Determining Factors Influencing Short-Term International Aviation Traffic Demand Using SHAP Analysis: Before COVID-19 and Now
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Song, Ki-Han | - |
dc.contributor.author | Choi, Solsaem | - |
dc.contributor.author | Elkosantini, Sabeur | - |
dc.contributor.author | Suh, Wonho | - |
dc.date.accessioned | 2024-01-22T17:03:45Z | - |
dc.date.available | 2024-01-22T17:03:45Z | - |
dc.date.issued | 2023-10 | - |
dc.identifier.issn | 2071-1050 | - |
dc.identifier.issn | 2071-1050 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/118003 | - |
dc.description.abstract | Due to the COVID-19 outbreak, international aviation travel has declined globally to the level it was 30 years ago. Influencing factors are explored to understand the difference in short-term international aviation travel demand before and after the COVID-19 pandemic. SHapley Additive exPlanations (SHAP), an exploratory data analysis methodology, is applied to identify the factors affecting aviation demand. Daily international aviation passenger volume data (1462 in total) between 2018 and 2021 are analyzed with 10 socioeconomic variables and the number of daily confirmed COVID-19 cases in Korea. It was found that the number of confirmed cases did not have the greatest direct influence on the short-term demand for international demand, but it has a strong correlation with socioeconomic factors. This study's findings on the factors influencing short-term international air passenger demand from a macro perspective will contribute to demand forecasting after COVID-19. It is expected that this research can be applied to other countries or other pandemic data to investigate the post-pandemic demand changes. | - |
dc.format.extent | 12 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | MDPI Open Access Publishing | - |
dc.title | Determining Factors Influencing Short-Term International Aviation Traffic Demand Using SHAP Analysis: Before COVID-19 and Now | - |
dc.type | Article | - |
dc.publisher.location | 스위스 | - |
dc.identifier.doi | 10.3390/su152014924 | - |
dc.identifier.wosid | 001095484900001 | - |
dc.identifier.bibliographicCitation | Sustainability, v.15, no.20, pp 1 - 12 | - |
dc.citation.title | Sustainability | - |
dc.citation.volume | 15 | - |
dc.citation.number | 20 | - |
dc.citation.startPage | 1 | - |
dc.citation.endPage | 12 | - |
dc.type.docType | Article | - |
dc.description.isOpenAccess | Y | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | ssci | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Science & Technology - Other Topics | - |
dc.relation.journalResearchArea | Environmental Sciences & Ecology | - |
dc.relation.journalWebOfScienceCategory | Green & Sustainable Science & Technology | - |
dc.relation.journalWebOfScienceCategory | Environmental Sciences | - |
dc.relation.journalWebOfScienceCategory | Environmental Studies | - |
dc.subject.keywordPlus | AIR-TRAVEL | - |
dc.subject.keywordPlus | MODEL | - |
dc.subject.keywordAuthor | aviation traffic demand | - |
dc.subject.keywordAuthor | influencing factors on demand | - |
dc.subject.keywordAuthor | SHAP analysis | - |
dc.subject.keywordAuthor | Shapley value | - |
dc.subject.keywordAuthor | big data analysis | - |
dc.identifier.url | https://www.mdpi.com/2071-1050/15/20/14924 | - |
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