Diffusion of technological innovations

Abstract

This paper discusses the interaction between technology and behavior from the perspective of the individual decision to adopt or reject a technical innovation. It is only when energy conservation interventions are made available to the public by policymakers that they can contribute to energy conservation. Dutch energy distribution companies have agreed to make a substantial contribution to energy conservation policy. So-called 'coordinators of Environmental Action Plans' have a key position in these organizations, and have to decide, for example, whether a certain energy conservation innovation will be offered to households. Thus, before the diffusion of innovations among end-users can start, an innovation has to be adopted by these coordinators of environmental action plans. Many evaluation studies on interventions or technical innovations to reduce energy use by households were conducted in the late nineteenseventies and 'eighties, after the first oil crisis. Although the results of these evaluation studies showed that psychological strategies can contribute to the motivation to adopt energy reducing activities in households (Winett & Neale, 1979; Baum & Singer, 1981; Cook & Berrenberg, 1981; McDougall, Gordon, Claxton, Ritchie & Anderson, 1981; Seligman & Hutton, 1981; Geller, 1989; Kempton, Darley & Stern, 1992; Cherulnik, 1993; Dwyer, Leeming, Cobern, Porter, Jackson, 1993), such interventions failed to come into general use. As might have been expected, neither consumers nor the responsible policymakers seem to use or adopt successful interventions automatically. The process of up-grading interventions from small-scale to widespread use can be conceptualized as the "diffusion of an innovation." Rogers (1995) defines an innovation as an idea, practice or object that is perceived as new by an individual or another unit of adoption. Our study used Rogers' diffusion theory to examine the diffusion of interventions in terms of technical, educational and/or motivational aspects among policymakers. According to Rogers (1995), the decision to adopt or reject an innovation is affected by five innovation attributes: observability, relative advantage, compatibility, trialability and complexity. The first four of these attributes are positively related to the rate of adoption, while complexity is assumed to be inversely related to the adoption rate (Rogers, 1995). The observability of an innovation is the degree to which the results of an innovation are visible to potential adopters. The relative advantage of an innovation is the degree to which an innovation is perceived as being superior to current practice or to the interventions it replaces. The compatibility of an innovation is the degree to which it is perceived to be consistent with social and cultural values and beliefs, previously introduced ideas and/or perceived needs. Trialability is the degree to which an innovation can be experimented with on a limited basis. Complexity is defined by Rogers as the degree to which an innovation is difficult to use and understand. Rogers' ideas on the diffusion of innovations have had a tremendous impact on the field, and have placed diffusion theory in the spotlight in a variety of disciplines, like marketing, psychology and communication sciences. According to Rogers, 49 to 87 percent of the variance in the adoption rate is explained by observability, relative advantage, compatibility, trialability and complexity. He assumes that the relative importance of the attributes differs with the nature of the innovation, although he remains rather vague about the decision rules behind the assessment of the five attributes. If people are indeed, as Fiske and Taylor (1991) put it, "cognitive misers", striving towards relatively simple and heuristic methods of decision-making, it seems very plausible that not all innovation attributes are rated before making the decision to reject or adopt an innovation. For instance, although a decision to adopt might be based on an assessment of all innovation attributes, the decision to reject an innovation might be based on less information processing (e.g. why bother about trialability if the relative advantage of the innovation is not very obvious?). We hypothesized that the decision to adopt an energy conserving innovation is a stepwise process, in which a conjunctive decision rule is applied. The use of a conjunctive decision rule implies that a decision-maker is supposed to define minimum cut-off points for each attribute. If an alternative does not exceed the cut-off value for one or more of the attributes, its adoption will be rejected. In this model, high values for one attribute cannot compensate for a below cut-off value for another attribute (Bettman, 1979). We assumed that not all attributes are relevant to the potential adopter at the same time, so that the conjunctive decision rule is applied to one innovation attribute at a time. The decision process was presumed to stop as soon as a relevant innovation characteristic is rated below the minimum cut-off value (decision: no adoption), or when all innovation attributes have scored at least the minimum cut-off values (decision: adoption). In view of the goal of an energy conservation innovation, it was hypothesized that coordinators are above all interested in the relative advantages (such as cost-effectiveness) of such innovations. In a second step, an energy conservation innovation would be judged on its compatibility with existing structures. Figure 1 shows the stepwise model we proposed. The first two steps of this model were examined in our study, and are described below. © 2006 Springer.