Journal of Management Control

, Volume 27, Issue 1, pp 61–88 | Cite as

Business model analysis using computational modeling: a strategy tool for exploration and decision-making

Original Paper

Abstract

A business model is an essential part of a company—regardless of whether the company is a small entity or a global enterprise. Interest in business models in research and in practice has grown significantly in the last decade. Strategic initiatives and changes in business models are particularly cost intensive and uncertain. Thus, the analysis and understanding of a business model’s structure and its changes induced by strategic initiatives is crucial. Approaches to business model analysis needs to support strategists and decision-makers, enabling them to evaluate strategic initiatives and alternatives in fluent environments where there is little or no prior experience. However, regrettably, the qualitative approaches currently available fall short of providing sound guidelines especially in uncertain, highly volatile situations that involve rapid technological developments and agile competitors, which middle managers and top-level executives are often faced with. The quantitative approach used in the article concerning business model analysis is founded on a systemic simulation methodology which enables decision makers to obtain insightful experimental designs with a company’s business model. Computational modeling helps to understand business models as complex systems with dynamic interdependencies and thereby it can complement existing tools. This article uses the approach for a case study in the e-commerce business. It discusses advantages and disadvantages of computational modeling as a strategy and management tool.

Keywords

Business model analysis Simulation-based experiments  Strategy tool Management tool Business model innovation System dynamics 

JEL Classification

C63 (Computational techniques simulation modeling) M10 (General business administration) 

Supplementary material

187_2015_222_MOESM1_ESM.docx (54 kb)
Supplementary material 1 (docx 54 KB)

References

  1. Abdelkafi, N. (2012). Open business models for the greater good. Die Unternehmung, 66(3), 299–317.CrossRefGoogle Scholar
  2. Amit, R., & Zott, C. (2001). Value creation in E-business. Strategic Management Journal, 22(6–7), 493–520.CrossRefGoogle Scholar
  3. Andersen, D. F., & Richardson, G. P. (1997). Scripts for group model building. System Dynamics Review, 13(2), 107–129.CrossRefGoogle Scholar
  4. Andersen, D. L., Luna-Reyes, L. F., et al. (2012). The disconfirmatory interview as a strategy for the assessment of system dynamics models. System Dynamics Review (Wiley), 28(3), 255–275.CrossRefGoogle Scholar
  5. Anthony, R. N., & Govindarajan, V. (2007). Management control systems. Boston: McGraw-Hill.Google Scholar
  6. Ashby, R. W. (1956). Introduction to cybernetics. London: Chapman & Hall.CrossRefGoogle Scholar
  7. Aspara, J., Lamberg, J.-A., et al. (2013). Corporate business model transformation and inter-organizational cognition: the case of Nokia. Long Range Planning, 46(6), 459–474.CrossRefGoogle Scholar
  8. Baden-Fuller, C., Demil, B., et al. (2010). Editorial. Long Range Planning, 43(2–3), 143–145.CrossRefGoogle Scholar
  9. Baden-Fuller, C., & Morgan, M. S. (2010). Business models as models. Long Range Planning, 43(2–3), 156–171.CrossRefGoogle Scholar
  10. Barlas, Y. (1996). Formal aspects of model validity and validation in system dynamics. System Dynamics Review, 12(3), 183–210.CrossRefGoogle Scholar
  11. Bass, F. M. (1969). New product growth for model consumer durables. Management Science, 15(5), 215–227.CrossRefGoogle Scholar
  12. Bass, F. M. (2004). Comments on a new product growth for model consumer durables the Bass Model. Management Science 50(12\_supplement), 1833–1840.Google Scholar
  13. Bellman, R., Clark, C. E., et al. (1957). On the construction of a multi-stage, multi-person business game. Operations Research, 5(4), 469–503.CrossRefGoogle Scholar
  14. Berry, A. J., Coad, A. F., Harris, E. P. et al. (2009). Emerging themes in management control: a review of recent literature. The British Accounting Review, 41(1), 2–20.Google Scholar
  15. Bianchi, C. (2010). Improving performance and fostering accountability in the public sector through system dynamics modelling: From an ’External’ to an ’Internal’ perspective. Systems Research and Behavioral Science, 27(4), 361–384.CrossRefGoogle Scholar
  16. Bianchi, C., & Montemaggiore, G. B. (2008). Enhancing strategy design and planning in public utilities through dynamic balanced scorecards: Insights from a project in a city water company. System Dynamics Review, 24(2), 175–213.CrossRefGoogle Scholar
  17. Bieger, T. and Reinhold, S. (2011). Innovative Geschäftsmodelle: Konzeptionelle Grundlagen, Gestaltungsfelder und unternehmerische Praxis. Innovative Geschäftsmodelle, pp. 13–70. T. Bieger, D. zu Knyphausen-Aufseß and C. Krys. Berlin, Springer.Google Scholar
  18. Black, L. J., & Andersen, D. F. (2012). Using visual representations as boundary objects to resolve conflict in collaborative model-building approaches. Systems Research and Behavioral Science, 29(2), 194–208.CrossRefGoogle Scholar
  19. Black, L. J., Carlile, P. R., et al. (2004). A dynamic theory of expertise and occupational boundaries in new technology implementation: Building on Barley’s Study of CT scanning. Administrative Science Quarterly, 49(4), 572–607.Google Scholar
  20. Bucherer, E. (2010). Business model innovation: Guidelines for a structured approach. Shaker: Aachen. 2010.Google Scholar
  21. Carlile, P. R. (2002). A pragmatic view of knowledge and boundaries: Boundary objects in new product development. Organization Science, 13(4), 442–455.CrossRefGoogle Scholar
  22. 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.CrossRefGoogle Scholar
  23. Chesbrough, H. (2010). Business model innovation: Opportunities and barriers. Long Range Planning, 43(2–3), 354–363.CrossRefGoogle Scholar
  24. Cusumano, M. (2013). Technology strategy and management—Evaluating a startup venture. Communications of the ACM, 56(10), 26–29.CrossRefGoogle Scholar
  25. DaSilva, C. M. and Trkman, P. (2013). Business model: What it is and what it is not. Long range planning.Google Scholar
  26. Davis, J. P., Eisenhardt, K. M., et al. (2007). Developing theory through simulation methods. Academy of Management Review, 32(2), 480–499.CrossRefGoogle Scholar
  27. Degraeve, Z., Labro, E., et al. (2000). Total cost of ownership purchasing of a service: The case of airline selection at Alcatel Bell. European Journal of Operational Research, 156(1), 23–40.CrossRefGoogle Scholar
  28. Demil, B., & Lecocq, X. (2010). Business model evolution. In search of dynamic consistency. Long Range Planning, 43(2–3), 227–246.CrossRefGoogle Scholar
  29. Eden, C., Williams, T., et al. (2000). On the nature of disruption and delay (D&D) in major projects. Journal of the Operational Research Society, 51(4), 291–300.Google Scholar
  30. Eisenhardt, K. M. (1989). Building theories from case-study research. Academy of Management Review, 14(4), 532–550.Google Scholar
  31. Ford, A., & Flynn, H. (2005). Statistical screening of system dynamics models. System Dynamics Review, 21(4), 273–303.CrossRefGoogle Scholar
  32. Forrester, J. W. (1961). Industrial dynamics. Cambridge: Productivity Press.Google Scholar
  33. Forrester, J. W. and Senge, P. M. (1980). Tests for building confidence in system dynamics models. System dynamics: TIMS studies in the management sciences, vol. 14. A. A. Legasto, J. W. Forrester and J. M. Lyneis. Amsterdam, North-Holland.Google Scholar
  34. Gage, D. (2012). The venture capital secret: 3 out of 4 startups fail. The wall street journal. New York.Google Scholar
  35. Gassmann, O., Frankenberg, K., et al. (2013). Geschäftsmodelle entwickeln: 55 innovative Konzepte mit dem St. Muenchen, Hanser Verlag: Galler Business Model Navigator.CrossRefGoogle Scholar
  36. Gonzalez, C., Vanyukov, P., et al. (2005). The use of microworlds to study dynamic decision making. Computers in Human Behavior, 21(2), 273–286.CrossRefGoogle Scholar
  37. Groesser, S. N. (2012). Stichwort: System dynamics. Heidelberg, Gabler: Gabler Wirtschaftslexikon.Google Scholar
  38. Groesser, S. N. (2015a). Lab or Reality: Entwicklung und analyse von Geschäftsmodellen durch das kybernetische Unternehmensmodell Blue Company. Exploring Cybernetics: Kybernetik im interdisziplinären Diskurs, pp. 91–116. S. Jeschke, R. Schmitt and A. Dröge. Berlin, Springer.Google Scholar
  39. Groesser, S. N. (2015b). Stichwort: Dynamische Komplexität. Heidelberg, Gabler: Gabler Wirtschaftslexikon.Google Scholar
  40. Groesser, S. N. and Buergi, M. (2014). Analyse von Geschäftsmodellen und Entwicklung von Maßnahmen durch computergestützte Simulationsexperimente. Modellbasiertes management, pp. 53–66. S. N. Groesser. Berlin, Duncker & Humblot.Google Scholar
  41. Groesser, S. N., & Schwaninger, M. (2012). Contributions to model validation: Hierarchy, process, and cessation. System Dynamics Review, 28(2), 157–181.CrossRefGoogle Scholar
  42. Guenther, T. (2013). Conceptualisations of ‘controlling’ in German-speaking countries: analysis and comparison with Anglo-American management control frameworks. Journal of Management Control, 23(4), 269–290.CrossRefGoogle Scholar
  43. Hall, R. I., Aitchison, P. W., et al. (1994). Causal policy maps of managers: Formal methods for elicitation and analysis. System Dynamics Review, 10(4), 337–360.CrossRefGoogle Scholar
  44. Harrison, J. R., Lin, Z., et al. (2007). Simulation modeling in organizational and management research. Academy of Management Review, 32(4), 1229–1245.CrossRefGoogle Scholar
  45. Homer, J. B. (1996). Why we iterate: Scientific modeling in theory and practice. System Dynamics Review, 12(1), 1–19.CrossRefGoogle Scholar
  46. Huelsbeck, D. P., Merchant, K. A., et al. (2011). On testing business models. The Accounting Review, 86(5), 1631–1654.CrossRefGoogle Scholar
  47. Jarzabkowski, P., Giulietti, M., et al. (2013). We don’t need no education—or do we? Management education and alumni adoption of strategy tools. Journal of Management Inquiry, 22(1), 4–24.CrossRefGoogle Scholar
  48. Jarzabkowski, P., & Kaplan, S. (2015). Strategy tools-in-use: A framework for understanding “technologies of rationality” in practice. Strategic Management Journal, 36(4), 537–558.CrossRefGoogle Scholar
  49. Johnson, M. W., Christensen, C. M. et al. (2008). Reinventing your business model. Harvard Business Review 86(12): 50.Google Scholar
  50. Karakul, M. and Quadrat-Ullah, H. (2008). How to improve dynamic decision making? Practice and promise. Complex Decision Making, pp. 3–24. H. Qudrat-Ullah, J. M. Spector and P. Davidsen. Berlin, Springer Publishing.Google Scholar
  51. Kasanen, E., Lukka, K., et al. (1993). The constructive approach in management accounting. Journal of Management Accounting Research, 5(4), 243–264.Google Scholar
  52. Katz, S., & Grösser, S. N. (2013). Explicate the links between external trends, stakeholder objectives, and an organization’s strategy by an augmented balanced scorecard. SEM Radar, 12(2), 29–47.Google Scholar
  53. Kurawarwala, A., & Matsuo, H. (1996). Forecasting and inventory management of short life-cycle products. Operations Research, 44(1), 131–150.CrossRefGoogle Scholar
  54. Labro, E. (2015). Using simulation methods in accounting research. Journal of Management Control, 26(2), 99–104.CrossRefGoogle Scholar
  55. Labro, E., & Tuomela, T.-S. (2003). On bringing more action into management accounting re-search: Process considerations based on two constructive case studies. European Accounting Review, 12(3), 409–442.CrossRefGoogle Scholar
  56. Labro, E., & Vanhoucke, M. (2007). A simulation analysis of interactions among errors in costing systems. The Accounting Review, 82(4), 939–962.CrossRefGoogle Scholar
  57. Lane, D. C. (1992). Modelling as learning: A consultancy methodology for enhancing learning in management teams. European Journal of Operational Research, 59(1), 64–84.CrossRefGoogle Scholar
  58. 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.CrossRefGoogle Scholar
  59. Levinthal, D. A. (1997). Adaption on rugged landscapes. Management Science, 43(7), 934–950.CrossRefGoogle Scholar
  60. Lindholm, A.-L. (2008). A constructive study on creating core business relevant CREM strategy and performance measures. Facilities, 28(7–8), 343–358.CrossRefGoogle Scholar
  61. Little, J. D. C. (1970). Models and managers: The concept of a decision calculus. Management Science 16(8): B-465–B-486.Google Scholar
  62. Lukka, K. (2000). The key issues of applying the constructive approach to field research. Management expertise for the new Millennium: In Commemoration of the 50th anniversary of the Turku school of economics and business administration. Publications of Turku school of economics and business administration, pp. 113–128. T. Reponen.Google Scholar
  63. Luna-Reyes, L. F., & Andersen, D. L. (2003). Collecting and analyzing qualitative data for system dynamics: Methods and models. System Dynamics Review, 19(4), 271–296.CrossRefGoogle Scholar
  64. Luna-Reyes, L. F., Diker, V. G., et al. (2003). Interviewing as a strategy for the assessment of system dynamics models. System Dynamics Review, 19(4), 271–296.CrossRefGoogle Scholar
  65. Mahadevan, B. (2000). Business models for internet-based E-commerce: An anatomy. California Management Review 42(4), 55.Google Scholar
  66. March, J. G. (1991). Exploration and exploitation in organizational learning. Organization Science, 2(1), 71–87.CrossRefGoogle Scholar
  67. Markides, C. C. (1999). A dynamic view of strategy. Sloan Management Review 40(3), 55.Google Scholar
  68. Markides, C. C. (2013). Business model innovation: What can the ambidexterity literature teach us? Academy of Management Perspectives, 27(4), 313–323.CrossRefGoogle Scholar
  69. Markóczy, L., & Goldberg, J. (1995). A method for eliciting and comparing causal maps. Journal of Management, 21(2), 305–333.CrossRefGoogle Scholar
  70. Merchant, K. A., & Otley, D. T. (2006). A review of the literature on control and accountability. Handbooks of Management Accounting Research. S. Christopher, A. G. H. Chapman and D. S. Michael. London, Elsevier., 2, 785–802.Google Scholar
  71. Merchant, K. A., & Van der Stede, W. A. (2003). Management control systems: performance measurement, evaluation and incentives. Harlow: Prentice Hall.Google Scholar
  72. Miller, G. (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information. The Psychological Review, 63(1), 81–97.CrossRefGoogle Scholar
  73. Morecroft, J. D. W. (1984). Strategy support models. Strategic Management Journal, 5(3), 215–229.CrossRefGoogle Scholar
  74. Morecroft, J. D. W. (2007). Strategic modelling and business dynamics: A feedback systems approach. Chichester, John Wiley & Sons.Google Scholar
  75. Morecroft, J. D. W., & Sterman, J. D. (Eds.). (1994). Modeling for learning organizations. OR, Productivity Press: System Dynamics Series. Portland.Google Scholar
  76. Norton, J. A., & Bass, F. M. (1987). A diffusion theory model of adoption and substitution for successive generations of high-technology products. Management Science, 33(9), 1069–1086.CrossRefGoogle Scholar
  77. O’Sullivan, A., & Sheffrin, S. M. (2003). Economics: Principles in action. N.J.: Pearson Prentice Hall, Upper Saddle River.Google Scholar
  78. Osterwalder, A., & Pigneur, Y. (2010). Business model generation: A handbook for visionaries, game changers, and challengers. New Jersey: Wiley.Google Scholar
  79. Otley, D. T. (1999). Performance management: A framework for management control systems research. Management Accounting Research, 10(4), 363–382.CrossRefGoogle Scholar
  80. Paich, M., & Sterman, J. D. (1993). Boom, bust, and failures to learn in experimental markets. Management Science, 39(12), 1439–1458.CrossRefGoogle Scholar
  81. Porter, M. E. (1996). What is strategy? Harvard Business Review, 74(6), 61–78.Google Scholar
  82. Porter, M. E., & Siggelkow, N. (2008). Contextuality within activity systems and sustainability of competitive advantage. Academy of Management Perspectives, 22(2), 34–56.CrossRefGoogle Scholar
  83. Qudrat-Ullah, H. (2014). Yes we can: improving performance in dynamic tasks. Decision Support Systems, 61(1), 23–33.CrossRefGoogle Scholar
  84. Rahmandad, H., & Repenning, N. (2015). Capability erosion dynamics. Strategic Management Journal. doi:10.1002/smj.2354.
  85. Repenning, N. P. (2002). A simulation-based approach to understanding the dynamics of innovation implementation. Organization Science, 13(2), 109–127.CrossRefGoogle Scholar
  86. Richardson, G. P. (2009). The basic elements of system dynamics. Encyclopedia of complexity and systems science, pp. 8967–8974. R. A. Meyers. New York, NY, Springer Publishing.Google Scholar
  87. Richardson, G. P. (2013). Concept models in group model building. System Dynamics Review (Wiley), 29(1), 42–55.CrossRefGoogle Scholar
  88. Rieg, R., & Esslinger, S. (2012). Die Wirksamkeit der balanced scorecard. Controlling. In: Zeitschrift für erfolgsorientierte UnternehmenssteuerungGoogle Scholar
  89. Rigby, D. (2001). Management tools and techniques: A survey. California Management Review, 43(2), 139–160.CrossRefGoogle Scholar
  90. Rigby, D., & Gillies, C. (2000). Making the most of management tools and techniques: A survey from Bain and Company. Strategic Change, 9(5), 269–274.CrossRefGoogle Scholar
  91. Rodrigues, A., & Bowers, J. (1996). The role of system dynamics in project management. International Journal of Project Management, 14(4), 213–220.CrossRefGoogle Scholar
  92. Rudolph, J. W., Morrison, B., et al. (2009). The dynamics of action-oriented problem solving: Linking interpretation and choice. Academy of Management Review, 34(4), 733–756.CrossRefGoogle Scholar
  93. Sargut, G., & McGrath, R. G. (2011). Learning to Live with Complexity. Harvard Business Review, 144(8), 4–14.Google Scholar
  94. Schöneborn, F. (2003). Strategisches controlling mit system dynamics. Heidelberg: Physica-Verlag.Google Scholar
  95. Schwaninger, M. (2009). Intelligent organizations: Powerful models for systemic management. Berlin: Springer.Google Scholar
  96. Schwaninger, M. (2010). Complex versus complicated: The how of coping with complexity. Kybernetes, 38(1/2), 83–92.Google Scholar
  97. Schwaninger, M., & Groesser, S. N. (2008). Model-based theory-building with system dynamics. Systems Research and Behavioral Science, 25(4), 447–465.CrossRefGoogle Scholar
  98. Schwaninger, M., & Groesser, S. N. (2009). System dynamics modeling: Validation for quality assurance. Encyclopedia of complexity and system science. Berlin, Springer.Google Scholar
  99. Schwenke, M. and Grösser, S. N. (2014). Modellbasiertes management für dynamische problemstellungen zur Erweiterung statischer managementwerkzeuge. Modellbasiertes management. S. N. Groesser, M. Schwaninger, M. Tilebein, T. Fischer and S. Jeschke. Berlin, Duncker und Humblot.Google Scholar
  100. Senge, P. M. (1990). The fifth discipline: The art and practice of the learning organization. New York, Currency & Doubleday.Google Scholar
  101. Shah, D., Kumar, V., et al. (2014). Managing customer profits: The power of habits. Journal of Marketing Research, 51(6), 726–741.CrossRefGoogle Scholar
  102. Sillanpää, A., & Laamanen, T. (2009). Positive and negative feedback effects in competition for dominance of network business systems. Research Policy, 38(5), 871–884.CrossRefGoogle Scholar
  103. Simons, R. L. (1995). Levers of control: how managers use innovative control systems to drive strategic renewal. Boston: Harvard Business School Press.Google Scholar
  104. Simons, R. L. (2000). Performance measurement and control systems for implementing strategy. Pearson: Upper Saddle River.Google Scholar
  105. Smith, W. K., Binns, A., et al. (2010). Complex business models: Managing strategic paradoxes simultaneously. Long Range Planning, 43(2–3), 448–461.CrossRefGoogle Scholar
  106. Sosna, M., Trevinyo-Rodríguez, R. N., et al. (2010). Business model innovation through trial-and-error learning: The Naturhouse Case. Long Range Planning, 43(2–3), 383–407.CrossRefGoogle Scholar
  107. Spee, A. P., & Jarzabkowski, P. (2009). Strategy tools as boundary objects. Strategic Organization, 7(2), 223–232.CrossRefGoogle Scholar
  108. Stake, R. E. (1996). The art of case study research. Thousand Oaks, CA: Sage Publications.Google Scholar
  109. Sterman, J. (2000). Learning in and about complex systems. Reflections, 1(3), 24–51.CrossRefGoogle Scholar
  110. Sterman, J., Oliva, R., et al. (2015). System dynamics perspectives and modeling opportunities for research in operations management. Journal of Operations Management. doi:10.1016/j.jom.2015.07.001.
  111. Sterman, J. D. (2000). Business dynamics: Systems thinking and modeling for a complex world. Boston, MA: McGraw-Hill.Google Scholar
  112. Sterman, J. D. (2001). System dynamics modeling: Tools for learning in a complex world. California Management Review, 43(4), 8–24.CrossRefGoogle Scholar
  113. Sterman, J. D. (2010). Does formal system dynamics training improve people’s understanding of accumulation? System Dynamics Review, 26(4), 316–334.CrossRefGoogle Scholar
  114. Sterman, J. D., Henderson, R., et al. (2007). Getting big too fast: Strategic dynamics with increasing returns and bounded rationality. Management Science, 53(4), 683–696.CrossRefGoogle Scholar
  115. Strauß, E., & Zecher, C. (2013). Management control systems: a review. Journal of Management Control, 23(4), 233–268.CrossRefGoogle Scholar
  116. Teece, D. J. (2007). Explicating dynamic capabilities: The nature and microfoundations of (sustainable) enterprise performance. Strategic Management Journal, 28(13), 1319–1350.CrossRefGoogle Scholar
  117. Teece, D. J. (2010). Business models, business strategy and innovation. Long Range Planning, 43(2–3), 172–194.CrossRefGoogle Scholar
  118. Van den Belt, M. (Ed.). (2004). Mediated modeling : A system dynamics approach to environmental consensus building. Washington, D.C, Island Press.Google Scholar
  119. van Nistelrooij, L. P. J., Rouwette, E. A. J. A., et al. (2015). The eye of the beholder: A case example of changing clients’ perspectives through involvement in the model validation process. Systems Research and Behavioral Science, 32(4), 437–449.CrossRefGoogle Scholar
  120. Vennix, J. A. M. (1995). Building consensus in strategic decision-making—System dynamics as a group support system. Group Decision and Negotiation, 4(4), 335–355.CrossRefGoogle Scholar
  121. Vennix, J. A. M. (1996). Group model building: Facilitating team learning using system dynamics. Chichester: Wiley.Google Scholar
  122. Warren, K. (2005). Improving strategic management with the fundamental principles of system dynamics. System Dynamics Review, 21(4), 329–350.CrossRefGoogle Scholar
  123. Warren, K. (2008). Strategic management dynamics Chichester. England, Wiley: West Sussex.Google Scholar
  124. Willemstein, L., van der Valk, T., et al. (2007). Dynamics in business models: An empirical analysis of medical biotechnology firms in the Netherlands. Technovation, 27(4), 221–232.CrossRefGoogle Scholar
  125. Wirtz, B. W. (2011). Business model management: Design-instrumente-Erfolgsfaktoren von Geschäftsmodellen. Wiesbaden: Gabler.CrossRefGoogle Scholar
  126. Yin, R. K. (2013). Case study research. Beverly Hills, CA: Sage Publications.Google Scholar
  127. Zott, C., Amit, R., et al. (2011). The business model: Recent developments and future research. Journal of Management, 37(4), 1019–1042.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  1. 1.School of Management, Strategy and Simulation LabBern University of Applied SciencesBernSwitzerland
  2. 2.LangenGermany

Personalised recommendations