Study of Emergent Phenomena in the Organization

• Autorzy: Agnieszka Kowalska-Styczeń , Vasyl Lytvyn
• Języki publikacji: EN

Abstrakty

EN

Purpose: The aim of this article is to draw attention to the specificity of emergent phenomena in organization and management, the study of which requires an approach derived from complex adaptive systems.

Design/methodology/approach: The article uses a critical analysis of research on emergent phenomena in organizations from the perspective of complex social systems. This analysis made it possible to distinguish types of emergence in organization and management depending on the type of agents (members) and interactions that take place in the organization and indicated the causes of emergent phenomena.

Findings: The article creates a research framework for complex emergent phenomena and shows how to use computer simulation to study complex emergent phenomena in organizations.

Originality/value: A relatively new direction of research are analyzes within the theory of complex adaptive systems, the aim of which is to model and explain the behavior of systems of interconnected objects based on knowledge about the laws of individual elements (at the local level) and the structure of their connections. Therefore, it seems interesting to use computer tools developed based on complexity theory, especially agent-based models, as proposed in this article to study emergent phenomena in organizations. Since there are many approaches and ways of using computer simulations to study complex adaptation phenomena, a method of creating a simulation model and a method of conducting research using it were proposed.(original abstract)

Słowa kluczowe

EN

Multi-agent system; Organisation and management; Computing simulation

PL

Systemy multiagentowe; Organizacja i zarządzanie; Symulacje komputerowe

• Czasopismo: Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska
• Rocznik: 2023
• Numer: z. 189 Współczesne zarządzanie = Contemporary management
• Strony: 339--350

Twórcy

autor

Agnieszka Kowalska-Styczeń

• Silesian University of Technology, Poland

autor

Vasyl Lytvyn

• Lviv Polytechnic National University

Bibliografia

• 1. Anderson, P. (1999). Complexity Theory and Organization Science. Organization Science, 10(3), 216-232.
• 2. Artime, O., De Domenico, M. (2022). From the origin of life to pandemics: emergent phenomena in complex systems. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 380(2227), 1-21.
• 3. Axelrod, R. Cohen, M.D. (2000). Harnessing Complexity: Organisational Implications of a Scientific Frontier. Free Press.
• 4. Axelrod, R. (1997). The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. New York: Princeton Univercity Press.
• 5. Axelrod, R., Mitchell, W., Thomas, R., Bennett, D., Bruderer, E. (1995). Coalition formation in standard-setting alliances. Management Science, 41, 1493-1508.
• 6. Bohórquez Arévalo, L.E., Espinosa, A. (2015). Theoretical approaches to managing complexity in organizations: A comparative analysis. Estudios Gerenciales, 31, 20-29.
• 7. Bonabeau, E., Dorigo, M., Theraulaz, G. (1999). Swarm Intelligence. Oxford University Press.
• 8. Borgatti, S.P., Mehra, A., Brass, D.J., Labianca, G. (2009). Network Analysis in the Social Sciences. Science, 323, 892-895.
• 9. Burkhart, R. (1996). The SWARM simulator: Applications in science and business. Embracing Complexity: Exploring the Application of Complex Adaptive Systems to Business. Cambridge MA: Ernst & Young Center for Business Innovation.
• 10. Burt, R.S. (1992). Structural Holes: The Social Structure of Competition. Cambridge, MA: Harvard University Press.
• 11. Carley, K.M. (1999). Learning within and among organizations. Advances in Strategic Management, 16, 33-53.
• 12. Checkland, P. (1981). Systems thinking, systems practice. John Wiley & Sons Ltd.
• 13. Contractor, N.S., Whitbred, R., Fonti, F., Hyatt, A., O'Keefe, B., Jones, P. (2000). Structuration theory and self-organizing networks. Paper presented at the Annual Organization Science Winter Conference, January, Keystone, CO.
• 14. Crowston, K. (1996). An approach to evolving novel organizational forms. Computational and Mathematical Organization Theory, 2(1), 29-47.
• 15. David, N. (2013). Validating Simulations. In: B. Edmonds, R. Meyer (eds.), Simulating Social Complexity. Berlin/Heidelberg: Springer-Verlag.
• 16. Edmondson, D.L., Kern, F., Rogge, K.S. (2019). The co-evolution of policy mixes and socio-technical systems: towards a conceptual framework of policy mix feedback in sustainability transitions. Res. Policy, 48, 103555.
• 17. Fleming, L., Sorenson, O. (2001). Technology as a complex adaptive system. Research Policy, 30(7), 1019-1039.
• 18. Ganco, M., Agarwal, R. (2009). Performance differentials between diversifying entrants and entrepreneurial start-ups: a complexity approach. Academy of Management Review, 34(2), 228-252.
• 19. Goldstein, J. (1999). Emergence as a construct: History and issues. Emergence, 1(1), 49-72.
• 20. Gotts, N.M., Polhill, J.G., Law, A.N.R. (2003). Agent-Based Simulation in the Study of Social Dilemmas. Artificial Intelligence Review, 19, 3-92.
• 21. Granovetter, M. (1978). Threshold models of collective behavior. American Journal of Sociology, 83(6), 1420-1443.
• 22. Grimm, V., Berger, U., DeAngelis, D.L., Polhill, J.G., Giske, J., Railsback, S.F. (2010). The ODD protocol: A review and first update. Ecological Modelling, 221(23), 2760-2768.
• 23. Grimm, V., Railsback, S.F., Vincenot, C.E., Berger, U., Gallagher, C., DeAngelis, D.L., Edmonds, B., Ge, J., Giske, J., Groeneveld, J., Johnston, A.S., Milles, A., Nabe-Nielsen, J., Polhill, J.G., Radchuk, V., Rohwäder, M.-S., Stillman, R.A., Thiele, J.C., Ayllón, D. (2020). The ODD Protocol for Describing Agent-Based and Other Simulation Models: A Second Update to Improve Clarity, Replication, and Structural Realism. Journal of Artificial Societies and Social Simulation, 23(2), 7-27.
• 24. Gunz, H., Lichtenstein, B.B., Long, R. (2001). Self-organization in career systems: a view from complexity science. M@n@gement, 5(1), 63-88.
• 25. Kauffman, S. (2000). Investigations. Oxford University Press
• 26. Kowalska-Styczeń, A., Sznajd-Weron, K. (2012). Access to information in word of mouth marketing within a cellular automata model. Advances in Complex Systems, 15(7), 1250080.
• 27. Krugman, P. (1996). The Self-Organizing Economy. Oxford, UK: Blackwell.
• 28. LeBaron, B. (2000). Empirical regularities from interacting long- and short-memory investors in an agent-based stock market. IEEE Transaction on Evolutionary Computation, 5(5), 442-455.
• 29. Lichtenstein, B.B, Mckelvey, B. (2011). Four types of emergence: A typology of complexity and its implications for a science of management. International Journal of Complexity in Leadership and Management, 1(4), 339-378.
• 30. Lichtenstein, B.B, Plowman, D.A. (2009). The leadership of emergence: A complex systems leadership theory of emergence at successive organizational levels. The Leadership Quarterly, 20(4), 617-630.
• 31. Macy, M.W. (1991). Threshold effects in collective action. American Sociological Review, 56(6), 730-747.
• 32. Maguire, S., McKelvey, B. (1999). Complexity and management: Moving from fad to firm foundations. Emergence, 1(2), 19-61.
• 33. Mainzer, K. (1994). Thinking in Complexity: The Complex Dynamics of Matter, Mind, and Mankind. New York: Springer.
• 34. McKelvey, B., Salmador Sanchez, M.P. (2011). Explaining the 2007 bank liquidity crisis: lessons from complexity science and econophysics. Working paper. Facultad de Ciencias Económicas, Universidad Autónoma de Madrid.
• 35. Meyer, A.D., Gaba, V., Colwell, A. (2005). Organizing Far from Equilibrium: Nonlinear Change in Organizational Fields. Organization Science, 16(5), 456-473.
• 36. Miller, J.H., Page, S.E. (2007). Complex Adaptive Systems. Princeton University Press.
• 37. Mitleton-Kelly, E. (2003). Ten Principles of Complexity & Enabling Infrastructures. In: E. Mitleton-Kelly (ed.), Complex Systems & Evolutionary Perspectives of Organisations: The Application of Complexity Theory to Organisations. London: Elsevier. 350 A. Kowalska-Styczeń, V. Lytvyn
• 38. Newman, D. (1996). Emergence and strange attractor. Philosophy of Science, 63(2), pp. 245-261.
• 39. Nonaka, I. (1994). A dynamic theory of organizational knowledge creation. Organization Science, 5(1), 14-37.
• 40. Paul, D.L., Butler, J.C., Pearlson, K.E., Whinston, A.B. (1996). Computationally modeling organizational learning and adaptability as resource allocation: an artificial adaptive systems approach. Computational and Mathematical Organization Theory, 2(4), 301-324.
• 41. Plowman, D.A., Baker, L., Beck, T., Silansky, S., Kulkarni, M., Travis, D. (2007). Radical change accidentally: The emergence and amplification of small change. Academy of Management Journal, 50, 515-543.
• 42. Plsek, P., Greenhalgh, T. (2001). The challenge of complexity in health care. British Medical Journal, 323, 625-628.
• 43. Porter, M., Siggelkow, N. (2008). Contextual interactions within activity systems and sustainability of competitive advantage. Academy of Management Perspectives, 22(2), 34-56.
• 44. Quitzow, R. (2015). Dynamics of a policy-driven market: the co-evolution of technological innovation systems for solar photovoltaics in China and Germany. Environ. Innov. Soc. Transit., 17, 126-148.
• 45. Rammela, Ch., Stagl, S., Wilfing, H. (2007). Managing complex adaptive systems - a co-evolutionary perspective on natural resource management. Ecological Economics, 63, 9-21.
• 46. Rotmans, J., Loorbach, D. (2009). Complexity and Transition Management. Journal of Industrial Ecology, 13(2), 184-196.
• 47. Sanders, T.I., McCabe, J.A. (2003). The Use of Complexity Science, http://www.hcs.ucla.edu/DoEreport.pdf.
• 48. Schelling, T. (1978). Micromotives and Macrobehavior. New York: W.W. Norton.
• 49. Seel, R. (2000). Culture and Complexity. New Insights on Organizational Change. Organizations & People, 7(2), 2-9.
• 50. Thomas, C., Kaminska-Labbé, R., McKelvey, B. (2005). Managing the MNC and exploitation/exploration dilemma: from static balance to irregular oscillation. In: G. Szulanski, Y. Doz, J. Porac (Eds.), Advances in Strategic Management, 22, 213-247. Oxford, UK: Elsevier.
• 51. Tucker, C.E. (2014). Social networks, personalized advertising, and privacy controls. Journal of Marketing Research, 51(5), 546-562

Identyfikatory

DOI

10.29119/1641-3466.2023.189.21