IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i6p3169-d516512.html
   My bibliography  Save this article

Mobility Need-Adaptive Housing Platforms: The Benefit of a Commute Time Search Feature

Author

Listed:
  • Tim-Benjamin Lembcke

    (Chair of Information Management, University of Goettingen, 37073 Göttingen, Germany)

  • Mathias Willnat

    (Chair of Information Management, University of Goettingen, 37073 Göttingen, Germany)

  • Henrik Lechte

    (Chair of Information Management, University of Goettingen, 37073 Göttingen, Germany)

  • Maike Greve

    (Chair of Information Management, University of Goettingen, 37073 Göttingen, Germany)

  • Julia Heinsohn

    (Chair of Information Management, University of Goettingen, 37073 Göttingen, Germany)

  • Alfred Benedikt Brendel

    (Chair of Business Informatics, esp. Intelligent Systems and Services, Technische Universität Dresden, 01169 Dresden, Germany)

Abstract

The growing influx of people to urban areas has resulted in a tense housing market in many places, making the search for a suitable residence an increased challenge. Dedicated online platforms facilitate this process and offer two distinct approaches to find suitable accommodations concerning its location. Traditionally, users can search for a general area like a city to narrow down the results displayed. Additionally, some platforms offer searches based on the maximum commute time between apartments and points of interest. This paper investigates the benefit such approaches yield concerning technology acceptance and the fit of the task and information representation. Thus, a prototypically implemented online platform with and without a commute time search feature was evaluated in an online experiment. The treatment specification achieved significantly better results in terms of information quality and technology acceptance, implicating that such a design should be preferred for websites that facilitate the search for apartments. These insights can contribute to an enhanced understanding of visual system design to reduce the negative sustainability impacts of traffic induced by a divergence of residential and workplaces.

Suggested Citation

  • Tim-Benjamin Lembcke & Mathias Willnat & Henrik Lechte & Maike Greve & Julia Heinsohn & Alfred Benedikt Brendel, 2021. "Mobility Need-Adaptive Housing Platforms: The Benefit of a Commute Time Search Feature," Sustainability, MDPI, vol. 13(6), pages 1-14, March.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:6:p:3169-:d:516512
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/6/3169/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/13/6/3169/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Catalina Georgiana PICU & Alina DINU, 2016. "Research on the Current Telecommuting Trends in United States and European Union Markets," Management and Economics Review, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 1(2), pages 194-202, December.
    2. Albert Saiz, 2010. "The Geographic Determinants of Housing Supply," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 125(3), pages 1253-1296.
    3. Charness, Gary & Gneezy, Uri & Kuhn, Michael A., 2012. "Experimental methods: Between-subject and within-subject design," Journal of Economic Behavior & Organization, Elsevier, vol. 81(1), pages 1-8.
    4. Ye, Runing & De Vos, Jonas & Ma, Liang, 2020. "Analysing the association of dissonance between actual and ideal commute time and commute satisfaction," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 47-60.
    5. Achim Ahrens & Sean Lyons, 2021. "Do rising rents lead to longer commutes? A gravity model of commuting flows in Ireland," Urban Studies, Urban Studies Journal Limited, vol. 58(2), pages 264-279, February.
    6. Patricia L Mokhtarian & Gustavo O Collantes & Carsten Gertz, 2004. "Telecommuting, Residential Location, and Commute-Distance Traveled: Evidence from State of California Employees," Environment and Planning A, , vol. 36(10), pages 1877-1897, October.
    7. Edward Glaeser & Joseph Gyourko, 2018. "The Economic Implications of Housing Supply," Journal of Economic Perspectives, American Economic Association, vol. 32(1), pages 3-30, Winter.
    8. Kory Kroft & Devin G. Pope, 2014. "Does Online Search Crowd Out Traditional Search and Improve Matching Efficiency? Evidence from Craigslist," Journal of Labor Economics, University of Chicago Press, vol. 32(2), pages 259-303.
    9. Ioannides, Yannis M. & Zabel, Jeffrey E., 2008. "Interactions, neighborhood selection and housing demand," Journal of Urban Economics, Elsevier, vol. 63(1), pages 229-252, January.
    10. Lorenz, Olga, 2018. "Does commuting matter to subjective well-being?," Journal of Transport Geography, Elsevier, vol. 66(C), pages 180-199.
    11. Ettema, Dick, 2010. "The impact of telecommuting on residential relocation and residential preferences: A latent class modelling approach," The Journal of Transport and Land Use, Center for Transportation Studies, University of Minnesota, vol. 3(1), pages 7-24.
    12. Rashidi, Taha Hossein & Auld, Joshua & Mohammadian, Abolfazl (Kouros), 2012. "A behavioral housing search model: Two-stage hazard-based and multinomial logit approach to choice-set formation and location selection," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(7), pages 1097-1107.
    13. Plaut, Pnina O., 2006. "The intra-household choices regarding commuting and housing," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(7), pages 561-571, August.
    14. Kobus, Martijn B.W. & Van Ommeren, Jos N. & Rietveld, Piet, 2015. "Student commute time, university presence and academic achievement," Regional Science and Urban Economics, Elsevier, vol. 52(C), pages 129-140.
    15. Balbontin, C. & Ortúzar, J. de D. & Swait, J.D., 2015. "A joint best–worst scaling and stated choice model considering observed and unobserved heterogeneity: An application to residential location choice," Journal of choice modelling, Elsevier, vol. 16(C), pages 1-14.
    16. Huihui Wang & Weihua Zeng, 2019. "Revealing Urban Carbon Dioxide (CO 2 ) Emission Characteristics and Influencing Mechanisms from the Perspective of Commuting," Sustainability, MDPI, vol. 11(2), pages 1-22, January.
    17. William H. DeLone & Ephraim R. McLean, 1992. "Information Systems Success: The Quest for the Dependent Variable," Information Systems Research, INFORMS, vol. 3(1), pages 60-95, March.
    18. Lawrence Frank & Mark Bradley & Sarah Kavage & James Chapman & T. Lawton, 2008. "Urban form, travel time, and cost relationships with tour complexity and mode choice," Transportation, Springer, vol. 35(1), pages 37-54, January.
    19. Fahim Ullah & Samad M. E. Sepasgozar & Changxin Wang, 2018. "A Systematic Review of Smart Real Estate Technology: Drivers of, and Barriers to, the Use of Digital Disruptive Technologies and Online Platforms," Sustainability, MDPI, vol. 10(9), pages 1-44, September.
    20. Zhao, Pengjun & Lü, Bin & Roo, Gert de, 2011. "Impact of the jobs-housing balance on urban commuting in Beijing in the transformation era," Journal of Transport Geography, Elsevier, vol. 19(1), pages 59-69.
    21. Vicki McKinney & Kanghyun Yoon & Fatemeh “Mariam” Zahedi, 2002. "The Measurement of Web-Customer Satisfaction: An Expectation and Disconfirmation Approach," Information Systems Research, INFORMS, vol. 13(3), pages 296-315, September.
    22. Mokhtarian, Patricia L. & Chen, Cynthia, 2004. "TTB or not TTB, that is the question: a review and analysis of the empirical literature on travel time (and money) budgets," Transportation Research Part A: Policy and Practice, Elsevier, vol. 38(9-10), pages 643-675.
    23. Gabriela Inchauste & Jonathan Karver & Yeon Soo Kim & Mohamed Abdel Jelil, 2018. "Living and Leaving," World Bank Publications - Reports 30898, The World Bank Group.
    24. Viswanath Venkatesh & Fred D. Davis, 2000. "A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies," Management Science, INFORMS, vol. 46(2), pages 186-204, February.
    25. Tiziana Campisi & Nurten Akgün & Dario Ticali & Giovanni Tesoriere, 2020. "Exploring Public Opinion on Personal Mobility Vehicle Use: A Case Study in Palermo, Italy," Sustainability, MDPI, vol. 12(13), pages 1-15, July.
    26. Iris Vessey & Dennis Galletta, 1991. "Cognitive Fit: An Empirical Study of Information Acquisition," Information Systems Research, INFORMS, vol. 2(1), pages 63-84, March.
    27. Alan R. Dennis & Traci A. Carte, 1998. "Using Geographical Information Systems for Decision Making: Extending Cognitive Fit Theory to Map-Based Presentations," Information Systems Research, INFORMS, vol. 9(2), pages 194-203, June.
    28. Richard J. Dunning & Andrew Grayson, 2014. "Homebuyers and the representation of spatial markets by information providers," International Journal of Housing Markets and Analysis, Emerald Group Publishing Limited, vol. 7(3), pages 292-306, July.
    Full references (including those not matched with items on IDEAS)

    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. Brown, Susan A. & Venkatesh, Viswanath & Kuruzovich, Jason & Massey, Anne P., 2008. "Expectation confirmation: An examination of three competing models," Organizational Behavior and Human Decision Processes, Elsevier, vol. 105(1), pages 52-66, January.
    2. Matthias Gräuler & Michael Freundlieb & Kerstin Ortwerth & Frank Teuteberg, 2013. "Understanding the beliefs, actions and outcomes of sustainability reporting: An experimental approach," Information Systems Frontiers, Springer, vol. 15(5), pages 779-797, November.
    3. Zhen Wang & John Lim & Xiaojia Guo, 2010. "Negotiator Satisfaction in NSS-Facilitated Negotiation," Group Decision and Negotiation, Springer, vol. 19(3), pages 279-300, May.
    4. Kwahk, Kee-Young & Ahn, Hyunchul & Ryu, Young U., 2018. "Understanding mandatory IS use behavior: How outcome expectations affect conative IS use," International Journal of Information Management, Elsevier, vol. 38(1), pages 64-76.
    5. Wen-Lung Shiau & Yogesh K. Dwivedi, 2013. "Citation and co-citation analysis to identify core and emerging knowledge in electronic commerce research," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(3), pages 1317-1337, March.
    6. Gudigantala, Naveen & Song, Jaeki & Jones, Donald, 2011. "User satisfaction with Web-based DSS: The role of cognitive antecedents," International Journal of Information Management, Elsevier, vol. 31(4), pages 327-338.
    7. Johannes Gettinger & Sabine T. Koeszegi, 2014. "Far from Eye, Far from Heart: Analysis of Graphical Decision Aids in Electronic Negotiation Support," Group Decision and Negotiation, Springer, vol. 23(4), pages 787-817, July.
    8. Premkumar, G. & Bhattacherjee, Anol, 2008. "Explaining information technology usage: A test of competing models," Omega, Elsevier, vol. 36(1), pages 64-75, February.
    9. Zhao, Pengjun & Cao, Yushu, 2020. "Commuting inequity and its determinants in Shanghai: New findings from big-data analytics," Transport Policy, Elsevier, vol. 92(C), pages 20-37.
    10. Philippe Cohard, 2020. "Information Systems Values: A Study of the Intranet in Three French Higher Education Institutions," Post-Print hal-02987225, HAL.
    11. Pengyu Zhu, 2013. "Telecommuting, Household Commute and Location Choice," Urban Studies, Urban Studies Journal Limited, vol. 50(12), pages 2441-2459, September.
    12. Tsung Teng Chen, 2012. "The development and empirical study of a literature review aiding system," Scientometrics, Springer;Akadémiai Kiadó, vol. 92(1), pages 105-116, July.
    13. Abdesamad Zouine & Pierre Fenies, 2014. "The Critical Success Factors Of The ERP System Project: A Meta-Analysis Methodology," Post-Print hal-01419785, HAL.
    14. Nicholas Kacher & Luke Petach, 2021. "Boon or Burden? Evaluating the Competing Effects of House-Price Shocks on Regional Entrepreneurship," Economic Development Quarterly, , vol. 35(4), pages 287-304, November.
    15. Proserpio, Luigi & Magni, Massimo, 2012. "Teaching without the teacher? Building a learning environment through computer simulations," International Journal of Information Management, Elsevier, vol. 32(2), pages 99-105.
    16. Sharma, Mahak & Antony, Rose & Sehrawat, Rajat & Cruz, Angel Contreras & Daim, Tugrul U., 2022. "Exploring post-adoption behaviors of e-service users: Evidence from the hospitality sector /online travel services," Technology in Society, Elsevier, vol. 68(C).
    17. Chen-Yuan Chen & Bih-Yaw Shih & Shih-Hsien Yu, 2012. "Disaster prevention and reduction for exploring teachers’ technology acceptance using a virtual reality system and partial least squares techniques," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 62(3), pages 1217-1231, July.
    18. Charles Ka Yui Leung & Joe Cho Yiu Ng & Edward Tang, 2020. "Why is the Hong Kong Housing Market Unaffordable? Some Stylized Facts and Estimations," Globalization Institute Working Papers 380, Federal Reserve Bank of Dallas.
    19. Christian A. L. Hilber, 2019. "Immobilienpreise und Immobilienzyklen und die Rolle von Angebotsbeschränkungen [The impact of local supply constraints on house prices and price dynamics]," Zeitschrift für Immobilienökonomie (German Journal of Real Estate Research), Springer;Gesellschaft für Immobilienwirtschaftliche Forschung e. V., vol. 5(1), pages 37-65, November.
    20. Gyourko, Joe & Krimmel, Jacob, 2021. "The impact of local residential land use restrictions on land values across and within single family housing markets," Journal of Urban Economics, Elsevier, vol. 126(C).

    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:gam:jsusta:v:13:y:2021:i:6:p:3169-:d:516512. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.