Decision tree learning for detecting turning points in business process orientation: a case of Croatian companies

Authors

  • Ljubica Milanović Glavan University of Zagreb, Faculty of Economics & Business, Department of Informatics
  • Vesna Bosilj Vukšić University of Zagreb, Faculty of Economics & Business, Department of Informatics
  • Nikola Vlahović University of Zagreb, Faculty of Economics & Business, Department of Informatics

Abstract

Companies worldwide are embracing Business Process Orientation (BPO) in order to improve their overall performance. This paper presents research results on key turning points in BPO maturity implementation efforts. A key turning point is defined as a component of business process maturity that leads to the establishment and expansion of other factors that move the organization to the next maturity level. Over the past few years, different methodologies for analyzing maturity state of BPO have been developed. The purpose of this paper is to investigate the possibility of using data mining methods in detecting key turning points in BPO. Based on survey results
obtained in 2013, the selected data mining technique of classification and regression trees (C&RT) was used to detect key turning points in Croatian companies. These findings present invaluable guidelines for any business that strives to achieve more efficient business processes.

Author Biographies

Ljubica Milanović Glavan, University of Zagreb, Faculty of Economics & Business, Department of Informatics

PhD, Department of informatics, assistant

Vesna Bosilj Vukšić, University of Zagreb, Faculty of Economics & Business, Department of Informatics

PhD, Department of Informatics, Full time professor

Nikola Vlahović, University of Zagreb, Faculty of Economics & Business, Department of Informatics

PhD, Department of Informatics, senior assistant

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Published

2015-04-29

Issue

Volume 6 (2015), Number 1

Section

CRORR Journal Regular Issue

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