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Traditional role-based resource allocation leads to effective process executions, since each task is performed by a resource that has the required skills and competencies to do so. However, the resulting allocations are typically not as efficient as they could be, since optimization techniques have yet to find their way in traditional business process management scenarios. On the other hand, operations research provides a rich set of analytical methods for supporting problem-specific decisions on resource allocation. This paper provides a novel framework for creating transparency on existing tasks and resources, supporting individualized allocations for each activity in a process, and the possibility to integrate problem-specific analytical methods of the operations research domain. To validate the framework, the paper reports on the design and prototypical implementation of a software architecture, which extends a traditional process engine with a dedicated resource management component. This component allows us to define specific resource allocation problems at design time, and it also facilitates optimized resource allocation at run time. The framework is evaluated using a real-world parcel delivery process. The evaluation shows that the quality of the allocation results increase significantly with a technique from operations research in contrast to the traditional applied rule-based approach.\n<\/jats:p>","DOI":"10.1007\/s00607-022-01093-2","type":"journal-article","created":{"date-parts":[[2022,6,17]],"date-time":"2022-06-17T18:02:41Z","timestamp":1655488961000},"page":"2405-2429","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["A framework for modeling and executing task-Specific resource allocations in business processes"],"prefix":"10.1007","volume":"104","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7318-6390","authenticated-orcid":false,"given":"Sven","family":"Ihde","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Luise","family":"Pufahl","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Maximilian","family":"V\u00f6lker","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Asvin","family":"Goel","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mathias","family":"Weske","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,6,17]]},"reference":[{"issue":"3","key":"1093_CR1","doi-asserted-by":"publisher","first-page":"364","DOI":"10.1504\/EJIE.2018.092009","volume":"12","author":"M Arias","year":"2018","unstructured":"Arias M, Munoz-Gama J, Sep\u00falveda M, Miranda JC (2018) Human resource allocation or recommendation based on multi-factor criteria in on-demand and batch scenarios. 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