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).

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