DETERMINANTS OF DEMAND FOR CITIES WITH HIGHER EDUCATION INSTITUTIONS: AN APPROACH BASED ON FRACTIONAL REGRESSION

dc.contributor.authorDionísio, Andreia
dc.contributor.authorRolim, Cassio
dc.contributor.authorRego, Conceição
dc.contributor.editorA. Ruxho, Filip(os)
dc.date.accessioned2025-07-24T23:01:07Z
dc.date.available2025-07-24T23:01:07Z
dc.date.issued2025
dc.description.abstractHigher education institutions are typically situated in urban areas, making them appealing destinations for students seeking advanced education. This paper aims to explore the factors influencing the demand for cities with these institutions, focusing on the Portuguese context. By analysing distance and the quality of life in municipalities, we can better understand what attracts students to these university cities. Our findings, based on a fractional regression model, reveal that proximity to home and the disparity in rental and accommodation expenses play a significant role in the appeal of these cities for students and their families.por
dc.identifier.authoremailandreia@uevora.pt
dc.identifier.authoremailcassio.rolim@gmail.com
dc.identifier.authoremailmcpr@uevora.pt
dc.identifier.citationDionisio A., Rolim C., Rego C., 2025. “Determinants of demand for cities with higher education institutions: An approach based on fractional regression”, Sustainable Regional Development Scientific Journal, Vol. II, (1), 2025, pp. 81- 93por
dc.identifier.issn3006-3884
dc.identifier.pagina81-93
dc.identifier.principalpublicationtitleSustainable Regional Development Scientific Journal
dc.identifier.scientificarea642por
dc.identifier.urihttps://www.srdsjournal.eu/articles/files/2025-1-7.pdf
dc.identifier.urihttp://hdl.handle.net/10174/39062
dc.identifier.volumeII (1)
dc.language.isoengpor
dc.peerreviewedyespor
dc.rightsopenAccesspor
dc.subjecthigher education institutionspor
dc.subjectfractional modelspor
dc.subjectmarket areaspor
dc.subjectdistancepor
dc.subjecthousing costspor
dc.titleDETERMINANTS OF DEMAND FOR CITIES WITH HIGHER EDUCATION INSTITUTIONS: AN APPROACH BASED ON FRACTIONAL REGRESSIONpor
dc.typearticlepor

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