Organizational decision making as rule following

Abstract

Introduction In recent years, studies of decision making have witnessed an increasing sophistication in modeling decision situations. Since the early days of simple choice-based probabilistic models, we have witnessed the evolution of complex statistical techniques incorporating uncertainty, multiple objectives, n -players, dynamic games, and Bayesian models. These models introduce additional factors in decision-making processes and in this sense move closer to real decision situations. Nonetheless, they put enormous demands on the decision makers to collect and make use of information and to adopt complex decision rules. In contrast, there is mounting evidence that individuals and organizations tend to adopt simple rules and heuristics in making decisions. Satisficing rather than optimizing has long been recognized as a basic rule regulating organizational decisions (Simon, 1957). Organizations often adopt simple rules in making decisions about R&D investment (Dosi, 1988). Predictable behaviors (i.e., simpler decisions) are induced precisely because of the complexity of the decision situation (Heiner, 1983). There is also evidence that simple rules often outperform complex models in game experiments (Axelrod, 1984). Organizational decision making is often governed by stable rules, and much of organizational decision making can be characterized as rule-following behavior. “Action is often based more on identifying the normatively appropriate behavior than on calculating the return expected from alternative choices” (March & Olsen, 1989, p. 22). In this chapter, I explore the basis of rule-following behavior and its implications for understanding organizational decision making.

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