IDEAS home Printed from https://ideas.repec.org/a/kap/transp/v49y2022i1d10.1007_s11116-021-10174-8.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11116-021-10174-8
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s11116-021-10174-8?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    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., 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.
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    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).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wu, Guoqiang & Hong, Jinhyun, 2022. "An analysis of the role of residential location on the relationships between time spent online and non-mandatory activity-travel time use over time," Journal of Transport Geography, Elsevier, vol. 102(C).
    2. Rodrigo J. Tapia & Gerard Jong & Ana M. Larranaga & Helena B. Bettella Cybis, 2021. "Exploring Multiple‐discreteness in Freight Transport. A Multiple Discrete Extreme Value Model Application for Grain Consolidators in Argentina," Networks and Spatial Economics, Springer, vol. 21(3), pages 581-608, September.
    3. Bhat, Chandra R. & Mondal, Aupal & Asmussen, Katherine E. & Bhat, Aarti C., 2020. "A multiple discrete extreme value choice model with grouped consumption data and unobserved budgets," Transportation Research Part B: Methodological, Elsevier, vol. 141(C), pages 196-222.
    4. Jian, Sisi & Rashidi, Taha Hossein & Dixit, Vinayak, 2017. "An analysis of carsharing vehicle choice and utilization patterns using multiple discrete-continuous extreme value (MDCEV) models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 103(C), pages 362-376.
    5. Sikder, Sujan & Pinjari, Abdul Rawoof, 2013. "The benefits of allowing heteroscedastic stochastic distributions in multiple discrete-continuous choice models," Journal of choice modelling, Elsevier, vol. 9(C), pages 39-56.
    6. Acharya, Bikram & Marhold, Klaus, 2019. "Determinants of household energy use and fuel switching behavior in Nepal," Energy, Elsevier, vol. 169(C), pages 1132-1138.
    7. Abdul Rawoof Pinjari & Chandra R. Bhat, 2011. "Activity-based Travel Demand Analysis," Chapters, in: André de Palma & Robin Lindsey & Emile Quinet & Roger Vickerman (ed.), A Handbook of Transport Economics, chapter 10, Edward Elgar Publishing.
    8. Tapia, Rodrigo J. & de Jong, Gerard & Larranaga, Ana M. & Bettella Cybis, Helena B., 2020. "Application of MDCEV to infrastructure planning in regional freight transport," Transportation Research Part A: Policy and Practice, Elsevier, vol. 133(C), pages 255-271.
    9. Palma, David & Hess, Stephane, 2022. "Extending the Multiple Discrete Continuous (MDC) modelling framework to consider complementarity, substitution, and an unobserved budget," Transportation Research Part B: Methodological, Elsevier, vol. 161(C), pages 13-35.
    10. Sobhani, Anae & Eluru, Naveen & Faghih-Imani, Ahmadreza, 2013. "A latent segmentation based multiple discrete continuous extreme value model," Transportation Research Part B: Methodological, Elsevier, vol. 58(C), pages 154-169.
    11. Pellegrini, Andrea & Pinjari, Abdul Rawoof & Maggi, Rico, 2021. "A multiple discrete continuous model of time use that accommodates non-additively separable utility functions along with time and monetary budget constraints," Transportation Research Part A: Policy and Practice, Elsevier, vol. 144(C), pages 37-53.
    12. Shasha Liu & Toshiyuki Yamamoto & Enjian Yao, 2023. "Joint modeling of mode choice and travel distance with intra-household interactions," Transportation, Springer, vol. 50(5), pages 1527-1552, October.
    13. Saxena, Shobhit & Pinjari, Abdul Rawoof & Paleti, Rajesh, 2022. "A multiple discrete-continuous extreme value model with ordered preferences (MDCEV-OP): Modelling framework for episode-level activity participation and time-use analysis," Transportation Research Part B: Methodological, Elsevier, vol. 166(C), pages 259-283.
    14. Calastri, Chiara & Giergiczny, Marek & Zedrosser, Andreas & Hess, Stephane, 2023. "Modelling activity patterns of wild animals - An application of the multiple discrete-continuous extreme value (MDCEV) model," Journal of choice modelling, Elsevier, vol. 47(C).
    15. Hanemann, Michael & Labandeira, Xavier & Labeaga, José M. & Vásquez-Lavín, Felipe, 2024. "Discrete-continuous models of residential energy demand: A comprehensive review," Resource and Energy Economics, Elsevier, vol. 77(C).
    16. Pawlak, Jacek & Polak, John W. & Sivakumar, Aruna, 2015. "Towards a microeconomic framework for modelling the joint choice of activity–travel behaviour and ICT use," Transportation Research Part A: Policy and Practice, Elsevier, vol. 76(C), pages 92-112.
    17. Pinjari, Abdul Rawoof & Augustin, Bertho & Sivaraman, Vijayaraghavan & Faghih Imani, Ahmadreza & Eluru, Naveen & Pendyala, Ram M., 2016. "Stochastic frontier estimation of budgets for Kuhn–Tucker demand systems: Application to activity time-use analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 88(C), pages 117-133.
    18. Bhat, Chandra R., 2018. "A new flexible multiple discrete–continuous extreme value (MDCEV) choice model," Transportation Research Part B: Methodological, Elsevier, vol. 110(C), pages 261-279.
    19. Sabreena Anowar & Naveen Eluru & Luis F. Miranda-Moreno, 2014. "Alternative Modeling Approaches Used for Examining Automobile Ownership: A Comprehensive Review," Transport Reviews, Taylor & Francis Journals, vol. 34(4), pages 441-473, July.
    20. La Paix Puello, Lissy & Chowdhury, Saidul & Geurs, Karst, 2019. "Using panel data for modelling duration dynamics of outdoor leisure activities," Journal of choice modelling, Elsevier, vol. 31(C), pages 141-155.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:kap:transp:v:49:y:2022:i:1:d:10.1007_s11116-021-10174-8. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.