Incorporating Inertia in Mode Choice and Influential Factors of Car Stickiness: Implications for Shifts to Public Transit

  • Kun Gao College of Transportation Engineering, Key Laboratory of Road and Traffic Engineering of the Ministry of Education Tongji University Shanghai, P. R. China
  • Lijun Sun College of Transportation Engineering, Key Laboratory of Road and Traffic Engineering of the Ministry of Education Tongji University Shanghai, P. R. China
Keywords: mode choice, mode-specific inertia, influential factors, car stickiness, elasticity analysis

Abstract

To explore efficient strategies of adjusting travel mode structure and support scientific implements of public transit system, this paper investigated travelers’ mode choice behavior in a multimodal network incorporating inertia in utility specifications. Comprehensive stated preference surveys considering four modes and four key decisive variables were designed, and face-to-face investigations were conducted to collect reliable data in Shanghai. The discrete choice technique considering mode-specific inertias was employed for modeling. The influencing factors of car stickiness were particularly explored. The results show that there are significant and mode-specific inertias in travelers’ choices of travel mode. The inertia of car users shifting to other modes is considerably large compared to inertias of public transit users. Travel time reliability and crowdedness in public transit are identified to be crucial factors influencing car users’ willingness to use public transit. Demographic attributes (age, income, education level and gender), spatial context features (commuting duration) and the regime of flexible work time are found to be significant influential variables of car stickiness. Moreover, direct and cross elasticity analyses were executed to show practical implications of shifting car users to public transit. The results provide serviceable support for transport planning and strategy making.

Author Biographiesaaa replica rolex repwatches replica rolex watches for men replica iwc watch

Kun Gao, College of Transportation Engineering, Key Laboratory of Road and Traffic Engineering of the Ministry of Education Tongji University Shanghai, P. R. China

College of Transportation Engineering, Key Laboratory of Road and Traffic Engineering of the Ministry of Education Tongji University Shanghai, P. R. China

Ph.D. Candidate

Lijun Sun, College of Transportation Engineering, Key Laboratory of Road and Traffic Engineering of the Ministry of Education Tongji University Shanghai, P. R. China

College of Transportation Engineering, Key Laboratory of Road and Traffic Engineering of the Ministry of Education Tongji University Shanghai, P. R. China

Full Professor

References

SURCTDRI, Multimodal Transportation Operations Annual Report(Year of 2015). 2016, Shanghai Urban and Rural Construction and Transportation Development Research Institute: Shanghai.

Florida UOS,Tampa, MEASURING DAY-TO-DAY VARIABILITY IN TRAVEL BEHAVIOR USING GPS DATA. 2000.

Verplanken B, Aarts H, Knippenberg AV, Habit, information acquisition, and the process of making travel mode choices. European Journal of Social Psychology, 1997. 27(5): p. 539–560.

Gärling T,Axhausen KW, Introduction: Habitual travel choice. Transportation, 2003. 30(1): p. 1-11.

Cantillo V, Juan DDO, Williams HCWL, Modeling Discrete Choices in the Presence of Inertia and Serial Correlation. Transportation Science, 2007. 41(2): p. 195-205.

Yáñez MF, Cherchi E, Ortúzar DD, Heydecker BG. Inertia and shock effects on mode choice panel data: implications of the Transantiago implementation. 2009.

Daganzo CF,Sheffi Y, “Multinomial Probit with Time Series Data: Unifying State Dependence and Serial-Correlation Models.”. Environment and Planning A, 1982. 14(10): p. 1377-1388.

Johnson L,Hensher D, Application of multinomial probit to a two-period panel data set. Transportation Research Part A General, 1982. 16(5-6): p. 457-464.

Ben-Akiva M,Morikawa T, Estimation of switching models from revealed preferences and stated intentions. Transportation Research Part A General, 1990. 24(6): p. 485-495.

Bradley MA,Daly AJ. Estimation Of Logit Choice Models Using Mixed Stated Preference And Revealed Preference Information. in Les Methodes D'analyse Des Comportements De Deplacements Pour Les Annees 1990 - 6e Conference Internationale Sur Les Comportements De Deplacements, Chateau Bonne Entente, Quebec, 22, 23, 24 Mai. 1991.

Morikawa T, Correcting state dependence and serial correlation in the RP/SP combined estimation method. Transportation, 1994. 21(2): p. 153-165.

YáÑEz MF, Zar S, Dios JD, Modelling choice in a changing environment : assessing the shock effects of a new transport system. 2010.

Cherchi E,Manca F, Accounting for inertia in modal choices: some new evidence using a RP/SP dataset. Transportation, 2011. 38(4): p. 679-695.

Cherchi E,Cirillo C, Understanding variability, habit and the effect of long period activity plan in modal choices: a day to day, week to week analysis on panel data. Transportation, 2014. 41(6): p. 1245-1262.

Ramadurai G,Inivasan KK, Dynamics and Variability in Within-Day Mode Choice Decisions: Role of State Dependence, Habit Persistence, and Unobserved Heterogeneity. Transportation Research Record Journal of the Transportation Research Board, 2006. 1977(-1): p. 43-52.

González RM, Marrero ÁS, Cherchi E, Testing for inertia effect when a new tram is implemented. Transportation Research Part A: Policy and Practice, 2017: p. 150–159.

Chorus C,Dellaert BGC, Travel Choice Inertia: The Joint Role of Risk Aversion and Learning. Journal of Transport Economics & Policy, 2010. volume 46(1): p. 139-155(17).

Chorus CG, Risk aversion, regret aversion and travel choice inertia: an experimental study. 2014. 37(4): p. 321-332.

González RM,Marrero GA, Induced road traffic in Spanish regions: A dynamic panel data model. Transportation Research Part A Policy & Practice, 2012. 46(3): p. 435–445.

Nordfjærn T, Lind HB, Şimşekoğlu Ö, Jørgensen SH, Lund IO, Rundmo T, Habitual, safety and security factors related to mode use on two types of travels among urban Norwegians. Safety Science, 2015. 76: p. 151-159.

Zhou J, Sustainable commute in a car-dominant city: Factors affecting alternative mode choices among university students. Transportation Research Part A Policy & Practice, 2012. 46(7): p. 1013–1029.

Bamberg S, Hunecke M, Blöbaum A, Social context, personal norms and the use of public transportation: Two field studies. Journal of Environmental Psychology, 2007. 27(3): p. 190-203.

Steg L, Car use: lust and must. Instrumental, symbolic and affective motives for car use. Transportation Research Part A Policy & Practice, 2005. 39(2-3): p. 147-162.

Schwartz SH,Howard JA, A normative decision making model of altruism. 1981.

Nordlund AM,Garvill J, Effects of values, problem awareness, and personal norm on willingness to reduce personal car use. Journal of Environmental Psychology, 2003. 23(4): p. 339-347.

De Groot JIM,Steg L, Relationships between value orientations, self-determined motivational types and pro-environmental behavioural intentions. Journal of Environmental Psychology, 2010. 30(4): p. 368-378.

Ajzen I, The theory of planned behavior. Research in Nursing & Health, 1991. 14(2): p. 137-144.

Jong GCD,Bliemer MCJ, On including travel time reliability of road traffic in appraisal. Transportation Research Part A Policy & Practice, 2015. 73: p. 80-95.

Guessous Y, Aron M, Bhouri N, Cohen S, Estimating Travel Time Distribution under different Traffic conditions. Transportation Research Procedia, 2014. 3: p. 339-348.

Tirachini A, Sun L, Erath A, Chakirov A, Hayashi Y, Valuation of sitting and standing in metro trains using revealed preferences. Transport Policy, 2016. 47: p. 94-104.

Shao M, Li T, SUN L, Survey Method and Model of Passengers' Cost Perception of Crowding Level in Bus. Journal of Tongji University(Nature Science), 2012(07): p. 1031-1034.

Metrics C, Ngene 1.1. 1 User Manual & Reference Guide. Sydney, Australia: ChoiceMetrics, 2012.

Hensher DA, Greene WH, Ho CQ, Random Regret Minimization and Random Utility Maximization in the Presence of Preference Heterogeneity: An Empirical Contrast. Journal of Transportation Engineering, 2016: p. 04016009.

Bergstad CJ, Gamble A, Hagman O, Polk M, Gärling T, Olsson LE, Affective–symbolic and instrumental–independence psychological motives mediating effects of socio-demographic variables on daily car use. Journal of Transport Geography, 2011. 19(1): p. 33-38.

Wood W, Quinn JM, Kashy DA, Habits in everyday life: thought, emotion, and action. Journal of Personality & Social Psychology, 2003. 83(6): p. 1281-97.

Gardner B, Modelling motivation and habit in stable travel mode contexts. Transportation Research Part F Traffic Psychology & Behaviour, 2009. 12(1): p. 68-76.

Published
2018-06-18
How to Cite
1.
Gao K, Sun L. Incorporating Inertia in Mode Choice and Influential Factors of Car Stickiness: Implications for Shifts to Public Transit. Promet [Internet]. 2018Jun.18 [cited 2024Apr.16];30(3):293-0. Available from: https://traffic.fpz.hr/index.php/PROMTT/article/view/2507
Section
Articles