Identifying latent mode-use propensity segments in an all-AV era. (December 2019)

• Record Type: Journal Article
• Authors: Kim, Sung Hoo; Circella, Giovanni; Mokhtarian, Patricia L.
• Is Part Of: Transportation research. Volume 130(2019)
• Page Start: 192
• Page End: 207
• Publication Date: 2019-12
• Subjects: Autonomous vehicles -- Perceptions -- Behavioral response -- Mode-use propensity -- Factor analysis -- Latent class cluster analysis; Transportation -- Research -- Periodicals; 388.011
• DOI: 10.1016/j.tra.2019.09.015
• Languages: English
• ISSNs: 0965-8564

Abstract

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.