<?xml version="1.0" encoding="UTF-8"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-10-23T13:47:01Z</responseDate><request verb="GetRecord" identifier="oai:gumushane-rdlopen.rawdatalibrary.net:gumushane/14220" metadataPrefix="oai_dc">https://gumushane-rdlopen.rawdatalibrary.net/oai/request</request><GetRecord><record><header><identifier>oai:gumushane-rdlopen.rawdatalibrary.net:gumushane/14220</identifier><datestamp>2026-10-22T11:36:54Z</datestamp><setSpec>openaire</setSpec><setSpec>com_gumushane_10000</setSpec><setSpec>col_gumushane_10001</setSpec><setSpec>com_gumushane_10007</setSpec><setSpec>col_gumushane_10180</setSpec><setSpec>com_gumushane_10008</setSpec><setSpec>col_gumushane_10188</setSpec></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:title>A regulated many-to-one two-sided matching model for emergency teams: a university case study</dc:title><dc:creator>Şimşek, Ahmet Bahadır</dc:creator><dc:creator>Göktekin, Zekiye</dc:creator><dc:creator>Şimşek, Tuğçe</dc:creator><dc:creator>Tunçer, Dilara</dc:creator><dc:subject>disaster management</dc:subject><dc:subject>emergency preparedness</dc:subject><dc:subject>Employee-team matching</dc:subject><dc:subject>multi-objective decision making</dc:subject><dc:subject>workplace health and safety</dc:subject><dc:description>In workplaces, emergency teams comprised of employees play a critical role in minimising damage during emergencies through rapid response. This study introduces a multi-objective employee-team matching model that optimally assigns employees to emergency teams, balancing stakeholder preferences and physical requirements. Using a regulated many-to-one matching framework, this model accounts for employee preferences, decision-maker evaluations, and team-specific physical standards, addressing limitations in current manual matching practices. Tested through a real case study in a university setting, the model demonstrates its efficacy by achieving stable, satisfactory matches that outperform traditional methods. Sensitivity analysis across multiple scenarios further illustrates the model’s adaptability, providing decision-makers with a systematic tool for improving team stability, performance, and flexibility in various emergency preparedness contexts. The main contribution of this study is the reconciliation of preference-based assignments with performance requirements through a tuneable objective function. By jointly considering soft (preferences) and hard (physical) constraints in a single framework, the model allows decision-makers to balance satisfaction and operational feasibility–an integration that existing approaches typically overlook. This approach presents a robust, data-driven solution to enhance organisational resilience and efficiency in critical situations.</dc:description><dc:publisher>Taylor and Francis Ltd.</dc:publisher><dc:date>2026</dc:date><dc:type>Article</dc:type><dc:identifier>https://rdlopen.rawdatalibrary.net/r/gumushane/14220</dc:identifier><dc:identifier>https://doi.org/10.1080/01605682.2025.2577774</dc:identifier><dc:identifier>0160-5682</dc:identifier><dc:language>en</dc:language><dc:relation>Journal of the Operational Research Society</dc:relation><dc:rights>info:eu-repo/semantics/closedAccess</dc:rights><dc:type>info:eu-repo/semantics/article</dc:type><dc:identifier>https://gumushane-rdlopen.rawdatalibrary.net/tr/items/gumushane/14220</dc:identifier></oai_dc:dc></metadata></record></GetRecord></OAI-PMH>