Deborah Compeau

Social cognitive theory and individual reactions to computing technology: a longitudinal study

A model, based on Banduras Social Cognitive Theory, was developed to test the influence of computer self-efficacy, outcome expectations, affect, and anxiety on computer usage. The model was tested using longitudinal data gathered from 394 end users over a one-year interval. Significant relationships were found between computer self-efficacy and outcome expectations, and between self-efficacy and affect and anxiety and use. Performance outcomes were found to influence affect and use, while affect was significantly related to use. Overall, the findings provide strong confirmation that both self-efficacy and outcome expectations impact on an individuals affective and behavioral reactions to information technology.

Assessing between-group differences in information systems research: a comparison of covariance-and component-based SEM

Multigroup or between-group analyses are common in the information systems literature. The ability to detect the presence or absence of between-group differences and accurately estimate the strength of moderating effects is important in studies that attempt to show contingent effects. In the past, IS scholars have used a variety of approaches to examine these effects, with the partial least squares (PLS) pooled significance test for multigroup becoming the most common (e.g., Ahuja and Thatcher 2005; Enns et al. 2003; Zhu et al. 2006). In other areas of social sciences (Epitropaki and Martin 2005) and management (Mayer and Gavin 2005; Song et al. 2005) research, however, there is greater emphasis on the use of covariance-based structural equation modeling multigroup analysis. This paper compares these two methods through Monte Carlo simulation. Our findings demonstrate the conditions under which covariance-based multigroup analysis is more appropriate as well as those under which there either is no difference or the component-based approach is preferable. In particular, we find that when data are normally distributed, with a small sample size and correlated exogenous variables, the component-based approach is more likely to detect differences between-group than is the covariance-based approach. Both approaches will consistently detect differences under conditions of normality with large sample sizes. With non-normally distributed data, neither technique could consistently detect differences across the groups in two of the paths, suggesting that both techniques struggle with the prediction of a highly skewed and kurtotic dependent variable. Both techniques detected the differences in the other paths consistently under conditions of non-normality, with the component-based approach preferable at moderate effect sizes, particularly for smaller samples.

Understanding and measuring user competence

End User Computing (EUC) is experiencing a resurgence of importance as managers realize it is tied to the new knowledge economy through knowledge-worker productivity. Assessing individuals capabilities with respect to end user technologies is central to both research on EUC and management of EUC in organizations. For this reason, we advance a new construct, User Competence, which is multi-faceted. It is composed of an individuals breadth and depth of knowledge of end user technologies, and his or her ability to creatively apply these technologies (finesse). Several issues are explored, including what User Competence means, how users differ in their capability, and how these differences relate to other individual characteristics. The experimental study of 100 subjects shows that the dimensions of competence relate differently to individual factors, such as gender, education, self-efficacy, and specific software-syntax skills. Reasons for and implications of these observed relationships are discussed.

Intentions to Use Information Technologies: An Integrative Model

An integrative model explaining intentions to use an information technology is proposed. The primary objective is to obtain a clearer picture of how intentions are formed, and draws on previous research such as the Technology Acceptance Model (Davis, Bagozzi, & Warshaw, 1989) and the Decomposed Theory of Planned Behavior (Taylor & Todd, 1995a). The conceptual model was tested using questionnaire responses from 189 subjects, measured at two time periods approximately two months apart. The results generally supported the hypothesized relationships, and revealed strong influences of both personal innovativeness and computer self-efficacy.

Understanding online customer repurchasing intention and the mediating role of trust - an empirical investigation in two developed countries

Although e-commerce adoption and customers’ initial purchasing behavior have been well studied in the literature, repeat purchase intention and its antecedents remain understudied. This study proposes a model to understand the extent to which trust mediates the effects of vendor-specific factors on customers’ intention to repurchase from an online vendor. The model was tested and validated in two different country settings. We found that trust fully mediates the relationships between perceived reputation, perceived capability of order fulfillment, and repurchasing intention, and partially mediates the relationship between perceived website quality and repurchasing intention in both countries. Moreover, multi-group analysis reveals no significant between-country differences of the model with regards to the antecedents and outcomes of trust, except the effect of reputation on trust. Academic and practical implications and future research are discussed.

Research Commentary---Generalizability of Information Systems Research Using Student Subjects---A Reflection on Our Practices and Recommendations for Future Research

Information systems researchers, like those in many other disciplines in the social sciences, have debated the value and appropriateness of using students as research subjects. This debate appears in several articles that have been published on the subject as well as in the review process. In this latter arena, however, the debate has become increasingly like a script---the actors (authors and reviewers) simply read their parts of the script; some avoid the underlying issues whereas others cursorily address generalizability without real consideration of those issues. As a result, despite the extent of debate, we seem no closer to a resolution. Authors who use student subjects rely on their scripted arguments to justify the use of student subjects and do not always consider whether those arguments are valid. But reviewers who oppose the use of student subjects are equally culpable. They, too, rely on scripted arguments to criticize work using student subjects, and do not always consider whether those arguments are salient to the particular study. By presenting and reviewing one version of this script in the context of theoretical discussions of generalizability, we hope to demonstrate its limitations so that we can move beyond these scripted arguments into a more meaningful discussion. To do this, we review empirical studies from the period 1990--2010 to examine the extent to which student subjects are being used in the field and to critically assess the discussions within the field about the use of student samples. We conclude by presenting recommendations for authors and reviewers, for determining whether the use of students is appropriate in a particular context, and for presenting and discussing work that uses student subjects.

Who controls the purse strings: A study of consumers' and retail buyers' reactions in an America's FTA environment

Abstract Comparisons were made of the perceptions of Canadian retail buyers and consumers concerning the products, the countries and the people of the United States, Canada, Mexico, Argentina and Chile to examine the differences in perceptions that might affect the buying behaviors of both groups. There was very close congruence of buyers and consumers in the images held of the countries and their products. Major differences were found for both groups in their views of developing and developed countries. A modeling approach revealed basic similarity of structure of relationships among beliefs sets and also some differences, which may affect the congruence of buying practices of retail buyers and their customers.

Self-regulated learning strategies and software training

We investigated one aspect of the growing trend towards self-management within organizations by examining the learning processes that individuals use when learning computer software alone in a web-based training environment, and found that individuals learn in different ways. Software training in any context requires individuals to apply self-regulated learning strategies to achieve their learning objectives. Self-regulated learning strategies are the processes that they use to manage their own learning. As self-guided training gains popularity, self-regulated learning strategies become increasingly important, because the learner typically has more control of their training. We found that self-regulated learning strategies led to better outcomes in our study of managers and professionals learning to use an ERP system. We also gained insights into the most popular learning strategies. This work enhanced our understanding of user processes when learning computer software. It should assist organizations in maximizing the return from their investment in training employees and managing knowledge.

Computer-assisted versus paper-and-pencil administration of questionnaires

In a field experiment using 95 employees, the results of computer-assisted versus paper-and-pencil administration of questionnaires during computer training were compared. Unlike past research, the computer mode of administration was made as similar as possible, in format, to the paper mode. No differences in means or reliabilities were found between any variables across the two conditions. However, when the correlations were examined, different patterns of relationships were found across the two conditions. Specifically, subjective or affective measures (software efficacy, playfulness, and training reaction) were more highly related when the measures were gathered by computer as opposed to paper-and-pencil. The relationships between subjective measures and more objective or factual measures (experience, performance, training transfer) were not affected. Thus, it appears that, while differences in mode of administration may not be reflected in differences in means, there are differences in nomological validity.

Experience effects on the accuracy of self-assessed user competence

Self-managed learning is the normal way that users learn to work with software within organizations. To be effective, self-managed, learning requires individuals to self-assess their IT knowledge; accurate self-assessment helps them optimize the capabilities they possess and be aware of those they do not. This study demonstrated that, in general, individuals did not accurately self-assess their knowledge of the software they used. However, we also found that the accuracy of self-assessment increased with greater experience in, and better understanding of, IT domains.Organizations need to recognize the self-assessment problem to facilitate effective software learning and to gain the most from their software investments.