IDEAS home Printed from https://ideas.repec.org/a/eee/transa/v160y2022icp1-20.html
   My bibliography  Save this article

Shippers’ willingness to use flexible transportation services

Author

Listed:
  • Khakdaman, Masoud
  • Rezaei, Jafar
  • Tavasszy, Lóránt

Abstract

Factors driving the choice of shipper firms for services of logistics service providers have long been recognized in the freight transportation literature. However, the willingness among shippers to choose flexible transportation services, where the service package can be adapted during planning and execution, has received less attention. In particular, little is known about the contextual circumstances under which shippers would be inclined to select such flexible transportation service. In this study, experimental scenarios and discrete choice modeling are used to investigate the willingness among shippers to use flexible transportation services. We estimate multinomial logit, mixed logit, and latent class models for a sample of nearly 200 global shipper firms and calculate willingness-to-pay measures for flexibility. The findings indicate that flexible services are essential in demand-volatile markets. Since logistics services may provide external flexibility for shipper firms, we also study which related internal flexibilities in supply chains drive these choices. In particular, our findings show that it is mainly the volume flexibility of shippers that mediates the choice of flexible transportation services.

Suggested Citation

  • Khakdaman, Masoud & Rezaei, Jafar & Tavasszy, Lóránt, 2022. "Shippers’ willingness to use flexible transportation services," Transportation Research Part A: Policy and Practice, Elsevier, vol. 160(C), pages 1-20.
  • Handle: RePEc:eee:transa:v:160:y:2022:i:c:p:1-20
    DOI: 10.1016/j.tra.2022.03.031
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0965856422000866
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.tra.2022.03.031?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. O. Norojono & W. Young, 2003. "A Stated preference freight mode choice model," Transportation Planning and Technology, Taylor & Francis Journals, vol. 26(2), pages 1-1, April.
    2. Simona Bolis & Rico Maggi, 2003. "Logistics Strategy and Transport Service Choices: An Adaptive Stated Preference Experiment," Growth and Change, Wiley Blackwell, vol. 34(4), pages 490-504, September.
    3. Xinyu (Jason) Cao & Patricia L. Mokhtarian & Susan L. Handy, 2008. "Examining the Impacts of Residential Self‐Selection on Travel Behaviour: A Focus on Empirical Findings," Transport Reviews, Taylor & Francis Journals, vol. 29(3), pages 359-395, October.
    4. Purvis, Laura & Gosling, Jonathan & Naim, Mohamed M., 2014. "The development of a lean, agile and leagile supply network taxonomy based on differing types of flexibility," International Journal of Production Economics, Elsevier, vol. 151(C), pages 100-111.
    5. Mokhtarian, Patricia L. & Cao, Xinyu, 2008. "Examining the impacts of residential self-selection on travel behavior: A focus on methodologies," Transportation Research Part B: Methodological, Elsevier, vol. 42(3), pages 204-228, March.
    6. Roso, Violeta & Woxenius, Johan & Lumsden, Kenth, 2009. "The dry port concept: connecting container seaports with the hinterland," Journal of Transport Geography, Elsevier, vol. 17(5), pages 338-345.
    7. Hamid Jafari, 2015. "Logistics flexibility: a systematic review," International Journal of Productivity and Performance Management, Emerald Group Publishing Limited, vol. 64(7), pages 947-970, September.
    8. van Donk, Dirk Pieter & van der Vaart, Taco, 2005. "A case of shared resources, uncertainty and supply chain integration in the process industry," International Journal of Production Economics, Elsevier, vol. 96(1), pages 97-108, April.
    9. Arne Risa Hole, 2007. "A comparison of approaches to estimating confidence intervals for willingness to pay measures," Health Economics, John Wiley & Sons, Ltd., vol. 16(8), pages 827-840, August.
    10. Cao, Xinyu & Mokhtarian, Patricia & Handy, Susan, 2008. "Examining The Impacts of Residential Self-Selection on Travel Behavior: Methodologies and Empirical Findings," Institute of Transportation Studies, Working Paper Series qt08x1k476, Institute of Transportation Studies, UC Davis.
    11. I. Nyoman Pujawan, 2004. "Assessing supply chain flexibility: a conceptual framework and case study," International Journal of Integrated Supply Management, Inderscience Enterprises Ltd, vol. 1(1), pages 79-97.
    12. Lucia Rotaris & Romeo Danielis & Igor Sarman & Edoardo Marcucci, 2012. "Testing for nonlinearity in the choice of a freight transport service," European Transport \ Trasporti Europei, ISTIEE, Institute for the Study of Transport within the European Economic Integration, issue 50, pages 1-4.
    13. Masoud Khakdaman & Kuan Yew Wong & Bahareh Zohoori & Manoj Kumar Tiwari & Rico Merkert, 2015. "Tactical production planning in a hybrid Make-to-Stock–Make-to-Order environment under supply, process and demand uncertainties: a robust optimisation model," International Journal of Production Research, Taylor & Francis Journals, vol. 53(5), pages 1358-1386, March.
    14. Sreedevi, R. & Saranga, Haritha, 2017. "Uncertainty and supply chain risk: The moderating role of supply chain flexibility in risk mitigation," International Journal of Production Economics, Elsevier, vol. 193(C), pages 332-342.
    15. McFadden, Daniel, 1974. "The measurement of urban travel demand," Journal of Public Economics, Elsevier, vol. 3(4), pages 303-328, November.
    16. Danielis, Romeo & Marcucci, Edoardo, 2007. "Attribute cut-offs in freight service selection," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 43(5), pages 506-515, September.
    17. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387.
    18. Peter Boxall & Wiktor Adamowicz, 2002. "Understanding Heterogeneous Preferences in Random Utility Models: A Latent Class Approach," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 23(4), pages 421-446, December.
    19. Herrmann, Andreas & Huber, Frank & Braunstein, Christine, 2000. "Market-driven product and service design: Bridging the gap between customer needs, quality management, and customer satisfaction," International Journal of Production Economics, Elsevier, vol. 66(1), pages 77-96, June.
    20. Greene, William H. & Hensher, David A., 2003. "A latent class model for discrete choice analysis: contrasts with mixed logit," Transportation Research Part B: Methodological, Elsevier, vol. 37(8), pages 681-698, September.
    21. Chung, Walter W. C. & Yam, Anthony Y. K. & Chan, Michael F. S., 2004. "Networked enterprise: A new business model for global sourcing," International Journal of Production Economics, Elsevier, vol. 87(3), pages 267-280, February.
    22. Gatta, Valerio & Marcucci, Edoardo & Scaccia, Luisa, 2015. "On finite sample performance of confidence intervals methods for willingness to pay measures," Transportation Research Part A: Policy and Practice, Elsevier, vol. 82(C), pages 169-192.
    23. Arencibia, Ana Isabel & Feo-Valero, María & García-Menéndez, Leandro & Román, Concepción, 2015. "Modelling mode choice for freight transport using advanced choice experiments," Transportation Research Part A: Policy and Practice, Elsevier, vol. 75(C), pages 252-267.
    24. Reis, Vasco, 2014. "Analysis of mode choice variables in short-distance intermodal freight transport using an agent-based model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 61(C), pages 100-120.
    25. Khakdaman, Masoud & Rezaei, Jafar & Tavasszy, Lóránt A., 2020. "Shippers’ willingness to delegate modal control in freight transportation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 141(C).
    26. Joan Walker & Jieping Li, 2007. "Latent lifestyle preferences and household location decisions," Journal of Geographical Systems, Springer, vol. 9(1), pages 77-101, April.
    27. Chandra R. Bhat, 1997. "An Endogenous Segmentation Mode Choice Model with an Application to Intercity Travel," Transportation Science, INFORMS, vol. 31(1), pages 34-48, February.
    28. Tongzon, Jose L., 2009. "Port choice and freight forwarders," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 45(1), pages 186-195, January.
    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. Khakdaman, Masoud & Rezaei, Jafar & Tavasszy, Lóránt A., 2020. "Shippers’ willingness to delegate modal control in freight transportation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 141(C).
    2. Kim, Sung Hoo & Mokhtarian, Patricia L., 2018. "Taste heterogeneity as an alternative form of endogeneity bias: Investigating the attitude-moderated effects of built environment and socio-demographics on vehicle ownership using latent class modelin," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 130-150.
    3. Larranaga, Ana Margarita & Arellana, Julian & Senna, Luiz Afonso, 2017. "Encouraging intermodality: A stated preference analysis of freight mode choice in Rio Grande do Sul," Transportation Research Part A: Policy and Practice, Elsevier, vol. 102(C), pages 202-211.
    4. Chunjiao Shao & Haiyan Wang & Meng Yu, 2022. "Multi-Objective Optimization of Customer-Centered Intermodal Freight Routing Problem Based on the Combination of DRSA and NSGA-III," Sustainability, MDPI, vol. 14(5), pages 1-25, March.
    5. Vega, Amaya & Feo-Valero, Maria & Espino-Espino, Raquel, 2018. "The potential impact of Brexit on Ireland's demand for shipping services to continental Europe," Transport Policy, Elsevier, vol. 71(C), pages 1-13.
    6. Wen, Chieh-Hua & Wang, Wei-Chung & Fu, Chiang, 2012. "Latent class nested logit model for analyzing high-speed rail access mode choice," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(2), pages 545-554.
    7. Tang, Wei & Mokhtarian, Patricia L, 2009. "Accounting for Taste Heterogeneity in Purchase Channel Intention Modeling: An Example from Northern California for Book Purchases," Institute of Transportation Studies, Working Paper Series qt9mg5s5g8, Institute of Transportation Studies, UC Davis.
    8. Román, Concepción & Arencibia, Ana Isabel & Feo-Valero, María, 2017. "A latent class model with attribute cut-offs to analyze modal choice for freight transport," Transportation Research Part A: Policy and Practice, Elsevier, vol. 102(C), pages 212-227.
    9. Rombach, Meike & Widmar, Nicole Olynk & Byrd, Elizabeth & Bitsch, Vera, 2018. "Do all roses smell equally sweet? Willingness to pay for flower attributes in specialized retail settings by German consumers," Journal of Retailing and Consumer Services, Elsevier, vol. 40(C), pages 91-99.
    10. Hurtubia, Ricardo & Nguyen, My Hang & Glerum, Aurélie & Bierlaire, Michel, 2014. "Integrating psychometric indicators in latent class choice models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 64(C), pages 135-146.
    11. Kim, Sung Hoo & Mokhtarian, Patricia L., 2023. "Finite mixture (or latent class) modeling in transportation: Trends, usage, potential, and future directions," Transportation Research Part B: Methodological, Elsevier, vol. 172(C), pages 134-173.
    12. Shen, Qing & Chen, Peng & Pan, Haixiao, 2016. "Factors affecting car ownership and mode choice in rail transit-supported suburbs of a large Chinese city," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 31-44.
    13. Evangelinos, Christos & Tscharaktschiew, Stefan & Marcucci, Edoardo & Gatta, Valerio, 2018. "Pricing workplace parking via cash-out: Effects on modal choice and implications for transport policy," Transportation Research Part A: Policy and Practice, Elsevier, vol. 113(C), pages 369-380.
    14. Kurtuluş, Ercan & Çetin, İsmail Bilge, 2020. "Analysis of modal shift potential towards intermodal transportation in short-distance inland container transport," Transport Policy, Elsevier, vol. 89(C), pages 24-37.
    15. Feo-Valero, María & Arencibia, Ana Isabel & Román, Concepción, 2016. "Analyzing discrepancies between willingness to pay and willingness to accept for freight transport attributes," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 89(C), pages 151-164.
    16. Tinessa, Fiore & Marzano, Vittorio & Papola, Andrea, 2020. "Mixing distributions of tastes with a Combination of Nested Logit (CoNL) kernel: Formulation and performance analysis," Transportation Research Part B: Methodological, Elsevier, vol. 141(C), pages 1-23.
    17. Tran, Minh Tu & Zhang, Junyi & Chikaraishi, Makoto & Fujiwara, Akimasa, 2016. "A joint analysis of residential location, work location and commuting mode choices in Hanoi, Vietnam," Journal of Transport Geography, Elsevier, vol. 54(C), pages 181-193.
    18. Haghani, Milad & Bliemer, Michiel C.J. & Hensher, David A., 2021. "The landscape of econometric discrete choice modelling research," Journal of choice modelling, Elsevier, vol. 40(C).
    19. Sfeir, Georges & Abou-Zeid, Maya & Rodrigues, Filipe & Pereira, Francisco Camara & Kaysi, Isam, 2021. "Latent class choice model with a flexible class membership component: A mixture model approach," Journal of choice modelling, Elsevier, vol. 41(C).
    20. Yang Yang & Jill E. Hobbs & David C. Natcher, 2020. "The Arctic as a food producing region: Consumer perceptions and market segments," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 68(4), pages 387-410, December.

    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:160:y:2022:i:c:p:1-20. 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.