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Agent-based strategizing

journal contribution
posted on 2019-02-11, 09:07 authored by Duncan RobertsonDuncan Robertson
Strategic management is a system of continual disequilibrium, with firms in a continual struggle for competitive advantage and relative fitness. Models that are dynamic in nature are required if we are to really understand the complex notion of sustainable competitive advantage. And new tools are required to tackle challenges of how firms should compete in environments characterized by both exogeneous shocks and intense endogenous competition. A rich history of alternative dynamic models exist in other social and natural sciences, some of which have been incorporated into the strategic management literature, notably the NK series of models. Yet there is a whole history of models from systems models, organizational ecology, and general fitness landscape models that can be converted to agent-based models and used for the study of strategic management. Agent-based modelling of firms’ strategies offers an alternative analytical approach, where individual firm or component parts of a firm are modelled, each with their own strategy. Where traditional models can assume homogeneity of actors, agent-based models simulate each firm individually. This allows experimentation of strategic moves, which is particularly important where reactions to strategic moves are non-trivial. This Element introduces agent-based models and their use within management, reviews the influential NK suite of models, and offers an agenda for the development of agent-based models in strategic management.

History

School

  • Business and Economics

Department

  • Business

Published in

Cambridge Elements

Citation

ROBERTSON, D.A., 2019. Agent-based strategizing (Elements in Business Strategy). Cambridge: Cambridge University Press. doi:10.1017/9781108767835.

Publisher

Cambridge University Press © Duncan A. Robertson

Version

  • AM (Accepted Manuscript)

Acceptance date

2018-12-24

Publication date

2019

Notes

This paper is closed access.

ISBN

9781108767835

ISSN

2515-0685

eISSN

2515-0693

Language

  • en

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