengers during the optimism of the boom period: 164

Capitalizing on the internet opportunity

Journal of Business & Industrial Marketing

George S. Day and Katrina J. Bens

Volume 20 · Number 4/5 · 2005 · 160 –168

Table IV Which B2B firms see the internet as a major (minor) opportunity (continuous ratio logit analysis)? Independent variable Customer-relating capability Market share rank Focus of strategy Customer perceptions of differences

Major opportunity vs rest ðn 5 160Þ


Minor opportunity vs no impact or threat ðn 5 121Þ 0.31 2 0.21 0.22 0.08

20.47 0.39
20.38
0.12

Note:
¼ p , 0:05

.

.

.

.

model, which many people believed would become the dominant model for pricing, but is now seen as another variation on well-established pricing formulas. Their approach works well with airline tickets because accurate, timely information about the best prices is hard to get, and the seats must be sold before the fight. But customers must be willing to put up with the inconvenience of not being able to choose their airline or time of day they will fly. These conditions are less likely to apply to B2B firms, so 67 percent of them didn’t see any impact.

The on-line auto infomediaries like Autobytel, Auto Web, and Cars.com, face restrictive state-level regulations that bar anyone from clinching the sale. Some states go further to require a new car buyer to pick-up their car at a dealership. Without the ability to make a sale the online buying services are left with only the revenues from lead generation for dealers. VerticalNet.com created a diverse e-marketplace in areas that ranged from aerospace technology to pulp and paper. Suppliers were provided with a customizable platform that allowed them to quickly get their products and services on line, while buyers were able to easily find multiple supply options. After a high of $148/share, VerticalNet.com stock is trading at about $1.25/share. In a search for profitability, the company has shifted its focus to software for automating business activities with suppliers. While the concept of Brandwise.com, a comparisonshopping website for appliances was appealing, it was unable to overcome two killer constraints. Up to 80 percent of sales to consumers of appliances are immediate replacements of broken units, leaving no time or inclination for careful comparison-shopping. Another impediment was the inability of geographically dispersed and incompatible retail systems to communicate inventory status or fulfill orders. The existing system had long adapted to these rigidities and had little incentive to change. Pure play online pharmacies’ were hobbled by the relationship of pharmaceutical benefit managers (PBMs) and pharmacies with major employers and health plans. These were never opened up. Further constraints were the unwillingness of consumers to wait for their prescription to be delivered so they could begin treatment, and hesitations about credit card security and sharing of their personal information.

Reverse auctions This auction format is called “reverse” because sellers bid rather than buyers, and prices are bid down instead of up. While they have always existed, their utility has been greatly enhanced by the internet, and as of 2002 about 15 percent of all firms were using them (Hannon, 2002). Further growth is coming from expanding the scope from products to services as varied as television ads and janitorial services. At the peak of the dot.com enthusiasm, this auction format was thought to be a major threat because it enabled customers to extract significant prices concessions. For some B2B firms, this was the case. We found 7 percent of the sample viewed auctions as a major threat, while another 31 percent saw them as a minor threat (and almost no one saw an opportunity). While reverse auctions can be used for short-term price savings, evidence from other studies suggests that the threat is not greater because purchasers have realized that continuously pressing for deeper price concessions might backfire and, in fact, inhibit collaboration (Jap, 2003). If margins are continually reduced, suppliers might be forced to exit the market or consolidate. A smaller base of suppliers could then lead to increase in supplier power. Public exchanges These exchanges attempted to insert themselves in the channel at the strategic point when customers decide who to buy from, how much to buy, and how much they will spend. As payment for matching buyers and sellers through electronic networks, on-line exchanges attempted to charge fees to sellers ranging from two to five percent of gross sales. Yet the vast majority of industrial suppliers are still independent distributors and dealers who continue to thrive due to their great skill at maintaining high levels of locally delivered customer service and support[6]. Although the fees the exchanges wanted to charge appeared low, they were more than 50 percent of a typical distributor’s net margin. Competition quickly lowered these transaction fees to marginal cost – or lower. Some exchanges saw transaction fees drop to as low as one-quarter of one percent, which was not enough to cover operating and capital expenses. Customers were also reluctant to disrupt systems that work,

The nature of on-line interactions imposes further constraints. Many products are unsuitable because their quality or reliability cannot be readily described or communicated in digital terms (Figueredo, 2000). There are inherent delays in navigating sites, finding information and making choices that are exacerbated by the volume of information and plethora of options. The lack of human contact eliminates opportunities for clarification, problem solving, reassurance and negotiation. These limitations don’t negate the internet, but often relegate it to a supportive and subordinate role in a market. Pricing models The internet made radically new pricing schemes possible, which encouraged start-ups to adopt pricing structures that departed greatly from traditional industry practice. The most famous example is the Priceline “name-your-own- price” 165

Capitalizing on the internet opportunity

Journal of Business & Industrial Marketing

George S. Day and Katrina J. Bens

Volume 20 · Number 4/5 · 2005 · 160 –168

even if those systems are partially uneconomic or somewhat inefficient. This is particularly true when the stakes are high, such as business customers that must procure supplies to keep factories and offices running without disruption or downtime. Exchanges looked promising because customers in most B2B channels face enormous procurement and inventory costs. On-line systems that could reduce these costs and improve efficiencies held great promise. But exchanges misdiagnosed their relative advantage. During the past ten years, industrial customers have been improving the efficiency of their supply chain by consolidating supply contracts and reducing the number of suppliers. A supplier that can lower a customer’s total cost of acquisition is preferred over one that simply offers a lower price. Many B2B exchanges went against these fundamental trends by emphasizing the lowest price instead of lowest total procurement cost. Prospects for pure play B2B exchanges were further dimmed with the advent of industry-wide exchanges created by consortia of bricks-and-mortar companies who could provide both financial strength and guaranteed volume. But even these consortia are sometimes supplanted by private B2B systems (Bloch and Catfolis, 2001; MacDuffie and Helper, 2003). One likely scenario is that each industry will have one or two public exchanges to help buyers and sellers find each other, with subsequent transactions taking place on private networks where logistics can be optimized. A few specialized exchanges will be available to conduct auctions or offer specialized financing and logistics services.

Managing channel proliferation Even before the internet arrived, companies were under pressure to serve their customers with more varied channels. With new toll-free services, companies added call centers at a rapid rate during the past decade. New composite channel designs were devised to divide up the channel functions. Instead of each channel performing all the functions the immediate customer requires, a team of channel partners, each specializing in a few tasks, satisfies the customer’s total needs. The supplier might negotiate the sale, while the partners take over order fulfillment, distribution and aftersales service (Anderson et al., 1997). This proliferation of channels and customer contact points poses acute synchronization problems. Customers also don’t limit themselves to a single channel; instead they pick the one that is most convenient or effective for the situation. But they also assume the firm will recognize them at each step of the way. When they place an order via the internet they expect call-center records to be updated, inventory information to be consistent across channels, and that they can return goods to the store. The internet plays two roles: it is a rich and interactive channel that complements existing channels, and the digital architecture enables the connection and synchronization of all channels. This is why the firms with the most channels are also the most enthusiastic about the internet (see Figure 1). Managing channel conflict Many channel members resisted the internet at first, because of the perceived threat of disintermediation. Airlines took the lead by selling tickets directly to passengers. Automakers thought they had found a cost-effective way to go around their dealers. Proponents of disintermediation also forecast the demise of real estate agents when home buyers could search, negotiate and buy houses on the internet. This prospect attracted a swarm of start-ups to the home buying arena. It is instructive that most have failed – but a few are thriving because they help agents by serving as a lead generation vehicle. Realtor.com lists over 1.4 million homes for sale, and directs inquiries to a local agent who takes over the relationship building part of the sales cycle. Realtor.com also develops customized web sites for agents, and helps them sell related services such as mortgages. In this way the two channels complement each other[7]. Because the internet has been so thoroughly co-opted and integrated into existing channels most of the concerns about conflict have dissipated. Even the minority of 7 percent of the sample who saw the internet as a major threat because it increased channel conflict, didn’t let that dampen their enthusiasm. We found no relationship between their judgment

Lesson 3: the internet complements other channels Two opposing forces have been contending to shape how companies view the impact of the internet on their distribution channels. On one side the net was welcomed as another way to reach existing customers, a new way to find new customers and a solution to the vexing question of how to synchronize proliferating channels. In opposition was the fear that the internet would encourage disintermediation and incite more channel conflict. With experience the fear factor has somewhat abated. While only seven percent of our sample viewed the internet as a serious threat because of increasing channel conflicts, another 33 percent saw a minor threat. However it is more than an additional channel. When used creatively it enhances all the other channels: call center employees with net-based CRM systems deliver better service, bricks-and-mortar stores using new location-based services are found by more customers, and sales people equipped with mobile devices have more information and tools available during their sales calls. Companies have so embraced the internet that is has become the most widely used channel. While 97 percent have direct sales forces, and 56 percent use direct mail to reach their markets, we found that already 85 percent are using web-site access and/or email. This rate of adoption is a testament to the adhesive powers of the internet. Most companies use a variety of channels, depending on the type of market. Firms in B2B markets used an average of 4.7 channels, while B2C firms used 4.2 channels out of nine possible ways to reach markets. Those that served both consumer and business markets used an average of 5.5 channels to serve more diverse customer segments.

Figure 1 Influence of number of channels

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about channel conflict and their overall judgment about the impact of the internet on customer relationships.

leads, sales blames marketing for not generating enough leads and service blames them both for too-high expectations, the promise of the CRM technology will not be realized. By some estimates 55 percent of all CRM projects will disappoint[8]. The stakes are considerable given that CRM systems may cost $35,000 or more per call-center agent to deploy and that much again to maintain them during the next three years. It will take strong leadership including the assignment of a senior manager to spearhead the initiative, cross-functional structures and collective incentives to motivate the functions to work together and ensure a return on this investment. Finally, we have learned it doesn’t pay to be paralyzed by channel conflict. Customers prefer a choice of channels and expect all channels including the internet to work together. To achieve this synchronization the place to start is a deep understanding of what the target customers want from the channel system, and then work back to assess how well the current channels meet those needs. The next step is to decompose the entire set of channel functions into their component parts. Only then is it possible to see where digital channels best fit; are they better than what is available for generating leads, or providing an online storefront or aggregating demand via hubs like Commerce One? Such an approach to integrating the internet into the channel system is far better than bolting it on as a separate channel. An integrative approach to digitally enhancing channels requires the same level of cross-functional coordination as CRM initiatives that use the internet to coordinate all customers touch points. Indeed, competitive advantage comes by integrating and aligning the internet with the overall strategy; and doing so better and faster than the competition.

Applying the lessons The new conventional wisdom is that most firms will find that the efficiency-boosting benefits of the internet will be offset by the margin-deflating effects of reduced market friction and enhanced buyer power. Furthermore, only a few firms will use the net to create unique and lasting advantages. Like all simplifications there is an element of truth here, but it also distorts the full picture. Instead of pessimism and fear we found enthusiasm across all markets. A large majority of our respondents saw more opportunity than threat, and 25 percent saw the internet as a major opportunity. These firms have embraced the net for a variety of reasons, but mainly to keep up with rivals and leverage their existing capabilities. Consequently the internet is now the most popular means of reaching and interacting with customers. But the biggest lesson is that the rewards of increased customer retention, growth and profitability will go only to those who are already the most proficient at managing their relationships with their most valuable customers. Only with a superior capability can a firm fully exploit the potential to tighten connections with better service, remember customer histories and requirements to deliver personalized solutions, and improve the synchronization of dispersed points of customer contact. This has several messages for firms trying to catch up or stay ahead. First, the technology of the internet is only a tool; it is not a competitive strategy or the capability to deliver the strategy. Thus the starting point is to know how well your capability compares to your rivals ( both where they are now and where they are going to be based on their intentions, plans and observed actions. Don’t rely solely on your sales and service people. Instead, go directly to the best and most demanding customers and ask for a frank assessment. Be sure to ask about their best suppliers who are not competitors and learn how they manage their customer relating capability. These “best of breed’ are worth benchmarking because they set the standard by which customer expectations are formed. Second, assess the quality of the present customer relationships. Are the most valuable customers really committed to the firm, or are their connections merely passive because of habit and inertia? This is the context for assessing whether internet-enabled services based on new market models such as reverse auctions or emerging technologies such as broadband and mobility will strengthen or undermine existing relationships. This is especially important in B2B markets with complex organizational buying processes. Suppliers who built close relationships with purchasing agents during a supplier reduction program are especially vulnerable. The threat often comes from senior management, who may overrule purchasing and impose a reverse auction to get lower prices. The third implication is that the success of initiatives to deploy the internet and CRM technologies are more about organizational alignment than data base management, systems integration and software selection. Internet-enabled CRM has to be managed as a cross-functional initiative that deepens the overall capability. This is especially so in organizations where functional divisions and interests prevail. If marketing historically blames sales for not closing

Notes 1 Representative sources are Greenberg (2001), and Siebel (2000). 2 See also McKenzie (2000), Sawhney and Zabin (2001), Imhoff et al. (2001) and Peppers and Rogers (1995). 3 To assess the risk of multicollinearity we conducted a varimax factor analysis of the 15 items in Table I. Five factors accounted for 47 percent of the variance – and only three variables held together on one factor. Because the intercorrelations were not high among these variables (customization of marketing messages, linking points of customer contact and encouraging customer feedback) we elected to keep them separate in the multiple regression analysis to facilitate interpretation. Additionally, we calculated the variance inflation factor (VIF) of each variable. VIFs with value over 10 are evidence of problems with multicollinearity. In this case, all values were below 2.0, which further suggests that multicollinearity is not a problem. 4 To determine if multicollinearity was a problem with the regression in Table III, we calculated the VIF of each variable. In this case, none of the VIFs were close to 10. In fact, all were under 2, showing that multicollinearity is not a problem. 5 This concept of capabilities is derived from the resourcebased theory of the firm. See Barney (1991), Collis and Montgomery (1995) and Mintzberg et al. (1998). 6 This discussion benefited greatly from Fein (2000, 2001). 7 Sawhney and Zabin (2001) describe in detail several models for the synchronization of channels to reallocate 167

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George S. Day and Katrina J. Bens

Volume 20 · Number 4/5 · 2005 · 160 –168

Hannon, D. (2002), “E-procurement adoptions progress slowly and steadily”, Purchasing Magazine Online, June 20, available at: www.purchasing.com/article/CA221936. html?text ¼ hannon Imhoff, C., Loftis, L. and Geiger, J.G. (2001), Building the Customer-Centric Enterprise, Wiley, New York, NY. Jap, S.D. (2003), “An exploratory study of the introduction of online reverse auctions”, Journal of Marketing, Vol. 67, pp. 96-107. MacDuffie, J.P. and Helper, S. (2003), “B2B and mode of exchange: evolutionary and transformative effects”, in Kogut, B. (Ed.), The Global Internet Economy, MIT Press, Cambridge, MA, p. 536. McKenzie, R. (2000), The Relationship-Based Enterprise, McGraw-Hill, New York, NY. Mintzberg, H., Ahlstrand, B. and Lampel, J. (1998), Strategy Safari, Free Press, New York, NY. Peppers, D. and Rogers, M. (1995), Enterprise One-to-One, Doubleday, New York, NY. Pine, B.J. (1992), Mass Customization: The New Frontier in Business Competition, Harvard Business School Press, Cambridge, MA. Porter, M.E. (2001), “Strategy and the internet”, Harvard Business Review, Vol. 79, pp. 62-79. Sawhney, M. and Zabin, J. (2001), Seven Steps to Nirvana, McGraw-Hill, New York, NY. Siebel, T. (2000), How to Become an eBusiness, Siebel Systems, San Mateo, CA. Usborne, N. (2001), “The death of permission”, Business 2.0, p. 72. Wind, Y., Mahajan, V. and Gunther, R.E. (2001), Convergence Marketing: Strategies for Reaching the New Hybrid Consumer, Prentice-Hall, Upper Saddle River, NJ. Yu, L. (2001), “Successful customer relationship management”, Sloan Management Review, Summer, pp. 18-19.

the functions and flows across the entire spectrum of available channels of which the internet is only one channel. 8 These data were from a Gartner, Inc. study cited in Caulfield (2001). Their conclusions are more measured than those of other surveys reported in Yu (2001).

References Anderson, E., Day, G.S. and Rangan, V.K. (1997), “Strategic channel design”, Sloan Management Review, Vol. 38, pp. 59-70. Barney, J.B. (1991), “Firm resources and sustained competitive advantage”, Journal of Management, Vol. 16, pp. 99-120. Bloch, N. and Catfolis, T. (2001), “B2B e-marketplaces: how to succeed”, Business Strategy Review, Vol. 12, pp. 20-8. Carr, N.G. (2003), “IT doesn’t matter”, Harvard Business Review, p. 27. Caulfield, J. (2001), “Facing up to CRM”, Business 2.0, August/September, pp. 149-50. Collis, J.B. and Montgomery, C.A. (1995), “Competing in resources: strategy in the 1990s”, Harvard Business Review, Vol. 73, July/August, pp. 118-28. Colvin, G. (2001), “Shaking hands on the internet”, Fortune, Vol. 143 No. 10, p. 54. Fein, A.J. (2000), “E-business realities for distribution channels”, Progressive Distributor, November. Fein, A.J. (2001), Facing the Forces of Change: Future Scenarios for Wholesale Distribution, National Association of Wholesalers, Washington, DC. Figueredo, J.M. (2000), “Finding sustainable profitability in electronic commerce”, Sloan Management Review, Vol. 41, pp. 41-52. Greenberg, P. (2001), CRM at the Speed of Light, McGrawHill, New York, NY.

168

The role of information technology in supply-chain relationships: does partner criticality matter? Daekwan Kim Florida State University, Tallahassee, Florida, USA, and

S. Tamer Cavusgil and Roger J. Calantone Michigan State University, East Lansing, Michigan, USA Abstract Purpose – There have been contradictory findings in the literature regarding the impact of information technology (IT) on firm productivity. While the debate known as the “IT paradox” still endures, there has been little empirical research to clarify why or when IT offers benefits to the owning firms. This study attempts to fill this gap in the literature by investigating when IT contributes to firm performance. Design/methodology/approach – Using survey data, this study explores how IT adoption by a firm, in the context of supply chain communication systems, influences its market performance. Of special interest are improvements in both the firm’s own and its partner’s coordination activities. Criticality of a firm’s channel partner is used as a moderating variable. Findings – Results suggest that a firm’s own coordination mediates the influence of IT adoption on market performance only when the partner being coordinated is critical to its success. If the partner is not critical to the success of the firm, the benefits of IT adoption can be materialized only through enhancements in the coordination activities of the partner. Originality/value – The study results clarify why the assumed benefits of IT have been inconsistent in the context of supply chain relationships. Keywords Supply chain management, Communication technologies, Partners Paper type Research paper

beyond-store IT on overall store performance in their survey of retailers. Coupled with this paradox, the recent disappointing outcomes of IT investment raise questions about the vital role of IT within a firm or supply chain (Taylor, 2003). For instance, managers of some small auto part suppliers in Detroit area are pessimistic about the actual benefit of Covisint, the newly introduced electronic market forum in the automobile industry for supply chain activities, despite the recent excitement and high expectations. Although they well recognize the ultimate potential it offers, their actual experiences revealed less than what they expected. The electronic market forum was formed by few key US automakers and, subsequently, parts suppliers that are interested in doing business with those automakers were requested to join in order to have access to business opportunities. That is, through the market forum, the major automakers strive to integrate their supply chain electronically. However, it turns out to be a push by the leading original equipment manufacturers (OEMs) (Willsher, 2003). According to Willsher (2003), “suppliers, subsuppliers and sub-sub suppliers, all saw this as yet another example of the big boys forcing them to do business their way, pushing risk down the line and squeezing them on price until their automotive engineering pips squeaked.” Surrounding the same electronic forum, the actual benefits firms perceive differ drastically, depending on the perspective they take: key automakers versus part suppliers. This study explores the role of IT in channel relationships and firm performance in the context of supply chain communication systems (SCCS), seeking plausible explanations for the IT paradox in the literature. Supply

An executive summary for managers and executive readers can be found at the end of this issue. Numerous articles in the business press cast doubt on the contributions of IT to firm performance, and a number of scholars claim that the real value of IT is questionable (Baker and Abrahams, 2001; Baker and Sinkula, 1999; Brynjolfsson, 1993; Brynjolfsson and Hitt, 1998; Kettinger et al., 1994; Powell and Dent-Michallef, 1997). IT productivity has been debate since the 1970s (Brynjolfsson, 1993; Thatcher and Oliver, 2001). Some researchers report either no effect or even a negative influence of IT on firm performance (Brynjolfsson, 1993; Brynjolfsson and Hitt, 1996; Kettinger et al., 1994; Loveman, 1991; Mukherjee, 2001; Panko, 1991; Powell and Dent-Michallef, 1997; Rai et al., 1996; Roach, 1987; Strassmann, 1990). For instance, Kettinger et al. (1994) report that 24 firms out of 30 experienced negative consequences of IT investment on market share or profits within five years of IT deployment. Powell and DentMichallef (1997) also found no effect of both in-store IT and The Emerald Research Register for this journal is available at www.emeraldinsight.com/researchregister The current issue and full text archive of this journal is available at www.emeraldinsight.com/0885-8624.htm

Journal of Business & Industrial Marketing 20/4/5 (2005) 169–178 q Emerald Group Publishing Limited [ISSN 0885-8624] [DOI 10.1108/08858620510603846]

169

The role of information technology in supply chain relationships

Journal of Business & Industrial Marketing

Daekwan Kim, S. Tamer Cavusgil and Roger J. Calantone

Volume 20 · Number 4/5 · 2005 · 169 –178

chain communication system is a key element of supply chain management systems (SCMS)[1] and is defined as an information system that links channel partners in order to carry out supply chain activities such as electronic transactions, quality and cost calibration, and collaborative forecasting and planning (Bowersox et al., 1999; Roberts and Mackay, 1998; Stank et al., 1999b; Tang et al., 2001). A typical SCCS incorporates some elements of various corporate information systems within SCMS including enterprise resource planning (ERP) system, customer relationship management (CRM) system, and advanced planning (AP) system among others. One traditional element of a most typical SCCS is electronic data interchange (EDI), which have contributed to the success of an SCMS significantly (Humphreys et al., 2001; Roberts and Mackay, 1998). However, there are emerging technologies of SCCS (e.g. Radio Frequency Exchange and Satellite Technology) that are likely to play a crucial role in supply chain communication. This study explores two research questions. First, it investigates whether, and in what way, a firm’s adoption of advanced information technology influences its own and partner’s coordination activities. We assess the empirical relationship between IT as a resource and coordination activities of the firm and its partner as a firm capability. Second, we examine how IT adoption for SCCS influences firm performance through enhanced channel capabilities of the firm and its partner. With these research questions, we attempt to clarify the conditions for little or no link between IT adoption and firm performance (Andersen and Segars, 2001; Baker and Abrahams, 2001; Fisher, 2001; Loveman, 1991; Panko, 1991; Weill, 1991) and for the recent convoluted experience with IT by some firms (Taylor, 2003).

advantage because of their wide availability in the market (Barney, 1991; Powell and Dent-Michallef, 1997). Only when the information technology is embedded into organizational processes (e.g. strategy making), it is expected to offer sustainable benefits (Barney, 1991). Firm coordination Transactions are a fundamental element of supply chain relationships, and coordination activities for such transactions are crucial for efficient channel activities (Clemons and Row, 1992). Firm coordination in this study is viewed as a channel capability, and conceptualized as the extent to which a firm coordinates transactions with channel partners efficiently (Clemons and Row, 1993; Kambil and Short, 1994; Malone et al., 1987; Shin, 1999). Some researchers view coordination as a multidimensional concept that embraces not only transactions but also information sharing and performance monitoring (e.g. Stank et al., 1999a). However, this study focuses on coordination activities for transactions only, as they already reflect the quality of information sharing and monitoring activities implicitly. Typical interfirm coordination ranges from the collection of product- and price-related information such as inventory level, new product launch, and pricing, to order follow-up activities including order confirmation and shipment tracking. An SCCS with advanced IT should offer efficient coordination activities to the owning firm by either reducing coordination costs or enhancing the quality of the coordination activities at the same cost (Clemons and Row, 1992, 1993; Evans et al., 1993; Lewis, 2001; Roberts and Mackay, 1998; Steinfield et al., 1995; Wigand and Benjamin, 1995). Particularly, in the context of electronic hierarchy where a close relationship is key (Malone et al., 1987), firms should be able to improve efficiency in coordination as their IT for SCCS enhances (Clemons and Row, 1993). Shin (1999) report empirical support for the positive effect of IT on interfirm coordination. Similarly, Clemons and Row (1993) argue that “IT reduces the cost of coordination, leading firms to coordinate more” (p. 10). The literature generally contends that adoption of advanced IT helps supply chain members reduce coordination costs associated with logistics activities (Lewis, 2001; Lewis and Talalayevsky, 1997). Thus, we offer the following hypothesis: H1. IT adoption for SCCS enhances firm coordination.

The conceptual framework Adopting the basic argument of the resource-based view (RBV) of the firm, this study contends that a firm’s IT adoption for SCCS, as a firm resource, affects its own as well as partner’s coordination activities, a channel capability, that are expected to contribute to firm market performance (Barney, 1991; Collis, 1994) as shown in Figure 1. Furthermore, the extent to which a firm’s given partner is critical to the success of its business, or partner criticality, moderates the influence of IT adoption on coordination activities and on market performance. Each construct will be discussed subsequently.

Partner coordination Partner coordination refers to the extent to which the channel partner of an IT adopting firm carries out coordination activities efficiently. Interfirm coordination in a supply chain by its nature implies dyadic involvement of two channel members (Bowersox et al., 1999; Clemons and Row, 1992; Lewis and Talalayevsky, 1997). As a result, adoption of advanced IT for SCCS by a firm affects not only the adopting firm but also its channel partners because it should accompany enhancements of interfirm connectivity in SCCS (Bowersox et al., 1999; Clemons and Row, 1992) and, thus, helps all partners within the network coordinate effectively (Clemons and Row, 1992). However, the literature does not pay attention to the effect of IT adoption of a firm on the coordination activities of its channel partners within the supply chain. As a simple illustration, imagine adoption of the ATM system by a bank.

IT adoption for SCCS IT adoption for SCCS is defined as the extent to which a firm adopts the most advanced available technology for SCCS and involves proactive adoption of the state-of-art IT to build new technical solutions for SCCS. The literature discusses IT object that embraces the degree of diffusion of information technology within a firm (Tippins and Sohi, 2003). However, IT adoption in this study, a distinctive concept from IT object, assesses how actively a firm seeks to adopt new IT ahead of competitors. The literature argues that IT adoption cultivates organizational capabilities that enable the firm to outperform their competitors (Rogers et al., 1993; Tippins and Sohi, 2003). However, adoption of information technology alone may not be a source of competitive 170

The role of information technology in supply chain relationships

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Daekwan Kim, S. Tamer Cavusgil and Roger J. Calantone

Volume 20 · Number 4/5 · 2005 · 169 –178

Figure 1 Conceptual framework and hypotheses

Adoption of ATMs by a bank naturally helps enhance customer service (e.g. transactions) of the bank. At the same time, it also provides significantly improved convenience to the customers. That is, to the extent advanced technology is adopted for dyadic relationships, the benefit will be distributed across the involved parties. Likewise, in a supply chain where dyadic channel relationships prevail, adoption of advanced information technology for SCCS by a firm is expected to improve the coordination activities of its channel partners (Clemons and Row, 1992). Thus: H2. IT adoption for SCCS improves partner coordination.

H3.

Firm coordination leads to enhanced market performance.

A similar argument can be made regarding the effect of partner coordination on market performance of the focal firm. Whether it is a supplier or buyer of the firm, an enhancement in a channel partner’s coordination helps reach end-customers of the supply chain more effectively (Bowersox et al., 1999; Clemons and Row, 1992; Lewis and Talalayevsky, 1997). For instance, offering a preferred type of product to the customers right time through enhanced SCCS will help expand market share and increase sales of the supply chain (Clemons and Row, 1992; Lewis and Talalayevsky, 1997) and, thus, of the focal firm. Hence: H4. Partner coordination leads to enhanced market performance of the firm.

Market performance The firm’s market performance, the outcome variable in this study, is assessed by sales growth, market share, market development, and product development (Sarkar et al., 2001; Venkatraman and Ramanujam, 1986). It is linked to IT adoption through the influences of firm coordination as well as partner coordination. According to the literature, EDI, an IT application in SCCS, enables channel partners to be responsive to customer requests (Rogers et al., 1993). Particularly, enhanced coordination activities stemming from information technology lead to on-time delivery, efficient ordering procedures, and customer responsiveness (Stank et al., 1999a). Therefore, firm coordination is expected to contribute to its market performance (Mohr and Nevin, 1990; Stank et al., 1999a). In a similar vein, Lewis (2001, p. 7) claims that IT allows firms to engage in “large scale tracking of customer preferences,” which should be associated with coordination activities and ultimately affects firm performance. Therefore:

Partner criticality as a moderator Firms work with numerous channel partners. However, not all of them are equally critical for the success of their business (Anderson et al., 2001). According to Turnbull and Gibbs (1987), firms are likely to exchange varying amounts of business information with channel partners depending upon the role and importance of the partners, which implies that the criticality of the partner will affect coordination activities. For example, one of the managers we interviewed suggested that automakers often do not share their specific production plans with all of their tier 1 suppliers because sharing too much information with partners through coordination activities could result in leaking their core competencies (Clemons and Row, 1992). In a similar vein, Morgan and Hunt (1994, p. 22) in their empirical study report that “shared values” and “relationship benefits” perceived by 171

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channel partners influence commitment and trust between them. In other words, the criticality of the channel partner is likely to determine the other partner’s commitment to the relationship including coordination activities in an effort to strengthen the relationship (Anderson et al., 2001). Subsequently, the impact of IT adoption on coordination activities of a firm and its partner and, thus, on firm performance is expected to be a function of the criticality of the partner. However, due to lack of research attention in the literature on the issue, we are unable to identify specific links between adoption of IT for SCCS and firm market performance where partner criticality functions as a moderator. Thus, we offer the following hypotheses: H5a. The more critical its partner is to a firm, the stronger the positive influence of IT adoption on firm coordination. H5b. The more critical its partner is to a firm, the stronger the positive influence of IT adoption on partner coordination. H5c. The more critical its partner is to a firm, the stronger the positive influence of firm coordination on market performance. H5d. The more critical its partner is to a firm, the stronger the positive influence of partner coordination on market performance.

Data collection To test the proposed model empirically, we sought the opinions from corporate executives who specialized in supply chain management, logistics, or purchasing. After considering various trade associations, we contacted the Council of Logistics Managers (CLM) for cooperation and were able to obtain a mailing list of member companies located in the USA. As part of their efforts to protect the privacy of their members, the mailing list only included first and last names of members along with email addresses and their affiliation. We examined the listed individual member in an effort to exclude non-qualifying members such as consultants, freight forwarders, and third-party logistics companies. The purification process yielded a list of 1,949 qualified managers. A preliminary request for participation was sent out to those managers via email. Five managers replied back to express that they were not interested in the study. In addition, 218 emails were returned as undeliverable for various reasons, such as recipient out of office, user name not valid, or recipient no longer with the company. Of the remaining 1,726 managers who we contacted with a URL link to our websurvey, 264 responded within our self-established deadline of three weeks, yielding the effective response rate of 15.3 percent (264/1,726). For the analysis, we include 184 responses, as the remaining 80 were partially incomplete. The industry distribution of our respondents includes consumer products (17.9 percent), industrial machinery (15.8 percent), computer and communication (13.0 percent), automotive (9.2 percent), electronic and medical equipment (15.7 percent), chemical (4.9 percent), other (21.2 percent), and not reported (2.3 percent).

Methods Measures Extant measurement scales were adopted from the literature for the present study to the extent it was feasible. However, because of the exploratory nature of the study, we had to develop measures for some constructs including firm coordination, partner coordination, and partner criticality. For scale development, we primarily followed the procedure suggested by the literature (e.g. Churchill, 1979), defining each construct so that elements to be included in or excluded from its definition are clearly delineated. Then, the literature was searched for available scales. Whether newly developed or adopted from the literature, we used multiple items for each construct in an effort to increase construct reliability. Specifically, we adapted the scales for IT adoption from Gatignon and Xuereb (1997). The original scales were in the new product context and subsequently adapted into our study context. However, we developed scales for firm coordination and partner coordination using the procedure above, as no scales were available for those constructs. For market performance, scales were adopted from Sarkar et al. (2001): sales growth, market share, market development, and product development. Finally, measures for partner criticality were developed to assess the partner’s criticality in meeting customer requirements, gaining long-term benefits, and materializing the focal firm’s core competency. The instrument was carefully reviewed by several experienced researchers in supply chain management. Their feedback was incorporated before we pre-test the instrument with several supply chain managers. Comments and suggestions from those managers were carefully evaluated and reflected in the questionnaire ensuring all the items are directed to adequate managers within each organization.

Model estimation and results Nonresponse bias In general, nonresponse bias in a sample is assessed by comparing responding and nonresponding firms on the basis of firm characteristics such as sales and number of employees (Armstrong and Overton, 1977). To emulate such comparison, our responses were divided into two groups based on the date received. Then, we ran t-tests to compare the early and late groups for potential differences and found that there is no significant difference between the two groups on popular demographic variables such as annual sales ðt ¼ 0:703Þ and number of employees ðt ¼ 0:285Þ, and on our key study variable, IT adoption ðt ¼ 0:425Þ (Armstrong and Overton, 1977). In addition, to compare our respondents with nonrespondents more realistically, we compiled some demographic information of 30 managers who had opted to drop out of the survey without completing it, believing that these managers who dropped out in the middle of the survey are most likely to resemble nonrespondents. Then, their demographic information and the key IT variable were compared with those of respondents who submitted a completed survey. A series of t-tests reveals that there is no significant difference between the respondents and those who opted out of the survey on their annual sales ðt ¼ 0:706Þ, number of employees ðt ¼ 0:828Þ, number of upstream ðt ¼ 0:239Þ and downstream ðt ¼ 0:315Þ channel members, year of major information systems deployed for supply chain activities ðt ¼ 0:770Þ, and the key variable, IT adoption for SCCS ðt ¼ 0:219Þ. Therefore, it appears that nonresponse bias is not a problem. 172

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Daekwan Kim, S. Tamer Cavusgil and Roger J. Calantone

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Measurement model and construct validity To assess the adequacy of the measurement model, a confirmatory factor analysis (CFA) was carried out using EQS for Windows 5.7b. All constructs, except for partner criticality, were included in the CFA. Through a measurement purification process, items with their loading less than 0.5 were eliminated to increase convergent validity. Furthermore, using the Lagrange multiplier (LM) test, some items that were cross-linked to more than one constructs are dropped off the model to improve discriminant validity. The purification process left at least three items for IT adoption, firm coordination, and market performance. However, there are two items for partner coordination included in the final CFA model. The CFA model revealed fit indexes of x2 ¼ 139:760 on 71 degrees of freedom (df), Tucker-Lewis index ðTLIÞ ¼ 0:950, comparative fit index ðCFIÞ ¼ 0:961, standardized root mean-square residual (SRMR) of 0.048, and root mean-square error of approximation (RMSEA) of 0.071 as shown in Table I. These fit indexes indicate an excellent fit of the model with the empirical covariances (Hu and Bentler, 1999; Shook et al., 2004). With the results of CFA, we assess the unidimensionality of constructs. For convergent validity, we examined the standardized loading and its significance. For an adequate level of convergent validity, items must load on the respective constructs significantly with their loading greater than 0.5. According to the CFA results, all items load significantly on the respective factor ð p , 0:01Þ and all loadings are greater than 0.5 as shown in Table I. Thus, the CFA results indicate

an adequate level of convergent validity of each construct (Bagozzi and Yi, 1988). Second, we examined factor correlations that are expected to be significantly less than unity, and average variance extracted that should be greater than shared variances of each construct for an adequate level of discriminant validity (Fornell and Larcker, 1981). The results indicate that all correlations between constructs differed significantly from one (Bagozzi et al., 1991; Burnkrant and Page, 1982), ranging from 0.23 to 0.71 as reported in the lower triangle of Table II. In addition, we calculated average variance extracted (AVE) using the formula suggested by Fornell and Larcker (1981). As shown in Table I, AVE ranged from 0.67 to 0.74 while shared variances among constructs are between 0.05 and 0.50 as shown in the upper triangle of Table II. These reveal a good level of discriminant validity between constructs used in the study. As a final step to assess the unidimensionality of each construct, Table II Intercorrelations and shared variances

IT adoption for SCCS (F1) Firm coordination (F2) Partner firm coordination (F3) Market performance (F4)

F1

F2

F3

F5

– 0.42 0.23 0.37

0.18 – 0.71 0.42

0.05 0.50 – 0.34

0.14 0.18 0.12 –

Note: The correlations are included in the lower triangle of the matrix. The shared variances are included in the upper triangle of the matrix

Table I Measures, reliabilities, and average variance extracted Constructs

Measuresa

IT adoption for SCCS

My BU uses the most advanced IT for SCCS Our IT for SCCS is always state-of-the-art technology My BU is very proactive in adopting or developing advanced IT for SCCS My BU is always first to use IT for SCCS in our industry My BU is more efficient in coordination activities with our partner than are our competitors with theirs My BU conducts transaction follow-up activities more efficiently with our partner than do our competitors with theirs My BU spends less time coordinating transactions with our partner than do our competitors with theirs My BU can conduct the coordination activities at less cost than our competitors Our partner spends less time searching for information about our products than its major competitors do for the information of their own partner’s products Our partner has reduced product-searching costs more than its competitors My BU performs much better than competitors in sales growth My BU performs much better than competitors in market share My BU performs much better than competitors in market development My BU performs much better than competitors in product development Please circle the number that best reflects your agreement with the following statements regarding your primary partner: Our partner is important for meeting customer requirements Our partner is critical for our BU’s long-term benefit Our partner is important for our BU’s core competency

Firm coordination

Partner coordination

Market performance

Partner criticalityc

Loadings

CR (AVE)b

0.90 0.92 0.90 0.69

0.92 (0.74)

0.89

0.89 (0.67)

0.93 0.68 0.75 0.85 0.83 0.80 0.80 0.91 0.79

0.83 (0.71)

0.73 0.80 0.63

0.85 (n/a)

0.90 (0.68)

Notes: CFA goodness of fit indices: chi-square ¼ 139:760 on 71 df; TLI ¼ 0:950; CFI ¼ 0:961; SRMR ¼ 0:048; RMSEA ¼ 0:072. a For all measures, sevenpoint Likert scales were used in the questionnaire (1 ¼ strongly disagree and 7 ¼ strongly agree). b CR ¼ composite reliability, AVE ¼ average variance extracted. c Partner criticality, the moderator, was not included in the CFA, as the moderating effect was assessed with a nested model and, subsequently, reliability reported is Cronbach’s alpha and loadings are item-to-total correlations

173

The role of information technology in supply chain relationships

Journal of Business & Industrial Marketing

Daekwan Kim, S. Tamer Cavusgil and Roger J. Calantone

Volume 20 · Number 4/5 · 2005 · 169 –178

we calculated composite reliabilities (Fornell and Larcker, 1981) and Table I presents them with the standardized parameters of measurement items. All composite reliabilities ranged from 0.83 to 0.92, which is far above the generally acceptable level of 0.70 (Nunnally, 1978). The good reliabilities along with adequate convergent and discriminant validities suggest the validity of constructs adopted in the study. To investigate the moderating effect of partner criticality effectively using structural equation modeling (SEM), we carried out a two-group analysis (Bentler, 1989). Before the two-group analysis, we conducted a two-group CFA. We separated the sample into two groups (e.g. high criticality vs low criticality) using the mean of the composite index of the three scales as the cutoff value. The process assigned 111 cases to the high criticality group and 73 cases to the low criticality group. The results of the two-group CFA provide fit indexes of x2 ¼ 242:375 on 142 df, LTI ¼ 0:928, CFI ¼ 0:944, SMR ¼ 0:063, and RMSEA ¼ 0:062. Although most fit indexes decreased from the first CFA model, these indexes still suggest a very good fit of the twogroup CFA model with the empirical covariances from the two groups (Hu and Bentler, 1999; Shook et al., 2004). Subsequently, we assess the validity of constructs using the same procedure we used for the first CFA. No issues on convergent and discriminant validities, and composite reliabilities emerged. Thus, we proceeded to estimate structural models for hypothesis testing.

To investigate the moderating effects of partner criticality, we estimated a two-group model, one group for high criticality and the other for low criticality. The estimation started with four constraints added to the model – one constraint per causal link. The LM test for releasing constraints indicated that there is a significant difference on the path between partner coordination and market performance ð p ¼ 0:012; x2 ¼ 6:25Þ. Subsequently, we released the constraint and re-estimated the model. The LM test suggests again that the constraint between firm coordination and market performance be released ð p ¼ 0:01; I2 ¼ 6:574Þ. Subsequently, the constraint was released before the final two-group model is estimated. According to the results, the final two group model fits the empirical covariances well with x2 ¼ 251:973 on 146 df, LTI ¼ 0:926, CFI ¼ 0:941, SRMR ¼ 0:085, and RMSEA ¼ 0:063 (Hu and Bentler, 1999). We tested for moderating effects of partner criticality based on the final two-group estimation. As shown in Table IV and Figure 2, the results reveal that partner criticality does not moderate the effects of IT adoption on firm coordination and partner firm coordination ð p . 0:05Þ. Thus, H5a and H5b are not supported. However, we found a positive moderating effect of partner criticality on the influence of firm coordination on market performance ð p , 0:01Þ, which lend support to H5c. Finally, the results indicate that partner criticality moderates the effect of partner coordination on market performance of the firm negatively ð p , 0:05Þ, which is against our expectation in H5d. Therefore, H5d is not supported.

Results Discussion and implications

For H1-H4, the proposed model with all measurement items from the first CFA model was estimated using EQS for Windows 5.7b. The results revealed an excellent fit of the model with the empirical covariances with x2 ¼ 148:441 on 72 df, LTI ¼ 0:945, CFI ¼ 0:957, SRMR ¼ 0:072, and RMSEA ¼ 0:076 (Hu and Bentler, 1999). With H1, we argued for a positive effect of IT adoption for SCCS on firm coordination activities. The empirical results reveal that IT adoption for SCCS affects firm coordination positively ð p , 0:01Þ. We also found that IT adoption of a firm enhances coordination activities of its supply chain partner ð p , 0:01Þ as postulated in H2. However, the results indicate that firm coordination does not affect market performance of the firm significantly ð p . 0:05Þ lending no support to H3. Relating to the effect of partner coordination, we hypothesized its positive effect on market performance of the firm. The results suggest that partner coordination influences market performance of the firm positively ð p , 0:01Þ. Therefore, H4 is supported. These results are summarized in Table III.

This study is a preliminary attempt to explore the impact of IT adoption on partner coordination. While the dyadic nature of supply chain relationships implies simultaneous impact of IT adoption of a channel member on both the adopting firm and its partner, it has not received significant research attention. As a pioneering work to investigate the empirical relationship between IT adoption of a channel member and its partner coordination activities, this study contributes to the literature by reporting a positive effect of IT adoption on partner coordination activities. As the results suggest, IT adoption for SCCS enhances coordination activities within the supply chain. This is evidenced by the positive impact of IT adoption on its own coordination as well as the coordination activities of its partner. Despite the IT paradox reported in the literature (Brynjolfsson, 1993; Brynjolfsson and Hitt, 1996; Kettinger et al., 1994; Loveman, 1991; Mukherjee, 2001; Panko, 1991; Powell and Dent-Michallef, 1997; Rai et al., 1996; Roach, 1987; Strassmann, 1990), the present study suggests that

Table III Proposed hypotheses and test results Hypotheses

Standardized parameter estimate

H1. IT adoption for SCCS enhances firm coordination H2. IT adoption for SCCS improves partner coordination H3. Firm coordination leads to enhanced market performance H4. Partner coordination leads to enhanced market performance of the firm




0.228 0.429
0.063 0.385


Conclusion Supported Supported Not supported Supported

Notes: Structural model goodness of fit indices: chi-square ¼ 148:441 on 72 df; TLI ¼ 0:945; CFI ¼ 0:957; SRMR ¼ 0:072; RMSEA ¼ 0:076.

174




p , 0:01

The role of information technology in supply chain relationships

Journal of Business & Industrial Marketing

Daekwan Kim, S. Tamer Cavusgil and Roger J. Calantone

Volume 20 · Number 4/5 · 2005 · 169 –178

Table IV Moderating effects of partner criticality Hypotheses

Standardized parameter estimate

H5a. The more critical its partner is to a firm, the stronger is the influence of IT adoption of the firm on firm coordination H5b. The more critical its partner is to a firm, the stronger is the influence of IT adoption of the firm on partner coordination H5c. The more critical its partner is to the firm, the stronger is the influence of firm coordination on market performance of the firm H5d. The more critical its partner is to a firm, the stronger is the influence of partner coordination on market performance of the firm

positive positive positive positive

a

Conclusion




HPC : 0.431 LPCb: 0.421
HPC: 0.209

LPC: 0.169

HPC: 0.672
LPC: 2 0.037 HPC: 20.237 LPC: 0.402



Not supported Not supported Supported Not supported

Notes: Structural model goodness of fit indices: chi-square ¼ 251:973 on 146 df; CFI ¼ 0:941; TLI ¼ 0:926; SRMR ¼ 0:085; RMSEA ¼ 0:063. a High partner criticality; b low partner criticality.
p , 0:01;

p , 0:05

Figure 2 The results of two-group-model estimation

supply chain members improve their productivities by investing in information technology. The study results further suggest that improvements in a firm’s coordination stemming from IT adoption do not lead to better market performance. It is an intriguing finding in that IT adoption cannot be empirically linked to firm performance (i.e. market performance) through the improvement of coordination activities of the firm. However, the results also suggest that the empirical linkage can be established only when IT adoption is linked to market performance through partner coordination. There appear to be multiple implications for these results. First, the results may reveal that it is not always possible to improve market performance through the enhancement of its coordination activities from the adoption of advanced information technology. This is probably because supply chain relationships are dyadic in nature and, therefore, unidirectional IT investments of firms could not be readily embedded into the dyadic coordination process (Barney, 1991). Thus, in the supply chain

relationship context, enhancement of coordination activities in one member firm would not promise a real improvement of interfirm coordination within the supply chain until improvements in coordination activities of its partners accompany. Second, the findings suggest why some studies in the literature failed to find an empirical association of IT with firm productivities. According to present findings, studies that do not consider the right managerial processes that mediate the effect of IT adoption are unlikely to find significant linkages between IT adoption and firm performance. That is, if partner firm coordination was not included in the model, our study may have also produced insignificant impact of IT adoption on market performance. Third, the results stress that it is critical to incorporate proper moderators in identifying the conditions under which IT adoption leads to enhanced firm performance. Without the moderator – partner criticality – our study could have reported that firm coordination does not affect firm market 175

The role of information technology in supply chain relationships

Journal of Business & Industrial Marketing

Daekwan Kim, S. Tamer Cavusgil and Roger J. Calantone

Volume 20 · Number 4/5 · 2005 · 169 –178

performance significantly. Fortunately, the two-group analysis indicates that IT adoption enhances market performance through firm coordination activities only with partners that are critical to the success of its business. When a partner is critical to the success of the firm, enhancements in its interfirm coordination activities with the partner affect market performance positively. However, when a partner is not critical, such enhancements in coordination activities do not influence market performance of the firm according to the results. It clearly reveals the moderation of partner criticality on the impact of IT adoption on market performance through firm coordination enhancements, meeting our expectation that IT adoption will have a greater impact on market performance when the partner is critical. That is, as coordination activities of the firm with partners become critical, the impact of new IT adoption for SCCS on market performance follows the direction of the criticality of the partner. In contrast, the improvements in coordination activities of a critical partner do not influence market performance of the firm positively. Only that of a less critical partner affects market performance of the firm positively. This finding suggests that enhancements in a partner’s coordination that stemmed from IT adoption will help improve market performance of the firm only when the partner is less critical. Then, why are the enhancements in coordination activities of a critical partner not helpful to the firm? It is likely that high partner criticality creates high dependence of the firm on the partner causing power imbalance (Emerson, 1962; Salancik and Pfeffer, 1974). That is, being a critical partner implies possible dependence on the partner (Pfeffer and Salancik, 1978; Salancik and Pfeffer, 1974). In such a scenario, enhancements resulting from IT adoption may not be materialized as enhanced market performance, as the partner shifts the distribution of additional value created by IT adoption toward its favor leveraging its relatively important position or dependency status of the IT adopting firm. Subsequently, if it is a very critical partner, an improvement in coordination of the partner, even though it stems from IT adoption of the firm, results in no significant market performance of the firm. On the other hand, an improvement in the partner’s coordination leads to market performance of the firm when the partner is less critical, as the less critical partner entails low dependence of the firm on the partner and, thus, the firm is able to secure its adequate share of additional value from IT adoption.

moderators including industry type, level of competition in the industry, tenure of IT deployment, and use of IT (as opposed to adoption of IT) among others. Moreover, mediators other than coordination, employed in this study, could be explored. Information sharing that assesses the extent to which quality information is shared among channel members, and supply chain responsiveness (responsiveness to new customer inquiries and market changes) could mediate the impact of IT adoption. IT offers unlimited benefits as well as challenges to firms and supply chains. However, our understanding of the extent to which it provides unprecedented opportunities for the firm is incomplete. The current study attempts to provide some insights on the impact of IT adoption on a firm’s own and its partner’s coordination activities and on its market performance. We hope that the findings reported here will inspire other scholars to extend our knowledge of the impact of Information Technology on contemporary business performance.

Note 1 Supply chain management system is defined as an internally and externally integrated corporate system that enables supply chain members to carry out supply chain relevant activities including strategic management functions (Bowersox et al., 2002).

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Daekwan Kim, S. Tamer Cavusgil and Roger J. Calantone

Volume 20 · Number 4/5 · 2005 · 169 –178

Stank, T., Crum, M. and Arango, M. (1999a), “Benefits of interfirm coordination in food industry supply chains”, Journal of Business Logistics, Vol. 20 No. 2, pp. 21-41. Stank, T.P., Daugherty, P.J. and Autry, C.W. (1999b), “Collaborative planning: supporting automatic replenishment programs”, Supply Chain Management, Vol. 4 No. 2, pp. 75-85. Steinfield, C., Kraut, R. and Plummer, A. (1995), “The impact of interorganizational networks on buyer-seller relationship”, Journal of Computer-Mediated Communication, Vol. 1 No. 3. Strassmann, P. (1990), The Business Value of Computers, Information Economics Press, New Canaan, CT. Tang, J.-t.E., Shee, D.Y. and Tang, T.-I. (2001), “A conceptual model for interactive buyer-supplier relationship in electronic commerce”, International Journal of Information Management, Vol. 21 No. 1, pp. 49-68. Taylor, D.A. (2003), “Supply chain vs supply chain”, Computerworld, Vol. 37, November 10, pp. 44-5. Thatcher, M.E. and Oliver, J.R. (2001), “The impact of technology investments on a firm’s production efficiency, product quality, and productivity”, Journal of Management Information Systems, Vol. 18 No. 2, pp. 17-45.

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Collaborative supply-chain partnerships built upon trust and electronically mediated exchange Niklas Myhr Kogod School of Business, American University, Washington, DC, USA, and

Robert E. Spekman The Darden Graduate School of Business Administration, University of Virginia, Charlottesville, Virginia, USA Abstract Purpose – To investigate how supply-chain partners can achieve collaboration under varying circumstances (transactional types) by developing trustbased social foundations and by utilizing electronically mediated exchange. Design/methodology/approach – A conceptual framework illustrates the roles of trust and electronically mediated exchange in achieving collaboration and its hypotheses are tested with a sample of 157 supply-chain relationships of international subsidiaries of Nordic multinational corporations (MNCs). Findings – Finds that collaborative partnerships can be achieved both via trust and through electronically mediated exchange. Results also indicate that electronically mediated exchange more readily enhances collaboration in exchange relationships involving standardized products, while trust plays a larger role when customized products are being exchanged. Research limitations/implications – The transactional type involved impacts the relative effectiveness of trust and electronically mediated exchange in achieving collaboration. This finding might stimulate research of the impact of other contextual factors. Limitations include that only managers on one side of inter-organizational dyads were surveyed. Practical implications – Practicing managers need to prioritize the time and effort they spend developing partnerships. While both trust and electronically mediated exchange play pivotal roles in fostering collaboration, managers involved in the exchange of standardized products can place a relative emphasis on electronically mediated exchange, while trust is of higher importance when customized products are being exchanged. Originality/value – This paper examines the complex interplay of trust and electronically mediated exchange in achieving collaborative supply-chain partnerships and offers guidance to practicing managers as well as implications of theoretical interest to academics. Keywords Supply chain management, Electronic commerce, Communication technologies, Buyer-seller relationships, Strategic alliances, Relationship marketing Paper type Research paper

need for integration across the overall supply chain. The idea is that when constellations of organizations in one supply chain deliberately collaborate, they can effectively outcompete other, less collaborative, supply chains. We are witnessing that companies that previously confronted customers and suppliers regarding the allocation of costs and profits, now engage in collaborative supply-chain partnerships to maximize joint performance outcomes (Corbett et al., 1999). In fact, Chrysler’s procurement organization, under the leadership of Tom Stallkamp coined the term “the extended enterprise” to capture the close ties the automaker had with its supply base. Interestingly, some of the gains afforded by these close ties have eroded since the merger with Daimler who has taken a more adversarial position with its US supply base. A number of academic studies have identified trust as a key partnership characteristic which fosters collaborative behaviors (Morgan and Hunt, 1994; Wilson, 1995). For example, a buyer and a supplier who trust each other are more likely to openly share detailed cost breakdowns with each

An executive summary for managers and executive readers can be found at the end of this issue.

Introduction Both academics and practitioners recognize the increasing importance of strategic alliances and partnerships in supply chains. Today, in order to emphasize core skills companies assume narrow and specialized roles within supply chains while they ally themselves with supply-chain partners, who have complementary skills, for mutual benefits. Collaborative supply-chain partnerships become the critical linking pins as higher degrees of specialization brings with it an increased The Emerald Research Register for this journal is available at www.emeraldinsight.com/researchregister The current issue and full text archive of this journal is available at www.emeraldinsight.com/0885-8624.htm

Journal of Business & Industrial Marketing 20/4/5 (2005) 179–186 q Emerald Group Publishing Limited [ISSN 0885-8624] [DOI 10.1108/08858620510603855]

This research was partially funded by grants from the Hans Werthe´n Foundation at the Royal Swedish Academy of Engineering Sciences (IVA).

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Conceptual framework

other (e.g. Ellram, 1996). Open access to such information enables partners to identify and manage inefficiencies and potential redundancies, whereby the total costs incurred in supply-chain relationships can be reduced. Trust alone is not sufficient, however, for supply-chain relationships to achieve collaboration since mechanisms must also be in place so that information can be readily exchanged among the partners. One such mechanism is electronically mediated exchange and its role in fostering collaboration is of particular interest in today’s increasingly digital economy. First, many internet-based communication technologies represent relatively affordable solutions as compared to more traditional information systems for conducting electronically mediated exchange. Second, investments in internet-based communication technologies can more readily be deployed in other supply-chain relationships if current relationships would go sour. A case in point is the document transmission technology of electronic data interchange (EDI) which is undergoing a radical transformation whereby more affordable and flexible internet-based EDI solutions are now available (Mount, 2003). Consequently, companies today do not have to be as concerned about making the investments necessary to conduct electronically mediated exchange given that these investments are both lower than before and in many cases also reusable (cf. Stump and Sriram, 1997). This is potentially good news for time-starved managers struggling to keep up with the management of more supplychain relationships than they realistically can handle. Naturally, not all supply-chain relationships merit close collaborative efforts and therefore would not represent partnerships as such. However, as the performance and loyalty benefits of the relationship marketing and partnership approaches are becoming increasingly evident, managers are certainly striving to engage in more, not fewer, collaborative supply-chain partnerships. At the same time, they find it harder to spend the quality time needed to build a solid trustbased foundation on which future collaborative efforts can thrive if they have too many suppliers to deal with. Consider, for example, the effort required to spend some quality time with each and every one of General Electric’s 45,000 suppliers (Mount, 2003). Even if GE concentrated on the top ten percent of its supply base, spending time with 4,500 suppliers is still a daunting task. This paper suggests that both trust and electronically mediated exchange have the potential to enhance collaboration in supply-chain relationships. In our empirical study, we specifically test for the impact of trust and electronically mediated exchange on the degree of collaboration. This study also fills a gap in the literature as research is needed to examine how the nature of transactions in supply-chain relationships influences the relative value of electronically mediated exchange (Ryssel et al., 2004). The context in which we investigate these issues is one of upstream supply-chain relationships of manufacturing business units of Nordic multinational corporations (MNCs). In the following section, we introduce our conceptual framework; discuss how it relates to the literature; and, offer our research hypotheses. Next, we present both the methodology used to test the conceptual framework and the findings. Finally, we discuss study limitations and the implications of this study for managers and researchers.

The theoretical model guiding the research largely builds upon the theories of relational contracting (e.g. Macneil, 1980) and organizational information processing (e.g. Daft and Lengel, 1986) as it addresses the following research questions: . How do trust and electronically mediated exchange affect collaboration in supply-chain relationships? . Is there a moderating effect of transactional type in supply-chain relationships which affects both the strength of the relationship between trust and collaboration, and the strength of the relationship between electronically mediated exchange and collaboration? Figure 1 shows the conceptual framework we use to address these research questions. Collaboration Collaboration is the degree to which partners are able to work together in a joint fashion toward their respective goals (Frazier, 1983), and has emerged as a key construct in the study of supply-chain partnerships given its espoused benefits. Collaborative supply-chain partnerships can both achieve significant cost savings and increase the overall competitiveness of the supply chain. Therefore, managers increasingly encourage and sponsor collaborative activities across organizational boundaries (Womack et al., 1990; Spekman et al., 1998). The impact of trust on collaboration Trust is the degree to which partners perceive each other as credible and benevolent (cf. Doney and Cannon, 1997; Ganesan, 1994; Kumar et al., 1995) and is expected to have a positive effect on the degree of collaboration in supply-chain relationships. If parties expect each other to be both able and willing to perform the necessary tasks, they are also likely to collaborate (Mohr and Spekman, 1994; Morgan and Hunt, 1994). Moreover, for supply-chain partnerships to become truly collaborative in nature, trust is not only a desired characteristic, but a necessary one (Spekman et al., 1998, p. 635). This reasoning results in the following hypothesis: H1. Trust in the relationship between the manufacturing business unit and a supplier is positively related to the degree of collaboration in the relationship.

Figure 1 A conceptual framework of the effects of trust and electronically mediated exchange on collaboration

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The impact of electronically mediated exchange on collaboration Electronically mediated exchange refers to the degree to which partners communicate through electronic media such as the internet, intranets, electronic mail, or electronic data interchange (EDI) systems (cf. Kulchitsky, 1997). Nohria and Eccles (1992) suggest that electronically mediated exchange contributes to increased collaboration because it empowers front-line workers with information; enables direct communication between individuals at low levels in the organization across time and space; and blurs organizational boundaries. In a supply-chain context, integrated information flows often absorb uncertainty (Allaire and Firsirotu, 1989) as well as reduce system volatility induced by information delays (Towill et al., 1992). The common theme is that electronically mediated exchange supports interorganizational collaboration by facilitating interaction and dissemination of information at all organizational levels. Because electronically mediated exchange is of assistance for people at the operational-level who need up-to-date information to effectively carry out their roles in supply-chain relationships, electronically mediated exchange is likely to have an immediate impact on the construct of collaboration with its day-to-day focus. This logic results in the following hypothesis: H2. The extent of electronically mediated exchange between the manufacturing business unit and a supplier is positively related to the degree of collaboration in the relationship.

given that routine information shared with the other company would not be of a very sensitive nature. Rather, the efficient exchange of useful routine information is what is necessary for collaboration to take place in these supply-chain relationships. Second, supply-chain relationships involving exchanges of customized products need to be more concerned with establishing a trust-based social foundation before high degrees of collaboration can be achieved. This is because the exchange of customized products is a complex and, by definition, an idiosyncratic process, typically requiring partners to share critical and sensitive information across organizational boundaries, something only trusting partners would be willing to do. Also, trust makes it more likely that the receiver of the information finds it credible and acts upon it in a collaborative manner. The above discussion results in the following hypothesis: H3. Transactional type will moderate the relationships between electronically mediated exchange and trust on the one hand, and collaboration on the other, such that, electronically mediated exchange is a more salient determinant of collaboration for standardized products exchange relationships, while trust is a more salient determinant of collaboration for customized products exchange relationships.

Research methodology Sampling process The sampling process focused on upstream supply-chain relationships of self-contained production units within a group of Nordic multinational corporations (MNCs) originating either in Finland, Norway, or Sweden. Despite their origins in Nordic countries, the sample firms are representative of transnational companies that produce, market, and distribute their products on a global basis. That is, we do not expect a bias due to unique characteristics that might prohibit us from generalizing beyond our sample of Nordic firms. First, we identified self-contained production units in which managers could serve as key informants regarding the nature of particular upstream supply-chain relationships. By self-contained production units, we refer to MNC subsidiaries that: contain at least the functional areas of manufacturing, purchasing, R&D, and marketing; have at least some external suppliers; and have at least some external customers. All in all, the sampling process secured participation by a total of 53 self-contained production units belonging to a total of 24 different MNCs. However, the unit of analysis is a particular supply-chain relationship between one of these self-contained units and one of its suppliers. Within each self-contained production unit, the initial contacts, typically purchasing directors, identified individuals whom they felt were willing to serve as key informants on behalf of some of the production units’ upstream supply-chain relationships. The criterion by which key informants were identified was that they were familiar with at least one upstream supply-chain relationship. Some key informants offered to respond also regarding a second supply-chain relationship, and, overall, usable data was gathered from 150 key informants regarding the nature of a total of 157 supplychain relationships. The use of key informants has been well established in this kind of research (e.g. John and Reve, 1982; Kumar et al., 1993; Joshi and Stump, 1999). Care was taken to ensure that the people identified by the initial contacts

The moderating effect of transactional type The previous sections introduced the expected direct effects of trust and electronically mediated exchange on collaboration. This section suggests that the relative effectiveness of trust and electronically mediated exchange in achieving collaboration depends on the transactional type, the type of product being exchanged between the supplychain partners. In this study, we will center our attention on the two transactional types of standardized and customized products. These transactional types were identified because they allow us to study the nature of supply-chain collaboration and its proposed determinants of trust and electronically mediated exchange in contexts resembling the two contrasting types of information-processing situations identified in organizational information processing theory (Daft and Lengel, 1986; Leamer and Storper, 2001). First, supply-chain relationships transacting standardized products require frequent information exchanges because of the typically high volumes of goods being transacted (Ryssel et al., 2004). Also, much of the information exchanged in such supply-chain relationships is routine in nature and is thereby neither complex nor sensitive. Since both high frequency and routine-type information exchanges can be conducted via electronically mediated exchange, we argue that supply-chain partners exchanging standardized products will be in a position in which they can reap significant and immediate collaborative benefits from the use of electronically mediated exchange. That is, companies involved in these supply-chain relationships can collaborate effectively even in the absence of a strong social foundation of trust. While we do not expect trust to be harmful, it may not be necessary either 181

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were, in fact, knowledgeable and able to report on these supply-chain relationships. Key informants were then instructed to select upstream supply-chain relationships between the self-contained production units and one of their suppliers in which some kind of direct materials were being exchanged. They were also instructed to limit themselves to relationships that had been in existence for at least two years. The two-year criterion was not an arbitrary time limit but is based on previous empirical research reported in work by Spekman (e.g. Spekman et al., 2000). An empirical examination of a cross-section of complex alliances suggests that it can take up to three-anda-half years for an alliance to work through its start-up difficulties. Given the complexity and scope of the alliances examined, we felt that for the purposes of this study, a twoyear period was sufficient to capture established supply-chain relationships and would yield a sample of established exchange relationships. In our sample, the average supplychain relationship duration was ten years.

key informants the choice between filling out a paper or a Web-based questionnaire. The questionnaire pre-testing process included four steps, each of which resulted in improvements of the questionnaire. First, a set of four academic experts offered their feedback on a series of questionnaire drafts presented with subsets of questionnaire items. Second, two self-contained production units of two different Nordic MNCs agreed to host pretests on their premises where supply managers indicated how questionnaire items rated in terms of clarity. The managers also completed an item-sort task (Anderson and Gerbing, 1991) by matching each questionnaire item to a construct that they felt was most related to the questionnaire item. Moreover, these pretest participants provided qualitative feedback on both the questionnaire cover letter and the questionnaire instructions during retrospective interviews (Dillman, 2000). Third, participants in an Executive Education seminar for supply managers offered written comments on an updated version of the questionnaire. Fourth, a number of individuals from both academic and industry backgrounds tested the Web-based version of the questionnaire so that we could learn whether the process of completing the questionnaire on the internet could cause difficulties for those managers who elected to respond online. The Appendix shows the measures used in the study.

Measures Previously tested measurement scales were used for the various constructs. The measure of collaboration was based on the measure used by Kahn (1996) to measure interdepartmental collaboration. The measure of trust borrows scale items that Doney and Cannon (1997) used to measure salesperson trust in a business-to-business relationship setting. They derived the scale items from two components of trust, namely credibility and benevolence, but find that trust is a unidimensional construct. Electronically mediated exchange was based on scale items used by Kulchitsky (1997) in the context of marketing channel relationships. Finally, transactional type was operationalized as standardized products if key informants identified the goods being exchanged in a particular supply-chain relationship as either raw materials or components and as customized products if either subassemblies or subsystems were being selected. In this sample context, subassemblies and subsystems tend to be developed for specific applications and were not to be easily utilized elsewhere. To a large extent, these customized products are non-fungible assets. The questionnaire items were changed to make sense in the specific context of upstream supply-chain relationships. Also, a challenge we faced with the key informant approach was to ensure that the key informants offered their assessments regarding overall relationships rather than only the perspectives of their own firms. Therefore, the questionnaire items were worded in dyadic, or relationship, terms with expressions such as “this relationship,” “this supplier relationship,” “both firms believe that,” or “neither of us trusts the other side,” to encourage respondents to consider how they think that a neutral observer closely monitoring the day-to-day relationship would characterize the overall relationship in question. English was used as the language on all questionnaires since the corporations in the sample all were international companies accustomed to interacting in English with both internal and external constituencies. Moreover, key informants were provided with a high degree of flexibility with respect to the way in which they responded to the questionnaire, and this was achieved with a so-called mixedmode questionnaire (Dillman, 2000). Therefore, we offered

Results The validity of the sampling process was examined empirically in several ways to assess whether the process introduced biases to the results. A comparison of the responses provided by early and late respondents indicated that non-response bias was not a cause for concern. Also, a test comparing responses stemming from the different modes of questionnaires, paper survey and Web-based survey, showed that there was not a significant bias in the responses based on the response mode. To test the first two hypotheses regarding the viability of the main effects of trust (H1) and electronically mediated exchange (H2) in achieving collaboration, a regression using the full sample of 157 supply-chain relationships was run with trust and electronically mediated exchange as independent variables. A control variable, expected relationship duration, was first added as an independent variable in the regression analysis to account for this potential alternative explanation of variation in the collaboration construct. The results of this analysis are shown in Table I. Jointly, trust and electronically mediated exchange significantly increased the adjusted R2 square by 14.7 percent over and beyond the R2 of 4.2 percent accounted for by the control variable. Individually, each of the projected main effects of trust and electronically mediated exchange proved to be strongly significant determinants of collaboration. H3 concerned the role of transactional type as a moderator affecting the relative influence of trust and electronically mediated exchange on collaboration. This hypothesis was tested with separate regressions for the parts of the sample involving standardized and customized products, respectively. The control variable of expected relationship duration was added as an independent variable also in these cases. Table II shows the results of the analysis of the 105 cases involving standardized products. In this case, trust and electronically mediated exchange together increased the adjusted R2 by 9.0 percent after considering the 3.8 percent 182

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Volume 20 · Number 4/5 · 2005 · 179 –186

Table I Regression results with full sample ðn ¼ 157Þ Collaboration regressed on:

R2 Adjusted R2 Standard error F Sig. F Variables in the equation (Constant) Expectation of relationship continuation Trust Electronically mediated exchange

Table III Regression results for customized products ðn ¼ 52Þ

Control variable

All variables

0.049 0.042 1.091 7.430 0.007

0.206 0.189 1.004 14.037 0.000

Collaboration regressed on:

B Std error Beta t Sig. 2.092 0.523 3.996 0.000 0.024 0.362

0.015 0.087

0.124 1.594 0.113 0.314 4.167 0.000

0.167

0.055

0.235 3.038 0.003

R2 Adjusted R2 Standard error F Sig. F Variables in the equation (Constant) Expectation of relationship continuation Trust Electronically mediated exchange

Control variable

All variables

0.048 0.038 1.076 4.833 0.030

0.155 0.128 1.025 5.875 0.004

B Std error Beta t Sig. 2.557 0.781 3.272 0.001 0.026 0.256

0.016 0.131

0.155 1.584 0.117 0.187 1.950 0.054

0.180

0.069

0.257 2.621 0.010

All variables

R2 Adjusted R2 Standard error F Sig. F

0.070 0.050 1.132 3.530 0.066

Variables in the equation (Constant) Expectation of relationship continuation Trust Electronically mediated exchange

B Std error Beta t Sig. 1.609 0.727 2.212 0.032

0.339 0.295 0.975 9.161 0.000

0.020 0.481

0.044 0.119

0.063 0.462 0.646 0.503 4.044 0.000

0.164

0.098

0.226 1.686 0.099

and collaboration. Results also identify electronically mediated exchange as having a key role in the development of collaboration that is consistent with earlier findings (e.g. Kulchitsky, 1997). Furthermore, electronically mediated exchange proves to be a more salient determinant of collaboration in supply-chain relationships involving exchanges of standardized products, while trust is more of a factor in achieving collaboration in exchanges involving customized products. This finding is consistent with the notion that trust serves to hold in check opportunistic behavior that could easily arise with the purchase of a customized product by virtue of the unique nature of the purchase and its idiosyncratic characteristics (Macneil, 1980). It would be a stretch to present the choice between trust and electronically mediated exchange in developing collaboration as a categorical either-or proposition. Rather, both trust and electronically mediated exchange are likely to be helpful in the process of developing collaborative supplychain partnerships. This study supports this view in that both trust and electronically mediated exchange were at least weakly significant determinants of collaboration in both contexts under consideration in this study. On one level, trust seems to establish a base-line level of collaboration that is enhanced and reinforced through the use of electronically mediated exchange. Previous research has argued that constant communication is essential to help foster and build trust (e.g. Morgan and Hunt, 1994). This is true once a relationship has been established. Non-personal interaction, such as seen in EDI, can supplement a trusting relationship and strengthen the ties between trading partners. That is, it is not sufficient to establish a trust-based foundation in a supply-chain relationship for it to reach its full collaboration potential. Rather, results indicate that firms should be encouraged to continue investing in electronic solutions to achieve collaborative supply-chain partnerships, at the same time as they build trust-based foundations on which partnerships can truly flourish. By constant interaction and information sharing via electronically mediated exchange, partners experience a closer bond and this serves to re-enforce trust that contributes to collaboration. Conversely, even if this study identified a main effect of electronically mediated exchange on collaboration,

Table II Regression results for standardized products ðn ¼ 105Þ Collaboration regressed on:

Control variable

explained by the control variable. Also, in this analysis electronically mediated exchange emerges as a very significant determinant of collaboration, while the impact of trust on collaboration is only weakly significant. Table III shows the results of the analysis of the 52 cases involving customized products. Here, trust and electronically mediated exchange increased the adjusted R2 by 24.5 percent from the 5.0 percent accounted for by the control variable. Now trust becomes a strongly significant determinant of collaboration while the relationship between electronically mediated exchange and collaboration is only weakly significant.

Discussion and implications This study presents empirical evidence supporting the presence of trust and electronically mediated exchange as determinants of collaboration in supply-chain relationships. The central role of trust in achieving collaborative relationships has been documented previously (e.g. Morgan and Hunt, 1994; Spekman et al., 1998). The results from the context of this study serve as further evidence of this effect because of the strongly significant relationship between trust 183

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Journal of Business & Industrial Marketing

Niklas Myhr and Robert E. Spekman

Volume 20 · Number 4/5 · 2005 · 179 –186

electronically mediated exchange in the complete absence of trust is not likely to achieve very high levels of collaboration. If the threshold level has not been achieved, these non-personal linkages cannot replace trust since these mechanisms will not be powerful enough to achieve the requisite base-line level of collaboration. However, given the fact that the supply-chain relationships analyzed in this study had all been in existence for at least two years, these relationships are likely to have reached at least a minimum threshold of trust necessary for the effective use of electronically mediated exchange. Also, as our results indicate, such more limited collaborative efforts might very well suffice in exchanges based on more commodity-like or standardized products. This is because the need for very close and collaborative dealings is reduced when products are more widely available and the threat of opportunism is less imminent. Still, requisite levels of collaboration can be achieved through the effective use of electronically mediated exchange, a finding which is in line with long-standing beliefs that increased accessibility to information increases the use of such information (O’Reilly, 1982). Limitations of this study include the fact that we only surveyed managers on one side of the inter-organizational dyads. Even if they were instructed to offer objective assessments, these key informants may have been biased in offering their subjective views of the supply-chain relationships in question. Also, we only considered one control variable, expectation of relationship continuation, in our analyses. Potentially, there are other factors that when recognized would explain most of the variance that we now attribute to the effects of trust and electronically mediated exchange.

transaction. Workflow coordination is critical for such commodity-like and often high-volume exchange supplychain relationships and contributes to higher degrees of collaboration. Our finding that transactional type indeed does determine the relative effectiveness of trust and electronically mediated exchange in achieving collaboration indicates that the best approach to develop collaborative supply-chain partnerships depends on the context. This is an interesting finding which can encourage more research into the effect of contextual factors other than transactional type in determining the relative effectiveness of various approaches to achieve collaborative supply-chain partnerships. Managerial implications The implementation of collaborative supply-chain partnerships implies lateral collaboration both across functional areas and organizational boundaries that require significant cultural and organizational changes in traditional, hierarchical organizations with strong functional areas. Still, as the formation of collaborative supply-chain partnerships is becoming increasingly prevalent, managers have little guidance when it comes to when and how to best achieve such cross-firm linkages. We tested empirically the viability of trust and electronically mediated exchange to advance collaboration in supply-chain relationships. Therefore, our findings are not only of theoretical interest, but can also be of great practical significance. For the practicing manager, the challenge is mainly one of balancing effort and knowing where to invest scarce time and effort. In short, our results suggest that managers wishing to develop collaborative supply-chain partnerships should invest efforts both in developing trusting relationships as well as in establishing means to conduct increased levels of electronically mediated exchange. Also, this study argues that managers of supply-chain relationships involving the exchange of standardized products can enhance collaboration by placing a relative emphasis on electronically mediated exchange, while the establishment of a solid trust-based social foundation is of higher importance in exchange relationships for customized products. Under all conditions and purchasing contexts, ensuring a seamless flow of materials and information is critical. Still, it might have gone without notice that communications between trading partners is key and electronically mediated exchange plays an important role despite a sense that the linkages are mundane. Ties between trusting partners can simply be made stronger through electronically mediated exchange. Yet, it is equally important to note that these electronically mediated exchanges cannot substitute for the face-to-face interactions that are essential for trust to build. Having established a trusting relationship, these forms of non-personal interactions that enable information dissemination can support and contribute to sustaining a trusting relationship. We have shed light on a subtle but important point – do not underestimate the importance of open and frequent exchanges of information. To some degree it is the process of information exchange and not the content of the exchange that is important. Trust is based, in part, on the seamless and accurate exchange of information. Nothing replaces personal interaction in the early stages of relationship building; at the same time, electronically mediated exchange and its technology should be seen as enablers and complementors.

Theoretical implications A major contribution of this paper is the conceptual linkage between trust and electronically mediated exchange. To some extent, this finding is similar to the roles played by trust and contracts in establishing the “rules of engagement” between supply-chain partners. That is, the two mechanisms act in parallel to lend support to the other in establishing closer ties among alliance partners (e.g. Das and Teng, 1998). This paper also answers the call for research on how the transactional type involved supply-chain relationships impacts the value and relative effectiveness of electronically mediated exchange (Ryssel et al., 2004). In the present context, trust has been shown to particularly influence the level of collaboration among supply-chain partners when the purchase is complex, more specialized, and tailored. Yet, it alone cannot sustain the level of collaboration and it is complemented by electronically mediated exchange that seems to contribute to the relationship by strengthening the bonds through the ongoing exchange of information and constant contact that EDI, for example, provides. This joint impact of trust and electronically mediated exchange re-enforces the relationship and seems to create a greater semblance of interdependence and embeddedness (Provan, 1993). When the product is a standardized, off-the-shelf type of purchase, the depth of the relationship is less critical since normal market mechanisms will partly guide the interaction between partners. Thus, trust takes a lesser role in managing the relationship and electronically mediated exchange becomes important in managing the workflow of the 184

Collaborative supply-chain partnerships

Journal of Business & Industrial Marketing

Niklas Myhr and Robert E. Spekman

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Given the attention given to RFID (radio frequency identification) and other enterprise-level technologies, it is clear that an in-depth appreciation for the mechanisms that drive collaboration is important. We have provided a glimpse into the complex interplay of these mechanisms.

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Appendix Table AI Measurement scales Item total correlations

Collaboration: Cronbach’s alpha 5 0:805 (based on Kahn, 1996) How much do you agree or disagree with the following statements regarding your business unit’s relationship with this supply-chain partner? We are achieving our long-term goals together In this supplier relationship, we share ideas, information, and/or resources We work together with this supplier as a team People from both companies work together informally

0.796 0.796 0.826 0.768

Trust: Cronbach’s alpha 5 0:776 (based on Doney and Cannon, 1997) How much do you agree or disagree with the following statements regarding your business unit’s relationship with this supply-chain partner? In this supplier relationship, we keep promises we make to each other Each party believes the information provided by the other We both find each other trustworthy

0.859 0.747 0.909

Electronically mediated exchange: Cronbach’s alpha 5 0:754 (based on Kulchitsky, 1997) How much do you agree or disagree with the following statements regarding your business unit’s relationship with this supply-chain partner? We are linked electronically so that we can share information of mutual interest In this supplier relationship, we frequently communicate through electronic media such as the internet, intranets, electronic mail or EDI systems In this relationship, we emphasize integrated information systems

186

0.857 0.864 0.728

Critical factors affecting intermediary web site adoption: understanding how to extend e-participation Tina Harrison and Kathryn Waite School of Management, The University of Edinburgh, Edinburgh, UK Abstract Purpose – To provide an investigation of e-commerce development via an examination of the forces shaping web site development among intermediaries in an extended supply chain. Design/methodology/approach – A two-stage research design combining qualitative and quantitative methods. Unstructured interviews conducted in the spirit of phenomenology elicited a range of critical incidents of web site development which were further examined via a quantitative survey of intermediaries to test for relationships between critical incidents and web site adoption. Findings – Adopter groups were identified which showed statistically significant differences in terms of the critical incidents driving web site development as well as differences in terms of key company characteristics. The timing of web site adoption was also found to affect the subsequent use of the technology, with early adopters making more advanced use. Research limitations/implications – Limitations associated with the use of retrospective data and respondents’ abilities to recall events, although attempts were made to minimise these through external validation. Practical implications – Provides useful insights for providers of financial services in understanding how to progress the adoption of web site technology by intermediaries, suggesting the development of networks of relationships involving IT suppliers rather than simply focusing on relationships with preferred intermediaries. Originality/value – Addresses a research gap in terms of business-to-business e-commerce and offers practical guidance on how to widen participation in the financial services supply chain. Keywords Internet, Innovation, Intermediaries, Supply chain management, Financial services Paper type Research paper

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distributors to overcome barriers to e-business (Zank and Vokurka, 2003). In addition, “the internet offers direct links with customers, suppliers and distributors . . . [enabling] companies to bypass others in the value chain . . . to dominate the “electronic channel” and thereby control access to customers and set terms of trade” (Walters and Lancaster, 1999, p. 800, original italics). Hence, e-commerce technology has the potential not only to enhance supply chain performance but also to change its structure and may even pose a threat to certain supply chain members. The term “disintermediation” describes this bypassing process. Disintermediation occurs where the ultimate supplier of a good or service circumvents intermediaries and sells directly to the consumer or where a new intermediary emerges that employs a lower-cost distribution method (Evans and Wurster, 2000). One strand of e-marketing literature proposes that disintermediation will be widespread and electronic markets will automatically reduce the need for brokers (Gallaugher, 1999; Choudhury et al., 1998). Examples of disintermediation can be found in several industries, most notably travel, where trends exist towards consumers dealing online directly with providers of goods or services, or using newly-established online intermediaries, thereby by-passing

Journal of Business & Industrial Marketing 20/4/5 (2005) 187–199 q Emerald Group Publishing Limited [ISSN 0885-8624] [DOI 10.1108/08858620510603864]

The research reported in this paper represents part of the “Pensions Online? Producer, Distributor and User Attitudes and Behaviour” project, which is being funded by the Economic and Social Research Council as part of its E-Society programme. Grant No. RES-335-25-0031.

An executive summary for managers and executive readers can be found at the end of this issue.

Introduction E-commerce technology is now viewed as an integral part of marketing channels and distribution systems (Rosenbloom, 2004). Supply chain constituents are able to form digital links to share information, to buy, sell and distribute products or services and to transfer cash flow. An e-enabled supply chain is perceived as having many advantages: for example; increased business efficiency, enhanced information flows, improved transaction speed, wider geographical spread, increased temporal reach, cost reduction and competitive differentiation for e-enabled constituents (Hoffman et al., 1998; Zank and Vokurka, 2003). In order to fully realise these benefits it has been suggested that upstream members of a supply chain, such as manufacturers, might work with The Emerald Research Register for this journal is available at www.emeraldinsight.com/researchregister

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established “bricks and mortar” intermediaries (Scott, 2000). Drivers for disintermediation include the desire to differentiate and compete on the basis of reduced error, increased speed, reduced costs, increased geographical reach and increased richness of the product offering (Davenport, 1993: Evans and Wurster, 2000). An additional factor also might be the desire to serve a growing online consumer market when incumbent intermediaries are failing to develop online capability. However, contrary to this position are studies that identify the importance and variety of functions that are provided by intermediaries which include specialised information provision, professional advice, customisation to consumers needs and reduction of uncertainty (Kimiloglu, 2004). Thus a company bypassing a distribution network built up over decades to pursue commerce in cyberspace is exposed to considerable risk (Ghosh, 1998). Zank and Vokurka (2003) in a survey of manufacturing supply chain constituents found that most companies perceive that the internet has positive supplementary impact on supply chain relationships. Therefore it is important to develop an understanding of the forces that are shaping e-business development within the supply chain. Co-ordinated and collaborative e-commerce development amongst supply chain members may increase effectiveness and strengthen linkages (Basch, 2000), but fragmented adoption might result in business inefficiency and weakened links between supply chain members. Business-tobusiness marketing practitioners need to understand the current and potential e-commerce requirements of their supply chain partners in order to maximise intended benefits and to ensure that e-commerce investment generates a return (Zank and Vokurka, 2003). Knowledge of the factors that are driving e-business capability amongst supply chain members will be of use in determining the nature, scope and need for any marketing support to facilitate adoption. Although a wide range of e-commerce activities are distinguishable, including EDI, e-mail and Intranet use (Chau, 2003), this study focuses on the development and use of web sites. A web site is the mechanism that combines the sales and marketing functions that an intermediary undertakes on behalf of the supplier, therefore an intermediary web site is the interface between the supplier and the customer and is a supplier’s route to the online market. Hence, this paper examines intermediary ecommerce development through examining the forces shaping web site development amongst intermediaries within an extended supply chain. This research uses Rogers’ (1995) model of innovation as the theoretical underpinning for a survey of 5,000 financial services intermediaries and reports on the factors influencing web site development, the characteristics of adopters and patterns of web site usage amongst this group.

information technology (see Larsen and McGuire, 1998), Rogers’ (1995) model of innovation diffusion is widely accepted by researchers as useful in an examination of the critical characteristics of technology adoption (Al Qirim, 2003). According to Rogers’ (1995) model, organisations within an established social environment will not all adopt a specific innovation at the same time (Beatty et al., 2001). Rogers (1995) suggests that it is possible to classify organisations into one of five adopter categories determined by their innovativeness relative to other organisations in their social system: innovators, early adopters, early majority, late majority and laggards. Thus, the first research question is: RQ1. Can adopter categories be identified within the intermediary population according to Rogers’ (1995) model? A number of factors have been shown to influence the adoption of innovations. Prior empirical research suggests four determinants of innovation adoption: the characteristics of the innovation, the characteristics of the organisation, the environmental context and the characteristics of the individual decision makers (Kaplan, 1999; Moore and Benbasat, 1996; Premkumar and Roberts, 1999; Thong, 1999; Thong and Yap, 1996). Innovation characteristics are given as: compatibility, complexity, relative advantage, trialability and observability (Rogers, 1995). Of these attributes relative advantage, compatibility and complexity have been found significantly to influence the adoption of systems technologies whilst trialability and observability have not been addressed widely in studies of IT innovation at an organisational level (Beatty et al., 2001). In terms of organisational characteristics the most frequently measured is size – usually measured through number of employees or revenues and relates positively to adoption (Nguyen et al., 2003). For example, larger firms tend to adopt before smaller firms. Blili and Raymond (1993) recognised that small and medium-sized enterprises (SMEs) – enterprises which are not in the largest 10 to 20 percent of industry firms (OECD, 2000) – encounter unique problems in comparison with larger firms: namely limited financial resources, low skills and minimal strategic management. Additional organisational factors identified as influencing IT adoption include, top management support, quality of IS, user involvement, product champion and resources (Kwon and Zmud 1987). External environment characteristics that may influence the adoption of IT include competitive pressure, support from technology vendors, pressure from buyers and suppliers (Premkumar and Roberts, 1999). Raymond (2001) argues for enriching Rogers’ (1995) model within an interorganisational context, particularly when adoption decisions may be linked to those of business partners. In this context, channels of communication can influence adoption behaviour. Competitors, B2B vendors, suppliers and customers are all potential sources of innovation communication and as such can be viewed as change agents, who are individuals with influence over innovation decisions (Rogers, 1995). Communication channels can be classified into those that are mass media (involving a transmitting medium), those that are interpersonal (face-to-face), those that are homophilous (from a source that shares similar attributes to the individual) and those that are heterophilous (from a source that is

Theoretical background Diffusion is defined as “the process by which an innovation is communicated through certain channels over time among members of a social system” (Rogers, 1995, p. 2). Diffusion research has been conducted by researchers from a variety of different disciplines and its origins can be traced back to Tarde (1903). However, in recent years, there has been an integration of concepts and generalisations (Rogers, 1995). Although not without criticism of its application to 188

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Research context

different or superior in terms of knowledge or skill to that of the individual) (Rogers, 1995). The influence of communication channels has been found to vary according to adopter category. For example, in the case of early adoption amongst farmers Ryan and Goss (1950) found that interpersonal homophilous sources were more important than interpersonal heterophilous sources. Finally the characteristics of the individual decision maker, such as age, experience and psychological traits have also been found to influence adoption (Rogers, 1995): RQ2. What is the relationship between the rate of adoption as indicated by adopter categories and influencing factors such as organisational size? RQ3. Are there any individual factors that appear to be critical for web site development?

Rogers (1995) defines a social system as a set of interrelated units that are engaged in joint problem-solving to accomplish a common goal. This research focuses on UK independent financial advisors (IFAs) as forming such a social system. IFA status was created by the Financial Services Act 1986, and indicates an intermediary who deals with savings and investment products from a range of financial services providers rather than a tied agent who deals with only one supplier (Harrison, 2000). The IFA is viewed as a critical channel to market for financial services institutions in the UK, as consumers demand impartial advice on savings and investment products whilst product providers have refocused on them as a pivotal channel in their overall distribution strategy (Datamonitor, 2002). Vasudavan and Standing (1999) have identified three common key tasks performed by intermediaries these are: information broker: passing information between customers and providers; transaction processor: completing application forms and forwarding payment to providers; and customer advisor. In addition, according to Vasudavan and Standing (1999), intermediaries have specialised knowledge and access to specialised sources of information. Specialised knowledge is to found amongst IFAs since professional qualifications have to be gained in order to become licensed as an IFA in the UK, and specialised information, that is not generally available to the consumer, is accessed through subscription and membership of online portals, dedicated publications, professional organisations and trading networks. These qualifications, tools and knowledge networks support the IFAs as experts in integrating the financial needs of consumers with the services provided by financial services suppliers and also create the links that constitute a social system. An overview of the factors driving web site development within the financial services sector is timely. A recent government report on the medium and long term savings industry identified that co-ordination and co-operation difficulties are manifest through a lack of customer facing sites, low levels of capital investment, poor integration of legacy systems and a lack of common standards (Sandler, 2002). Due to successive and proposed legislation to remove entry barriers and cap administrative charges, providers are looking to reduce their processing costs. Investment in technology is one option which in turn increases the necessity for IFAs to have enhanced technological capability that facilitates end-to-end processing in order to realise cost savings. Furthermore, within the banking sector there are indications that consumers value the relative advantage of online banking in terms of the increased convenience and enhanced service of online access (Kolodinsky et al., 2003). However the technological capability of IFAs is relatively poor hence the market presents a significant “technology catch-up” opportunity (Datamonitor, 2002). Therefore this paper reports on the factors driving web site development amongst IFAs who are involved in the distribution of medium and long-term investment products.

Although each characteristic may exert a separate influence on innovation adoption and diffusion, it has been shown that the combination and interplay between factors within specific contexts is also important (Al-Qirim, 2003). Rogers (1995) outlines the need for context specific research into variables related to innovation adoption, the factors that explain the rate of adoption and the role of communication channels at different stages of adoption. In the context of online banking, Bradley and Stewart (2003) highlight key factors driving banks to adopt online banking are the adoption by other banks, competitive forces, consumer demand and the availability of technology: RQ4. Do the individual factors combine meaningfully to stimulate web site development? Early adopters of IT can gain an advantage through early adoption, in the same sense that early entrants into a market can gain advantage (Lambkin, 1988). Early adopters are companies that have perceived the advantage to be gained by action, are likely to be forward thinking, and are less likely to be inhibited by the IT demands placed on companies by moving to the web (O’Keefe et al., 1998). Indeed, the goals and motivations for being an innovator or first adopter can have a significant impact on the decision of whether to adopt and when. Such goals might be to achieve competitive advantage or protect strategic position (Bass, 1980; Johannessen et al., 1999) often promoted by the desire for the organisation to become superior to competitors and to serve customers better or meet the demands of customers better (John and Davies, 2000). However, the extent to which adoption of an innovation can yield a competitive advantage is relatively short-lived. As the innovation becomes more widespread, competitive advantage diminishes and innovation becomes a necessary competitive requirement. It is argued that the need for innovation leads to imitation (Bradley and Stewart, 2003). Hence, the organisational goals or motivations for adopting an innovation and the subsequent use or implementation of the innovation may change over time according to adopter categories: RQ5. Do the web site development drivers influence the timing of adoption? (i.e. are different adopter categories influenced by different critical factors?) RQ6. Does web site adoption timing influence subsequent use of the technology? (i.e. do the different adopter categories make different use of the technology ?)

Research method A two-stage research design, combining qualitative and quantitative phases, was considered appropriate for the 189

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research questions being addressed. The qualitative phase was used to develop a list of factors that IFAs identified as being important to their initial decision to develop a company web site. The use of qualitative research captures the “social actors” points of view (Blaikie, 2000) and thus meets the objective of exploring the perceptions of the social system. Rogers (1995) notes that diffusion research has been criticised for its pro-innovation bias and that there exists a need for researchers to “see an innovation through the eyes of their respondents” (p. 111). Data were collected through a total of 20 UK-wide individual interviews conducted from November 2003 to May 2004. Participants volunteered to take part in the research after a request was circulated through a professional network. Interviews were conducted in the major UK financial centres such as London, Bristol and Edinburgh together with other key areas such as the Home Counties and the North East. Participants were drawn from the different sizes of IFA companies ranging from those with turnovers of more than £5 million to sole traders and represented IFAs at different stages of web site development. Given the dynamic and, at times, complex relationship between internet development and social interaction, data collection followed the phenomenological tradition and respondents were asked to relate the story of web site development. (Thompson et al., 1989). The methodology facilitated the capture of the “processural view” of web site development and captured some degree of longitudinal data through participants’ recollections (Bryman, 1988, p. 140). The interviews were transcribed and then analysed using a method of content analysis informed by critical incidence technique (CIT). CIT is a classification technique employing the content of stories or “critical incidents” as data. Critical incidents are defined as “certain important facts concerning behaviour in defined situations” (Flanagan, 1954). It is recognised that these research methods come from what is perceived to be disparate philosophical traditions of positivism and interpretivism (see Denzin and Lincoln, 2000). The combined use of these techniques was considered appropriate given the financial industry’s rising resentment towards

research and awareness of a fixed agenda as a consequence of successive government reviews (Sandler, 2002). Hence use was made of an open unstructured interview format to allow respondents maximum freedom of expression. The 20 interviews lastest on average an hour each, ranging from 45 minutes to just over two hours. This resulted in interview transcripts of between 10 and 20 pages per interview. The “story of web site development” theme was one of several themes explored through the interviews and represented approximately one fifth of the interview time, or roughly around two pages of transcript per interview. Three of the 20 companies represented in the interviews had not developed a web site; hence, the analysis was based on the remaining 17 companies. Events that were described as shaping web site development were clustered around themes. 54 statements were elicited from the interviews which described events that shaped web site adoption and development. The 54 statements clustered into 11 key themes (shown in Table I). Identification and classification of the critical incidents was performed by the authors, who had both carried out the interviews together. Each performed an independent assessment which was then compared. Discrepancies were resolved and both authors agreed with the final classification. Within each interview, between one and six different themes were mentioned as having an impact on web development in the company. The mean and modal number of themes per company was three. This initial analysis would suggest that factors shaping web development are multidimensional, and that certain influences are linked. The 11 themes were developed into questionnaire statements, designed to measure their relative influence on the company’s web development. The “client expectation” theme was developed into two statements to reflect the differences between individual and corporate clients. The frequency of the incidents mentioned in the qualitative phase may not have reflected the importance of the incidents, for example respondents may be reporting memorable events rather than critical incidents (Fountain, 1999). Therefore to test whether the incidents actually were “critical” respondents

Table I Classification of critical incidents Theme

No. of times theme mentioned

Strategic decisions Spending on computers/IT Specific person leading web site development Key person outside company Key person inside company Web site development services Software availability/providers

8 5 5 3

Competitors’ actions Internet boom Client expectations

3 3 8

Provider developments

5

Total

9 2 3

54 statements

Example “We had an idea of really trying to enable clients to transact business online” “The biggest step forward was us getting broadband to be honest” “I had a bit more time to really try and forge the way forward . . . I saw it as part of my role” “We had a guy . . . who came in to run our web site” “It was driven by the owner” “The technology has become available” “I came across [software company] they were pushing their web site which had all the functionality that we were trying to get” “Everybody’s got a web site . . . we should just have one” “It was the sort of internet boom that was going on” “[academics] . . . they tend to have access to the internet on a day to day basis . . . expect communication by email” “They [provider] had developed a system where we as broker could input stuff into their mainframes” 17 companies

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were asked to rate their importance on a five-point scale (Andersson and Nilsson, 1964). The extract from the questionnaire is shown in the Appendix. Measurement in this way allows for differences in the relative importance of the influences within any adopter categories to be assessed. In addition to the critical incidents, the questionnaire also captured data on the web presence of the IFA including length of time on the web, how the web site is being used and key company and individual characteristics. The survey instrument was piloted among the same sample of interviewees for clarity, relevance and to estimate a response rate. The pilot was particularly useful in serving as a check of accuracy and relevance for the CIT categories, as well as resulting in a small number of changes to other items. Of the 20 companies interviewed, 16 responded to the pilot within the timeframe requested. The final questionnaire was mailed to a random sample of 5,000 IFAs stratified by size of firm. The sample was purchased from a commercial database. Questionnaires were distributed in June 2004, with a followup in July 2004. A total of 692 usable questionnaires were returned, yielding a 14 per cent response rate. There are 26,000 active advisors in the UK working in an estimated 5,000 firms, of these 37 per cent are operating as sole practitioners (Sandler, 2002). Since the prime objective of the study is to provide an insight into the development and adoption of web sites by IFAs, only a sub-set of the sample was relevant to the analysis (217 firms). The sub-set therefore consisted of those firms that have a web site and have all been in business for at least the same length of time as the company which has had a web site for the longest length of time[1]. The longest any firm in the sample had a web site for was 10 years, hence the analysis focused on all companies who had been in business for at least 10 years. This represented 388 firms, out of which 44 per cent had a web site, 12 per cent were in the process of developing a web site, and 44 per cent did not have a web site. The final sample, thus, consisted of the 217 companies who either had a web site or were in the process of developing a web site.

and £5 million and only 4 per cent have a turnover over £5 million. Almost all sole-traders (98 per cent) have turnovers of less than £1 million. Limited companies are more likely to have higher turnovers, as over one quarter (27 per cent) of the sample have turnovers over £1 million, and around 15 per cent of partnerships have turnovers of over £1 million. These characteristics are broadly consistent with the characteristics of the total sample. Can adopter categories be identified? Firms were classified into five adopter categories consistent with Rogers’ adoption curve. Classification was based on the number of years the company had a web site. The longest length of time that any company in the sample had a web site was 10 years, the most recent related to those companies who were in the process of developing a web site. Rogers (1995) uses the mean and standard deviation as key statistics by which to identify adopter categories. Continuous data is required to perform the classification in this manner. Two separate questions were used in the questionnaire to capture the data on web site adoption. One question (categorical) asked respondents whether they had a web site, did not have a web site or were in the process of developing a web site. For those companies which had an “established” web site, they were asked approximately how long they had had the web site for. The question was open-ended and elicited a combination of numerical and alphanumerical responses. While the majority responded giving the number of complete years, those with web sites for less than a year responded in a variety of ways (for example “six months”, “half a year” “a couple of weeks”) which meant that the data had to be treated as categorical. Thus, classification of adopter categories could not be performed strictly according to Rogers’ (1995) recommendation. Despite this, for those companies with web sites for one year or more, the mean length of time could be calculated and was 3.5 years with a standard deviation of 1.91. According to Rogers (1995), the cut-off point for the innovators should be 7.4 years ðmean þ 2SDÞ and the cut-off point for the early adopters should be 5.49 years ðmean þ SDÞ. While not entirely reliable, it does offer some indication of classification boundaries. Since Rogers’ recommendation could not be applied strictly, an alternative means of classification based on categorical groupings was considered. Beatty et al. (2001) conducted a study into web site adoption and classified companies into adopter categories based on natural groupings in the data. Examination of the frequency of responses for length of time in this study indicated natural groupings as indicated in Table II.

Quantitative research findings In terms of type of firm, 56 per cent of the final analysis sample comprises limited companies, 28 per cent are partnerships and 16 per cent are sole traders. In addition to this, approximately 6 per cent of the sample belongs to a network (roughly equal numbers of sole-traders and limited companies, much fewer partnerships belong to a network). With regard to the size of client base, 37 per cent of the sample has 100 or fewer clients, 31 per cent has between 1001-3000 clients and 32 per cent has over 3000 clients. The majority of the sample (76 per cent) has turnovers of less than £1 million, 20 per cent have turnovers between £1 million Table II Adopter categories Category

Timeframe

Innovators Early adopters Early majority Late majority Laggards Total

Between 7 and 10 years At least 5 years but less than 7 years At least 3 years but less than 5 years Less than 3 years Currently developing site

191

Frequency

Percentage

10 42 63 49 45 209

4.8 20.1 30.1 23.4 21.5 100.0

Critical factors affecting intermediary web site adoption

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Beatty et al. (2001) note that commercial web use is estimated to have started around 1993, however the earliest date which any company in this sample developed a web site was in 1994 one year after this date. Due to the differences in time of first adoption, the overall timeframe of the study, and the industrial context of the sample, it is not possible to retain complete parity with the study of Beatty et al. However, some overlaps exist in terms of the timeframe for innovators (adopting around three years before the early adopters), the two-year timeframes of early adopters and the early majority, and the classification of laggards as those currently developing a web site. The main difference is in terms of the late majority, which is less than three years in this study and less than one year in the study by Beatty et al. (2001). Combined with the results from the means and standard deviation analysis, the categories presented in Table II seem to be appropriate. In terms of how this relates to Rogers’ (1995) original model, Figure 1 shows the comparison. While the proportions within each of the categories are different, the general shape and pattern of the curve is similar for the first three groups. The last two groups do not show the same tailing off as in the Rogers’ (1995) model. An explanation for this could be that Rogers’ model commonly refers to the adoption of an innovation throughout its life-cycle, bearing a similarity to and consistency with the product life-cycle curve. The web could be argued to be at the mature stage of its life cycle; it has certainly not reached the end of its life, and this would

explain the apparent continued adoption of the web by firms in the sample. What is the relationship between adopter categories and firm socio-economic characteristics? Given that all the firms in the analysis are intermediaries in the financial services sector, an underlying assumption is that they are all part of the same social system. Notwithstanding, different types of firms exist. The industry comprises at one extreme sole traders with under 100 clients and a very local presence and at the other extreme large organisations with a number of outlets, over 3000 clients and a national presence. It is therefore important to assess whether any differences exist in adoption patterns among firm types. A chi-square measure of association was conducted to test for statistically significant differences between the adopter categories and the following key company characteristics: type of firm, size of client base and turnover (see Table III). No statistically significant differences were found in terms of type of firm and adopter categories, although it is interesting to note that 80 per cent of innovators are limited companies. Statistically significant differences, however, were noted between the adopter categories and size of client base and the adopter categories and turnover at the 10 per cent (Pearson chi-square value of 13.852 and sig. 0.086) and 5 per cent (Pearson chi-square value of 10.821 and sig. 0.029) levels respectively. Larger client bases tend to produce larger

Figure 1 Comparison of Rogers’ curve with the sample adoption curve

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Volume 20 · Number 4/5 · 2005 · 187 –199

Table III Profile of adopter categories Company characteristic

Firm type Limited company Partnership Sole trader Total Size of client base Under 1,000 1,001-3,000 Over 3,000 Total Turnover Under £1 million Over £1 million Total

Innovator

Early adopter

Early majority

Late majority

Laggards

80 10 10 100

50 33 17 100

64 23 13 100

49 34 17 100

56 23 21 100

40 10 50 100

28 30 42 100

35 27 38 100

44 31 25 100

37 47 16 100

80 20 100

69 31 100

65 35 100

79 21 100

91 9 100

Note: Figures are percentages

characterised by formal strategic planning. However Chau (2003) in an examination of e-business activities amongst Australia SMEs, differentiates between the experimental use of E-commerce to support existing business processes and its strategic use to leverage new business opportunities and benefits. Importantly he observes that contrary to many existing staged models of e-business adoption, SMEs do not necessarily move between phases in a sequential manner. Doolin et al. (2003) draw similar conclusions in relation to larger enterprises engaged in e-commerce. Comparing distributors (which is essentially part of an IFAs role) with manufacturers and customers, Zank and Vokurka (2003) found that distributors were more likely to believe that the role of e-business in overall strategy was a necessary response to competition than the other groups. Therefore, it seems that e-business strategy is primarily a reactive approach for distributors and may explain the inconsistency is how strategic issues have been reported between the interviews and the survey. This may explain why the internet boom in general is ranked higher than the influence of clients or product providers, suggesting a reaction to general internet excitement rather than a response to either client needs or requests from trading partners.

turnovers, although the two variables are not perfectly correlated, neither is the relationship between firm size and turnover and firm size and client base. Compared with the other adopter categories, innovators have a much higher proportion of larger client bases. At the same time, innovators also seem to be polarised between high and low client base sizes, which further distinguishes them from the other adopter categories. Are any individual incidents critical for web site development? Table IV shows the 12 statements along with their mean and modal scores. The statements were measured using a fivepoint importance scale ranging from 1 ¼ not at all important to 5 ¼ very important. Overall, the top two factors influencing the original development of the web site are the strategic decisions made by the company and the influence of a key person within the company, suggesting the dominance of formal strategic planning. This is somewhat contradictory to the unstructured responses of some of the small IFA firms interviewed and might suggest the influence of a “halo” effect. Indeed, Stockdale and Standing (2004) cite Hall (1995) as saying that SME’s participation in e-commerce is not often Table IV Factors influencing web site development Statement

The influence of a key person within my company Strategic decisions made by my company A specific person within the company who took the lead in web developments The internet boom in general Individual clients expected us to have a web site Corporate clients expected us to have a web site Developments by product providers Web site development services were offered by an outside company Competitors were launching web sites Software became available that we could use My company was spending money on computers The influence of a key person outside my company

193

Mean

Mode

3.06 3.29 2.91 3.17 2.85 2.73 2.65 2.65 2.53 2.29 2.20 2.01

4 3 3 3 3 1 1 1 1 1 1 1

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Journal of Business & Industrial Marketing

Tina Harrison and Kathryn Waite

Volume 20 · Number 4/5 · 2005 · 187 –199

Do the individual critical incidents combine meaningfully to stimulate web site development? The first step involved assessing the dimensionality of the 12 web site development influencers as this was not known a priori. The qualitative research indicated that certain influences worked together, suggesting the potential multidimensionality of the statements. According to Spector (1992, p. 54) “exploratory factor analysis is a good technique for studying the dimensionality of a scale, either a (supposedly) unidimensional or a multidimensional one”. Principal components analysis was chosen as the most appropriate technique of factor analysis. Prior to performing PCA the suitability of the data was assessed. Inspection of the correlation matrix revealed the presence of many coefficients of 0.3 and above. The Kaiser-Meyer-Olkin of 0.711 exceeds the recommended value of 0.6 (Kaiser, 1970, 1974) and the Bartlett’s test of sphericity (Bartlett, 1954) reached statistical significance, supporting the factorability of the correlation matrix. In addition, the ratio of observations to variables far exceeds the acceptable ratio of 4-5:1 recommended by (Hair et al., 1987). A Varimax rotation was used, as this is considered the best for computing factor scores to be used in subsequent analysis. PCA revealed the presence of four components with eigenvalues exceeding 1, explaining in total 60.6 per cent of variance. Table V shows the results of the analysis. The subsequent dimensions were then subjected to reliability analysis to test for the internal consistency of the scale constructs. The results indicate three of the dimensions show very good internal consistency, factor 3 shows weaker internal consistency. However, since the correlation coefficients for the two items on which this factor loaded were high it was decided to retain the factor in subsequent analysis. The four factors were then labelled “emergent”, “deliberate”, “responsive” and “me-too” influences following inspection of the individual statements:

.

.

.

.

Factor 1: emergent. These items are all external influences and relate predominately to the opportunities created externally to develop a web site or the fortuitous circumstances surrounding the web site development. Hence, web site development emerged as a result of these external influences, it was not planned or guided strategically but rather occurred serendipitously. It might be expected that the early majority and perhaps some early adopters would be influenced most by such factors. The initial innovators would have already adopted the technology and external influences may then make use of marketing to widen the participation to other segments providing opportunities for engagement. Factor 2: deliberate. These items all relate to a planned strategic effort to develop a web site that was managed and handled internally. Hence, it represents a deliberate effort to develop a web site. We would expect that the innovators and early adopters would be influenced the most by this factor. Factor 3: responsive. The two main items that this factor loads on are the expectations of clients, both individual and corporate, however the influence of providers also shows a moderate loading in addition to factor 1. It would appear that companies are responding to the expectations of clients (and perhaps other supply-chain members) to have a web site, hence this reflects a responsive developmental effort. We would expect the early and late majority to be influenced by this the most – as clients begin to realise that companies offer web services, they will begin to expect it to be offered more as a standard feature. Factor 4: me-too. The two main items loading on this factor relate to the influence of competitors and the internet boom in general, suggesting that web site development is a “me-too” reaction to the marketplace in general. Rogers (1995) suggests that the heart of the diffusion process consists of the modelling and imitation by potential adopters of their network partners who have adopted

Table V Principal components analysis results Factor 1 Emergent

Item My company was spending money on computers The influence of a key person outside my company Web site development services were offered by an outside company Software became available that we could use Developments by product providers Strategic decisions made by my company A specific person within my company who took the lead in web site development The influence of a key person within my company Individual clients expected us to have a web site Corporate clients expected us to have a web site Competitors were launching web sites The internet boom in general Eigenvalue Percentage of variance Cumulative percentage of variance

Factor 3 Responsive

Factor 4 Me-too

0.564 0.680 0.712 0.582 0.502 0.540 0.830 0.831 0.886 0.890

3.216 26.803 26.803

Notes: Kaiser-Meyer-Olkin ¼ 0:711. Bartlett’s test of sphericity: approx. chi square: 1144.044, df 66, sig. 0.000

194

Factor 2 Deliberate

1.576 13.135 39.938

1.456 12.129 52.068

0.779 0.743 1.032 8.598 60.665

Critical factors affecting intermediary web site adoption

Journal of Business & Industrial Marketing

Tina Harrison and Kathryn Waite

Volume 20 · Number 4/5 · 2005 · 187 –199

previously. Such a follower strategy would be expected from the late majority and laggards.

Table VII reveals that three of the dependent variables show significance at the 5 per cent level. The one variable that clearly shows no significant difference is the responsive dimension, which indicated poor internal consistency earlier. To understand what the actual differences are, the mean scores for each of the variables need to be inspected. Table VIII shows the mean scores for the three variables emergent, deliberate and me-too along with the standard deviation and rank. The findings reveal that innovators have the highest mean score on the deliberate dimension, indicating that they are most driven by the strategic direction of the organisation and key people within the company who took the lead for web site development. This is an expected finding, confirming our assumption. Early adopters have the second highest score on the deliberate dimension, which is also expected. The early majority have the highest score on the me-too dimension followed by the laggards. This is expected of the laggards and, on reflection, is perhaps not surprising for the early majority. The late majority have the lowest scores on deliberate and metoo. Laggards have the highest mean score on the emergent dimension, indicating that they are more influenced by opportunism and fortuitous circumstances surrounding web site development.

Do the web site development drivers influence the timing of adoption? In order to test our assumptions, a one-way between groups multivariate analysis of variance was performed to investigate differences in factors influencing web site development among the adopter categories. The four dependent variables used consisted of the regression factor scores of the four dimensions influencing web site development: emergent, deliberate, responsive and me-too influences. The independent variable consisted of the adopter categories. Preliminary assumption testing was conducted to check for normality, linearity, univariate and multivariate outliers, homogeneity of variance-covariance matrices, and multicollinearity with no serious violations noted. Box’s M sig. value of 0.957 clearly indicates that the data does not violate the assumption of homogeneity of variance-covariance matrices (as it is greater than0.001). Levene’s test of equality of error variances also indicates that the assumption of equality of variance for each of the web site development influencing dimensions has not been violated (e.g. sig. values of 0.376, 0.945, 0.429, and 0.751 respectively for each of the four factors are all greater than 0.05). Statistically significant differences were found between the adopter categories on the combined dependent variables (see Table VI). Wilk’s Lambda value of 0.828 and sig. of 0.002 (i.e. less than 0.05) indicates there is a statistically significant difference among the adopter groups in terms of the overall factors influencing web site adoption. However, to what extent do adopter categories differ on all the factors influencing web site development? To answer this, it is necessary to consider the dependent variables separately.

Does web site adoption timing influence subsequent use of the technology? Having established statistically significant differences between the adopter groups in terms of the factors that influenced initial web site development, the analysis then went on to consider whether differences existed in terms of how the web site is being used by firms who had adopted the web at different times. Does the time at which the innovation is adopted affect the subsequent use of the technology? For example, we may expect that firms that adopted the technology early (such as innovators and early adopters), with a deliberate strategic intention might be making greater use of the web compared with those that adopted the technology later with a less clear idea. Two key areas of web site use help to inform this. First, we asked IFAs to indicate how products were represented on

Table VI Reliability of scale constructs Reliability analysis Alpha coefficient No. of items

Factor 1

Factor 2

Factor 3

Factor 4

0.7174 5

0.6881 3

0.4340 2

0.7052 2

Table VII MANOVA results Dependent variable Emergent Deliberate Responsive Me-too

Type III sum of squares

df

Mean square

F

Sig.

10.424 11.111 1.450 12.531

4 4 4 4

2.606 2.778 0.363 3.133

2.817 2.908 .347 3.269

0.026 0.023 0.846 0.013

Table VIII Relative importance of the factors influencing web site development Adopter category

Mean

Emergent SD

Rank

Mean

Deliberate SD

Rank

Mean

Me-too SD

Rank

Innovators Early adopters Early majority Late majority Laggards

2.380 2.176 2.307 2.192 2.662

0.689 0.820 0.778 0.837 0.634

2 5 3 4 1

4.111 3.206 3.137 2.812 3.151

0.726 0.982 0.893 1.097 1.064

1 2 4 5 3

2.400 2.952 3.123 2.347 2.956

0.936 0.967 1.00 1.016 1.142

4 3 1 5 2

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their web site. This reveals the extent to which the web site is being used in the following ways: . Purely as a commercial brochure or as static advertising (i.e. there are no products displayed on the web site). . As a means of providing information (i.e. product information is provided). . As a sales channel (i.e. clients can make an application for and/or buy a product online).

way in which the web site is used with implications for the whole of the supply chain. Innovators and early adopters are more likely to have a clearer reason for developing a web site and are making most advanced use of it, with obvious benefits for both suppliers and customers. The key contribution of the research, both academically and practically, is that it provides an understanding of the factors that affect intermediary web site adoption and the role that the factors can play in widening e-participation among financial intermediaries. Rogers (1995) acknowledges that “a common problem for many individuals and organisations is how to speed up the rate of diffusion of an innovation” (p. 1). While research into web adoption exists in the context of travel and tourism and also online banking (see, for example, Wynne et al., 2001; Sathye, 1999), research into financial intermediaries and the adoption of online technology remains lacking (Laing, 1995). Adoption of technology among UK financial intermediaries is relatively limited (Datamonitor, 2002). Hence, research that offers a closer understanding of the factors that may widen e-participation is of benefit. It is widely acknowledged within the UK pensions and insurance industry that the future of efficient business lies with technology (see Pensions Management, June 2004). Yet, developing an online system is a major financial commitment that providers cannot afford to undertake without widespread support and acceptance from intermediaries (see Pensions Management, September 2004). In terms of the specific factors affecting web site adoption, the findings of this research suggest that innovators’ and early adopters’ web site adoption is planned and deliberate, consistent with the overall business strategy. In order to make adoption successful, providers need to understand the strategic orientation of intermediaries to ensure that the right facilities and services are offered. For example, different emphasis will be placed on web facilities to achieve transaction volume growth compared with increased service for existing clients. Innovators and early adopters have been shown to comprise mainly larger firms with larger turnovers, which is also supported by the findings of this research. Due to the size and degree of fragmentation of the financial intermediary market, product providers have tended to develop relationships with a number of preferred intermediaries, developing proprietary technology and networks. This tailoring of developments to typically larger organisations is argued to be a barrier to emarketplace participation (Stockdale and Standing, 2004). However, a large proportion of the financial intermediary sector comprises small and medium sized enterprises. Some of the barriers to adoption relate to recognised problems common to SME e-commerce adoption, such as connectivity, while others are more specific to the individual company such as lack of resources. In contrast, the realisation of the benefits of participation generally rests with the ability of individual SMEs to identify opportunities and to plan their online trading effectively within the constraints of their industry environment. The early majority are mainly influenced by the actions of competitors and appear to be operating a “copy-cat” strategy. For providers this is important in that they need to be aware of what the current trends are among intermediaries and show an appreciation of the most common or frequently requested web tools and facilities in order to make adoption beneficial. The late majority and the laggards are mostly influenced by

Second IFAs were asked how much of their total business is conducted online. In terms of how the web site is being used, overall 38 per cent of firms do not display or mention any products on their web site, 45 per cent offer product information only, and 17 per cent offer clients the possibility to apply for and/or buy products online. With regards to how this looks for each of the adopter categories a Chi-Square measure of association was conducted to test for statistically significant differences between the adopter groups and how the web site is being used. Table IX shows that there are statistically significant differences at the 10 per cent level. Note that laggards could not be included in the analysis as, by definition, they are only developing a web site at present. Hence web site use is not relevant to this group. The findings reveal that innovators show the most advanced use of the web site: none of the innovators are using the web site purely as brochure-ware and 44 per cent offer clients the opportunity to apply for and/or buy products online. The early adopters and the early majority show a greater propensity to use the web site for providing product information, whereas the late majority show a greater propensity not to provide any products on the web site, suggesting the greatest likelihood of using the web as a brochure or static advertising. In terms of the proportion of business conducted online, the sample is split almost equally: 52 per cent of firms do not conduct any business online, 48 per cent conduct some business online, although for the majority this represents small amounts of no more than a quarter of the total business. In terms of how this looks across the adopter groups, a ChiSquared analysis revealed no statistically significant differences.

Conclusions and implications This paper has examined intermediary e-commerce development, focusing specifically on the adoption and use of web sites, the factors influencing initial adoption, the characteristics of adopters and subsequent patterns of web site use. The findings show that there are clear differences between financial intermediaries in terms of the timing of adoption, the factors driving web site development and the Table IX Web site use by adopter category Adopter category Innovators Early adopters Early majority Late majority

Not on web site

Product information only

Apply and/or buy

0 39 30 45

56 49 54 36

44 12 16 19

Notes: Figures are percentages. Pearson chi-square: 11.243, df 6, sig. 0.081

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opportunities that arose or were presented to them to take advantage of web site technology, particularly services offered by IT/software developers. In terms of what these findings mean for providers in attempting to widen e-participation, the relationship between larger companies in developing technological relationships is seen as important, not only in capturing a significant part of the marketplace but also in terms of providing an example by which other firms influenced by a “me-too” development strategy can follow. However, given the disadvantages associated with developments tailored to larger or preferred intermediaries, an alternative or complementary approach might be to communicate with IT suppliers. A significant proportion of the sample appear to be influenced by the emergent driver – essentially opportunities that arose or emerged to develop a web site provided by external parties, mainly software developers. Rather than attempting to develop a technological relationship directly with financial intermediaries, a networked approach might prove more beneficial in this context, whereby IT suppliers act as a further intermediary in the technology supply chain between provider and IFA. This approach does not necessarily have to preclude individual provider-intermediary relationships but may offer a more inclusive approach to technology adoption and speed up the rate at which it is adopted.

take account of a wider range of facilities as they become more widespread. This study only focused on companies that had adopted the web and the critical factors affecting adoption. A similar study could be conducted into firms that have not adopted the web to understand critical factors preventing or inhibiting adoption. As well as snap-shot studies, such research could also be conducted longitudinally based on a systematic analysis of the relationships between observed external events and technology adoption as they occur.

Note 1 The decision was taken to focus only on firms that had all been in business for the same length of time since firms that had only been in business for the last two years, for example, could not have developed a web site any earlier. In this way, the analysis controlled for varying business start-up times that obviously have an impact.

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Limitations and directions for future research The research is not without its limitations, and these should be considered in terms of the impact on the findings of the research. One limitation concerns the way in which data was captured concerning the length of time the web site had been in operation. Since the data captured was not entirely continuous data, limitations were placed on the type of analysis that could be conducted. In fairness, however, it would be unrealistic to expect companies to recall the exact month when the web site was developed if that event occurred several years ago. The use of retrospective data is also a limitation affecting respondent ability to recall critical incidents (Fountain, 1999). For example, the longer the time period between events and data gathering, the greater the danger that participants may reply with expected stereotypical responses (such as the supposed halo effect noted earlier in relation to the overall importance of “strategic decisions”). In order to minimise these effects, the comprehensiveness of incidents was compared against the literature in the field as well as with a sample of intermediaries. In terms of the face validity of the categories and their constructs, Fountain (1999) notes that when a priori categories are used in studies where existing theories are clear (as in the case of this research), the validity of categories becomes less problematic than when categories are built inferentially from the data. Further studies could overcome these limitations by gathering the data longitudinally at the same time as technology adoption occurs, however, the time lags would be greater. Another limitation concerns the scope of web facilities that could be incorporated in the study. It was acknowledged in the paper that use of internet technology by financial intermediaries is quite low in the UK, hence the scope of facilities covered by the survey was scaled down to reflect current usage patterns. Future research could extend this to 197

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Kwon, T. and Zmud, R. (1987), “Unifying the fragmented models of information systems implementation”, in Borland, R. and Hirschhem, R. (Eds), Critical Issues in Information System Research, John Wiley, New York, NY, pp. 252-7. Laing, A. (1995), “The marketing of financial services to independent distributors”, Journal of Services Marketing, Vol. 9 No. 4, pp. 6-18. Lambkin, M. (1988), “Order of entry and performance in new markets”, Strategic Management Journal, Vol. 9, special issue, pp. 127-40. Larsen, T. and McGuire, E. (Eds) (1998), Innovation Systems Innovation and Diffusion: Issues and Directions, Idea Publishing Group, Hershey, PA. Moore, G. and Benbasat, I. (1996), “Integrating diffusion of innovations and theory of reasoned action models to predict utilisation of information technology by end-users”, in Kautz, K. and Preis-Heje, J. (Eds), Diffusion and Adoption of Information Technology, Chapman & Hall, London, pp. 132-46. Nguyen, D.T.H.C., Murphy, J. and Olaru, D. (2003), “Investigating the adoption of electronic customer service by Australian businesses”, Managing Service Quality, Vol. 13 No. 6, pp. 492-503. OECD (2000), The Bologna Charter on SME Policies: Enhancing the Competitiveness of SMEs, The Global Economy: Strategies and Policies, OECD, Bologna. O’Keefe, R.M., O’Connor, G. and Kung, H. (1998), “Early adopters of the web as a retail medium: small company winners and losers”, European Journal of Marketing, Vol. 32 Nos 7/8, pp. 629-43. Premkumar, G. and Roberts, M. (1999), “Adoption of new information technologies in rural small businesses”, OMEGA International Journal of Management Science, Vol. 27 No. 4, pp. 467-84. Raymond, L. (2001), “Determinants of web site implementation in small business”, Internet Research: Electronic Networking Applications and Policy, Vol. 11 No. 5, pp. 411-24. Rogers, E.M. (1995), Diffusion of Innovations, 4th ed., The Free Press, New York, NY. Rosenbloom, B. (2004), Marketing Channels, 7th ed., Thomson South-Western, Cincinnati, OH. Ryan, B. and Goss, N.C. (1950), “Acceptance and diffusion of hybrid seed corn in two Iowa communities”, Research Bulletin, No. 372, Agricultural Experiment Station, Ames, IA, pp. 665-6, 679. Sandler, R. (2002), Medium- and Long-Term Retail Savings in the UK – A Review, HM Treasury, London. Sathye, M. (1999), “Adoption of internet banking by Australian consumers: an empirical investigation”, International Journal of Bank Marketing, Vol. 17 No. 7, pp. 324-34. Scott, J. (2000), “Emerging patterns from the dynamic capabilities of internet intermediaries”, Journal of ComputerMediated Communication, Vol. 5 No. 3, available at: www. ascusc.org/jcmc/vol5/issue3/scott.html (accessed 22 October 2003). Spector, P.E. (1992), “Summated rating scale construction: an introduction”, Quantitative Applications in the Social Sciences, Series No. 07-082, Sage, Newbury Park, CA. Stockdale, R. and Standing, C. (2004), “Benefits and barriers of electronic marketplace participation: an SME 198

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perspective”, The Journal of Enterprise Information Management, Vol. 17 No. 4, pp. 301-11. Tarde, G. (1903), The Laws of Imitation, Clews Parsons, E. (trans.), Holt, New York, NY. Thompson, C.J., Locander, W.B. and Pollio, H.R. (1989), “Putting consumer experience back into consumer research: the philosophy and method of existential phenomenology”, Journal of Consumer Research, Vol. 16 No. 2, pp. 133-45. Thong, J.Y.L. (1999), “An integrated model of information systems adoption in small business”, Journal of Management Information Systems, Vol. 15 No. 4, pp. 187-214. Thong, J. and Yap, C. (1996), “Information technology adoption by small business: an empirical study”, in Kautz, K. and Preis-Heje, J. (Eds), Diffusion and Adoption of Information Technology, Chapman & Hall, London, pp. 160-75. Vasudavan, T. and Standing, C. (1999), “The impact of the internet on the role of travel consultants”, Participation and Empowerment: An International Journal, Vol. 7 No. 8, pp. 213-26.

Walters, D. and Lancaster, G. (1999), “Using the internet as a channel for commerce”, Management Decision, Vol. 37 No. 10, pp. 800-16. Wynne, C., Berton, P., Pitt, L., Ewing, M. and Napoli, J. (2001), “The impact of the internet on the distribution value chain”, International Marketing Review, Vol. 18 No. 2, pp. 420-31. Zank, G.M. and Vokurka, R.J. (2003), “The internet: motivations, deterrents, and impact on supply chain relationships”, SAM Advanced Management Journal, Vol. 68 No. 2, pp. 33-400.

Further reading Datamonitor (2001), UK Independent Advisors 2001, reference code DMFS1385, Datamonitor Europe, London. Tabachnick, B.G. and Fidell, L.S. (1996), Using Multivariate Statistics, 3rd ed., Chapter 11, Lawrence Erlbaum, Mahwah, NJ. Thompson, C.J. and Haytko, D.L. (1997), “Speaking of fashion: consumers’ uses of fashion discourses and the appropriation of countervailing cultural meanings”, Journal of Consumer Research, Vol. 24 No. 1, pp. 15-24.

Appendix Figure A1 Extract from the questionnaire

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Cooperative adoption of complex systems: a comprehensive model within and across networks Angela Hausman The University of Texas-Pan American, Edinburg, Texas, USA

Wesley J. Johnston Center for Business and Industrial Marketing, Georgia State University, Atlanta, Georgia, USA, and

Adesegun Oyedele The University of Texas-Pan American, Edinburg, Texas, USA Abstract Purpose – The purpose of this study was to develop a better understanding of cooperation among members of network firms. Design/methodology/approach – An extensive literature review of industrial cooperation/adaptation was conducted, especially research pertaining to industrial adoption of communication technology across partner firms. This review was combined with elements of population ecology, as it has been applied to business networks, and other sociological aspects of inter-firm relationships to develop a set of propositions related to cooperative adoption. Findings – This is a conceptual paper, so there were no quantifiable results. Instead, the paper contains a number of propositions related to the relational, structural, and influential aspects that affect adoption and sustained use of innovative products in a network context. Research limitations/implications – The lack of empirical support for hypothesized relationships is the major limitation. However, the study provides guidance toward empirical testing and suggests a number of managerial implications resulting from the understandings provided by the proposed relationship. Originality/value – This study helps extend earlier models developed to understand intra-organizational adoption to reflect the more common situation where adoption occurs within and affects a network of related firms. Keywords Organizations, Telecommunication networks, Business-to-business marketing Paper type Research paper

systems commonly include hardware, software, network facilities, procedures and rules, data/databases, and knowledge exchange between two or more firms (Barrett and Konsynski, 1982). As such, IOS are complex, involving substantive changes in the operation of individual firms, with requisite adoption extending to encompass other networked firms. Unfortunately, IOS are a two edged sword and most of the advantages of these systems are also its major drawbacks. Specifically, sharing between organizational units decreases flexibility in the network by increasing idiosyncratic investment and increases firm vulnerability to potentially unethical behaviors of both partners and outsiders who might effectively breach system security (Emmelhainz, 1990). Add to this the tangible and intangible costs of adoption, including acquisition costs and short-term productivity declines, and it is easy to see why adoption of such systems is problematic (Emmelhainz, 1990; Iacovou et al., 1995). Now add to these difficulties by imagining the inter-organizational effort needed to encourage adoption by networked firms and the potential power struggle between them and you get some idea of the difficulties encountered. Extant research on organizational adoption suggests that organizational adoption is more complex and this complexity increases as the number of firms affected increases (e.g. Tornatzky and Fleischer, 1990; Wang and Tsai, 2002; Srinivasan et al., 2002). The very nature of interorganizational adoption adds an additional layer of

An executive summary for managers and executive readers can be found at the end of this issue.

Introduction In today’s increasingly competitive global marketplace, companies create value and ensure survival based on their ability to manage the complex web of suppliers and customers comprising their value chain. At the heart of this process is the accurate, timely, and complete disclosure of information between value chain partners to enables the types of coordinated action mandated by exchange partners (Handfield and Nichols, 1999). This coordinated action is facilitated by inter-organizational systems (IOS) such as EDI (electronic data interchange), ERP (enterprise resource planning), and VMI (vendor managed inventory), which act as electronic information conduits between partners. IOS The Emerald Research Register for this journal is available at www.emeraldinsight.com/researchregister The current issue and full text archive of this journal is available at www.emeraldinsight.com/0885-8624.htm

Journal of Business & Industrial Marketing 20/4/5 (2005) 200–210 q Emerald Group Publishing Limited [ISSN 0885-8624] [DOI 10.1108/08858620510603873]

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complexity to the organizational process, since adoption in this context (termed cooperative adoption) is often initiated by a major value chain partner (the focal firm) who encourages other networked firms (the recipient firms) to adopt an IOS system to facilitate the exchange and flow of transaction information (Barber, 1991; Hausman and Stock, 2003). In networks, we might more accurately model this as focal firms, recognizing that several firms may band together to encourage adoption among a group of recipient firms. Effective cooperative innovation adoption requires recipient firms implement the system without creating conflict that might damage the relationship between recipients and focal firms. Network theory argues that each firm is embedded within multiple overlapping networks, such that changes in one network impact their functionality and relationship with firms in other networks to which they are members. This web of relationships is analogous to an ecosystem, in that changes tend to ripple through the system affecting the appropriateness of individual strategic decisions. Additionally, in a focal firm-initiated adoption, the recipient firms may perceive some level of pressure as the focal firm uses its leverage to influence their adoption (Pitts, 1991) or members lobby for alternate strategies. Since networks are self-organizing systems, where cooperation occurs through the successful negotiation of numerous local internal and external relationships, individual firms have the ability to either acquiesce to the demands of the focal firm or reject those demands (Ritter et al., 2004). Recipient firms who are “coerced” into cooperation by stronger partners may not be totally committed to the implementation of the system and their lack of commitment can hinder networked firms from realizing the system’s full benefit. Moreover, use of leverage by the focal firm (or other network firms) might negatively impact the relationship between one or more recipient firms; a danger that might outweigh the benefits of IOS adoption. The dominant paradigm in the diffusion/adoption literature involves the role of information exchange in driving the process, including the bass model (Mahajan et al., 1990) and Rogers’s (1995) treatment of adoption. These models presume awareness of an innovation is a major limiting factor in its adoption and extensive research has investigated factors that promote the flow of this awareness to nonadopters, as well as adopter traits and product features that promote adoption. Certainly, awareness of the innovation and its relative advantages contribute significantly to our understanding of the adoption decision by the focal firm, but do not go far enough in explaining how the innovation moves from the focal firm to those recipient firms whose adoption is needed. Less research has fully developed the role of inter-organizational and social forces between actors involved in the adoption process, although this aspect is alluded to in the Bass model through the interpersonal communication construct. Maute and Locander (1994) contend that adoption is better understood by looking at these social forces. Prior research associated social aspects of adoption has been fragmented, focusing on evaluating a relatively small number of variables that potentially impact the adoption of specific IOS, while ignoring the breadth of forces acting on this adoption. In addition, while existing models define intrafirm variables affecting the decision, dyadic and network factors impacting adoption of these systems have been largely

ignored. Finally, existing models tend to be static and fail to model the sustained use of the innovation (implementation) and the ultimate effect of the process on the network. To fill this void, a multi-level model of adoption is needed, incorporating empirically tested financial, economic, and interpersonal variables that may influence the decision to adopt and implementation of an innovation (simply referred to as adoption) proposed by a focal firm. This paper develops a model to facilitate understanding of the first level of this model, the network level. There are two major advantages to the model developed in this paper over existing ones. First, the model is more holistic, proposing relationships between a very broad number of potential influential variables acting at the network interface.. Second, the model proposes relationships affecting the adoption process within the network, recognizing the effect of these variables on multiple firms and how that effect might be different in the network context than within an individual firm. In developing this framework, we integrate work on inter-organizational adoption (cf. Tornatzky and Fleischer, 1990; Hausman and Stock, 2003; Wang and Tsai, 2002; Srinivasan et al., 2002), with insights from other types of adoption and innovation literature, especially those alluding to the social nature of adoption like, Maute and Locander (1994) and Rogers (1995). These perspectives are combined with other adoption research (both in organizational and consumer adoption) and empirical evidence from the interorganizational adaptation and relationship literatures (cf. Anderson and Weitz, 1992; Anderson et al., 1994; Heide and John, 1990; Venkatesh et al., 1995; Wilson, 1995).

The process of inter-organizational adoption Several different approaches have been used to understand the functionality of networks. This section will review the contributions of these approaches to the emerging model of network adoption. We begin with population ecology – a set of theories borrowed from the biological sciences to understand the interrelationships of different species occupying and competing in the same habitat. We then move on to a discussion of adoption within human social systems. Networks and population ecology To understand how cooperative adoption might be different from other types of adoption, we must look at the structure of inter-organizational systems. Increasingly, firms are part of a web of relationships that encompass both vertical partners (such as suppliers and customers) and horizontal partners (including both competing and non-competing firms), which overlap within markets (Achrol, 1997). Managing such networks is unwieldy, as they are “self-organizing systems where there is not necessarily a leader or captain” (Ritter and Gemu¨nden, 2003, p. 693). Organization in these systems, like those in ecosystems, involves many microinteractions to coproduce outcomes (Ritter et al., 2004). Not all networks are the same, however, and some networks have powerful members or groups of members who have the ability direct the actions of other firms through their control over necessary resources (Ritter et al., 2004). These negative dependencies may be expedient for producing joint action, but they have negative long-term consequences. For instance, the dependency may coerce 201

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partners into cooperative action, only to see the action fail through their lack of commitment to the course of action. This symbolic adoption and its negative consequences noted in prior studies (Rogers, 1995). Moreover, negative dependency might lead to dissolution of the relationship since the conflict generated by the use of coercive influence acts as a cancer to slowly destroy the effectiveness of other joint actions. The cycle of conflict, decreased cooperation, and lower performance ultimately outweighs any benefits achieved and one or more firms decide to terminate the relationship. Unlike ecosystems, however, organizations have the ability to act proactively by anticipating or directing change within the network. In fact, organizational (perhaps network) survival relies on the ability of firms to recognize environmental opportunities and mobilize network partners to behave in a manner that capitalizes on them. The learning organization literature refers to the first as environmental sensing and a great deal of research supports its importance in organizational survival (Day, 1994). The latter involves interorganizational adaptation or, in the context of innovations, cooperative adoption (Hausman and Stock, 2003). This suggests a positive dependency that encourages joint action among partner firms that encourages integration of individual competencies toward mutually beneficial outcomes (Ritter et al., 2004).

innovation including compatibility, relative advantage, complexity and trailability (e.g. Rogers, 1995; Zaltman et al., 1973). Although these provide insights into the network adoption process, they do not include variables specific to cooperative adoption.

Conceptual framework of cooperative adoption Prior models of organizational adoption are primarily limited to the intra-organizational context where the firm makes an adoption decision and employees subsequently decide whether to use the innovation (cf. Zaltman et al., 1973). Our framework builds on these models, specifically postulating critical relationships functioning in the interface between firms. It categorizes network-level determinants of cooperative adoption into four major factors: structural factors, influence factors, which include various efforts the focal firm (or firms) might use to encourage recipient adoption, and relational factors, which include interorganizational social exchange characteristics, reflecting the composition of the network. The next section will develop specific propositions underlying this model. Although not modeled in this study, the organizational and individual-level factors identified in Frambach and Schillewaert (2002) might also have substantial impact on adoption or utilization of the technology.

Cooperative adoption Rogers (1995) defines adoption as “a decision to make full use of a new idea as the best course of action available.” In other words, adoption involves some form of evaluation of an innovation to determine if it will best satisfy the needs of the prospective adopting organization, as well as the sustained use of the innovation (commonly referred to as full implementation). Rogers has identified elements of the innovation, the adopting unit, and the environment that affect the adoption decision. Many of these elements are more pronounced in the adoption of IOS due to the complexity of this high-technology product, which is why this research is framed using this technology. According to Rogers, organizational innovation decisions can be classified as collective (the decision process to adopt or reject an innovation involves consensual consideration among the members of a system) or authoritative (the decision process to adopt or reject an innovation decision involves relatively few individuals who have power, status or technical expertise in a system) innovation decisions (Rogers, 1995) with each organization determining which of these forms to use. Cooperative adoption specifically refers to a collective inter-organizational process whereby adoption is led by a focal firm or firms. The organizational adoption process has been wellresearched across different disciplines (e.g. Frambach and Schillewaert, 2002; Gatignon and Robertson, 1989; Speier and Venkatesh, 2002; Srinivasan et al., 2002). Among the organizational variables reflected in these studies are: knowledge of the environment, sensing of environmental threats, problem-solving skills, communication across organization units, risk-readiness, and resource availability. Other studies have shown that size and structure of the organization and interpersonal variables are salient in the organizational adoption process (Kennedy, 1983). Some of the variables are associated with the characteristics of an

Network level determinants of IOS adoption Structural factors One of the key variables commonly found to be positively related to the adoption of any innovation is the size of a firm (Kennedy, 1983). Several conditions commonly encountered in small organizations, such as resource constraints and limited technical know-how, might account for differences observed based on firm size. In a network context, instead of firm size, we model the number of firms involved irrespective of the size of individual firms. Resource constraints, therefore, should have less impact on firm adoption or its ability to implement the innovation. However, large networks are likely to face additional constraints that negatively impact these abilities. For instance, large networks likely contain bureaucratic elements and political structures that impede change. Moreover as the number of firms increases, the potential for overlap between networks is likely to increase. These overlaps conceivably increase the difficulties associated with change. For instance, imagine a single firm involved in two networks; one of which desires to implement a new IOS program and the other does not. The firm is faced with having to maintain two systems; one utilized in each network. From a transaction cost perspective this situation is suboptimal, leading to redundancy and potential errors. As an example of potential errors imagine the firm operates a VMI system with suppliers in one network and a manual inventory system with suppliers in another network. It is easy to see how critical material purchases might be overlooked under the assumption that the supplier was electronically monitoring current inventory levels when, in fact, the material in question was to be obtained from a noon-VMI supplier. Or assume the VMI supplier shipped material based on their observations of current inventory. Meanwhile the material might have been manually ordered from a non-VMI vendor by an employee who neglected to manually update inventory records. Now 202

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imagine a situation where the firm is involved in more than two networks and the difficulties compound exponentially. In large networks, where firms are likely involved in overlapping networks, firms facing adoption decisions would have to weigh the potential operational and relational benefits of adoption against the complexity of maintaining multiple systems: P1. Larger networks have a lower propensity to adopt an IOS innovation than smaller networks.

supports this relationship between adoption and technological readiness in EDI and IOS adoption (Dewar and Dutton, 1986). Within a network, we can see where the same principles might function. Instead of organizational level technological readiness, however, the current means used to achieve interorganizational collaboration might be a more appropriate assessment of the technological readiness of the network. Thus, using manual systems for collaboration represents a larger gap in implementing IOS than if the firms already have some level of automatic collaboration in place. Readiness is enhanced if some members within a business network have previously adopted the innovation, a prospective adopter is more likely to adopt a similar innovation based on access to valuable information from this partner. (Frambach and Schillewaert 2002). In fact, as adoption of the innovation reaches critical mass within the network, there is increased pressure on previous non-adopters to adopt. For instance, non-adopters may lose their competitive advantage to competitive firms who have adopted the innovation (Abrahamson and Rosenkopf, 1993; Robertson and Gatignon, 1986). Further, the non-adopter may be ostracized from adopting network members, who find working with this firm is made more difficult by their inability to use IOS technology, and see their sales decline. Thus, we propose the following: P3. The rate of adoption of IOS innovation by a network will be: (a) positively related to the degree of organizational readiness in member firms; and (b) positively related to the extent of their partners experience with the specific IOS innovations.

Using a similar argument, the amount of product variety a firm supports might be expected to affect cooperative adoption, however the direction of this impact is unclear. A positive relationship has been found between product variety and adoption of an IOS system in the context of e-commerce (e.g. Boeker and Huo, 1998). Boeker and Huo (1998), using an economies of scale argument, found companies offering a variety of products can enhance their economic development by using the internet to promote their products to prospective customers. Wang and Tsai (2002) similarly point out that a firm offering a wide variety of products may be able to reduce the cost of exchanging transaction information through the adoption of an IOS, such as e-technology. On this basis, an organization offering a variety of products will have a higher propensity to adopt an IOS innovation, such as e-commerce technology. Unfortunately, the economies of scale provided by large product variety might be outweighed by increased transaction cost incurred when that variety concomitantly increases the number of network interrelationships. Since product variety and organizational size might be correlated variables, the same arguments made above with respect to size might also be valid with respect to product variety. Thus, it is difficult to propose the direction of the relationship between variety and adoption. In fact, an inverted U-shaped curve might be the most accurate reflection of the effect of variety on adoption. At relatively low and high levels of variety, adoption is negatively impacted, first due to an inability to capitalize on economies of scale, then to the size and overlap of networks required to provide for the variety. In the middle, variety does promote adoption due to favorable economies, without requiring networks that are too large or overlapping to function efficiently: P2. Networked organizations offering a smaller amount of product variety or a very large amount of product variety will have a lower propensity to adopt an IOS innovation than organizations offering intermediate levels of product variety.

Perceptions of the value of the innovation by members of an organization’s decision-making group influence the final decision to adopt a new innovation (Rogers, 1995; Tornatzky and Klein, 1982). Value is a reflection of both the costs and benefits of innovative technologies. Perceived benefit can be defined as the prospective adopters’ belief in the probability that the new innovation will be beneficial to the organization. Not surprisingly, the more benefit a firm anticipates from an innovation, the more likely they are to adopt it (Mansfield, 1993). Among the benefits inherent in IOS adoption are strategic, operational, and opportunity ones (Sloane, 1994). Strategic benefits arise through improved customer satisfaction, cost efficiency, increased productivity, reduced manpower, and inventory control reduction (Sriram et al., 2000). Operational benefits are improvement of process activities, such as order entry, data accuracy, tracing shipment, better communication, paperwork reduction and quick response/access to information (Sriram et al., 2000). Opportunity benefits result from the organization’s visibility among trading partners. In other words, as more companies adopt an EDI trading system, the companies using EDI increase their chances of securing new businesses from a wider choice of trading partners (Husein and Moreton, 1996). These benefits appear to function in both a dyadic context, between partners, and a network context, across partners. In fact, network membership might further increase the benefits achieved through cooperative adoption. For instance, acquiescence to the focal firm’s request to adopt an IOS sends a clear message about the willingness of the recipient firms to cooperate and demonstrates their internalization of

As with other types of organizational adoption involving complex technologies, technology readiness might affect IOS adoption. Technological readiness is a function of existing technological capabilities or the extent to which the firm currently uses innovative knowledge and skills (Dosi, 1991). This is based, in part, on the gap between existing technologies and proposed technologies. If this gap is large, implementing the technology involves a great deal of learning and increases the difficulty encountered in moving from one technology to a new one. For instance, the gap between two software versions is relatively small, while the gap between manual and automatic information processing is more substantial. In the first case, implementation might occur seamlessly while the second case will require retraining, possibly replacing existing workers. Empirical evidence 203

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relational norms, in addition to making the relationship more efficient (Hildebrand and Biemans, 2003). The net effect of cooperative adoption by the recipients is a strengthening of the relationship, encouraging deeper relationships, and a build-up of social capital that greases future demands of the recipients on the focal firm. Of course, these benefits are counterbalanced by the costs involved in adoption of IOS (Wang and Tsai, 2002). For example, the deployment of an IOS innovation such as EDI or e-commerce involves considerable investment in hardware, software and skilled personnel (Howells and Wood, 1995). Aside from the initial set-up, other costs related to network maintenance of the IOS innovation should be considered (Howells and Wood, 1995). If the investment in the new innovation is perceived to be overwhelming cost-wise, the deployment of the new innovation will most likely happen at a slower pace or be squelched all together (Davies, 1979). The results of studies in the pharmaceutical industry support this contention (Howells and Wood, 1995). Based on these foregoing points, if the organization perceives the cost of deploying the IOS innovation as high, the propensity for adopting the IOS innovation will be low. In addition to the normal costs associated with organizational adoption, networked firms potentially deal with a host of costs related to their network membership. One such cost comes from their membership in multiple networks. If not all the networks decide to adopt and IOS or they choose different IOS applications, the firm has the additional problem of reconciling these differences through utilization of different processes with firms from different networks. As mentioned earlier, this is unwieldy and potentially fraught with errors. Another potential cost in cooperative adoption throughout the network is related to political issues across firms. For instance, a schism might develop, dividing firms in the network into two or more groups with different proposals for IOS adoption or opinions that adoption is not in the best interests of their firm. This situation can quickly become a political minefield where the firm cannot operate without aligning with one of the constituencies. Aligning with the losing contingency might have long-term costs for the firm. Similarly, the firm faces the possibility that the political process might weaken or destroy the network, reducing efficiency and profitability for all its members. One of the key problems confronting the decision maker is the difficulty involved in assessing the true value of IOS innovation. Ahituv (1980) highlighted three major questions that the decision maker must consider when evaluating the value of any information related technological innovation. First, is the decision maker assesses the value from the perspective of the entire organization and the network. The second question is related to the type of value being considered by the decision maker. For example is the type of value to be assessed related to the perceived value by the user, by the network, or is it related to the calculated normative value of the innovation. The third question addresses the issue of when the value is assessed (in the near term or long term) and who will be responsible for performing the evaluation, the firm or other network partners. In network adoption, it is entirely likely that some firms will benefit more than others and some might see little benefit or might experience costs that exceed their benefit (Ahituv,

1980). The question of who determines the value thus becomes a critical one. In addition to answering these complex questions, the evaluator of the innovation is also faced with some technical problems in terms of selecting the relevant attributes for evaluating information technology related innovation. Some of the problems include the measurement of each attribute and the relationship of each attribute to the innovation (Ahituv, 1980). Mukhopadhyay et al. (1995) study on evaluating the business value of EDI technology between Chrysler and its suppliers discussed measurement related problems, such as the measurement of IT outputs and aggregation issues. Aggregation problems denote the complexity that may arise from attempting to assess the effectiveness of all the IT applications within the firm together as one whole system, without consideration for the value added by each application as a stand alone unit. Irani and Love’s (2001), study on the evaluation of an MRPII system by leading UK manufacturing organization provides some useful insight about the different complexities involved in evaluating the value of an IS innovation. Their study finds that the use of traditional appraisal processes does not suffice in capturing the actual value of an IS innovation. As a consequence the adopting firm or the potential adopting firm may draw wrong conclusion about the actual value of the innovation. The use of more complex approaches that integrates human and other organizational factors were found to be significant in evaluating the value of IS investment: P4. The rate of adoption of an IOS innovation by networked organizations will be positively related to the value the recipient firms anticipate from the innovation.

Influence Underlying the process of cooperative adoption is communication across network members, which spreads information about the proposed innovation (Robertson and Gatignon, 1986), builds social capital (Anderson and Narus, 1990; Mohr and Nevin, 1990); and builds consensus among network members leading to adoption (Blau, 1964). In its role as an information source, communication between members must be bi-directional, open, frequent, and interpersonal (Mohr and Nevin, 1990). Communication, especially its openness and bi-directionality, is also necessary to ensure participative decision-making (which is discussed later in this section). Frequent communication is necessary to build social capital and to overcome the strains inherent in organizational change (Aiken and Hage, 1968). Thus, communication both directly impacts adoption intentions and moderates the relationship between participative decision-making and trust and these intentions. The direct relationship has been supported in the context of dyadic relationships, although the moderated relationship has not (Hausman and Stock, 2003). Influence is a specific type of communication likely to occur between focal firms and recipients in their efforts to encourage adoption. These attempts to influence innovation adoption are likely to create some level of resistance, especially as the influence becomes more coercive (Hausman and Stock, 2003). One method of weakening this resistance is to involve members of recipient firms in the 204

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Journal of Business & Industrial Marketing

Angela Hausman, Wesley J. Johnston and Adesegun Oyedele

Volume 20 · Number 4/5 · 2005 · 200 –210

decision process, thereby encouraging two-way communication between the firms (Mohr and Nevin, 1990; Rogers, 1995). This was supported by Hausman and Stock (2003) in the specific contest of cooperative adoption where there was a positive relationship between participative management and cooperative adoption. These studies amplify the importance of participative management and communication in the adoption and implementation of IOS. Thus, we propose: P5. The rate of adoption of an IOS innovation by networked organizations will be: (a) positively related to communication between the focal firms and recipient firms; and (b) positively related to their participation in the adoption decision.

antecedents of inter-firm alliances offers a good basis for understanding the importance of social ties in collaborative adoption. Prior research in this area can be attributed to network theorists (e.g. Mizruchi and Galaskeiwicz, 1993). They argue that if the focal firm and the recipient organizations have well-established social ties, the propensity for the firms to collaborate on future projects will be enhanced. For example, a focal firm with well-established social ties with a recipient firm has a higher likelihood to be successful at persuading the recipient firm to adopt an IOS than a focal firm with weak social ties. Social ties also build social capital through the give-and-take involved in maintaining such relationships. This social capital, held by champions and other network spanners, can be expended to encourage cooperative adoption. Thus, we propose: P6. The rate of adoption of IOS innovation by networked organizations will be: (a) positively related to the presence of an innovation champion within the organization; and (b) positively related to the extent of social ties between the focal firms and the recipient organizations.

Champions perform a vital role in the diffusion of innovations across organizations by using interpersonal influence to speed the adoption by others (Howell and Higgins, 1990; Lawless and Price, 1992). A champion is an individual who exceeds their formal role to promote adoption through their ability to focus efforts on the innovative idea, exert influence to overcome resistance, and provide leadership (Howell and Higgins, 1990). Champions exert influence both in their legitimate roles and through expenditure of social capital raised in prior contact between relational partners (Pfeffer and Salanick, 1978). They also bridge cultural differences between organizations to improve communication between firms and encourage cooperation within their own firm (Dougherty, 1992). In a network, there may be several different champions, some working within the organization to mobilize adoption efforts and some between organizations who act as conduits for information and influence. The literature refers to these inter-organizational individuals as boundary spanners or relationship promoters (Hildebrand and Biemans, 2003; Woodside, 1996). In addition to their role as champion of the innovation, these individuals also may perform task coordination activities to help facilitate adoption and may act as filters to guard against the spread of information unfavorable toward adoption (Ancona and Caldwell, 1990). The influence of an innovation champion in terms of enhancing the adoption of technological innovations within an organization has gained considerably attention among adoption researchers (Howell and Higgins, 1990; Van de Ven, 1986). The former investigated the role of the champions by focusing on understanding their personality characteristics, leadership behaviors, and influence tactics. This study suggests that champions are more disposed to taking risk and also have a higher level of innovativeness than non-champions. In line with these findings are the results of an empirical study of German construction and engineering sector linking successful with the presence of a champion (Hauschildt and Kirchmann, 2001). The same conclusion was also drawn from Nam and Tatum’s (1997) empirical. The role of champions in speeding adoption underscores the assertion by Maute and Locander (1994) that the adoption of innovations is fundamentally a social process. Unfortunately, adoption research has not fully developed these aspects of the process. Zaltman et al. (1973) point out that the involvement of members in an informal social network can enhance the level of information flow for a new innovation thereby influencing the rate of adoption of that innovation. Furthermore, knowledge about the structural

Relational The use of power in inter-organizational relationships acts to frame decision-making (Weick, 1979). As such, it is the primary means by which focal firms gain the cooperation of recipients (Stern and El-Ansary, 1992). Power is achieved relative to the focal firm’s ability to control resources needed by the recipient firms (French and Raven, 1959; Stern and ElAnsary, 1992). In a network, power may be distributed throughout the network, such that each firm has countervailing powers it might use to influence or thwart adoption. Communication acts as a conduit for using power, or more specifically influence, across the network. This influence may take many forms, including both coercive (threats, promises, and legalistic pleas) and non-coercive (requests, recommendations, and information exchange) (Frazier and Summers, 1986). An alternative schema classifies influence strategies into three types: coercive, soft-coercive, and noncoercive modalities (Brown et al., 1995). Coercive influence may speed the adoption process, but can also create problems by disrupting existing power structures and threatening the long-term success of the relationship (Frazier et al., 1988; Heide, 1994). Conventional wisdom suggests that the use of coercive influence will lead to more conflict while attempts to compromise and engage will result to reduced conflict (Thamhain and Wilemon, 1974). Several organizational research studies have shown the impact of influence on behavioral responses and tactical choices in a conflict situation (e.g. Bacharach and Lawler, 1980; Johnson and Ford, 1996). Attempts by the focal firm to use power might meet countervailing powers held by recipient firms, creating conflict that damages the relationship without producing adoption (Heide, 1994; Pfeffer and Salancik, 1978). The use of power might also lead to symbolic adoption, where a firm appears to adopt the innovation while generating internal roadblocks that interfere with its implementation (CITE). Multiple organizations are involved in networks and each network has some level of power to influence the actions of other member organizations. Thus, rather than a dyadic use 205

Cooperative adoption of complex systems

Journal of Business & Industrial Marketing

Angela Hausman, Wesley J. Johnston and Adesegun Oyedele

Volume 20 · Number 4/5 · 2005 · 200 –210

of power, the scenario probably looks more like a political process, where no organization has clear cut power. This process would involve forming alliances among network members using promises and trade-offs. Power is then wielded by the focal alliance, rather than a single firm, to achieve coordinated action. Thus: P7. The rate of adoption of IOS innovation by a recipient firm will be negatively related to the use of power by the focal alliance.

leads to more frequent and open exchange of information, which improves the chances of cooperative adoption (Zand, 1972). Trust is built over time across successful interactions between network firms, both those directly observed by the recipient firm and those communicated to the recipient firm by other firms. Logic suggests recipient firms will be unwilling to engage in any activity advocated by a focal firm they do not trust, since the strategy might be in the best interest of the focal firm, but not in the best interests of the recipient firms (Dwyer et al., 1987; Morgan and Hunt, 1994). Trusted network members encourage commitment to the relationship, as well as specific courses of action (Morgan and Hunt, 1994). Empirical evidence supports this logic in simulations and in surveys of a variety of inter-organizational contexts. For instance, trust was a critical mediating variable in interfirm relationship performance (Morgan and Hunt, 1994). Similarly, Ratnasingam’s (2003) simulation study demonstrates the importance of inter-organizational trust in the adoption of e-commerce due to the need to collaborate and communicate information in a timely manner between trading partners. In addition, researchers in different disciplines, particularly in the area of social psychology and channel relationships, have clearly demonstrated the importance of trust in inter-firm relations (e.g. Young and Wilkinson, 1989). Several technology-related adoption research studies similarly support the impact of trust on the adoption of IOS innovation in dyadic relationships (Hausman and Stock, 2003; Ratnasingam, 2003). This impact is magnified when dealing with an inter-organizational network because sharing access to computer records, inventory, pricing, etc. makes the firm particularly vulnerable to the opportunistic behaviors of all the networked firms. To operate efficiently, IOS systems provide access to necessary network firms and any one of them might breach security or share sensitive information that damages firm operations. Hence, even if the recipient firm trusts the focal firm, it might not trust other network firms that are linked by the IOS: P9. The rate of adoption of IOS innovation by an organization will be positively related to the degree of entrenched trust between the recipient firm and other networked firms.

The effects of power to speed adoption might be a function of the inherent dependence between a particular recipient firm and a focal firm or might reflect the average dependence of all recipient firms on the focal firm. In order to understand the effect of inter-organizational dependence on the rate of adoption of IOS, a brief overview of the definition and classification of the dependence variable as it relates to organizational relationships is provided. First, for the purpose of this study the word “dependence” and “dependency” will be used interchangeably. In a study (Kumar and Van Dissel, 1996), there were cited three notable ways in which the work of organizational units may be dependent on one another. This includes pooled dependency (e.g. use of a common data processing center), sequential dependency (e.g. supplierbuyer relationship along a value system), and reciprocal dependency (e.g. a concurrent re-engineering team consisting of customers, suppliers, and distributors working together to develop a product/service). Cooperative adoption represents this last type of dependency, which may force network firms closer together and restrict the entrance of new firms into the network by increasing entrance barriers (Brennen and Turnbull, 1999). Prior research provides conflicting support for the role of dependence on cooperative adoption of technological innovation. Some researchers find a negative relationship between dependence and adoption of innovations (Dwyer and Gassenheimer, 1992); while others detect no effect (Hausman and Stock, 2003). Additional research findings in support of the negative relationship between dependence and adoption of IOS come from an empirical study of Spanish automotive manufacturers (Sanchez and Perez, 2003). Conflicting data come from the Lusch and Brown (1996) study, which indicate a positive relationship between dependency and adoption of technological innovation: P8. The rate of adoption of IOS innovation by a recipient firm will be negatively related to the dependence between the focal firm and the recipient firm.

Conclusion

Trust is widely believed to be critical in alleviating negative conflict, enabling the formation of informal work groups, enabling collaborative relationships and network cooperation (Miles and Snow, 1992). Rousseau et al. (1998) also argued that the concept of trust is sometimes confused with cooperation, this confusion, has created some level of ambiguity about the meaning of trust-related behaviors and the construct of trust. One aspect of trust is a firm’s belief that another firm will not engage in activities that will generate potential damage to the firm or the network (Anderson and Narus, 1990). An equally important aspect of trust is the belief in the competence of other firms in the network (Morgan and Hunt, 1994). One important point that can be deduced about these different views of trust is that trust reduces uncertainty and feelings of vulnerability, which is positively related to change (Little et al., 1995). Trust also

In developing this framework, we integrated work on interorganizational adoption (cf. Tornatzky and Fleischer, 1990; Hausman and Stock, 2003, Wang and Tsai, 2002; Srinivasan et al., 2002), with insights from other types of adoption and innovation literature (cf. Gatignon and Robertson, 1989; Maute and Locander, 1994; Rogers, 1995) and empirical evidence from the inter-organizational relationships literature (cf. Heide and John, 1990; Venkatesh et al., 1995; Wilson, 1995). The proposed framework represents the first attempt to generate a holistic categorization of salient variables that might modulate the cooperative adoption of IOS innovations or other complex innovative technologies and ideas. As noted earlier, most adoption researchers have mainly focused on evaluating a few variables that impact the adoption of specific technologies by a single firm or consumer, mostly disregarding a holistic consideration of factors that might 206

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Journal of Business & Industrial Marketing

Angela Hausman, Wesley J. Johnston and Adesegun Oyedele

Volume 20 · Number 4/5 · 2005 · 200 –210

shape cooperative adoption, especially in a network context. Arguably, the synthesis of several factors from previous research offers a more inclusive framework to better understand the cooperative adoption process. Cooperative adoption is also a special case of interorganizational cooperation. Thus, the model may facilitate understanding of other types of inter-organizational cooperation necessary to reach strategic goals or to adapt to any number of internal or external changes. This commonality between cooperative adoption and other types of inter-organizational cooperation increases the contribution of this study to the organizational literature.

quantitative. The use of grounded theory to further develop the model while simultaneously testing the model appears appropriate (Glaser and Strauss, 1967). By using multiple informants representing firms both within the network and across networks this methodology achieves both improved specificity and generalizability. The first step is designed to capture intricacy in the proposed relationships, specifically potential mediator/ moderator relationships between proposed variables and cooperative adoption. For example, the perceived benefit of the innovation may be influenced by the extent of the prospective adopter’s involvement in the network. For example, a supplier or recipient firm with strong social ties with a focal firm may perceive the benefit of an innovation recommended by the focal firm as very high, due the high level of trust that may have been cultivated over a long period of time. Moreover, as suggested earlier, trust and communication may be related in some way, yet is not modeled in order to ensure the parsimony of the model. There may be additional interrelationships among modeled variables that have not been elucidated in extant literature. Further, qualitative data collection is designed to capture context factors affecting these relationships. The final rationale for including qualitative data is to ensure modeling of all major factors impacting cooperative adoption. External variables acting on the network may affect cooperative adoption are one example that appears salient. Specifically, the response of customers and suppliers outside the focal network may impact the decision. There are also other variables mentioned in this discussion that have not been specifically modeled, such as social capital. Thus, despite efforts to develop a holistic model, the result is suboptimal. Quantitative data collection will further test proposed relationships, quantify the impact of proposed factors on cooperative adoption, and tease out additional contextual factors. Another pressing need is to develop an understanding of the specific factors affecting implementation and continued use of the innovation. It is possible these are some of the same factors involved in the adoption process, but there may be additional factors that become critical at this stage in the process or the relative importance of proposed factors might shift during the implementation stage. Given the criticality of implementation for sustained benefit from the innovation, an understanding of these factors is important. This study has, as promised, developed one level of the multilevel model for understanding cooperative adoption in networked organizations. Another level is at the interorganizational level, where some firms may be promoting adoption while other firms lobby for other innovative solutions or the status quo. The question of how these political and social dynamics affect the cooperative process is unclear. Certainly, some of the same factors function in the inter-organizational interface, but how these affect and are affected by network level forces requires further development. The next level in this multilevel model is the organizational level and several studies attempt to model influential variables at this stage (cf. Gatignon and Robertson, 1989; Frambach and Schillewaert, 2002). These models have not been empirically tested and there may be additional variables acting within the organization affecting implementation, which is not well incorporated into these models. The final level, the individual level appears to have received the most

Managerial implications As industry rapidly moves toward a networked economy, cooperation among individual firms involved in overlapping network relationships is critical for success (Achrol and Kotler, 1999). Managing these diverse relationships allows networked firms to respond to environmental opportunities with a minimum of stress (Wilkinson and Young, 1994). Unfortunately, the literature on this topic is under-developed. Firms used to the competitive paradigm need guidance on the incorporation of cooperative strategies into their internal operating procedures, as well as their external relationships. The model developed in this study is an important step in this direction by clearly delineating the principal factors that may influence the decision to adopt innovations across a broad range of variables. The study draws the manager’s attention to interorganizational influence factors as well as relational factors under their direct control. In addition, strategies for dealing with structural factors, over which they have little control, are presented. Importantly, the effect of these variables on adoption has been modified from the perspective of an individual firm or dyad, to the more complex situation encountered in networks. Further, the study focuses on “soft side” or social variables that appear to be critical in encouraging cooperation in the absence of bureaucratic governance mechanisms, since these are fundamentally absent from network relationships. These variables feature open communication prominently as a means of building trust and allowing participation. Open communication also builds social ties and generates social capital to facilitate cooperation and empower champions. In dealing with these factors, it appears that firms must first establish a supporting organizational culture, since it seems implausible that firms can act cooperatively in their interorganizational encounters and bureaucratically in their intraorganizational relationships. Specifically, firms must establish good internal lines of communication that rely on encouraging employees to work cooperatively toward mutually beneficial goals and build strong internal relationships among departments and their employees. The model also suggests some context specific factors affecting the network adoption process, specifically size of firms.

Future research Obviously, one of the most pressing issues is empirical testing of proposed relationships. Toward that end, we are planning a two-step approach, the first qualitative and the second 207

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Angela Hausman, Wesley J. Johnston and Adesegun Oyedele

Volume 20 · Number 4/5 · 2005 · 200 –210

conceptual development and empirical testing of the model components. Thus, testing at this level is not deemed necessary.

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Cooperative adoption of complex systems

Journal of Business & Industrial Marketing

Angela Hausman, Wesley J. Johnston and Adesegun Oyedele

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Inter-organisational collaboration for the digital economy Elizabeth Houldsworth and Gillian Alexander Henley Management College, Henley-on-Thames, UK Abstract Purpose – This paper was intended to explore the concept of learning in networks using recent literature from this emerging field. In order to do so, it takes as a case study a pan-European e-learning project, which required collaborative working and learning within a distributed team. Design/methodology/approach – The approach has been qualitative and exploratory. Data have been collected via interviews with project partners and participant observation of the steering group meetings. Analysis has similarly been qualitative in nature. Findings – Analysis suggests that there are links with earlier literature on inter-organisational learning networks, particularly around culture, management style and leadership in virtual collaboration. Interestingly, even supposed “experts” in the field of e-learning technologies showed a preference to work face-to-face. Research limitations/implications – The research to date has been exploratory and small-scale. More work is required to test the findings in a wider context. Practical implications – The findings are believed to have considerable practical value, both for the European Union, as the funding body, but also for one’s own practice, and that of others as they attempt to facilitate learning and collaborating in networks. Originality/value – The paper adds value as it is one of only a small number to approach networked learning from a non-experimental standpoint. It is also original in its application of the frameworks around network learning and learning in networks, as advanced by Knight in 2002 and Knight and Pye in 2002. Keywords Learning, Telecommunication networks, Learning organizations, Organizational culture Paper type Case study

The process is technology driven. Just as steam and electricity changed the way we organised society, . . . we are now caught up in the digital revolution.

An executive summary for managers and executive readers can be found at the end of this issue.

More broadly, Steeples and Jones (2002) see a network society to have emerged, which has impacted on the debate about skills as well as highlighting the needs of a knowledge-based economy. This is perhaps not surprising given the virtual and distributed environments in which many people and project managers are working. For example, Tsoukas (1993) describes people managers as having a variety of communication technologies to help them to co-ordinate dispersed activities. The implication is that this is very different to more “traditional” environments where face-to-face interactions on a daily basis are managed under the same roof.

Introduction This paper reports on learning from a pan-European project, established to support small- to medium-sized enterprise (SME) managers to do business in the digital world. We take as our focus the collaboration that occurred amongst the partners as they attempted to work in a virtual network in pursuit of the main project objectives. The new millennium has seen the continuation of earlier massive changes in culture, society and education, based around new technologies. According to Steeples and Jones (2002) the explosive growth of the Web has been a major driver of educational changes at all levels. The Internet has emerged from its military beginnings and a period of academic development into a general, social and commercial resource in the 1990s. Speaking of changes within universities, Spender, 2000 has said:

Virtual collaboration Sole and Edmondson (2002) have described some of the likely challenges facing project managers and managers of distributed teams. Their in-depth qualitative study saw virtual teams grapple with differences in time zones as well as non face-toface communication media. They quote an engineer as saying: On each of these dispersed projects, our big challenge is that we just don’t get together as a team because we’re spread so far apart. So it forces us to collaborate . . . but to do that in non-traditional ways where we can’t just have a meeting or work with each other across the hall.

The Emerald Research Register for this journal is available at www.emeraldinsight.com/researchregister The current issue and full text archive of this journal is available at www.emeraldinsight.com/0885-8624.htm

Their findings suggest that spending time together helps to create a foundation for team effectiveness beyond the current

Journal of Business & Industrial Marketing 20/4/5 (2005) 211–217 q Emerald Group Publishing Limited [ISSN 0885-8624] [DOI 10.1108/08858620510603882]

This paper was accepted by referees for presentation at the Networked Learning Conference Lancaster April 2004 and an earlier version is contained within the Conference Proceedings.

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task in hand. In addition re-location and co-location across the dispersed teams was found to be an effective strategy for team learning. Therefore moving people physically, if not for the duration of the project at least for a period, was encouraged to allow for participation in certain key events. Similarly, Granovetter (1985), has underlined the social nature of business interactions through the concept of embeddedness. This perspective suggests that all economic action, including that of organizations is enabled, constrained and shaped by social ties among individuals. Uzzi (1997) is just one author who has built on these concepts in a study of 23 entrepreneurial firms to suggest, amongst other things, the personal nature of inter-firm ties and how these can impact organisational and economic outcomes. In a 2003 study Tregaski focused on three foreign-owned subsidiaries in the UK, which she names as TelCo, WaterCo and InksCo. She also discovered that face-to-face contact is important in facilitating development activity. Tregaski’s findings suggest that location is important for collaboration. She reports management teams as believing that it is far better to use locally available expertise, familiar with the industry and its problems, than to buy in from further afield. These examples, from the increasing body of literature on learning networks, suggest that the future looks set to involve harnessing technology to a greater degree. It would appear that technologies will be used both to deliver content and to support and manage learning, but also to support virtual networks, both within and across organizations. The context for this paper is our interest in considering learning within a situated and social context, as described by Lave and Wenger (1991) and Chaiklin and Lave (1993) amongst others. We recognize that this learning may be technologically supported, for example using e-learning and computer mediated conferencing (CMC), or not.

be seen that the six partners play a role in two networks of importance to the project – the network of partners (facilitated by the business school) and the network of local SMEs (which each partner is responsible for facilitating). Although the proposition for the project was e-learning for SME managers, our unit of analysis here is the network of steering group partners. The project developed a web infrastructure to support online collaboration between the partners but, despite the fact that the project was about elearning technologies, found it was little used. The ESeN partners were, however, required to work together to deliver the projects outcomes. This collaboration was therefore supported by project steering group meetings with e-mail communication in between and some occasional video conferencing. In addition some steering group members had their own pre-existing relationships and used face-to-face conversations either outside the formal steering group meetings or on other occasions when they met for different projects or meetings. Table I summarises the communication channels available to steering group members and indicates their relative degrees of “project legitimacy” and “project usage”. Network learning We were particularly interested in using this European Union e-Learning Action Plan (EU) funded project as a case study for examining the ideas described in Knight’s (2002) human relations paper. She recognises that a popular subject is networks and that they lead us to consider learning as a social and situational process. She distinguishes between network learning, inter-organisational learning and learning networks. Network learning she defines as the sum of the learning of individuals, groups and organisations that constitute the network. The learning entity therefore is the complete network and learning outcomes are evidenced through changes such as network level or network wide routines, strategies, culture, processes and systems. Inter-organisational learning, on the other hand at its simplest might involve a learning entity that is an individual, a group of individuals, an organisation or an inter-organisational network. Knight sees it to be distinguished by the fact that the learning takes place in an inter-organisational context. She defines learning networks as any deliberate learning through interaction with others whether as an individual, group or organisational. Knight (2002) has said of learning in networks “Network actors collaborate, that is they purposefully cooperate over time.” This is we feel an appropriate definition for the participants of ESeN. Knight (2002) presents a table (see Table II) to capture her arguments about the different manifestations of learning in networks and network learning and uses this as a framework for understanding prior research. She does so by mapping the different levels of learner against the learning context and uses

This study The subject for consideration is a European Union eLearning Action Plan (DG/EAC/21/01) funded project that revolves around the creation of a European SME e-learning network (ESeN)[1]. The project has sought to engage with SMEs in order to equip them with emerging knowledge management tools, so that they may become more effective users of information communications technology (ICT) in their decision-making. The project involves a business school as the main partner with collaborators from six EU countries, comprising a mix of academic and business partners, all of whom were experienced in the use and application of virtual technologies. It is possible to see that the partners serve a dual role, in the first instance they sit on the project steering group and at the same time they are involved in building relationships with SMEs within their local area. In terms of networks it can thus

Table I Communication channels deployed by steering group members and degree of “project legitimacy” and “project usage” Communication channel

Project legitimacy

Project usage

Official project web infrastructure Steering group meetings Video-conferencing Personal 1:1 e-mail 1:1 informal meetings between partners or between coordinator and partners

High High Medium high Low Low

Minimal High Low take-up and effect High given failure of groupware High

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Table II Cross-tabulation of level of learner and context of learning

a naming method of row/column (learner then context) to identify different cases. For the cells above the top left to bottom right diagonal (as indicated by the arrow), context is described as being a setting within which the group is learning. Below the diagonal, e.g. cell G/I the context is taken to mean catalyst for learning. Knight positions network learning as learning by a group of organisations in any context – the unit of learning is the network and she maps this onto the bottom row of Table II. For Knight (2002) there is a particular interest in interorganisational learning. She defines this as learning in a dyadic or inter-organisational setting in which the learner could be an individual, a group, an organisation, a dyad or a network. This view differs from earlier researchers such as Larsson et al. (1998) amongst others, but our experience here of facilitating an inter-organisational network causes us to agree with her definition. Where learning networks would be mapped depends, according to Knight (2002) on the specific example. A group of professionals (e.g. solicitors) informally exchanging information would be mapped as individuals learning within a group (cell I/G). A group of firms routinely sharing knowledge that is applied within the member firms would be mapped as organisations learning within a network (O/I-O). For further examples see Knight (2002).

SME leaders participating in ESeN will become incorporated into how their organisation does things. This would be mapped as the organization learning within an organisational context (O/I-O), using Knight’s approach. Figure 1 shows the relationship diagrammatically: Alternatively, there is a second level of learning going on within the project, which occurs for the steering group partners. We might expect this to be reflected in the first row of Table II, where the level of learner is represented as being the individual interacting and learning within an interorganisational context (I/IO), represented in Figure 2.

Methodology To date, according to Hodgson et al. (2002) most research in the emerging field of networked management learning has been US-based and the dominant research approach has been quasi-experimental. Hodgson et al. (2002) provide an account of some of the more recent constructionist and ethnographic studies, which have been carried out to understand more about online collaboration and group working. We were keen to use something similar, but were faced with the challenge of there not being an active online discussion area for the ESeN project that we could scrutinize. Instead, the steering group meetings and collaborative activities conducted outside of these seemed the best opportunity for us to consider the partner collaborations. As project researchers, we had access to the three steering group meetings conducted to date. The decision was taken to use these to conduct participant observation. The approach adopted was that of complete participation, as described by Gold (1958), accepting that the researcher must be reflexive and acknowledging that their own bias will underpin how they make sense of what they observe (Gill and Johnson, 1991). We believed the inclusion of such a participative method was appropriate for striving to understand learning in the social world, as Symons and Cassell (1998) have described.

Conceptual framework We started out with a particular interest in applying the Knight’s (2002) and Knight and Pye’s (2002) frameworks to a case study situation. We were interested to consider the learning that emerged from participation in the ESeN network. In the case of ESeN it is possible to identify two units of analysis when we consider the level of learner and learning context. Using the previous example from Knight, of firms sharing information so that it is applied within the member firms, we can perhaps assume that the learning for 213

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Figure 1 Learning interactions for SME leaders within ESeN

Figure 2 The network of ESeN partners

“frame” which is agreed in advance by the research team. In this case, four core areas were identified, these were: . Why have you been involved in learning networks/ networks of collaboration? . How have you been involved in the past (steer the conversation here into successful/unsuccessful examples)? . What, in your experience serves to support the process of networks of collaboration/learning? . Reflections on your learning in networks.

In addition, we have been able to interview six of the 11 steering group members regarding their perceptions and experience of learning in networks of collaboration. Given the interviews were of an exploratory nature a small number was felt to be sufficient. We aimed to include at least 50 per cent of the partner group and sought to achieve a mix of nationalities and partner “type.” The six interviewees did represent over 50 per cent of the partner group. They were drawn from five steering group organizations across three of the six different countries involved in the project. Of the six, four were from academic partners and two from practitioner partners. An approach to interviewing was adopted which utilised “conversation as method” (for more information, see Josselson et al., 1997; Levy, 2002). This approach is rooted in the belief that learning is situated and contextual and that participants will have a range of different collaborative experiences upon which to draw. In brief the approach is relatively unstructured, reflecting a conversation around a

Given the fact that we did not wish the research to be construed as evaluative of the ongoing ESeN project we did not overtly seek input or views on this particular collaborative experience, although we were happy for it to emerge naturally during the conversation, should it do so. The interviews took place either face to face or over the telephone and lasted between 20-40 minutes. They were not taped, but notes were typed up from each interview. 214

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Analysis and outcomes

networks and used the field notes from the observation to look for how these have (or have not) been manifested in practice.

The conversational frame around four key areas provided a useful structure for dividing up the main themes that appeared from the six interviews. The field notes for each interview were read through and manually highlighted to support the emergence of possible themes. Each highlighted section was annotated with a short description of what the passage was about. Once the notes from the six interviews had been reviewed in this way it was possible to consolidate the main themes into a summary table, using the conversational frame as the main organising device (see Table III). This was supplemented by two other themes that emerged as common across all the interviews: . issues that get in the way of learning in networks; and . our interpretation as researchers of models of learning being described by the interviewee (using Knight’s ideas from Table II).

Discussion Although our findings are still under consideration at this stage, we have sought to link themes from the interviews and observation back to the literature around learning and collaboration in networks. We have found Tregaski (2003) and Knight and Pye (2002) particularly useful here. Although writing about subsidiaries Tregaski’s (2003) identification of four potential learning network modes is useful for supporting our positioning of the learning network under consideration here. Of the four modes she suggests, we believe the ESeN network reflects an international interorganisational network. Tregaski (2003) also writes about the role played by culture and power, both of which were manifested in our data. Given the pan-European nature of ESeN, it is perhaps not surprising that we saw evidence to reinforce the role of national culture. For example, a Scandinavian Steering group member reported that collaboration was for him an organisational and cultural norm, although this reference to national culture did not hold true for all the other participants. In addition there was evidence of different styles of organisational/functional

Once the interviews were completed and analysed the field notes from the participant observation were considered in order to understand more about the actual process of collaborative learning at play. For the purpose of this paper we have used the themes from the interviews as a starting point for the sense making process. Therefore we have taken what the learners have said about learning and collaborating in

Table III Summary outcomes from the interviews and the participant observation Interview area

Themes about collaboration from interviews Participant observation themes

Why collaborate?1. Task focus 2. Share mutual interests 3. Organisational or national culture 4. Access to more knowledge and resources 5. Feedback on ideas and concepts 6. Dialogue to help analyse and explain 7. Social interaction How? 1. Scientific methodology 2. Project methodology similar to “day” job, e.g. worldwide project implementation 3. Previous EU projects 4. Surveyors, e.g. of a network 5. MBA programme 6. Corporate academic network What works? 1. Strong facilitation and lots of energy 2. Common goals and agreement on ways of working (team charter) 3. Shared language 4. Geographical proximity 5. F:F meetings 6. Electronic support as appropriate 7. Social interaction 8. Time to develop own rhythm What hinders? 1. Differing agendas 2. Lack of buy-in and urgency 3. Distance 4. Poor relations caused by different personalities Reflections and As two interviewees pointed out, collaboration is level difficult. Interviewees describe learning at an of learning individual level, in the context of a group and/or network

1. To fulfil EU requirements and justify taking share of funding 2. To produce and supply something tailored to own locality and SME interests 3. To learn from the experience of collaboration and sharing

1. Followed espoused “best practice”: produced a charter, community of practice input and social event 2. Use of action learning methodology for both medium and message

1. Attempts to be participative and democratic (had limited success) 2. Strong steer by coordinator helped 3. Social interaction to support negotiations 4. F:F meetings.

1. Lack of strong facilitation from coordinator 2. Disunity/power struggle within coordinator contributed to lack of direction 3. Different languages/communities – academics vs practitioners 4. Different agendas No evidence from steering groups to suggest learning at anything other than an individual level

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culture. Two partners involved in scientific fields as well as those from a project environment described collaborative working as their normal mode of working. Frustrations evident in the steering group meetings may also in part be attributable to different organisational norms. There was evidence of different “tribes” or communities at work. The non-academic partners showed frustration around what they perceived to be ongoing “academic concerns”. They felt they had to provide the “real world” insight and reality check. At the third steering group and in correspondence afterwards, they were keen to ensure that the proposed programme for SME managers, maintained an action learning element and that this was flexible so that it could be tailored to local business needs in their host country. Again Tregaski (2003) alludes to something similar, acknowledging the barriers that can arise from a lack of recognition of the value and legitimacy of the skills and knowledge of those educated elsewhere. It would seem that personal relations, supported by social interaction helped overcome this in the case of ESeN. Tregaski suggests that personal relations, along with communication skills are particularly important in crosscultural settings. Sole and Edmondson (2002) have similarly suggested that time together, beyond the task in hand may contribute to the success of dispersed teams. In the case of ESeN, there were some stormy exchanges in the second steering group, which were to an extent relieved by the deliberate social events scheduled into the meetings. If we turn to Knight and Pye (2002) they suggest that collaboration can be supported in a network via through organisational or personal capacity or both. The characteristics that they suggest are included in Table IV. Given the nature of learning we believe to have been manifested (being individual in nature) it would appear that the personal capacities are most appropriate here. All four capacities perhaps contribute to some of the discrepancies between what was reported in the interviews and what we observed in practice. We shall deal with each in turn. All the interviewees mentioned the need for a common interest or shared task or goal to support a network. We might assume this would translate into a high reliance on the network to deliver. However, observation from the steering groups suggested different agendas at play. In the early stages of the project only the co-ordinator of the partners appeared aware of their dependency on the others to deliver to contract. In terms of displaying a positive attitude towards suppliers and an understanding of trust and mistrust, there was a lot of early energy devoted to building a positive attitude and team spirit. However, as the project progressed our steering group observations reveal certain frustrations for all parties. These were particularly apparent if individuals were late, left early or did not appear very “engaged” in the process. As a result

defensive feelings, if not mistrust were discernible in steering groups 2 and 3. Like the issue of a common goal, all interviewees seem to acknowledge that a network is not self-sustaining and strong facilitation is required. This links to Knight and Pye’s (2002) final “personal capacity” to support collaboration which they describe as a high level of personal and/or role influence. The coordinating partner appears to have been lacking this influence in the early stages and attempts to be highly participative and democratic had only limited success. Interestingly the use of a more directive approach appeared to lead to greater collaboration and the generation of outputs.

Summary and managerial implications for practice Our starting point at the beginning of this investigation was to apply and explore the framework produced by Knight (2002). Her framework captures both the context of learning and unit or level of learner. The interviews with the six steering group members suggest that in the ESeN partner network the unit of learning is individual. The context appears to be the interorganisational network, therefore using the Knight methodology and framework captured earlier in Table II, we would describe this as (I-I-O). We can therefore describe this project as an example of learning within a network, but not as networked learning, as there is no evidence of the network itself learning and changing. In conducting the study we have also used a number of different frameworks around learning in networks and supporting collaborative working, some of which appear to have more relevance for our ongoing practice. Having collected evidence from interviews we have been able to compare this to what actually happened in “collaborative practice” in the project steering group meetings. We have been able to see evidence of a number of themes from the literature around collaborating and learning in networks, notably around culture, the need for a common focus and agenda, and the need for strong facilitation and influence. In particular we have been influenced by the personal capacities for collaboration produced in 2002 by Knight and Pye and captured in Table IV. The fact that these capacities were not always present (or at least were not enacted) may perhaps be seen as the cause of some of the frustration and slow progress of the project. Interestingly as the coordinating partner, the lessons to be learnt about the need to take a strong and decisive stance and provide direction seem to sit uneasily with some of the ideals of participation and negotiation associated with collaborative working.

Table IV Personal and organisational characteristics supporting collaboration Personal capacity

Organisational capacity

High reliance on the relationship Positive (i.e. not defensive) attitude towards suppliers Understanding of “principles” of trust and mistrust

High organisational dependence Clear rules Alignment between performance measurement of players and of the contract and relationship Organisational proximity of players

High levels of influence (role and/or personal)

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Conclusions and limitations

Josselson, R., Lieblich, A., Sharabany, R. and Wiseman, H. (1997), Conversation as Method – Analysing the Relational World of People Who Were Raised Communally, Sage Publications, Thousand Oaks, CA. Knight, L. (2002), “Network learning: exploring learning by inter-organisational networks”, Human Relations, Vol. 55 No. 4. Knight, L. and Pye, A. (2002), “A learning and change in inter-organisational networks: the case for network learning and network change”, 3rd European Conference on Organisational Knowledge, Learning and Capabilities, ALBA, Athens. Larsson, R., Bengtsson, L., Henriksson, K. and Sparks, J. (1998), “The interorganisational learning dilemma: collective knowledge development in strategic alliances”, Organization Science, No. 3, pp. 285-305. Lave, J. and Wenger, E. (1991), Situated Learning: Legitimate Peripheral Participation, Cambridge University Press, Cambridge. Levy, P. (2002), “Researching networked learning and teaching: a case study in practitioner knowledge construction”, Networked Learning, pp. 100-8. Sole, D. and Edmondson, A. (2002), “Situated knowledge and learning in dispersed teams”, British Journal of Management, September. Spender, D. (2000), “The role of a university in a dot com society: what is it?”, available at: http://collaborate.shef.ac. uk/nl2000.html Steeples, C. and Jones, C. (Eds) (2002), Networked Learning: Perspectives and Issues, Springer-Verlag, London. Symons, G. and Cassell, C. (1998), Qualitative Methods and Analysis in Organisational Research: A Practical Guide, Sage, London. Tregaski, O. (2003), “Learning networks, power and legitimacy”, International Journal of Human Resource Management, Vol. 14 No. 3. Tsoukas, H. (1993), “Ways of seeing – topographic and network representations in organisation theory”, Systems Practice, Vol. 5, pp. 441-56. Uzzi, B. (1997), “Social structure and competition in interfirm networks: the paradox of embeddedness”, Administrative Science Quarterly, Vol. 42 No. 1, p. 35.

Based on our learning to date it would appear that despite the consultative and learner focused nature of many of the theories of situated learning, the adoption of such an approach does not necessarily lend itself to virtual project work relying on collaboration. As researchers and practitioner working within this field, we have been keen to learn from the lessons of ESeN as we carry out new projects. Particular project management styles which involve strong facilitation and personal influence seem to be called for, in the place of more participative approaches which had less impact in the case of ESeN. We acknowledge that the empirical work conducted on ESeN has been limited in nature. We are currently seeking to extend this on a subsequent project by deploying a similar interview-based methodology. The new data collection phase will see us interview all 12 Project Partners at 3 times during the project life cycle. We believe this will help to test out further the emerging findings on engaging networks for working in the digital economy.

Note 1 ESeN Project (2002-4094), funded by the European Commission Directorate General for Education and Culture (see www.esen.eu.com).

References Chaiklin, S. and Lave, J. (1993), Understanding Practice: Perspectives on Activity and Context, Cambridge University Press, Cambridge. Gill, J. and Johnson, P. (1991), Research Methods for Managers, Paul Chapman, London. Gold, R. (1958), “Roles in sociological field observations”, Social Forces, Vol. 36, pp. 217-23. Granovetter, M. (1985), “Economic action and social structure: the problem of embeddedness”, American Journal of Sociology, Vol. 91, pp. 481-510. Hodgson, V., Watland, P. and Asensio, M. (2002), “Researching networked learning”, in Rust, C. (Ed.), Improving Student Learning Using Learning Technologies, Oxford Centre for Staff and Learning Development (OCSLD), Oxford.

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An empirical framework developed for selecting B2B e-business models: the case of Australian agribusiness firms Eric Ng Faculty of Business, University of Southern Queensland, Toowoomba, Australia Abstract Purpose – To develop a preliminary framework for Australian agribusiness organisations seeking to select business-to-business (B2B) e-business models. Design/methodology/approach – A literature review was conducted on topics related to strategic decision making and B2B e-business models. Particularly, factors influencing the strategic decision on the choice of e-business models to be selected were examined. The review aims to provide an initial framework for the research study to be conducted. The research was conducted in two stages: depth interviews (stage one) and case studies (stage two). Findings – Provides information on factors (both internal and external) influencing the choice of e-business models and also insight into the current practices of Australian agribusiness in relation to the selection process of B2B e-business models. A framework was developed to assist agribusiness organisations to make decisions on the selection of the most appropriate e-business models. Research limitations/implications – This study is exploratory in nature and thus the findings cannot be generalised to the population at large. Further conclusive explanatory research is required for generalisation and the guidelines developed in this study could be replicated and tested in other agribusiness sectors or in other industries. Practical implications – Managers are able to consider and examine the relevance of the guidelines and criteria developed, and determine the essential factors that require consideration during their selection process. The guidelines can also assist managers to determine the level of resources, technological infrastructure and knowledge and understanding of e-business models required. Originality/value – This paper brings together two disciplines – strategic decision making and development of e-business models – that have not been combined prior to this study. The research findings have contributed to the development of existing theory in these two areas. The research also offers insights into the selection of e-business models within the agribusiness industry that traditionally lagged behind in e-business. The development of the framework and guidelines has assisted managers in their selection of e-business models and given them an appreciation of what others in the industry are doing. Keywords Business-to-business marketing, Electronic commerce, Australia, Agriculture Paper type Research paper

E-business has played a significant role in the business-tobusiness segment where it has grown significantly (NOIE, 2000) and is expected to reach US$8.5 trillion worldwide by the year 2005 (Gartner Group, 2001). This trend requires existing business models to be rethought to reflect the transformation required by organisations to take advantage of this environment (Barnes and Hunt, 2001). Furthermore, organisations are faced with a wide range of e-business models, with many factors influencing their ultimate choice. The increasing adoption of e-business by organisations both worldwide and in Australia and the resulting lack of empirical research to assist organisations in making these choices have resulted in the need to develop a framework to assist organisations in selecting appropriate B2B e-business models. This phenomenon is particularly evident in the Australian agribusiness industry (NOIE, 2001). Agribusiness organisations worldwide have capitalised on the many advantages of e-business to improve the marketing of their products (Allen Consulting Group, 2000). In Australia, the agribusiness industry is regarded as a major contributor to the economy and this is particularly evident in Queensland, where it accounts for one-third of exports and employs over 80,000 people (Queensland Government, Department of State Development, n.d.). Although this

An executive summary for managers and executive readers can be found at the end of this issue.

Introduction E-business continues to be of growing importance with many organisations increasingly conducting their business activities in the electronic environment (Goodridge, 2000; Kalakota and Robinson, 1999; Cunningham and Froschl, 1999). The use of technology has played a major role in many strategic initiatives (such as reengineering and cost-cutting) where attempts have been made to capitalise the benefits of e-business to strengthen customer and supplier relationships, and establish new markets (Hackbarth and Kettinger, 2000). The Emerald Research Register for this journal is available at www.emeraldinsight.com/researchregister The current issue and full text archive of this journal is available at www.emeraldinsight.com/0885-8624.htm

Journal of Business & Industrial Marketing 20/4/5 (2005) 218–225 q Emerald Group Publishing Limited [ISSN 0885-8624] [DOI 10.1108/08858620510603891]

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industry consists of a large number of small enterprises, many are supportive of the adoption of e-commerce techniques (The Australian Electronic Business Network, 1998). In addition, the high reliance on accurate and timely information (such as weather and stock information) and large physical distances between producers and customers in this industry, have made this sector conducive to the benefits of e-business (Allen Consulting Group, 2000). This exploratory research will address the question “What factors influence the choice of B2B e-business models used by Australian agribusiness organisations?” and develop a preliminary framework for Australian agribusiness organisations seeking to select B2B e-business models.

which nine are internal and seven are external in nature (see Figure 1). Based on the literature, a preliminary model (see Figure 1) was developed suggesting that although the choice of B2B e-business models is a unique strategic decision, traditional factors (both internal and external) that would normally impact such a decision will apply in this context. Furthermore, the relative importance of each of the factors in the strategic decision process will also be examined as it is assumed that some of these factors may be more important than others, and in addition differences may also occur based on size and sector.

Methodology This study was exploratory in nature and was conducted in two stages; depth interviews (stage one) and case studies (stage two). During the depth interviews stage, interview protocol was developed and was structured into three sections that consisted of 20 questions, aimed at addressing the relevant issues and objectives. Interviewees for the depth interviews were selected based on their extensive experiences in the agribusiness industry (either in the private or in the public sector) as well as their extended knowledge and expertise (practical or theoretical) in the fields of e-business, e-commerce and strategic management. Eight depth interviews with e-business experts and industrial professionals were undertaken to examine the appropriateness of those B2B e-business models and factors identified in the preliminary model whilst organisational size and industry sector were also explored as possible influencing factors to the choice of models. In addition, general issues associated with homogeneity within the agribusiness sector as well as potential frameworks were also investigated. The second stage of this research used case studies to assist in confirming or disconfirming the preliminary model as several sources (Perry, 1998; Yin, 1994) confirm the appropriateness of a case study methodology when building theory as in this research. From the findings of the depth interviews, ten cases across two sectors, grain (five) and cotton (five) with large (five) and small medium (five) enterprise organisations that were either intending to conduct, or who were currently conducting B2B e-commerce were selected judgementally. Two interviews were conducted in each case with the managing director or equivalent and a middle level manager or operational personnel, to determine if there are any significant differences in their respective opinions (management and operations perspectives) on the selection of models. Furthermore, where possible, secondary sources such as the company’s business plans, marketing plans and other relevant documentation were used to further triangulate the results.

Literature review The choice of B2B e-business model is one of many strategic decisions that organisations make when conducting business activities in the e-business environment. Current literature on both strategic decision making and the development of B2B ebusiness models does not adequately address the many complexities facing today’s agribusiness organisations considering e-business initiatives. The existing literature is disparate in that it addresses how organisations should make strategic decisions in general (Song et al., 2002; Gulati et al., 2000), and the detail and development of e-business models (Wise and Morrison, 2000; Timmers, 1999; Rappa, 2001) but the two disciplines have nowhere been combined. Furthermore, practical and operational issues (such as resources availability, technology infrastructure and knowledge required) that impact such decisions, specifically for agribusiness organisations, have also not been addressed. In developing the framework, organisations need to have a good understanding on the types of models available for adoption. While there is no single unique classification system for the types of B2B e-business models available (Rappa, 2001; Timmers, 1999), B2B e-business models are generally classified into four generic categories: merchant models; manufacturer models; the buy-side model; and brokerage models (Timmers, 1999; Rappa, 2001; Strauss and Frost, 2001). Each of these models has different functional characteristics resulting in different models being more applicable or suitable to particular industries, markets or situations. In addition, the focus of these models varies from buyer centric (such as the buy-side model) to supplier centric (such as the manufacturer model) with some being neutral (such as the mega-exchange model). Based on these four categories, a recent study has identified 10 specific e-business models (see Table I for their comparative features) as being used for conducting B2B e-commerce in the agribusiness industry (Ng, 2002). In addition to the complexity of the models, many factors are known to influence the strategic decision making process of organisations (Eisenhardt and Martin, 2000), which are also likely to impact on the choice of B2B e-business models. The choice of e-business model is a strategic decision as the model chosen will form the framework for the organisation to pursue its business activities in the e-business environment and will also affect an organisations’ overall strategic direction (Nwachukwu, 2002; Malhotra, 2000). Factors influencing the choice of e-business models can be classified into two categories; internal and external (Papadakis et al., 1998). The literature suggests 16 influencing factors, of

Depth interview results Findings from depth interviews confirmed the ten models identified in the literature were used for conducting B2B e-commerce, five of these models (the procurement portal, manufacturer, mega-exchange, online storefront and distribution portal models) appeared to be commonly used. Whilst, the e-speculator, solution provider, buy-side, sell-side asset exchange and specialist originator models were less frequently mentioned. All interviewees agreed that the procurement portal model was the most commonly used 219

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Table I Comparative features of B2B e-business models Type of B2B e-business models Online storefront

Manufacturer

Buy-side

Distribution portal

E-speculator

Mega-exchange

Procurement portal

Sell-side asset exchange Solution provider

Specialist originator

Features

Nature of model

Usually operated by wholesalers and retailers over the internet Allows the provision of updated information on products/services Has the ability to instigate immediate business transaction Permits manufacturers to reach buyers directly through the internet Involves a major supplier providing its products/services to potential buyers via the internet Has the potential of creating conflicts within a manufacturer’s supply chain A major buyer seeking products/services from potential suppliers via the internet Encourages potential suppliers to initial business relationships or transactions by approaching the buyer Enables buyers to reduce their costs with the ability to view the list of products/services being offered to them Collates a few major suppliers who then sell their products/services as a group to a set of potential buyers via the internet Allows selling organisations to greatly decrease the cost of sales through more efficient order processing and tracking of order changes Attractive to buyers as it allows them to make several purchases from a group of suppliers that offer a range of related products/services Enables organisations to gain real-time information that can be transferred into a competitive advantage among a large group of buyers Seeks to capitalise on a large quantity of market information (such as pricing) Acts as a central trading hub to facilitate transactions between buyers and suppliers Usually run by third-party market makers where it gathers buyers and suppliers to enable efficient trading between them Bringing a few buyers together to purchase products/services as a group from a set of potential suppliers via the internet Enables buying organisations to gain economic benefits (such as bulk discount) Allows trading, swapping and reselling of orders among a closed group of suppliers Requires strong relationships within the supplier community Success relies on the ability to swap and resell orders efficiently within the group of suppliers Intended to embed unique and valuable services to the product sales Enables organisations to leverage their distinctive expertise in specific areas Provides the opportunity to capture niche markets that have regarded value added services as being more important than price in the buying decision Seeks to standardise and automate the buyer decision-making process for more complex products Aggregate complex products and bundle them into larger order requests, then send the transactions to the exchanges for execution Requires organisations to have a good understanding of issues related to customer decision making and to be committed to providing real-time support for online customers

Supplier-centric

Supplier-centric

Buyer-centric

Supplier-centric

Buyer-centric

Neutral between supplier and buyer Buyer-centric

Supplier-centric

Neutral between supplier and buyer

Buyer-centric

Source: Wise and Morrison (2000), Rappa (2001), Perrott (2000) and Strauss and Frost (2001)

model in the agribusiness industry because current market trends indicated that buyers were making purchases as groups and they were acknowledging the benefits (such as discount purchases) involved. On the other hand, the two least frequently mentioned models identified by the interviewees were sell-side asset exchange and specialist originator models. The main reason for the lack of use of these two models was their complexity and perceived lack of suitability to the agribusiness industry, which was seen to be only in the infant stage of adopting e-business. The results also revealed support for the 16 factors identified in the literature as potential influencing factors to the choice of models with the most frequently mentioned influencing factor being the type of industry, since interviewees suggested that models that were used in one industry might not be applicable in other industries or sectors as they could be quite different. Environmental factors (such

as economy) were regarded as the least important influencing factor where interviewees indicated that organisations alone had limited control over this factor, thus having very minimal impact on the selection of models. In addition, potential differences within agribusiness based on industry sector and organisational size were also highlighted. These findings were then further investigated in stage two of this research to determine if different frameworks were needed by individual sector (grain and cotton) and organisational size (large enterprise and small- to mediumsized enterprise (SME)).

Case-study results The findings in the second stage of the research supported the 16 factors (internal and external) developed in the preliminary model as influencing the choice of B2B 220

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Figure 1 Preliminary model for the selection of B2B e-business models

might adopt the distribution portal model as this model enable suppliers to work as a group so that relationships and mutual understanding could be developed and enhanced.

e-business models. However, five of the 16 influencing factors were identified in this study as being less important to the selection of B2B e-business models with the internal factors appearing to be more influential than the external factors.

External factors Four of the seven external influencing factors were identified as important in the selection of e-business models. Strategic partners were regarded as important since these types of partnerships were formed to achieve common goals and therefore decisions were mutually influential (Gulati et al., 2000). For example, an organisation (suppliers) that insisted on adopting the distribution portal model might not have the support or agreement of their strategic partners if their intention was to swap orders among themselves to gain efficiency. Therefore, relationships between strategic partners under such circumstances could be damaged or not sustainable. Another important factor was the type of industry where organisations would tend to select models that were similar in nature to those used by others in the industry that they were operating in (Timmers, 1999). For example, agribusinesses that offered commodity like products (which required little or no product differentiation) may find the sell-side asset exchange model suitable as this model enabled the swapping and reselling of orders among a group of suppliers. Finally, market trends and competitors were seen as essential influencing factors as they could indicate the models that were common and successful while maintaining competitiveness in the industry. For example, organisations that sought to adopt newer e-business models (such as the especulator model) were considered to be technologically advanced and capable of keeping up with the market changes.

Internal factors Seven of the nine internal factors were identified as important to the selection of e-business models. Respondents supported resources available and technological infrastructure and knowledge as being critical in determining the organisation’s capability to develop and support the selected e-business model (Bagchi and Tulskie 2000). For example, the megaexchange model would be more suitable for SMEs as this model required a lesser commitment (such as financial and human resources) from these smaller organisations, which were subject to intense resource constraint. Target market segment and market scope were regarded as essential to organisations where customers’ needs in the various target market segments must be met with specific models (Hoffman et al., 1997) whilst it was also important that organisations select models that matched the nature of the products or services they offered (Timmers, 1999). For example, the solution provider model might be more appropriate in a niche market since organisations could use this model to offer unique and valuable services to specific target markets. A good understanding of e-business models, including the nature and benefits of the various e-business models, would provide organisations with theoretical and technical knowledge to determine the suitability of the model to be adopted (Timmers, 1999). Lastly, the types of business strategy and organisational structure and culture were important in setting the foundation for the models to be adopted in order to achieve overall strategic goals (Song et al., 2002; Nwachukwu, 2002). For example, organisations (suppliers) seeking a defensive strategy of strategic alliance

Differences in response The findings suggested that there were differences in responses for ten of the 16 factors based on organisational 221

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size, current state of e-business model adoption and management perspective. Respondents from large enterprises agreed that the types of business strategy and the type of industry as two important factors in their choice of B2B e-business models, as they acknowledged the importance of the inclusion of e-business activities in the business plan and recognised that specific industry characteristics would influence the nature of the enterprise and thus choice of a suitable e-business model. In contrast, respondents from SMEs were more concerned with three other factors; understanding of e-business models, on-and off-line marketing strategies and objectives and market trends, as they believed these factors could further enhance the competitiveness of their organisations in competing with those large enterprises in the industry. Respondents in organisations that had adopted an ebusiness model, agreed that the organisational structure and culture, type of industry and competitors’ influence were critical to their model selection. Respondents revealed the importance of mission and vision statements in the e-business models selection process and the need to continually observe competitors. On the other hand, respondents in organisations that were intending to adopt e-business models suggested that market trends and the on-and off-line marketing strategy and objectives were crucial because of the need to keep up with market trends and development. From the management perspective, respondents believed that consultant’s advice was important. Respondents acknowledged that consultants had the expertise and knowledge to provide them with suggestions to assist in making better decisions. In contrast, respondents from operational roles indicated that consultant’s influence was not seen as important since these respondents had minimal involvement in their respective organisations’ strategic planning. Furthermore, respondents suggested that they had very few opportunities to interact with consultants, therefore diminishing the potential influence.

commented that “It is a complicated process that requires extensive planning and understanding on the various steps involved”. The results showed no significant variation in opinions by industry sector or by organisational size. Agribusiness organisations (regardless of sector and size) usually begin the selection process with the identification of the types of e-business models available for conducting B2B e-commerce (step 1). In this step, organisations identify and acquire adequate understanding of the different types of e-business models available (such as features and characteristics) such that considerations could be made to align the organisation’s goals and needs with the nature of these models (see Table II). Through this, organisations could ensure that they were aware of all the models available and how these models could possibly match their needs. This research identified and investigated ten relevant e-business models, while only seven of these models (see Table II) were subsequently identified by respondents as commonly used in the agribusiness industry. The remaining three models were not commonly adopted since they were complicated in nature and hence inappropriate for most of the agribusiness industry, which was relatively new to the e-business concept. Upon aware of the e-business models available for conducting B2B e-commerce and their characteristics, agribusiness organisations would then make a decision to adopt a particular model by considering the impact of a range of internal and external factors (steps 2 and 3). During step 2 of the selection process, organisations identified a list of potential factors (both internal and external) that they would consider when evaluating suitable models. This stage was seen to be important as indicated by one respondent where he commented that “We can’t simply choose a model without knowing what (factors) will affect our decision”. With the list of influencing factors identified (step 2), organisations suggested that they would then seek to evaluate each of the factors and determine their relevance and importance (step 3). The findings revealed that organisations make their choice of model(s) after considering a combination of factors rather than just one single dominant factor and further that the level of importance of the influencing factors differs between organisations and situations. In acknowledging this selection complexity, guidelines were developed (see Table II) to assist organisations to assess and determine the relevance and applicability of the influencing factors in relation to their choice of model(s) to be adopted. The factors in bold in first column (in Table II) with levels or options could potentially help organisations to better understand and match their needs and adopt the

The selection process In addition to the findings on the factors influencing the choice of models, the second stage of the research also found that the selection of a B2B e-business model requires agribusiness organisations to go through a series of steps prior to making their decision (see Figure 2). Furthermore, each step requires an awareness and knowledge of a range of factors that allow organisations to assess the relevance and applicability of the information used to assist the decision. In supporting the complexity of this process, a respondent Figure 2 The selection process of B2B e-business models

222

Online storefronta Manufacturer modela

U

U

U

U

223 U

U

U

U

U

U

U

U U

U U

U

U

U

U

U

Distribution portala

U

U

Buy-side modela

U

U

U U

U U

U

U

U

U

U

U

U

U

U

U U

U

U

U

U

U

MegaE-speculatora exchangea

U

U

U

U U

U

U

U

U

U

Procurement portala

U U

U

U

U

U U

U

U

U

U

U

Sell-side asset exchange

U

U

U U U

U

U

U

U

U

U

Solution provider

U U

U

U U U

U

U

U

U

U

U

Specialist originator

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Eric Ng Volume 20 · Number 4/5 · 2005 · 218 –225

Note: a Models commonly used in the agribusiness industry Source: Analysis of field data and developed for this research

Resources required High U Medium U Low Target market segment and market scope Diversified/global U U Specific/niche market Nature of products or services Commodity U U Real-time information services/ digitised U Complex/specialised/value-added Technological infrastructure and knowledge required High Medium U U Low Level of selected e-business model understanding High Medium U U Low Types of organisation SME U Large enterprise U U Types of possible business strategy pursuing Joint venture/cooperative arrangements Concentric diversification U Product/market development U Focused differentiation Corporate control U Potential on- and off-line marketing strategy and objectives pursuing Increase bargaining power, cost reduction Increase awareness, branding and image Enhance customer/business relationship U U Product/service customisation or differentiation Channel disintermediation U Possible market perception Innovative Modern/technological advance U Market nicher Market leader U

Factors/models

Table II Guidelines on factors affecting the types of B2B e-business model

An empirical framework developed for selecting B2B e-business models

An empirical framework developed for selecting B2B e-business models

Journal of Business & Industrial Marketing

Eric Ng

Volume 20 · Number 4/5 · 2005 · 218 –225

appropriate model. For example, the level (high, medium or low) of technological infrastructure and knowledge required would impact an organisation’s choice of e-business model since some models (such as the e-speculator model) were more complicated and require a higher level of technological knowledge than other models (such as the mega-exchange model). The complexity of the selection process is evident in the response where one respondent stated “I don’t think the choice will be affected by one factor, usually we have to consider a combination of factors. We also have to prioritise according to their level of importance”. Thus, the findings of this research suggested that it is essential to incorporate the consideration of this combination of factors and for each organisation to determine the relevance and significance of these influencing factors in the guidelines (see Table II) for their selection of B2B e-business models. In acknowledging this, agribusiness organisations can then take appropriate actions (such as resources allocation and business strategy to be adopted) according to the influencing factors and determine the suitability of the e-business model to be adopted. For example, an organisation with limited resources might choose to adopt the mega-exchange model since this model is usually operated by a third party, which greatly reduces establishment and maintenance costs incurred by the organisation. On the other hand, an organisation pursuing a defensive strategy (such as a joint venture) might attempt to adopt the sell-side asset exchange model as this model enables organisations to work in a form of partnership that allows them to swap orders among themselves.

Since this study is exploratory in nature, further conclusive explanatory research is required for generalisation and the guidelines developed in this study should be replicated and tested in other agribusiness sectors, such as the seed sector and the beef sector which were frequently mentioned in either the in-depth interviews or the case studies interviews as potentially involve in e-business. This could further made contributions to the theory and practice where comparisons to the findings could be made to determine if any significance existed between these sectors on the factors influencing the choice of B2B e-business models and the guidelines to be developed. In addition, other industries (such as the telecommunications industry) or countries (such as the USA) could also benefit from considering the implications of this study to their particular contexts since they were regarded as active participants of e-business and findings could also be examined from other perspectives.

References Allen Consulting Group (2000), E-commerce beyond 2000, The Commonwealth Department of Communications, Information Technology and the Arts, Canberra. (The) Australian Electronic Business Network (1998), Small Business Attitudes to Electronic Commerce: Taking the Plunge, The Department of Communications, Information Technology and the Arts, Canberra. Bagchi, S. and Tulskie, B. (2000), “E-business models: integrating learning from strategy development experiences and empirical research”, available at: www.research.ibm. com/strategy/pub/ebbb.pdf Barnes, S. and Hunt, B. (2001), E-commerce and V-business: Business Models for Global Success, Butterworth-Heinemann, Oxford. Cunningham, P. and Froschl, F. (1999), Electronic Business Revolution: Opportunities and Challenges in the 21st Century, Springer-Verlag, Berlin. Eisenhardt, K.M. and Martin, J.A. (2000), “Dynamic capabilities: what are they?”, Strategic Management Journal, Vol. 21 Nos 10/11, pp. 1105-21. Gartner Group (2001), “B2B e-data: Gartner projects worldwide business-to-business internet commerce to reach $8.5 trillion in 2005”, available at: www.itaa.org/isec/pubs/ e20013-06.pdf Goodridge, E. (2000), “E-business grows amid market turmoil”, Information Week, No. 811, June 11, p. 256. Gulati, R., Nohria, N. and Zaheer, A. (2000), “Strategic networks”, Strategic Management Journal, Vol. 21 No. 3, pp. 203-15. Hackbarth, G. and Kettinger, W.J. (2000), “Building an e-business strategy”, Information Systems Management, Vol. 17, Summer, pp. 78-95. Hoffman, D.L., Novak, T.P. and Chatterjee, P. (1997), “Commercial scenarios for the web: opportunities and challenges”, in Kalakota, R. and Whinston, A.B. (Eds), Readings in Electronic Commerce, Addison-Wesley, Reading, MA. Kalakota, R. and Robinson, M. (1999), E-business: Road-map for Success, Addison-Wesley, Reading, MA. Malhotra, Y. (2000), “Knowledge management for e-business performance: advancing information strategy to internet time”, Information Strategy: The Executive’s Journal, Vol. 16, Summer, pp. 5-16.

Conclusions and implications In conclusion, this paper has explored the factors influencing the choice of e-business models and provided insight into the current practices of Australian agribusiness in relation to the selection process of e-business models for conducting B2B ecommerce. The findings have highlighted the relative importance of those influencing factors and help to provide a framework to agribusiness organisations in assisting them to make decisions on the selection of the most appropriate ebusiness model. From this framework, managers are able to consider and examine the relevance of these guidelines and criteria, and determine the essential factors that require consideration during their selection processes. The guidelines can also assist managers to determine the level of resources, technological infrastructure and knowledge and the understanding of e-business models, required. For example, managers from SMEs might consider resources available to be critical to their selection of models whilst managers from large enterprises would regard organisational structure and culture as important to their choice of models. Furthermore, agribusinesses can also use the guidelines to help evaluate their business and marketing strategies in relation to the appropriateness of the various models available for adoption. The guidelines can also provide indications of the type of models suitable for specific situations. For example, organisations with substantial resources that seek ultimate control and long-term relationships might choose to adopt either the manufacturer or the buy-side model as these models would be managed by the organisations themselves and give the ability to work closely with business partners. The steps that organisations take when selecting an e-business model and the information required of each step can be used as a checklist for agribusiness organisations. 224

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Ng, E. (2002), “The selection of e-business models for conducting B2B e-commerce in Australian agribusiness organisations”, DBA thesis, University of Southern Queensland, Toowoomba. NOIE (2000), E-Commerce beyond 2000, NOIE, Canberra. NOIE (2001), B2B E-Commerce: Capturing Value Online, NOIE, Canberra. Nwachukwu, L.S. (2002), “Analysis of the failure of e-commerce businesses: a strategic management perspective”, Proceedings of the Annual Meeting of the Association of Collegiate Marketing Educators, St Louis, MO. Papadakis, V.M., Lioukas, S. and Chambers, D. (1998), “Strategic decision-making processes: the role of management and context”, Strategic Management Journal, Vol. 19 No. 2, pp. 115-47. Perrott, B.E. (2000), “Towards an internet marketing effectiveness model”, Working Paper Series, No. 4, Faculty of Business, University of Technology, Sydney. Perry, C. (1998), “Processes of a case study methodology for postgraduate research in marketing”, European Journal of Marketing, Vol. 32 Nos 9/10, pp. 758-802.

Queensland Government, Department of State Development (n.d.), “Agribusiness: industry overview”, available at: www.sd.qld.gov.au/export/industry/agribusiness/overview/ Rappa, M. (2001), “Business models on the web”, available at: http://ecommerce.ncsu.edu/topics/models/models.html Song, M., Calantone, J.R. and Di Benedetto, C.A. (2002), “Competitive forces and strategic choice decisions: an experimental investigation in the United States and Japan”, Strategic Management Journal, Vol. 23, pp. 969-78. Strauss, J. and Frost, R. (2001), E-Marketing, 2nd ed., Prentice-Hall, Englewood Cliffs, NJ. Timmers, P. (1999), Electronic Commerce: Strategies and Models for Business-to-Business Trading, John Wiley & Sons, Singapore. Wise, R. and Morrison, D. (2000), “Beyond the exchange: the future of B2B”, Harvard Business Review, No. 201, November/December, pp. 86-96. Yin, R.K. (1994), Case Study Research: Design and Methods, Sage, Thousand Oaks, CA.

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A decision-support system for business-to-business marketing Behrooz Noori and Mohammad Hossein Salimi Department of Industrial Engineering, Amirkabir University of Technology, Tehran, Iran Abstract Purpose – The main purpose of this paper is to review the related literature and propose a new decision-support-system (DSS) framework for marketing in the business-to-business (B2B) arena based on customer-relationship management (CRM) and knowledge-driven marketing to help related-field graduate students and marketing managers. Design/methodology/approach – Reviews a range of the most important works published between 1966 and 2004 in order to demonstrate both practical and theoretical aspects. The main method of this research is analytical and conceptual and the approach to this subject was to investigate the gap between marketing DSSs and analytical CRM. Findings – Provides information about a customized marketing DSS in a B2B context, indicates related literature and frameworks and, finally, tests the ideas with a case study. Practical implications – Outcomes and applications are identified for developing new activities in improving marketing decision making and marketing planning based on customer orientation and customer satisfaction. Originality/value – Despite such interdependencies, the research in the fields of DSSs and CRM solutions has not adequately considered the integration of such systems. The novel contribution of this paper lies in integrating marketing DSSs and CRM with regard to knowledge-driven marketing in B2B marketing, in both theoretical and practical aspects. Keywords Business-to-business marketing, Customer relations, Decision support systems, Data handling Paper type Conceptual paper

The current issue and full text archive of this journal is available at www.emeraldinsight.com/0885-8624.htm

There is an obvious need for tools, which can improve marketing decision making. Many efforts have been made to develop suitable software tools, that can act as consultants for marketing managers. There are many opportunities for applications of information systems in the marketing area. The modern information technology and information systems can assist a company to manage the increasing information flow and improve its quality. There is a growing interest in the use of marketing-decision-support systems (MDSSs) designed to be used in complicated marketing decision making problems (Talvinen, 1995). An MDSS is defined as “a coordinated collection of data, models, analytic tools and computing power by which an organization gathers information from the environment and turns it into a basis for action” (Little, 1979). The concepts of mass production and mass marketing, first created during the Industrial revolution, are being supplanted by new ideas in which customer relationships are the central business issue. Firms today are concerned with increasing customer value through analysis of the customer lifecycle. The old model of “design-build-sell” (a product-oriented view) is being replaced by “sell-build-redesign” (a customeroriented view). The traditional process of mass marketing is being challenged by the new approach of one-to-one marketing. In the traditional process, the marketing goal is to reach more customers and expand the customer base. But given the

Journal of Business & Industrial Marketing 20/4/5 (2005) 226–236 q Emerald Group Publishing Limited [ISSN 0885-8624] [DOI 10.1108/08858620510603909]

The authors would like to thank the Ministry of Science, Research and Technology of Iran for its financial support and authors gratefully acknowledge Iran Insurance Co. (largest Iranian insurance company) and ¨ V Iran Co. for providing suitable infrastructures for this project. RWTU

An executive summary for managers and executive readers can be found at the end of this issue.

1. Introduction Intense competition is forcing companies to develop innovative marketing activities to capture customer needs and improve customer satisfaction and retention. Businesses can benefit significantly from analyzing customer data to determine their preferences and thus improve marketing decision support (Liu and Shih, 2005; Liang and Lai, 2002). More and more managers are faced with a rapidly changing and highly competitive marketing environment. Marketing managers are forced to become more competitive through better decision making. A decision can be considered as the output of a productive activity whose inputs include intellectual efforts of an individual or a group of individuals, computing hardware and software, data, etc. The advances in computer technology and the computerbased techniques for handling information allow the development of decision-support systems (DSSs), than can play a crucial role in the progress of a firm (Alexouda, 2005). The Emerald Research Register for this journal is available at www.emeraldinsight.com/researchregister

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high cost of acquiring new customers, it makes better sense to conduct business with current customers. In business-to-business (B2B) environments, a tremendous amount of information is exchanged on a regular basis. B2B is one of the most broadly used marketing terms in the information technology (IT) world. In its simplest definition a B2B process is any business process between two companies that uses digital technology. The term can represent functions that provide information, or facilitate transactions, or execute transactions or completely integrate shared business processes into separate, existing enterprise resource planning (ERP) systems. B2B markets have been considered an attractive ebusiness venue for the realization of cost reduction and exchange creation utilities (Hunter et al., 2004). As any perusal of the appropriate journals indicates, the use of quantitative methodologies in business-to-customer (B2C) marketing has been widespread for decades, while B2B marketing has not embraced these techniques to the same extent (Nairn et al., 2004). An increase in the B2B market is potentially of much greater significance than one in the B2C market (Berthon et al., 2003). The explosion in internet-based B2B is driven by economics – the internet offers the potential for reduced prices for goods and reduced transaction costs, but this is not simply derived from the internet as a communications infrastructure (Kuechler et al., 2001). Furthermore, with the advances in computers, databases, communications and the internet technologies, modern organizations nowadays collect massive amounts of data on about everything like, payment records, financial transactions, loan applications and others. Analyzing data on this scale and converting it into knowledge to help decision making, presents exciting new challenges. Customer-relationship management (CRM) has become one of the leading business strategies in the new millennium. It is difficult to find out a totally approved definition of CRM. We, however, can describe it as “managerial efforts to manage business interactions with customers by combining business processes and technologies that seek to understand a company’s customers”, i.e. structuring and managing the relationships with customers. CRM covers all the processes related to customer acquisition, customer cultivation, and customer retention (Hwang et al., 2004). Data mining is a new generation of computerized technologies for discovering knowledge hidden in large amounts of data. Support of domain expertise to make better decisions and new IT techniques to promote B2B marketing are essential (Changchien and Lu, 2001). Data mining techniques are useful for extracting marketing knowledge and further supporting marketing decisions (Bose and Mahapatra, 2001; Shaw et al., 2001). In this paper, we focus on a very specific DSS on behalf of market managers who want to develop and implement efficient B2B marketing programs by fully utilizing a customer database. This is important because, due to the growing interest in marketing, many firms devote considerable resources to identifying households that may be open to targeted marketing messages. This becomes more critical through the easy availability of data warehouses combining demographic, psychographic and behavioral information (Kim and Street, 2004). In this paper we will focus on DSSs for the B2B market that are driven by data mining modeling and analysis. The buying patterns of individual customers and groups can be identified via analyzing

customer data (Wells et al., 1999), but also allows a company to develop one-to-one marketing strategies that provide individual marketing decisions for each customer (Peppers and Rogers, 1997). The ultimate goal of DSSs is to provide managers with information that is useful for understanding various managerial aspects of a problem and to choose a best solution among many alternatives. The paper is organized as follows. Section 2 deals with the presentation of DSS and CRM. Literature review of MDSS studies are provided in section 3. In section 4 the proposed MDSS is presented and in section 5 related case study and implications is discussed. Finally, in section 6, the conclusions of the paper are summarized.

2. Introduction to DSS and CRM 2.1. DSS A DSS is an interactive computer-based system designed to help in decision making situations by utilizing data and models to solve unstructured problems. The aim of DSSs is to improve and expedite the processes by which management makes and communicates decisions – in most cases the emphasis in DSSs is on increasing individual and organizational effectiveness. It is very difficult to tell precisely where the interrelatedness of various business functions to one another vertically and horizontally is emphasized (Talvinen, 1995). A DSS is a coordinated collection of data, system tools, and techniques with supporting software and hardware by which an organization gathers and interprets relevant information from business and the environment and turns it into a basis for making management decisions[1]. The system, usually based on a model and computer software package, describes the implications of specific marketing decisions and/or recommends specific marketing actions, using a set of input information. This information may either reside permanently in the DSS or be input for the particular scenario of interest (or both). The information can consist of primary information (e.g. sales and cost information from company records, or subjective judgments by managers about the likely impact of increased advertising spending) and/or secondary information (e.g. sales of competitors’ products from a syndicated database constructed via store audits). An important aspect of many DSSs is the facilitation of “what if” analyses, i.e. the sensitivity of optimal marketing strategy to the assumptions in the input information. DSSs are divided into four main parts in systematic view: 1 Input: low-volume data or massive databases, analytical models. 2 Processing: interactive, simulations, data analysis tools. 3 Output: special reports, decision analyses, responses to queries. 4 Users: professionals, managers. Organizations are becoming increasingly complex with emphasis on decentralized decision making. This trend necessitates enterprise DSSs for effective decision making. In the process of decision-making, decision makers combine different types of data (e.g. internal data and external data) and knowledge (both tacit knowledge and explicit knowledge) available in various forms in the organization. The decisionmaking process itself results in improved understanding of the 227

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problem and the process, and generates new knowledge. In other words, the decision-making and knowledge creation processes are interdependent.

departments handle this complex feedback procedure. Campaign management software manages and monitors customer communications across multiple touchpoints, such as direct mail, telemarketing, customer service, point-of-sale, e-mail, and the Web. While campaign management software may be part of the overall solution, it is primarily the people and processes that contribute to smooth interactions between marketing, IT, and the sales channels. The outcome of this process is marketing data intelligence, which is defined as “Combining data driven marketing and technology to increase the knowledge and understanding of customers, products and transactional data to improve strategic decision making and tactical marketing activity, delivering the CRM challenge” (Rygielski et al., 2002). There are two critical components of marketing data intelligence: customer data transformation and customer knowledge discovery. Raw data extracted and transformed from a wide array of internal and external databases, marts or warehouses.

2.2. CRM: an overview CRM is defined by four elements of a simple framework: know, target, sell, service. CRM requires the firm to know and understand its markets and customers. This involves detailed customer intelligence in order to select the most profitable customers and identify those no longer worth targeting (Rygielski et al., 2002). CRM also entails development of the offer: which products to sell to which customers and through which channel. In selling, firms use campaign management to increase the marketing department’s effectiveness. Finally, CRM seeks to retain its customers through services such as call centers and help desks. CRM is essentially a two-stage concept. The task of the first stage is to master the basics of building customer focus. This means moving from a product orientation to a customer orientation and defining market strategy from outside-in and not from inside-out. The focus should be on customer needs rather than product features. Companies in the second stage are moving beyond the basics; they do not rest on their laurels but push their development of customer orientation by integrating CRM across the entire customer experience chain, by leveraging technology to achieve real-time customer management, and by constantly innovating their value proposition to customers (Rygielski et al., 2002). Analytical CRM provides all components to analyze customer characteristics (behaviors) in order to accomplish operational CRM activities. An enterprise data warehouse is a critical component of a successful CRM strategy (Rygielski et al., 2002). Most firms have massive databases that contain marketing, human resource (HR), and financial information. However, the data required for CRM can be limited to a marketing data mart with limited feeds from other corporate systems. Experience with CRM will dictate when to aggregate data for reasons of simplicity and when to keep the data granular. External sources of data or purchased databases can be a key source for gaining customer knowledge advantage (Freeman, 1999; Hill, 1999). Some examples of external data sources include lookups for current address and telephone number, household hierarchies, Fair-Isaacs credit scores, and Webpage viewing profiles (Freeman, 1999). Next, the CRM system must analyze the data using statistical tools and data mining. Whether the firm uses traditional statistical techniques or one of the data mining software tools, marketing professionals need to understand the customer data and business imperatives. The firm should employ data mining analysts who will be involved but will also make sure the firm does not lose sight of their original reason for doing data mining. Thus, having the right people who are trained to extract information with these tools is also important. The end result is segmentation of the market, and individual decisions are made regarding which segments are attractive. The last component of a CRM system is campaign execution and tracking. These are the processes and systems that allow the user to develop and deliver targeted messages in a testand-learn environment. Implementation of decisions made as a result of data mining and online analytical processing (OLAP) is done through campaign execution and tracking. Today there are software programs that help marketing

2.3. DSSs and CRM Despite such interdependencies, the research in the fields of DSSs and CRM solutions has not adequately considered the integration of such systems. Proper integration of DSSs and CRM will support the required interaction and will present new opportunities for enhancing the quality of support provided by each system. A synergy can be created through the integration of decision support and CRM, as these two technology consist of activities that complement each other. More specifically, the knowledge acquisition, storage and distribution activities in CRM enable the dynamic creation and maintenance of decision models, in this way, enhancing the decision support process. In return, the application and evaluation of various decision models and the documentation of decision instances, supported by a DSS, provide the means for acquiring and storing the tacit and explicit knowledge of different decision makers and facilitate the creation of new knowledge. Such integration is expected to enhance the quality of support provided by the system to decision makers and also to help in building up organizational memory and knowledge bases. Decision makers, through the experience of using such tools and techniques, gain new knowledge pertaining to the specific problem area. Specific DSSs are built using data extracted from various data sources and models extracted from various knowledge sources.

2.4. Digital technology and marketing strategy The emergence of digital technology is creating fundamental changes to the way that business is conducted. These changes are altering the way in which every enterprise acquires wealth and creates shareholder value. The myriad of powerful computing and communications technology allow organizations to streamline their business processes, enhance customer service and offer products and services. In the process of forming a marketing strategy to respond to the challenges of environmental change, a firm should analyze its active customers to identify opportunities for marketing innovation. Choice of appropriate marketing strategy could lead to superior performance (Chang et al., 2003). 228

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touch points through which they occurred, and identification information of relevant personnel.

2.5. B2B and B2C context 2.5.1. E-commerce Researchers believe that e-commerce on the internet goes beyond simply buying and selling electronically as it involves a wide variety of pre- and post-sales activities, such as advertising, maintaining business relationships, and enhancing business communication (Zwass, 1996). Based on the parties involved in the business transaction, ecommerce can be divided into: . B2C: the sale of products and services to individuals. . B2B: the buying and selling of products and services among businesses.

2.5.3. B2B and B2C differences B2B and B2C differences concern relationships. Relationship information represents the terms and conditions of any ongoing business between you and your customers. For B2B relationships, this information represents the contracts between you and your customers. Contracts have product, price, quality of service, and payment terms. They are associated with a customer’s organizational entity, and they have identification, role, and authority information for contacts and administrators (different than identification contacts). For B2C relationships, this information might represent warranties or service contracts that include product, price, and quality-of-service terms, as well as contact identification information. Table I represents a tabular comparison of B2B and B2C differences.

In this paper, we focus on B2B, which has become an increasingly important topic for both researchers and practitioners (Teo and Ranganathan, 2004). 2.5.2. B2B and B2C similarity There are some similarity aspects (Seybold, 2002): . Marketing information. Marketing information should include customer value, customer profitability, the segments to which a customer belongs, and scores and indicators for loyalty, satisfaction, recency, frequency, and wallet share, it should also include a history of all the campaign offers that you’ve made to the customer and the customer’s responses to those offers. . Sales information. Sales information should include the quotes and proposals that you’ve made to customers and the orders that your customers have placed with you. It should include complete quote, proposal, and order histories, all quote, proposal, and order details (as you represent them), and an indication of the touch point with relevant touch point information. . Service information. Service information represents your customers’ requests and your responses for product support and service, order management actions such as returns and complaints, and customer management actions such as identification information changes. This information should include outstanding requests and their priority, the histories and details of these interactions, the

3. Literature review 3.1. Overview of MDSS and related literature This section briefly reviews the marketing DSS literature and also examines related. IT support for marketing planning can aid in the use of marketing tools, facilitate group planning, and support moves towards continuous planning based on a live marketing model of the business. But, amongst other factors, achieving these benefits depends on the style of support provided by the system. And a review of relevant DSS literature was seen (Wilson and McDonald, 2001). Marketing was the first functional area to embrace the concept of a management information system (MIS) and tailor it to the needs of managers. Kotler (1994) coined the term “marketing nerve center” and explained how a firm could create a separate area for its computer resources dedicated to supporting marketing activity. This notion was immediately grasped by a number of marketing academicians who developed conceptual models of marketing information systems (later given the acronym MKIS) to illustrate system components and uses (Lia et al., 2001). Mitchell and Wilson

Table I Another comparison of B2C and B2B B2C commerce

B2B commerce

Customer acquisition methods Entry barriers for competitors Relationship types

Mass communication: advertising, affiliate programs Low: audience size, logistics capability, experience quality Browsing of catalogs Placement of orders Payment execution Status tracking

Selling Market size

Smaller buyers Consumer markets are measured in the “millions”

Personal selling: direct salesforce, trade shows High: domain expertise, buyer/supplier relationships MRO procurement Direct procurement Payment execution Status tracking Catalog information management Order fulfillment Collaborative forecast management Promotions management Returns management Design collaboration Work-in-process tracking Collaborative planning management Larger buyers B2B firms have customer bases over “thousands”

Source: Kaplan (2000) and Olsen (2000)

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(1998) reviewed some current guidance on when and how to segment B2B markets. Since the early 1980s, the concept of relationship management in marketing area has gained its importance. Acquiring and retaining the most profitable customers are serious concerns of a company to perform more targeted marketing campaigns. For effective CRM, it is important to gather information on customer value. Few have considered customer lifetime value (CLV). From the perspective of niche marketing, all customers are not equal (they have different lifetime value or purchase behaviors), even if they purchase identical products or services; market segmentation is therefore necessary. Firms are increasingly recognizing the importance of the lifetime value of customers (Berger and Nasr, 1998). Several studies have considered the use of CLV. Generally, recency, frequency, and monetary (RFM) methods have been used to measure it (Kahan, 1998; Miglautsch, 2000). The concept has been applied to cluster customers for niche marketing (Ha and Park, 1998). Prediction models have focused mainly on expected future cash flow derived from customers’ past profit contribution. Hwang et al. (2004) suggest an CLV model considering past profit contribution, potential benefit, and defection probability of a customer. The concept of segmentation is central to marketing. A search on this keyword in article titles only resulted in more than 30 articles in the Journal of Marketing, more than 50 in the Journal of Marketing Research. In the early marketing applications, the process of dividing a population of customers by means of clustering techniques into homogeneous groups was often done without the use of a dependent/target variable. However, marketers realized that segmentation should not be an end in itself, but rather a means to an end. As most companies want to maximize profits (or some others quantity, e.g. sales), marketers quickly realized that a segmentation should ensure that “better” customers are separated from other customers. This largely explains the popularity of clustering techniques using a dependent variable such as chi-square automated interaction detection (CHAID) (Jonker et al., 2004). Also the application of segmentation and predictive modeling is an important topic in the database marketing (DBM) (Verhoef et al., 2002). subsystems in marketing information systems (MKIS) support new product evaluation, forecasting demand or sales, product deletion, pricing strategy, analyzing sales profit, promotion strategy, computing operating budgets, selecting advertising media, assigning sales representatives to territories, approving customer credit, location of facilities (e.g. warehouses or stores), routing of salesperson or deliveries, computing economic order quantities (EOQ) and computing reorder points (Lia et al., 2001). Talvinen (1995) clarified the applicability of marketing information systems (MKIS) to other marketing and management related IS, such as MIS and DSS. In terms of classification, customer-centric analytic applications belong to the business intelligence (BI) or decision support domain (we use these terms synonymously). They’re not software that you use to do business. Because, they’re software that you use to analyze business. Further, within BI or DSS, there are many types of analytic applications – customer-centric or CRM analytics, business operations analytics, financial analytics, and supply chain analytics, just to name a few. Because our interest, really our corporate focus, is on the customer, we consider the domain to be customer-centric intelligence, and

we’re most interested in customer-centric analytic applications, also commonly called CRM analytics or analytical CRM customer-centric analytic applications are tools that help make you more customer-focused (Seybold, 2002).Montgomery and Urban (1970) and Crissy and Mossman (1977) viewed the MKIS as a DSS, whereas King and Cleland (1974) recognized its value in planning marketing strategy. Eom (1999) investigates the changing intellectual structure of the general DSS field by means of an empirical assessment of the DSS literature over two successive time periods, 1971-1990 and 1991-1995. Other related and important studies are van Bruggen et al. (1996, 1998), Little (1979), Zinkhan et al. (1987), Higby and Farah (1991), Duan and Burrell (1995), Benbasat and Peter (1996), Hoch and Schkade (1996), Claire (1997), Wierenga and van Bruggen (1997), Bucklin et al. (1998), Jiang et al. (1998), Beynon et al. (2001), Kohli et al. (2001), Berg and Rietz (2003), Beroggi (2003) and Tsaia and Chen (2004). Bose and Sugumaran (2003) proposed an integrated framework for CRM through the application of knowledge management technology. Davies (2001) discussed comprehensively application of AHP within a marketing knowledge-based DSS (KB-DSS). Perhaps even more remarkably, despite quite widespread computer literacy and the adoption of ERP, SCM and CRM systems, the utility of information systems is still an issue (Hulbert, 2003). The above referenced studies deal with the use of DSSs and related modules for real-life marketing decision making in companies. 3.2. B2B-specific related literature The intense pressure to improve the efficiency and effectiveness of marketing efforts in B2B markets requires new approaches to old problems (Cannon and Perreault, 1999). Strategic decisions in business markets can benefit from the development and use of analytical approaches derived from industrial organization economics theory (Sashi and Kudpi, 2001). B2B markets have fewer partners, closer buyer-seller relationships, better technology and better information exchange than B2C markets (Hutt and Speh, 1998). Gummesson (2004) argued the comparison of B2B and B2C relationship marketing. Wouters (2004) investigated the development of customer service strategies deployed by industrial organizations and the impact this has on their marketing strategy in B2B situations. Wouters (2004) argued that some information aspects those are important in B2B marketing are: . general information (e.g. company name, number of employees, turnover previous year, expected turnover current year, geographical scope, describe major products and processes and relevant stakeholders, etc.); and . marketing and sales information (e.g. turnover last year, turnover next year, total market volume, market share, major trends, market support, product range, product quality, logistics and people based service, etc.). B2B customer-related activities are (Teo and Ranganathan, 2004): . accept and process customer orders; . pre-sales activities/services; . product/service delivery via the web; . post-sale service (e.g. complaints, support, etc.); . distribution activities (supply chain coordination, etc.); 230

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profiles, a marketer is interested in the customer demographic details as well as the characteristics of the purchase transactions of the customer. The data mining tasks used in customer profiling can be dependency analysis, class identification and concept description, and we present a list of transaction characteristics that can help the marketer construct useful customer profiles (Shaw et al., 2001).

gathering customer data and analysis; and accept and process customer payments.

Deeter-Schmelz and Kennedy (2004) investigated related literature of B2B online activities. Easton and Araujo (2003) studied customer relationships in B2B area. Each customer has his own requirements and demands, and reconciling them creates issues of prioritization part of the problem is that of managers getting timely information. It follows that a well-designed and wellresourced customer information system or DSS could be used to flag up potential problems and conflicts and help resolve them (Easton and Araujo, 2003). Pires and Aisbett (2003) presented a review of a crosssection of 21 papers in the business and academic literature yielded over 50 advantages and forty disadvantages that may impact on firms when they adopt e-commerce in B2B operations. Other references about B2B related to our work are (Gordon et al., 1993; Cann, 1998; Freytag and Clarke, 2001; Kohli et al., 2001; Kuechler et al., 2001; Hunter et al., 2004).

4.1.1. Frequency of purchases How often does the customer buy your product or service? By knowing this, the marketer (or marketing manager) can build targeted promotions such as a frequent buyer programs. 4.1.2. Size of purchases or monetary How much does the customer spend on a typical transaction? This information helps the marketer devote appropriate resources to the customer who spends more. 4.1.3. Recency of purchases How long has it been since this customer last placed an order? The marketer may investigate the reasons why a customer or a group has not purchased over a long period of time and take appropriate steps. Many times, this could be due to the customer having moved from that location or having shifted loyalty.

4. The structure of proposed marketing DSSs Today’s customers have such varied tastes and preferences that it is not possible to group them into large homogenous populations to develop marketing strategies. In fact, each customer wants to be served according to her individual and unique needs. Database marketing, characterized by marketing strategies based on the great deal of information available from the transaction databases and customer databases became popular and most organizations have built up massive databases about their customers and their purchase transactions. But, due to lack of appropriate tools and techniques to analyze these huge databases, a wealth of customer information and buying patterns is permanently hidden and unutilized in such databases. Knowledge-based marketing, which uses appropriate data mining tools and knowledge management framework, addresses this need and helps leverage knowledge hidden in databases. The components of the proposed MDSS are as shown in Figure 1.

4.1.4. Identifying typical customer groups The characteristics of each group can be obtained by class identification or concept description. Knowing the customer and targeting the right deal gets a far better response rate than a general message. 4.1.5. Computing customer lifetime values With customer profiling supported by data mining and knowledge discovery systems, a number of marketing activities can be enhanced, such as computing customer lifetime values, prospecting and success or failure of marketing programs. Customer lifetime values, a measure to understand what is happening to the size and value of a customer base, can be computed by using the customer profile information combined with the product and promotional statistics. Customer lifetime values are asset measures that can help marketers judge their expenditures by measuring a plan’s efficiency in producing assets. 4.1.6. Prospecting Customer profiles, especially their buying patterns, give clues to the marketer on prospective customers.

4.1. Customer profiling One of the useful knowledge about a customer is her profile, which is used to make several important marketing decisions. A customer profile is a model of the customer, based on which the marketer decides on the right strategies and tactics to meet the needs of that customer. While learning customer

4.1.7. Successor failure of marketing programs Customer databases provide accurate information on the results of marketing programs. The marketer can use the

Figure 1 Data road-map

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preliminaries to formulating strategies segmentation, targeting and positioning.

patterns of purchase discovered from the database and the related marketing programs to measure the short-term and long-term effects of the programs.

for

market

5. Decision support in B2B context: service sector case study

4.2. Deviation analysis Knowledge of deviations from normal is extremely important to a marketer. A deviation can be an anomaly fraud or a change. In the past, such deviations were difficult to detect in time to take corrective action. Data mining tools provide powerful means such as neural networks for detecting and classifying such deviations. Once a deviation has been discovered as a fraud, the marketer takes steps to prevent such frauds and initiates corrective action. If the deviation has been discovered as a change, further information collection is necessary. For example, a change can be that a customer got a new job and moved to a new house. In this case, the marketer has to update the knowledge about the customer. A marketer can use the deviation detection capability to query changes that occurred as a result of recent price changes or promotions.

5.1. Content The role of information in services marketing information has been recognized as a key element of most services. However, information has been generally viewed as a way to support the basic service and to enhance performance rather than a central focus for segmentation purposes. In the traditional view, information is generally classified as one of eight supplemental services (along with order taking, safekeeping, billing, consultation, hospitality, exceptions and payment) and seen as essential if customers are to obtain full value from any good or service. Most research on the role of information in services marketing has focused on the technology issues involved in developing effective information collection systems, rather than on how information can best be used to gain competitive advantage in the marketing of services. Information technology can be used to increase the tangibility of services, as well as a tool for analyzing customers’ purchasing habits and altering marketing strategy. Competitive success is often determined by “incremental differences in companies’ abilities to acquire, distribute, store, analyze, and invoke actions based upon information”. This ability to manage and effectively use information technology is considered especially important as the market moves further into the era of the virtual business. With information on products and services becoming instantly available to customers and competitors, it will become increasingly important to develop new strategies of differentiation and to develop strong bonds with customers to offset the “increased pressure of commoditization” (Emmelhainz and Kavan, 1999). While important in a supporting role for many types of services, information is the core service in a number of industries. Services are classified into four categories based upon the type of service provided and the recipient of the service: tangible actions to people’s bodies, tangible actions to physical possessions, intangible actions directed at a client’s mind, and intangible actions directed at intangible assets (Emmelhainz and Kavan, 1999). The latter category, which includes financial services, along with accounting, law, management consulting, medical diagnosis, and the like, is referred to as information processing services. The service sector, where information is the service is sizeable and it is predicated that by 2000, 44 percent of those employed in the service sector will be working in the information area (Sisodia, 1992). In these industries, the critical aspect of information is not so much the effective use of information technology to acquire, store and analyze data on customers, but rather the understanding of and ability to respond to differing information capabilities and needs of customers. Here the focus is on using information needs as a way of building customer loyalties, increasing customer involvement in the service process, and strengthening customer relationships. In other words, information is becoming an essential element for successful relationship marketing (Emmelhainz and Kavan, 1999). B2B service marketing has received comparatively less attention in the academic literature than B2B product marketing; much of the service marketing literature

4.3. Trend analysis Trends are patterns that persist over a period of time. Trends could be short-term trends like the immediate increase and subsequent slow decrease of sales following a sales campaign. Or, trends could be long-term, like the slow flattening of sales of a product over a few years. Data mining tools, such as visualization, help us detect trends, sometimes very subtle and hidden in the database, which would have been missed using traditional analysis tools like scatter plots. In marketing decisions, trends can be used for evaluating marketing programs or to forecast future sales. 4.3.1. Forecast future sales A forecast future sale is one of the popular uses of trend analysis. Marketers are interested in knowing how various marketing programs affect future sales of their products. Data mining allows discovery of subtle relationships like a peak in sales of a product associated with a change in the profile of a particular group of customers. 4.4. Other CRM components In the proposed DSS, we used four key steps for CRM based on knowing customers better: 1 identifying the right customers; 2 differentiating among them; 3 interacting with and learning from existing customers; and 4 customizing the product or service to the needs of individual customers. Current efforts on CRM are focused on the customer interface and managing customer interactions. But inadequate information about customers and the lack of a systematic information management framework continue to hinder the efforts of organizations, particularly the marketing function, to manage their customer relationships. 4.5. Data-mining component Data warehouses and data marts are accessed by decision makers using tools supporting OLAP, queries and ad hoc queries. 4.6. Marketing strategy The development of effective marketing strategy involves conducting internal, competitor and customer analyses as 232

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discusses the ways in which services and products are different. Compares service marketing to product marketing in the industrial sector from the perspective of customer value creation (Gordon et al., 1993).

a non-zero purchase but have never made any transactions, were also removed. 5.3. The solution The DSS was developed in Visual Basic application language with Access 2000 database and supported with SPSS 12 and Expert Choice. It runs on a PC and can link with legacy systems. A block diagram of the DSS is shown in Figure 2.

5.2. The problem Our current implementation of the DSS is part of an professional services. We are building it for the Rheinisch¨ berwachung Verwain Iran Westfa¨lische Technischen U ¨ (RWTU VIran), a German and Iranian joint-venture ¨ V is abbreviation of Technical U ¨ berwachung company. TU Verwain (Technical Inspection Union). Part of case study services include: technical inspection in industrial sites, automotive inspection and commodity inspection, safety evaluation of medical devices, product certification and conformity tests, quality management mystem certifications, environmental quality management system certifications, Industrial projects, IT services and technical training in different fields in central Asia. It has approximately 1,600 clients and active customers in B2B market. The marketing motto and vision of the case is: better, closer, more. Better means to be better than the competition is their supreme goal. Being closer to customers and to innovations is for them a matter of course. More services is the essence of company’s portfolio. It’s decision makers must target customer groups, develop market strategies to satisfy customer needs, predict customer behavior thereby, recommend new services, attract potential customers, set product promotion system and retain active customers. Data for customer transactions have been collected from the data warehouse and internal data servers (data warehouses) between 2002 and September 2004. The data set was preprocessed to extract customer transactions. Unreasonable records, such as those of customers who have

5.4. Database On the left side of Figure 2 basic components are shown. There are several sources of internal data (sources for the external data are on company web server): . summary tables that describe customers (e.g. billing records); . customer surveys of a subset of customers who answer detailed questions; . behavioral data contained in transactions systems (web logs, credit card records, etc.); and . accounting computerized system. 5.5. Processing Processing component is based on section 4. The DSS organizes the database and performs analysis. All this is done interactively in a user-friendly environment. 5.6. Outputs Outputs are shown in Figure 2. These outputs are synthesized into related reports. 5.7. System benefits The system provides both monetary and managerial benefits: . Monetary benefits: savings are estimated at about $10,000 per new sell. . Managerial benefits: the decision-making process has been considerably improved by quicker and better analysis.

Figure 2 Structure of MDSS

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5.8. Results of proposed DSS Results of the proposed DSS are as follows: . understand the behavior of customers; . understand the products and services that customers need and the ones that they buy; . identify best customers; . identify most loyal customers; . understand how efficient and effective marketing, sales, and service business processes, and the applications that implement them, are in addressing customers’ needs; . tune marketing, sales, and service business processes and the applications that implement them to better serve customers; and . marketing strategic planning, an important concern for service businesses is how to develop an appropriate segmentation and relationship marketing strategy that is tied to the value contribution of the customer base (Emmelhainz and Kavan, 1999).

evolutionary algorithms”, Decision Support Systems, Vol. 38 No. 4, pp. 495-509. Benbasat, I. and Peter, T. (1996), “The effects of decision support and task contingencies on model formulation: a cognitive perspective”, Decision Support Systems, Vol. 17, pp. 241-52. Berg, J.E. and Rietz, T.A. (2003), “Prediction markets as decision support systems”, Information Systems Frontiers, Vol. 5 No. 1, pp. 79-93. Berger, P. and Nasr, N. (1998), “Customer lifetime value: marketing models and applications”, Journal of Interactive Marketing, Vol. 12 No. 1, pp. 17-30. Beroggi, G.E.G. (2003), “Internet multi-attribute group decision support in electronic commerce”, Group Decision and Negotiation, Vol. 12, pp. 481-99. Berthon, P., Ewing, M., Pitt, L. and Naude, P. (2003), “Understanding B2B and the web: the acceleration of coordination and motivation”, Industrial Marketing Management, Vol. 32, pp. 553-61. Beynon, M., Curry, B. and Morgan, P. (2001), “Knowledge discovery in marketing: an approach through rough set theory”, European Journal of Marketing, Vol. 35 No. 7, pp. 915-37. Bose, I. and Mahapatra, R.K. (2001), “Business data mining – a machine learning perspective”, Information and Management, Vol. 39 No. 3, pp. 211-25. Bose, R. and Sugumaran, V. (2003), “Application of knowledge management technology in customer relationship management”, Knowledge and Process Management, Vol. 10 No. 1, pp. 3-17. Bucklin, R.E., Lehmann, D.R. and Little, J.D.C. (1998), “From decision support to decision automation: a 2020 vision”, Marketing Letters, Vol. 9 No. 3, pp. 235-46. Cann, C.W. (1998), “Eight steps to building a business-tobusiness relationship”, Journal of Business & Industrial Marketing, Vol. 13 Nos 4/5, pp. 393-405. Cannon, J.P. and Perreault, W.D. Jr (1999), “Buyer-seller relationships in business markets”, Journal of Marketing Research, Vol. 36, November, pp. 439-60. Chang, K., Jackson, J. and Grover, V. (2003), “E-commerce and corporate strategy: an executive perspective”, Information & Management, Vol. 40, pp. 663-75. Changchien, S. and Lin, M.-C. (2005), “Design and implementation of a case-based reasoning system for marketing plans”, Expert Systems with Applications, Vol. 28 No. 1, pp. 43-53. Changchien, S.W. and Lu, T. (2001), “Mining association rules procedure to support online recommendation by customers and products fragmentation”, Expert Systems with Applications, Vol. 20, pp. 325-35. Claire, C. (1997), “Marketing decision support systems”, Industrial Management & Data Systems, Vol. 97 No. 8. Crissy, W.J.E. and Mossman, F. (1977), “Matrix models for marketing planning: an update and expansion”, MSU Business Topics, Vol. 25, pp. 17-26. Davies, M. (2001), “Adaptive AHP: a review of marketing applications with extensions”, European Journal of Marketing, Vol. 35 Nos 7/8, pp. 872-93. Deeter-Schmelz, D.R. and Kennedy, K.N. (2004), “Buyerseller relationships and information sources in an e-commerce world”, Journal of Business & Industrial Marketing, Vol. 19 No. 3, pp. 188-96.

6. Conclusions and future research There is a clear and present need to exploit the available data and technologies to develop the next generation of business applications that can combine data-dictated methods with domain specific knowledge. Analytical information technologies, which include DSSs, are particularly suited for these tasks. These technologies can facilitate both automated and human expert driven knowledge discovery and predictive analysis, and can also be made to utilize the results of models and simulations that are based on business insights. Despite such interdependencies, the research in the fields of DSS and CRM solutions has not adequately considered the integration of such systems. The novel of this paper is integrating marketing DSSs and CRM regard to knowledge driven marketing in B2B marketing in theoretical and practical aspects. Our findings provide information about a customized MDSS in a B2B context and offer related literature and framework and finally tests it with a case study. For future research, there are two categories for our work: 1 Model-based extension/case-based reasoning (CBR), which consists of retrieving, reusing, revising, and retaining cases. CBR has been proved effective in retrieving information and knowledge from prior situations and being widely researched and is applied in a great variety of problem territories (Changchien and Lin, 2005). Improving MDSSs with CBR can be a new horizon of this research. 2 MDSS extension with distributed group support system (DGSS). DGSS is a technology that can help groups to overcome some of the difficulties associated with being in different places and sometimes in different time zones (Tung and Turban, 1998). Designing and developing DGSS for marketing is anther considerable topic.

Note 1 American Marketing Association (www.marketingpower. com).

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Why doesn’t marketing use the corporate data warehouse? The role of trust and quality in adoption of data-warehousing technology for CRM applications Fay Cobb Payton Department of Business Management, College of Management, North Carolina State University, Raleigh, North Carolina, USA, and

Debra Zahay College of Business, Northern Illinois University, De Kalb, Illinois, USA Abstract Purpose – This paper aims to investigate organizational factors to explain why a corporate data warehouse (CDW) was not used by marketing to the extent that it was expected to be used for CRM and other marketing purposes. Design/methodology/approach – A case study of a single health-care payor organization is used in this study. Findings – Reveals the three primary implementation factors related to marketing’s lack of trust in the data, low perceived data quality and perception of marketing needs not being met. Practically, the unique data needs of marketing should be considered in the implementation of a CDW and its interface. Originality/value – This is the first study of its kind to take the needs of marketing users into consideration. Keywords Data handling, Customer relations, Trust Paper type Research paper

concludes that three interrelated constructs emerge in explaining 50 percent of the disappointing use of a corporate data warehouse by the marketing function for CRM applications. These three primary implementation factors are as follows: marketing’s lack of trust in the data in the CDW; marketing’s low perceived quality of the data; and marketing’s perceived lack of incorporation of their needs in the design of the data warehouse and data warehouse interface. This study also suggests perceived data quality is related to both trust in the data and trust in the information technology (IT) department. Together, these implementation factors can lead to successful implementation in dataintensive and information-sharing environments characteristic of data warehousing technologies supporting CRM applications. The proliferation of data warehousing technologies and applications has been widely documented among information technology consultants and vendors. According to Gartner, organizations will be confronted with the challenges of managing over 30 times more data by 2005 in a continual effort to meet the demands associated with electronic commerce and supply-chain applications (Hochberg, 2000). Defined as a central repository used for decision support, data warehouses are integrated repositories of subject oriented, time-variant data from throughout the organization. Data related to the industry and the customer are collected over time and used to perform trend analyses, forecasting and comparative analyses. Typically, these data are not updated in real time; data are refreshed on a periodic basis from operational systems. To enable these capabilities, data warehousing implementations deploy multiple, parallel and massive processing databases well as a series of other

An executive summary for managers and executive readers can be found at the end of this issue.

Introduction This paper uses a single case study to investigate organizational factors that explain why a corporate data warehouse (CDW) that was implemented in a health care payor organization was not used by marketing to the extent that it was expected to be used by that function for CRM purposes. This study demonstrates that findings from the marketing research context (Moorman et al., 1992) are supported in the context of the adoption of the corporate data warehouse by marketing professionals. As in the context of marketing research users and suppliers, this study suggests that, in a marketing context, information supplier and information user relationships as well as data quality influence the extent by which CDW data are used in decision making. While the information technology literature would predict that many other implementation factors, such as training and overall environmental factors, are important, this study The Emerald Research Register for this journal is available at www.emeraldinsight.com/researchregister The current issue and full text archive of this journal is available at www.emeraldinsight.com/0885-8624.htm

Journal of Business & Industrial Marketing 20/4/5 (2005) 237–244 q Emerald Group Publishing Limited [ISSN 0885-8624] [DOI 10.1108/08858620510603918]

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hardware and software technologies (Wixom and Watson, 2001). Customer relationship management (CRM) applications as well as Sales Force Automation (SFA) and contact management are often enabled by data warehousing technologies. These data-based applications have been viewed as an emerging research stream in the marketing and information systems fields (Kalakota and Robinson, 1999; Romano, 2001; Shaw et al., 2001; Abbott et al., 2001; Starkey and Woodcock, 2002; Reinartz et al., 2004). Despite widely reported implementation failures ranging in rates of 55 to 75 percent and warnings about the perils of implementation (Woodcock and Starkey, 2001) data warehouses have been described as the linchpin to any effective marketing effort that intends to include CRM as part of its strategy. To this end, IDC projected that the worldwide spending on CRM applications, including databases, would total $20 billion by 2004. Broadly defined, CRM is a process/application that permits organizations to gather and analyze customer data rapidly while seeking to improve customer loyalty via targeted products and services (Rigby et al., 2002). From a functional point of view, CRM depends upon operational integration of disparate sources of data, often in a data warehouse. The analytical functions of CRM are typically performed in the marketing or sales function itself, with support from a data mining or statistical analysis group. Cooper et al. (2000), in a case of First America Corporation, described analytical CRM applications as including campaign and contact management, profitability analyses and analysis of customer preferences and profiles. The data in the data warehouse must not only be the type of data necessary to support these marketing applications, but the data must also be easily accessible by the marketing function. Prior implementation studies have offered the factors to investigate the change associated with technology adoption. In a study of 111 organizations, Wixom and Watson (2001) offered empirical findings impacting data warehousing implementations but not in a marketing context. Few researchers, with the exception of Cooper et al. (2000) and Haley et al. (1998), have investigated the implementation of data warehouses for the purposes of supporting specific marketing applications, such as analytical CRM, but from the point of view of upper management. While one qualitative study has focused on the data aspect of CRM implementation (Abbott et al., 2001), no major studies have investigated the implementation of data warehouses for the purposes of supporting marketing applications, such as CRM focusing on the needs of marketing managers. Thus, the general question this exploratory research was designed to answer was as follows: What organizational implementation factors are most important in explaining why marketing would not use a corporate data warehouse and its interface to the extent that it was expected to be used by that function for CRM purposes? The single case study method was used through the cooperation of a single health care payor that was a research partner in the ecommerce program at a southeastern university. This firm allowed the research team access to functional marketing, information systems and other managers that used or were expected to use the CDW in their job functions. A series of focus groups and one-on-one interviews was employed to answer the managerial question “Why doesn’t marketing use our corporate data warehouse

and what went wrong in our implementation process?” As a starting point, the research team examined prior implementation models and then developed questions based on one particular model. This paper describes the initial model, the focus group process and presents the results of the qualitative study, including a revised model.

The research method There are many systems implementation models in the information systems literature. As a starting point, the Payton and Ginzberg (2001) model, developed to explore the implementations of multiple health care information networks, provided a broad base from which to begin the analysis. The Payton and Ginzberg model, based on the diffusion work of Cooper and Zmud (1990), although not developed in the data warehouse context, does provide a broad perspective of adoption across organizations. This inter-organizational context where many organizations must work together is analogous to the case studied here, where one company is seeking to adopt a CDW across different functional areas. Additionally, the model offered a broad framework from which to investigate the data warehouse implementation from many perspectives in the organization, including organizational dynamics. The dependent variable in this model as shown in Figure 1 is the success of the implementation effort. Three factor clusters are defined: push/pull factors, behavioral factors and shared systems topologies (Payton and Ginzberg, 2001). Push or pull factors are elements that can influence an organization’s willingness to adopt a given technology, strategy, and/or change initiative. These factors include competitive pressures and perceived economic benefits from the system (Cooper et al., 2000). Behavioral factors in this model are those factors that stand to impact and/or influence stakeholders and include end-user support, organizational autonomy and control, as well as vendor and top management support (Wixom and Watson, 2001). Political factors are those factors that arise from conflicting personal and organizational objectives among stakeholders. Political factors will tend to impede rather than facilitate implementation progress. Shared or integrated systems topologies represent certain aspects of the infrastructure needed for a data warehouse. These factors include arrangements for cooperation and information sharing as well as for assuring information quality. Both elements of shared system topologies, information sharing and information quality were predicted to have favorable impacts on implementation progress. As the degree of information sharing among internal departments increased, the quality of information available was also expected to increase, thereby fostering successful implementation (Cooper et al., 2000; Wixom and Watson, 2001). Others (Wixom and Watson, 2001) offered the suggestion that implementation success impacts perceived systems success, which can be defined here as the quality of data warehouse and the data that is extracted from the system. This model would imply that information quality is a central measure of the success or failure of a data warehouse to sustain CRM initiatives. Although our results support the importance of data quality in CDW adoption, several other implementation factors are highlighted by this research in the marketing context. 238

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Figure 1 Implementation model

Method

were sufficient to elicit comments that related to all areas of the model. The questions were also broad and flexible enough to allow the team to uncover some additional constructs and, as will be seen, some unexpected results. All focus group sessions were recorded and transcribed by a professional writer on staff at the health care organization as well as a member of the research team. The research team member provided a transcript within 48 hours and the professional writer worked from simultaneous tape recordings. Names and titles were withheld from all transcribed documents when given to data coders. Followup interviews with top management and other key users were conducted for clarification. The research team analyzed the data in the transcripts and then developed coding dictionaries to capture the marketing and information systems-related constructs. The coding dictionaries (Appendix 2) were developed to capture the marketing and information systems constructs that would capture the essence of the responses to the questions in Appendix 1. Two independent coders were used and a simple percentage agreement among constructs was calculated initially. Next, the initial coding dictionary was refined and factors were eliminated and/or combined where appropriate. This new coding dictionary was given to three new and different independent coders for an additional analysis beyond simple percentage agreement. A coefficient of interrater reliability among the three different independent coders was calculated. To facilitate the calculation of

The model in Figure 1 was used as a starting point from which data were gathered from five two-hour focus group sessions with a large health care payor group. Sessions were held exclusively with either all marketing (users), all “power” users who were systems experts, or all information systems teams (service providers). Teams included current, soon-to-be and power users, data warehousing internal systems staff and middle management. The size of the groups were small, typically four or five members and lasted a full two hours each. This small group size, combined with one-on-one follow-up interviews where necessary, assured that all focus group questions would be addressed and that all members would have time to answer the questions. In addition, top management agreed not to attend the focus group sessions to avoid biasing responses. An experienced focus group facilitator, one of the team members, worked to elicit responses from all focus group participants. For the most part, participants were enthusiastic supporters of this research effort and had an interest in seeing the CDW succeed in the organization. Appendix 1 lists the questions that were asked of all focus group participants. Prior to using these questions in the focus group sessions, the research model was pre-tested via five one-hour interviews with managers from the health care organization. Meeting notes were analyzed and the team determined that the initial exploratory questions from the Payton and Ginzberg model 239

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interrater reliability, only three of the five focus group transcripts were analyzed (marketing managers, active marketing users and newly trained marketing users) and only the results of these three groups are reported below. These three specific transcripts were used to focus the analysis because these groups were the three groups composed solely of marketing personnel. The results of analyzing these three transcripts is summarized in Table I. To analyze the focus group data, the team adopted the analysis method prescribed by Yin (1994). This method involved looking for patterns in the data and making adjustments in the analysis accordingly. This flexible, interactive process allowed the team to change the implementation model based on emerged findings. For example, though the initial questions (Appendix 1) did not focus on trust and integrating marketing needs, these factors proved to be important in this case study context. The analysis meant that the model needed to be changed based on the patterns that emerged. To help explain these changes, it was then necessary to consult the relevant marketing literature. Scott’s kappa (also known as the bias-adjusted kappa or p) was calculated for interrater reliability. Lacking any a priori expectations of the marginal proportions, this method of calculation accounts for the possibility of chance agreement among coders. Although coding elements (categories) were established, the verbal contributions (focus group comments) were free to vary and “fall” into any cell within the coding table. p is not influenced by the frequency by which categories are used and is calculated as:

The interrater reliability results were calculated between coders 1 and 2 (0.689); coders 2 and 3 (0.472); and coders 1 and 3 (0.720) Overall, the mean kappa value is 0.627 and, given the typical 0 to 1.0 scale of reliability, demonstrates substantial agreement based on Scullen et al. (2003). This result would strongly suggest that the dictionary captures those factors impacting the initial research question: “Why doesn’t marketing use the corporate data warehouse?” These results are particularly strong given the exploratory nature of this research.

Findings The detailed results of the analysis of the three marketing focus groups using the coding categories shown in Appendix 2 are reported and summarized in Table I. Table I indicates that coders categorized a total of 441, most of which related to the significance of data quality (22.45 percent), ability to support specific marketing needs (20.63 percent) and trust (13.15 percent). Together, these three constructs constituted nearly 50 percent of the coded comments from the focus group transcripts and will be discussed in detail below. Much of the information systems literature, both academic and practitioner, has pointed to the criticality of the economic impact and costs associated with data warehousing implementations. These results show that only 3.17 percent of the comments in this study were concerned with economic factors. In addition, coded comments failed to support the significance of the internal IT support organization in adoption (4.08 percent). Data integration (shared systems topology in the original model) which was mentioned 10.3 percent of the time and data quality were the only two significant factors from the original model that were supported. While data integration is undoubtedly important in adoption, the three factors of data quality, trust and unmet marketing needs dominated these focus group discussions. Because these three factors accounted for 50 percent of the mentions and appear from the analysis to be related, the discussion of the findings focuses primarily on these factors. Our results indicate that the model for predicting the adoption of a CDW in a marketing context needs to look quite different from models in the information systems literature. Marketing managers and system users are not primarily concerned with broad economic factors nor with the level of systems support. Although the information systems model was a good starting point, a more realistic view of what might predict adoption of a CDW by marketing for CRM and other applications is represented in Figure 2. In this figure, the three major factors of quality, trust and understanding of marketing needs dominate the explanation of the adoption of the CDW.

kappa ðpÞ ¼ ðo 2ðe =ð1 2 ðe Þ; where Po is probability of observed and Pe is the probability of expected. Additional justification for p can be found in Currall et al. (1999) and Neuendorf (2002). While Currall et al. (1999) offered a framework for developing coding categories and Neuendorf (2002) illustrated the mechanics of the statistical kappa calculations, Scullen et al. (2003) offered guidelines for judging significance; these guidelines recommended the following ranges: 0.41-0.60 indicating a moderate agreement and 0.61-0.80 indicating substantial agreement. Table I Categories by total classification by coders by percentage of total comments Number ðn 5 441Þ 99 91 58 45 35 33 25 23 18 14 441

Percent 22.45 20.63 13.15 10.20 7.94 7.48 5.67 5.22 4.08 3.17

Category a

Data quality Ability to support marketing needs Trust Data integration Top management support Role of marketing in the organization Training End-user support Internal IT support Economic impact

Marketing needs and data quality The reason for the substantial disconnect between the organization and its marketing function in terms of the use of the CDW can be explained by the history of the CDW implementation in this particular organization. Part of the motivation in CDW development in this organization was to enable a single source supporting privacy, data management and reporting regulations. However, other parts of the organization had also looked to the data warehouse to solve

Note: a Intrinsic, conceptual, representational and accessibility dimensions

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Figure 2 Model as a result of qualitative focus-group research

In addition, these needs for external, demographic and descriptive data for the consumer market and Dun & Bradstreet company descriptive data for the commercial (B2B) applications which were missing from the data warehouse. Other missing data included information on former customers and prospective customers, neither of which are in the data warehouse. These data were in the system previously used by marketing. Focus group participants reported “reconciling” mainframe reports to the information from the data warehouse. In addition, overall quality issues were mentioned frequently, such as overall accuracy of the information and other dimensions of data quality. In fact, the general category of marketing needs included several categories that, after our initial analysis, also appeared to be strongly related to overall data quality dimensions (Wang and Strong, 1996). As can be seen from the coding dictionary in Appendix 2, by data quality the users meant data that were accurate, timely, easily accessible, easy to understand and believable, common ways of looking at quality from both the marketing (Parasurman et al., 1994) and information systems (Wang and Strong, 1996) literature. When users mentioned ease of use of the data warehouse interface in conjunction with the “data” itself,” these comments can be seen as analogous to accessibility dimension of quality as noted in Wang and Strong (1996). Users also mentioned that they needed other data that were not in the warehouse, concepts which relate to the accessibility dimension noted in Wang and Strong (1996). In addition, users expressed interest in having access to a data dictionary, the concept of access relates to the perceived ease of understanding of the data as an element of data quality as well as accessibility. Users needed a dictionary because when accessing the data did not have an idea exactly what data items meant. Without a knowledge of the data items the users could not use the data. Perhaps most importantly, users and potential users distrusted data extracted from the warehouse; lack of interest relates to the intrinsic dimension of quality known as believability (Wang and Strong, 1996). Because of the interrelationships between these concepts the revised model in Figure 2 also shows marketing needs to be correlated with data quality dimensions. Similarly, in Figure 2 trust dimensions are shown as correlated with needs understanding. It is certainly likely that the more marketing trusts that the organization works well and produced good quality underlying data, the more likely marketing will its needs are understood.

various managerial problems. Although the organization formed a cross-functional team, in the needs definition process marketing needs became less of a focal point of the CDW. As the implementation progressed, more emphasis was placed on financial and billing applications rather than marketing. Marketing’s unique needs in terms of analyzing past customer performance, incorporating outside data sources into its analyses, analyzing specific customer data and running targeted marketing campaigns, were not the needs of the underwriting, billing and other financial and strategic functions of the organization. As a result, as the focus group results reveal, when marketing was interviewed after implementation, the group was quite frustrated with both the warehouse and the data interface. In fact, the company was considering giving marketing access to the warehouse via mini “data marts” to facilitate an easier, more user-friendly GUI (graphical user interface) with quick response time and decision support functions. Marketing had actually possessed its own dedicated system before implementation and, as the following comments reveal, actually felt functionality was lost or difficult to get at with the CDW and its interface: All right, so we’re using less than ideal ways of measuring the effectiveness of those things right now, I would say. Because we don’t, I think, have the data or don’t understand how to use the existing data (from the warehouse) well enough to be able to get at it. This is a matter of trusting this data and its quality to make major business decisions and we are not there, yet (marketing manager). “What would you expect from [our] data warehouse?” I would say that you either looking to do one of a few things[sic]. That is, decrease your costs, increase your membership – increase or retain your membership. We cannot do this or it takes a LOT of work to meet our marketing needs (marketing manager).

Trust and data quality As with understanding of marketing needs, the element of trust in the data in the CDW is strongly related to the concept of data quality. Trust was not initially predicted as a success factor in the original model. Organizational trust and rust of the data in the warehouse emerged as significant factors in predicting whether users would use the data in the corporate data warehouse to perform CRM analyses (Figure 2). Schoorman et al. (1995) synthesized how trust had been defined among multiple disciplines including organizational development, psychology, organizational behavior and strategy. Notwithstanding the plethora of definitions, Schoorman et al. (1995) determined that several common

Marketers expected the interface to look like it had in training when a prepared dataset was used or to be similar to other packages that they used in their work, like SPSS. Marketers wanted “click and drag” and other systems features with which they were familiar from other marketing applications. Marketers participating in the focus group said they were less likely to use reporting tools (e.g. business objects) themselves and more likely to draw upon the expertise of local “power users.” These users had become internal experts on the CDW application and, as a result, were somewhat overworked in the organization. 241

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themes existed, namely: the willingness to take risks; and minimal presence of two parties – a trustor and a trustee. In a marketing context, the literature has specifically focused on trust in an organizational context, with organizations as trustor and trustee as the two parties necessary for trust to occur. Morgan and Hunt (1994) suggested the importance of trust and commitment in the development of long-term exchange partner relationships. Like much of the research in the area of relationship marketing, Morgan and Hunt’s (1994) work is based upon social relations theory. Just as two individuals need trust as the basis of an interpersonal relationship, so do two organizations (or in this case two units of the same organization) need to trust each other in order to develop a commercial relationship. Trust needs to be present in an exchange relationship, such as using information from a central depository like a CDW, for that relationship to function. In the context of marketing information use, trust is defined as a willingness to rely on an exchange partner in whom one has confidence (Moorman et al., 1992). In fact, Moorman et al. (1992) suggest that information supplier and information user relationships influence the extent by which “data” are used in decision making in marketing research applications. In fact, the situation studied here of the CDW implementation can be seen analogous to the marketing research situation studied by Moorman et al. (1992) with the internal information systems department as the information supplier and the marketing department as the information user. In this study, users mentioned two aspects of trust. One aspect of trust in this situation was organizational in nature and referred to the lack of established working relationships among functional areas and a lack of commitment to information sharing. Yet in the context of organizational trust, there is also the need for individuals involved in the commercial exchange, i.e. trust in the salesperson as well as the organization h/she represents. Ganesan and Hess (1997) have found that in exchange relations, buyers distinguish between both interpersonal and organizational credibility. In this research context, our preliminary analysis indicated that there was a level of trust between individuals working in the organization. Users reported a long-term social relation among functional areas (Appendix 2) but not established working relationships among functional area and no commitment to information sharing. In other words, employees trusted each other individually enough to interact on a daily basis but the organization did not necessarily operate with a high degree of trust. Because trust issues arose in this intra-organizational context, the marketing function was hesitant to use data prepared by the information systems function in the organization. In the language of organizational trust, marketing was unwilling to rely on IT as an exchange partner, in this case the exchange being marketing information prepared by another department. Another aspect of trust in adoption of the CDW uncovered in this study was trust in the underlying information in the shared system. This concept of trust in the underlying information in this shared system is related to the concept of data quality as well. Moorman et al. (1992) suggest that, although trust and data quality are separate, trust heightens the perception of data quality in our study context. Although this prior literature indicates trust is a prerequisite to quality, is it possible that quality might also signal trust in a system and a willingness to move forward in the relationship, or, in

this case, the implementation the data warehouse. Consequently, our revised model shows trust and data quality to be correlated. It is difficult to imagine a situation in this type of implementation where users would trust the data yet not use some aspect of the system. In fact, Moorman et al. (1992) also suggest that both well defined, pre-established relationships with high quality interactions and data quality define the degree of trust in the provider-user relationship.

Practical implications The chief contribution of this research is in identifying the major components of an overarching model to understand how a corporate data warehouse can be best implemented for use by marketing, particularly the factors of intraorganizational trust, trust in the data, data quality and an understanding of the marketing functions needs. While trust has long been considered a factor of importance in interorganizational relationships between marketing vendors and their customers, trust needs to be applied in the intraorganizational context to provide an understanding of which factors can facilitate success in the field of data warehouse applications for marketing. This study indicates that marketing applications must be considered carefully before the data is developed for a data warehouse if marketing is going to use the CDW for CRM and other marketing purposes. Marketing functions tend to use data that is in some cases different from the rest of the organization, including looking at past-customer data, lostcustomer data and outside information sources. Because marketing is driving the future of the organization through using a variety of primarily customer-based data sources and not reporting upon its past using financial information, the factors predicting success of marketing’s use of a CDW are different than the factors that predict implementation success for other types of systems applications. These findings have been presented to the top management at the health care organization studied. The organization had not previously considered the relationship between the quality and trust dimensions discussed herein and had not realized that marketing did not perceive its needs were being met. The organization is addressing these issues.

Research limitations and future research Recognizing the limitations in generalizability of this type of study with a single firm, a quantitative study of organizations using corporate data warehouses to support the marketing function is planned. This work suggests that more research be focused on the complex intra-organizational exchange relationships that stand to impact data warehousing implementations. In the future study, it would be expected that organizations successful in CDW implementation use by marketing would be characterized by highest perceived data quality and trust in these intra-organizational relationships. Just as trust is important in long-term social relationships between individuals, in the successful marketing implementation of data warehouse applications, a high level of intra-organizational trust and trust in the data itself should be expected. In addition, perceived high quality data would not be expected without trust; trust factors are expected to be correlated with various aspects of perceived data quality. 242

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Marketing would also be expected to perceive its needs have been met if there is trust as well as data quality. Another key contribution of this future research might be that the importance of perceived data quality and trust might be expected vary over the stages of the systems implementation (Payton and Ginzberg, 2001). Just as relationships form, grow and decline, the importance of organizational trust should change as intra-organizational relationships develop (Morgan and Hunt, 1994). This research suggests that data quality, meeting marketing needs and trust are correlated relationships. As the social context of the implementation evolves, perceptions of these key factors would also evolve.

Rigby, D.K., Reichheld, F.F. and Schefter, P. (2002), “Avoid the four perils of CRM”, Harvard Business Review, Vol. 80 No. 2, pp. 101-9. Romano, N. (2001), “Customer relationship management research: an assessment of sub-field development and maturity”, Proceedings of the 34th Hawaii International Conference on System Sciences, Big Island, HI. Schoorman, D., Mayer, R.C. and Davis, J.H. (1995), “An integrative model of organizational trust”, Academy of Management Review, Vol. 20 No. 3, pp. 709-34. Scullen, S., Mount, M.K. and Judge, T.A. (2003), “Evidence of construct validity of developmental ratings of managerial job performance”, Journal of Applied Psychology, Vol. 88 No. 1, pp. 50-66. Shaw, M., Subramaniam, C., Tan, G.W. and Welge, M.E. (2001), “Knowledge management and data mining for marketing”, Decision Support Systems, Vol. 31 No. 1, pp. 127-37. Starkey, M. and Woodcock, N. (2002), “CRM systems: necessary but not sufficient. REAP the benefits of customer management”, Journal of Database Marketing, Vol. 9 No. 3, pp. 10-22. Wang, R.Y. and Strong, D. (1996), “What data quality means to data consumers”, Journal of Management Information Systems, Vol. 12 No. 4, pp. 5-34. Wixom, B. and Watson, H. (2001), “An empirical investigation of the factors affecting data-warehousing success”, MIS Quarterly, Vol. 25 No. 1, pp. 17-41. Woodcock, N. and Starkey, M. (2001), “‘I wouldn’t start from here’: finding a way in CRM projects”, Journal of Database Marketing, Vol. 9 No. 1, pp. 35-44. Yin, R.K. (1994), “Case study research: design and methods”, Applied Social Research Methods Series, Vol. 5, revised ed., Sage Publications, Newbury Park, CA.

References Abbott, J., Stone, M. and Buttle, F. (2001), “Customer relationship management in practice – a qualitative study”, Journal of Database Marketing, No. 1, pp. 24-34. Cooper, R.B. and Zmud, R. (1990), “Information technology implementation research: a technological diffusion approach”, Management Science, Vol. 36 No. 2, pp. 404-20. Cooper, R.B., Watson, H., Wixom, B. and Goodhue, D. (2000), “Data warehousing supports corporate strategy at First American Corporation”, MIS Quarterly, Vol. 24 No. 4, pp. 547-67. Ganesan, S. and Hess, R. (1997), “Dimensions and levels of trust: implications for commitment to a relationship”, Marketing Letters, Vol. 8 No. 4, pp. 439-48. Haley, B.J., Watson, H. and Goodhue, D. (1998), “The benefits of data warehousing at Whirlpool”, in Khosrowpour, P. (Ed.), Annals of Cases on Information Technology Applications and Management in Organizations, Idea Group Publishing, Hershey, PA, pp. 14-25. Hochberg, A. (2000), Changing IT Priorities in the Year 2000, Gartner, Inc., Stamford, CT, available at: www. knightsbridge.com/big_data3.html#sources Kalakota, R. and Robinson, M. (1999), E-business: Road-map for Success, Addison-Wesley, Reading, MA. Moorman, C., Zaltman, G. and Deshpande´, R. (1992), “Relationships between providers and users of market research: the dynamics of trust within and between organizations”, Journal of Marketing Research, Vol. 14, August, pp. 314-28. Morgan, R.M. and Hunt, S.D. (1994), “The commitmenttrust theory of relationship marketing”, Journal of Marketing, Vol. 58 No. 3, pp. 20-38. Neuendorf, K.A. (2002), The Content Analysis Guidebook, Sage Publications, Thousand Oaks, CA. Parasuraman, A., Zeithaml, V.A. and Berry, L.L. (1994), “Alternative scales for measuring service quality: a comparative assessment based on psychometric and diagnostic criteria”, Journal of Retailing, Vol. 70 No. 3, pp. 201-30. Payton, F.C. and Ginzberg, M. (2001), “Interorganizational health-care systems implementations: an exploratory study of early electronic commerce initiatives”, Health Care Management Review, Vol. 26 No. 2, pp. 20-32. Reinartz, W., Krafft, M. and Hoyer, W. (2004), “The customer relationship management process: its measurement and impact on performance”, Journal of Marketing Research, Vol. 41 No. 3, pp. 293-305.

Appendix 1. Interview guide Push/pull factors: 1 What economic benefits is your organization anticipating (has experienced) as a result of data warehouse implementation? 2 Were there any costs to your organization as a result of participating in this effort? Do (have) the benefits outweigh costs? Explain. 3 How has the competitive environment influenced your decision to implement the data warehouse? Shared topology: 4 What types of information will be shared (are shared) among data warehouse users? 5 How (has) will information sharing benefit your organization? 6 Does the data warehouse provide the precise (e.g. content), timely, current, relevant and accurate information you need? Does the data warehouse provide quality information to facilitate your needs? If not, what is needed to improve information quality? 7 How has the data warehouse impacted (expected to impact) the quality of the information that you receive (will receive) and use to facilitate decision making? Behavioral facilitators: 8 What (has been) will be the role of the internal IT group (vendor)? 243

9 10 11 12

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What types of services/expertise has/should the IT group provided? How has (will) top management been involved in the implementation process? Who are the champions and what are their roles? What end-users are (will be) involved in the data warehouse implementation process? How was (will be) end-user support gained and assessed? How has (will be) departmental control and autonomy been impacted during the implementation process?

F. Top management support F1 F2 F3 F4 F5

Top management is not visible. Top management’s role is unclear. Top management fails to communicate the key mission and strategy. Top management is not committed to the implementation process. Top management is supportive (financially & in actions).

Appendix 2. Coding dictionary

G. Internal IT (information technology) support

A. Data integration (as impacting information sharing)

G1

A1 A2

G2

A3 A4

Need for standardized data definitions and structures. Need for agreed up definitions among diverse user groups. Continual use of Legacy Systems for source data prior to CRM initiative. Continual use Legacy Systems for sources data after the CRM initiative.

H. Trust H1

B. Training

H2

B1

H3

B2 B3

IT group is knowledgeable with respective to the technical application. IT group is not knowledgeable with respective to the business functions (e.g. marketing needs, examples).

Users not engaged in appropriate training based on job roles. Level of technical delivery is appropriate. Continual training throughout the implementation process.

H4 H5

There is not an established, working relationship among functional areas. There is a long-term social relation among functional areas (high-quality interactions). Users do not believe in the information shared and gathered from the system. Users are not willing to reply on data from system as shared by various departments. Lack of commitment to the information-sharing relationships.

C. Data quality C1 C2 C3 C4 C5

Data Data Data Data Data

are are are are are

not not not not not

accurate. timely. easily accessible. easy to understand. believable.

I. Ability to support CRM, marketing needs I1 I2 I3 I4

D. End-user support D1 D2

Use of power users (often too much emphasis on power users). Role ambiguity and conflict among new users and power users.

Requests for data take too long. Data analyses take too long. Support applications (business objects and SQL) are not accessible. Inability to support and/or perform segmentation, identification of profitable customers, prospects, differentiation, longitudinal analyses, etc.

J. Role of marketing in the organization J1 J2 J3

E. Economic impact E1 E2

Perceived benefits of the application are not tangible (e.g. ROI, payback period, rapid time to market). Application is expensive to implement yet useful.

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Lacks influence in the implementation process. Marketing needs are not a top priority. Other functional areas get IT and top management support before marketing (marketing requests are acted upon afterwards).

Creating digital value: at the heart of the I-E-I framework Tim Foster Division of Industrial Marketing and E-commerce, Lulea˚ University of Technology, Lulea˚, Sweden Abstract Purpose – The purpose of this study is to provide a better understanding on the use of web sites for creating value in industrial buyer-seller relationships. Design/methodology/approach – Through an extensive yet not exhaustive review of previous studies on business-to-business (B2B) web site development, the extranet level of a conceptual model (the I-E-I framework) is tested in an industrial setting in Sweden. Using four research questions as a guide, a qualitative, case study approach is followed in order to uncover both the industrial sellers’ and buyers’ perspectives on the true value of an industrial extranet. Findings – The findings show that, for true value to be created at this level, both the seller and the buyer must not only take value out, but also put it in. Value in this setting focuses on information as the heart of true value creation, and the view that the extranet can indeed be considered the “superglue” of such seller-buyer relationships. Research limitations/implications – Although the aim of qualitative research is rarely to generalize in any way, it does allow one to probe more deeply and uncover detailed clues and descriptions of what is happening in an area of research that is itself dynamic and constantly changing. What practitioners can take from this study is that extranets can be developed to serve and create true value at the (core) seller-buyer relationship. Originality/value – Empirical evidence regarding extranets in such settings has been limited. This study helps to fill this gap and provide a foundation for future research efforts within the area. Keywords Extranets, Worldwide web, Business-to-business marketing, Manufacturing industries, Buyer-seller relationships, Sweden Paper type Research paper

advent of e-commerce has examined the influence of the internet as an industrial communication tool. This study aims to make a contribution by filling in the gap that exists within the research area due to a lack of empirical evidence. Value is in part derived from technology, information, knowledge, and social interaction (Baker et al., 1998), all of which are key components of the internet. However, it must also be recognized that doing business in a digital world implies not losing site of the importance of coordinating online strategies with the ones used more traditionally offline by organizations (Porter, 2001). Sellers in B2B settings are embracing technology-mediated sales communication tools such as web sites to reach out to buyers (MacDonald and Smith, 2004). Sharma (2002) explains that if companies do not capture the value that emerging technologies such as the internet provide, then value will actually begin to migrate from their companies. To overcome this risk, Sharma suggests that firms develop an information platform that encompasses all of the functions of a firm and its partners (i.e. the network of organization including but not limited to suppliers, partners, and customers). The value of such an approach is in information exchange leading to a reduction in exchange friction. This will then allow for an increase in both the efficiency and effectiveness for firms in such a network of business relationships.

An executive summary for managers and executive readers can be found at the end of this issue.

Introduction Value creation in a digital world Information technology, and more specifically the internet, provides myriad tools for creating value in industrial, or in the wider context, business-to-business (B2B) settings (Vlosky et al., 2000; Berthon et al., 2003). In fact, we have entered an “era of value maximization” when it comes to the web in such B2B settings (Berthon et al., 2003, p. 560). Yet the concept of adding value has received little attention in the business marketing literature (Payne and Holt, 2001; Ulaga, 2001; Beverland and Lockshin, 2003), and even less when it pertains to creating value on (or using) the internet (Vlosky and Fontenot, 1999; Arnott and Bridgewater, 2002). Parasuraman and Zinkhan (2002) add that the need for more internet research from a B2B perspective is imperative, and that this technological revolution has transformed lives and the way we do business. Yet, according to DeeterSchmelz and Kennedy (2001), no empirical study since the The Emerald Research Register for this journal is available at www.emeraldinsight.com/researchregister The current issue and full text archive of this journal is available at www.emeraldinsight.com/0885-8624.htm

The value of long-term relationships Although it is recognized that little research has been done within the area of online value creation, scholarly research in B2B settings is focusing more and more on the importance of doing so, as this assists organizations in building and maintaining long-term relationships (Beverland and Lockshin, 2003). Even though relationships in B2B settings

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are often strained (Emiliani, 2003), technology is coming to the rescue and being used to create opportunities for organizations keen on becoming more effective and efficient in such relationships (Sahay et al., 2003). The use of technology to improve relationships between sellers and buyers, or in any relationship within an industrial network, is pushing organizations to take a more careful look at the use of their web sites in creating value for customers (Sharma, 2002), as well as other stakeholders in the value/supply chain network (Fink and Laupase, 2000). The supply chain today is seen as being an important element in the value creation process (McGuffog, 1997; Dawson, 2002), yet there is a “core” to this network: Ritter and Gemu¨nden (2003) present at the core of a network of innovation partners the focal company, surrounded first by suppliers and buyers, but then also co-suppliers, administration, consultants, competitors, and distributors. For Anderson et al. (1994), the “core” is in fact the buyerseller relationship, or what they refer to as the focal relationship. Surrounding this core relationship is a number of continuing dyads (business relationships) that connect into a larger business-to-business network. All of this adds up to an ever-changing value chain of inter-organizational relationships. Ulaga (2001) adds that one can investigate value creation at this core (seller-buyer) level from three different perspectives: The seller’s perspective, the buyer’s perspective, or from the seller-buyer perspective. From the discussion above, the purpose of this study is to provide a better understanding on the use of web sites for creating value in industrial buyer-seller relationships. In light of the above discussion and the research purpose that results from it, this article will focus on the use of web sites only and not broader internet or IT applications.

web sites. They found that wile organization of the web site was most important, nontransaction-related interactivity, privacy/security, and how informative the site was were also important. Of relatively little importance were factors such as transaction-related interactivity, personalization, and entertainment. Yet so many of these studies look at web sites as if there was a single layer, when there are actually three broad layers: First, there is the general (public) web site mentioned by Ling and Yen (2001), which can also be viewed as the “entryway” or online portal into the organization in cyberspace. Following this is the extranet level, often used for specific, pre-approved stakeholder groups, such as suppliers, partners and/or customers (Lamb, 2003). Finally, there is the innermost intranet level for employees within a specific organization (Ling and Yen, 2001; Lamb, 2003; Chaffey et al., 2003). In a study that looked at web site use from several of these perspectives, Hoey (1998) developed one of the first frameworks focusing on the use of web sites throughout a (virtual) supply chain in a B2B setting. Hoey showed that such a supply chain provides its members, through a web site, a framework where each member of the value chain not only provides but is also provided information through its own resources (information) and the resources of other members. Through this interaction, the web site provides a form of web connectivity. Sharma (2002) shows a similar internet connection between suppliers, the selling firm, and its customers, referring to it as a “common information platform” (p. 80). However, it was recognized that “web connectivity” according to both Hoey (1998) and Sharma (2002) meant that such a connection existed on only one level. Scholars such as Vlosky et al. (2000), Lamb (2003) and Chaffey et al. (2003), feel that different stakeholders within such a value chain require different access points at the internet (public), extranet (specific third parties, e.g. customers, partners, suppliers), and intranet (employeeonly) levels. By combining the work of Hoey (ibid.) and Chaffey et al. (ibid.), Foster (2004) developed a framework that looked at the use of the internet (specifically B2B web sites) from the perspective of all three levels across the entire value chain in what can be referred to as the I-E-I framework (see Figure 1). The I-E-I Framework can be investigated as a whole but, like an onion, can (and should) be peeled, level-by-level, and within each I-E-I level, layer-by-layer, focusing on the value created for stakeholders across the entire supply/value chain. This study will do just that, focusing on those parts of the framework shaded in grey in Figure 1, namely the extranet level and the use of it by a selling organization and its buyers.

Literature review The evolution of B2B web sites The design of B2B web sites is critical (Evans and King, 1999). More specifically, Shoemaker (2001) stipulates that relationships between sellers and buyers can actually be damaged by offering a poorly developed web site. According to Ling and Yen (2001), such sites have evolved from first being developed as general (public) internet web sites, moving on to include new levels, such as employee-only intranets. Not only are the web sites themselves evolving, but the B2B marketer is evolving right along with them (Sharma, 2002). One of the main opportunities with web site design according to Honeycutt et al. (1998) is with regards to how the company and/or product are communicated online. They found that one of the downsides of these B2B sites included the development of what can simply be viewed as dull (i.e. static) web sites. Yet little research has been done on establishing models and frameworks for maximizing the interaction between an organization’s web site and its stakeholders (Fink and Laupase, 2000). Many studies on web sites in B2B settings to date have focused on what type of content the site should have (e.g. Perry and Bodkin, 2000; Bauer and Scharl, 2000), the overall web site design (e.g. Lord and Collins, 2002; Kim et al., 2003) or the stages in its development (Arnott and Bridgewater, 2002). Only recently have studies started to look at what truly makes a B2B web site more valuable, such as Chakraborty et al. (2003), who asked customers what factors were the most important in using B2B

The use of extranets in B2B settings The development of extranet research has been limited at best, and the study of this level represents the next trend in internet research (Ling and Yen, 2001). This is not only due to the evolution of the area, but perhaps also due to “access” to such levels being an issue, as gaining access to such sensitive levels of an organization’s online efforts is no easy task. Access, according to Gummesson (2000), is of vital importance in management research. McCune (1998) recognized that very few companies even had extranets before the new millennium. Baker (2000) added that the use of extranets in B2B settings is basically overlooked and underused by most organizations, yet is one of the most 246

Creating digital value: at the heart of the I-E-I framework

Journal of Business & Industrial Marketing

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Figure 1 The I-E-I framework

marketing, product development, customer service, human resource applications, as well as financial applications. Starting in 2002, Sharma began to look more at “value” and extranets specifically from a B2B perspective. Taking an evolutionary perspective on the use of the internet in such settings, Sharma found that value will increase as the users of an extranet take a journey through various levels of extranet development: Starting with information, then communication, transactions, relationship marketing, and finally e-commerce. The flaw with this thinking is that “value” is only created if something is sold and purchased online, yet in many industrial settings, this is not possible. This is also contradictory to other scholars who feel that information is of much greater value compared to where Sharma places it: Freiden et al. (1998) state that information itself is a unique and important part of a new concept of “product”, which focuses on an equal integration of tangible good, services associated with, and information included in the “product”. Information, according to Walton (2000), will become the gold of the twenty-first century. Dubas and Brennan (2002) published research on the marketing implications of extranets and webcasting, but again the focus of the article was on the benefits that collaboration among extranet participants (including producers, suppliers, distributors, and customers) brings. It was at this juncture of the literature review that an important question arose: Is what the supplier or buyer receives in terms of “benefits” the only true measure of online value creation? Gummesson (2002) explains that the “value economy” of today means that, “suppliers both produce and consume value . . . and customers do the same” (p. 587). Phairor and Hanmer-Lloyd (2002) focused on the extranet and its profound impact on the way channel members communicate with one another, the value of which is in the improvement of the communication and in the overall relationships themselves (including the putting in of information in order to take it out). Metaphorically, they state that communication is the glue that holds a channel together. Could it be that the extranet has become the “superglue” of B2B relationships? Based on the aforementioned purpose of this study, along with the thinking of Phairor and Hanmer-Lloyd (2002) and Gummesson (2002), that value is created by both putting something in as well as taking something out, the following research questions emerge as being relevant for this study: . What is the value input to this online (extranet) environment by industrial sellers? . What is the value input to this online (extranet) environment by industrial buyers? . What is the value output taken from this online (extranet) environment by industrial sellers? . What is the value output taken from this online (extranet) environment by industrial buyers?

important strategic choices an organization can make. The early studies on extranets seemed to focus primarily on the benefits of developing and using one with business partners. McCune (1998) looked at cost benefits, as well as less tangible benefits such as helping customers help themselves and thereby deepening the ties between a seller and buyer. Anandarajan et al. (1998), also looked at the cost-related benefits of an extranet from a value chain perspective, noting that the adoption of an extranet by an organization aids it in three areas: Strategic benefits, tactical benefits, and operational benefits. Although the early studies made a contribution and pushed both scholars and practitioners to start thinking more about this increasingly important web site level, as we entered the twenty-first century, extranet research grew up. Vlosky et al. (2000) put it bluntly in the first sentence of their article on extranets and their impact on business practices and relationships in B2B settings: “Add value” (p. 438). Their overall conclusion was that companies can tailor technologies such as the internet to their own, unique needs, as well as the needs of others in the value chain. These scholars discussed not only the development of and benefits from extranet use, but went on to discuss the value of extranets in buyer-seller relationships and how they are actually used in such settings. Baker (2000) explained four keys to success in developing an extranet strategy in the form of four functions: First, extranets have always been (and always will be) about information sharing with suppliers, partners, and/or customers; the second function is that, beyond information sharing, an extranet could be used as a strategic form of communication between companies; the third function focuses on providing access to key information application processes (i.e. order entry and production tracking); the fourth function, and possibly most critical according to Baker, is overall security, or the ability to safeguard such information and the way in which it is communicated. From this, Ling and Yen (2001) weighed the advantages versus disadvantages of using an extranet, as well as the use (or applications) of them within sales and

Methodology A case study approach The methodology employed to collect the data to answer the research questions stated above was an in-depth, longitudinal, multiple-case study approach. This longitudinal approach is recommended by the authors of one of the more recent and extensive studies done to date on technology-mediated communication in a B2B context (MacDonald and Smith, 2004). Longitudinal research is also used when focusing on 247

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value creation in seller-buyer relationships (Beverland and Lockshin, 2003). What made this study longitudinal in nature was the fact that the data on the extranet (as well as other levels of the I-E-I framework in this context), was collected over a nearly one-year time period as a part of an ongoing series of research efforts focusing on peeling the I-E-I framework back, level-by-level, layer-by-layer. The use of case studies is a common approach in B2B research and has been used by various scholars looking at the various levels of web sites within such settings (e.g. Anandarajan et al., 1998; Yen and Chou, 2001). For the purpose of this study, an industrial company with an advanced extranet application was first identified, namely LKAB, a high-tech mineral/mining company in northern Sweden, one of the more advanced IT countries in the world (Deboo et al., 2003). In early contact with LKAB, a total of four buying organizations within the Nordic region in Europe (i.e. Sweden and Finland) were identified as companies with the only access to LKAB’s extranet. Of these four, two buying organizations, along with specific individuals in them, were identified by the sales manager (SM) at LKAB as the most extensive users of the LKAB extranet. The focus on buyers in such situations is of vital importance according to Beverland and Lockshin (2003), who state that to understand “value”, one must focus on the customer’s perspective and not only the seller’s. MacDonald and Smith (2004) support this by asserting that the consideration of buyer reactions to a seller’s implementation of technology-mediated communication is vital, as the use of such technology is especially important from a relationship perspective. Case 1 will represent the seller’s perspective of the extranet. Because such a selling organization has more than one customer, the customer perspective is represented by two of the four buying organizations mentioned above, namely SSAB Oxelo¨sund in Sweden (case 2), and Rautaruukku in Finland (case 3). These three case studies and the phenomena under investigation, as outline in the purpose, are depicted in Figure 2. In case study research, Yin (1994) explains that the use of multiple sources of evidence is very important in order to increase the validity of the findings. Data collection for these three case studies relied upon three sources of evidence: Observation of and interaction with the LKAB extranet; indepth interviews with those who used it (i.e. key informants within the selling organization and the two buying organizations), and documentation (in the form of anything written that pertained specifically to LKAB’s extranet and general web site strategies). Those specific individuals who were interviewed will be presented in the findings below. Interviews were conducted both in person and over the

telephone, with follow-up via e-mail and phone on several occasions.

The study Findings from the three case studies The findings from the three case studies will be presented following the value in – value out theme of the four research questions, first from the seller’s perspective (case 1) and then from the buyers’ perspective (case 2 and case 3). In order to gain access to LKAB’s extranet, contact was first taken with the vice president of public relations and quality (herein referred to as VP). Vlosky et al. (2000) used a similar strategy in B2B web site research, using e-mail to first establish contact with those in public relations and corporate communication positions in the selling organization. It was VP who presented and discussed all three levels of the I-E-I framework at LKAB, each level developed with certain stakeholders in mind: The internet (public) level focused on the general public and mass media; the extranet focused on certain customers; and the intranet on employees at LKAB. From this initial contact with VP, the sales manager for the Nordic region (herein referred to as SM) was made possible. Data from the sales manager in this case is also justified by Shoemaker (2001), who states that salespeople focus on building relationships that result in connecting customers through the use of extranets. Case 1: the LKAB extranet from the seller’s perspective The LKAB extranet was first entered and then experienced through a demonstration by VP, providing a broader overview of LKAB’s extranet within the entire I-E-I framework used within the organization. This was followed by a separate demonstration by SM, who provided a more specific and advanced understanding of what a customer actually experiences, which was important before actually talking to those in the buying side case studies. LKAB is primarily in the business of mining and selling iron ore in the form of pellets. Each order of pellets is unique in terms of its intended use, size, makeup, and quality. According to SM, who oversees much of this part of the organization’s online efforts, the LKAB extranet is all about giving their four primary customers the information (and interaction opportunities) they need, when they need it, and how they want it. The extranet was developed exclusively with these primary customers in mind. These customers were used early on in the extranet creation process as a sounding board and testing ground for online collaboration and the development of this level of LKAB’s I-E-I framework. The LKAB extranet efforts for its Nordic customers is not about “placing orders”, as iron ore cannot be bought, sold or shipped over the internet. Instead, other value-added efforts are being made and coordinated, both online and offline, to enhance the industrial seller-buyer relationship. As SM explained, “We are 98 per cent product flow, 2 per cent information flow”. He added, however, that the information is a vital part of the seller-buyer relationship and it is seen as a true value-added service. The key is being able to coordinate these onlineoffline efforts as a means for truly serving the customer. Everything that LKAB does for its customers online is based on what the customer has asked for. From their offline discussions with their customers, LKAB’s extranet was developed around three primary areas: Physical needs, IT

Figure 2 Overview of the case-study approach used for this study

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applications, and customer data. SM feels that what they make work within these Nordic relationships can be a means for possibly attracting new customers in the future, providing LKAB with a dual offline (the quality of their iron ore) and online (the value-added information services) competitive advantage. For their physical needs, LKAB has developed an offline form of value: “The Experimental Blast Furnace”. To process the pellets that LKAB sells, blast furnaces at steel plants are used to melt and develop the steel to be sold further sold to industries dependent on it. Shutting down a blast furnace to “test” something or even for routine maintenance is a costly and risky venture. A “miniature” version of an actual blast furnace was developed by LKAB to be able to run tests which relate to improving the effectiveness and efficiency of forging steel. Although LKAB sees the blast furnace as a “magnet” for both potential customers as well as a means for taking care of their existing customer relationships offline, their web site (online) is seen as a “magnet” for getting this part of the value chain involved in their extranet. They do this by (briefly) discussing the furnace and its potential to offer rich, customer-specific information at the public (internet) level of their main web site, lkab.com. According to VP, the problem with this being launched and used today revolves around online security issues: Each “test” of the blast furnace produces customer-specific data, and this information needs to be shared with that customer only. Although SM also sees incredible value being created by sharing information online via an extranet application, the security risks that both LKAB and its customers feel is always present prohibits this information from going online at the present time. Regarding IT applications, SM logged on and showed the depths of their extranet application as if he were a customer (an actual recent iron ore order was used as the example while we were online). It was explained that, from the customer’s perspective, the extranet is basically an order-tracking IT application, with certain features that are used to create value in the relationship for both sides throughout the respective selling and buying processes. After logging on, each customer will come to their own personalized “extranet” site. Once there, the customer can then click on “Delivery info”, “Contact info”, and “CRM”. SM explained that the speed and access to this information is of key importance to customers, and what they feel is lacking now is “one-click” access to the information they want. Once they click on any of these three areas, the customer is then able to go deeper into that area to interact, obtain information, and even supply information back to the LKAB. This includes several main categories from which to choose, including “subscribing” only to those value-added services they are interested in. This menu of choices includes “Delivery information”, which includes information on where the shipment is in the delivery process or the ability to change vessels to speed up the process; “Document services”, which offers risk analysis, protocols, PowerPoint presentations, and process overviews; “Remarks”, which is an area where the customer can leave complaints and other postings. SM feels that this is the most important part of the extranet, as it allows for a true, interactive service that provides information to and from LKAB and its customers. Finally, there is “Special info”, which allows for more group-oriented – i.e. multiple customers – to receive information of interest to all of them.

Regarding customer information, this is what SM feels will truly make a difference in allowing LKAB to use the extranet to provide customer-specific information to create true value. Here SM would like to allow LKAB to obtain real-time access to each customer’s data online in order to not only avoid problems, but take advantage of opportunities as they develop. This, according to SM is more of a future objective online rather than a current reality. Included in this future goal would be the ability to create online value in the form of data that originates from offline value being created through the use of a true competitive advantage for LKAB, such as the experimental blast furnace discussed earlier. Again, the sensitivity to such data and the security needed to keep it safe keeps LKAB from allowing such customer-specific information to be placed online at this time. Case 2 and Case 3: the LKAB extranet from the buyer’s perspective For each of the buying side case studies, SM provided specific names of those individuals he thought were relevant to start talking to, as they were identified as the main users of the LKAB extranet within the respective buying organizations. In each case, SM provided someone in an active purchasing role, as well as someone in a more technical non-purchasing role. In both cases, this could be seen as providing a perspective on the use of the extranet from someone in a pre-purchase position and someone in a post-purchase position. At SSAB in Oxelo¨sund, Sweden (case 2), the purchaser of raw materials, who negotiated the orders with LKAB and saw to it that LKAB delivered what they agreed to, was interviewed, along with another person more focused on post-purchase issues, namely the person in charge of raw material planning. The buying case at Rautaruukku in Finland (case 3) included the purchasing manager (pre-purchase) and the production manager (post-purchase). As was presented in analyzing the seller case data, analysis of the buyer side interviews also supports the idea that there is not only the value taken out of the LKAB extranet by buyers, but there is also the value they put in to it. In terms of the value they take from using the extranet, the primary value identified in both cases was time saved, which seems to be among their most important reasons for using the extranet. In both buying side case studies, saving time makes their work more efficient. Efficient for them implies a proper use of resources such as time, which also implies money and energy (i.e. work), as they are using such company resources to obtain and use the information they take out of the extranet. However, efficiency is only half the equation. They must also have the right kind of information, and this they feel they are getting when it comes to the IT applications made available by the extranet. Part of the right information comes from the information being more dynamic in nature. Examples of more dynamic data included being able to review a contract signed for a specific order with LKAB, being able to obtain information about the ore itself, as well as the logistics behind the actual shipment, including the ability to change vessels to get the order delivered faster or to avoid delays. Furthermore, in both cases, old data that used to be saved on their own computers or placed in paper form in an archive somewhere on their office shelves was now permanently available on the extranet, a service that was greatly appreciated. This implies that the extranet is also effective. This mix of increased efficiency (saved time, money, energy, 249

Creating digital value: at the heart of the I-E-I framework

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etc.) plus being effective (i.e. getting the right information in the right way) is perhaps where true buyer side value in B2B extranets resides. One interesting finding across both cases was that the prepurchase (i.e. both purchasing managers at each company) were more positive regarding the extranet, either in terms of specific features they liked and/or in being more likely to use it. The post-purchase (“technical”) buying team members seemed more negative towards its use: Either they used it less or found aspects they simply did not like. Some of this is based not only on preferring the “old way” of receiving information (i.e. over the telephone or via fax), but also in terms of the effort it took to obtain the information they needed. As one post-purchase buying team user of the extranet explained, the first IT efforts by LKAB were not extranet based, but instead relied upon the use of e-mail. Via e-mail, information about the ore and its shipment was sent regularly, meaning the person on the buying side got the information without having to request it or look for it once they received it. This meant they had to use only one click to open the e-mail before the data was in front of them. With the extranet, e-mail is used now only as a “warning” device that new information is available (click number one), followed by the need to log-on to their specific extranet site (which meant a second click plus filling in username and password info), followed by going to that part of the extranet where the shipping info they might be interested in resides (clicks three and possibly more). One suggestion was that a link within the e-mail being sent allows them to utilize an auto log-on to the extranet that takes them directly to specific types of information. The e-mail, in that sense was a “menu” of information that allowed, by one-click access, an auto log-on to the extranet and a route directly to that information they clicked within the e-mail. Yet value output (what the buyers take out of the extranet) was only half of it. In terms of value input, what buyers in this setting put into the extranet includes providing information and making known their extranet habits. These buyers are providing LKAB the potential to become more proactive in meeting their needs and solving their problems as customers, which in turn makes LKAB more efficient (use of resources) and effective (giving the customer what they want, sometimes before they realize they even need it). This can come in the form of eventually being able to have access to offline value being delivered online in the form of information about the results of tests on the experimental blasting furnace or getting the customer used to leaving more information in the “remarks” section, be it a suggestion, complaint, observation, or even a compliment. None of those interviewed in either buying side case study regularly used the “remarks” section of the LKAB extranet, hindering LKAB from not only getting the information, but using it to identify patterns of problems across all of its relationships, which would allow them to become more proactive. In the end, the use of the extranet by the buyers resulted in more satisfied customers through the value added services provided by the efficiency and effectiveness of the information obtained.

of previous studies on B2B web site development in general, and more specifically the use of extranets, four research questions emerged. These research questions provided a methodological foundation from which empirical evidence could be obtained from an industrial setting in Sweden. Using within-case as well as cross-case analysis (Miles and Huberman, 1994), findings were compared not only with the theory on extranets reviewed, but between the cases as well. From this, the following specific conclusions and implications for future research are provided. In general, access to the extranet was exclusive to those buyers geographically and culturally closest to the selling organization. It seems the farther away buyers were in the real world, the less access they had in the digital world of cyberspace, at least at the extranet level of this seller’s I-E-I framework. Of particular interest was the finding that within the buying organizations, there was more use (and therefore value) of the extranet by the pre-purchase member of the buying team versus the post-purchase member in that same team. There is not indication as to why this is, leading to the question, is it the role within the buying team that determines extranet use or is it the individual characteristics (i.e. background, personality, etc.) of the member within that team? This of course deserves more research. Value in-value out In order for a stakeholder to take out something of value from the (extranet) level they have access to, they must in turn put something in: For the industrial seller in this study, time, money, effort and talent are all a part of putting the valueadded service it provides to its customers. What the seller takes out is a more satisfied customer and the opportunity to become proactive in handling customer problems versus only reactive. The extranet is not the “crystal ball” they might want, but it’s the next best thing. In the end, the industrial selling organization gets out of their input an improved relationship with its customers in what is becoming an increasingly competitive environment. They are also able to better serve their customers’ needs while at the same time saving resources, as the speed to react to customer needs or problems is greatly increased via the use of the extranet. Industrial buyers also have value inputs into the extranet: Their use of the extranet provides the seller information through not only downloading order-specific information, but also other types of documentation that otherwise required them to save on their own computer or in a notebook on an office shelf. For industrial buyers, time, which they consider highly valuable, is not only put into using the extranet, but they also take out (i.e. save) time. In general, what industrial sellers get out of this extranet is the value of having the right information (current, order-specific information as well as historical data), at the right time (i.e. right now), and in the right way (never more than a few clicks away, with e-mail reminders of when new information is available, or perhaps in the future, via a web link directly from the e-mail with no logon necessary). Taking the portion of the I-E-I framework shaded in grey as presented earlier in Figure 1, namely the use of the extranet level of the framework by industrial sellers and buyers, the findings from the case studies presented above results in an online/offline value input-value output relationship between industrial sellers and buyers. The result of this is the

Conclusions and implications This article set out to provide a better understanding on the use of web sites for creating value in industrial buyer-seller relationships. Through an extensive yet not exhaustive review 250

Creating digital value: at the heart of the I-E-I framework

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development of a B2B online value-creation model shown in Figure 3. The “wedding band” visualization shown on both sides of the B2B online value-creation model above is no accident. It demonstrates that, as in other forms of legally-binding relationships (e.g. “marriage”), where a formal contract is put in writing and an informal one (trust) is often taken for granted, both sides of this relationship must work together and each should have something to offer if true value is to be created. The findings of this study indicate that both seller and buyer must, in order to take out value, collectively and/or individually provide it as well. The model also represents the importance of the link between the online and offline environments, supporting Porter’s (2001) contention that true value is created when integrating the internet into overall (including offline) strategy. The spiral effect of value emanating from both the online world and the offline world shows that the value input of the industrial seller becomes the value output of the industrial buyer, while the value input of the buyer becomes the value output of the seller. Such a spiral could also provide a basis for certain value inputs and outputs being preferred over others, as was found in this study. In support of Chakraborty et al. (2003), organization of the web site, nontransaction-related interactivity, privacy/security, and how informative the site was, were also important, whereas transaction-oriented interactivity and entertainment value were not. This also implies that the argument from Sharma (2002), i.e. that “information” was of the least value, needs to be reconsidered. Regardless of where one starts, be it with the selling or buying organization, and regardless of whether it is an input or output, the idea is simple: The more value that is provided and used between the seller and buyer, coming from both online and off, the more “true value” (seen at the heart of the model) is actually developed. What binds industrial sellers and buyers is metaphorically laid out by Phairor and Hanmer-Lloyd (2002): The extranet in this study can in fact be seen as the communication “superglue” that brings together and creates mutual value between both sides of this focal seller-buyer relationship, but only if both are willing to create value and not just become the beneficiary of it. The extranet is indeed the heart of the I-E-I framework. What remains to be seen is if this “super-glue”

holds for other relationships throughout the value chain network and within the other layers of the I-E-I framework. The future of extranets and the I-E-I framework The scholarly contribution of this article, as discussed above and resulting in the B2B online value-creation model, is of no use if it does not also somehow add something to those running (or considering to start up) an extranet as a part of their own corporate I-E-I framework development. What practitioners can take from this study is that extranets can be developed to serve and create value at the (core) seller-buyer relationship in such B2B settings. It can also serve to enhance other relationships with suppliers, partners, investors, etc. Yet it must be kept in mind, value is a two-way street: You get out what you put in. This of course deserves future research. There are more value inputs and value outputs to be discovered, discussed and debated, as this article only got things started. This look at the heart of the I-E-I framework, in this case the core industrial seller-buyer relationship, is but one example and is presented here as a starting point for future research. As all research should, it likely gives rise to more questions versus providing answers. Based on a qualitative, case study approach, limitations of course exist, the main one being the generalizabiltiy of the findings. Although the aim of qualitative research is rarely to generalize in any way, such research does allow us to go more in depth and uncover detailed clues and descriptions of what is happening in an area of research that is itself dynamic and constantly changing. Keeping up with it means taking a continual look at other extranet applications as they pertain not only to industrial seller-buyer relationships, but to other channel relationships as well, regardless of whether such relationships exist on the innermost intranet level, the extranet level, or the outermost (public) internet level. Other examples of and uses for the extranet level are out there and must be shared in order to gain a continuing understanding of how the internet is used as a marketing (communication) tool to create value for all stakeholders in this ever-changing digital world we live in.

References Anandarajan, M., Anandarajan, A. and Wen, H.J. (1998), “Extranets: a tool for cost control in a value chain framework”, Industrial Management & Data Systems, Vol. 98 No. 3, pp. 120-8. Anderson, J.C., Ha˚kansson, H. and Johanson, J. (1994), “Dyadic business relationships within a business network context”, Journal of Marketing, Vol. 58 No. 4, pp. 1-15. Arnott, D.C. and Bridgewater, S. (2002), “Internet, interaction and implications for marketing”, Marketing Intelligence & Planning, Vol. 20 No. 2, pp. 86-95. Baker, M.J., Buttery, E.A. and Richter-Buttery, E.M. (1998), “Relationship marketing in three dimensions”, Journal of Interactive Marketing, Vol. 12 No. 4, pp. 47-62. Baker, S. (2000), “Getting the most from your intranet and extranet strategies”, Journal of Business Strategy, Vol. 21 No. 4, pp. 40-3. Bauer, C. and Scharl, A. (2000), “Quantitative evaluation of web site content and structure”, Internet Research: Electronic Networking Applications and Policy, Vol. 10 No. 1, pp. 31-43. Berthon, P., Ewing, M., Pitt, L. and Naude´, P. (2003), “Understanding B2B and the web: the acceleration of

Figure 3 Creating digital value in industrial seller-buyer relationships

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Lord, K.R. and Collins, A.F. (2002), “Supplier web-page design and organizational buyer preferences”, Journal of Business & Industrial Marketing, Vol. 17 Nos 2/3, pp. 139-50. McCune, J.C. (1998), “The ins and outs of extranets”, Management Review, Vol. 87 No. 7, pp. 23-5. MacDonald, J.B. and Smith, K. (2004), “The effects of technology-mediated communication on industrial buyer behavior”, Industrial Marketing Management, Vol. 33 No. 2, pp. 107-16. McGuffog, T. (1997), “The obligation to keep value chain managements simple and standard”, Supply Chain Management, Vol. 2 No. 4, pp. 124-33. Miles, M.B. and Huberman, M.A. (1994), Qualitative Data Analysis, 2nd ed., Sage Publications, London. Parasuraman, A. and Zinkhan, G.M. (2002), “Marketing to and serving customers through the internet: an overview and research agenda”, Journal of the Academy of Marketing Science, Vol. 30 No. 4, pp. 286-95. Payne, A. and Holt, S. (2001), “Diagnosing customer value: integrating the value process and relationship marketing”, British Journal of Management, Vol. 12 No. 2, pp. 159-82. Perry, M. and Bodkin, C. (2000), “Content analysis of Fortune 100 company web sites”, Corporate Communications: An International Journal, Vol. 5 No. 2, pp. 87-96. Phairor, K. and Hanmer-Lloyd, S. (2002), “Rethinking channel communications: an emerging role for the extranets within distribution channels”, Marketing Theory and Applications, American Marketing Association, Winter 2002 Educators’ Conference, Vol. 13, pp. 16-22. Porter, M.E. (2001), “Strategy and the internet”, Harvard Business Review, Vol. 79 No. 3, pp. 63-77. Ritter, T. and Gemu¨nden, H.G. (2003), “Network competence: its impact on innovation success and its antecedents”, Journal of Business Research, Vol. 56, pp. 745-55. Sahay, B.S., Cavale, V. and Mohan, R. (2003), “Insight from industry: the ‘Indian’ supply chain architecture”, Supply Chain Management: An International Journal, Vol. 8 No. 2, pp. 93-106. Sharma, A. (2002), “Trends in internet-based business-tobusiness marketing”, Industrial Marketing Management, Vol. 31 No. 2, pp. 77-84. Shoemaker, M.E. (2001), “A framework for examining ITenabled market relationships”, Journal of Personal Selling & Sales Management, Vol. 21 No. 2, pp. 177-85. Ulaga, W. (2001), “Customer value in business markets: an agenda for inquiry”, Industrial Marketing Management, Vol. 30 No. 4, pp. 315-19. Vlosky, R. and Fontenot, R.J. (1999), “Learning to love extranets”, Marketing Management, Vol. 8 No. 3, pp. 33-5. Vlosky, R.P., Fontenot, R. and Blalock, L. (2000), “Extranets: impacts on business practices and relationships”, Journal of Business & Industrial Marketing, Vol. 15 No. 6, pp. 438-67. Walton, P. (2000), “Isolation and professional adaptation”, 10th IAALD World Congress, Dakar, 24-28 January, available at: www.iaaldcee.hu/dakar2000/papers/walton. html (accessed 15 October 2004). Yen, D.C. and Chou, D.C. (2001), “Intranets for organizational innovation”, Information Management & Computer Security, Vol. 9 No. 2, pp. 80-7. Yin, R.K. (1994), Case Study Research, Design and Methods, Sage Publications, Thousand Oaks, CA.

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The size of the opportunity to reduce customer-service costs, because customers can serve themselves, was the third most important determinant of the overall judgement about the internet. The firms that saw the internet as a major opportunity were operating in market environments that were especially conducive, and were better equipped to exploit the opportunities than their rivals. Firms seeing the greatest opportunity in the internet as a tool for strengthening customer relationships were much better than their rivals at managing customer relationships generally, and had a lower market share rank, which suggests that smaller firms see the internet as a way to add another channel to reach their customers and close the gap with larger rivals that have broader channel systems. The authors believe that most firms will not realize the expected benefits of the internet. The gains will mainly go to firms that were already good at forging close customer relationships. These leaders were able to anticipate earlier how to use the internet to connect with customers, exploited it faster and implemented the initiative better. At the peak of internet enthusiasm, extravagant pronouncements were made about the possibilities for reverse auctions, open exchanges, buying groups, infomediaries and name-your-own-price models. But the authors’ research confirms that these models have limited or negligible roles in most markets. The internet is more than an additional channel to reach customers. When used creatively, it enhances all the other channels. For example, call-centre employees with net-based customer relationship management systems deliver better service, bricks-and-mortar stores using location-based services are found by more customers, and sales people equipped with mobile devices have more information and tools available during their sales calls. Firms need to synchronise the various channels. Customers pick the channel that is most convenient or effective for the situation, and assume that the firm will recognize them at each step of the way. Companies should therefore ensure that when, for example, a customer places an order over the internet the call-centre records are updated, that inventory information is consistent across the channels and that they can return goods to the store. Firms should assess what target customers want from the channel system, then work back to assess how well the current channels meet those needs. Internet technology is only a tool. Firms need to know how well their internet capability compares with that of their rivals. Companies should therefore ask their best and most demanding customers for a frank assessment. Firms should assess the quality of their present customer relationships and judge whether internet-enabled services based on new market models will strengthen or undermine existing relationships. Deploying internet and customer relationship management technologies successfully is more about organizational alignment than database management, systems integration and software selection. Internet-enabled customer relationship management has to be managed as a crossfunctional initiative that deepens overall capability. It will take strong leadership – including the assignment of a senior manager to spearhead the initiative, cross-functional structures and collective incentives – to motivate functions to work together and ensure a return on investment in technology.

Executive summary and implications for managers and executives This summary has been provided to allow managers and executives a rapid appreciation of the content of the articles. Those with a particular interest in the topic covered may then read the article in toto to take advantage of the more comprehensive description of the research undertaken and its results to get the full benefit of the material present.

Capitalizing on the internet opportunity Opinions about the impact of the internet of customer relationships have evolved over the last 15 years. The prevailing view in the 1990s was that the resulting market transparency would shrink margins and reduce customer loyalty. As firms gained experience with the internet, some replaced their anxiety with enthusiasm over the possibilities for cutting customer service costs while tightening connections with customers. The main view today seems to be that digital technologies – and especially the internet – offer only limited advantages because the applications are readily copied. Day and Bens surveyed 165 senior US marketing, sales and management information systems managers on the impact of the internet on their ability to manage customer relationships. The research reveals that a quarter of the managers saw the internet as a major opportunity and only 1 per cent viewed it as a major threat. A further 57 per cent saw the internet as a minor opportunity and 13 per cent said it was neither an opportunity nor a threat. Overall, the internet was judged to offer opportunities to reduce customer service costs, while tightening customer relationships by encouraging dialogue, linking more parts of customer contact and facilitating the personalization of communications. Fears of channel conflict, price wars and new business models disrupting their markets were overshadowed by these opportunities. Firms in business-to-business markets appear to believe that the internet will enable the customers they do not currently serve to find them more easily, and then they have a good chance of being chosen on their merits. At the same time, they have confidence that their current customers will stay with them even after having considered new sources. Between 32 and 43 per cent of all business-to-business respondents to the Day and Bens survey saw major opportunities to encourage customer feedback and dialogue, facilitate linking more points of customer contact and make it easier to personalize marketing messages. For some firms, the personalization of interactions and communications is a step on the road to using the internet to help customers to design products to their specific requirements. However, only 14 per cent of respondents saw such “mass customization” as a major opportunity, while 35 per cent viewed it as a minor opportunity. Journal of Business & Industrial Marketing 20/4/5 (2005) 253–259 q Emerald Group Publishing Limited [ISSN 0885-8624]

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The role of information technology in supply-chain relationships: does partner criticality matter?

Collaborative supply-chain partnerships built upon trust and electronically mediated exchange

Kim et al. explore the role of information technology in channel relationships and company performance in the context of supply chain communication systems – the information systems that link channel partners in order to carry out such supply chain activities as electronic transactions, quality and cost calibration, and collaborative forecasting and planning. The study explores: . whether, and in what way, a firm’s adoption of advanced technology influences its own and its partner’s coordination activities; and . how IT adoption for supply chain communication systems influences market performance through enhanced channel capabilities of the firm and its partner.

In order to emphasise core skills, companies assume narrow and specialised roles in supply chains while they ally themselves with supply chain partners, who have complementary skills, for mutual benefits. Collaborative supply chain partnerships have become the critical linking pins as higher degrees of specialisation have brought an increased need for integration across the overall supply chain. When constellations of organizations in one supply chain deliberately collaborate, they can out-compete other, less collaborative supply chains. Trust is a key partnership characteristic that fosters collaboration. For example, a buyer and supplier who trust each other are more likely to share detailed cost breakdowns. Open access to such information enables partners to identify and manage inefficiencies and potential redundancies and reduce the total costs incurred in supply chain relationships. But trust alone is not sufficient. Mechanisms must also be in place so that information can readily be exchanged among the partners. One such mechanism is electronically mediated exchange, where partners communicate through electronic media such as the internet, intranets, electronic mail or electronic data exchange. Electronically mediated exchange is particularly helpful for people at the operational level who need up-to-date information in order to carry out their roles in supply chain relationships. However, to some degree, it is the process of information exchange and not the content of the exchange that is important. Trust is based, in part, on the seamless and accurate exchange of information. Nothing replaces personal interaction in the early stages of relationship building. At the same time, electronically mediated exchange and its technology should be seen as enablers and complementors. Through research involving 157 supply chain relationships drawn from international subsidiaries of Nordic multinational companies, Myhr and Spekman find that both trust and electronically mediated exchange foster collaboration. Trust seems to establish a base-line level of collaboration that is enhanced and reinforced through the use of electronically mediated exchange. The research also indicates that electronically mediated exchange more readily enhances collaboration in exchange relationships involving standardized products, while trust seems to play a larger role in fostering collaboration when customized products are being exchanged. Supply chain relationships transacting standardized products require frequent information exchanges because of the typically high volume of goods being transacted. Also, much of the information exchanged in such supply chain relationships is routine in nature and neither complex nor sensitive. Both high frequency and routine-type information exchanges can be conducted by electronically mediated exchange. While trust, in these cases, is not harmful, it is not really necessary given that routine information shared with the other company tends not to be of a sensitive nature. However, the exchange of customized products is a complex and idiosyncratic process, typically requiring partners to share critical and sensitive information across organizational boundaries. This is something only trusting partners would be willing to do.

By IT adoption is meant how actively a firm seeks to adopt new technology ahead of its rivals. Company co-ordination is the extent to which a firm co-ordinates transactions with channel partners efficiently. Partner co-ordination deals with how far the channel partner of an IT adopting firm carries out co-ordination activities efficiently. Market performance is assessed by sales growth, market share, market development and product development. The study reveals that IT adoption for supply chain communication systems enhances co-ordination activities within the supply chain. IT adoption has a positive impact on the firm’s own co-ordination as well as the co-ordination activities of its partner. Supply chain members improve their productivities by investing in IT. The study further suggests that improvements in the firm’s co-ordination stemming from IT adoption do not lead to better market performance. The linkage can be established only when IT adoption is linked to market performance through partner co-ordination. Enhancement of coordination activities in one member firm does not promise a real improvement of interfirm co-ordination in the supply chain until accompanied by improvement in the co-ordination activities of its partners. When the partner is critical to the success of the firm, enhancements in its interfirm co-ordination activities with the partner affect market performance positively. But when the partner is not critical to the success of the firm, such enhancements in co-ordination activities do not influence the market performance of the firm. In contrast, improvement in the co-ordination activities of a partner that is critical to the success of the firm does not influence the market performance of the firm positively. Only that of a less critical partner affects the market performance of the firm positively. The reason that enhancements in the co-ordination activities of a critical partner are not helpful to the firm may be that high partner criticality makes the firm highly dependent on the partner, causing an imbalance of power. Against this background, enhancements resulting from IT adoption may not feed through to enhanced market performance, as the partner shifts the distribution of additional value created by IT adoption in its own favour, taking full advantage of its relatively important position.

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Also, trust makes it more likely that the receiver of the information finds it credible and acts upon it in a collaborative manner.

opportunities that arose or were presented to them to take advantage of website technology – particularly services offered by information technology or software developers.

Critical factors affecting intermediary web site adoption: understanding how to extend e-participation

Cooperative adoption of complex systems: a comprehensive model within and across networks

Increased business efficiency, enhanced information flows, improved transaction speed, wider geographical spread, increased temporal reach, cost reduction and competitive differentiation for e-enabled constituents result when the members of a supply chain are able to share information, to buy, sell and distribute products or services and to transfer cash flow online. A key element is the company website, which typically combines sales and marketing functions. Intermediary websites provide a key interface between the supplier and the marketplace. Consequently, adoption and use of websites by intermediaries can benefit an extended supply chain. Harrison and Waite examine intermediary e-commerce development in the context of UK independent financial advisers involved in the distribution of medium and long-term investment products. The research focuses specifically on the adoption and use of websites, the factors influencing initial adoption, the characteristics of adopters and the patterns of website use. Firms were classified into categories based on the number of years the company had possessed a website: innovators (between seven and ten years); early adopters (at least five years but less than seven years); early majority (at least three years but less than five years); late majority (less than three years); and laggards (currently developing a site). The research reveals that innovators and early adopters tend to be mainly the larger firms with larger turnovers. Small and medium-size firms – which make up a large proportion of the financial intermediary sector – may lack the resources to set up and maintain their own websites. Moreover, due to the size and degree of fragmentation of the financial intermediary market, product providers have tended to develop relationships with a number of preferred intermediaries, developing proprietary technology and networks. This tailoring of developments to typically larger organizations could be a barrier to e-market participation for smaller firms. Innovators and early adopters are more likely to have a clearer reason for developing a website and are making most advanced use of it. None of the innovators in the research uses the website purely as brochure-ware and 44 per cent offer clients the opportunity to apply for and/or buy products online. The early adopters and early majority show a greater propensity to use the website for providing product information, whereas the late majority show a greater propensity not to provide any products on the website, suggesting the greatest likelihood of using the web as a brochure or static advertisement. Innovators’ and early adopters’ website adoption tends to be planned and deliberate, consistent with the overall business strategy. These factors have obvious benefits for both suppliers and customers. The early majority are mainly influenced by the actions of competitors and appear to be operating a “copy cat” strategy. The late majority and laggards are mostly influenced by

As industry rapidly moves toward a networked economy, cooperation among individual firms involved in overlapping network relationships is critical for success. Companies accustomed to competition need guidance on how to incorporate co-operative strategies into their internal operating procedures and their external relationships. Hausman et al. develop a model delineating the main factors that could influence the decision to adopt interorganizational systems (IOS) innovations across a range of variables. IOS systems such as electronic data interchange, enterprise resource planning and vendor managed inventory, which act as electronic information conduits between partners, commonly include hardware, software, network facilities, procedures and rules, data and databases, plus knowledge exchange. They therefore involve major changes in the way individual firms operate, with the requisite adoption extending to encompass other networked firms. Most researchers have mainly focused on evaluating a few variables that affect the adoption of specific technologies by a single firm or consumer. Hausman et al., in contrast, focus on the factors that might shape co-operative adoption in a network context. The study draws managers’ attention to inter-organizational influence factors, as well as relational factors under their direct control. In addition, strategies for dealing with structural factors, over which they have little control, are presented. In terms of structural factors, the authors put forward the following propositions: . Larger networks have a lower propensity to adopt an IOS innovation than smaller networks. This is because, in large networks, where firms are likely to be involved in overlapping networks, firms facing adoption decisions would have to weigh the potential operational and relational benefits of adoption against the complexity of maintaining multiple systems. . Networked organizations offering a smaller amount of product variety or a very large amount of product variety will have a lower propensity to adopt an IOS innovation than organizations offering intermediate levels of product variety. The authors explain: “At relatively low and high levels of variety, adoption is negatively impacted, first due to an inability to capitalize of economies of scale, then to the size and overlap of networks required to provide for the variety. In the middle, variety does promote adoption due to favourable economies, without requiring networks that are too large or overlapping to function effectively.” . The rate of adoption of IOS innovation by a network will be positively related both to the degree of organizational readiness in member firms and to the extent of their partners’ experience with the specific IOS innovations. . The rate of adoption of an IOS innovation by networked organizations will be positively related to the value the recipient firms anticipate from the innovation. 255

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The partners not only sat on the project steering group, but also were involved in building relationships with SMEs in their local area. The six partners therefore played a role in the network of partners (facilitated by the business school) and the network of local SMEs (which each partner was responsible for facilitating). Although the proposition for the project was e-learning for SME managers, the unit of analysis of Houldsworth and Alexander was the network of steering group partners. The project developed a web infrastructure to support online collaboration between the partners. But this web infrastructure was little used, despite the fact that the project was about e-learning technologies. The partners instead tended to achieve collaboration through meetings of the project steering group, with e-mail communication in between and some occasional video-conferencing. In addition, some steering group members had their own preexisting relationships and used face-to-face conversations either outside the formal steering group meetings or on other occasions when they met for different projects or reasons. Houldsworth and Alexander collected data through interviews with project partners and through observing the steering group meetings. The ESeN network reflected an international interorganizational network. It became evident during steering group meetings that participants from some nationalities (for example, the Scandinavians) and from some organizations and functions (for example, people involved in scientific fields) were more at home than others with collaborative working. The non-academic partners sometimes showed frustration around what they perceived to be ongoing “academic concerns” and felt that they occasionally had to provide the “real world” insight. They were keen to ensure that the proposed programme for SME managers maintained an action learning element and that this was flexible so that it could be tailored to local business needs in the host country. There were some stormy exchanges in one of the steering group meetings, which were to an extent relieved by the deliberate social events scheduled into the meetings. All the interviewees mentioned the need for a common interest or shared task or goal to support the network. However, observation of the steering group suggested different agendas at play. In the early stages of the project, only the co-ordinator of the partners appeared aware of their dependency on the others to deliver the contract. A lot of early energy was devoted to building a positive attitude and team spirit. But observation of the steering group revealed certain frustrations for all parties as the project progressed. Defensive feelings, if not mistrust, became apparent. All the interviewees seemed to acknowledge that a network is not self-sustaining and strong facilitation is needed. The coordinating partner seemed to lack this influence in the early stages and attempts to be highly participative and democratic had only limited success. The use of a more direct approach appeared to lead to greater collaboration and the generation of outputs. The ESeN project was an example of learning within a network, where the individual was interacting and learning within an inter-organizational context. The project was not an example of network learning, as there was no evidence of the network itself learning and changing.

In terms of inter-organizational influence factors the authors put forward the following propositions: . The rate of adoption of an IOS innovation by networked organizations will be positively related both to communication between the focal and recipient firms and to their participation in the adoption decision. . The rate of adoption of IOS innovation by networked organizations will be positively related both the presence of an innovation champion within the organization and to the extent of social ties between the focal firms and the recipient organizations. In terms of relational factors, the authors put forward the following propositions: . The rate of adoption of IOS innovation by a recipient firm will be negatively related to the use of power by the focal alliance. . The rate of adoption of IOS innovation by a recipient firm will be negatively related to the dependence between the focal firm and the recipient firm. (Some prior researchers have found a negative relationship between dependence and adoption of innovations, while others have found a positive relationship.) . The rate of adoption of IOS innovation by an organization will be positively related to the degree of entrenched trust between the recipient firm and other networked firms. The authors focus on social variables that appear to be critical in encouraging co-operation, since “bureaucratic governance mechanisms. . .are fundamentally absent from network relationships”. In particular, the authors believe that open communication helps to build trust and social ties and generates social capital to facilitate co-operation and empower champions. Hausman et al. conclude: “In dealing with these factors, it appears that firms must first establish a supporting organizational culture, since it seems implausible that firms can act co-operatively in their inter-organizational encounters and bureaucratically in the intra-organizational relationships. Specifically, firms must establish good internal lines of communication that rely on encouraging employees to work co-operatively toward mutually beneficial goals and build strong internal relationships among departments and their employees.” Obviously, the relationships proposed by the authors now need to be tested empirically.

Inter-organisational collaboration for the digital economy Houldsworth and Alexander report on a project, funded by the European Union e-Learning Action Plan, which revolved around the creation of a European small and medium size enterprise e-learning network (ESeN). The project sought to engage with SMEs in order to equip them with emerging knowledge management tools, so that they may become more effective users of information and communication technology in their decision making. The project involved a business school as the main partner, with collaborators from six EU countries, comprising a mixture of academic and business partners, all of whom were experienced in the use and application of virtual technologies. 256

Executive summary and implications for managers and executives

Journal of Business & Industrial Marketing Volume 20 · Number 4/5 · 2005 · 253 –259

An empirical framework developed for selecting B2B e-business models: the case of Australian agribusiness firms The internal and external factors affecting how Australian agribusiness organizations choose an e-business model are considered by Ng. He also explores how the organizations behave in their choice of e-business models for conducting business-to-business e-commerce. The ten business-to-business e-business models are: 1 Online storefront, a supplier-centric model that: is usually operated by wholesalers and retailers over the internet; allows the provision of updated information on products and services; and has the ability to instigate immediate business transaction. 2 Manufacturer, another supplier-centric model that: permits manufacturers to reach buyers directly through the internet; involves a major supplier providing its products and services to potential buyers via the internet; but has the potential of creating conflicts in a manufacturer’s supply chain. 3 Buy-side, a buyer-centric model that: involves a major buyer seeking products or services from potential suppliers via the internet; encourages potential suppliers to initiate business relationships by approaching the buyer; and enables buyers to reduce their costs by enabling them to view the list of products or services being offered to them. 4 Distribution portal, a supplier-centric model that: collates a few major suppliers who then sell their products or services as a group, to a set of potential buyers, via the internet; enables selling organizations to cut the cost of sales through more efficient order processing and tracking of order changes; and is attractive to buyers because it enables them to make several purchases from a group of suppliers that offer a range of related products or services. 5 E-speculator, a buyer-centric model that: enables organizations to gain real-time information that can be transferred into competitive advantage among a large group of buyers; and seeks to capitalize on a large quantity of market information, such as pricing. 6 Mega-exchange, a model that is neutral between supplier and buyer and that: acts as a central trading hub to facilitate transactions between buyers and suppliers; is usually run by third-party market makers, where it gathers buyers and suppliers to enable efficient trading between them. 7 Procurement portal, a buyer-centric model that: brings a few buyers together to purchase products or services as a group from a set of potential suppliers via the internet; and enables buying organizations to gain economic benefits such as bulk discount. 8 Sell-side asset exchange, a supplier-centric model that: enables trading, swapping and reselling of orders among a closed group of suppliers; requires strong relationships within the supplier community; and depends, for its success, on the ability to swap and resell orders efficiently within the group of suppliers. 9 Solution provider, a model that is neutral between supplier and buyer and that: is intended to embed unique and valuable services to the product sales;

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enables organizations to leverage their distinctive expertise in specific areas; and provides the opportunity to capture niche markets that have regarded value-added services as being more important than price in the buying decision. Specialist originator, a buyer-centric model that: seeks to standardize and automate the buyer decision-making process for more complex products; aggregates complex products and bundles them into larger order requests, then sends the transactions to the exchanges for execution; and requires organizations to have a good understanding of issues related to customer decision making and to be committed to providing real-time support for online customers.

Ng reveals that the internal influencing factors regarded as important by Australian agribusiness organizations in the selection of business-to-business e-business models are: the resources available; target market segment and market scope; nature of products or services; technological infrastructure and knowledge; understanding of e-business models; organizational structure and culture; and types of business strategy. The external influencing factors are: strategic partners’ influence; type of industry; competitors’ influence; and market trends. The research reveals that, in general, the internal factors appear to be more influential than the external factors. Ng’s research shows that, among Australian agribusinesses, the procurement portal, manufacturer, mega-exchange, online storefront and distribution portal models appear to be commonly used. In contrast, the e-spectator, solution supplier, buy-side, sell-side asset exchange and specialist originator models are less frequently used. The procurement portal model is the most commonly used in the agribusiness industry because current market trends indicate that buyers are making purchases as groups and are acknowledging the benefits (such as discount purchases) involved. The sell-side asset exchange and specialist originator models are the two least used, probably because of their complexity and perceived lack of sustainability to the agribusiness industry, which is in only the infant stage of adopting e-business. Ng presents a selection process for business-to-business ebusiness models: . Step 1: identify and understand the types of model available. . Step 2: identify the factors influencing the choice of models. . Step 3: determine the appropriateness, relevance and importance of the influencing factors. . Step 4: select the business-to-business e-business model.

A decision-support system for businessto-business marketing Today’s customers have such varied tastes and preferences that it is not possible to group them into large homogeneous populations to develop marketing strategies. In many cases, each customer wants to be served according to his or her individual needs. The technologies of data warehousing, data mining and other customer relationship management techniques bring new opportunities for businesses to act on 257

Executive summary and implications for managers and executives

Journal of Business & Industrial Marketing Volume 20 · Number 4/5 · 2005 · 253 –259

Why doesn’t marketing use the corporate data warehouse? The role of trust and quality in adoption of data-warehousing technology for CRM applications

the concepts of relationship marketing. Particularly through data mining – the extraction of hidden predictive information from large databases – organizations can identify valuable customers, predict future behaviours and generally be better placed to make knowledge-driven decisions. Noori and Salimi propose a marketing decision support system with the following components: . Customer profiling. This includes demographic details and the characteristics of purchasing transactions, which the marketer uses to decide on the right strategies and tactics to meet the customer’s needs. By knowing how often a customer buys the company’s products, the marketing manager can build targeted promotions such as frequent buyer programmes. Knowing how much the customer spends on a typical transaction helps the marketer to devote appropriate resources to the customer. By knowing if a significant time has elapsed since the customer last placed an order, the marketer can investigate the reasons why and take appropriate steps. If a marketer can identify typical customer groups, he or she can use a more specific marketing message. A marketer who uses data mining and knowledge discovery systems to support customer profiling can better compute customer lifetime values – a measure which provides greater understanding of what is happening to the size and value of a customer base. Moreover, customer databases can provide accurate information on the results of a marketing programme. . Deviation analysis. A deviation can be an anomaly, fraud or a change such as the customer moving to a new house or new job. In the past, it was difficult for marketers to detect deviations in time to take corrective action. But data mining tools provide powerful means, such as neural networks, for detecting and classifying such deviations at a much earlier stage. . Trend analysis. Advanced tools such as visualization help marketers to detect trends – sometimes very subtle trends – that would have been missed using traditional analysis tools such as scatter plots. In marketing decisions, trends can be used for evaluating marketing programmes or to forecast future sales. Advanced tools can bring to light, for example, a peak in sales of a product associated with a change in the profile or a particular group of customers. . Systematic information-management framework. Customer relationship management involves identifying the right customers, differentiating among them, interacting with and learning from existing customers, and customizing the product or service to the needs of individual customers. All these are based on knowing customers better. Current efforts on customer relationship management focus on the customer interface and managing customer interactions. But inadequate information about customers and the lack of a systematic information management framework continue to hinder the efforts of organizations to manage their customer relationships. . Data-mining component. Decision makers can access data warehouses and data marts using tools supporting online analytical processing. . Internal, competitor and customer analyses. The development of effective marketing strategy involves conducting internal, competitor and customer analyses as preliminaries to formulating strategies for market segmentation, targeting and positioning.

A corporate data warehouse is a central repository of information from throughout a company. The information is typically used to perform, for example, trend analyses, forecasting and comparative analyses. A corporate data warehouse can be used to support such marketing functions as sales force automation, contact management, profitability analyses and analysis of customer preferences and profiles. For the data warehouse to support these functions properly, the information it contains must not only be good quality and of the right type, but also easily accessible by the marketing function. Through case study research involving a single health-care payer, Payton and Zahay seek to reveal why marketing tends not to use a corporate data warehouse as much as might be expected. Three main factors explain half of marketing’s disappointing use of the corporate data warehouse for customer relationship management. First, marketing lacks trust in the data contained in the corporate data warehouse. Employees of the case study organization individually trust each other enough to interact on a daily basis, but the organization as a whole does not operate with a high degree of trust. Because of this, marketing is hesitant to use information prepared by the organization’s information systems function. Secondly, marketing perceives that the quality of the information in the corporate data warehouse is low. Data quality centres on the overall accuracy of the information, its timeliness, and that it should be easily accessible, easy to understand and believable. Thirdly, marketing believes that its needs were not incorporated into the design of the data warehouse or data warehouse interface. The case study organization placed more emphasis on financial and billing applications than marketing. Marketing’s unique needs in terms of analysing part customer performance, incorporating outside data sources into its analyses, analysing specific customer data and running targeted marketing campaigns are not the needs of the underwriting, billing and other financial and strategic functions of the organization. External, demographic and descriptive data, for the consumer market, and companydescriptive data, for the commercial applications, are missing from the data warehouse. Also missing is information on former and prospective customers. Because marketing is driving the future of the organization through using a variety of primarily customer-based data sources, and not reporting on its past using financial information, the factors predicting success of marketing’s use of a central data warehouse differ from those that predict implementation success for other types of systems applications. Other factors, which influence to a much lesser extent marketing’s trust in the corporate data warehouse, include: data integration (10.2 per cent); top management support (7.94 per cent); the role of marketing in the organization (7.48 per cent); training (5.67 per cent); end-user support (5.22 per cent); the internal information technology support 258

Executive summary and implications for managers and executives

Journal of Business & Industrial Marketing Volume 20 · Number 4/5 · 2005 · 253 –259

organization (4.08 per cent); and economic factors (3.17 per cent).

LKAB puts money, time, effort and talent into its extranet, and benefits from a more satisfied customer and the chance to become proactive in handling customer problems. LKAB therefore gains an improved relationship with its customers in what is becoming an increasingly competitive market. LKAB is better able to serve its customers’ needs while at the same time saving resources, as the speed to react to customer needs or problems is greatly increased through use of the extranet. The buying organizations also “put in” to the extranet. They must, for example, download order-specific information and other information that previously would probably have been sent to them through the post or handed over by a sales person. The buying organizations therefore put time into using the extranet – but the extranet can also save them time by ensuring that they have the right information at the right time. (These factors also benefit the selling organization.) Foster concludes that, in order to take out value, both seller and buyer must provide it as well. The value input of the industrial seller becomes the value output of the industrial buyer, while the value input of the buyer becomes the value output of the seller. Moreover, the link between online and offline environments is also important, supporting the claims of earlier researchers that true value is created when the internet is integrated into overall strategy. (A pre´cis of the special issue “Doing business in a digital world”. Supplied by Marketing Consultants for Emerald.)

Creating digital value: at the heart of the I-E-I framework There are three broad layers to most company websites: the general, public website; the extranet, which is often used for specific, pre-approved groups such as suppliers, customers and partners; and the intranet, for the organization’s employees. Foster focuses on the extranet in his quest to provide a better understanding of the use of websites for creating value in industrial buyer-seller relationships. The author puts forward the view that what the buyer or supplier receives in terms of “benefits” is not the only true measure of online value creation. Suppliers both produce and consume value, and customers do the same. The extranet has a profound impact on the way in which channel members communicate, the value of which is in the improvement of communication and in the overall relationships themselves. Communication is the glue that holds a channel together. Foster presents the results of a case study involving LKAB, a high-technology mineral and mining company in northern Sweden, and two of its key buying organizations that have access to the LKAB extranet. This permits the author to understand “value” in terms of the customer’s perspective as well as that of the seller.

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