Effects of urban environmental attributes on graduate job preferences in Northeastern China

An application of conjoint analysis and big data methods

Datos Bibliográficos

ID15545337
AutoresJiahao Zhang (0000-0002-6291-1729, The University of Kitakyushu, autor de correspondencia), Hiroatsu Fukuda (0000-0003-4223-035X, The University of Kitakyushu), Xindong Wei (0000-0002-3171-6170, Jilin Jianzhu University), Li Zhang (0000-0002-4441-5131, Shenzhen University, autor de correspondencia), Jinming Jiang (0000-0001-8204-977X, Qingdao University of Technology)
Año2021
Volumen16
Número11
Páginas115008-115008
Fecha de publicación2021-10-11
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaEnvironmental Research Letters (JOURNAL)
Identificadores de la revistaISSN: 1748-9326 • E-ISSN: 1748-9326
EditorialIOP Publishing (PUBLISHER • GB)
DOI10.1088/1748-9326/ac2e87
OpenAlexW3206180101
IdiomaEN
Citas recibidas3
Referencias citadas52

A constant supply of novel ideas and contributions from all economic sectors is required to further the sustainable development of cities. Therefore, there is a growing need for well-educated graduates to enter metropolitan job markets. As urban environments and culture have been shown to affect a graduates’ eventual carrier choice and trajectory, governments often seek to change their local environments to attract graduates who can help efficiently allocate and utilize a city’s often-limited environmental budgets. In this study, the conjoint analysis (CA) method was employed to explore the effects of four environmental attributes (water pollution, air pollution, littering, and green area) on graduate employment preferences in northeast China. Water pollution was shown to have the greatest effect on graduate preferences (43.6%), followed by air pollution (34.1%), littering (20.7%), and green area (1.6%). According to this ranking of importance, cities could improve their environmental attributes to maximize the attraction of Northeast graduates. Moreover, this study applied the Baidu index (a big data sharing platform) to improve the attribute selection process of the CA method. The improvement reduced the cost of the CA method and enhanced its objectivity

Business · China · Conjoint analysis · Downtown · Economics · Environmental economics · Environmental resource management · Geography · Metropolitan area · Preference · Ranking (information retrieval · Computer Science · Diverse Aspects of Tourism Research · Economic and Environmental Valuation · Environmental Science · Urban Transport and Accessibility