Acquiring logistics process intelligence: Methodology and an application for a Chinese bulk port

  • Authors:
  • Ying Wang;Filip Caron;Jan Vanthienen;Lei Huang;Yi Guo

  • Affiliations:
  • School of Economics and Management, Beijing Jiaotong University, 100044 Beijing, China;Department of Decision Sciences and Information Management, Faculty of Economics and Business, KU Leuven, Naamsestraat 69, 3000 Leuven, Belgium;Department of Decision Sciences and Information Management, Faculty of Economics and Business, KU Leuven, Naamsestraat 69, 3000 Leuven, Belgium;School of Economics and Management, Beijing Jiaotong University, 100044 Beijing, China;School of Economics and Management, Beijing Jiaotong University, 100044 Beijing, China

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2014

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Abstract

The processes of logistics service providers are considered as highly human-centric, flexible and complex. Deviations from the standard operating procedures as described in the designed process models, are not uncommon and may result in significant uncertainties. Acquiring insight in the dynamics of the actual logistics processes can effectively assist in mitigating the uncovered risks and creating strategic advantages, which are the result of uncertainties with respectively a negative and a positive impact on the organizational objectives. In this paper a comprehensive methodology for applying process mining in logistics is presented, covering the event log extraction and preprocessing as well as the execution of exploratory, performance and conformance analyses. The applicability of the presented methodology and roadmap is demonstrated with a case study at an important Chinese port that specializes in bulk cargo.