۱- Introduction

۲- Methodology

۳- Results and discussion

۴- Conclusion

References

Abstract

This study aims to develop a research model that analyzes the effects of the innovation and organizational characteristics in literature on ERP application users’ rates of adoption. Innovation characteristics model in literature is extended and new research model, which includes both innovation and organizational characteristics, is developed and both models are tested on 403 users with factor analysis. Moreover, the sample is divided into 10 categories to observe how characteristics differentiate in both models in each category. Results indicate that categorizations of the sample have distinctive impacts for both models and create dynamic structure which flexes the rigidity in literature.

Introduction

With the advancement of information technology, producers, distributors and retailers have started to perform many of their business tasks electronically. Basically, all the companies that try to increase their efficiency have started to establish electronic work models in order to compete and improve their position. They have increasingly tended to resort to ERP applications to increase their effectiveness. As ERP software markets are featured as high potential margin and intense competition, these systems have gained much attention from both practitioners and researchers (Kao and Hsu, 2011). With the increase in ERP applications use, continuous research in development and improvement has been underway and companies have started to concentrate on innovation management. Therefore, innovation has been an important focus for the attention of academic circles and policy makers in industries (Koc, 2011). Innovation is an idea, practice, or object that is perceived as new by an individual or other unit of adoption. Rate of adoption is the relative speed with which an innovation is adopted by members of a social system (Rogers, 1995). According to diffusion of innovation theory, five different attributes of innovations are described. Each of these is somewhat empirically interrelated with the other four, but they are conceptually distinct (Rogers, 1995). The way people in a social system perceive the five attributes of an innovation determines its rate of adoption. The five attributes are Relative Advantage, Compatibility, Complexity, Trialability, and Observability (Rogers, 1995; Do, 2008). Relative advantage is the degree to which an innovation is perceived as being better than the idea it supersedes (Rogers, 1995). The sub-dimensions of this attribute include economic profitability, savings of time and effort, low initial cost, social prestige. Compatibility is the degree to which an innovation is perceived as consistent with the existing values, past experiences, and needs of potential adopters (Rogers, 1995). The sub-dimensions of this attribute include socio-cultural values and beliefs, past experiences, needs of potential adopters and name (Do, 2008). Complexity is the degree to which an innovation is perceived as relatively difficult to understand and use. The sub-dimensions of this attribute include ease of using and ease of understanding (Rogers, 1995).