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DES also allows testing of resource configurations to assess their impact on performance. To evaluate their efficiency, data envelopment analysis (DEA) can be used. However, current DES software does not automate DEA for efficiency evaluation, requiring separate analysis of performance measures and resource efficiency. This complicates finding the most efficient resource configuration, especially in healthcare systems. To address this, this paper proposes a framework combining DES and DEA for simpler analysis of their inputs and outputs. The framework automates data transfer mechanisms between DES outputs and DEA inputs and implements an integrated computational approach to DEA. To validate the framework, a case study in an emergency department was conducted, where complex interconnected processes are common, and optimizing resource allocation is critical for patient care and system performance. The case study analyzed 35 resource configurations to identify the most efficient one. The results demonstrated the framework\u2019s potential to simplify resource analysis, identify optimal configurations, and enhance decision-making, thereby improving the system\u2019s operational efficiency. The framework provides a robust, portable, and scalable solution applicable across diverse industries for effectively optimizing system performance and resource allocation.<\/jats:p>","DOI":"10.1177\/00375497251337090","type":"journal-article","created":{"date-parts":[[2025,5,5]],"date-time":"2025-05-05T06:42:22Z","timestamp":1746427342000},"page":"1003-1026","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["A framework integrating discrete event simulation and data envelopment analysis to evaluate resource configuration performance in discrete systems"],"prefix":"10.1177","volume":"101","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4283-0737","authenticated-orcid":false,"given":"Ruzelan","family":"Khalid","sequence":"first","affiliation":[{"name":"Institute of Strategic Industrial Decision Modelling, School of Quantitative Sciences, Universiti Utara Malaysia, Malaysia"}]},{"given":"Mohd Kamal","family":"Mohd Nawawi","sequence":"additional","affiliation":[{"name":"Institute of Strategic Industrial Decision Modelling, School of Quantitative Sciences, Universiti Utara Malaysia, Malaysia"}]},{"given":"Razamin","family":"Ramli","sequence":"additional","affiliation":[{"name":"Institute of Strategic Industrial Decision Modelling, School of Quantitative Sciences, Universiti Utara Malaysia, Malaysia"}]},{"given":"Nurhanis","family":"Ishak","sequence":"additional","affiliation":[{"name":"Faculty of Management and Information Technology, Universiti Sultan Azlan Shah, Malaysia"}]},{"given":"Nur Fatihah","family":"Sakari","sequence":"additional","affiliation":[{"name":"Intel Corporation, Malaysia"}]}],"member":"179","published-online":{"date-parts":[[2025,5,5]]},"reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jclepro.2023.138023"},{"key":"e_1_3_3_3_2","volume-title":"A practical guide to service management: insights from industry experts for uncovering, implementing, and improving service management practices","author":"Sutherland KD","year":"2023","unstructured":"Sutherland KD, Sheets LJ, Schwartz L. 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