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Series:   Elements in Business Strategy

Agent-Based Strategizing

Published online by Cambridge University Press:  17 July 2019

Duncan A. Robertson
Duncan A. Robertson
Affiliation:
Loughborough University

Summary

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. New tools are required to tackle challenges of how firms should compete in environments characterized by both exogeneous shocks and intense endogenous competition. 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.
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Keywords

agent-based modellingstrategic management
Type
Element
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Series: Elements in Business Strategy
Online ISBN: 9781108767835
Publisher: Cambridge University Press
Print publication: 17 October 2019

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References

Allen, P. M., Strathern, M., and Baldwin, J. S. (2007) ‘Complexity and the Limits to Learning’, Journal of Evolutionary Economics, 17(4), 401–31Google Scholar
Anderson, P. (1999) ‘Complexity Theory and Organization Science’, Organization Science, 10(3), 216–32CrossRefGoogle Scholar
Anderson, P. W. (1988) ‘Spin Glass Hamiltonians: a Bridge between Biology, Statistical Mechanics and Computer Science, In: Pines, D. (Ed.) Emerging Syntheses in Science, pp. 17–20, Redwood City, CA: Addison-WesleyGoogle Scholar
Anderson, P., Meyer, A., Eisenhardt, K., Carley, K., and Pettigrew, A. (1999) ‘Introduction to the Special Issue: Applications of Complexity Science to Organization Science’, Organization Science, 10(3), 233–6CrossRefGoogle Scholar
Axelrod, R. (1997) The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration, Princeton, NJ: Princeton University PressCrossRefGoogle Scholar
Axelrod, R. and Tesfatsion, L. (2006) ‘A Guide for Newcomers to Agent-Based Modeling in the Social Sciences’, In: Tesfatsion, L. and Judd, K. L. (Eds.), Handbook of Computational Economics: Agent-Based Computation in Economics, New York, NY: North-HollandGoogle Scholar
Axtell, R. (2001) ‘Zipf Distribution of U. S. Firm Sizes’, Science, 293, 1818–20Google Scholar
Bak, P. and Chen, K. (1991) ‘Self-Organized Criticality’, Scientific American 264, 46–53CrossRefGoogle Scholar
Bak, P., Tang, C., and Wiesenfeld, K. (1987) ‘Self-Organized Criticality: an Explanation of 1/f Noise’, Physical Review Letters, 59(4), 381–4Google Scholar
Bass, F. M. (1969) ‘A New Product Growth for Model Consumer Durables’, Management Science, 15(5), 215–27Google Scholar
Baum, J. A. C., Dobrev, S. D., and Van Witteloostuijn, A. (2006) Ecology and Strategy, Amsterdam: ElsevierGoogle Scholar
Beer, A. S. (1959) ‘Cybernetics and Management’, London: English Universities PressGoogle Scholar
Bonabeau, E. (2002) ‘Agent-based Modeling: Methods and Techniques for Simulating Human Systems’, Proceedings of the National Academy of Sciences of the United States of America, 99(Supplement 3), 7280–7Google ScholarPubMed
Brown, S. L. and Eisenhardt, K. M. (1998) Competing on the Edge: Strategy as Structured Chaos, Boston, MA: Harvard Business School PressGoogle Scholar
Bylund, P. L. (2015) ‘Signifying Williamson’s Contribution to the Transaction Cost Approach: an Agent‐Based Simulation of Coasean Transaction Costs and Specialization’, Journal of Management Studies, 52(1), 148–74Google Scholar
Caldart, A. A. and Oliveira, F. (2010) ‘Analysing Industry Profitability: a “Complexity as Cause” Perspective’, European Management Journal, 28, 95–107CrossRefGoogle Scholar
Caldart, A. A. and Ricart, J. E. (2007) ‘Corporate Strategy: an Agent-Based Approach’, European Management Review, 4, 107–20CrossRefGoogle Scholar
Carley, K. M. and Lee, J.-S. (1998) ‘Dynamic Organizations: Organizational Adaptation in a Changing Environment’, Advances in Strategic Management, 15, 269–7Google Scholar
Carley, K. M. and Svoboda, D. M. (1996) ‘Modeling Organizational Adaptation as a Simulated Annealing Process’, Sociological Methods and Research, 25(1), 138–68Google Scholar
Carroll, G. (1984) ‘Organizational Ecology’, Annual Review of Sociology, 10(1), 71–93CrossRefGoogle Scholar
Carroll, G. R. and Hannan, M. T. (2000) ‘The Demography of Corporations and Industries’, Princeton, NJ: Princeton University PressGoogle Scholar
Černý, V. (1985) ‘Thermodynamical Approach to the Traveling Salesman Problem: an Efficient Simulation Algorithm’, Journal of Optimization Theory and Applications, 45, 41–51Google Scholar
Chang, M.-H. and Harrington, J. E. (1998) Organizational Structure and Firm Innovation in a Retail Chain’, Computational and Mathematical Organization Theory’, 3(4), 267–88CrossRefGoogle Scholar
Chang, M.-H. and Harrington, J. E. (2000) ‘Centralization vs. Decentralization in a Multi- Unit Organization: a Computational Model of a Retail Chain as a Multi-Agent Adaptive System’, Management Science, 46(11), 1427–40Google Scholar
Chang, T.-H., Lee, J.-Y., and Chen, R.-H. (2008) ‘The Effects of Customer Value on Loyalty and Profits in a Dynamic Competitive Market’, Computational Economics, 32, 317–39CrossRefGoogle Scholar
Coase, R. (1937) ‘The Nature of the Firm’, Economica, 4(16), 386–405Google Scholar
Cohen, M. D. (1981) ‘The Power of Parallel Thinking’, Journal of Economic Behavior and Organization, 2(4), 285–306CrossRefGoogle Scholar
Cosenz, F. and Noto, G. (2016) ‘Applying System Dynamics Modelling to Strategic Management: a Literature Review’, Systems Research and Behavioral Science, 33(6), 703–41CrossRefGoogle Scholar
Cyert, R. M. and March, J. G. (1963) A Behavioral Theory of the Firm, Englewood Cliffs, NJ: Prentice-HallGoogle Scholar
Darwin, C. (1859) On the Origin of Species by Means of Natural Selection, or the Preservation of Favoured Races in the Struggle for Life, London: John MurrayGoogle Scholar
D’Aveni, R. A. (1994) Hypercompetition: Managing the Dynamics of Strategic Maneuvering, New York, NY: Free PressGoogle Scholar
Delre, S. A., Jager, W., Bijmolt, T. H. A., and Janssen, M. A. (2007) ‘Targeting and Timing Promotional Activities: an Agent-Based Model for the Takeoff of New Products’, Journal of Business Research, 60, 826–35Google Scholar
Dierickx, I. and Cool, K. (1989) ‘Asset Stock Accumulation and Sustainability of Competitive Advantage’, Management Science, 35(12), 1504–11Google Scholar
Dillon, D. (2001) ‘Review of the Santa Fe Institute: Institutional and Individual Qualities of Expert Interdisciplinary Work’, Working Paper, Harvard Interdisciplinary Studies ProjectGoogle Scholar
DiMaggio, P. J. and Powell, W. (1983) ‘The Iron Cage Revisited: Institutional Isomorphism and Collective Rationality in Organizational Fields’, American Sociological Review, 48, 147–60Google Scholar
Epstein, J. M. (1999) ‘Agent-Based Computational Models and Generative Social Science’, Complexity, 4(5), 41–603.0.CO;2-F>CrossRefGoogle Scholar
Epstein, J. M. (2001) ‘Learning to Be Thoughtless: Social Norms and Individual Computation’, Computational Economics, 18, 9–24Google Scholar
Epstein, J. M. (2002) ‘Modeling Civil Violence: an Agent-Based Computational Approach’, Proceedings of the National Academy of Sciences of the United States of America, 99(3), 7243–50Google Scholar
Epstein, J. M. and Axtell, R. L. (1996) Growing Artificial Societies: Social Science from the Bottom Up, Cambridge, MA: MIT PressGoogle Scholar
Ethiraj, S. K. and Levinthal, D. (2004) ‘Modularity and Innovation in Complex Systems’, Management Science, 50(2), 59–173CrossRefGoogle Scholar
Farmer, J. D. and Foley, D. (2009) ‘The Economy Needs Agent-Based Modelling’, Nature, 460, 685–6Google Scholar
Federal Trade Commission (2009) ‘Guides Concerning Use of Endorsements and Testimonials in Advertising’, 16 C. F. R. (Code of Federal Regulations) § 255Google Scholar
Fioretti, G. (2018) ‘Computer Code for the NK Model’, www.cs.unibo.it/~fioretti/CODE/NK/, accessed June 2018Google Scholar
Fleming, L. and Sorenson, O. (2001) ‘Technology as a Complex Adaptive System: Evidence from Patent Data’, Research Policy, 30(7), 1019–1039CrossRefGoogle Scholar
Forrester, J. W. (1961) Industrial Dynamics, Cambridge, MA: MIT PressGoogle Scholar
Garcia, R. (2005) ‘Uses of Agent-Based Modeling in Innovation/New Product Development Research’, Journal of Product Innovation Management, 22, 380–98CrossRefGoogle Scholar
Garcia, R. and Jager, W. (2011) ‘From the Special Issue Editors: Agent-Based Modeling of Innovation Diffusion’, Journal of Product Innovation Management, 28, 148–51Google Scholar
Garcia, R. and Rummel, P. (2004) ‘Netlogo, Exploratron/Exploitation Dilemma in Innovation Model’, http://ccl.northwestern.edu/netlogo/models/community/EXPLORE%20VS%20EXP OLTE, accessed June 2018Google Scholar
Gardner, M. (1970) ‘Mathematical Games – The Fantastic Combinations of John Conway’s New Solitaire Game “Life”’, Scientific American, 223, 120–3Google Scholar
Gavetti, G., Helfat, C. E., and Marengo, L. (2017) ‘Searching, Shaping, and the Quest for Superior Performance’, Strategy Science, 2(3), 194–209Google Scholar
Gavetti, G. and Levinthal, D. A. (2000) ‘Looking Forward and Looking Backward: Cognitive and Experiential Search’, Administrative Science Quarterly, 45, 113–37CrossRefGoogle Scholar
Gavetti, G., Levinthal, D. A., and Rivkin, J. W. (2005) ‘Strategy Making in Novel and Complex Worlds: The Power of Analogy’, Strategic Management Journal, 26, 691–712Google Scholar
Gilbert, N. (2008) ‘Agent-Based Models’, Thousand Oaks, CA: SageCrossRefGoogle Scholar
Gilbert, N., Jager, W., Deffuant, G., and Adjali, I. (2007) ‘Complexities in Markets: Introduction to the Special Issue’, Journal of Business Research, 60(8), 813–5Google Scholar
Gilbert, N. and Troitzsch, K. (2005) Simulation for the Social Scientist, Maidenhead, UK: Open University PressGoogle Scholar
Gladwell, M. (2000) The Tipping Point: How Little Things Can Make a Big Difference, London: Little, Brown.Google Scholar
Goel, N. S., Maitra, S. C., and Montroll, E. W. (1971) ‘On the Volterra and Other Nonlinear Models of Intereacting Populations’, Reviews of Modern Physics, 43, 231–76Google Scholar
Goldenberg, J., Libai, B., and Muller, E. (2010) ‘The Chilling Effects of Network Externalities’, International Journal of Research in Marketing, 27, 4–15Google Scholar
Granovetter, M. (1978) ‘Threshold Models of Collective Behavior’, American Journal of Sociology, 83(6), 1420–43Google Scholar
Hannan, M. T. and Carroll, G. R. (1992) Dynamics of Organizational Populations, New York, NY: Oxford University PressGoogle Scholar
Hannan, M. T. and Freeman, J. (1977) ‘The Population Ecology of Organizations’, American Journal of Sociology, 82(5), 929–64CrossRefGoogle Scholar
Hannan, M. T. and Freeman, J. (1984) ‘Structural Inertia and Organizational Change’, American Sociological Review, 49(2), 149–64Google Scholar
Hannan, M. T. and Freeman, J. (1989) Organizational Ecology, Cambridge, MA: Harvard University PressCrossRefGoogle Scholar
Hildalgo, C. A., Klinger, B., Barabási, A.-L., and Hausmann, R. (2007) ‘The Product Space Conditions in the Development of Nations’, Science, 317, 482–7Google Scholar
Holland, J. H. and Miller, J. H. (1991) ‘Artificial Adaptive Agents in Economic Theory’, American Economic Review, 81(2), 365–70Google Scholar
Hotelling, H. (1929) ‘Stability in Competition’, The Economic Journal, 39(153), 41–57Google Scholar
Julka, N., Srinivasan, R., and Karimi, I. (2002) ‘Agent-Based Supply Chain Management – 1: Framework’, Computers and Chemical Engineering, 26, 1755–69Google Scholar
Kaihara, T. (2003) ‘Multi-Agent Based Supply Chain Modelling with Dynamic Environment’, International Journal of Production Economics, 85, 263–9CrossRefGoogle Scholar
Kauffman, S. A. (1984) ‘Emergent Phenomena in Random Complex Phenomena’, Physica D, 145–56CrossRefGoogle Scholar
Kauffman, S. A. (1993) The Origins of Order: Self-Organization and Selection in Evolution, New York, NY: Oxford University PressGoogle Scholar
Kauffman, S. A. and Levin, S. (1987) ‘Towards a General Theory of Adaptive Walks on Rugged Landscapes’, Journal of Theoretical Biology, 128, 11–45CrossRefGoogle ScholarPubMed
Kauffman, S. A. and Weinberger, E. D. (1989) ‘The NK Model of Rugged Fitness Landscapes and Its Application to Maturation in the Immune Response’, Journal of Theoretical Biology, 141, 211–45Google Scholar
Kotler, P. (1997) Marketing Management, New York, NY: Prentice-HallGoogle Scholar
Lancaster, K. J. (1966) ‘A New Approach to Consumer Theory’, The Journal of Political Economy, 74(2), 132–157.Google Scholar
LeBaron, B. (2000) ‘Agent-Based Computational Finance: Suggested Readings and Early Research’, Journal of Economic Dynamics and Control, 24(5–7), 679–702Google Scholar
LeBaron, B. (2006) ‘Agent-Based Computational Finance’, In: Tesfatsion, L. and Judd, K. L. (Eds.) Handbook of Computational Economics, 2, 1187–233Google Scholar
Lenox, M. J., Rockart, S. F., and Lewin, A. Y. (2006) ‘Interdependency, Competition, and the Distribution of Firm and Industry Profits’, Management Science, 52(5), 757–72Google Scholar
Levinthal, D. A. (1997) ‘Adaptation on Rugged Landscapes’, Management Science, 43, 934–50Google Scholar
Levinthal, D. A. and March, J. G. (1981) ‘A Model of Adaptive Organizational Search’, Journal of Economic Behavior and Organization, 2(4), 307–33CrossRefGoogle Scholar
Levinthal, D. A. and March, J. G. (1993) ‘The Myopia of Learning’, Strategic Management Journal, 14, 95–112Google Scholar
Levinthal, D. A. and Warglien, M. (1999) ‘Landscape Design: Designing for Local Action in Complex Worlds’, Organization Science, 10(3), 342–57Google Scholar
Lewin, A. Y. (1999) ‘Application of Complexity Theory to Organization Science’, Organization Science, 10(3), 215CrossRefGoogle Scholar
Lotka, A. J. (1920) ‘Analytical Note on Certain Rhythmic Relations in Organic Systems’, Proc. Natl. Acad. Sci. U.S.A., 6, 410–5Google Scholar
Lotka, A. J. (1925) Elements of Physical Biology, Baltimore, MD: Williams & WilkinsGoogle Scholar
Macy, M. W. (1991) ‘Chains of Cooperation: Threshold Effects in Collective Action’, American Sociological Review, 56(6), 730–47Google Scholar
March, J. G. (1991) ‘Exploration and Exploitation in Organizational Learning’, Organization Science, 2(1), 71–87Google Scholar
March, J. G. and Simon, H. (1958) Organizations, New York, NY: WileyGoogle Scholar
McKelvey, B. (1999) ‘Avoiding Complexity Catastrophe in Coevolutionary Pockets: Strategies for Rugged Landscapes’, Organization Science, 10(3), 294–321CrossRefGoogle Scholar
McMullen, J. S. and Dimov, D. (2013) ‘Time and Entrepreneurial Journey: The Problems and Promise of Studying Entrepreneurship as a Process’, Journal of Management Studies, 50(8), 1481–512Google Scholar
Midgley, D. F., Marks, R. E., and Cooper, L. C. (1997) ‘Breeding Competitive Strategies’, Management Science, 43, 257–75CrossRefGoogle Scholar
Miller, J. H. and Page, S. E. (2007) Complex Adaptive Systems: An Introduction to Computational Models of Social Life, Princeton, NJ: Princeton University PressGoogle Scholar
Miller, K. D., Fabian, F., and Lin, S.-J. (2009) ‘Strategies for Online Communities’, Strategic Management Journal, 30(3), 305–22Google Scholar
Mintzberg, H., Ahlstrand, B., and Lampel, J. (1998) Strategy Safari: A Guided Tour Through the Wilds of Strategic Management, London: Prentice HallGoogle Scholar
Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., and Group, P. (2009) ‘Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement, PLoS Medicine, 6, e1000097Google Scholar
Morecroft, J. D. W. (1984) ‘Strategy Support Models’, Strategic Management Journal, 5(3), 215–29Google Scholar
Morecroft, J. D. W. (1988) ‘System Dynamics and Microworlds for Policymakers’, European Journal of Operational Research, 35, 301–20Google Scholar
Nelson, R. R. and Winter, S. G. (1982) ‘An Evolutionary Theory of Economic Change’, Cambridge, MA: Harvard University PressGoogle Scholar
North, M. J. and Macal, C. M. (2007) ‘Managing Business Complexity: Discovering Strategic Solutions with Agent-Based Modeling and Simulation’, Oxford: Oxford University PressGoogle Scholar
Orponen, P. (2007) ‘Combinatorial Models and Stochastic Algorithms’, Helsinki University of Technology Laboratory for Theoretical Computer Science, https://users.ics.aalto.fi/orponen/lectures/komsta_2007.pdfGoogle Scholar
Padget, J., Vidgen, R., Mitchell, J., Marshall, A., and Mellor, R. (2008) ‘Sendero: An Extended, Agent-Based Implementation of Kauffman’s NKCS Model’, University of Bath Working Paper, https://wiki.bath.ac.uk/display/sendero/NKC, accessed June 2018Google Scholar
Penrose, E. T. (1959) The Theory of the Growth of the Firm, New York, NY: WileyGoogle Scholar
Rand, W. (2014) ‘The Future Applications of Agent-Based Modeling in Marketing’, In: Moutinho, L., Bigne, E., and Manrai, A. K. (Eds.) The Routledge Companion to the Future of Marketing, London: RoutledgeGoogle Scholar
Rivkin, J. W. (2000) ‘Imitation of Complex Strategies’, Management Science, 46(6), 824–44Google Scholar
Rivkin, J. W. (2001) ‘Reproducing Knowledge: Replication without Imitation at Moderate Complexity’, Organization Science, 12(3), 274–93Google Scholar
Rivkin, J. W. and Siggelkow, N. (2003) ‘Balancing Search and Stability: Interdependencies among Elements of Organizational Design’, Management Science, 49(3), 290–311Google Scholar
Rivkin, J. W. and Siggelkow, N. (2006) ‘Organizing to Strategize in the Face of Interactions: Preventing Premature Lock-in’, Long Range Planning, 39, 591–614Google Scholar
Robertson, D. A. (2003) ‘Agent-Based Models of a Banking Network as an Example of a Turbulent Environment: the Deliberate vs. Emergent Strategy Debate Revisited’, Emergence, 5(2), 56–71Google Scholar
Robertson, D. A. (2005) ‘Agent-Based Modeling Toolkits: NetLogo, RePast, and Swarm’, Academy of Management Learning and Education, 4(4), 525–7Google Scholar
Robertson, D. A. (2019) ‘Spatial Transmission Models: a Taxonomy and Framework’, Risk Analysis, 39(1), 225–43Google Scholar
Robertson, D. A. and Caldart, A. A. (2008) ‘Natural Science Models in Management: Opportunities and Challenges’, Emergence: Complexity & Organization, 10(2), 61–75Google Scholar
Robertson, D. A. and Caldart, A. A. (2009) The Dynamics of Strategy, Oxford: Oxford University PressGoogle Scholar
Robinson, S. (2004) Simulation: The Practice of Model Development and Use, Chichester: John Wiley & SonsGoogle Scholar
Rosenkopf, L. and Nerkar, A. (2001) ‘Beyond Local Search: Boundary-Spanning, Exploration, and Impact in the Optical Disk Industry’, Strategic Management Journal, 22(4), 287–306CrossRefGoogle Scholar
Schelling, T. C. (1969) ‘Models of Segregation’, American Economic Review, 59(2), 488–93Google Scholar
Schelling, T. C. (1971a) ‘Dynamic Models of Segregation’, Journal of Mathematical Sociology, 1, 143–86CrossRefGoogle Scholar
Schelling, T. C. (1971b) ‘On the Ecology of Micromotives’, The Public Interest, 25, 61–98Google Scholar
Schelling, T. C. (1973) ‘Hockey Helmets, Concealed Weapons, and Daylight Saving: a Study of Binary Choices with Externalities’, Journal of Conflict Resolution, 17(3), 381–428Google Scholar
Schelling, T. C. (1978) Micromotives and Macrobehavior, NortonGoogle Scholar
Senge, P. (1990) The Fifth Discipline: The Art & Practice of the Learning Organization, New York, NY: DoubledayGoogle Scholar
Senge, P. and Sterman, J. D. (1992) ‘Systems Thinking and Organizational Learning: Acting Locally and Thinking Globally in the Organization of the Future’, European Journal of Operational Research, 59, 137–50Google Scholar
Shiozawa, Y. (2016) ‘A Guided Tour of the Backside of Agent-Based Simulation’, In: Kita, H., Taniguchi, K., and Nakajima, Y. (Eds.) Realistic Simulation of Financial Markets: Analyzing Market Behaviors by the Third Mode of Science, Economics and Social Complexity Science, 4, Japan: SpringerGoogle Scholar
Siggelkow, N. and Levinthal, D. A. (2003) ‘Temporarily Divide to Conquer: Centralized, Decentralized, and Reintegrated Organizational Approaches to Exploration and Adaptation’, Organization Science, 14(6), 650–69Google Scholar
Siggelkow, N. and Rivkin, J. W. (2006) ‘When Exploration Backfires: Unintended Consequences of Multilevel Organizational Search’, Academy of Management Journal, 49(4), 779–95Google Scholar
Simon, H. A. (1947) Administrative Behavior: a Study of Decision-Making Processes in Administrative Organization, 1st ed., New York, NY: MacmillanGoogle Scholar
Simon, H. A. (1962) ‘The Architecture of Complexity’, Proceedings of the American Philosophical Society, 106, 67–82Google Scholar
Simon, H. A. (1996) The Sciences of the Artificial, 3rd ed., Cambridge, MA: MIT PressGoogle Scholar
Simon, H. A. (1997) Administrative Behavior: a Study of Decision-Making Processes in Administrative Organizations, 4th ed., New York, NY: The Free PressGoogle Scholar
Spencer, H. (1864) Principles of Biology, London: William and NorgateGoogle Scholar
Starbuck, W. (1965) ‘Organizational Growth and Development’, In: March, J. G. (Ed.) Handbook of Organizations, Chicago, IL: Rand-McNallyGoogle Scholar
Stein, D. L. (2016) ‘Frustration and Fluctuations in Systems with Quenched Disorder’, In: PWA90: A Lifetime of Emergence, Chandra, P., Coleman, P., Kotliar, G., Ong, N. P., Stein, D. L. and Yu, C. (Eds.), Singapore: World Scientific, pp. 169–86Google Scholar
Steinbruner, J. D. (1974) The Cybernetic Theory of Decision: New Dimensions of Political Analysis, Princeton, NJ: Princeton University PressGoogle Scholar
Stuart, T. E. and Podolny, J. M. (1996) ‘Local Search and the Evolution of Technological Capabilities’, Strategic Management Journal, 17, 21–38Google Scholar
Stummer, C., Kiesling, E., Gunther, M., and Vetschera, R. (2015) ‘Innovation Diffusion of Repeat Purchase Products in a Competitive Market: an Agent-Based Simulation Approach’, European Journal of Operational Research, 245, 157–67Google Scholar
Suzuki, R. and Arita, T. (2005) ‘How Niche Construction Can Guide Coevolution’, In: Capcarrere, M. S., Freitas, A. A., Bentley, P. J., Johnson, C. G., and Timmis, J. (Eds.) Advances in Artificial Life: 8th European Conference, ECAL 2005, Canterbury, UK; Berlin: Springer-VerlagGoogle Scholar
Swaminathan, J. M., Smith, S. F., and Sadeh, N. M. (2007) ‘Modeling Supply Chain Dynamics: a Multiagent Approach’, Decision Sciences, 29(3), 607–32Google Scholar
Tay, N. S. P. and Lusch, R. F. (2005) ‘A Preliminary Test of Hunt’s General Theory of Competition: Using Artificial Adaptive Agents to Study Complex and Ill-Defined Environments’, Journal of Business Research, 58(9), 1155–68Google Scholar
Tesfatsion, L. (2002), ‘Agent-Based Computational Economics: Growing Economies from the Bottom Up’, Artificial Life, 8(1), 55–82Google Scholar
Tesfatsion, L. (2006) ‘Agent-Based Computational Economics: a Constructive Approach to Economic Theory’, In: Tesfatsion, L. and Judd, K. L. (Eds.), Handbook of Computational Economics, Volume 2: Agent-Based Computational Economics, ElsevierGoogle Scholar
Tesfatsion, L. (2017) ‘Modeling Economic Systems as Locally-Constructive Sequential Games’, Journal of Economic Methodology, 24(4), 1–26Google Scholar
Tesfatsion, L. and Judd, K. L. (Eds.) (2006) Handbook of Computational Economics, Volume 2: Agent-Based Computational Economics, ElsevierGoogle Scholar
Troutman, C., Clark, B., and Goldrick, M. (2008) ‘Social Networks and Intraspeaker Variation During Periods of Language Change’, University of Pennsylvania Working Papers in Linguistics, 14(1), Article 25Google Scholar
Tushman, M. and Romanelli, E. (1985) ‘Organizational Evolution: a Metamorphosis Model of Convergence and Reorientation’, In: Cummings, L. and Staw, B. (Eds.) Research in Organizational Behavior, 7, 171–222Google Scholar
Utomo, D. S., Onggo, B. S., and Eldridge, S. (2017) ‘Applications of Agent-Based Modeling and Simulation in the Agri-Food Chains’, European Journal of Operational Research, 269, 794–805Google Scholar
Valente, M. (2014) ‘An NK-Like Model for Complexity’, Journal of Evolutionary Economics, 24(1), 107–34Google Scholar
Van Eck, P. S., Jager, W., and Leeflang, P. S. H. (2011) ‘Opinion Leaders’ Role in Innovation Diffusion: a Simulation Study’, Journal of Product Innovation Management, 28, 187–203Google Scholar
Vidgen, R. and Padget, J. (2009) ‘Sendero: an Extended, Agent-Based Implementation of Kauffman’s NKCS Model’, Journal of Artificial Societies and Social Simulation, 12(4), 8Google Scholar
Volterra, V. (1926) ‘Variazioni e fluttuazioni del numero d’individui in specie animali conviventi’, Mem. Acad. Lincei Roma, 2, 31–113Google Scholar
Von Neumann, J. (1966) Theory of Self-Reproducing Automata, Burks, A. W. (Ed.), Champaign, IL: University of Illinois PressGoogle Scholar
Vrabel, M. (2015) ‘Preferred Reporting Items for Systematic Reviews and Meta- Analyses’, Oncology Nursing Forum, 552–4Google Scholar
Wang, J., Gwebu, K., Shanker, M., and Troutt, M. D. (2009) ‘An Application of Agent- Based Simulation to Knowledge Sharing’, Decision Support Systems, 46, 532–41Google Scholar
Watts, D. (2002) ‘A Simple Model of Global Cascades on Random Networks’, Proceedings of the National Academy of Sciences of the USA, 99, 5766–71CrossRefGoogle ScholarPubMed
Watts, D. J. and Strogatz, S. H. (1998) ‘Collective Dynamics of “Small-World” Networks’, Nature, 393(6684), 440–2Google Scholar
Wiener, N. (1948) Cybernetics, or Control and Communication in the Animal and the Machine, Cambridge, MA: MIT PressGoogle Scholar
Wilensky, U. (1999) NetLogo, Evanston, IL: Center for Connected Learning and Computer-Based Modeling, Northwestern UniversityGoogle Scholar
Wilensky, U. and Reisman, K. (1999) ‘ConnectedScience: Learning Biology through Constructing and Testing Computational Theories – an Embodied Modeling Approach’, International Journal of Complex Systems, 234, pp. 1–12Google Scholar
Wilensky, U. and Reisman, K. (2006) Thinking Like a Wolf, a Sheep or a Firefly: Learning Biology through Constructing and Testing Computational Theories – an Embodied Modeling Approach, Cognition and Instruction, 24(2), 171–209Google Scholar
Williamson, O. E. (1981) ‘The Economics of Organization: the Transaction Cost Approach’, American Journal of Sociology, 87(3), 548–77Google Scholar
Winter, S. G. (1964) ‘Economic “Natural Selection” and the Theory of the Firm’, Yale Economic Essays, 4, 224–72Google Scholar
Woodridge, M. and Jennings, N. R. (1995) ‘Intelligent Agents: Theory and Practice’, Knowledge Engineering Review, 10, 115–52Google Scholar
Wright, S. (1932) ‘The Roles of Mutation, Inbreeding, Crossbreeding, and Selection in Evolution’, Proceedings of the Sixth International Congress on Genetics, 355–66Google Scholar
Young, H. P. (1998) Individual Strategy and Social Structure, Princeton, NJ: Princeton University PressGoogle Scholar

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Agent-Based Strategizing
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Save element to Google Drive

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Agent-Based Strategizing
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