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Investigating the temporal changes in the relationships between time spent on the internet and non-mandatory activity-travel time use

Author

Listed:
  • Guoqiang Wu

    (University of Leeds)

  • Jinhyun Hong

    (University of Glasgow)

  • Piyushimita Thakuriah

    (Rutgers University)

Abstract

The amount of time we spend online has been increasing dramatically, influencing our daily travel and activity patterns. However, empirical studies on changes in the extent to which the amount of time spent online are related to changes in our activity and travel patterns are scarce, mainly due to a lack of available longitudinal or quasi-longitudinal data. This paper explores how the relationships between the time spent using the Internet, and the time spent on non-mandatory maintenance and leisure activities, have evolved over a decade. Maintenance activities include out-of-home activities such as shopping, banking, and doctor visits, while leisure activities include entertainment activities, visiting friends, sporting activities, and so forth. Our approach uses two datasets from two major cross-sectional surveys in Scotland, i.e. the 2005/06 Scottish Household Survey (SHS) and the 2015 Integrated Multimedia City Data (iMCD) Survey, which were similarly structured and formed. The multiple discrete–continuous extreme value (MDCEV) model and difference-in-differences (DD) estimation are applied and integrated to examine how the relationships between the time spent on the Internet and travel have changed over time and the direction and magnitude of the changes. Our findings suggest that the complementary associations between Internet use and individuals’ non-mandatory activity-travel time use are diminishing over time, whereas their substitutive associations are increasing. We additionally find that such temporal changes are significant in the case of those who spent moderate to high levels of time on the Internet (5 h or more online) per week.

Suggested Citation

  • Guoqiang Wu & Jinhyun Hong & Piyushimita Thakuriah, 2022. "Investigating the temporal changes in the relationships between time spent on the internet and non-mandatory activity-travel time use," Transportation, Springer, vol. 49(1), pages 213-235, February.
  • Handle: RePEc:kap:transp:v:49:y:2022:i:1:d:10.1007_s11116-021-10174-8
    DOI: 10.1007/s11116-021-10174-8
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    as
    1. Lu, Hui & Hess, Stephane & Daly, Andrew & Rohr, Charlene, 2017. "Measuring the impact of alcohol multi-buy promotions on consumers' purchase behaviour," Journal of choice modelling, Elsevier, vol. 24(C), pages 75-95.
    2. Bhat, Chandra R. & Sen, Sudeshna, 2006. "Household vehicle type holdings and usage: an application of the multiple discrete-continuous extreme value (MDCEV) model," Transportation Research Part B: Methodological, Elsevier, vol. 40(1), pages 35-53, January.
    3. Frontuto, Vito, 2019. "Forecasting household consumption of fuels: A multiple discrete-continuous approach," Applied Energy, Elsevier, vol. 240(C), pages 205-214.
    4. Chinh Ho & Corinne Mulley, 2013. "Tour-based mode choice of joint household travel patterns on weekend and weekday," Transportation, Springer, vol. 40(4), pages 789-811, July.
    5. Choo, Sangho & Mokhtarian, Patricia L, 2008. "Telecommunications and travel demand and supply: Aggregate structural equation models for the US," University of California Transportation Center, Working Papers qt6q8518s4, University of California Transportation Center.
    6. Timothy J. Richards & Lisa Mancino, 2014. "Demand for food-away-from-home: a multiple-discrete–continuous extreme value model," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 41(1), pages 111-133, February.
    7. Mokhtarian, Patricia & Meenakshisundaram, Ravikumar, 1999. "Beyond Tele-Substitution: Disaggregate Longitudinal Structural Equations Modeling of Communication Impacts," Institute of Transportation Studies, Working Paper Series qt4hg365gh, Institute of Transportation Studies, UC Davis.
    8. Wu, Guoqiang & Hong, Jinhyun & Thakuriah, Piyushimita, 2019. "Assessing the relationships between young adults’ travel and use of the internet over time," Transportation Research Part A: Policy and Practice, Elsevier, vol. 125(C), pages 8-19.
    9. Robert Schlich & Kay Axhausen, 2003. "Habitual travel behaviour: Evidence from a six-week travel diary," Transportation, Springer, vol. 30(1), pages 13-36, February.
    10. Woo, JongRoul & Choi, Jae Young & Shin, Jungwoo & Lee, Jongsu, 2014. "The effect of new media on consumer media usage: An empirical study in South Korea," Technological Forecasting and Social Change, Elsevier, vol. 89(C), pages 3-11.
    11. Charles Raux & Tai-Yu Ma & Eric Cornelis, 2016. "Variability in daily activity-travel patterns: the case of a one-week travel diary," Post-Print halshs-01389479, HAL.
    12. Marianne Bertrand & Esther Duflo & Sendhil Mullainathan, 2004. "How Much Should We Trust Differences-In-Differences Estimates?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 119(1), pages 249-275.
    13. Erika Spissu & Abdul Pinjari & Chandra Bhat & Ram Pendyala & Kay Axhausen, 2009. "An analysis of weekly out-of-home discretionary activity participation and time-use behavior," Transportation, Springer, vol. 36(5), pages 483-510, September.
    14. Bhat, Chandra R., 2008. "The multiple discrete-continuous extreme value (MDCEV) model: Role of utility function parameters, identification considerations, and model extensions," Transportation Research Part B: Methodological, Elsevier, vol. 42(3), pages 274-303, March.
    15. Chandra Bhat & Rajul Misra, 1999. "Discretionary activity time allocation of individuals between in-home and out-of-home and between weekdays and weekends," Transportation, Springer, vol. 26(2), pages 193-229, May.
    16. Bhat, Chandra R., 2005. "A multiple discrete-continuous extreme value model: formulation and application to discretionary time-use decisions," Transportation Research Part B: Methodological, Elsevier, vol. 39(8), pages 679-707, September.
    17. Alberto Abadie, 2005. "Semiparametric Difference-in-Differences Estimators," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(1), pages 1-19.
    18. Sivaramakrishnan Srinivasan & Chandra Bhat, 2005. "Modeling household interactions in daily in-home and out-of-home maintenance activity participation," Transportation, Springer, vol. 32(5), pages 523-544, September.
    19. Pinjari, Abdul Rawoof, 2011. "Generalized extreme value (GEV)-based error structures for multiple discrete-continuous choice models," Transportation Research Part B: Methodological, Elsevier, vol. 45(3), pages 474-489, March.
    20. Donggen Wang & Fion Law, 2007. "Impacts of Information and Communication Technologies (ICT) on time use and travel behavior: a structural equations analysis," Transportation, Springer, vol. 34(4), pages 513-527, July.
    21. Choo, Sangho & Mokhtarian, Patricia L., 2007. "Telecommunications and travel demand and supply: Aggregate structural equation models for the US," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(1), pages 4-18, January.
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    1. Wang, Jiangquan & Ma, Xiaowei & Zhang, Jun & Zhao, Xin, 2022. "Impacts of digital technology on energy sustainability: China case study," Applied Energy, Elsevier, vol. 323(C).

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