Organizational learning has many virtues, virtues which recent writings in strategic management have highlighted. Learning processes, however, are subject to some important limitations. As is well-known, learning has to cope with confusing experience and the complicated problem of balancing the competing goals of developing new knowledge (i.e., exploring) and exploiting current competencies in the face of dynamic tendencies to emphasize one or the other. We examine the ways organizations approach these problems through simplification and specialization and how those approaches contribute to three forms of learning myopia, the tendency to overlook distant times, distant places, and failures, and we identify some ways in which organizations sustain exploration in the face of a tendency to overinvest in exploitation. We conclude that the imperfections of learning are not so great as to require abandoning attempts to improve the learning capabilities of organizations, but that those imperfections suggest a certain conservatism in expectations.

https://www.jstor.org/stable/pdfplus/2486499.pdf

The myopia of learning

Myopia of learning

Contemporary theories of politics tend to portray politics as a reflection of society, political phenomena as the aggregate consequences of individual behavior, action as the result of choices based on calculated self-interest, history as efficient in reaching unique and appropriate outcomes, and decision making and the allocation of resources as the central foci of political life. Some recent theoretical thought in political science, however, blends elements of these theoretical styles into an older concern with institutions. This new institutionalism emphasizes the relative autonomy of political institutions, possibilities for inefficiency in history, and the importance of symbolic action to an understanding of politics. Such ideas have a reasonable empirical basis, but they are not characterized by powerful theoretical forms. Some directions for theoretical research may, however, be identified in institutionalist conceptions of political order.

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The New Institutionalism: Organizational Factors in Political Life

What can computer simulation contribute to the social sciences? Which of the many approaches to simulation would be best for my social science project? How do I design, carry out and analyse the results from a computer simulation? This is a practical textbook on the techniques of building computer simulations to assist understanding of social and economic issues and problems. Interest in social simulation has been growing rapidly worldwide as a result of increasingly powerful hardware and software and also a rising interest in the application of ideas of complexity, evolution, adaptation and chaos in the social sciences. This authoritative book details all the common approaches to social simulation, to provide social scientists with an appreciation of the literature and allow those with some programming skills to create their own simulations.New for this edition is a chapter on how to use simulation as a tool. A new chapter on multi-agent systems has also been added to support the fact that multi-agent modelling has become the preferred approach to simulation. Social scientists in a wide range of fields will find this book an essential tool for research, particularly in sociology, economics, anthropology, geography, organizational theory, political science, social policy, cognitive psychology and cognitive science. It will also appeal to computer scientists interested in distributed artificial intelligence, multi-agent systems and agent technologies.

Simulation for the Social Scientist

Past research has resulted in contradictory findings concerning the effect of risk on decision-making behavior in organizations. This article proposes a model that reconciles these unresolved contradictions by examining the usefulness of placing risk propensity and risk perception in a more central role than has been previously recognized. Based on this analysis, it is posited that risk propensity dominates both the actual and perceived characteristics of the situation as a determinant of risk behavior. Propositions derived from the conceptual model provide an agenda for future research on individual risk behavior in organizational settings.

Reconceptualizing the Determinants of Risk Behavior

What is a model? How do you construct one? What are some common models in the social sciences? How can models be applied in new situations? What makes a model good? Focusing on answers to these and related questions, this multidisciplinary introduction to model building in the social sciences formulates interesting problems that involve students in creative model building and the process of invention. The book describes models of individual choice, exchange, adaptation, and diffusion. Throughout, student participation in analytical thinking is encouraged. Originally published in 1975 by HarperCollins Publishers.

Charles A. Lave

Papers

An introduction to models in the social sciences