Identifying latent mode-use propensity segments in an all-AV era
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim Sung Hoo | - |
dc.contributor.author | Circella Giovanni | - |
dc.contributor.author | Mokhtarian Patricia L. | - |
dc.date.accessioned | 2022-10-25T06:43:09Z | - |
dc.date.available | 2022-10-25T06:43:09Z | - |
dc.date.issued | 2019-12 | - |
dc.identifier.issn | 0965-8564 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/111101 | - |
dc.description.abstract | This study offers an early glimpse of how individuals perceive the advantages/disadvantages of AVs, their mode-use intentions, and potential market segments with respect to mode use, should AVs eventually become the only way to travel by car. To do so, we implemented a statewide survey of Georgia residents (N = 2890) and using that data, we applied factor analyses to two blocks of AV-related statements. The first block measured 12 perceptions of AVs, and yielded two psychological constructs: AV pros (advantages/ benefits) and AV overuse cons (negative outcomes specifically associated with the excessive use of AVs). The second block of statements measured respondents' inclinations between AV and non-AV options for 12 hypothetical transportation "needs", and factor analysis identified four mode-use propensity constructs: AV(-inclined) over walk/bike, AV over flight, zero-occupant AV over occupied AV, and AV over transit. The main goal of the paper was to segment the sample on the basis of these four mode-use propensities, to identify clusters with similar propensity profiles or response vectors. We applied latent class cluster analysis to do so, and identified seven potential market segments: some preferring AV options in general, others preferring non-AV options or having unique propensity patterns based on certain contexts (e.g. long distance travel and vehicle occupancy). In the model, socio-demographics, geography, attitudes, and perceptions of AVs help characterize those market segments, and this provides a basis for deeper interpretation and consideration of policy implications. | - |
dc.format.extent | 16 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | Pergamon Press Ltd. | - |
dc.title | Identifying latent mode-use propensity segments in an all-AV era | - |
dc.type | Article | - |
dc.publisher.location | 영국 | - |
dc.identifier.doi | 10.1016/j.tra.2019.09.015 | - |
dc.identifier.scopusid | 2-s2.0-85072622014 | - |
dc.identifier.wosid | 000530907200013 | - |
dc.identifier.bibliographicCitation | Transportation Research Part A: Policy and Practice, v.130, pp 192 - 207 | - |
dc.citation.title | Transportation Research Part A: Policy and Practice | - |
dc.citation.volume | 130 | - |
dc.citation.startPage | 192 | - |
dc.citation.endPage | 207 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | sci | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | ssci | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Business & Economics | - |
dc.relation.journalResearchArea | Transportation | - |
dc.relation.journalWebOfScienceCategory | Economics | - |
dc.relation.journalWebOfScienceCategory | Transportation | - |
dc.relation.journalWebOfScienceCategory | Transportation Science & Technology | - |
dc.subject.keywordPlus | AUTONOMOUS VEHICLES | - |
dc.subject.keywordPlus | AUTOMATED VEHICLES | - |
dc.subject.keywordPlus | CLUSTER-ANALYSIS | - |
dc.subject.keywordPlus | TRAVEL MODE | - |
dc.subject.keywordPlus | PREFERENCES | - |
dc.subject.keywordPlus | ATTITUDES | - |
dc.subject.keywordPlus | TIME | - |
dc.subject.keywordPlus | OWNERSHIP | - |
dc.subject.keywordPlus | PROFILE | - |
dc.subject.keywordAuthor | Autonomous vehicles | - |
dc.subject.keywordAuthor | Behavioral response | - |
dc.subject.keywordAuthor | Factor analysis | - |
dc.subject.keywordAuthor | Latent class cluster analysis | - |
dc.subject.keywordAuthor | Mode-use propensity | - |
dc.subject.keywordAuthor | Perceptions | - |
dc.identifier.url | https://www.sciencedirect.com/science/article/pii/S0965856419303556 | - |
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