Figure 1.8 - Rogers' Model of Innovation Adaptation Behavior (Rogers, 1995, p. 170)
Perhaps the most famous result of Rogers work is the classification of the adopters of innovation into innovators, early adopters, early majority, late majority and laggards (Everett M. Rogers, 1983, p. 281). The categories are categorized to divide a classical Gaussian normal distribution of the target population (see figure 1.9). The second to groups – early adopters and early majority – are found to be decisive for the general market acceptance of an innovation.

Figure 1.9 - Adopter Categorization on the Basis of Innovativeness (Rogers, 1995, p.281)
Rogers’ findings illustrate that the adopters are not one homogenous group, but rather that in one professional group – such as academics – one can expect to find the whole distribution from innovators to laggards. Nevertheless, as Zellenweger writes, it is a combination of individual disposition and the organizational context that determines the overall practices of e.g. a university (Zellweger-Moser, 2003, p. 104).

Another widely cited concept in innovation studies is the technology acceptance model (TAM). It has the perceived usefulness as well as easy operation of a given innovation as its key factors (Lee, Cho, Gay, Davidson, & Ingraffea, 2003). The TAM model is however assessed not to be very suitable to investigate and explain the rather complex internet based knowledge practice innovations like e-learning and e-research, because of its conceptualization of the decision to a simple yes or no. Rather for the innovations in question, the process of appropriation is gradual and users tend to increasingly improve their usage. This theme of classifying the innovations is elaborated by Fitchmann (1992), who categorizes a Type 1 and Type 2 technologies. Hereby Type 1 entities are characterized by a lack of user interdependencies as well as no special demands regarding knowledge or competence on part of the user. Type 2 innovations on the other hand are embedded in or cause interdependencies among stakeholders and special knowledge is needed to exploit the innovations potential. On a second axis Fitchmann addresses the theme of individual versus organizational appropriation of the new technology. Zellweger (Zellweger-Moser, 2003) is correct in assessing that classical innovation theory, like Rogers, deals first and almost exclusively with Type 1 innovations being adopted by individuals. In the case of educational technology there is almost certainly special knowledge needed and as knowledge systems deal with codification and communication there are also always interdependencies. As a consequence more complex scenarios taking organizational decision making processes, cultural characteristics, and competitive effects into consideration (Fitchmann, 1992, p. 9).

Having reviewed all the work implemented on innovation diffusion, technology acceptance, etc. it has been opted to use ‘innovation appropriation’ as conceptualization. Innovation appropriation has been selected as concept describing the act of integrating something innovative into the organization (i). The concept is based on the economic investigations about absorptive capacity as coined by Cohen & Levinthal (Cohen & Levinthal, 1990). In their conceptualization absorptive capacity is the organization’s ability to recognize the value of new information or technology, assimilate it, and apply it to commercial ends. Hence the concept focuses on the realization of an opportunity for improved functionality and as such is in tune with the entrepreneurial perspective developed. But like ‘traditional entrepreneurship’, absorptive capacity is seen there from a pure economic perspective hence they are almost exclusively interested in econometric measures for macro- and micro-economic understanding, which is not transferable to knowledge entrepreneurship and the mission of the university. Nevertheless appropriation is chosen as it is considered more appropriate than innovation diffusion (Everett M. Rogers, 1983), which follows a particular innovation rather than the human activity. The concept of innovation integration (Darking, 2004) is assessed to describe a very similar process (ii), as it deals with the process of incorporating an innovation into the practices of an individual or organization, but it leaves out the important part of entrepreneuring and strategically planning an overall approach to innovation as well as the identification and assessment of the opportunity before the process of integration even starts.

Only three studies (Luambano & Nawe, 2004; Oyelaran-Oyeyinka & Adeya, 2004; Ynalvez et al., 2005) have been identified to deal with the process of appropriating internet based innovations into the university. All three deal with the special case of practices and impact of the internet in developing countries and their special interests and results are therefore not really transferable to the European background. One other study (Nachmias, 2002) deals with the development and provision and further development of an online learning environment at an Israeli university. Unfortunately it is pursuing very technical interests and does not bear insights for this research.

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(i) Either from the inside – a self-produced innovation – or from the external envirnment.
(ii) and hence the term integration is used from time to time

1.3.6.1. Innovation at Universities
Education has long been acknowledged as one of the key sectors for the application of new innovations, especially ICT based innovations. However the visions and expectation of the observers have seldom been realized or at least not been realized to the degree and within the timeframe specified. radical optimist the eminent scientist, entrepreneur, and futurologist Ray Kurzweil has envisioned the future of education as follows: "Because of current bandwidth limitations and the lack of effective three-dimensional displays, the virtual environment provided today through routine Web access does not yet fully compete with 'being there', but that will change. In the early part of the second decade of this century visual-auditory virtual-reality environments will be full immersion, very high resolution, and very convincing. Most colleges will follow MIT's lead, and students will increasingly attend classes virtually. Virtual environments will provide high-quality virtual laboratories where experiments can be conducted in chemistry, nuclear physics, or any other scientific field. Students will be able to interact with a virtual Thomas Jefferson or Thomas Edison, or even to become a virtual Thomas Jefferson. Classes will be available for all grade levels in many languages. The devises needed to enter these high-quality, high-resolution virtual classrooms will be ubiquitous and affordable even in third world countries. Students at any age, from toddlers to adults, will be able to access the best education in the world at any time and from any place" (Kurzweil, 2005, p. 337). As stated, this radial position has to seen with skepticism as most of these kinds of visions turn out wrong. For example the very Thomas Edison mentioned in the above quote proclaimed in 1913: "Books will soon be obsolete in schools ... It is possible to teach every branch of human knowledge with the motion picture. Our school system will be completely changed in the next ten years" (as cited by Reiser, 2001). Traditional media and practices have enormous advantages when it comes to usability and the possibility of inter-generational understanding of the practices.

Probably one of the first researchers to tackle the precise question how universities innovate was Arthur Levine (1980). He has written a book entitled ‘Why innovation fails’, which despite its pessimistic title, is investigating how universities and colleges can successfully change. His findings are explained as example of a whole group of scholars, who, over the following years have done considerable amount of investigation into barriers of change and especially technology adaptation. Levine developed and tested a model to describe the success or failure, the institutionalization or termination of an innovation in an organization. His theory builds upon the concept of boundary expansion. Each organization has a unique set of norms, values and goals which constitute its boundaries. He quotes Kai Erikson who described these boundaries as a “symbolic set of parentheses” controlling the organizations social space in order to retain “a limited range of activities and a given pattern of constancy and stability within the larger environment” (Erikson, 1966, p. 10). Thus these boundaries circumscribe the personality or culture appropriate to the organization. These boundaries are – similar to human development – relatively flexible in the early stage and become more and more rigid and eager to maintain the status quo the older the organization gets.

He describes the process of how the ‘personality traits’ of the innovation penetrates the host organization if it is received positively as boundary expansion. Two processes make up boundary expansion, on the one hand is the innovation diffusing into the organization and thereby changing its routines (he calls this process enclaving), on the other hand are the users changing and appropriating their uses and utilities to the innovation (a process which has been described as ‘user driven innovation’ (Hippel & Sloan School of Management., 1999)). When the innovation is perceived negatively boundary contraction happens. Boundary contraction is characterized by activities of the users to construct organizational boundaries which are meant to exclude the innovation. Thereby the innovation is labeled “deviant” and viewed as illegitimate. Two sanctions are applied to innovations that are perceived as deviant: either they are re-socialized – a process by which the innovative aspects that were in conflict with the traditional boundaries are changed making the innovation practically inexistent; or the innovation is terminated all together, meaning that it is eliminated from the organization.

Profitability and compatibility (congruence) are then proposed (in accordance with the results of many earlier studies) as the main determines for the rejection of incorporation of an innovation (i). Compatibility (ii) is the degree to which the norms, values and goals of an innovation are congruent with those of the host. Profitability is more difficult, because it is rather subjective (this is true especially in knowledge work). Rogers and Havens (1961) have therefore opted to define profitability as the adopter’s perceived profitability and not an objective measure. Maintenance is of great importance when it comes to compatibility. Levine distinguishes between two types of profitability – self-interest profitability and general profitability. Self-interest profitability is what motivates the sub-units and the individuals to adopt an innovation. General profitability is what makes the organization as a whole to go after an innovation. These two might be in conflict with each other. An organization might decide that an enterprise resource planning system is what is needed to get the processes and administration more efficient, thus profitable, while the sub-units are un-pleased with the idea of central control and an innovative but rigid system. On the other-hand the www can be seen as a good example which makes many jobs more diverse and is as such highly appreciated by the individual but deemed controversial for it is used for private goals as well as organizational goals. Two measurements are suggested for profitability – whether it satisfies the specific need for which it was created, and whether it positively or negatively affect the rest of the organization. Obviously the two indicators are highly interwoven (iii). When an innovation becomes incompatible it also becomes unprofitable. Therefore un-profitability is the ultimate indicator for innovation failure.

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(i) Other factors as reported from a literature review of Rogers and Shoemaker (E M Rogers & Shoemaker, 1971) include – relative advantage (“the degree to which an innovation is perceived as being better than the idea it supersedes”); compatibility (“the degree to which an innovation is perceived as consistent with the existing values, past experiences, and needs of the receiver”); complexity (“the degree to which an innovation is perceived as relatively difficult to understand and use”),; trialability, elsewhere called tryability or divisibility (“the degree to which an innovation may be experimented with on a limited basis”) and observability also called communicability (“the degree to which the results of an innovation are visible to others”)

(ii) Compatibility and profitability also include a strategic fit with externally demanded qualities – such as state or market demands (ministry policies and assessments, external ratings etc.)

(iii) Interestingly he states that scientists of culture (anthropologists and sociologists) are prone to highlight compatibility, while scientists of the individual (economists and psychologists) tend to stress profitability. Also the setting of the research is diagnosed to have an influence on the outcomes: Studies of researching innovation adoption in western industrialized countries stressed the profitability while studies looking at the conditions in developing countries found compatibility to be more important. Thirdly the research method had an influence on the outcomes: in-depth long term, participant observation case studies have more often stated compatibility as the main cause of boundary expansion or contraction, while studies using survey research methods reported profitability to be more important. Levine reasons that this might be so because compatibility is a more flexible variable (innovations can be adopted easier to the predominant routine) but profitability is a rather stiff measurement which either produces better results or not.

1.3.6.2. Internet-based Innovation Appropriation at Universities
‘The development and implementation of information and communication technology (ICT) forces today’s universities and colleges to respond to societal trends that point to a transformation of our society into a so-called ‘knowledge economy’ (Manuel Castells,1996). With these words describes Castells the current wave of innovation happening in education. One notices the identification of society and economy in this passage. Maybe not consciously Castells is therefore alluring to a point cut out straight by Nobel: "universities are not only the real undergoing a technological transformation. Beneath issues that change, and of camouflaged by it, lies another: the Second commercialization of higher education" (Noble, 1998). Acknowledging the efficiency gains of ICT deployment, this research is however rather interested in the benefits on knowledge production and services rather than economic optimization.

Lets remember, Rogers (1983) defined the process of innovation diffusion as “the process by which an innovation is communicated though certain channels over time among members of a social system” (p. 5). As stated in the corresponding section (1.3.6.) in this research internet appropriation, and hence the variation is investigated from the perspective of the actor as knowledge entrepreneur and with the innovations being the constant stream of new internet technologies and services and universities as social systems.

During the internet hype of the mid to late 1990’s a whole industry of e-learning providers emerged and even though e-learning was not the killer application, many products have developed into an mature state (Yanosky, Harris, & Zastrocky, 2004), and in fact an advanced market consolidation has left only very few big players in the commercial field, while the open source approach gains momentum. This seems somehow natural, because many universities do have experts who are able to tweak and optimize the e-learning applications so they fit to their demands and the collegiality and humanism (sharing benefits with institutions in developing countries) among academics also is in line the open source approach. E-learning is but one example of a field of internet based innovation where actors first have unrealistic expectations and subsequently are disillusioned when the results are sobering. Zellweger Moser assesses: “It is only with solid research and development efforts that the technology matures and becomes a productive innovation adopted by many businesses” (Zellweger-Moser, 2003, p. 82).

Many authors have investigated the barriers and resistance to innovation (Ertmer, 1999; Maguire, 2005; Miller, Martineau, & Clark, 2000; Weston, 2005) rather than the motivators or institutional facilitators. Miller et. al. for example makes a distinction between individual resistance to change and organizational barriers. For them individual resistance is based on technological illiteracy and competence to assess innovations correctly but they are also the result of organizational barriers like a missing incentive structures and the fact that innovation in teaching is not valued in higher education. The missing incentive structure is directly related with their finding that universities have difficulties to redirect significant but necessary amounts of resources from the traditional and proven model of education towards technology based education. The whole process boils down to the single question of "Why change" (ibid p. 238). They also find that still many faculty believe face-to-face instruction to be the most effective form of teaching (ibid p. 233)

Maguire (2005) has conducted a literature review and essentially agrees with the classification of individual and organizational barriers for the participation in distance education. She classifies the findings of 13 empirical studies into intrinsic, extrinsic, and institutional motivators and deterrents. Her particular emphasis is on peer communication and practice as a motivator.

Another conceptualization comes from Brikner (as cited in Ertmer, 1999, p. 48) who defines a distinction between first-order barriers, which hinder the incremental evolution of a current practice, and second order barriers which are the psychological dispositions and mindsets of the teachers. According to Ertmer first-order barriers include lack of computer access, insufficient time to plan instruction, and inadequate support services. Second-order barriers are factors like believes about teaching, believes about computers, the culture and practice that has naturally emerged over time as well as a fundamental aversion of change. Also Weston (2005) supports this external internal division in his anecdotal explanations of why faculty did or did not integrate e-learning aspects into their teaching. It remains however unclear in all these cases how these internal or external factors can be leveraged with the goal of creating more favorable conditions.

A more procedural approach, similar to Rogers (1983), is presented by Celsi & Wolfinbarger who also propose a three stage model of technology integration. They suggest a model that makes a distinction between the potential of the technology and the innovation in practice. According to them, technology is first used as a support function of the dominant traditional practice, in the second stage it is used to mirror the practice and it takes over certain teaching functions. It is only in the third stage that professors actually let go of the established practices and engage in discontinuous innovation. Their model comes very close to Bates stages of innovative technology exploitation (Bates, 2000; Bates & Poole, 2003, see Chapter 5 section 1.3.1 for description and application to the case studies).

One last study that deploys a different methodological approach and hence a new perspective on the subject has been put forward by Mergel (2005). In her doctoral study the social networking aspect towards the spread of innovation has been given central stage. Concretely, Mergel studied the e-learning adoption practices at a Swiss business school. She found four strongly overlapping network types: (1) the connection and (2) direction regarding advisory support about the software platform; (3) the social networks observing who is dealing with whom at social events; as well as (4) the professional relations network investigating who is interacting with whom for professional occasions. The findings she reports are rather clear. Colleagues interact mostly with peers in the same department while there is no gender bias amongst academics. Both top-down and bottom-up communication channels are used to spread information about the e-learning tool. Somewhat unexpectedly comes the finding that early adopters do not actively share information about their work (Mergel, 2005, p. 120).

The internet as a socio-technological space
Even though the internet is only less than 40 years old (Abbate, 1999) and has been a tool of mass media only since the mid 1990’s, it is used today by more than 1,08 billion people around the planet. It has been described as cyberspace (Benschop, 2001) and as noossphere (mindsphere, (Arquilla & Ronfeldt, 1999; Senges, 2002)) both terms see a socio-technological (i) environment suitable for human development similar to Vogotzky’s (Mejías, 2004; Watson, Audio Lectures) zone of proximal development, and surely beyond the technology from which it is composed.

This research’s perspective on the internet is affiliated with the field of social study of technology (ii), “a perspective which encompasses a range of sociological and historical approaches that place technology – of whatever size, shape or scale – firmly within ‘the social’. Technology is not ‘outside’ of society but a carrier and mediator of social relations, meaning and interests” (McLaughlin, 1999, p. 6). This perspective goes against technology as bits & pieces artifacts, and it is also distinct from a managerial perspective on technology. “Instead [technology] is to be regarded as a socio-technical ensemble, whose component parts and their composition are shot through with, and held together by social relations among people, as much as by more physical ties such as screws, bolts or electrons” (ibid) It is hence the role of the internet as ‘knowledge media’ (Daniel, 1999) that makes the innovations a relevant subject for investigation of knowledge entrepreneurship. Eisenstadt, who according to Daniel introduced the term, states that knowledge media are about capturing, storing, imparting, sharing, accessing and creating knowledge, and it is exactly in this regard the this study is interested in the universities’ practice in realizing such potentials in internet based innovations.
The role of universities
The question then is, how do universities, some of which originally participated in the creation of the cyberspace, act out their role in the development and exploitation of the internet’s potentials?

Overall, universities are still on the forefront of internet use and development. There are few institutions which have embraced email especially as rapidly into their organizational repertoire, also- universities were among the first institutions to use websites as a means of marketing and information. Thus it is true that much more could be done, and some pioneering universities are constantly pushing the limits, but given the well established and proved practices of academic conduct, it comes as no surprise that internet-based innovations are not centrally rolled out throughout the whole university, but rather experimented with by innovators, and early adopters and then gradually spread across departments (Bates, 2000; Bates & Poole, 2003).

Universities strategic reaction and outlook to the flood of technological innovations has been researched in 2002 by Collins and van der Wende, et.al. targeting all universities in Netherlands, Germany, the United Kingdom, Australia, Sweden, Finland, and the United States of America (there only a sample of 200 institutions was targeted). They report (Collis & Wende, 2002) ‘continual but non revolutionary change’. From the four proposed scenarios for the future development they find that while universities are and will be experimenting with all options, no radical change is to be expected. The report is a great indicator for what academia in Europe and the US believe is happening. We can however – as is the case for all future assessments – be assured that the real impact of the net will most likely be different than these early assessments .

While several studies discuss certain aspects of internet-based innovation appropriation, such as e-learning strategies (Zellweger-Moser, 2003), no systemic approach has yet been applied. The common agreement is that the integration of new tools into university practice requires more than just cosmetic adaptations and needs to be approached strategically. Many studies report (see Zellweger for list) that the organization of education and research technology support structures and the effect on faculty behavior are not well understood. This relationship is problematic and of importance for HEI and therefore needs to be studied in more depth.

“Moreover, there is a gap between vision and reality. Or put differently, the ‘Virtual University’ works in theory but not in practice (Pollock & Cornford, 2002). Many institutions are still struggling to overcome the "pioneer" or the "1000 flowers blooming" phase, while trying to move into a phase of more mainstream engagement.” (Collis & Wende, 2002) The concepts and results developed in this research intend to contribute to a better understanding of what conditions are favorable to the optimal exploitation of the potential of the internet.


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(i) Within this scheme technological change and organizational change are mutual processes therefore one can speak of techno-organizational change. One can speak of a process of socio-technological deconstruction and reconstruction that is happening when new technologies are introduced.

(ii) Another example of a similar study is McLaughlin (McLaughlin, 1999). She recounts the case study they had conducted with a medium size English university, which was partaking in an effort to introduce a MAC (Management and Administrative Computing) system. The process took the enormous time of 8 years and was considered by many participants to be a failure. Partially because there was no experience in engaging in such a project on the administrative side, partially because it a collaborative development effort and all sorts of approaches were taken, and maybe most decisively the Higher Education sector was forced to undergo some major transformations during the implementation time of the project so that the needs were analyzed for a time before the development was planned. Another criticized step was the installation of the students module before the finance model, as the latter was seen to be key for the smooth administration of all other parts of the system. One positive effect of the mess and problems that were encountered during the long project time was that networking and knowledge sharing (problem solving) created new inter- and intra-organizational networks.
Allow me to remind the reader of Bill Gates’ claim that a memory of 640kb will be sufficient for all home PC users. A reminder that even the thought leaders in a field can be way of with their future forecasts.

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