Hostname: page-component-586b7cd67f-t7fkt Total loading time: 0 Render date: 2024-11-30T15:55:46.516Z Has data issue: false hasContentIssue false
  • English
  • Français

Agent-based models and hypothesis testing: an example of innovation and organizational networks

Published online by Cambridge University Press:  26 April 2012

Allen Wilhite  and
Eric A. Fong
Allen Wilhite*
Affiliation:
Department of Economics and Information Systems, University of Alabama in Huntsville, Huntsville, AL, USA; e-mail: [email protected]
Eric A. Fong*
Affiliation:
Department of Management and Marketing, University of Alabama in Huntsville, Huntsville, AL, USA; e-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Hypothesis testing is uncommon in agent-based modeling and there are many reasons why (see Fagiolo et al. (2007) for a review). This is one of those uncommon studies: a combination of the new and old. First, a traditional neoclassical model of decision making is broadened by introducing agents who interact in an organization. The resulting computational model is analyzed using virtual experiments to consider how different organizational structures (different network topologies) affect the evolutionary path of an organization's corporate culture. These computational experiments establish testable hypotheses concerning structure, culture, and performance, and those hypotheses are tested empirically using data from an international sample of firms. In addition to learning something about organizational structure and innovation, the paper demonstrates how computational models can be used to frame empirical investigations and facilitate the interpretation of results in a traditional fashion.

Type
Articles
Information
The Knowledge Engineering Review , Volume 27 , Special Issue 2: Agent-Based Computational Economics , 26 April 2012 , pp. 221 - 238
Copyright
Copyright © Cambridge University Press 2012

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Acs, Z. J., Audretsch, D. B. 1988. Innovation in large and small firms: an empirical analysis. The American Economic Review 78(4), 678–690.Google Scholar
Axtell, R., Axelrod, R., Epstein, J., Cohen, M. 1997. Aligning simulation models: a case study and results. In The Complexity of Cooperation, Axelrod, R. (ed.). Princeton University Press, 181–205.Google Scholar
Burns, T., Stalker, G. M. 1968. The Management of Innovation. Tavistock Publications.Google Scholar
Carley, K. M., Lin, Z. 1997. Organizational decision making and error in a dynamic task environment. Journal of Mathematical Sociology 100, 720–749.Google Scholar
Chang, M., Harrington, J. E. 2005. Discovery and diffusion of knowledge in an endogenous social network. American Journal of Sociology 110, 937–976.CrossRefGoogle Scholar
Cohen, W. M., Klepper, S. 1996. A reprise of size and R & D. The Economic Journal 106, 925–951.CrossRefGoogle Scholar
Denison, D. R., Mishra, A. K. 1995. Toward a theory of organizational culture and effectiveness. Organization Science 6(2), 204–223.CrossRefGoogle Scholar
Fagiolo, G., Windrum, P., Moneta, A. 2007. A critical guide to empirical validation of agent-based models in economics: methodologies, procedures, and open problems. Computational Economics 30(3), 195–226.CrossRefGoogle Scholar
Harrington, J. E. 1998. The social selection of flexible and rigid agents. The American Economic Review 88(1), 63–82.Google Scholar
Harrison, J. R., Carroll, G. R. 2006. Culture and Demography in Organizations. Princeton University Press.CrossRefGoogle Scholar
Jackson, M. 2005. A survey of models of network formation: stability and efficiency. In Group Formation in Economics: Networks, Clubs, and Coalitions. Demange, G. and Wooders, M. (eds). Cambridge University Press, 11–57.Google Scholar
Mansfield, E. 1981. Composition of R & D expenditures: relationship to size of firm, concentration and innovative output. Review of Economics and Statistics 63, 610–615.CrossRefGoogle Scholar
March, J. G. 1991. Exploration and exploitation in organizational learning. Organizational Science 2(1), 71–87.CrossRefGoogle Scholar
Menon, A., Bharadwaj, S. G., Adidam, P. T., Edison, S. W. 1999. Antecedents and consequences of marketing strategy making: a model and a test. Journal of Marketing 63(April), 18–40.CrossRefGoogle Scholar
Nakata, C., Sivakumar, K. 1996. National culture and new product development: an integrative review. Journal of Marketing 60, 61–72.CrossRefGoogle Scholar
O'Reilly, C. A., Chatman, J. A. 1996. Culture as social control: corporations, culture and commitment. In Research in Organizational Behavior, Staw, B. M. and Cummings, L. L. (eds). JAI Press, 18, 157–200.Google Scholar
O'Reilly, C. A., Chatman, J., Caldwell, D. F. 1991. People and organizational culture: a profile comparison approach to assessing person–organization fit. Academy of Management Journal 34, 487–516.CrossRefGoogle Scholar
Ravasi, D., Schultz, M. 2006. Responding to organizational identity threats: exploring the role of organizational culture. Academy of Management Journal 49, 433–458.CrossRefGoogle Scholar
Scherer, F. M. 1982. Inter-industry technology flows and productivity growth. Review of Economics and Statistics 64, 627–634.CrossRefGoogle Scholar
Scherer, F. M. 1992. Schumpeter and plausible capitalism. Journal of Economic Literature 30(3), 1416–1433.Google Scholar
Schumpeter, J. A. 1942. Capitalism, Socialism and Democracy. Harper.Google Scholar
Smircich, L. 1983. Concepts of culture and organizational analysis. Administrative Science Quarterly 28, 339–359.CrossRefGoogle Scholar
Song, M. X., Parry, M. E. 1997. The determinants of Japanese new product success. Journal of Marketing Research 34, 64–76.CrossRefGoogle Scholar
Song, M. X., Souder, W. E., Dyer, B. 1997. A causal model of the impact of skills, synergy, and design sensitivity on new product performance. Journal of Product Innovation Management 14(2), 88–101.CrossRefGoogle Scholar
Sørensen, J. B. 2002. The strength of corporate culture and the reliability of firm performance. Administrative Science Quarterly 47, 70–91.CrossRefGoogle Scholar
Souder, W. 1996. Interprod: An International Study of New Product Innovation. Center for the Management of Science and Technology (CMOST), University of Alabama.Google Scholar
Teece, D. J. 1996. Firm organization, industrial structure and technological innovation. Journal of Economic Behavior and Organization 31, 193–224.CrossRefGoogle Scholar
Vriend, N. J. 2006. CE models of endogenous interactions. In Handbook of Computational Economics: Agent-Based Computational Economics, Tesfatsion, L. and Judd, K. L. (ed.). North Holland, 1047–1079.Google Scholar
Watts, D., Strogatz, S. H. 1998. Collective dynamics of ‘small-world’ networks. Nature 393, 440–442.CrossRefGoogle ScholarPubMed
Wilhite, A. 2006a. Economic Activity on Fixed Networks. In Handbook of Computational Economics: Agent – Based Computational Economics, Tesfatsion, L. and Judd, K. L. (eds). North Holland, 1012–1045.Google Scholar
Wilhite, A. 2006b. Protection and social order. Journal of Economic Behavior and Organization 61, 691–709.CrossRefGoogle Scholar
Young, H. P., Burke, M. A. 2001. Competition and custom in economic contracts: a case study of Illinois agriculture. American Economic Review 91, 559–573.CrossRefGoogle Scholar