Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/46265
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dc.contributor.authorDEPAIRE, Benoit-
dc.contributor.authorLeopold, H-
dc.contributor.authorMendling, J-
dc.contributor.authorMeyerhenke, H-
dc.date.accessioned2025-06-23T07:56:23Z-
dc.date.available2025-06-23T07:56:23Z-
dc.date.issued2024-
dc.date.submitted2025-06-23T07:44:07Z-
dc.identifier.citationMarrella, A.; Resinas, M.; Jans, M.; Rosemann, M. (Ed.). Business process management, BPM 2024, SPRINGER-VERLAG BERLIN, p. 531 -537-
dc.identifier.issn0302-9743-
dc.identifier.urihttp://hdl.handle.net/1942/46265-
dc.description.abstractAlgorithms play an important role for business process management. Indeed, all of the 27 papers accepted for BPM 2023 refer to algorithms in one way or the other. Some of these research papers propose new algorithms, such as the paper on the Agent Miner [8], they compose analytical pipelines, such as the paper on process mining video data [5], or they discuss the evaluation of algorithms, such as the paper on sustainability dimensions [3]. So far, however, the BPM community has not developed explicit guidelines for evaluating algorithmic contributions. This tutorial describes an overarching methodological framework of how algorithms can be researched. In turn, we discuss its foundations in three dimensions. First, we describe four ontological entities including real-world problem, algorithmic task, algorithm design, and algorithm implementations. Second, we distinguish knowledge contributions along two dimensions, that is a) knowledge relating to tasks and to designs and b) knowledge of and knowledge about. Third, we discuss how methodologically new or better knowledge is established. The objective of this tutorial is to present specific strategies how algorithms can be systematically researched for early career researchers. These are illustrated by good examples of BPM papers.-
dc.description.sponsorshipThe research of the author was supported by Einstei, Foundation Berlin under grant EPP-2019-524, by the German Federal Ministry of Education and Research under grant 16DII133, and by Deutsche Forschungsgemeinschaft under grant ME 3711/2-1-
dc.language.isoen-
dc.publisherSPRINGER-VERLAG BERLIN-
dc.relation.ispartofseriesLecture Notes in Computer Science-
dc.rightsThe Author (s), under exclusive license to Spring Nature Switzerland AG 2024-
dc.subject.otherAlgorithm engineering-
dc.subject.otherEvaluation of algorithms-
dc.subject.otherDesign and Analysis of Algorithms-
dc.subject.otherProcess Mining-
dc.titleEvaluation of Algorithmic Contributions to Business Process Management-
dc.typeProceedings Paper-
local.bibliographicCitation.authorsMarrella, A.-
local.bibliographicCitation.authorsResinas, M.-
local.bibliographicCitation.authorsJans, M.-
local.bibliographicCitation.authorsRosemann, M.-
local.bibliographicCitation.conferencedate2024, September 01-06-
local.bibliographicCitation.conferencename22nd International Conference on Business Process Management (BPM)-
local.bibliographicCitation.conferenceplaceAGH Univ Krakow, Krakow, POLAND-
dc.identifier.epage537-
dc.identifier.spage531-
dc.identifier.volume14940-
local.bibliographicCitation.jcatC1-
local.publisher.placeHEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY-
local.type.refereedRefereed-
local.type.specifiedProceedings Paper-
dc.identifier.isi001332313700030-
local.provider.typeWeb of Science-
local.bibliographicCitation.btitleBusiness process management, BPM 2024-
local.uhasselt.internationalyes-
item.contributorDEPAIRE, Benoit-
item.contributorLeopold, H-
item.contributorMendling, J-
item.contributorMeyerhenke, H-
item.fulltextWith Fulltext-
item.accessRightsRestricted Access-
item.fullcitationDEPAIRE, Benoit; Leopold, H; Mendling, J & Meyerhenke, H (2024) Evaluation of Algorithmic Contributions to Business Process Management. In: Marrella, A.; Resinas, M.; Jans, M.; Rosemann, M. (Ed.). Business process management, BPM 2024, SPRINGER-VERLAG BERLIN, p. 531 -537.-
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