{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T08:41:32Z","timestamp":1764578492038,"version":"3.46.0"},"reference-count":72,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2025,11,28]],"date-time":"2025-11-28T00:00:00Z","timestamp":1764288000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"CONSTRUCT\u2014Instituto de I&D em Estruturas e Constru\u00e7\u00f5es","award":["UID\/04708\/2025"],"award-info":[{"award-number":["UID\/04708\/2025"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sustainability"],"abstract":"<jats:p>This paper investigates the integration of proximity theory (PT) into the management of public transport service disruptions within sustainable Mobility-as-a-Service (MaaS) systems, an area that is largely underexplored. PT provides a multidimensional framework for analyzing relationships and interactions within complex systems, encompassing five dimensions: geographical, cognitive, institutional, organizational, and social, each influencing coordination, learning, and adaptability. Building on this framework, the study introduces temporal proximity as an original sub-dimension of geographical proximity, forming a spatial\u2013temporal proximity theory (PTST), which highlights the critical role of timing, synchronization, and coordinated responses in transport disruption management. To operationalize these principles, a mixed-integer programming (MIP) model was developed to optimize traveler assignments across 50 routes for 10 travelers, minimizing delays, transfers, walking distance, crowding, and CO2 emissions. Two scenarios were analyzed: one without environmental considerations and another with CO2 penalties. Results show that emissions were reduced by up to 50% for certain routes, while maintaining feasible travel times and route choices. The case study demonstrates that PTST can be operationalized as a practical tool, bridging mobility resilience and environmental responsibility, and providing actionable insights for sustainable and intelligent MaaS platforms.<\/jats:p>","DOI":"10.3390\/su172310686","type":"journal-article","created":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T08:13:49Z","timestamp":1764576829000},"page":"10686","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Sustainable Mobility-as-a-Service: Integrating Spatial\u2013Temporal Proximity and Environmental Performance in Transport Disruption Management"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2470-9834","authenticated-orcid":false,"given":"Cec\u00edlia","family":"Vale","sequence":"first","affiliation":[{"name":"Faculty of Engineering of University of Porto, R. Dr. Roberto Frias, 4200-465 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6638-6060","authenticated-orcid":false,"given":"Leonor","family":"Vale","sequence":"additional","affiliation":[{"name":"Faculty of Economics and Management of University of Porto, R. Dr. Roberto Frias, 4200-465 Porto, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2025,11,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"144652","DOI":"10.1016\/j.jclepro.2025.144652","article-title":"Urban sprawl, public transportation efficiency and carbon emissions","volume":"489","author":"Lyu","year":"2025","journal-title":"J. Clean. Prod."},{"key":"ref_2","unstructured":"Rupprecht Consult (2019). Guidelines for Developing and Implementing a Sustainable Urban Mobility Plan."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Vale, C., and Vale, L. (2025). 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