The Role of Leading Edge Users in the Adoption of Technological Innovations By Organizations

ABSTRACT - The literature on the adoption of innovations has paid little attention to communication processes, nor has it had wide application in the industrial marketing setting. In this paper we modify the recent construct of leading edge users to examine the industrial diffusion process. Using an application to libraries in an Asian/Pacific country we study the continuous analog of leading edge users (leading edge status) and contrast it to the more traditional construct of innovators. By relating leading edge status to opinion leadership and network connectedness and examining characteristics associated with it, we are able to better understand the role of different adopters in the diffusion process.



Citation:

Pamela D. Morrison, David F. Midgley, and John H. Roberts (1994) ,"The Role of Leading Edge Users in the Adoption of Technological Innovations By Organizations", in AP - Asia Pacific Advances in Consumer Research Volume 1, eds. Joseph A. Cote and Siew Meng Leong, Provo, UT : Association for Consumer Research, Pages: 65-71.

Asia Pacific Advances in Consumer Research Volume 1, 1994      Pages 65-71

THE ROLE OF LEADING EDGE USERS IN THE ADOPTION OF TECHNOLOGICAL INNOVATIONS BY ORGANIZATIONS

Pamela D. Morrison, University of New South Wales

David F. Midgley, University of New South Wales

John H. Roberts, University of New South Wales

ABSTRACT -

The literature on the adoption of innovations has paid little attention to communication processes, nor has it had wide application in the industrial marketing setting. In this paper we modify the recent construct of leading edge users to examine the industrial diffusion process. Using an application to libraries in an Asian/Pacific country we study the continuous analog of leading edge users (leading edge status) and contrast it to the more traditional construct of innovators. By relating leading edge status to opinion leadership and network connectedness and examining characteristics associated with it, we are able to better understand the role of different adopters in the diffusion process.

INTRODUCTION

The objective of this paper is to better understand the nature and role of Leading Edge Users in the individual adoption and aggregate diffusion processes for technological innovations. Our research focuses on:

* the study and identification of Leading Edge Users (LEUs) in the organization adoption decision,

* the relative connectedness of LEUs to other organizations in the interorganizational communication network, and

* the relation between LEUs and Opinion Leaders (OLs), including the role of LEUs in the decision making process of later adopters.

Despite the fact that organizational markets constitute over 50% of all economic activity in the industrialized world (Lilien 1987), they have received very little attention in the adoption/diffusion literature. While some work has been undertaken studying various elements of the decision process, specifically context variables (Gatignon and Robertson 1989), and adopter characteristics (Khan and Manopichetwattana 1989), these studies have focused on only part of the adoption decision. Although interpersonal communication has been demonstrated to be an important influence in consumer adoption (Gatignon and Robertson 1991), it has been largely ignored in industrial marketing, with the exceptions of Czepiel (1974) and Midgley, Morrison and Roberts (1992).

The objective of this research is to address this imbalance by studying the role of leading edge users and opinion leaders in the decision process for adopting technological innovations, with particular attention to the overlap of leading edge users and opinion leaders.

BACKGROUND

Characteristics of Adopters: The Existence of Leading Edge Users

When studying the adopting population in an industrial marketing setting, one important concept to have emerged recently is the role of leading edge (or lead) users. von Hippel (1986, p796) has defined "lead users" as those displaying two characteristics with respect to the novel product or service:

"Lead users face needs that will be general in a marketplace-but face them months or years before the bulk of that marketplace encounters them, and

Lead users are positioned to benefit significantly by obtaining a solution to those needs."

Most research to date involving Leading Edge Users (LEU's) has focused on their role in the development of new products (Urban & von Hippel 1988; Voss 1985). But this is not their only role. As an extension of their new product development aspect, Urban and von Hippel (1988) have suggested that LEU's can play an important role in both the pre-launch stage as test sites, and post-launch as Opinion Leaders, thus fuelling the diffusion process. LEUs also play an important role in developing new applications. This is exemplified by the behavior of DEC which tends to "rely on customers to find uses for minicomputers, rather than burdening the company with huge costs of developing and marketing applications on its own" (Uttal 1979, p 100).

Urban and von Hippel (1988) propose that Leading Edge Users have the ability to develop new knowledge and new patterns of experience. When this is combined with their early need for new technology, it makes them important players in the diffusion process; both as early adopters, and in their potential role in building and communicating the knowledge and experience base necessary to fuel the diffusion process.

von Hippel (1986) suggests that potential adopters either are LEUs or they are not. In the study of leading edge users, nowhere is there any rationale as to why the population should be dichotomous. To enable a finer and more flexible definition of LEUs, we introduce the construct of Leading Edge Status (LES), a continuous variable. LES is defined to be 'the degree to which organizations use and apply technology innovations in new and different ways to solve problems faced by the organization, and the degree to which they perceive the benefits of new products earlier than the rest of the marketplace'. We define LEUs to be those organizations exhibiting high levels of LES, though whether there is a clear cut-off is an empirical question. We propose that the elements associated with high LES are:

(a) the ability to benefit significantly from adoption of the innovation,

(b) a strong need for products and their applications before the general marketplace, and

(c) the ability to manipulate the technology to meet the needs of the organization.

The Diffusion Process: The Role of Communication Networks

Although the importance of interpersonal communication networks to the diffusion process is well accepted (Rogers 1983), networks have largely been both theoretically and empirically ignored in the organizational diffusion literature with the exceptions of Czepiel (1974) and Midgley, Morrison and Roberts (1992). Organizations generally seek to avoid uncertainty (MacCrimmon and Wehrung 1986). One strategy commonly adopted to reduce uncertainty associated with adopting technological innovations is to develop inter-organizational communication ties, thus enabling organizations to learn from the experience of others.

Opinion Leadership

All adopters, particularly early adopters, do not participate equally in the Word of Mouth (WOM) process (Midgley 1976). While early studies found only weak evidence for overlap of early adopters and OLs (Robertson and Myers 1969), more recent studies in the consumer marketing literature have indicated a strong relationship between Early Adoption and Opinion Leadership (eg Venkatraman 1989). Though there has been considerable research on WOM and OLs in a consumer marketing setting, similar study in organizational marketing has been minimal. Czepiel (1974) in studying the adoption of process innovations within the steel industry found evidence that OLs played an active role in the diffusion process, and also that there was considerable overlap between early adopters and OLs. Midgley, Morrison and Roberts (1991) found similar evidence in the Australian insurance industry.

It is evident from the consumer and organizational marketing literature that interpersonal communication is an important phenomena driving the diffusion process. It is also obvious that little research effort has been devoted to the investigation of interpersonal communication in an organizational setting. By studying the communication patterns between organizations involved in an adoption decision, and particularly the role of LEUs, we begin to address this gap.

In this study we use a network framework to:

(i) study the communication patterns of organizations with high LES (both within and external to the industry),

(ii) define and identify Opinion Leaders (OLs) in the inter-organization technology diffusion process,

(iii) test the relationship between LES and OLs, and

(iv) examine the effects of these relations on the diffusion process.

METHODOLOGY

To examine the role of LEUs in the adoption process we selected Australian libraries as an adopting population. They were chosen because they exhibited:

* homogeneity with respect to product interest,

* heterogeneity with respect to size, adoption rate, market sector, and

* capability of good recall and an interest in the information being sought.

Because the group nature of the organization adoption decision makes the use of multiple respondents highly desirable data was collected from multiple respondents for the larger organizations in the sample. Qualitative research showed that in smaller organizations the adoption decision was usually made by the principal librarian. Within each library the primary respondent was the head librarian or the librarian responsible for information processing technology, whichever was more appropriate. Where multiple respondents were used the secondary respondents were librarians who had been involved in the selection of at least one of the new technologies. The pre-tested questionnaire was administered by mail with a telephone follow-up. It was sent to 747 Australian libraries, comprising all large libraries (with five or more professional staff) as well as to a sample of other libraries stratified by type and size.

The innovations we investigated were: Online Public Access Catalogues (OPAC), Online Database Systems, CD Roms, and Electronic Data Interchange (EDI). We selected these innovations on the basis of the following requirements:

* the decision to adopt the product was a reasonably important one so that information about the decision could be easily recalled,

* the products should have been adopted fairly recently, and

* the products to have been adopted across different types of organizations (eg Academic, Public, Private Libraries).

Respondents were asked to name all those organizations with which they had regular discussions regarding general issues. They were also asked a similar question but in the context of communications concerning these four innovations. In addition, respondents were asked questions relating to organization characteristics, attitudes to technology, and actual adoption behavior.

RESULTS

463 out of 747 libraries responded to our survey. This response rate of 62% showed no obvious bias, with all types of libraries being well represented. Multi-item measures of LES and OL were developed, grounded in current literature. These comprised self measures, such as 'we often find that we are suggesting new applications to equipment developers', as well as measures of the degree of LES and Opinion Leadership of an organization judged by other organizations in the sample.

Leading Edge Status - its measurement and relation to Innovators

In TABLE 1 we present the six items comprising LES and their pairwise correlations demonstrating the convergent validity of this construct. Each of these items, except for the self evaluation, was measured on a 5 point scale. The self evaluation measure used a 7 point scale. For the purposes of this paper the LES construct is represented by a summated scale of these six items, having a possible range from 6 (Low LES) to 32 (High LES).

The two items used for the OL scale were measured using a 5 point scale and are:

1. Vendors often ask us to show potential purchasers how we use their products, and

2. Generally we are viewed as a good source of advice on new technology.

As mentioned previously, it is an empirical question as to whether LES is dichotomous, thereby making the identification of LEUs a well-defined task. FIGURE A suggests that LES is a continuous variable, leading to the conclusion that an LEU dichotomy is not a good representation of the population and it throws away useful information. In the discussion following, the LES of organizations is discussed in terms of where on the continuum from LOW to HIGH a particular organization is.

TABLE 1

CONVERGENT VALIDITY OF LEADING EDGE STATUS: PAIRWISE CORRELATION

FIGURE A

DISTRIBUTION OF LEADING EDGE STATUS CONSTRUCT

In TABLE 2 we present the relationship between measures of LES and Innovators. These constructs come from two separate streams of literature. LES is compared with three separate measures of innovativeness. The first is the actual Time of Adoption [TOA] for those organizations having already adopted the innovation (measured as the date the innovation was first adopted by the organization). The second measure is termed 'adoption score' and is based on TOA for organizations having already adopted and 'intentions to adopt/not adopt' for those who have yet to make the adoption decision. This measure makes use of Rogers 1983 adoption categories. The third measure, 'number of innovations adopted', is a count of the number of different innovations adopted by the organization. All three measures are well grounded in the adoption literature (Rogers 1983). It is interesting to note that while there is a significant overlap of the constructs as shown by the significant correlations in TABLE 2, when we look more closely at characteristics of organizations with high levels of LES and those which are Innovators (TABLE 3) we see that there are substantial differences between them.

In Table 3 we note that organizations which are Leading Edge, Innovative and Opinion Leaders all have high levels of experience with adopting other innovations (measured by the number of innovations adopted), and are large in size. But while the level of respondent knowledge about the specific innovation is more highly correlated with Innovativeness than with LES or OL (and this is particularly so for very recent innovations such as Electronic Mail and Electronic Data Interchange), LEUs and OLs are more likely to exhibit an innovative work environment, perform better than libraries of a similar type and size, and have a higher level of autonomy in new technological decisions than Innovative organizations. It is interesting that high LES organizations are more similar in characteristics to OLs than those with high innovativeness

TABLE 2

LEADING EDGE STATUS AND INNOVATORS: PAIRWISE CORRELATIONS

TABLE 3

CHARACTERISTICS OF LEUs, INNOVATORS, AND OPINION LEADERS

The aim of the study was to examine the communication process involved in the adoption of technological innovations. Before looking at the specific role of LEUs in this process we examine the communication links used by libraries for both general issues and for learning about specific innovations. In TABLE 4 we present the general communication links showing the percentage of links to libraries within the same category (that is, for example, from a Business library to another Business library). For the major five library categories the percentage of links within the same category is in the range 63% to 85% indicating that strong cliqueing occurs. This supports Czepiel's (1974) finding for communication within the US steel industry. Similar cliques were found to exist for innovation specific communication in the sample.

TABLE 5 presents the standardized residuals from crosstabulations of LES with a measure of connectedness to other libraries for general communication. Connectedness is measured by the number of links to other libraries. This table shows that organizations with high LES are better connected to other organizations within the industry than are organizations with low LES. The relationship between LES and 'connectedness' is significant at P=.000.

An examination of the links LEUs have with other libraries concerning specific innovations showed a similar and significant pattern. That is, LEU libraries are more likely to have links with multiple libraries than are non-LEUs.

TABLE 4

GENERAL COMMUNICATION LINKS: % OF LINKS TO LIBRARIES WITHIN SAME CATEGORY

TABLE 5

USE OF LIBRARY COMMUNICATION LINKS - GENERAL COMMUNICATION

In TABLE 6 we present evidence that LEUs serve as bridges in the communication networks, activating links to organizations outside the library system. By studying the standardized residuals in Table 6 we observe that organizations with a high level of LES (that is LEUs) are more likely to activate links to non-library organizations for communication concerning both general issues and specific innovation issues than non-LEUs. Similar results were found for OLs. That is, OLs are more likely to have outside links than non-OLs.

As well as using communication links to organizations within and outside the industry to learn about technological innovations, organizations also use sources of information such as journals, attending conferences, and relationships with suppliers. How often these sources of information were used for each of the innovations under study was measured, and it was found that LEUs, OLs and Innovators were all more likely to use these sources of information more frequently than non-LEUs, non-OLs, and Later Adopters. The pairwise correlations of these sources of information with LES follows. All correlations are significant at P= 0.000.

Journals          p=.3028;

Conferences   p=.2796;

Suppliers        p=.2321.

We have seen in TABLE 3 that OLs have similar characteristics to LEUs. We have also noted that they fill similar roles to LEUs acting as bridges to communication networks outside their industry (TABLE 6), and they have similar patterns of using other sources of information such as journals and conferences. We now look at the overlap of LEUs and OLs. Two distinct measures of each of these constructs is available. The first are scales based on self-perception items, used in the paper up to now, the second is a measure derived from the judgment of others in the survey. Each respondent was asked to name libraries they:

* 'might approach to seek information about technological innovations', and

* would regard as being "leading edge" in the use of technological innovations'.

TABLE 6

USE OF NON-LIBRARY ORGANIZATION COMMUNICATION LINKS

The correlations between LES and Opinion Leadership using these different measures are:

[A] Self perceptions r=0.7863 n=430

      (LES: 6 item scale a=.86); (OL : 2 item scale a=.72)

[B] Judgment by other respondents r=0.8575 n=465

FINDINGS AND IMPLICATIONS

In this research we have provided a generalization of the concept of leading edge users and developed rigorous measures for its identification. We have also studied the innovation-related communication patterns between organizations, with specific attention to the overlap of leading edge users and opinion leaders and their role in the decision making process.

We have shown that LEUs have a high level of connectedness with other potential adopters (TABLE 5). We have shown that they are better connected to organizations outside their industry (TABLE 6), better enabling technology transfer. We have also shown that there is a strong relationship between the constructs LES and Opinion Leadership, and that this subset of the adopting population share similar organizational characteristics (TABLE 3). This strong overlap of LEUs with OLs demonstrates their influence in the adoption decision. This leads us to the conclusion that these organizations could be harnessed to speed the diffusion process by using them as seeding agents.

The managerial implications of this research are important. The study shows for this industry that LEUs deserve special attention not only because of their "innovativeness" (early recognition of need and early adoption) which is von Hippel's argument (1986), but also because of their "opinion leadership" (they do indeed lead). Thus seeding and targetted selling strategies combined with product information support (eg, brochures, technical specifications) are likely to pay high returns amongst this group. However, more importantly, the result that the distribution of leading edge status is far from dichotomous, suggesting a continuum of this characteristic rather than a distinct group of LEUs, suggests that management may well be advised to implement a gradated marketing effort proportional to the level of LES rather than putting all the effort into one small group of LEUs. In addition, because of the multiple measures of LES which have high convergent validity, the research gives managers a number of reliable methods of identifying users with high Leading Edge Status.

REFERENCES

Czepiel, John A., (1974) "Word-of-Mouth Processes in the Diffusion of a Major Technological Innovation," Journal of Marketing Research, XI, May, pp 172-80.

Gatignon, Hubert and Thomas S. Robertson, (1989) "Technology Diffusion: An Empirical Test of Competitive Effects," Journal of Marketing, 53, Jan. pp 35-49.

Gatignon, Hubert and Thomas S. Robertson, (1991) "Innovative Decision Processes," Ch 9 in Handbook of Consumer Behavior, Eds. T.S. Robertson and H.H.Kassarjian, Englewood Cliffs, New Jersey, Prentice-Hall.

Khan, A.M. and V. Manopichetwattana, (1989) "Innovative and Noninnovative Small Firms: Types and Characteristics," Management Science, Vol. 35, No. 5, May, pp 597-606.

Lilien, Gary L., (1987) "Business Marketing: Present and Future," Industrial Marketing and Purchasing, 2, No.3, 3-21.

MacCrimmon K.R. and D.A. Wehrung, (1986) Taking Risks, New York: Free Press.

Midgley, D.F., (1976) " A Simple Mathematical Theory of Innovative Behavior," Journal of Consumer Research, Vol. 3, June, pp 31-41.

Midgley, David F., Pamela D. Morrison, and John H. Roberts, (1991) "The Nature of Communication Networks Between Organizations Involved in the Diffusion of Technological Innovations", Advances in Consumer Research, 18.

Midgley, David F., Pamela D. Morrison, and John H. Roberts, (1992) "The Effect of Network Structure in Industrial Diffusion Processes," Research Policy,. 21, No. 6, pp 533-552.

Robertson, Thomas S. and James H. Myers, (1969) "Personality Correlates of Opinion Leadership and Innovative Buying Bahavior," Journal of Marketing Research, VI, May, pp 164-168.

Rogers, Everett M., (1983) Diffusion of Innovations: 3rd Ed., New York: Free Press.

Urban, Glen L. and Eric von Hippel, (1988) "Lead User Analyses For The Development of New Industrial Products," Management Science, 34, 5, May, pp 569-582.

Uttal, Bro (1979), Fortune, April, p 100.

Venkatraman, Meera P., (1989) "Opinion Leaders, Adopters, and Communicative Adopters: A Role Analysis," Psychology and Marketing, 6 (1), Spring, pp 51-68.

von Hippel, Eric, (1986) "Lead Users: A Source of Novel Product Concepts," Management Science, 32, 7, July, pp 791-805.

Voss, C.A., (1985), "The Role of Users in the Development of Applications Software," Journal of Product Innovation Management, 2, pp 113-121.

----------------------------------------

Authors

Pamela D. Morrison, University of New South Wales
David F. Midgley, University of New South Wales
John H. Roberts, University of New South Wales



Volume

AP - Asia Pacific Advances in Consumer Research Volume 1 | 1994



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