The arrival of the ‘information age’ holds great promise in terms of providing organizations with access to a wealth of information stores. However, the free exchange of electronic information also brings the threat of providing easy, and many times unwanted, access to personal information. Given the potential backlash of consumers, it is imperative that both researchers and practitioners understand the nature of consumers' concern for information privacy and accurately model the construct within evolving research and business contexts. Drawing upon a sample of 355 consumers and working within the framework of confirmatory factor analysis, this study examines the factor structure of the concern for information privacy (CFIP) instrument posited by Smith et al. (1996), Consistent with prior findings, the results suggest that each dimension of this instrument is reliable and distinct. However, the results also suggest that CFIP may be more parsimoniously represented as a higher-order factor structure rather than a correlated set of first-order factors. The implication of these results is that each dimension of CFIP as well as the supra dimension derived from the associations among dimensions are important in capturing CFIP and associating the construct to other important antecedents and consequences.
Evaluation of information system success has been the focus of much research. However, most variables such as user satisfaction and system usage can only be measured after system implementation. To predict system success before actual implementation, behavioral theories indicate that it is necessary to evaluate behavioral intention or users' motivation to use the system. Expectancy theory is considered one of the most promising models of individual motivation. This study examines the use of expectancy theory in explaining the motivation to use an expert system. Data gathered from 95 M.B.A. students in a judgmental modeling exercise suggest that the model is a significant predictor of motivation. It also provides insight into the development of such systems. The successful use of this model further suggests that it is appropriate for evaluating and understanding individual motivation to use a system and, subsequently, system success.