IDEAS home Printed from https://ideas.repec.org/a/eee/transa/v149y2021icp62-75.html
   My bibliography  Save this article

What determines the acceptance of socially optimal traffic coordination?: A scenario-based examination in Germany

Author

Listed:
  • Koller, Florian

Abstract

Social optimization emerged as a strategy for the attainment of more efficient road traffic (i.e., minimal total or average travel time). In order to achieve efficiency benefits, collective action is needed. A major challenge is that not every individual benefits equally from social optimization. Thus, a corresponding technological implementation (i.e., a social optimizing traveler information system (SOTIS)) is prone to rejection. The question remains as to which factors underlie the acceptance of such a system. Therefore a sample of 391 car drivers in Germany, stratified by kilometers driven per year, age and gender, completed a scenario-based questionnaire addressing attitudinal acceptance of a SOTIS.

Suggested Citation

  • Koller, Florian, 2021. "What determines the acceptance of socially optimal traffic coordination?: A scenario-based examination in Germany," Transportation Research Part A: Policy and Practice, Elsevier, vol. 149(C), pages 62-75.
    • Handle: RePEc:eee:transa:v:149:y:2021:i:c:p:62-75
    DOI: 10.1016/j.tra.2021.04.004
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0965856421001026
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tra.2021.04.004?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. Blake E. Ashforth & Kristie M. Rogers & Michael G. Pratt & Camille Pradies, 2014. "Ambivalence in Organizations: A Multilevel Approach," Organization Science, INFORMS, vol. 25(5), pages 1453-1478, October.
    2. Mariska van Essen & Tom Thomas & Eric van Berkum & Caspar Chorus, 2020. "Travelers’ compliance with social routing advice: evidence from SP and RP experiments," Transportation, Springer, vol. 47(3), pages 1047-1070, June.
    3. Charles Raux & Stéphanie Souche & Yves Croissant, 2009. "How fair is pricing perceived to be? An empirical study," Public Choice, Springer, vol. 139(1), pages 227-240, April.
    4. Levy, Nadav & Klein, Ido & Ben-Elia, Eran, 2018. "Emergence of cooperation and a fair system optimum in road networks: A game-theoretic and agent-based modelling approach," Research in Transportation Economics, Elsevier, vol. 68(C), pages 46-55.
    5. Jakobsson, C. & Fujii, S. & Gärling, T., 2000. "Determinants of private car users' acceptance of road pricing," Transport Policy, Elsevier, vol. 7(2), pages 153-158, April.
    6. Rosseel, Yves, 2012. "lavaan: An R Package for Structural Equation Modeling," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i02).
    7. Gary C. Moore & Izak Benbasat, 1991. "Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation," Information Systems Research, INFORMS, vol. 2(3), pages 192-222, September.
    8. Xuelong Li & Marko Jusup & Zhen Wang & Huijia Li & Lei Shi & Boris Podobnik & H. Eugene Stanley & Shlomo Havlin & Stefano Boccaletti, 2018. "Punishment diminishes the benefits of network reciprocity in social dilemma experiments," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 115(1), pages 30-35, January.
    9. El Bachir Diop & Shengchuan Zhao & Tran Van Duy, 2019. "An extension of the technology acceptance model for understanding travelers’ adoption of variable message signs," PLOS ONE, Public Library of Science, vol. 14(4), pages 1-17, April.
    10. Olaf Jahn & Rolf H. Möhring & Andreas S. Schulz & Nicolás E. Stier-Moses, 2005. "System-Optimal Routing of Traffic Flows with User Constraints in Networks with Congestion," Operations Research, INFORMS, vol. 53(4), pages 600-616, August.
    11. Dirk Helbing & Martin Schönhof & Hans-Ulrich Stark & Janusz A. Hołyst, 2005. "How Individuals Learn To Take Turns: Emergence Of Alternating Cooperation In A Congestion Game And The Prisoner'S Dilemma," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 8(01), pages 87-116.
    12. Cohen-Charash, Yochi & Spector, Paul E., 2001. "The Role of Justice in Organizations: A Meta-Analysis," Organizational Behavior and Human Decision Processes, Elsevier, vol. 86(2), pages 278-321, November.
    13. 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.
    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. Ioanna Roussou & Emmanouil Stiakakis & Angelo Sifaleras, 2019. "An empirical study on the commercial adoption of digital currencies," Information Systems and e-Business Management, Springer, vol. 17(2), pages 223-259, December.
    2. Morosan, Cristian, 2016. "An empirical examination of U.S. travelers’ intentions to use biometric e-gates in airports," Journal of Air Transport Management, Elsevier, vol. 55(C), pages 120-128.
    3. Sarv Devaraj & Robert F. Easley & J. Michael Crant, 2008. "Research Note ---How Does Personality Matter? Relating the Five-Factor Model to Technology Acceptance and Use," Information Systems Research, INFORMS, vol. 19(1), pages 93-105, March.
    4. Paul Juinn Bing Tan, 2013. "Applying the UTAUT to Understand Factors Affecting the Use of English E-Learning Websites in Taiwan," SAGE Open, , vol. 3(4), pages 21582440135, October.
    5. Schweizer, T.S., 2002. "Managing interactions between technological and stylistic innovation in the media industries, insights from the introduction of ebook technology in the publishing industry," ERIM Report Series Research in Management ERS-2002-16-ORG, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    6. Wang, Guoqiang & Tan, Garry Wei-Han & Yuan, Yunpeng & Ooi, Keng-Boon & Dwivedi, Yogesh K., 2022. "Revisiting TAM2 in behavioral targeting advertising: A deep learning-based dual-stage SEM-ANN analysis," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    7. Riffat Ara Zannat Tama & Md Mahmudul Hoque & Ying Liu & Mohammad Jahangir Alam & Mark Yu, 2023. "An Application of Partial Least Squares Structural Equation Modeling (PLS-SEM) to Examining Farmers’ Behavioral Attitude and Intention towards Conservation Agriculture in Bangladesh," Agriculture, MDPI, vol. 13(2), pages 1-22, February.
    8. Buvár Ágnes & Gáti Mirkó, 2023. "Digital marketing adoption of microenterprises in a technology acceptance approach," Management & Marketing, Sciendo, vol. 18(2), pages 127-144, June.
    9. Francisco Rejón-Guardia & Juán Sánchez-Fernández & Francisco Muñoz-Leiva, 2011. "Motivational Factors that influence the Acceptance of Microblogging Social Networks: The µBAM Model," FEG Working Paper Series 06/11, Faculty of Economics and Business (University of Granada).
    10. Milenković, Marina & Glavić, Draženko & Maričić, Milica, 2019. "Determining factors affecting congestion pricing acceptability," Transport Policy, Elsevier, vol. 82(C), pages 58-74.
    11. Siti Salwa Mohd Ishak & Sidney Newton, 2018. "Testing a Model of User Resistance Towards Technology Adoption in Construction Organizations," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 15(06), pages 1-27, December.
    12. Raouf Jaziri & Mohammad Miralam, 2019. "Modelling the crowdfunding technology adoption among novice entrepreneurs: an extended tam model," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 6(4), pages 2159-2179, June.
    13. Faqih, Khaled M.S., 2016. "An empirical analysis of factors predicting the behavioral intention to adopt Internet shopping technology among non-shoppers in a developing country context: Does gender matter?," Journal of Retailing and Consumer Services, Elsevier, vol. 30(C), pages 140-164.
    14. Sanjeev Verma, 2015. "Harnessing the Benefit of Social Networking Sites for Intentional Social Action: Determinants and Challenges," Vision, , vol. 19(2), pages 104-111, June.
    15. Queiroz, Maciel M. & Fosso Wamba, Samuel, 2019. "Blockchain adoption challenges in supply chain: An empirical investigation of the main drivers in India and the USA," International Journal of Information Management, Elsevier, vol. 46(C), pages 70-82.
    16. Sarv Devaraj & Ming Fan & Rajiv Kohli, 2002. "Antecedents of B2C Channel Satisfaction and Preference: Validating e-Commerce Metrics," Information Systems Research, INFORMS, vol. 13(3), pages 316-333, September.
    17. Li-Su Huang & Cheng-Po Lai, 2014. "Knowledge Management Adoption And Diffusion Using Structural Equation Modeling," Global Journal of Business Research, The Institute for Business and Finance Research, vol. 8(1), pages 39-56.
    18. Youngcheoul Kang & Nakbum Choi & Seoyong Kim, 2021. "Searching for New Model of Digital Informatics for Human–Computer Interaction: Testing the Institution-Based Technology Acceptance Model (ITAM)," IJERPH, MDPI, vol. 18(11), pages 1-36, May.
    19. Mohammadbashir Sedighi & Hamideh Parsaeiyan & Yashar Araghi, 2021. "An Empirical Study of Intention to Continue Using of Digital Ride-hailing Platforms," The Review of Socionetwork Strategies, Springer, vol. 15(2), pages 489-515, November.
    20. Gansser, Oliver Alexander & Reich, Christina Stefanie, 2021. "A new acceptance model for artificial intelligence with extensions to UTAUT2: An empirical study in three segments of application," Technology in Society, Elsevier, vol. 65(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:eee:transa:v:149:y:2021:i:c:p:62-75. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/547/description#description .

    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.