The measurement of meaning

Despite recurring concerns about common method variance (CMV) in survey research, the information systems (IS) community remains largely uncertain of the extent of such potential biases. To address this uncertainty, this paper attempts to systematically examine the impact of CMV on the inferences drawn from survey research in the IS area. First, we describe the available approaches for assessing CMV and conduct an empirical study to compare them. From an actual survey involving 227 respondents, we find that although CMV is present in the research areas examined, such biases are not substantial. The results also suggest that few differences exist between the relatively new marker-variable technique and other well-established conventional tools in terms of their ability to detect CMV. Accordingly, the marker-variable technique was employed to infer the effect of CMV on correlations from previously published studies. Our findings, based on the reanalysis of 216 correlations, suggest that the inflated correlation caused by CMV may be expected to be on the order of 0.10 or less, and most of the originally significant correlations remain significant even after controlling for CMV. Finally, by extending the marker-variable technique, we examined the effect of CMV on structural relationships in past literature. Our reanalysis reveals that contrary to the concerns of some skeptics, CMV-adjusted structural relationships not only remain largely significant but also are not statistically differentiable from uncorrected estimates. In summary, this comprehensive and systematic analysis offers initial evidence that (1) the marker-variable technique can serve as a convenient, yet effective, tool for accounting for CMV, and (2) common method biases in the IS domain are not as serious as those found in other disciplines.

Common Method Variance in IS Research: A Comparison of Alternative Approaches and a Reanalysis of Past Research

The rapid growth of investment in information technology (IT) by organizations worldwide has made user acceptance an increasingly critical technology implementation and management issue While such acceptance has received fairly extensive attention from previous research, additional efforts are needed to examine or validate existing research results, particularly those involving different technologies, user populations, and/or organizational contexts In response, this paper reports a research work that examined the applicability of the Technology Acceptance Model (TAM) in explaining physicians' decisions to accept telemedicine technology in the health-care context The technology, the user group, and the organizational context are all new to IT acceptance/adoption research The study also addressed a pragmatic technology management need resulting from millions of dollars invested by health-care organizations in developing and implementing telemedicine programs in recent years The model's overall fit, explanatory power, and the individual causal links that it postulates were evaluated by examining the acceptance of telemedicine technology among physicians practicing at public tertiary hospitals in Hong Kong Our results suggested that TAM was able to provide a reasonable depiction of physicians' intention to use telemedicine technology Perceived usefulness was found to be a significant determinant of attitude and intention but perceived ease of use was not The relatively low R-square of the model suggests both the limitations of the parsimonious model and the need for incorporating additional factors or integrating with other IT acceptance models in order to improve its specificity and explanatory utility in a health-care context Based on the study findings, implications for user technology acceptance research and telemedicine management are discussed

Examining the technology acceptance model using physician acceptance of telemedicine technology

The IT implementation literature suggests that various implementation factors play critical roles in the success of an information system; however, there is little empirical research about the implementation of data warehousing projects. Data warehousing has unique characteristics that may impact the importance of factors that apply to it. In this study, a cross-sectional survey investigated a model of data warehousing success. Data warehousing managers and data suppliers from 111 organizations completed paired mail questionnaires on implementation factors and the success of the warehouse. The results from a Partial Least Squares analysis of the data identified significant relationships between the system quality and data quality factors and perceived net benefits. It was found that management support and resources help to address organizational issues that arise during warehouse implementations; resources, user participation, and highly-skilled project team members increase the likelihood that warehousing projects will finish on-time, on-budget, with the right functionality; and diverse, unstandardized source systems and poor development technology will increase the technical issues that project teams must overcome. The implementation's success with organizational and project issues, in turn, influence the system quality of the data warehouse; however, data quality is best explained by factors not included in the research model.

An empirical investigation of the factors affecting data warehousing success

The Technology Acceptance Model (TAM) represents an important theoretical contribution toward understanding IS usage and IS acceptance behaviors. However, as noted by several IS researchers, TAM is incomplete in one important respect: it doesn't account for social influence in the adoption and utilization of new information systems. Davis (1986) and Davis et al. (1989) noted that it is important to account for subjective norm (SN), the construct denoting social influence. However, they observed that the conceptualization of SN based on TRA (Theory of Reasoned Action) has theoretical and psychometric problems. Specifically, they observed that it is difficult to distinguish if usage behavior is caused by the influence of referents on one's intent or by one's own attitude. They suggested that this problem may be circumvented by using an alternative theoretical basis for conceptualizing SN, specifically in terms of Kelman's (1958, 1961) processes of social influence (compliance, identification and internalization). Within the context of organizational enterprisewide implementation and adoption of collaboration and communication technologies, this study establishes theoretical and empirical bases for the above conceptualization originally suggested by Davis and his colleagues. The construct of social influence is operationalized in terms of Kelman's processes of internalization, identification and compliance. Analyses of field study data provide evidence of the reliability and validity of the proposed constructs, factor structures and measures. The findings enable future researchers to account for social influence in further investigating TAM.

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Extending the technology acceptance model to account for social influence: theoretical bases and empirical validation

Surveys that require users to evaluate or make judgments about information systems and their effect on specific work activities can produce misleading results if respondents do not interpret or answer questions in the ways intended by the researcher. This paper provides a framework for understanding both the cognitive activities and the errors and biases in judgment that can result when users are asked to categorize a system, explain its effects, or predict their own future actions and preferences with respect to use of a system. Specific suggestions are offered for wording survey questions and response categories so as to elicit more precise and reliable responses. In addition, possible sources of systematic bias are discussed, using examples drawn from published IS research. Recommendations are made for further research aimed at better understanding how and to what extent judgment biases could affect the results of IS surveys.

User Response Data: The Potential for Errors and Biases

The article reviews the book “Managing Complexity in High Technology Organizations,” edited by Mary Ann Von Glinow and Susan Albers Mohrman.

Managing Complexity in High Technology Organizations

Prior research on technological frames indicates that many of the difficulties associated with systems implementation stem from differences in the meanings users, managers, and system developers attribute to automation projects. Although the concept of technological frames has been used to explore the bases for intergroup conflict during implementation, it is also a useful device for probing more deeply into the effects complex systems have on users' perceptions of their work and the role-altering effects of new technologies. Drawing upon personal construct theory and job characteristics theory, we adapted the repertory grid technique to explore the technology-in-use frames of a group of occupationally certified fingerprint technicians (FPTs). Our investigation reveals the important role the FPTs' occupationally defined values and norms played in structuring their existing work practices and the tensions produced by organizationally mandated efforts to restructure the logic of their expertise-based hierarchies. These insights illuminate the effects work redesign had on the FPTs' task environment, the process logic that guided specific work practices, and the roles defined by their expertise-based hierarchies, providing a basis for understanding the FPTs' unanticipated reactions to the automation of their work.

/pdf/through-the-eyes-of-experts-a-sociocognitive-perspective-on-u34bq18j91.pdf

Through the eyes of experts: a sociocognitive perspective on the automation of fingerprint work

A model of end-user computing policy: Context, process, content and compliance

Problems can arise in decentralized organizations when usage-based chargeback systems are implemented to control computing resources. A case study of a company that is changing from negotiated pricing to full cost pricing illustrates the fact that concerns about fairness can arise not only with respect to specific characteristics of the chargeback system (e.g., understandability, controllability), but also as a result of central management policies governing internal transactions between the users and MIS. In particular, this examination identifies three factors that affect the fairness perceptions of autonomous divisional managers: (1) a high degree of interdependence between user divisions and MIS such that the behavior of MIS could have a significant impact on divisional performance; (2) restrictions on divisional managers' freedom to purchase computer services from external sources; and (3) the tendency for full cost to exceed market prices early in the life of a data center. A dual pricing approach may be an interim solution to reduce conflict and improve user perceptions of fairness.

Ellen M. Hufnagel

Papers

User Response Data: The Potential for Errors and Biases

Managing Complexity in High Technology Organizations

Through the eyes of experts: a sociocognitive perspective on the automation of fingerprint work

A model of end-user computing policy: Context, process, content and compliance

Perceived chargeback system fairness in decentralized organizations: an examination of the issues