Survey research is believed to be well understood and applied by management information systems (MIS) scholars. It has been applied for several years and it has precise procedures which, when followed closely, yield valid and easily interpretable data. Our assessment of the use of survey research in the MIS field between 1980 and 1990 indicates that this perception is at odds with reality. Our analysis indicates that survey methodology is often misapplied and is plagued by five important weaknesses: (1) single-method designs where multiple methods are needed, (2) unsystematic and often inadequate sampling procedures, (3) low response rates, (4) weak linkages between units of analysis and respondents, and (5) overreliance on cross-sectional surveys where longitudinal surveys are really needed. Our assessment also shows that the quality of survey research varies considerably among studies of different purposes: explanatory studies are of good quality overall, exploratory and descriptive studies are of moderate to poor quality. This article presents a general framework for classifying and examining survey research and uses this framework to analyze the usage of survey research conducted in the past decade in the MIS field. In an effort to improve the quality of survey research, this article makes specific recommenoations that directly address the major problems highlighted in the review.

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Survey research methodology in management information systems: an assessment

SURVEY RESEARCH METHODOLOGY IN MANAGEMENT INFORMATION SYSTEMS: AN ASSESSMENT Alain Pinsonneault Ecole des Hautes Etudes Commerciales 5255 Decelles Avenue Montreal, Quebec Canada H3T 1V6 and Kenneth L. Kraemer Graduate School of Management University of California Irvine, California U.S.A. 92717 Working Paper #URB-022 The authors would like to thank the participants of the 1991 Queen's-HEC workshop and two anonymous reviewers and the Editor in chief of JMIS for their helpful comments on an earlier version of this paper. This study was supported financially by Ecole des Hautes Etudes Commerciales de Montreal and the University of California at Irvine.

Survey Research Methodology in Management Information Systems: An Assessment

There is widespread agreement among researchers that system usage, defined as the utilization of information technology IT by individuals, groups, or organizations, is the primary variable through which IT affects white collar performance. Despite the number of studies targeted at explaining system usage, there are crucial differences in the way the variable has been conceptualized and operationalized. This wide variation of system usage measures hinders the efforts of MIS researchers to compare findings across studies, thus impeding the accumulation of knowledge and theory in this area.

The purpose of this paper is to address conceptual as well as methodological issues related to measuring system usage. First, via LISREL measurement modeling techniques, we compare subjective and objective measures of system usage, namely, self-reported versus computer-recorded measures. Next, using a modified form of Davis' Technology Acceptance Model TAM as a nomological net, we test the nomological validity of these system usage constructs and measures.

Results of the LISREL measurement and nomological net analysis suggest that system usage should be factored into self-reported system usage and computer-recorded system usage. Contrary to expectations, these constructs do not appear to be strongly related to each other. Moreover, while self-reported measures of system usage are related to self-reported measures of TAM independent variables, objective, computer-recorded measures show distinctly weaker links.

In the face of such counter-evidence, it is tempting to argue that research that has relied on subjective measures of system usage for example, research confirming TAM may be artifactual. There are several alternative explanations, though, that maintain the integrity of TAM and studies that measure system usage subjectively. These alternative explanations suggest directions for further research as well as new approaches to measurement.

Measuring System Usage: Implications for IS Theory Testing

Supporting Business Decision-Making Gaining Competitive Advantage with Decision Support Systems Analyzing Business Decision Processes Designing and Developing Decision Support Systems Designing and Evaluating DSS User Interfaces Understanding DSS Architecture, Networking, and Security Issues Implementing Communications-Driven and Group Decision Support Systems Building Data and Document-Driven Decision Support Systems Building Knowledge-Driven DSS and Mining Data Building Model-Driven Decision Support Systems Building Web-Based and Inter-Organizational Decision Support Systems Evaluating Decision Support System Projects Decision Support Audit Questions Decision Support Systems Glossary Reference and Selected Bibliography Index

Decision Support Systems: Concepts and Resources for Managers

Information systems are becoming increasingly critical to the daily operations and success of many firms. This, combined with the rising investments in design and development of these systems, make implementation a high priority research topic. Although information systems implementation has been a topic of interest to researchers over the past two decades, the extent to which the existing body of research reflects substantial and cumulative development is not entirely clear.The objective of this study is to conduct a rigorous and quantitative review of the empirical DSS implementation literature as a basis for providing guidelines for implementation management and conduct of future research. Meta-analysis of 144 findings from3 3 studies indicates that user-situational variables (involvement, training and experience) are more important than psychological factors to DSS implementation success and that user-situational variables can improve the implementation success by as much as 30 percent. Furthermore, the meta-analytic findings regarding the methodological characteristics of studies provide useful insights for the design of future research studies of implementation. The findings also allow us to put into perspective the incremental contribution of additional substantive and empirical studies in this area. Additionally, several specific domains (e.g., construct validation research on user involvement and causal modeling) might profit most form future research efforts.

Revisiting DSS implementation research: a meta-analysis of the literature and suggestions for researchers

Decision Support Systems (DSS) have become an increasingly important type of computer-based information system. However, there has been limited research on management's role in DSS approval and administration. Because of this, the authors recently investigated eighteen decision support systems and report the findings here. The specific areas explored include motivations for developing a DSS, methods for evaluating the desirability of creating a DSS, planning and organizing for building a DSS, techniques for reviewing and controlling DSS projects, and managing a DSS as an organizational entity.

Management's role in the approval and administration of decision support systems

:Managerial involvement in information systems has often been suggested. Decision support systems (dss) may well represent the information system category most demanding of management’s time. In this paper the author proposes a framework for investigating management involvement in dss. Next, a report is provided of findings of how, when, and why management involvement in dss is required. These findings are based upon an examination of eighteen dss cases and of the existing literature. Last, the framework is compared with the “conventional wisdom’’ in the existing literature.

A framework for the examination of management involvement in decision support systems

Decisionsupport systems are one of the latest developments incomputer-based information systems. There are a variety of indications that their development differs in important ways from othertypes of information systems. This article reports the findings of an investigation of how 18 decision support systems were developed. Six major areas were explored: (1) the nature of the developmental approach; (2) user involvement in system development; (3) the time required for system development; (4) the incorporation of the decision maker's style in the system; (5) the role of information systems and operations research/management science personnel in the developmental effort; and (6) specific procedures and techniques used in system development Introduction should be built, used, and modified as needed. The system should reflect the user's decision-maldng style. Beginning in the late 19604 there appeared a type of The user should be an integral member of the developcomputer-based information system (CBIS) with mentteam The systemshould be builtquickly, usingthe capabilities and characteristics different from previous latest computer hardware and software technology. systems. Unlike electronic data processing (EDP) or Developmentshouldbeinthehandsofusersratherthan management information systems (MIS), these decision CBIS professionals support systems (DSS) have had a significantimpacton semistructured and unstructured decision making in a These generalizations have been applied to a number growing number of organizations. They emerged in reof decision support systems. however, it has been the sponse to managers' and others' needs for decision authors' experience that some decision support systems support, evolving computer hardware and software are developed in ways that differ considerably from the technology, and a growing understanding of what is regeneralizations Because of this, the authors conducted quired in order to support difficult decisions. a survy of 18 decision supportsystems to determine how they were developed. Six major areas were explored: (1) Early in the evolution of DSS it became apparent that the nature of the development:al approach; (2) user traditionalDBIS developmental methodologies, suchas involvement in system development (3) the time required the systems development life cycle, were often inapfor system development; (4) the incorporation of the propriate for DSS. The decision-making environment decisionmaker's style inthe system; (5) the role ofCBIS changes too rapidly to allow a formal set of system and operations research/management science personnel specifications to exist for long. Decision makers are in the developmental effort; and (6) specific procedures unable to specify in advance exactly what their inforand techniques used in system development The survey's mation needs are. CBIS professionals are unable to findings provide an expanded and enhanced perspective make timely delivery of the types of systems needed. of how decision support systems are currently being developed. Also provided is a discussion of what factors Alternative development methodologies wem suggested appear to influence DSS development Since all the under a variety of names: adaptive, evolutionary, DSSwerereportedasbeingsuccessfulbytheirusersthe heuristic, and middle out These methodologies contain findings and discussion may provide helpsulinsights for several elements in common Small tentative systems DSS developers.

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Current Practices in the Development of Decision Support Systems

https://www.jstor.org/stable/info/40397858

Jack T. Hogue

Papers

Management's role in the approval and administration of decision support systems

A framework for the examination of management involvement in decision support systems

Current Practices in the Development of Decision Support Systems

A framework for the examination of management involvement in decision support systems

An examination of decision-makers' utilization of decision support system output