Accounting for multi-dimensional dependencies among decision-makers within a generalized model framework: An application to understanding shared mobility service usage levels

Pragun Vinayak, Felipe F. Dias, Sebastian Astroza, Chandra R. Bhat, Ram Pendyala, Venu M. Garikapati

Research output: Contribution to journalArticle

Abstract

Activity-travel choices of individuals are influenced by spatial dependency effects. As individuals interact and exchange information with, or observe the behaviors of, those in close proximity of themselves, they are likely to shape their behavioral choices accordingly. For this reason, econometric choice models that account for spatial dependency effects have been developed and applied in a number of fields, including transportation. However, spatial dependence models to date have largely defined the strength of association across behavioral units based on spatial or geographic proximity. In the current context of social media platforms and ubiquitous internet and mobile connectivity, the strength of associations among individuals is no longer solely dependent on spatial proximity. Rather, the strength of associations among individuals may be based on shared attitudes and preferences as well. In other words, behavioral choice models may benefit from defining dependency effects based on attitudinal constructs in addition to geographical constructs. In this paper, frequency of usage of car-sharing and ride-hailing services is modeled using a generalized heterogeneous data model (GHDM) framework that incorporates multi-dimensional dependencies among decision-makers. The model system is estimated on the 2014–2015 Puget Sound Regional Travel Study survey sample, with proximity in latent attitudinal constructs defined by a number of personality trait variables. Model estimation results show that social dependency effects arising from similarities in attitudes and preferences are significant in explaining shared mobility service usage. Ignoring such effects may lead to erroneous estimates of the adoption and usage of future transportation technologies and mobility services.

Original languageEnglish (US)
Pages (from-to)129-137
Number of pages9
JournalTransport Policy
Volume72
DOIs
StatePublished - Dec 1 2018

Fingerprint

decision maker
car sharing
travel
Economic and social effects
transportation technology
information exchange
system model
personality traits
social media
econometrics
Data structures
Railroad cars
decision
services
Acoustic waves
connectivity
Internet
automobile
effect

Keywords

  • Attitudinal proximity
  • Latent constructs
  • Shared mobility service usage
  • Social interactions
  • Spatial dependence
  • Values and behavior

ASJC Scopus subject areas

  • Geography, Planning and Development
  • Transportation

Cite this

Accounting for multi-dimensional dependencies among decision-makers within a generalized model framework : An application to understanding shared mobility service usage levels. / Vinayak, Pragun; Dias, Felipe F.; Astroza, Sebastian; Bhat, Chandra R.; Pendyala, Ram; Garikapati, Venu M.

In: Transport Policy, Vol. 72, 01.12.2018, p. 129-137.

Research output: Contribution to journalArticle

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