Design and Implementation of an Internet-Based Household Activity Scheduling Survey in Cairo, Egypt
Publication: Journal of Urban Planning and Development
Volume 140, Issue 4
Abstract
This paper reports on the design and implementation of an internet-based survey that focuses on household activity scheduling in Cairo, Egypt. The survey is referred to as Internet-based daily activity scheduling of household activities (IDASHA). The main emphasis of the survey was on different types of household interactions and coordination over a multiple-day period. The survey also collected detailed information about information and communication technology (ICT) usage and the role that telecommunications play in household interactions in the planning and scheduling process. The survey was conducted over one week during the months of March to May 2009. The final sample size included 42 households of married couples (i.e., 84 adults). The survey was evaluated according to several criteria, and was shown to provide a rich source of data while minimizing the burden on the survey respondents. Moreover, statistical analyses were carried out to investigate several issues such as time allocation behavior, weekly household interactions in activity participation, and the development of a horizon index that shows how far ahead in time an event was planned. Basic need activities, work, and household obligation activities were found to have the highest portion of time at both the daily and weekly levels. However, there was a significant difference in the mean episode duration of these three groups of activities. According to the activity location, in-home activity episodes were found to be usually short, yet occupying a large portion of time per day. Out-of-home activities, however, had longer durations but were much less frequent than in-home activities. As for the companion type in joint activity participation, joint activities with only household members were shown to be more frequent than other participation types. In contrast, the activities performed with nonhousehold members were, on average, longer but much less frequent than those done alone or with household members.
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References
Arentze, T. A., and Timmermans, H. J. P. (2005). “Albatross version 2: A learning-based transportation oriented simulation system. Eindhoven.” European Institute of Retailing and Services Studies, The Netherlands.
Bates, J., Skinner, A., Scholefield, G., and Bradley, R. (1997). “Study of parking and traffic demand: 2. A traffic restraint analysis model.” Traffic Eng. Contr., 38(3), 135–141.
Ben-Akiva, M., Bowman, J., and Gopinath, D. (1996). “Travel demand model system for the information era.” Transportation, 23(3), 241–266.
Ben-Akiva, M. E., and Bowman, J. L. (1998). “Integration of an activity-based model system and a residential location model.” Urban Studies, 35(7), 1131–1153.
Bhat, C. R., and Pendyala, R. M. (2005). “Modeling intra-household interactions and group decision-making.” Transportation, 32(5), 443–448.
Bowman, J. L., and Ben-Akiva, M. E. (1995). “Activity-based model system of urban passenger travel demand.” 74th Annual Meeting of Transportation Research Board, Transportation Research Board, National Research Council, Washington, DC.
Doherty, S., and Miller, E. J. (2000). “A computerized household activity scheduling survey.” Transportation, 27(1), 75–97.
Doherty, S. T., Nemeth, E., Roorda, M. J., and Miller, E. J. (2004). “Design and assessment of Toronto area computerized household activity scheduling survey.” Transport. Res. Rec. J. Transport. Res. Board, 1894, National Research Council, Washington DC, 140–149.
Ettema, D., Borgers, A., and Timmermans, H. (1994). “Using interactive computer experiments for identifying activity scheduling heuristics.” 7th Int. Conf. on Travel Behaviour, Elsevier, Pergamon, Oxford.
Gärling, T., et al. (1989). “Household activity scheduling.” Transport Policy, Management and Technology Towards 2001: Selected Proc., 5th World Conf. on Transport Research, Vol. 4, Western Periodicals, Ventura, CA, 235–248.
Gärling, T., Kwan, M.-P., and Golledge, R. G. (1994). “Computational-process modeling of household travel activity scheduling.” Transport. Res. B, 28(5), 355–364.
Hägerstraand, T. (1970). “What about people in regional science?” Proc., Regional Science Association, 24(1), 7–21.
Hayes-Roth, B., and Hayes-Roth, F. (1979). “A cognitive model of planning.” Cognitive Science, 3(4), 275–310.
ICT Indicators. “In brief: Monthly issue.” The Ministry of Communications and Information Technology of Egypt, 〈http://www.mcit.gov.eg/〉 (July 21, 2012).
Joh, C-H. (2004). “Measuring and predicting adaptation in multidimensional activity-travel patterns.” Ph.D. thesis, 79, Technical Univ. of Eindhoven, The Netherlands.
Kang, K., and Scott, D. M. (2011). “Impact of different criteria for identifying intra-household interactions: A case study of household time allocation.” Transportation, 38(1), 81–99.
Kitamura, R. (1998). “An evaluation of activity-based travel analysis.” Transportation, 15(1), 9–34.
Kitamura, R., Chen, C., and Pendyala, R. M. (1997). “Generation of synthetic daily activity-travel patterns.” Transport. Res. Rec. J. Transport. Res. Board, 1607, National Research Council, Washington, DC, 154–162.
Kitamura, R., Pendyala, R. M., Pas, E. I., and Reddy, P. (1995). “Application of AMOS, an activity-based TCM evaluation tool, to the Washington, DC, metropolitan area.” 23rd European Transport Forum: Proc., Seminar E Transportation Planning Methods, PTRC Education and Research Services, London, 177–190.
Miller, E. J., and Roorda, M. J. (2003). “Prototype model of household activity-travel scheduling.” Transport. Res. Rec. J. Transport. Res. Board, 1831, National Research Council, Washington, DC, 114–121.
Spear, B. D. (1996). “New approaches to transportation forecasting models: A synthesis of four research proposals.” Transportation, 23, 215–240.
Srinivasan, S., and Bhat, C. R. (2008). “An exploratory analysis of joint-activity participation characteristics using the American time use survey.” Transportation, 35(3), 301–327.
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© 2014 American Society of Civil Engineers.
History
Received: Nov 24, 2012
Accepted: Sep 3, 2013
Published online: Sep 5, 2013
Discussion open until: Jul 7, 2014
Published in print: Dec 1, 2014
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