IDEAS home Printed from https://ideas.repec.org/a/eee/transa/v158y2022icp210-223.html
   My bibliography  Save this article

A public transport-based crowdshipping concept as a sustainable last-mile solution: Assessing user preferences with a stated choice experiment

Author

Listed:
  • Fessler, Andreas
  • Thorhauge, Mikkel
  • Mabit, Stefan
  • Haustein, Sonja

Abstract

In this study, we analyse user preferences for a public transport based crowdshipping concept, where users carry parcels along on their ride. The concept offers potential economic, environmental and social benefits over other last-mile solutions. We set up a stated choice experiment in which respondents indicate whether they would be willing to bring a parcel along on their ride, while varying the number of parcels, their size, weight, the compensation and required extra time. Based on data from 524 public transport passengers in the Greater Copenhagen Area, we estimate a mixed logit model and find all main effects to be significant. Our results indicate that young(er) individuals, students and (to a lesser extent) employed and self-employed individuals are more likely to participate in the crowdshipping concept, while old(er) individuals (60 + ) are less willing to participate. Our findings further show that the marginal disutility of time spent retrieving and dropping off parcels is higher for old(er) respondents and individuals with high(er) income, while it is lower for individuals with a short-term education. Finally, we find the value of time to be slightly higher than the official Danish value for waiting time but lower than the value of travel time delay. Findings can inform the design of a crowdshipping system as well as related engagement efforts.

Suggested Citation

  • Fessler, Andreas & Thorhauge, Mikkel & Mabit, Stefan & Haustein, Sonja, 2022. "A public transport-based crowdshipping concept as a sustainable last-mile solution: Assessing user preferences with a stated choice experiment," Transportation Research Part A: Policy and Practice, Elsevier, vol. 158(C), pages 210-223.
    • Handle: RePEc:eee:transa:v:158:y:2022:i:c:p:210-223
    DOI: 10.1016/j.tra.2022.02.005
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0965856422000337
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tra.2022.02.005?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. Börjesson, Maria & Fosgerau, Mogens & Algers, Staffan, 2012. "On the income elasticity of the value of travel time," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(2), pages 368-377.
    2. Devari, Aashwinikumar & Nikolaev, Alexander G. & He, Qing, 2017. "Crowdsourcing the last mile delivery of online orders by exploiting the social networks of retail store customers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 105(C), pages 105-122.
    3. Marta Viu-Roig & Eduard J. Alvarez-Palau, 2020. "The Impact of E-Commerce-Related Last-Mile Logistics on Cities: A Systematic Literature Review," Sustainability, MDPI, vol. 12(16), pages 1-19, August.
    4. Ermagun, Alireza & Stathopoulos, Amanda, 2018. "To bid or not to bid: An empirical study of the supply determinants of crowd-shipping," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 468-483.
    5. Felipe F. Dias & Patrícia S. Lavieri & Venu M. Garikapati & Sebastian Astroza & Ram M. Pendyala & Chandra R. Bhat, 2017. "A behavioral choice model of the use of car-sharing and ride-sourcing services," Transportation, Springer, vol. 44(6), pages 1307-1323, November.
    6. Wei Qi & Lefei Li & Sheng Liu & Zuo-Jun Max Shen, 2018. "Shared Mobility for Last-Mile Delivery: Design, Operational Prescriptions, and Environmental Impact," Manufacturing & Service Operations Management, INFORMS, vol. 20(4), pages 737-751, October.
    7. Nielsen, Thomas Alexander Sick & Haustein, Sonja, 2018. "On sceptics and enthusiasts: What are the expectations towards self-driving cars?," Transport Policy, Elsevier, vol. 66(C), pages 49-55.
    8. Punel, Aymeric & Stathopoulos, Amanda, 2017. "Modeling the acceptability of crowdsourced goods deliveries: Role of context and experience effects," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 105(C), pages 18-38.
    9. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387.
    10. Allahviranloo, Mahdieh & Baghestani, Amirhossein, 2019. "A dynamic crowdshipping model and daily travel behavior," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 128(C), pages 175-190.
    11. Özhan Zurel & Laurent Hoyweghen & Stijn Braes & Aurelie Seghers, 2018. "Parcel Lockers, an Answer to the Pressure on the Last Mile Delivery?," Topics in Regulatory Economics and Policy, in: Pier Luigi Parcu & Timothy J. Brennan & Victor Glass (ed.), New Business and Regulatory Strategies in the Postal Sector, pages 299-312, Springer.
    12. Basu, Debasis & Hunt, John Douglas, 2012. "Valuing of attributes influencing the attractiveness of suburban train service in Mumbai city: A stated preference approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(9), pages 1465-1476.
    13. Hess, Stephane & Train, Kenneth E. & Polak, John W., 2006. "On the use of a Modified Latin Hypercube Sampling (MLHS) method in the estimation of a Mixed Logit Model for vehicle choice," Transportation Research Part B: Methodological, Elsevier, vol. 40(2), pages 147-163, February.
    14. Wang, Yuan & Zhang, Dongxiang & Liu, Qing & Shen, Fumin & Lee, Loo Hay, 2016. "Towards enhancing the last-mile delivery: An effective crowd-tasking model with scalable solutions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 93(C), pages 279-293.
    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. Fessler, Andreas & Cash, Philip & Thorhauge, Mikkel & Haustein, Sonja, 2023. "A public transport based crowdshipping concept: Results of a field test in Denmark," Transport Policy, Elsevier, vol. 134(C), pages 106-118.
    2. Zhu, Shengda & Bell, Michael G.H. & Schulz, Veronica & Stokoe, Michael, 2023. "Co-modality in city logistics: Sounds good, but how?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 168(C).
    3. Xiao, Haohan & Xu, Min & Wang, Shuaian, 2023. "Crowd-shipping as a Service: Game-based operating strategy design and analysis," Transportation Research Part B: Methodological, Elsevier, vol. 176(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. Pourrahmani, Elham & Jaller, Miguel, 2021. "Crowdshipping in last mile deliveries: Operational challenges and research opportunities," Socio-Economic Planning Sciences, Elsevier, vol. 78(C).
    2. Tapia, Rodrigo J. & Kourounioti, Ioanna & Thoen, Sebastian & de Bok, Michiel & Tavasszy, Lori, 2023. "A disaggregate model of passenger-freight matching in crowdshipping services," Transportation Research Part A: Policy and Practice, Elsevier, vol. 169(C).
    3. Behrend, Moritz & Meisel, Frank & Fagerholt, Kjetil & Andersson, Henrik, 2019. "An exact solution method for the capacitated item-sharing and crowdshipping problem," European Journal of Operational Research, Elsevier, vol. 279(2), pages 589-604.
    4. Ghaderi, Hadi & Zhang, Lele & Tsai, Pei-Wei & Woo, Jihoon, 2022. "Crowdsourced last-mile delivery with parcel lockers," International Journal of Production Economics, Elsevier, vol. 251(C).
    5. Alireza Ermagun & Ali Shamshiripour & Amanda Stathopoulos, 2020. "Performance analysis of crowd-shipping in urban and suburban areas," Transportation, Springer, vol. 47(4), pages 1955-1985, August.
    6. Nils Boysen & Stefan Fedtke & Stefan Schwerdfeger, 2021. "Last-mile delivery concepts: a survey from an operational research perspective," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 43(1), pages 1-58, March.
    7. Ermagun, Alireza & Stathopoulos, Amanda, 2018. "To bid or not to bid: An empirical study of the supply determinants of crowd-shipping," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 468-483.
    8. Punel, Aymeric & Stathopoulos, Amanda, 2017. "Modeling the acceptability of crowdsourced goods deliveries: Role of context and experience effects," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 105(C), pages 18-38.
    9. Patricija Bajec & Danijela Tuljak-Suban, 2022. "A Strategic Approach for Promoting Sustainable Crowdshipping in Last-Mile Deliveries," Sustainability, MDPI, vol. 14(20), pages 1-17, October.
    10. Jagienka Rześny-Cieplińska & Agnieszka Szmelter-Jarosz, 2019. "Assessment of the Crowd Logistics Solutions—The Stakeholders’ Analysis Approach," Sustainability, MDPI, vol. 11(19), pages 1-26, September.
    11. Le, Tho V. & Ukkusuri, Satish V. & Xue, Jiawei & Van Woensel, Tom, 2021. "Designing pricing and compensation schemes by integrating matching and routing models for crowd-shipping systems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 149(C).
    12. Bathke, Henrik & Hartmann, Evi, 2021. "Accepting a crowdsourced delivery - A choice-based conjoint analysis," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Jahn, Carlos & Kersten, Wolfgang & Ringle, Christian M. (ed.), Adapting to the Future: Maritime and City Logistics in the Context of Digitalization and Sustainability. Proceedings of the Hamburg International Conf, volume 32, pages 65-95, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    13. Xiao, Fei & Wang, Haijun & Guo, Shuojia & Guan, Xu & Liu, Baoshan, 2021. "Efficient and truthful multi-attribute auctions for crowdsourced delivery," International Journal of Production Economics, Elsevier, vol. 240(C).
    14. Cheng, Xi & Gou, Qinglong & Yue, Jinfeng & Zhang, Yan, 2019. "Equilibrium decisions for an innovation crowdsourcing platform," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 241-260.
    15. Shen, Hui & Lin, Jane, 2020. "Investigation of crowdshipping delivery trip production with real-world data," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 143(C).
    16. Michele D. Simoni & Edoardo Marcucci & Valerio Gatta & Christian G. Claudel, 2020. "Potential last-mile impacts of crowdshipping services: a simulation-based evaluation," Transportation, Springer, vol. 47(4), pages 1933-1954, August.
    17. Wang, Haibo & Alidaee, Bahram, 2023. "White-glove service delivery: A quantitative analysis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 175(C).
    18. Behrend, Moritz & Meisel, Frank, 2018. "The integration of item-sharing and crowdshipping: Can collaborative consumption be pushed by delivering through the crowd?," Transportation Research Part B: Methodological, Elsevier, vol. 111(C), pages 227-243.
    19. Behrend, Moritz & Meisel, Frank & Fagerholt, Kjetil & Andersson, Henrik, 2021. "A multi-period analysis of the integrated item-sharing and crowdshipping problem," European Journal of Operational Research, Elsevier, vol. 292(2), pages 483-499.
    20. Martin W.P Savelsbergh & Marlin W. Ulmer, 2022. "Challenges and opportunities in crowdsourced delivery planning and operations," 4OR, Springer, vol. 20(1), pages 1-21, March.

    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:158:y:2022:i:c:p:210-223. 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.