IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i20p15008-d1262167.html
   My bibliography  Save this article

Disaggregate Modelling for Estimating Location Choice of Safe and Secure Truck Parking Areas: A Case Study

Author

Listed:
  • Marina Kouta

    (Department of Civil Engineering, University of Patras, Rio, 26500 Patras, Greece)

  • Yorgos Stephanedes

    (Department of Civil Engineering, University of Patras, Rio, 26500 Patras, Greece)

Abstract

Responding to the increasing need for safety and security in road freight transport, and to targeted legislation specifying the availability of freight drivers’ rest areas, this paper proposes a plan and a model for deployment of safe and secure parking areas for truck drivers. Disaggregate analysis within a stated preference and conjoint analysis framework leads to the modelling of truck parking area selection by each truck driver that registers in the system proposed in this research. The concept builds upon the Cooperative Intelligent Transport Systems (C-ITS) upgrading of the Trans-European Transport Network (TEN-T) infrastructure systems while adapting to novel transport and logistics needs in an operationally safe, secure, and efficient environment for the supply chain. The analysis is applied in the Orient/East-Med Corridor of the TEN-T and is supported by the clustering of available truck parking areas for each truck route in the application subnetwork. The personalised approach is scalable and can be integrated into platforms for safe and secure truck parking areas, thus facilitating their acceptance and increasing awareness by the end-users. From pilot implementation on the Hellenic motorways, functional evaluation of use cases indicates 94.4% estimated choice probability of the most suitable parking area by the pilot drivers.

Suggested Citation

  • Marina Kouta & Yorgos Stephanedes, 2023. "Disaggregate Modelling for Estimating Location Choice of Safe and Secure Truck Parking Areas: A Case Study," Sustainability, MDPI, vol. 15(20), pages 1-20, October.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:20:p:15008-:d:1262167
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/20/15008/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/20/15008/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Theo Arentze & Tao Feng & Harry Timmermans & Jops Robroeks, 2012. "Context-dependent influence of road attributes and pricing policies on route choice behavior of truck drivers: results of a conjoint choice experiment," Transportation, Springer, vol. 39(6), pages 1173-1188, November.
    2. Urciuoli, Luca, 2016. "What are the causes of transport insecurity? Results from a survey with transport operators," Transport Policy, Elsevier, vol. 47(C), pages 189-202.
    3. Papadima, Georgia & Genitsaris, Evangelos & Karagiotas, Ioannis & Naniopoulos, Aristotelis & Nalmpantis, Dimitrios, 2020. "Investigation of acceptance of driverless buses in the city of Trikala and optimization of the service using Conjoint Analysis," Utilities Policy, Elsevier, vol. 62(C).
    4. Vital, Filipe & Ioannou, Petros, 2021. "Scheduling and shortest path for trucks with working hours and parking availability constraints," Transportation Research Part B: Methodological, Elsevier, vol. 148(C), pages 1-37.
    5. Pilz, Danny & Schwerdfeger, Stefan & Boysen, Nils, 2022. "Make or break: Coordinated assignment of parking space for breaks and rest periods in long-haul trucking," Transportation Research Part B: Methodological, Elsevier, vol. 164(C), pages 45-64.
    6. Hajime Seya & Junyi Zhang & Makoto Chikaraishi & Ying Jiang, 2020. "Decisions on truck parking place and time on expressways: an analysis using digital tachograph data," Transportation, Springer, vol. 47(2), pages 555-583, April.
    7. Hainmueller, Jens & Hopkins, Daniel J. & Yamamoto, Teppei, 2014. "Causal Inference in Conjoint Analysis: Understanding Multidimensional Choices via Stated Preference Experiments," Political Analysis, Cambridge University Press, vol. 22(1), pages 1-30, January.
    8. Green, Paul E & Srinivasan, V, 1978. "Conjoint Analysis in Consumer Research: Issues and Outlook," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 5(2), pages 103-123, Se.
    9. Nagurney, Anna & Shukla, Shivani & Nagurney, Ladimer S. & Saberi, Sara, 2018. "A game theory model for freight service provision security investments for high-value cargo," Economics of Transportation, Elsevier, vol. 16(C), pages 21-28.
    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. Ohlwein, Martin, 2022. "Same but different - The effect of the unit of measure on the valuation of a unit price," Journal of Retailing and Consumer Services, Elsevier, vol. 66(C).
    2. Fa Wang & Haifeng Wang & Joung Hyung Cho, 2022. "Consumer Preference for Yogurt Packaging Design Using Conjoint Analysis," Sustainability, MDPI, vol. 14(6), pages 1-13, March.
    3. Tsusaka, T. & Orr, A. & Msere, H. & Harris, D. & Rao, N. Vpr Ganga, 2018. "Fuelwood or Grain? A Conjoint Analysis of Trait Preferences for Pigeonpea among Smallholders in Southern Malawi," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277435, International Association of Agricultural Economists.
    4. Kao, Kristen & Lust, Ellen & Rakner, Lise, 2022. "Vote-buying, anti-corruption campaigns, and identity in African elections," World Development, Elsevier, vol. 160(C).
    5. Winfried Steiner & Harald Hruschka, 2002. "A Probabilistic One-Step Approach to the Optimal Product Line Design Problem Using Conjoint and Cost Data," Review of Marketing Science Working Papers 1-4-1003, Berkeley Electronic Press.
    6. Merja Halme & Kari Linden & Kimmo Kääriä, 2009. "Patients’ Preferences for Generic and Branded Over-the-Counter Medicines," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 2(4), pages 243-255, December.
    7. Chaikaew, Pasicha & Hodges, Alan W. & Grunwald, Sabine, 2017. "Estimating the value of ecosystem services in a mixed-use watershed: A choice experiment approach," Ecosystem Services, Elsevier, vol. 23(C), pages 228-237.
    8. Dufhues, T. & Buchenrieder, G., 2004. "Der Beitrag der Conjoint Analyse zur nachfrageorintierten Entwicklung des ländlichen Finanzsektors in Vietnam," Proceedings “Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V.”, German Association of Agricultural Economists (GEWISOLA), vol. 39.
    9. Martinovici, A., 2019. "Revealing attention - how eye movements predict brand choice and moment of choice," Other publications TiSEM 7dca38a5-9f78-4aee-bd81-c, Tilburg University, School of Economics and Management.
    10. James Agarwal & Wayne DeSarbo & Naresh K. Malhotra & Vithala Rao, 2015. "An Interdisciplinary Review of Research in Conjoint Analysis: Recent Developments and Directions for Future Research," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 2(1), pages 19-40, March.
    11. Mahesh Balan U & Saji K. Mathew, 2021. "Personalize, Summarize or Let them Read? A Study on Online Word of Mouth Strategies and Consumer Decision Process," Information Systems Frontiers, Springer, vol. 23(3), pages 627-647, June.
    12. Shin, Jungwoo & Hwang, Won-Sik, 2017. "Consumer preference and willingness to pay for a renewable fuel standard (RFS) policy: Focusing on ex-ante market analysis and segmentation," Energy Policy, Elsevier, vol. 106(C), pages 32-40.
    13. Haaijer, Marinus E., 1996. "Predictions in conjoint choice experiments : the x-factor probit model," Research Report 96B22, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
    14. Ha, Jinkyung, 2018. "Consumer valuation of Fintech: The case of Mobile Payment in Korea," 22nd ITS Biennial Conference, Seoul 2018. Beyond the boundaries: Challenges for business, policy and society 190341, International Telecommunications Society (ITS).
    15. P. A. Ferrari & S. Salini, 2008. "Measuring Service Quality: The Opinion of Europeans about Utilities," Working Papers 2008.36, Fondazione Eni Enrico Mattei.
    16. Steinhorst, M.P. & Bahrs, E., 2013. "Renditansprüche im Kontext gleichmäßiger Rückflüsse – Ergebnisse eines Experiments mit Stakeholdern des Agribusiness," Proceedings “Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V.”, German Association of Agricultural Economists (GEWISOLA), vol. 48, March.
    17. Yavuz Taşcıoğlu & Mevlüt Gül & Metin Göksel Akpınar & Bahri Karlı & Bektaş Kadakoğlu & Bekir Sıtkı Şirikçi & Musa Acar & Hilal Yılmaz, 2023. "Optimum Support Policy Component for the Development of Agricultural Production: Potato Producer," Agriculture, MDPI, vol. 13(5), pages 1-13, April.
    18. Luisa Menapace & Gregory Colson & Carola Grebitus & Maria Facendola, 2011. "Consumers' preferences for geographical origin labels: evidence from the Canadian olive oil market," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 38(2), pages 193-212, June.
    19. Henrik Serup Christensen & Lauri Rapeli, 2021. "Immediate rewards or delayed gratification? A conjoint survey experiment of the public’s policy preferences," Policy Sciences, Springer;Society of Policy Sciences, vol. 54(1), pages 63-94, March.
    20. Srinivasan, V. Seenu & Netzer, Oded, 2007. "Adaptive Self-Explication of Multi-attribute Preferences," Research Papers 1979, Stanford University, Graduate School of Business.

    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:15:y:2023:i:20:p:15008-:d:1262167. 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.