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Organization of Innovation in a Multi-Unit Firm: Coordinating Adaptive Search on Multiple Rugged Landscapes

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  • Myong-Hun Chang
  • Joseph E Harrington

Abstract

In Chang and Harrington (2000a) a computational model of a multi-unit firm is developed in which unit managers continually search for better practices Search takes place over a rugged landscape defined over the space of unit practices There it is shown that a more centralized organization is optimal when markets are not too different and the horizon is not too long The robustness of those results are explored here with respect to the shape of the landscape In particular we find that centralization does better when the search space is larger and there is a stronger correlation in a consumer's preferences across different dimensions A richer description of comparative dynamics is also provided

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Bibliographic Info

Paper provided by The Johns Hopkins University,Department of Economics in its series Economics Working Paper Archive with number 442.

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Date of creation: Nov 2000
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Handle: RePEc:jhu:papers:442

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Cited by:
  1. Chang, Myong-Hun & Harrington, Joseph Jr., 2006. "Agent-Based Models of Organizations," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 26, pages 1273-1337 Elsevier.
  2. Jason Barr & Nobuyuki Hanaki, 2005. "Firm Structure, Search and Environmental Complexity," Working Papers Rutgers University, Newark 2005-007, Department of Economics, Rutgers University, Newark.
  3. Guido Fioretti, 2005. "Agent-Based Models of Industrial Clusters and Districts," Urban/Regional 0504009, EconWPA.

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