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Auflistung nach Autor:in "Martin, Niels"

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  • Zeitschriftenartikel
    Batching vs. Non-batching in Business Processes.
    (EMISA Forum: Vol. 38, No. 1, 2018) Pufahl, Luise; Martin, Niels
  • Zeitschriftenartikel
    Opportunities and Challenges for Process Mining in Organizations: Results of a Delphi Study
    (Business & Information Systems Engineering: Vol. 63, No. 5, 2021) Martin, Niels; Fischer, Dominik A.; Kerpedzhiev, Georgi D.; Goel, Kanika; Leemans, Sander J. J.; Röglinger, Maximilian; van der Aalst, Wil M. P.; Dumas, Marlon; La Rosa, Marcello; Wynn, Moe T.
    Process mining is an active research domain and has been applied to understand and improve business processes. While significant research has been conducted on the development and improvement of algorithms, evidence on the application of process mining in organizations has been far more limited. In particular, there is limited understanding of the opportunities and challenges of using process mining in organizations. Such an understanding has the potential to guide research by highlighting barriers for process mining adoption and, thus, can contribute to successful process mining initiatives in practice. In this respect, the paper provides a holistic view of opportunities and challenges for process mining in organizations identified in a Delphi study with 40 international experts from academia and industry. Besides proposing a set of 30 opportunities and 32 challenges, the paper conveys insights into the comparative relevance of individual items, as well as differences in the perceived relevance between academics and practitioners. Therefore, the study contributes to the future development of process mining, both as a research field and regarding its application in organizations.
  • Zeitschriftenartikel
    The Use of Process Mining in Business Process Simulation Model Construction
    (Business & Information Systems Engineering: Vol. 58, No. 1, 2016) Martin, Niels; Depaire, Benoît; Caris, An
    The paper focuses on the use of process mining (PM) to support the construction of business process simulation (BPS) models. Given the useful BPS insights that are available in event logs, further research on this topic is required. To provide a solid basis for future work, this paper presents a structured overview of BPS modeling tasks and how PM can support them. As directly related research efforts are scarce, a multitude of research challenges are identified. In an effort to provide suggestions on how these challenges can be tackled, an analysis of PM literature shows that few PM algorithms are directly applicable in a BPS context. Consequently, the results presented in this paper can encourage and guide future research to fundamentally bridge the gap between PM and BPS.