nach oben

Erschienen in:

2023 | OriginalPaper | Buchkapitel

7. Effects of Family Structure on Travel Behaviour

verfasst von : Pengjun Zhao, Dandan Yuan

Erschienen in: Population Growth and Sustainable Transport in China

Verlag: Springer Nature Singapore

Einloggen

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

search-config

KI-gestützte Suche

Aus

Abstract

Family is the basic unit of the social and economic activities of the population. A large number of studies abroad have shown that family attributes have an important influence on the daily activities and travel behaviour of individuals, but there is still a lack of relevant research on family travel behaviour in China. Based on the family structure attributes of the population, this study uses statistical description analysis and multiple logistic regression analysis to identify travel behaviour differences between different family types, and it quantitatively examines the family attributes that affect individual travel decisions. The results show that the trip volume of single-person households is higher than that of multi-person households, and the proportion of leisure trip activities is larger. Households with higher incomes and larger scales have higher car ownership rates, but lower bicycle ownership rates. In general, factors such as family size, family income level, family transport ownership, whether there are children in the family, whether there are older people, etc., all have varying degrees of impact on residents’ travel behaviour. With the characteristics of miniaturisation and diversification of family types in China’s population structure, high-quality transport services that meet the needs of the population need to combine the differentiated travel characteristics of different families to provide customised and personalised travel services.

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

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Vorheriges Kapitel Travel Differences Between the Urban and Rural Population

Nächstes Kapitel Gendered Mobility

In this section, the central urban area in Beijing consists of Xicheng, Dongcheng, Chaoyang, Haidian, Fengtai and Shijingshan.

In this section, the suburbs of Beijing consist of Tongzhou, Shunyi, Daxing, Fangshan, Mentougou and Changping.

In this section, the outer suburbs of Beijing refers consist of Pinggu, Yanqing, Huairou and Miyun.

In this chapter, older people are over 65 years old.

In this chapter, a child is below 12 years old.

In China, middle-aged and older people are increasingly gathering in open public spaces such as squares to learn dancing with music. This form of entertainment is usually called a square dance.

Abuhamoud, M. A. A., Rahmat, R. A. O. K., & Ismail, A. (2011). Modeling of transport mode in Libya: A binary Logit model for government transportation encouragement. Australian Journal of Basic & Applied Sciences, 5(5), 1291–1296.

Aizezi, M., Lin, Q., Yao, Z. G., & Xi, E. C. (2017). Behavior of students’ travel mode choice based on family structure differences. Chang’an Daxue Xuebao/Journal of Chang’an University, 37(6), 113–120.

Allard, M. D., & Janes, M. (2008). Time use of working parents: A visual essay. Monthly Labor Review, 131(6), 3–14.

Bartosiewicz, B., & Pielesiak, I. (2019). Spatial patterns of travel behaviour in Poland. Travel Behaviour and Society, 15, 113–122. https://doi.org/10.1016/j.tbs.2019.01.004.CrossRef

Basarić, V., Vujičić, A., Simić, J. M., Bogdanović, V., & Saulić, N. (2016). Gender and age differences in the travel behavior—A Novi sad case study. Transportation Research Procedia, 14, 4324–4333. https://doi.org/10.1016/j.trpro.2016.05.354.CrossRef

Bernardo, C., Paleti, R., Hoklas, M., Bhat, C., et al. (2015). An empirical investigation into the time-use and activity patterns of dual-earner couples with and without young children. Transportation Research, Part A. Policy practice, 76A(Jun.), 71–91.

Bhat, C. R., & Singh, S. K. (2000). A comprehensive daily activity-travel generation model system for workers. Transportation Research Part A Policy Practice, 34(1), 1–22.CrossRef

Bjerkan, K. Y., & Nordtomme, M. E. (2014). Car use in the leisure lives of adolescents. Does household structure matter? Transport Policy, 33(may), 1–7.

Boarnet, M. G., & Hsu, H.-P. (2015). The gender gap in non-work travel: The relative roles of income earning potential and land use. Journal of Urban Economics, 86, 111–127. https://doi.org/10.1016/j.jue.2015.01.005.CrossRef

Bruijn, G. D., Kremers, S., Schaalma, H., Mechelen, W. V., & Brug, J. (2005). Determinants of adolescent bicycle use for transportation and snacking habior. Preventive Medicine, 40, 658–667.

Chakrabarti, S., & Joh, K. (2019). The effect of parenthood on travel behavior: Evidence from the California Household Travel Survey. Transportation Research Part A: Policy Practice, 120(FEB.), 101–115.

Craig, L., & van Tienoven, T. P. (2019). Gender, mobility and parental shares of daily travel with and for children: A cross-national time use comparison. Journal of Transport Geography, 76, 93–102. https://doi.org/10.1016/j.jtrangeo.2019.03.006.CrossRef

Daniel, F., Lise, G., Yan, K., Mark, D., Michel, F., Patrick, M., & Louis, D. (2013). Impact evaluation of a public bicycle share program on cycling: a case example of BIXI in Montreal, Quebec. American Journal of Public Health, 103(3).

Deka, D., & Fei, D. (2019). A comparison of the personal and neighborhood characteristics associated with ridesourcing, transit use, and driving with NHTS data. Journal of Transport Geography, 76(APR.), 24–33.

Dieleman, F., Dijst, M., & Burghouwt, G. (2002). Urban form and travel behaviour: Micro-level household attributes and residential context. Urban Studies, 39(3), 507–527.CrossRef

Ding, C., Liu, C., Zhang, Y., Yang, J., & Wang, Y. (2017). Investigating the impacts of built environment on vehicle miles traveled and energy consumption: Differences between commuting and non-commuting trips. Cities, 68(aug.), 25–36.

Elias, W., & Katoshevski-Cavari, R. (2014). The role of socio-economic and environmental characteristics in school-commuting behavior: A comparative study of Jewish and Arab children in Israel. Transport Policy, 32, 79–87. https://doi.org/10.1016/j.tranpol.2013.12.007.CrossRef

Etminani-Ghasrodashti, R., & Ardeshiri, M. (2015). Modeling travel behavior by the structural relationships between lifestyle, built environment and non-working trips. Transportation Research Part A: Policy and Practice, 78, 506–518. https://doi.org/10.1016/j.tra.2015.06.016.CrossRef

Ettema, D., & van der Lippe, T. (2009). Weekly rhythms in task and time allocation of households. Transportation, 36, 113–129.

Faghih-Imani, A., & Eluru, N. (2015). Analysing bicycle-sharing system user destination choice preferences: Chicago’s Divvy system. Journal of Transport Geography, 44.

Feng, J. (2017). The influence of built environment on travel behavior of the elderly in urban China. Transportation Research Part D: Transport and Environment, 52, 619–633. https://doi.org/10.1016/j.trd.2016.11.003.CrossRef

Feng, J., Dijst, M., Wissink, B., & Prillwitz, J. (2015). Elderly co-residence and the household responsibilities hypothesis: evidence from Nanjing, China. Urban Geography, 36(5).

Fischer, D., Harbrecht, A., Surmann, A., & McKenna, R. (2019). Electric vehicles’ impacts on residential electric local profiles—A stochastic modelling approach considering socio-economic, behavioural and spatial factors. Applied Energy, 233–234, 644–658. https://doi.org/10.1016/j.apenergy.2018.10.010.CrossRef

Goh, E. (2009). Grandparents as childcare providers: An in-depth analysis of the case of Xiamen China. Journal of Aging Studies, 23(1), 60–68.CrossRef

Hamidi, Z., & Zhao, C. (2020). Shaping sustainable travel behaviour: Attitude, skills, and access all matter. Transportation Research Part d: Transport and Environment, 88, 102566. https://doi.org/10.1016/j.trd.2020.102566.CrossRef

He, S. Y., Cheung, Y. H. Y., & Tao, S. (2018). Travel mobility and social participation among older people in a transit metropolis: A socio-spatial-temporal perspective. Transportation Research Part A: Policy and Practice, 118, 608–626. https://doi.org/10.1016/j.tra.2018.09.006.CrossRef

Heinen, E., Wee, B. v., & Maat, K. (2010). Commuting by bicycle: An overview of the literature. Transport Reviews, 30(1), 59–96. https://doi.org/10.1080/01441640903187001.

Hsu, H. P., & Saphores, J. D. (2014). Impacts of parental gender and attitudes on children’s school travel mode and parental chauffeuring behavior: Results for California based on the 2009 National Household Travel Survey. Transportation, 41(3), 543–565.CrossRef

Johansson, M. (2006). Environment and parental factors as determinants of mode for children’s leisure travel. Journal of Environmental Psychology, 26(2), 156–169.CrossRef

Kamruzzaman, M., Shatu, F., & Habib, K. N. (2020). Travel behaviour in Brisbane: Trends, saturation, patterns and changes. Transportation Research Part A: Policy and Practice, 140, 231–250. https://doi.org/10.1016/j.tra.2020.08.019.CrossRef

Kang, H., & Scott, D. M. (2010). Exploring day-to-day variability in time use for household members. Transportation Research Part A Policy Practice, 44(8), 609–619.CrossRef

Kitamura, R., & Kostyniuk, L. P. (1986). Maturing motorization and household travel: The case of nuclear-family households. Transportation Research Part A: General, 20(3), 245–260.CrossRef

Kotval-K, Z., & Vojnovic, I. (2015). The socio-economics of travel behavior and environmental burdens: A Detroit, Michigan regional context. Transportation Research Part d: Transport and Environment, 41, 477–491. https://doi.org/10.1016/j.trd.2015.10.017.CrossRef

Larsen, K., Gilliland, J., Hess, P., Tucker, P., Irwin, J., & He, M. (2009). The influence of the physical environment and sociodemographic characteristics on children's mode of travel to and from school. American Journal of Public Health.

Lee, Y., Washington, S., & Frank, L. D. (2009). Examination of relationships between urban form, household activities, and time allocation in the Atlanta Metropolitan Region. Transportation Research Part A, 43(4), 360–373.

Mao, Y., & Li, J. (2020). Ji yu jia ting sheng ming zhou qi li lun de lao nian ren ri chang sheng huo quan qing jing yan jiu. [Context in daily life circle of the elderly based on family life circle theory: A case study of Xi'an]. Areal Research and Development, 39(2), 169–175.

Matiaske, W., Menges, R., & Spiess, M. (2012). Modifying the rebound: It depends! Explaining mobility behavior on the basis of the German socio-economic panel. Energy Policy, 41, 29–35. https://doi.org/10.1016/j.enpol.2010.11.044.CrossRef

Mcdonald, N. C. (2008). Household interactions and children’s school travel: The effect of parental work patterns on walking and biking to school. Journal of Transport Geography, 16(5), 324–331.CrossRef

Merom, D., Tudor-Locke, C., Bauman, A., & Rissel, C. (2006). Active commuting to school among NSW primary school children: Implications for public health. Health & Place, 12(4), 678–687.CrossRef

Nakanishi, H., Dillon, A., & Tranter, P. (2017). Getting more children walking and cycling to school: Insights from parents in three Australian cities. In Paper presented at the ATRF 2017—Australasian Transport Research Forum 2017, Proceedings.

Pont, K., Ziviani, J., Wadley, D., Bennett, S., & Abbott, R. (2009). Environmental correlates of children’s active transportation: A systematic literature review. Health & Place, 15(3), 849–862.CrossRef

Richter, M., Erhart, M., Vereecken, C. A., Zambon, A., Boyce, W., & Gabhainn, S. N. (2009). The role of behavioural factors in explaining socio-economic differences in adolescent health: A multilevel study in 33 countries. Social Science & Medicine, 69(3), 396–403. https://doi.org/10.1016/j.socscimed.2009.05.023.CrossRef

Sánchez, O., Isabel, M., & González, E. (2014). Travel patterns, regarding different activities: Work, studies, household responsibilities and Leisure. Transportation Research Procedia, 3, 119–128.CrossRef

Sayer, L. C. (2016). Trends in women’s and men’s time use, 1965–2012: Back to the future?. Springer International Publishing.

Schwanen, T., Kwan, M. P., & Fang, R. (2008). How fixed is fixed? Gendered rigidity of space-time constraints and geographies of everyday activities. Geoforum, 39(6), 2109–2121.CrossRef

Shokoohi, R., Hanif, N. R., & Dali, M. (2012). Influence of the socio-economic factors on children’s school travel. Procedia—Social and Behavioral Sciences, 50, 135–147. https://doi.org/10.1016/j.sbspro.2012.08.022.CrossRef

Srinivasan, S., & Bhat, C. R. (2005). Modeling household interactions in daily in-home and out-of-home maintenance activity participation. Transportation, 32(5), 523–544.CrossRef

Srinivasan, S., & Ferreira, J. (2002). Travel behavior at the household level: Understanding linkages with residential choice. Transportation Research. D, 7D(3), 225–242.CrossRef

Stapleton, L., Sorrell, S., & Schwanen, T. (2017). Peak car and increasing rebound: A closer look at car travel trends in Great Britain. Transportation Research Part D Transport & Environment, 53, 217–233.CrossRef

Sweet, M., & Kanaroglou, P. (2016). Gender differences: The role of travel and time use in subjective well-being. Transportation Research Part f: Traffic Psychology and Behaviour, 40, 23–34. https://doi.org/10.1016/j.trf.2016.03.006.CrossRef

Surprenant-Legault, J., Patterson, Z., & El-Geneidy, A. M. (2013). Commuting trade-offs and distance reduction in two-worker households. Transportation Research Part A: Policy Practice.

Ta, N., Kwan, M. P., Chai, Y., & Liu, Z. (2016). Gendered space-time constraints, activity participation and household structure: A case study using A GPS-based activity survey in suburban Beijing, China. Tijdschrift Voor Economische En Sociale Geografie.

Taylor, B. D., Ralph, K., & Smart, M. (2015). What explains the gender gap in schlepping? Testing various explanations for gender differences in household-serving travel. Social Science Quarterly, 96(5), 1493–1510.CrossRef

Witte, A. D., Hollevoet, J., Frederic, D., Hubert, M., & Macharis, C. (2013). Linking modal choice to motility: A comprehensive review. Transportation Research Part A, 49(1), 329–341.

Yarlagadda, A. K., & Srinivasan, S. (2008). Modeling children’s school travel mode and parental escort decisions. Transportation, 35, 201–218.

Yoon, S. Y., Doudnikoff, M., & Goulias, K. G. (2011). Spatial analysis of propensity to escort children to school in Southern California. Transportation Research Record Journal of the Transportation Research Board.

Zhang, Y., Zhao, P., & Lin, J. J. (2021). Exploring shopping travel behavior of millennials in Beijing: Impacts of built environment, life stages, and subjective preferences. Transportation Research Part A: Policy and Practice, 147, 49–60. https://doi.org/10.1016/j.tra.2021.03.012.CrossRef

Zhao, C., Nielsen, T. A. S., Olafsson, A. S., Carstensen, T. A., & Meng, X. (2018). Urban form, demographic and socio-economic correlates of walking, cycling, and e-biking: Evidence from eight neighborhoods in Beijing. Transport Policy, 64, 102–112. https://doi.org/10.1016/j.tranpol.2018.01.018.CrossRef

Zhou, J., & Chai, Y. (2013). Zhong guo lao nian ren kong jian xing wei yan jiu jin zhan. [Research progress on spatial behaviors of the elderly in China]. Progress in Geography, 32(5), 722–732.

Titel: Effects of Family Structure on Travel Behaviour
verfasst von: Pengjun Zhao
Dandan Yuan
Verlag: Springer Nature Singapore
Buch: Population Growth and Sustainable Transport in China
Print ISBN: 978-981-19-7469-4

Electronic ISBN: 978-981-19-7470-0

Copyright-Jahr: 2023
DOI: https://doi.org/10.1007/978-981-19-7470-0_7

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"

Springer Professional "Wirtschaft"

Premium Partner