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Innovation Diffusion and Innovation Decision Process Model

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Innovation diffusion uses an approach in which the decision to adopt new technology is mainly based on perceptions of the technology within the decision-making unit (Rogers 1995; Tatnall & Burgess 2004). IDPM was based on communication theory, where the innovation was communicated to the audience (potential adopters). IDPM could be viewed as the adoption part of the Diffusion of Innovation model by Rogers (Seligman 2000). The IDPM stages as depicted in Figure 1., defined by Rogers (1995) are:

  • Knowledge. The decision-making unit is exposed to the existence of innovation. In this case the innovation could be new hardware, software, methodology, or tools. The main activity in this stage is cognitive (knowing). The knowledge about innovation might come through different communication channels. It could be in the form of advertising, word of mouth, formal education or training. Hassinger argues that the knowledge-finding activity is not a passive exercise (cited in Rogers 1995). The knowledge-finding activity would be initiated when the need for innovation exists.
  • Persuasion. The decision-making unit forms an opinion toward the innovation. This opinion could be favourable or unfavourable. The main activity in this stage is affective (feeling). The decision-making unit would actively seek information about the innovation of concern before developing an opinion.
  • Decision. The decision-making unit decides either to reject (rejection) or accept (adoption) the innovation. Usually, the decision to adopt or reject would be made based on a trial period. The result would determine either to adopt or reject the innovation. External parties might be involved by providing an opportunity to demonstrate the innovation.
  • Implementation. The decision-making unit actually uses the innovation. This is where the activities shift from strictly mental to real action. It would involve behaviour change due to the implementation. In this stage, the decision-making unit would discover whether the initial knowledge and perception of innovation were true or not. The implementation stage would end when innovation becomes an integrated part of the adopter’s life or the innovation perceived as useless.
  • Confirmation. The decision-making unit confirms or reverses the decision to reject or adopt the innovation made in the previous stage. The reason for this change is that information received about innovation may have conflicted with the previous beliefs.

IDPM

Figure 1. Innovation–Decision Process Model (adopted from Rogers 1995)

IDPM also incorporates the conditions prior to the knowledge stage that influence the knowledge stage. These conditions are previous practices, the need to be fulfilled or the problem to be solved, innovativeness of the decision-making unit, and the norms of the social systems. IDPM assumes that the adoption process is continuous (Rogers 1995). A decision to adopt or reject an innovation could be changed in the future if more knowledge and persuasion become available to the decision-making unit. It also could change due to the realities faced during the implementation process.

IDPM has been used to study IT adoption. IDPM has been used to find factors affecting IT adoption in general (Everdingen & Wierenga 2002; Knol & Stroeken 2001; Premkumar & Ramamurthy 1995; Premkumar & Roberts 1999; Waarts, Everdingen & Hillegersberg 2002; Wong 2003), EDI adoption (Angeles et al. 2001; Jimenez-Martinez & Polo-Redondo 2004), computer technology adoption in less developed countries (Al-Gahtani 2003; Anandarajan, Igbaria & Anakwe 2002; Utomo & Dodgson 2001), senior IS managers’ adoption of new computing architectures (Bajaj 2000), and adoption of web service standards (Chen 2003). Others have studied the relationship between the level of internet adoption and competitive advantage (Teo & Pian 2003), general IT diffusion patterns (Teng, Grover & Guttler 2002), and the role of change agents in IT adoption (Elsammani, Hackney & Scown 2003). The research in IT adoption uses Rogers’s IDPM stages to find factors influencing the whole adoption process within a particular context or to explain the role of a particular factor in a particular adoption process (Akkeren & Harker 2002; Al-Gahtani 2003; Chau 2001; Fink 1998; Sharma & Rai 2003).

In IDPM, it is assumed that every innovation is desirable and therefore rejection of innovation would be considered as resistance to change (McMaster & Kautz 2002; Robertson, Swan & Newell 1996). The reality is that not every innovation is embraced by the community, as Rogers himself (1995) pointed out in the Persuasion stage. The innovation characteristics of relative advantage, compatibility, triability, and observability would influence the opinions of the decision-making unit toward the innovation.

Within the IDPM model depicted in Figure 2.2, Rogers portrayed the implementation stage when the decision to adopt was made; however, the real action of implementation was not the focus of this theory. Instead, the focus is more on the communication of information regarding the innovation to the adopter that might change the perception toward innovation. The emphasis on the communication process implies that the adoption is achieved when the decision to accept the innovation is made.

IDPM explains the adoption of innovation on an individual level very well, but not at the organisational level. Most studies using IDPM assume that organisations are at the same level of granularity as an individual level. The consequence of this assumption is that the interaction among individuals within an organisation as an integrated unit has been ignored.

References

Akkeren, J.V. & Harker, D. 2002, ‘Mobile Data Technologies and Small Business Adoption and Diffusion: An Empirical Study of Barriers and Facilitators’, in B. Mennecke & T. Strader (eds), Mobile Commerce: Technology, Theory, and Applications, IDEA Group Publishing, Hershey, pp. 218-244.

Al-Gahtani, S.S. 2003, ‘Computer Technology Adoption in Saudi Arabia: Correlates of Perceived Innovation Attributes’, Information Technology for Development, vol. 10, no. 1, pp. 57-69.

Anandarajan, M., Igbaria, M. & Anakwe, U.P. 2002, ‘IT Acceptance in a Less-developed Country: a Motivational Factor Perspective’, International Journal of Information Management, vol. 22, no. 1, pp. 47-65.

Angeles, R., Corritore, C.L., Basu, S.C. & Nath, R. 2001, ‘Success Factors for Domestics and International Electronic Data Interchange (EDI) Implementation for US Firms’, International Journal of Information Management, vol. 21, no. 5, pp. 329-347.

Bajaj, A. 2000, ‘A Study of Senior Information Systems Manager’s Decision Models in Adopting New Computing Architectures’, Journal of The Association for Information Systems, vol. 1, no. 4, pp. 1-56.

Chau, P.Y.K. 2001, ‘Inhibitors to EDI Adoption in Small Businesses: An Empirical Investigation’, Journal of Electronic Commerce Research, vol. 2, no. 2, pp. 78-88.

Chen, M. 2003, ‘Factors Affecting The Adoption and Diffusion of XML and Web Services Standards for E-Business Systems’, International Journal of Human-Computer Studies, vol. 58, no. 3, pp. 259-279.

Elsammani, Z.A., Hackney, R. & Scown, P. 2003, ‘SMEs Adoption and Implementation Process of Websites in The Presence of Change Agents’, in A.-Q. Nabeel A.Y (ed.), Electronic Commerce in Small to Medium-sized Enterprises: Frameworks, Issues, and Implications, IDEA Group Publishing, Hershey, pp. 146-163.

Everdingen, Y.V. & Wierenga, B. 2002, ‘Intra-firm Adoption Decisions: Role of Inter-firm and Intra-firm Variables’, European Management Journal, vol. 20, no. 6, pp. 649-663.

Fink, D. 1998, ‘Guidelines for The Successful Adoption of Information Technology in Small and Medium Enterprises’, International Journal of Information Management, vol. 18, no. 4, pp. 243-253.

Jimenez-Martinez, J. & Polo-Redondo, Y. 2004, ‘The Influence of EDI Adoption Over Its Perceived Benefits’, Technovation, vol. 24, no. 1, pp. 73-79.

Knol, W.H.C. & Stroeken, J.H.M. 2001, ‘The Diffusion and Adoption of Information Technology in Small and Medium-sized Enterprises through IT Scenarios’, Technology Analysis & Strategic Management, vol. 13, no. 2, pp. 227-246.

McMaster, T. & Kautz, K. 2002, ‘A Short History of Diffusion’, in  Proceedings of IFIP WG 8.6 5th International Working Conference on Diffusion, Adoption, and Implementation of Information Technology, eds D. Bunker, D. Wilson & S. Elliot, IFIP, Sydney, pp. 10-22.

Premkumar, G. & Ramamurthy, K. 1995, ‘The Role of Interorganizational and Organizational Factors on the Decision Mode for Adoption of Interorganizational Systems’, Decision Sciences, vol. 26, no. 3, pp. 303-336.

Premkumar, G. & Roberts, M. 1999, ‘Adoption of New Information Technologies in Rural Small Businesses’, Omega The International Journal of Management Science, vol. 27, no. 4, pp. 467-484.

Robertson, M., Swan, J. & Newell, S. 1996, ‘The Role of Networks in The Diffusion of Technological Innovation’, Journal of Management Studies, vol. 33, no. 3, pp. 333-359.

Rogers, E.M. 1995, Diffusion of Innovations, 4th edn, Free Press, New York.

Seligman, L. 2000, ‘Adoption as Sensemaking: Toward an Adopter-Centered Process Model of IT Adoption’, in  Proceeding of The 21st International Conference on Information Systems, Brisbane, pp. 361-370.

Sharma, S. & Rai, A. 2003, ‘An Assessment of The Relationship Between ISD Leadership Characteristics and IS Innovation Adoption in Organizations’, Information & Management, vol. 40, no. 5, pp. 391-401.

Tatnall, A. & Burgess, S. 2004, ‘Using Actor-Network Theory to Identify Factors Affecting the Adoption of E-Commerce in SMEs’, in M. Singh (ed.), E-Business Innovation and Change Management, IDEA Group Publishing, Hershey, pp. 152-169.

Teng, J.T.C., Grover, V. & Guttler, W. 2002, ‘Information Technology Innovations: General Diffusion Patterns and Its Relationship to Innovation Characteristics’, IEEE Transactions on Engineering Management, vol. 49, no. 1, pp. 13-27.

Teo, T.S.H. & Pian, Y. 2003, ‘A Contingency Perspective on Internet Adoption and Competitive Advantage’, European Journal of Information Systems, vol. 12, no. 2, pp. 78-92.

Utomo, H. & Dodgson, M. 2001, ‘Contributing Factors to The Diffusion of IT Within Small and Medium-sized Firms in Indonesia.’, Journal of Global Information Technology Management, vol. 4, no. 2, pp. 22-37.

Waarts, E., Everdingen, Y.V. & Hillegersberg, J.V. 2002, ‘The Dynamics of Factors Affecting the Adoption of Innovations’, The Journal of Products Innovation Management, vol. 19, no. 6, pp. 412-423.

Wong, P.-K. 2003, ‘Global and National Factors Affecting E-Commerce Diffusion in Singapore’, The Information Society, vol. 19, no. 1, pp. 19-32.

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Author: systemscraft

I am s senior lecturer in information systems at Accounting Department, Faculty of Economics, Atma Jaya Yogyakarta University in Indonesia.

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