Impact of time-space prism accessibility on time use behavior and its propagation through intra-household interaction

REFERENCES

• Auld, J. & Mohammadian, A. (2009). Framework for the Development of the Agent-Based Dynamic Activity Planning and Travel Scheduling (ADAPTS) Model, Transportation Letters: The International Journal of Transportation Research, Vol. 1(3), 2009, pp. 245–255.
   Google Scholar
• Badoe, D. & Miller, E. (2000). Transportation-Land-Use interaction: Empirical findings in North America, and their implications for modeling. Transportation Research Part D: Transport and Environment, 5(4), 235–263.
   Web of Science ®Google Scholar
• Bentler, P.M. (1995). EQS Structural Equations Program Manual. Multivariate Software, Encino, CA.
   Google Scholar
• Bentler, P.M. & Chou, C.P. (1987). Practical issues in struc-tural modeling. Sociological Methods and Research, 16: 78–117.
   Web of Science ®Google Scholar
• Bhat, C.R. & Pendyala, R.M. (2005). Modeling intra-household interactions and group decision-making. Transportation, 32: 443–448, Springer.
   Google Scholar
• Boomsma, A. & Hoogland, J.J. (2001). The robustness of LISREL modeling revisited. In: Cudeck, R., du Toit, S., Sörbom, D. (Eds.), Structural Equation Modeling: Present and Future. Scientific Software International, Chicago, pp. 139–168.
   Google Scholar
• Bradley, M. & Vovsha, P. (2005). A model for joint choice of daily activity pattern types of household members. Transportation, 32: 545–571, Springer.
   Web of Science ®Google Scholar
• Burns, L. (1979). Transportation, temporal, and spatial com-ponents of accessibility. Lexington Books, Lexington, Mass.
   Google Scholar
• De Abreu e Silva, J. E., Golob, T. & Goulias, K. (2006). Effects of land use characteristics on residence and employment location and travel behavior of urban adult workers. Transportation Research Record: Journal of the Transportation Research Board, 1977, 121–131.
   Google Scholar
• Ewing R. & Cervero R. (2010). Travel and the Built Environment: A Meta-Analysis, Journal of the American Planning Association, 76:3, pp. 265–294.
   Web of Science ®Google Scholar
• Gliebe, J.P. & Koppleman, F.S. (2005). Modeling house-hold activity-travel interactions as parallel constrained choices. Transportation, 32: 449–471. Springer.
   Web of Science ®Google Scholar
• Golledge, R. G. (1984). An anchor point theory of the acquisi-tion of spatial knowledge and some empirical observations. Paper presented at the AAG meetings, Washington, DC.
   Google Scholar
• Golob, T.F. & McNally, M.G. (1997). A model of activity participation and travel interactions between household heads. Transportation Research B, 31(3): 177–194.
   Google Scholar
• Golob, T.F. (1998). A model of household demand for activ-ity participation and mobility. In T. Gärling, T. Laitila and K. Westin, eds. Theoretical Foundations of Travel Choice Modeling: 365–398, Oxford: Pergamon.
   Google Scholar
• Golob, T.F. (2003). Structural equation modeling for travel behavior research. Transportation Research, B - Methodological, 37: 1–25.
   Google Scholar
• Goulias, K. G. & Henson, K. (2006). On Altruists and Egoists in Activity Participation and Travel: Who are they and do they live together? Transportation, 33(5): 447–462.
   Web of Science ®Google Scholar
• Goulias, K. G., Blain, L., Kilgren, N., Michalowski, T. & Murakami, E. (2007). Catching the next big wave: Do observed behavioral dynamics of baby boom-ers force rethinking of regional travel demand mod-els? Transportation Research Record: Journal of the Transportation Research Board, 2014: 67–75.
   Web of Science ®Google Scholar
• Flägerstrand, T. (1970). What about people in regional sci-ence? Papers and Proceedings of the Regional Science Association, 24: 7–24.
   Google Scholar
• Handy, S. (1992). Regional versus local accessibility: Neo-Traditional development and its implications for non-work travel. Built Environment, 18(4), 253–267.
   Google Scholar
• Handy, S. (1996). Methodologies for exploring the link between urban form and travel behavior. Transportation Research Part D: Transport and Environment, 1(2): 151–165.
   Web of Science ®Google Scholar
• Hildebrand, E. D. (2003). Dimensions in elderly travel behaviour: A simplified activity-based model using life-style clusters. Transportation, 30(3), 285–306.
   Web of Science ®Google Scholar
• Kim, H-M & Kwan, M-P (2003). Space-time accessibility measures: a geocomputational algorithm with focus on the feasible opportunity set and possible activity dura-tion, LP Journal of Geographical Systems, 5: 71–91.
   Google Scholar
• Kitamura, R. (1989). Life-Style and Travel Demand. Transportation Research Board Special Report (220), 149–189.
   Google Scholar
• Kitamura, R., Akiyama, T., Yamamoto, T. & Golob, T.F. (2001). Accessibility in a Metropolis: Toward a Better Understanding of Land Use and Travel. Transportation Research Record: Journal of the Transportation Research Board 1780: 64–75.
   Web of Science ®Google Scholar
• Kline, R.B. (Ed.) (1998a). Principles and Practice of Structural Equation Modeling. Guilford Press, New York.
   Google Scholar
• Kline, R.B. (1998b). Software programs for structural equa-tion modeling: AMOS, EQS, and LISREL. Journal of Psychoeducational Assessment 16: 302–323.
   Google Scholar
• Koenig, J.G. (1980). Indicators of urban accessibility: theory and application. Transportation, 9:145-172. Springer.
   Web of Science ®Google Scholar
• Kostyniuk, L.P. & Kitamura, R (1981). Life cycle and household time-space paths: empirical investigation, Transportation Research Record, 879: 28–37.
   Google Scholar
• Krizek, K. J. & Waddell, P. (2002). Analysis of lifestyle choices: Neighborhood type, travel patterns, and activity participation. Transportation Research Record: Journal of the Transportation Research Board, 1807(-1), 119–128.
   Google Scholar
• Kwan, M-P (1998). Space-time and integral measures of individual accessibility: a comparative analysis using a point-based framework, Geographical Analysis, 30: 191–217.
   Web of Science ®Google Scholar
• Loehlin, J.C. (1998). Latent Variable Models: An Introduction to Factor, Path, and Structural Analysis. Lawrence Erlbaum Associates, Mahwah, NJ.
   Google Scholar
• Meister, K., Frick, M. & Axhausen, K.W. (2005) A GA-based household scheduler. Transportation, 32: 473–494. Springer.
   Web of Science ®Google Scholar
• Miller, H.J. (1991). Modeling accessibility using space-time prism concepts within geographical information sys-tems. International Journal of Geographical Information Systems 5: 287–301.
   Web of Science ®Google Scholar
• Miller H.J. (2005). Place-based versus people-based acces-sibility, in D. Levinson and K. J. Krizek (eds.) Access to Destinations, Elsevier, 63–89.
   Google Scholar
• Miranda-Moreno, L. F. & Lee-Gosselin, M. (2008). A week in the life of baby boomers: How do they see the spatial-temporal organization of their activities and travel? Transportation, 35(5), 629–653.
   Web of Science ®Google Scholar
• Muthén, L.K. & Muthén, B.O. (2002). How to use a Monte Carlo study to decide on sample size and determine power. Structural Equation Modeling, 4:599–620.
   Web of Science ®Google Scholar
• Okola, A. (2003). Departure time choice for recreational activities by elderly nonworkers. Transportation Research Record: Journal of the Transportation Research Board, 1848, 86–93.
   Google Scholar
• Pendyala, R. M., Yamamoto, T. & Kitamura, R. (2002). On the formulation of time-space prisms to model constraints on personal activity-travel engagement. Transportation 29: 73–94.
   Web of Science ®Google Scholar
• Srinivasan, K.K. & Athuru, S.R. (2005). Analysis of within-household effects and between-household differences in maintenance activity allocation. Transportation, 32: 495–521. Springer.
   Web of Science ®Google Scholar
• Srinivasan, S. & Bhat, C.R. (2005). Modeling household interactions in daily in-home and out-of-home mainte-nance activity participation. Transportation, 32: 523–544. Springer.
   Web of Science ®Google Scholar
• Srinivasan, N., McGuckin, N. & Murakami, E. (2006). Working retirement: Travel trends of the aging work-force. Transportation Research Record: Journal of the Transportation Research Board, 1985: 61–70.
   Google Scholar
• Stevens, J. (1996). Applied Multivariate Statistics for the Social Sciences. Lawrence Erlbaum Associates, Mahwah, NJ.
   Google Scholar
• Sun, Y., Waygood, E.O.D., Fukui, K. & Kitamura, R. (2009). Built Environment or Household Life-Cycle Stages-Which Explains Sustainable Travel More? Transportation Research Record: Journal of the Transportation Research Board, 2135: 123–129.
   Google Scholar
• Tanaka, J.S. (1993). Multifaceted conceptions of fit in struc-tural equation models. In Bollen, K.A. & Long, J.S. (Ed.), Testing structural equation models.
   Google Scholar
• Vovsha, P. & Petersen, E. (2005). Escorting children to school: Statistical analysis and applied modeling approach. Transportation Research Record: Journal of the Transportation Research Board, 1921(-1), 131–140.
   Google Scholar
• Weber, J. & Kwan, M-P (2002). Bringing time back in: a study on the influence of travel time variations and facil-ity opening hours on individual accessibility, The profes-sional geographer, 54(2): 226–240.
   Web of Science ®Google Scholar
• Weibull, J.W. (1980). On the numerical measurement of accessibility, Environment and Planning A, 12(1): 53–67.
   Web of Science ®Google Scholar
• Yarlagadda, A. K. & Srinivasan, S. (2008). Modeling chil-dren's school travel mode and parental escort decisions. Transportation, 35(2), 201–218.
   Web of Science ®Google Scholar
• Yoon, S.Y. & Goulias, K.G., (2010). Constraint-based assess-ment of intra-household bargaining on time allocation to activities and travel using individual accessibility measures. Proceedings of the 89th Annual Meeting of the Transportation Research Board, January 2010.
   Google Scholar
• Zhang, J. & Fujiwara, A (2006). Representing household time allocation behavior by endoge-nously incorporating diverse intra-household interactions: A case study in the context of elderly couples. Transportation Research Part B: Methodological, 40(1): 54–74.
   Web of Science ®Google Scholar
• Zhang, J., Timmermans, H.J.P. & Borgers, A.W.J. (2002). A utility-maximizing model of house-hold time use for independent, shared and allocated activities incor-porating group decision mechanisms. Transportation Research Record, 1807: 1–8.
   Google Scholar
• Zhang, J., Timmermans, H.J.P. & Borgers, A.W.J. (2005). A model of household task allocation and time use. Transportation Research B, 39, 81–95.
   Google Scholar
• Zahavi, Y. (1979). The UMOT Project. US Department of Transportation RSPA-DPB, vol. 20-79-3, US Department of Transportation, Washington.
   Google Scholar