Business Research

, Volume 6, Issue 2, pp 196–213 | Cite as

Improving Environmental Scanning Systems Using Bayesian Networks

  • Simon WelterEmail author
  • Jörg H. Mayer
  • Reiner Quick
Open Access


As companies’ environment is becoming increasingly volatile, scanning systems gain in importance. We propose a hybrid process model for such systems’ information gathering and interpretation tasks that combines quantitative information derived from regression analyses and qualitative knowledge from expert interviews. For the latter, we apply Bayesian networks. We derive the need for such a hybrid process model from a literature review. We lay out our model to find a suitable set of business environment indicators to forecast a company’s key financials. Deriving lessons learned from a prototype in the industrial sector, we evaluate the utility of our model following the design science research paradigm. We find our model to especially convince in completeness, transparency and transportability when compared with “pure” mathematical models.

JEL classification

C02 C11 C53 G17 M49 


corporate management balancing opportunities and threats regression analyses Bayesian networks information systems (IS) design design science research in IS case study 


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© The Author(s) 2013

This article is published under license to BioMed Central Ltd. Open AccessThis article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.

Authors and Affiliations

  1. 1.A.T. Kearney GmbHGermany
  2. 2.Institute of Information ManagementUniversity St. GallenSwitzerland
  3. 3.Department of Accounting and AuditingDarmstadt University of TechnologyGermany

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