Agent-Based Organizational Ecologies: A Generative Approach to Market Evolution

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

Social scientists have long studied the evolution of market structures and have tried to explore the internal mechanisms of industrial dynamics. Market evolution has attracted the attention of researchers from fields such as industrial organization, economic sociology, and management. The tradition in industrial organization has focused on empirically understanding the relationship between market structure, firm’s conduct, and performance. Economic sociologists have explored effects on firms’ entry and exit rates and have developed explanatory mechanisms about market formation according to the interplay of such entry and exit rates. Management scholars have used the so-called NK fitness landscape imagery to relate firm-level adaptation features to industry dynamics. Nonetheless, researchers in these distinct fields have come to realize that a better understanding of market evolution would imply considering real (i.e., boundedly rational) firm behavior, out-of-equilibrium processes, and time dynamics. Computational approaches have emerged naturally as a way to explore new theoretical frameworks by simultaneously inspecting the joint effect of adaptive features of individual firms and market selection forces, among others. In this chapter, I review the implications of using agent-based computational modeling to study market structures as emergent properties of the interplay between entry, exit, and adaptation of heterogeneous firms. This emphasizes an abductive approach, in addition to the traditional deductive and inductive ones, to study market processes.
Original languageEnglish
Title of host publication Pathways Between Social Science and Computational Social Science
EditorsTamás Rudas, Gábor Péli
PublisherSpringer
Pages179-196
ISBN (Electronic)978-3-030-54936-7
ISBN (Print)978-3-030-54935-0
DOIs
StatePublished - 2021

Publication series

NameComputational Social Sciences
PublisherSpringer
ISSN (Print)2509-9574
ISSN (Electronic)2509-9582

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