nach oben

Transportation

Erschienen in:

01.01.2016

Empirical analysis and comparisons about time-allocation patterns across segments based on mode-specific preferences

verfasst von: Xuemei Fu, Zhicai Juan

Erschienen in: Transportation | Ausgabe 1/2016

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

A three-stage approach, i.e., factor-cluster-multi-group Structural Equation Modeling (SEM), is designed to explore the commonalities and diversities with respect to relationships between socio-demographic characteristics and time-use patterns across different segments. Factor-cluster analysis is conducted to extract meaningful factors from attitudinal statements, and then group the sample population into three segments, each with a unique combination of mode preferences for public transit, private car, and motorcycle. By virtue of multi-group SEM, the relationships between socio-demographics and time allocated to activities and travel are found to be significantly different across segments. This study highlights the importance of latent psychological factors in segmentation. For policy implication, specific population with unique psychological features must be targeted in order to efficiently and effectively design and implement transport measures.

Vorheriger Artikel Compliance and data quality in GPS-based studies

Nächster Artikel Built environment impacts on walking for transport in Brisbane, Australia

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Ajzen, I.: The theory of planned behavior. Organ. Behav. Hum. Decis. Process. 50(2), 179–211 (1991)CrossRef

Ajzen, I., Cote, N.G.: Attitudes and the prediction of behavior. Attitudes Attitude Chang. 289–311 (2008)

Anable, J.: ‘Complacent car addicts’ or ‘aspiring environmentalists’? Identifying travel behaviour segments using attitude theory. Transp. Policy 12(1), 65–78 (2005)CrossRef

Anable, J., Gatersleben, B.: All work and no play? The role of instrumental and affective factors in work and leisure journeys by different travel modes. Transp. Res. Part A: Policy Pract. 39(2), 163–181 (2005)

Bamberg, S., Fujii, S., Friman, M., Gärling, T.: Behaviour theory and soft transport policy measures. Transp. Policy 18(1), 228–235 (2011)CrossRef

Bamberg, S., Schmidt, P.: Theory-driven subgroup-specific evaluation of an intervention to reduce private car use1. J. Appl. Soc. Psychol. 31(6), 1300–1329 (2001)CrossRef

Bohte, W., Maat, K., van Wee, B.: Measuring attitudes in research on residential self-selection and travel behaviour: a review of theories and empirical research. Transp. Rev. 29(3), 325–357 (2009)CrossRef

Bollen Kenneth, A.: Structural Equations with Latent Variables. Wiley, New York (1989)

Churchill Gilbert A.: Marketing Research: Methodological Foundations, 7th edn. The Dryden Press, New York (1999)

Fishbein, M., Ajzen, I.: Belief, attitude, intention and behavior: An introduction to theory and research. Addison-Wesley, Reading, MA (1975)

Fujii, S., Gärling, T.: Application of attitude theory for improved predictive accuracy of stated preference methods in travel demand analysis. Transp. Res. Part A: Policy Pract. 37(4), 389–402 (2003)

Fujii, S., Kitamura, R.: Evaluation of trip-inducing effects of new freeways using a structural equations model system of commuters’ time use and travel. Transp. Res. Part B: Methodol. 34(5), 339–354 (2000)CrossRef

Gehlert, T., Dziekan, K., Gärling, T.: Psychology of sustainable travel behavior. Transp. Res. Part A 48(Complete), 19–24 (2013)

Golob T.F.: A model of household demand for activity participation and mobility. In: Gärling, T., Laitilla, T., Westin, K. (eds.) Theoretical Foundations of Travel Choice Modelling, pp. 365–398. Pergamon, Oxford (1996)

Golob, T.F.: A simultaneous model of household activity participation and trip chain generation. Transp. Res. Part B: Methodol. 34(5), 355–376 (2000)CrossRef

Golob, T.F.: Structural equation modeling for travel behavior research. Transp. Res. Part B: Methodol. 37(1), 1–25 (2003)CrossRef

Golob, T.F., Kitamura, R., Lula, C.: Modeling the effects of commuting time on activity duration and non-work travel. In: 73rd Annual Meeting of the Transportation Research Board, Washington, DC, 1994

Golob, T.F., McNally, M.G.: A model of activity participation and travel interactions between household heads. Transp. Res. Part B: Methodol. 31(3), 177–194 (1997)CrossRef

Gorsuch, R.: Factor Analysis. LEA, Hillsdale (1983)

Gould, J., Golob, T.F.: Shopping without travel or travel without shopping? An investigation of electronic home shopping. Transp. Rev. 17(4), 355–376 (1997)CrossRef

Hair, J.F., Anderson, R.E., Tatham, R.L., Black, W.C.: Multivariate Analysis. Prentice Hall International, Englewood (1998)

Hair, J.F., Tatham, R.L., Anderson, R.E., Black, W.: Multivariate data analysis, vol. 6. Pearson Prentice Hall, Upper Saddle River (2006)

Heath, Y., Gifford, R.: Extending the theory of planned behavior: predicting the use of public transportation1. J. Appl. Soc. Psychol. 32(10), 2154–2189 (2002)CrossRef

Hunecke, M., Haustein, S., Böhler, S., Grischkat, S.: Attitude-based target groups to reduce the ecological impact of daily mobility behavior. Environ. Behav. 42(1), 3–43 (2010)CrossRef

Hunecke, M., Haustein, S., Grischkat, S., Böhler, S.: Psychological, sociodemographic, and infrastructural factors as determinants of ecological impact caused by mobility behavior. J. Environ. Psychol. 27(4), 277–292 (2007)CrossRef

Kamakura, W.A., Wedel, M.: Market Segmentation: Conceptual and Methodological Foundations. Kluwer Academic Press, New York (1999)

Kitamura, R.: An evaluation of activity-based travel analysis. Transportation 15(1–2), 9–34 (1988)

Kitamura, R., Robinson, J., Golob, T.F., Bradley, M., Leonard, J., van der Hoorn, T.: A comparative analysis of time use data in the Netherlands and California, Research Report Number: UCDITS-RR-92–9, Institute of Transportation Studies, University of California, Davis, June (1992)

Kuhnimhof, T., Chlond, B., von der Ruhren, S.: Users of transport modes and multimodal travel behavior steps toward understanding travelers’ options and choices. Transp. Res. Rec.: J. Transp. Res. Board 1985(1), 40–48 (2006)CrossRef

Kuppam, A.R., Pendyala, R.M.: A structural equations analysis of commuters’ activity and travel patterns. Transportation 28(1), 33–54 (2001)CrossRef

Lanzendorf, M.: Mobility styles and travel behavior: application of a lifestyle approach to leisure travel. Transp. Res. Rec.: J. Transp. Res. Board 1807(1), 163–173 (2002)CrossRef

Lu, X., Pas, E.I.: Socio-demographics, activity participation and travel behavior. Transp. Res. Part A: Policy Pract. 33(1), 1–18 (1999)CrossRef

Ma, J., Goulias, K.G.: Application of Poisson regression models to activity frequency analysis and prediction. Transp. Res. Rec.: J. Transp. Res. Board 1676(1), 86–94 (1999)CrossRef

Ohnmacht, T., Götz, K., Schad, H.: Leisure mobility styles in Swiss conurbations: construction and empirical analysis. Transportation 36(2), 243–265 (2009)CrossRef

Pendyala, R., Kitamura, R., Prasuna Reddy, D.: Application of an activity-based travel-demand model incorporating a rule-based algorithm. Environ. Plan. B 25, 753–772 (1998)CrossRef

Pronello, C., Camusso, C.: Travellers’ profiles definition using statistical multivariate analysis of attitudinal variables. J. Transp. Geogr. 19(6), 1294–1308 (2011)CrossRef

Schwartz, S.H.: Normative influences on altruism. Adv. Exp. Soc. Psychol. 10, 221–279 (1977)CrossRef

Shen, J.: Latent class model or mixed logit model? A comparison by transport mode choice data. Appl. Econ. 41(22), 2915–2924 (2009)CrossRef

Spears, S., Houston, D., Boarnet, M.G.: Illuminating the unseen in transit use: a framework for examining the effect of attitudes and perceptions on travel behavior. Transp. Res. Part A: Policy Pract. 58, 40–53 (2013)

Sung, H.H.: Classification of adventure travelers: behavior, decision making, and target markets. J. Travel Res. 42(4), 343–356 (2004)CrossRef

Vermunt, J.K., Magidson, J.: Latent class cluster analysis. In: Hagenaars, J.A, McCutcheon, A.L. (eds.) Advances in Latent Class Analysis. Cambridge University Press (2002)

Vermunt, J.K., Magidson, J.: Latent class models for classification. Comput. Stat. Data Anal. 41(3), 531–537 (2003)CrossRef

Wedel, M., Kamakura, W.: Market Segmentation. Conceptual and Methodological Foundation. Kluwer Academic Publisher, Boston–Dordrecht–London (1998)

Titel: Empirical analysis and comparisons about time-allocation patterns across segments based on mode-specific preferences
verfasst von: Xuemei Fu
Zhicai Juan
Publikationsdatum: 01.01.2016
Verlag: Springer US
Erschienen in: Transportation / Ausgabe 1/2016
Print ISSN: 0049-4488
Elektronische ISSN: 1572-9435
DOI: https://doi.org/10.1007/s11116-014-9561-2

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Weitere Artikel der Ausgabe 1/2016

Predicting consumers’ intention to adopt hybrid electric vehicles: using an extended version of the theory of planned behavior model

An analysis of activity time use on vehicle usage rationed days

Rail freight transport and demand requirements: an analysis of attribute cut-offs through a stated preference experiment

Costs of school transportation: quantifying the fiscal impacts of encouraging walking and bicycling for school travel

An exploratory analysis of spatial effects on freight trip attraction

Built environment impacts on walking for transport in Brisbane, Australia

Premium Partner