Using I-D maps to Represent the Adoption of Internet Applications by Local Cricket Clubs

Using I-D maps to Represent the Adoption of Internet Applications by Local Cricket Clubs

Scott Bingley (Victoria University, Australia) and Steven Burgess (Victoria University, Australia)
DOI: 10.4018/978-1-60960-197-3.ch006


This chapter describes the development of a visual aid to depict the manner in which Internet applications are being diffused through local sporting associations. Rogers’ (2003) Innovation-Decision process stages, specifically the knowledge, persuasion, adoption and confirmation stages, are used as the theoretical basis for the aid. The chapter discusses the Innovation-Decision process as an important component of Rogers’ (2003) Innovation Diffusion approach. It then outlines the particular problem at hand, determining how best to represent different sporting (cricket) associations and their adoption and use of Internet applications across the innovation-decision process stages. Different data visualisation approaches to representing the data (such as line graphs and bar charts) are discussed, with the introduction of an aid (labelled I-D maps) used to represent the adoption of different Internet applications by cricket associations in New Zealand, Australia and the UK. The Internet applications considered are email, club websites, association and/or third party websites and the use of the Internet to record online statistics. The use of I-D maps provides instant interpretation of the different levels of adoption of Internet applications by different cricket associations.
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There are a number of approaches that can be used to examine the adoption and use of technology. One of the most popular is known as the diffusion of innovations. The theory has been used to conduct research into the adoption of many different innovations and the theory itself has undergone some modifications, with the 5th edition of the book Diffusion of Innovations being published in 2003.

The use of Rogers (2003) Innovation Diffusion approach, and the Innovation-Decision Process, has provided an important insight into how technologies are adopted into everyday lives. The theory was introduced by Rogers in the 1960s. It has since been revised a number of times and has been used to describe change in many sectors. The approach provides a general explanation of how new ideas disseminate themselves through social systems over time (Kappelman 1995, Suraya 2005).

Rogers (2003) explains the diffusion of an innovation as “the process in which an innovation is communicated through certain channels over time among the members of a social system. It is a special type of communication, in that the messages are concerned with new ideas.” (Rogers 2003: 5)

According to Rogers (2003), an innovation is “an idea, practice, or object that is perceived as new by an individual or other unit of adoption” (Rogers 2003: 12). In fact, Rogers suggests that the idea does not actually have to be new- it only needs to appear to be new to the individual. The perceived attributes of an innovation explain the rate of adoption of an innovation. Research into the characteristics of innovations has described the relationship between these characteristics and the adoption of an innovation (Rogers 2003, Tornatzky and Klein 1982). In a review of 75 articles relating to innovation characteristics and their relationship to innovation adoption, Tornatzky and Klein (1982) concluded that three innovation characteristics (relative advantage, compatibility, and complexity) had the most consistent, significant relationships to the innovation process. Al-Gahtani (2003) found that relative advantage and compatibility were both positively related and complexity was negatively related to the innovation adoption process. Rogers (2003) identified five characteristics that he argued accounted for 87% of the variance in rates of adoption (Al-Gahtani 2003). These characteristics are (Rogers 2003, Al-Gahtani 2003):

  • Relative Advantage: the degree to which an innovation is perceived to be better that the innovation it has replaced.

  • Compatibility: the degree in which an innovation is perceived to be consistent with the present socio-cultural values and beliefs.

  • Complexity: the degree of which an innovation is perceived to be difficult to implement, understand, or use

  • Trialability: the degree to which an innovation may be experimented with on a limited basis by an individual.

  • Observability: the degree to which the results of an innovation are perceptible to others.

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