Modeling Customer-Related IT Diffusion

Modeling Customer-Related IT Diffusion

Shana L. Dardan (Susquehanna University, USA), Ram L. Kumar (University of North Carolina at Charlotte, USA) and Antonis C. Stylianou (University of North Carolina at Charlotte, USA)
DOI: 10.4018/978-1-60566-128-5.ch014
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This study develops a diffusion model of customer-related IT (CRIT) based on stock market announcements of investments in those technologies. Customer-related IT investments are defined in this work as information technology investments made with the intention of improving or enhancing the customer experience. The diffusion model developed in our study is based on data for the companies of the S&P 500 and S&P MidCap 400 for the years of 1996-2001. We find empirical support for a sigmoid diffusion model. Further, we find that both the size and industry of the company affect the path of CRIT diffusion. Another contribution of this study is to illustrate how data collection techniques typically used for fi- nancial event studies can be used to study information technology diffusion. Finally, the data collected for this study can serve as a Bayesian prior for future diffusion forecasting studies of CRIT.
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Technology innovation and the investment into technologies by firms have been touted as a driving force in organizational competitiveness and even as the key driver of future competitive capability (Fichman, 1999). The diffusion of CRIT is affected both by the characteristics of the technology and by the characteristics of the firm using it (Rogers, 1995 and Fichman, 1999). Diffusion models are attitude change models, and the basis of these types of models is that consumers follow a rational decision-making or problem-solving approach in their actions that is not always linear (Robertson, 1970). Examples of diffusion models are the Sigmoidal Curve (or Logistics Curve), the Bass Model and the Survival Curve (Bass, 1969; Bauer, 1964; and Pindyck and Rubinfeld, 1998). Based on different assumptions about communication channels or influence sources, diffusion models have been classified into three fundamental types: internal, external, and mixed (Mahajan and Peterson, 1985).

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