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Process Science in Action: A Literature Review on Process Mining in Business Management

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  • Zerbino, Pierluigi
  • Stefanini, Alessandro
  • Aloini, Davide

Abstract

Process Mining is a new kind of Business Analytics and has emerged as a powerful family of Process Science techniques for analysing and improving business processes. Although Process Mining has managerial benefits, such as better decision making, the scientific literature has investigated it mainly from a computer science standpoint and appears to have overlooked various possible applications. We reviewed management-orientated literature on Process Mining and Business Management to assess the state of the art and to pave the way for further research. We built a seven-dimension framework to develop and guide the review. We selected and analysed 145 papers and identified eleven research gaps sorted into four categories. Our findings were formalised in a structured research agenda suggesting twenty-five research questions. We believe that these questions may stimulate the application of Process Mining in promising, albeit little explored, business contexts and in mostly unaddressed managerial areas.

Suggested Citation

  • Zerbino, Pierluigi & Stefanini, Alessandro & Aloini, Davide, 2021. "Process Science in Action: A Literature Review on Process Mining in Business Management," Technological Forecasting and Social Change, Elsevier, vol. 172(C).
  • Handle: RePEc:eee:tefoso:v:172:y:2021:i:c:s0040162521004534
    DOI: 10.1016/j.techfore.2021.121021
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    1. Potoniec, Jedrzej & Sroka, Daniel & Pawlak, Tomasz P., 2022. "Continuous discovery of Causal nets for non-stationary business processes using the Online Miner," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1304-1320.
    2. Jonghyeon Ko & Marco Comuzzi, 2023. "A Systematic Review of Anomaly Detection for Business Process Event Logs," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 65(4), pages 441-462, August.
    3. Maria-Isabel Sanchez-Segura & Roxana González-Cruz & Fuensanta Medina-Dominguez & German-Lenin Dugarte-Peña, 2022. "Valuable Business Knowledge Asset Discovery by Processing Unstructured Data," Sustainability, MDPI, vol. 14(20), pages 1-24, October.

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