DISCOVERY AND REPRESENTATION OF CAUSAL RELATIONSHIPS IN MIS RESEARCH - A METHODOLOGICAL FRAMEWORK

The lack of theories and methodological weakness have been pointed out as two distinct but related problems in empirical management informat ion systems (MIS) research. Reinforcing the existing belief that too m uch attention has been devoted to ''what'' as opposed to ''why'' or '' when'' relationships exist, this paper focuses on a subset of model bu ilding and methodology issues involving the systematic discovery and r epresentation of causal relationships. Our analysis of the existing em pirical MIS literature reveals the need to build richer causal models, to increase the flexibility of model representation, to integrate the isolated worlds of pure latent and pure manifested variables, and to provide a fighter linkage between the exploratory and confirmatory res earch phases. Based on philosophy of science and advances in the field s of experimental economics and sociology, we propose a foundation for developing richer models by explicitly considering the exogeneity and endogeneity of constructs and a manipulative account of causality, an d by recognizing the role of incentives, agent, and organizational cha racteristics in MIS models. Since richer models require more flexible tools and techniques, the paper describes the representational shortco mings and statistical pitfalls of factor-analytic methods commonly dep loyed in empirical research. We suggest that weak exploratory phase to ols and approaches may allow violations of causal assumptions to pass undetected to the confirmatory phase. Since confirmatory tools like LI SREL also make factor-analytic assumptions, these violations are not l ikely to be detected at the confirmatory phase either. We propose usin g TETRAD, a non-parametric tool, at the exploratory phase for its abil ity to accommodate a wide variety of causal models. The findings are s ummarized within an integrated framework, which enhances the likelihoo d of discovering relationships through richer theoretical support and powerful exploratory analysis.