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Co-evolutionary market dynamics in a peaked resource space

Co-evolutionary market dynamics in a peaked resource space. César E. García-Díaz Arjen van Witteloostuijn Department of International Economics & Business Rijks universiteit Groningen (RuG) The Netherlands. Artificial Economics 2006. September 15-16, 2006. Aalborg, Denmark. Agenda.

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Co-evolutionary market dynamics in a peaked resource space

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  1. Co-evolutionary market dynamics in a peaked resource space César E. García-Díaz Arjen van Witteloostuijn Department of International Economics & Business Rijksuniversiteit Groningen (RuG) The Netherlands Artificial Economics 2006. September 15-16, 2006. Aalborg, Denmark.

  2. Agenda 1º. Theoretical background 2º. Research questions 3º. The model 4º. Findings 5º. Conclusions

  3. 1o. Theoretical background Organizational Ecology (OE) tries to explain the evolution organizational populations from a demographic approach: studying founding and mortality rates (Hannan & Freeman, 1989). OE focus on population-level adaptation (i.e. when individual organizations that are not able to fit the new environmental conditions are replaced by new ones, so that a firm-level selection process takes place). For OE scholars, selection is more dominant than adaptation.

  4. 1o. Theoretical background • Co-evolutionary processes have recently captured attention from social scientists. Some representative works are: • Empirical studies design in organization theory (Lewin and Volberda 2001) • Price dispersion modeling in the Marseille fish market (Kirman and Vriend 2001) • Joint ventures (Inkspen and Currall 2004) • Strategic Alliances (Koza and Lewin 1998) • Emergence of market dominance (Harrington and Chang 2005)

  5. 1o. Theoretical background • OE’s resource-partitioning theory (RP) explains market partitioning (between specialist and generalist organizations) under scale economies, unimodal resource spaces and enough consumer heterogeneity (Carroll, 1985). • RP Predictions: As concentration increases as a consequence of scale dominance of generalist organizations at the market center, the life chances of them decrease but those of specialists increase. Generalists’ total space gets contracted (Carroll and Hannan 2000).

  6. 1o. Theoretical background • Two other positive effects on specialists’ survival chances: • The increase of the number of dimensions of the resource space opens up space for small organizations (Péli and Nooteboom 1999) • Flattening of the resource space (Carroll and Hannan 1995)

  7. 1o. Theoretical background: Resource-partitioning theory + High amount of consumers A A rt < rm.e.s. rt+t’ = rm.e.s. Scale resource space A R R time t, low concentration (generalists only) time t+t’, high concentration (entry of specialists) - Low amount of consumers Carroll (1985), Carroll and Hannan (1995, 2000)

  8. 2o. Research questions • If preferences are assumed to be fixed over time, will the market center’s scale economies / center-periphery niche-width diseconomies be enough to produce the generalists’ space contraction? • What is the effect of consumer mobility on firm’s scale advantages? • What is the effect of consumer mobility on specialists’ proliferation?

  9. 3o. The model: The resource space

  10. 3o. The model: Firm behavior Production costs Niche-width costs Large-scale firm Small-scale firm

  11. 3o. The model: Consumer behavior Consumer’s utility function Niche overlap

  12. 3o. The model: Firm-consumer dynamics • Firm entry drawn from a negative binomial distribution, according to empirical estimates of OE’s density-dependence model (Carroll and Hannan 2000) • Calculation of firm’s expected demand at entry: • Firms move to the market location where consumers are more abundant • Consumers mobility takes effect according to i) closest matched taste and ii) highest expected utility

  13. 4o. Findings: Consumer immobility *30 simulation runs with 6 different parameter combinations

  14. 4o. Findings: Match-improving consumer mobility *30 simulation runs with 6 different parameter combinations

  15. 4o. Findings: Utility-maximizing consumer mobility *30 simulation runs with 6 different parameter combinations

  16. 4o. Findings: Effects on large-scale firms’ space *Total of 90 simulation runs with 6 different parameter combinations. Experiment 1 (left), 2 (center) and 3 (right)

  17. 5o. Conclusions • Consumer mobility might diminish the power of scale effects, and eventually it might open up resources to small-scale firms • The contraction of generalist organizations’ total space needs a “demand side” explanation, apart from the “supply side” story brought by OE.

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