Search results

The papers collected in this volume celebrate the 40th anniversary of “A Garbage Can Model of Organizational Choice” – one of the most influential and sustained attempts to represent organizational decision-making processes in a way that accounts for generally recognized but hard to accept features of organizational life. In our overview of the volume we emphasize ways in which the garbage can model (GCM) differs from more generally accepted models of organizational decision making. We suggest that future progress in linking the GCM to specific empirical settings might be facilitated by attempts to model explicitly the interdependencies connecting participants, problems, solutions, and decision opportunities in organizations. We discuss examples of current work in which this strategy is followed in a way that is consistent with the original spirit of the model. We present the overall organization of the volume and discuss how the various chapters contribute to the further development of organizational research inspired by ideas contained in the original GCM and in some of its more recent variants and critiques.

We build three stochastic models of garbage can processes in an organization populated by boundedly rational agents. Although short-run behavior in our models can be quite chaotic, they generate systematic, testable predictions about patterns of organizational choice. These predictions are determined, in fairly intuitive ways, by the degree of preference conflict among agents in the organization, by their patterns of attention, and by their tendencies to make errors. We also show that nontrivial temporal orders can arise endogenously in one of our models, but only when some form of intentional order, based on agents’ preferences, is also present.

In this study, the authors unpack the micro-level processes of knowledge accumulation (experiential learning) and knowledge application (problem solving) to examine how task allocation structures influence organizational learning. The authors draw on untapped potential of the classical garbage can model (GCM), and extend it to analyze how restrictions on project participation influence differentiation and integration of organizational members’ knowledge and consequently organizational efficiency in solving the diverse, changing problems from an uncertain task environment. To isolate the effects of problem or knowledge diversity and experiential learning, the authors designed three simulation experiments to identify the most efficient task allocation structure in conditions of (1) knowledge homogeneity, (2) knowledge heterogeneity, and (3) experiential learning. The authors find that free project participation is superior when the members’ knowledge and the problems they solve are homogenous. When problems and knowledge are heterogeneous, the design requirement is on matching specialists to problem types. Finally, the authors found that experiential learning creates a dynamic problem where the double duty of adapting the members’ specialization and matching the specialists to problem types is best solved by a hierarchic structure (if problems are challenging). Underlying the efficiency of the hierarchical structure is an adaptive role of specialized members in organizational learning and problem solving: their narrow but deep knowledge helps the organization to adapt the knowledge of its members while efficiently dealing with the problems at hand. This happens because highly specialized members reduce the necessary scope of knowledge and learning for other members during a certain period of time. And this makes it easier for the generalists and for the organization as a whole, to adapt to unforeseen shifts in knowledge demand because they need to learn less. From this nuanced perspective, differentiation and integration may have a complementary, rather than contradictory, relation under environmental uncertainty and problem diversity.

This chapter explores geopolitics, garbage cans, the need for interdisciplinary insight, and the lures and limitations of one-sided mono-disciplinary conceptual models in understanding strategic decision making. We argue that a combination of the garbage can model and Nathan Leites’ psycho-cultural approach to decision making might be useful in giving insights for events and for organizational behavior. As a decision making case, we consider the 1941 decision of the Empire of Japan to declare war on the Allied Powers. We find that there could be useful lines of integration between the garbage can framework and other perspectives in geopolitical decision making. In using a historical example to illustrate the possible integration, we argue that there are inherent limits to single-model decision making approaches. Developing interdisciplinary frameworks for understanding foreign policy decision making may lead to better insights in real-world processes and seems like a step in a fruitful direction.