Business model experimentation in micro and small enterprises: integrating Business Model Canvas and System Dynamics

Letícia da Silva Stefano; Pedro Paulo Barbosa Feitosa; Daniel Pacheco Lacerda; Maria Isabel Wolf Motta Morandi; Fabio Sartori Piran

doi:10.14488/1980-5411.20260032

Research Article

Business model experimentation in micro and small enterprises: integrating Business Model Canvas and System Dynamics

Letícia da Silva Stefano; Pedro Paulo Barbosa Feitosa; Daniel Pacheco Lacerda; Maria Isabel Wolf Motta Morandi; Fabio Sartori Piran

http://dx.doi.org/10.14488/1980-5411.20260032 Production, vol.36, e20260032, 2026

PDF

Downloads: 0

Abstract

Paper aims: The static nature of the Business Model Canvas (BMC) limits strategic decision-making in dynamic environments, particularly for micro and small enterprises (MSEs). This study develops and validates a dynamic framework integrating the BMC and System Dynamics (SD) to support business model experimentation over time.

Originality: The research transforms the BMC into a dynamic simulation environment by incorporating feedback loops, delays, and non-linear relationships.

Research method: A mixed-method approach was adopted. A systematic literature review identified key business model variables and relationships. Based on the nine BMC building blocks, a System Dynamics model was developed, validated by experts, and applied to scenario analyses involving different business models, market growth conditions, and input price variations.

Main findings: The simulations reveal dynamic effects not captured by static representations. B2B models showed lower but more stable performance under adverse conditions, whereas B2C models achieved higher profitability under favorable scenarios but greater sensitivity to input price volatility.

Implications for theory and practice: The framework integrates business model design and systems thinking while providing entrepreneurs with a decision-support tool to test strategic alternatives under uncertainty. Future research should apply the model in real-world settings to evaluate its effects on entrepreneurial decision-making and firm survival.

Keywords

Business Model Canvas, System Dynamics, Business model experimentation, Scenario analysis, Decision support

References

Bertrand, J. W. M., & Fransoo, J. C. (2002). Operations management research methodologies using quantitative modeling. International Journal of Operations & Production Management, 22(2), 241-264. https://doi.org/10.1108/01443570210414338.

Bhatia, P., & Diaz-Elsayed, N. (2023). Facilitating decision-making for the adoption of smart manufacturing technologies by SMEs via fuzzy TOPSIS. International Journal of Production Economics, 257, 108762. https://doi.org/10.1016/j.ijpe.2022.108762.

Bland, D. J., Osterwalder, A., Smith, A., & Papadakos, T. (2020). Testing business ideas. Retrieved in 8 March 2026, from https://www.strategyzer.com/pages/hubspot-form-test

Brugler, S., Gardezi, M., Dadkhah, A., Rizzo, D. M., Zia, A., & Clay, S. A. (2024). Improving decision support systems with machine learning: identifying barriers to adoption. Agronomy Journal, 116(3), 1229-1236. https://doi.org/10.1002/agj2.21432.

Brunswicker, S., Wrigley, C., & Bucolo, S. (2013). Business model experimentation: what is the role of design-led prototyping in developing novel business models? In M. Curley & P. Formica (Eds.), The experimental nature of new venture creation (Innovation, Technology, and Knowledge Management, pp. 139-151). Cham: Springer. https://doi.org/10.1007/978-3-319-00179-1_13.

Ching, H. Y., & Fauvel, C. (2013). Criticisms, variations and experiences with Business Model Canvas. European Journal of Agriculture and Forestry Research, 1(2), 26-37.

Cosenz, F. (2017). Supporting start-up business model design through system dynamics modelling. Management Decision, 55(1), 57-80. https://doi.org/10.1108/MD-06-2016-0395.

Cosenz, F., & Noto, G. (2018). A dynamic business modelling approach to design and experiment new business venture strategies. Long Range Planning, 51(1), 127-140. https://doi.org/10.1016/j.lrp.2017.07.001.

Cosenz, F., Rodrigues, V. P., & Rosati, F. (2020). Dynamic business modeling for sustainability: exploring a system dynamics perspective to develop sustainable business models. Business Strategy and the Environment, 29(2), 651-664. https://doi.org/10.1002/bse.2395.

Demil, B., & Lecocq, X. (2010). Business model evolution: in search of dynamic consistency. Long Range Planning, 43(2–3), 227-246. https://doi.org/10.1016/j.lrp.2010.02.004.

Euchner, J., & Ganguly, A. (2014). Business model innovation in practice: a systematic approach to business model innovation can help capture value and reduce risks. Research Technology Management, 57(6), 33-39.

Khodaei, H., & Ortt, R. (2019). Capturing dynamics in business model frameworks. Journal of Open Innovation, 5(1), 8. https://doi.org/10.3390/joitmc5010008.

Kim, H., & Andersen, D. F. (2012). Building confidence in causal maps generated from purposive text data: mapping transcripts of the Federal Reserve. System Dynamics Review, 28(4), 311-328. https://doi.org/10.1002/sdr.1480.

Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33(1), 159-174. https://doi.org/10.2307/2529310. PMid:843571.

Madanaguli, A., Parida, V., Sjödin, D., & Oghazi, P. (2023). Literature review on industrial digital platforms: a business model perspective and suggestions for future research. Technological Forecasting and Social Change, 194, 122606. https://doi.org/10.1016/j.techfore.2023.122606.

Martikainen, A., Niemi, P., & Pekkanen, P. (2014). Developing a service offering for a logistical service provider-Case of local food supply chain. International Journal of Production Economics, 157(1), 318-326. https://doi.org/10.1016/j.ijpe.2013.05.026.

Martins, J. C., Lacerda, D. P., Wolf Motta Morandi, M. I., Goldmeyer, D., & Piran, F. S. (2020). Systems dynamic modeling to analyze the systemic viability of the combined use of regenerative converters and energy storage in a UPS manufacturer. Journal of Cleaner Production, 246, 118950. https://doi.org/10.1016/j.jclepro.2019.118950.

Orji, I. J., & Liu, S. (2020). A dynamic perspective on the key drivers of innovation-led lean approaches to achieve sustainability in manufacturing supply chain. International Journal of Production Economics, 219, 480. https://doi.org/10.1016/j.ijpe.2018.12.002.

Osterwalder, A., & Pigneur, Y. (2011). Business Model Generation: inovação em modelos de negócios (Vol. 3). Rio de Janeiro: Alta Books.

Poles, R. (2013). System Dynamics modelling of a production and inventory system for remanufacturing to evaluate system improvement strategies. International Journal of Production Economics, 144(1), 189-199. https://doi.org/10.1016/j.ijpe.2013.02.003.

Romero, M. C., Villalobos, J., & Sanchez, M. (2015). Simulating the business model canvas using system dynamics. In 2015 10th Colombian Computing Conference, 10CCC 2015 (pp. 527-534), Bogota, Colombia. New York: IEEE. https://doi.org/10.1109/ColumbianCC.2015.7333469.

Saka, A. B., Chan, D. W. M., & Wuni, I. Y. (2022). Knowledge-based decision support for BIM adoption by small and medium-sized enterprises in developing economies. Automation in Construction, 141, 104407. https://doi.org/10.1016/j.autcon.2022.104407.

Santos, S. P., Belton, V., & Howick, S. (2002). Adding value to performance measurement by using system dynamics and multicriteria analysis. International Journal of Operations & Production Management, 22(11), 1246-1272. https://doi.org/10.1108/01443570210450284.

Schoemaker, P. J. H. (1991). When and how to use scenario planning: a heuristic approach with illustration. Journal of Forecasting, 10(6), 549-564. https://doi.org/10.1002/for.3980100602.

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

Serviço Brasileiro de Apoio às Micro e Pequenas Empresas – SEBRAE. (2021). A sobrevivência das empresas. Brasília.

Serviço Brasileiro de Apoio às Micro e Pequenas Empresas – SEBRAE. (2024). Micro e pequenas empresas geram 27% do PIB do Brasil. Brasília. Retrieved in 8 March 2026, from https://sebrae.com.br/sites/PortalSebrae/ufs/mt/noticias/micro-e-pequenas-empresas-geram-27-do-pib-do-brasil,ad0fc70646467410VgnVCM2000003c74010aRCRD

Sinuany-Stern, Z. (2023). Foundations of operations research: from linear programming to data envelopment analysis. European Journal of Operational Research, 306(3), 1069-1080. https://doi.org/10.1016/j.ejor.2022.10.046.

Sterman, J. D. (2000). Business Dynamics Systems: thinking and modeling for a complex world. Boston: Irwin/McGraw-Hill.

Teece, D. J., Pisano, G., & Shuen, A. (1997). Dynamic capabilities and strategic management. Strategic Management Journal, 18(7), 509-533. https://doi.org/10.1002/(SICI)1097-0266(199708)18:7<509::AID-SMJ882>3.0.CO;2-Z.

Wrigley, C., Bucolo, S., & Straker, K. (2016). Designing new business models: blue sky thinking and testing. The Journal of Business Strategy, 37(5), 22-31. https://doi.org/10.1108/JBS-04-2015-0041.

Submitted date:
03/04/2026

Accepted date:
06/26/2026

Business model experimentation in micro and small enterprises: integrating Business Model Canvas and System Dynamics

Letícia da Silva Stefano; Pedro Paulo Barbosa Feitosa; Daniel Pacheco Lacerda; Maria Isabel Wolf Motta Morandi; Fabio Sartori Piran

Abstract

Keywords

References

Links

Share

Production