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Research Article

Adaptation of the boundary system in growing firms: an agent-based computational study on the role of complexity and search strategy

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Pages 2881-2903 | Received 20 Jun 2019, Accepted 06 Sep 2019, Published online: 29 Oct 2019

References

  • Ahrens, T., & Chapman, C. S. (2007). Theorizing practice in management accounting research. In C. S. Chapman, A. G. Hopwood, & M. D. Shields (Eds.), Handbook of management accounting research (Vol. 1, pp. 99–112). Amsterdam etc.: Elsevier.
  • Andersén, J., & Samuelsson, J. (2016). Resource organization and firm performance: How entrepreneurial orientation and management accounting influence the profitability of growing and non-growing SMEs. International Journal of Entrepreneurial Behavior & Research, 22(4), 466–484. doi:10.1108/IJEBR-11-2015-0250
  • Baumann, O., Schmidt, J., & Stieglitz, N. (2019). Effective search in rugged performance landscapes: A review and outlook. Journal of Management, 45(1), 285–318. doi:10.1177/0149206318808594
  • Bedford, D. S. (2015). Management control systems across different modes of innovation: Implications for firm performance. Management Accounting Research, 28, 12–30. doi:10.1016/j.mar.2015.04.003
  • Beese, J., Haki, M. K., Aier, S., & Winter, R. (2019). Simulation-based research in information systems. Business & Information Systems Engineering, 61(4), 503–521. doi:10.1007/s12599-018-0529-1
  • Bisbe, J., & Otley, D. (2004). The effects of the interactive use of management control systems on product innovation. Accounting, Organizations and Society, 29(8), 709–737. doi:10.1016/j.aos.2003.10.010
  • Brenner, T. (2006). Agent learning representation: Advice on modelling economic learning. In L. Tesfatsion, & K. L. Judd (Eds.), Handbook of computational economics (Vol. 2, pp. 895–947). Amsterdam etc.: Elsevier.
  • Burton, R. M., & Obel, B. (2011). Computational modeling for what-is, what-might-be, and what-should-be studies—and triangulation. Organization Science, 22(5), 1195–1202. doi:10.1287/orsc.1100.0635
  • Bush, R. R., & Mosteller, F. (1955). Stochastic models for learning. Oxford: John Wiley & Sons.
  • Chang, M.-H., & Harrington, J. E. (2006). Agent-based models of organizations. In L. Tesfatsion, & K. L. Judd (Eds.), Handbook of computational economics (Vol. 2, pp. 1273–1337). Amsterdam etc.: Elsevier.
  • Chenhall, R. H. (2003). Management control systems design within its organizational context: Findings from contingency-based research and directions for the future. Accounting, Organizations and Society, 28(2-3), 127–168. doi:10.1016/S0361-3682(01)00027-7
  • Chenhall, R. H., & Morris, D. (1986). The impact of structure, environment, and interdependence on the perceived usefulness of management accounting systems. Accounting Review, 61(1), 16–35. doi:10.1016/0361-3682(94)90010-8
  • Csaszar, F. A. (2018). A note on how NK landscapes work. Journal of Organization Design, 7(1), 1–6. doi:10.1186/s41469-018-0039-0
  • Davila, A. (2005). An exploratory study on the emergence of management control systems: Formalizing human resources in small growing firms. Accounting, Organizations and Society, 30(3), 223–248. doi:10.1016/j.aos.2004.05.006
  • Davila, A., Foster, G., & Jia, N. (2015). The valuation of management control systems in start-up companies: International field-based evidence. European Accounting Review, 24(2), 207–239. doi:10.1080/09638180.2014.965720
  • Davila, A., Foster, G., & Li, M. (2009). Reasons for management control systems adoption: Insights from product development systems choice by early-stage entrepreneurial companies. Accounting, Organizations and Society, 34(3-4), 322–347. doi:10.1016/j.aos.2008.08.002
  • Davila, A., Foster, G., & Oyon, D. (2009). Accounting and control, entrepreneurship and innovation: Venturing into new research opportunities. European Accounting Review, 18(2), 281–311. doi:10.1080/09638180902731455
  • Davis, J. P., Eisenhardt, K. M., & ., & Bingham, C. B. (2007). Developing theory through simulation methods. Academy of Management Review, 32(2), 480–499. doi:10.5465/amr.2007.24351453
  • Davis, P., & Lay-Yee, R. (2019). Simulating societal change: Counterfactual modelling for social and policy inquiry. Cham: Springer International Publishing.
  • Eisenhardt, K. M. (1989). Agency theory: An assessment and review. Academy of Management Review, 14(1), 57–74. doi:10.5465/amr.1989.4279003
  • Epstein, J. M. (1999). Agent-based computational models and generative social science. Complexity, 4(5), 41–60. doi:10.1002/(SICI)1099-0526(199905/06)4:5<41::AID-CPLX9>3.0.CO;2-F
  • Epstein, J. M. (2006). Agent-based computational models and generative social science. In J. M. Epstein (Ed.), Generative social science: Studies in agent-based computational modeling (pp. 4–46). Princeton: Princeton University Press.
  • Galbraith, J. R. (1974). Organization design: An information processing view. Interfaces, 4(3), 28–36. doi:10.1287/inte.4.3.28
  • Gilbert, N., & Troitzsch, K. G. (2005). Simulation for the social scientist (2nd ed.) Buckingham: Open University Press.
  • Grabner, I., & Moers, F. (2013). Management control as a system or a package? Conceptual and empirical issues. Accounting, Organizations and Society, 38(6-7), 407–419. doi:10.1016/j.aos.2013.09.002
  • Harrison, J. R., Zhiang, L. I. N., Carroll, G. R., & Carley, K. M. (2007). Simulation modeling in organizational and management research. Academy of Management Review, 32(4), 1229–1245. doi:10.5465/amr.2007.26586485
  • Hesford, J. W., Lee, S.-H. S., Van der Stede, W. A., & Young, S. M. (2007). Management accounting: A bibliographic study. In C. S. Chapman, A. G. Hopwood, & M. D. Shields (Eds.), Handbooks of management accounting research (Vol. 1, pp. 3–26). Amsterdam etc.: Elsevier.
  • Kauffman, S. A. (1993). The origins of order: Self-organization and selection in evolution Oxford: Oxford University Press.
  • Kauffman, S. A., & Levin, S. (1987). Towards a general theory of adaptive walks on rugged landscapes. Journal of Theoretical Biology, 128(1), 11–45. doi:10.1016/S0022-5193(87)80029-2
  • Kirman, A. P. (1992). Whom or what does the representative individual represent? Journal of Economic Perspectives, 6(2), 117–136. doi:10.1257/jep.6.2.117
  • Kruis, A.-M., Speklé, R. F., & Widener, S. K. (2016). The levers of control framework: An exploratory analysis of balance. Management Accounting Research, 32, 27–44. doi:10.1016/j.mar.2015.12.002
  • Lambert, R. A. (2001). Contracting theory and accounting. Journal of Accounting and Economics, 32(1-3), 3–87. doi:10.1016/S0165-4101(01)00037-4
  • Langfield-Smith, K. (2007). A review of quantitative research in management control systems and strategy. In C. S. Chapman, A. G. Hopwood, & M. D. Shields (Eds.), Handbook of management accounting research (Vol. 2, pp. 753–783). Amsterdam etc.: Elsevier.
  • Lawrence, P. R., & Lorsch, J. W. (1967). Differentiation and integration in complex organizations. Administrative Science Quarterly, 12(1), 1–47. doi:10.2307/2391211
  • Leitner, S., & Wall, F. (2015). Simulation-based research in management accounting and control: An illustrative overview. Journal of Management Control, 26(2-3), 105–129. doi:10.1007/s00187-015-0209-y
  • Leitner, S., & Wall, F. (2019). Decision-facilitating information in hidden-action setups: An agent-based approach. arXiv Preprint arXiv:1908.07998.
  • Levitan, B., & Kauffman, S. A. (1995). Adaptive walks with noisy fitness measurements. Molecular Diversity, 1(1), 53–68. doi:10.1007/BF01715809
  • Li, R., Emmerich, M. M., Eggermont, J., Bovenkamp, E. P., Bäck, T., Dijkstra, J., & Reiber, J. C. (2006). Mixed-integer NK landscapes. In T. Runarsson, H.-G. Beyer, E. Burke, J. Merelo-Guervós, L. D. Whitley, & X. Yao (Eds.), Parallel problem solving from nature–PPSN IX (Vol. 4193, pp. 42–51). Berlin: Springer.
  • Lockett, A., Wiklund, J., Davidsson, P., & Girma, S. (2011). Organic and acquisitive growth: Re-examining, testing and extending Penrose’s growth theory. Journal of Management Studies, 48(1), 48–74. doi:10.1111/j.1467-6486.2009.00879.x
  • López, O. L., & Hiebl, M. R. W. (2015). Management accounting in small and medium-sized enterprises: Current knowledge and avenues for further research. Journal of Management Accounting Research, 27(1), 81–119. doi:10.2308/jmar-50915
  • Lorscheid, I., Heine, B.-O., & Meyer, M. (2012). Opening the ‘black box’ of simulations: Increased transparency and effective communication through the systematic design of experiments. Computational and Mathematical Organization Theory, 18(1), 22–62. doi:10.1007/s10588-011-9097-3
  • Macintosh, N. B., & Daft, R. L. (1987). Management control systems and departmental interdependencies: An empirical study. Accounting, Organizations and Society, 12(1), 49–61. doi:10.1016/0361-3682(87)90015-8
  • Majumdar, S. (2008). Modelling growth strategy in small entrepreneurial business organisations. The Journal of Entrepreneurship, 17(2), 157–168. doi:10.1177/097135570801700204
  • Malmi, T., & Brown, D. A. (2008). Management control systems as a package—Opportunities, challenges and research directions. Management Accounting Research, 19(4), 287–300. doi:10.1016/j.mar.2008.09.003
  • Malone, T. W. (1987). Modeling coordination in organizations and markets. Management Science, 33(10), 1317–1332. doi:10.1287/mnsc.33.10.1317
  • Merchant, K. A., & Van der Stede, W. A. (2017). Management control systems: Performance measurement, evaluation and incentives (4th ed.). New York: Pearson Education.
  • Messersmith, J. G., & Guthrie, J. P. (2010). High performance work systems in emergent organizations: Implications for firm performance. Human Resource Management, 49(2), 241–264. doi:10.1002/hrm.20342
  • Querbes, A., & Frenken, K. (2018). Grounding the ‘mirroring hypothesis’: Towards a general theory of organization design in new product development. Journal of Engineering and Technology Management, 47, 81–95.
  • Redman, T. C. (1998). The impact of poor data quality on the typical enterprise. Communications of the ACM, 41(2), 79–82. doi:10.1145/269012.269025
  • Rivkin, J. W., & Siggelkow, N. (2007). Patterned interactions in complex systems: Implications for exploration. Management Science, 53(7), 1068–1085. doi:10.1287/mnsc.1060.0626
  • Safarzyńska, K., & van den Bergh, J. (2010). Evolutionary models in economics: A survey of methods and building blocks. Journal of Evolutionary Economics, 20(3), 329–373. doi:10.1007/s00191-009-0153-9
  • Sah, R. K., & Stiglitz, J. E. (1986). The architecture of economic systems: Hierarchies and polyarchies. American Economic Review, 76(4), 716–727.
  • Samagaio, A., Crespo, N. F., & Rodrigues, R. (2018). Management control systems in high-tech start-ups: An empirical investigation. Journal of Business Research, 89, 351–360. doi:10.1016/j.jbusres.2017.12.028
  • Shields, M. D. (1997). Research in management accounting by North Americans in the 1990s. Management Accounting Research, 9, 3–62. doi:10.1006/mare.1998.0081
  • Siggelkow, N., & Rivkin, J. W. (2005). Speed and search: Designing organizations for turbulence and complexity. Organization Science, 16(2), 101–122. doi:10.1287/orsc.1050.0116
  • Simon, H. A. (1955). A behavioral model of rational choice. The Quarterly Journal of Economics, 69(1), 99–118. doi:10.2307/1884852
  • Simons, R. (1994a). How new top managers use control systems as levers of strategic renewal. Strategic Management Journal, 15(3), 169–189. doi:10.1002/smj.4250150301
  • Simons, R. (1994b). Levers of control: How managers use innovative control systems to drive strategic renewal. Boston, MA: Harvard Business Press.
  • Simons, R., Dávila, A., & Kaplan, R. S. (2000). Performance measurement & control systems for implementing strategy. Upper Saddle River, NJ: Prentice Hall.
  • Sutton, R. S., & Barto, A. G. (2012). Reinforcement learning: An introduction (2nd ed.) Cambridge, MA: MIT Press.
  • Tesfatsion, L. (2003). Agent-based computational economics: Modeling economies as complex adaptive systems. Information Sciences, 149(4), 262–268. doi:10.1016/S0020-0255(02)00280-3
  • Thompson, J. D. (1967). Organizations in action. Social science bases of administrative theory. New York, NY: McGraw-Hill.
  • Van de Ven, A. H., Ganco, M., & Hinings, C. R. (2013). Returning to the frontier of contingency theory of organizational and institutional designs. Academy of Management Annals, 7(1), 393–440. doi:10.5465/19416520.2013.774981
  • Wall, F. (2016). Agent-based modeling in managerial science: An illustrative survey and study. Review of Managerial Science, 10(1), 135–193. doi:10.1007/s11846-014-0139-3
  • Wall, F. (2018). Emergence of task formation in organizations: Balancing units’ competence and capacity. Journal of Artificial Societies and Social Simulation, 21(2), 1–25. doi:10.18564/jasss.3679
  • Wall, F. (2019). Coordination with erroneous communication: Results of an agent-based simulation. Knowledge and Information Systems, 61(1), 161–195. doi:10.1007/s10115-018-1292-9
  • Welch, B. L. (1938). The significance of the differences between two means when the population variances are unequal. Biometrika, 25, 350–362. doi:10.1093/biomet/29.3-4.350
  • Widener, S. K. (2007). An empirical analysis of the levers of control framework. Accounting, Organizations and Society, 32(7-8), 757–788. doi:10.1016/j.aos.2007.01.001
  • Za, S., Spagnoletti, P., Winter, R., & Mettler, T. (2018). Exploring foundations for using simulations in IS research. Communications of the Association for Information Systems, 42, 268–300. doi:10.17705/1CAIS.04210