Journal of Management Control

, Volume 27, Issue 1, pp 61–88

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

Original Paper

DOI: 10.1007/s00187-015-0222-1

Cite this article as:
Groesser, S.N. & Jovy, N. J Manag Control (2016) 27: 61. doi:10.1007/s00187-015-0222-1


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.


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)

Funding information

Funder NameGrant NumberFunding Note
Seventh Framework Programme
  • 609027

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

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