Effects of urban environmental attributes on graduate job preferences in Northeastern China: an application of conjoint analysis and big data methods
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 g...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IOP Publishing
2021-01-01
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| Series: | Environmental Research Letters |
| Subjects: | |
| Online Access: | https://doi.org/10.1088/1748-9326/ac2e87 |
| _version_ | 1827869974662742016 |
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| author | Jiahao Zhang Hiroatsu Fukuda Xindong Wei Li Zhang Jinming Jiang |
| author_facet | Jiahao Zhang Hiroatsu Fukuda Xindong Wei Li Zhang Jinming Jiang |
| author_sort | Jiahao Zhang |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-12T15:51:16Z |
| format | Article |
| id | doaj.art-c9f19122ac3448a497d6ddf92b52d23e |
| institution | Directory Open Access Journal |
| issn | 1748-9326 |
| language | English |
| last_indexed | 2024-03-12T15:51:16Z |
| publishDate | 2021-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | Environmental Research Letters |
| spelling | doaj.art-c9f19122ac3448a497d6ddf92b52d23e2023-08-09T15:09:11ZengIOP PublishingEnvironmental Research Letters1748-93262021-01-01161111500810.1088/1748-9326/ac2e87Effects of urban environmental attributes on graduate job preferences in Northeastern China: an application of conjoint analysis and big data methodsJiahao Zhang0https://orcid.org/0000-0002-3331-3092Hiroatsu Fukuda1Xindong Wei2Li Zhang3Jinming Jiang4Faculty of Environmental Engineering, The University of Kitakyushu , Kitakyushu, JapanFaculty of Environmental Engineering, The University of Kitakyushu , Kitakyushu, JapanSchool of Environmental and Municipal Engineering, Jilin Jianzhu University , Changchun, People’s Republic of ChinaSchool of Architecture and Urban Planning, Shenzhen University , Shenzhen, People’s Republic of ChinaInnovation Institute for Sustainable Maritime Architecture Research and Technology, Qingdao University of Technology , Qingdao, People’s Republic of ChinaA 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.https://doi.org/10.1088/1748-9326/ac2e87sustainable developmentbig datajob preferencesconjoint analysis |
| spellingShingle | Jiahao Zhang Hiroatsu Fukuda Xindong Wei Li Zhang Jinming Jiang Effects of urban environmental attributes on graduate job preferences in Northeastern China: an application of conjoint analysis and big data methods Environmental Research Letters sustainable development big data job preferences conjoint analysis |
| title | Effects of urban environmental attributes on graduate job preferences in Northeastern China: an application of conjoint analysis and big data methods |
| title_full | Effects of urban environmental attributes on graduate job preferences in Northeastern China: an application of conjoint analysis and big data methods |
| title_fullStr | Effects of urban environmental attributes on graduate job preferences in Northeastern China: an application of conjoint analysis and big data methods |
| title_full_unstemmed | Effects of urban environmental attributes on graduate job preferences in Northeastern China: an application of conjoint analysis and big data methods |
| title_short | Effects of urban environmental attributes on graduate job preferences in Northeastern China: an application of conjoint analysis and big data methods |
| title_sort | effects of urban environmental attributes on graduate job preferences in northeastern china an application of conjoint analysis and big data methods |
| topic | sustainable development big data job preferences conjoint analysis |
| url | https://doi.org/10.1088/1748-9326/ac2e87 |
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