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Reconciling Competing Hypotheses from Economics And Sociology

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June 22, 1999AbstractAshkenas, R., D. Ulrich, T. Jick, and S. KerrGalbraith, F. R., E. E. Lawler III, and AssociatesPrietula, M. J., K. M. Carley, and L. GasserTable 1. Contrasting the perspectivesTable 2. Summary of empirical regularities across levels of analysis and academic fields(Price 1961;1963)(Crane 1972)(Madsen )(Knott and Bryce 1998)(Price 1961;1963)(Rogers 1962; 1995)(Price 1961; 1963)(Hagerstrand 1952)Sociology literatureGeographic proximity-Knowledge is more readily shared by entities in close physical proximityEpisodic growthDefer to follow-on: Requires multi-population studyDiminishing returnsKNOWLEDGE DYNAMICS:Reconciling Competing Hypotheses from Economics And Sociology*Anne Marie Knott*The Wharton Schoolof the University of Pennsylvania2023 Steinberg Hall-Dietrich HallPhiladelphia, PA 19104-6370Phone: (215) 573-9628Fax: (215) [email protected] McKelveyAnderson School at UCLA110 Westwood PlazaBox 951481Los Angeles, CA 90095-1418Phone: (310) 825-7796Fax: (310) [email protected] 22, 1999* Please address all correspondence to the senior author, Anne Marie Knott.The authors would like to thank Dan Levinthal and participants at the Reginald Jones Center seminar series forhelpful comments during development of this research. We would also like to acknowledge financial support fromthe Huntsman Center for Emerging Technologies.KNOWLEDGE DYNAMICS:Reconciling Competing Hypotheses from Economics And SociologyAbstractOur goal is to reconcile competing null hypotheses from sociology and economics with respect to knowledge flow—sociology assumes that knowledge flow is viscous, whereas economics assumes knowledge flows fluidly thereby discouraging investment in its creation. The concern is that the two fields’ attendant prescriptions might cancel one another. Our vehicle for reconciliation is a simulation of knowledge flow that embodies empirical regularities emerging from studies in both fields. Through simulation we find that both fields are partially correct. More importantly we find that the fields’ prescriptions for knowledge growth, rather than canceling one another, actually complement one another. ii1. INTRODUCTIONBoth economics and sociology agree that innovation and human capital formation normally improves social welfare, but they differ in starting assumptions. In general, economics studies knowledge creation—How can public policy create incentives for firms to create new knowledge? Sociology, on the other hand, looks at knowledge diffusion—How can institutions get individuals to share their own knowledge and adopt that of others? Corresponding to these goals, the two fields have opposing null hypotheses regarding the flow of knowledge. In general, economists holdthat knowledge flows freely—the challenge is to impede knowledge flow. In contrast, sociologists generally hold that knowledge is inert—the challenge is to facilitate knowledge flow.The null hypothesis that each field has adopted makes sense given its respective approach to innovation. Economists worry that firms will not invest in knowledge creation if they can not appropriate the returns from those investments. The greatest threat to appropriation is the relative ease with which knowledge can be transferred. Sociologists suspect that organizations will not share knowledge if they derive benefit from controlling it. They also see firms as comprised of boundaries around individuals and subunits that act as barriers to information flow. The problem with the opposing null hypotheses is that they may lead to contrary prescriptions that may potentially offset one another, such that neither innovation nor growth occurs. Thus, it is importantto understand the relative correctness of each field’s null hypothesis. Are economists correct that knowledge flow is fluid, or are sociologists correct that knowledge is inert?We take a step toward resolving the debate by studying the impact of the driving assumptions, given various firm and industry conditions. Our approach begins with harvesting a set of stylized facts or known empirical regularities of knowledge flow from both literatures so as to develop a simple model of knowledge dynamics. We focus on empirical regularities spreading across several fields of research and introduce a computational modeling approach so as to study the dynamics in 1between the extremes of the economists’ and sociologists’ assumptions—the range of dynamics more likely to be of use by managers interested in speeding up human capital appreciation within their firm, but worried about possible increased flow out to competitors. Thus, we try to answer questions regarding the inherent state of knowledge in a firm or an industry and the effects of various stimuli on knowledge growth in firms or in an industry. The method we use is an interacting agent model derived from the “spin glass” family of models frequently used in physics(Fischer and Hertz, 1993).In this article we: (1) highlight the debate; (2) resolve the debate such that research findings from the two literatures may be constructively integrated toward a theory of knowledge dynamics between the two extremes; and (3) provide some new insights that might guide public as well as managerial policy. We begin by reviewing the sociology of science, diffusion, technology economics, and management of technology literatures, setting out the empirical regularities as we go. Then we propose a formal model of knowledge dynamics that we evaluate through computer simulation. We validate the simulation relative to the empirical regularities and then utilize it to explore the dynamics affecting knowledge growth. Results and Discussion follow.2. COMPARING THE PERSPECTIVES2.1 Sociology of Science and OrganizationSociological perspectives on knowledge flow are probably best exemplified by the sociology of science and the study of bureaucratic structure. Sociology of science is concerned with the interrelationship of science and society. How has science influenced values, education, class structure, ways of life, political decisions, and ways of looking at the world? How has society, in turn, influenced the development of science itself (Kaplan, 1964)? Organizational sociology has uncovered significant deleterious effects of bureaucratic structure that inhibit the flow of information across organizational boundaries.2Sociology of science emerged


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