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

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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.

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Notes

  1. The term tool is a generic name for frameworks, concepts, approach, or methods (Jarzabkowski and Kaplan 2015).

  2. In the following, we refer to the company as MIFLORA.

  3. In the following, model variables are written in italics.

  4. Zendesk (http://www.zendesk.de) is a customer service provider. It is designed for companies that want to establish and improve their customer relationships.

  5. ©Vensim (www.vensim.com) is developed by Ventana Systems.

References

  • Abdelkafi, N. (2012). Open business models for the greater good. Die Unternehmung, 66(3), 299–317.

    Article  Google Scholar 

  • Amit, R., & Zott, C. (2001). Value creation in E-business. Strategic Management Journal, 22(6–7), 493–520.

    Article  Google Scholar 

  • Andersen, D. F., & Richardson, G. P. (1997). Scripts for group model building. System Dynamics Review, 13(2), 107–129.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Anthony, R. N., & Govindarajan, V. (2007). Management control systems. Boston: McGraw-Hill.

    Google Scholar 

  • Ashby, R. W. (1956). Introduction to cybernetics. London: Chapman & Hall.

    Book  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Baden-Fuller, C., Demil, B., et al. (2010). Editorial. Long Range Planning, 43(2–3), 143–145.

    Article  Google Scholar 

  • Baden-Fuller, C., & Morgan, M. S. (2010). Business models as models. Long Range Planning, 43(2–3), 156–171.

    Article  Google Scholar 

  • Barlas, Y. (1996). Formal aspects of model validity and validation in system dynamics. System Dynamics Review, 12(3), 183–210.

    Article  Google Scholar 

  • Bass, F. M. (1969). New product growth for model consumer durables. Management Science, 15(5), 215–227.

    Article  Google Scholar 

  • Bass, F. M. (2004). Comments on a new product growth for model consumer durables the Bass Model. Management Science 50(12\_supplement), 1833–1840.

  • 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.

    Article  Google Scholar 

  • 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.

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

  • 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.

    Article  Google Scholar 

  • 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 

  • Bucherer, E. (2010). Business model innovation: Guidelines for a structured approach. Shaker: Aachen. 2010.

    Google Scholar 

  • Carlile, P. R. (2002). A pragmatic view of knowledge and boundaries: Boundary objects in new product development. Organization Science, 13(4), 442–455.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Chesbrough, H. (2010). Business model innovation: Opportunities and barriers. Long Range Planning, 43(2–3), 354–363.

    Article  Google Scholar 

  • Cusumano, M. (2013). Technology strategy and management—Evaluating a startup venture. Communications of the ACM, 56(10), 26–29.

    Article  Google Scholar 

  • DaSilva, C. M. and Trkman, P. (2013). Business model: What it is and what it is not. Long range planning.

  • Davis, J. P., Eisenhardt, K. M., et al. (2007). Developing theory through simulation methods. Academy of Management Review, 32(2), 480–499.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Demil, B., & Lecocq, X. (2010). Business model evolution. In search of dynamic consistency. Long Range Planning, 43(2–3), 227–246.

    Article  Google Scholar 

  • 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 

  • Eisenhardt, K. M. (1989). Building theories from case-study research. Academy of Management Review, 14(4), 532–550.

    Google Scholar 

  • Ford, A., & Flynn, H. (2005). Statistical screening of system dynamics models. System Dynamics Review, 21(4), 273–303.

    Article  Google Scholar 

  • Forrester, J. W. (1961). Industrial dynamics. Cambridge: Productivity Press.

    Google Scholar 

  • 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.

  • Gage, D. (2012). The venture capital secret: 3 out of 4 startups fail. The wall street journal. New York.

  • Gassmann, O., Frankenberg, K., et al. (2013). Geschäftsmodelle entwickeln: 55 innovative Konzepte mit dem St. Muenchen, Hanser Verlag: Galler Business Model Navigator.

    Book  Google Scholar 

  • Gonzalez, C., Vanyukov, P., et al. (2005). The use of microworlds to study dynamic decision making. Computers in Human Behavior, 21(2), 273–286.

    Article  Google Scholar 

  • Groesser, S. N. (2012). Stichwort: System dynamics. Heidelberg, Gabler: Gabler Wirtschaftslexikon.

    Google Scholar 

  • 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.

  • Groesser, S. N. (2015b). Stichwort: Dynamische Komplexität. Heidelberg, Gabler: Gabler Wirtschaftslexikon.

  • 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.

  • Groesser, S. N., & Schwaninger, M. (2012). Contributions to model validation: Hierarchy, process, and cessation. System Dynamics Review, 28(2), 157–181.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Harrison, J. R., Lin, Z., et al. (2007). Simulation modeling in organizational and management research. Academy of Management Review, 32(4), 1229–1245.

    Article  Google Scholar 

  • Homer, J. B. (1996). Why we iterate: Scientific modeling in theory and practice. System Dynamics Review, 12(1), 1–19.

    Article  Google Scholar 

  • Huelsbeck, D. P., Merchant, K. A., et al. (2011). On testing business models. The Accounting Review, 86(5), 1631–1654.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Johnson, M. W., Christensen, C. M. et al. (2008). Reinventing your business model. Harvard Business Review 86(12): 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.

  • Kasanen, E., Lukka, K., et al. (1993). The constructive approach in management accounting. Journal of Management Accounting Research, 5(4), 243–264.

    Google Scholar 

  • 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 

  • Kurawarwala, A., & Matsuo, H. (1996). Forecasting and inventory management of short life-cycle products. Operations Research, 44(1), 131–150.

    Article  Google Scholar 

  • Labro, E. (2015). Using simulation methods in accounting research. Journal of Management Control, 26(2), 99–104.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Labro, E., & Vanhoucke, M. (2007). A simulation analysis of interactions among errors in costing systems. The Accounting Review, 82(4), 939–962.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Levinthal, D. A. (1997). Adaption on rugged landscapes. Management Science, 43(7), 934–950.

    Article  Google Scholar 

  • Lindholm, A.-L. (2008). A constructive study on creating core business relevant CREM strategy and performance measures. Facilities, 28(7–8), 343–358.

    Article  Google Scholar 

  • Little, J. D. C. (1970). Models and managers: The concept of a decision calculus. Management Science 16(8): B-465–B-486.

  • 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.

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Mahadevan, B. (2000). Business models for internet-based E-commerce: An anatomy. California Management Review 42(4), 55.

  • March, J. G. (1991). Exploration and exploitation in organizational learning. Organization Science, 2(1), 71–87.

    Article  Google Scholar 

  • Markides, C. C. (1999). A dynamic view of strategy. Sloan Management Review 40(3), 55.

  • Markides, C. C. (2013). Business model innovation: What can the ambidexterity literature teach us? Academy of Management Perspectives, 27(4), 313–323.

    Article  Google Scholar 

  • Markóczy, L., & Goldberg, J. (1995). A method for eliciting and comparing causal maps. Journal of Management, 21(2), 305–333.

    Article  Google Scholar 

  • 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.

  • Merchant, K. A., & Van der Stede, W. A. (2003). Management control systems: performance measurement, evaluation and incentives. Harlow: Prentice Hall.

    Google Scholar 

  • 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.

    Article  Google Scholar 

  • Morecroft, J. D. W. (1984). Strategy support models. Strategic Management Journal, 5(3), 215–229.

    Article  Google Scholar 

  • Morecroft, J. D. W. (2007). Strategic modelling and business dynamics: A feedback systems approach. Chichester, John Wiley & Sons.

  • Morecroft, J. D. W., & Sterman, J. D. (Eds.). (1994). Modeling for learning organizations. OR, Productivity Press: System Dynamics Series. Portland.

  • 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.

    Article  Google Scholar 

  • O’Sullivan, A., & Sheffrin, S. M. (2003). Economics: Principles in action. N.J.: Pearson Prentice Hall, Upper Saddle River.

    Google Scholar 

  • Osterwalder, A., & Pigneur, Y. (2010). Business model generation: A handbook for visionaries, game changers, and challengers. New Jersey: Wiley.

    Google Scholar 

  • Otley, D. T. (1999). Performance management: A framework for management control systems research. Management Accounting Research, 10(4), 363–382.

    Article  Google Scholar 

  • Paich, M., & Sterman, J. D. (1993). Boom, bust, and failures to learn in experimental markets. Management Science, 39(12), 1439–1458.

    Article  Google Scholar 

  • Porter, M. E. (1996). What is strategy? Harvard Business Review, 74(6), 61–78.

    Google Scholar 

  • Porter, M. E., & Siggelkow, N. (2008). Contextuality within activity systems and sustainability of competitive advantage. Academy of Management Perspectives, 22(2), 34–56.

    Article  Google Scholar 

  • Qudrat-Ullah, H. (2014). Yes we can: improving performance in dynamic tasks. Decision Support Systems, 61(1), 23–33.

    Article  Google Scholar 

  • Rahmandad, H., & Repenning, N. (2015). Capability erosion dynamics. Strategic Management Journal. doi:10.1002/smj.2354.

  • Repenning, N. P. (2002). A simulation-based approach to understanding the dynamics of innovation implementation. Organization Science, 13(2), 109–127.

    Article  Google Scholar 

  • 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.

  • Richardson, G. P. (2013). Concept models in group model building. System Dynamics Review (Wiley), 29(1), 42–55.

    Article  Google Scholar 

  • Rieg, R., & Esslinger, S. (2012). Die Wirksamkeit der balanced scorecard. Controlling. In: Zeitschrift für erfolgsorientierte Unternehmenssteuerung

  • Rigby, D. (2001). Management tools and techniques: A survey. California Management Review, 43(2), 139–160.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Rodrigues, A., & Bowers, J. (1996). The role of system dynamics in project management. International Journal of Project Management, 14(4), 213–220.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Sargut, G., & McGrath, R. G. (2011). Learning to Live with Complexity. Harvard Business Review, 144(8), 4–14.

    Google Scholar 

  • Schöneborn, F. (2003). Strategisches controlling mit system dynamics. Heidelberg: Physica-Verlag.

    Google Scholar 

  • Schwaninger, M. (2009). Intelligent organizations: Powerful models for systemic management. Berlin: Springer.

    Google Scholar 

  • Schwaninger, M. (2010). Complex versus complicated: The how of coping with complexity. Kybernetes, 38(1/2), 83–92.

    Google Scholar 

  • Schwaninger, M., & Groesser, S. N. (2008). Model-based theory-building with system dynamics. Systems Research and Behavioral Science, 25(4), 447–465.

    Article  Google Scholar 

  • Schwaninger, M., & Groesser, S. N. (2009). System dynamics modeling: Validation for quality assurance. Encyclopedia of complexity and system science. Berlin, Springer.

  • 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.

  • Senge, P. M. (1990). The fifth discipline: The art and practice of the learning organization. New York, Currency & Doubleday.

  • Shah, D., Kumar, V., et al. (2014). Managing customer profits: The power of habits. Journal of Marketing Research, 51(6), 726–741.

    Article  Google Scholar 

  • Sillanpää, A., & Laamanen, T. (2009). Positive and negative feedback effects in competition for dominance of network business systems. Research Policy, 38(5), 871–884.

    Article  Google Scholar 

  • Simons, R. L. (1995). Levers of control: how managers use innovative control systems to drive strategic renewal. Boston: Harvard Business School Press.

    Google Scholar 

  • Simons, R. L. (2000). Performance measurement and control systems for implementing strategy. Pearson: Upper Saddle River.

    Google Scholar 

  • Smith, W. K., Binns, A., et al. (2010). Complex business models: Managing strategic paradoxes simultaneously. Long Range Planning, 43(2–3), 448–461.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Spee, A. P., & Jarzabkowski, P. (2009). Strategy tools as boundary objects. Strategic Organization, 7(2), 223–232.

    Article  Google Scholar 

  • Stake, R. E. (1996). The art of case study research. Thousand Oaks, CA: Sage Publications.

    Google Scholar 

  • Sterman, J. (2000). Learning in and about complex systems. Reflections, 1(3), 24–51.

    Article  Google Scholar 

  • 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.

  • Sterman, J. D. (2000). Business dynamics: Systems thinking and modeling for a complex world. Boston, MA: McGraw-Hill.

    Google Scholar 

  • Sterman, J. D. (2001). System dynamics modeling: Tools for learning in a complex world. California Management Review, 43(4), 8–24.

    Article  Google Scholar 

  • Sterman, J. D. (2010). Does formal system dynamics training improve people’s understanding of accumulation? System Dynamics Review, 26(4), 316–334.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Strauß, E., & Zecher, C. (2013). Management control systems: a review. Journal of Management Control, 23(4), 233–268.

    Article  Google Scholar 

  • Teece, D. J. (2007). Explicating dynamic capabilities: The nature and microfoundations of (sustainable) enterprise performance. Strategic Management Journal, 28(13), 1319–1350.

    Article  Google Scholar 

  • Teece, D. J. (2010). Business models, business strategy and innovation. Long Range Planning, 43(2–3), 172–194.

    Article  Google Scholar 

  • Van den Belt, M. (Ed.). (2004). Mediated modeling : A system dynamics approach to environmental consensus building. Washington, D.C, Island Press.

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Vennix, J. A. M. (1996). Group model building: Facilitating team learning using system dynamics. Chichester: Wiley.

    Google Scholar 

  • Warren, K. (2005). Improving strategic management with the fundamental principles of system dynamics. System Dynamics Review, 21(4), 329–350.

    Article  Google Scholar 

  • Warren, K. (2008). Strategic management dynamics Chichester. England, Wiley: West Sussex.

    Google Scholar 

  • 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.

    Article  Google Scholar 

  • Wirtz, B. W. (2011). Business model management: Design-instrumente-Erfolgsfaktoren von Geschäftsmodellen. Wiesbaden: Gabler.

    Book  Google Scholar 

  • Yin, R. K. (2013). Case study research. Beverly Hills, CA: Sage Publications.

    Google Scholar 

  • Zott, C., Amit, R., et al. (2011). The business model: Recent developments and future research. Journal of Management, 37(4), 1019–1042.

    Article  Google Scholar 

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Acknowledgments

This research was supported by the EU-Seventh Framework Program Grant No. 609027.

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Groesser, S.N., Jovy, N. Business model analysis using computational modeling: a strategy tool for exploration and decision-making. J Manag Control 27, 61–88 (2016). https://doi.org/10.1007/s00187-015-0222-1

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