Identifying latent mode-use propensity segments in an all-AV era

Sung Hoo Kim, Giovanni Circella and Patricia Mokhtarian

Transportation Research Part A: Policy and Practice, 2019, vol. 130, issue C, 192-207

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.

Keywords: Autonomous vehicles; Perceptions; Behavioral response; Mode-use propensity; Factor analysis; Latent class cluster analysis (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (9)

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DOI: 10.1016/j.tra.2019.09.015

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