Preservation of organizational memory becomes increasingly important to organizations as it is recognized that experiential knowledge is a key to competitiveness. With the development and widespread availability of advanced information technologies (IT), information systems become a vital part of this memory. We analyze existing conceptualizations and task-specific instances of IT-supported organizational memory. We then develop a model for an organizational memory information system (OMIS) that is rooted in the construct of organizational effectiveness. The framework offers four subsystems that support activities leading to organizational effectiveness. These subsystems rest on the foundation of five mnemonic functions that provide for acquisition, retention, maintenance, search, and retrieval of information. We then identify the factors that will limit the success of OMIS implementation, although full treatment of this issue is outside the scope of the paper. To initiate a research agenda on OMIS, we propose an initial contingency framework for OMIS development depending on the organization's environment and its life-cycle stage, and discuss the relationships between an OMIS and organizational learning and decision making.

In a survey of IS instruments spanning the years 1973 to 1988 (Zmud and Boynton [Zmud, R. W., A. C. Boynton. 1991. Survey measures and instruments in MIS inventory and appraisal. K. I. Kraemer, ed. The Information Systems Research Challenge Survey Research Methods, Vol. 3. Harvard Business School, Boston, 149–180.]), Doll and Torkzadeh's (Doll, W. J., G. Torkzadeh. 1988. The measurement of end-user computing satisfaction. MIS Quart. (June) 259–274.) 12-item End-User Computing Satisfaction instrument was reported as one of three IS instruments that met conditions to qualify as “well developed.” Recently, Etezadi-Amoli and Farhoomand (Etezadi-Amoli, J., A. F. Farhoomand. 1991. Issues and opinions on end-user computing satisfaction. MIS Quart. (March) 1–5.) questioned the validity of these measures. Part of their critique centered on the poor model fit obtained in a re-analysis using LISREL. While other potentially valid points were raised by Etezadi-Amoli and Farhoomand's critique, this report focuses only on their use of confirmatory factor analysis. In our re-analyses of Doll and Torkzadeh's original covariance measures, we show how model fit is extremely dependent on model specification. While still maintaining the same number of constructs and respective measures, we demonstrate how two alternatives to the original model analyzed by Etezadi-Amoli and Farhoomand can result in models with acceptable fits.