{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,6]],"date-time":"2026-10-06T03:51:02Z","timestamp":1791258662245,"version":"4.1.0"},"reference-count":52,"publisher":"Wiley","issue":"9","license":[{"start":{"date-parts":[[2026,8,22]],"date-time":"2026-08-22T00:00:00Z","timestamp":1787356800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,8,22]],"date-time":"2026-08-22T00:00:00Z","timestamp":1787356800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Risk Analysis"],"published-print":{"date-parts":[[2026,9]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>Urban agglomerations increasingly confront disaster risks that overwhelm individual cities\u2019 reserve capacities. Collaborative emergency reserves offer a potential remedy but also introduce coordination burdens and distributional concerns. To address this, this study formulates a multi\u2010objective optimization problem that integrates economic utility with perceived fairness. The model explicitly accounts for residents\u2019 shortage and delay experiences alongside managers\u2019 perceptions of coordination costs, reserve burdens, and cross\u2010city disparities. It is solved using an enhanced multi\u2010objective particle swarm optimization algorithm coupled with the \u03b5\u2010constraint method and driven by Monte Carlo disaster scenario generation. A numerical illustration based on 21 mainland prefecture\u2010level cities in Guangdong Province evaluates the framework under heterogeneous risk, budget, and coordination conditions. Sobol's global sensitivity analysis identifies regional budget, inter\u2010city collaboration experience, disaster intensity, and nonlinear perceived\u2010loss parameters as dominant drivers of collaborative advantage, whereas transportation costs and standalone city resilience exert weaker effects. The results demonstrate that collaboration generally outperforms independent reserves, especially under severe disasters and fiscal constraints. This advantage diminishes when disasters are widespread or when transaction and coordination costs are prohibitive. Distributional stress tests further reveal that resource\u2010abundant hub cities may perceive lower fairness when acting primarily as providers yet stand to gain substantially when severe shocks occur locally. This research provides a decision\u2010making framework for jointly evaluating efficiency and perceived fairness. It highlights mutual\u2010aid agreements, fiscal compensation, contribution\u2010credit mechanisms, and joint exercises as institutional complements to optimized reserve strategies.<\/jats:p>","DOI":"10.1111\/risa.70321","type":"journal-article","created":{"date-parts":[[2026,8,22]],"date-time":"2026-08-22T08:54:51Z","timestamp":1787388891000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Bridging Economic Efficiency and Perceived Fairness: A New Framework for Collaborative Disaster Material Reserves"],"prefix":"10.1111","volume":"46","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-8116-6129","authenticated-orcid":false,"given":"Fei","family":"Wang","sequence":"first","affiliation":[{"name":"International School of Business &amp; Finance Sun Yat\u2010sen University  Zhuhai Guangdong China"},{"name":"Guangdong Provincial Key Laboratory of Fire Science and Intelligent Emergency Technology  Guangzhou Guangdong 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