IDEAS home Printed from https://ideas.repec.org/h/zbw/hiclch/249647.html
   My bibliography  Save this book chapter

Accepting a crowdsourced delivery - A choice-based conjoint analysis

In: Adapting to the Future: Maritime and City Logistics in the Context of Digitalization and Sustainability. Proceedings of the Hamburg International Conference of Logistics (HICL), Vol. 32

Author

Listed:
  • Bathke, Henrik
  • Hartmann, Evi

Abstract

Purpose: The increase in parcel quantities on the last mile requires new and innovative concepts to support sustainability efforts in urban areas. Crowdsourced delivery (CSD) represents a promising concept as it allows private couriers to take over the parcels' last mile on trips they would have traveled anyway. Whereas first research on the attributes leading to the acceptance of CSD requests via platforms exists, the attributes' respective importance remains unclear. Methodology: A choice-based conjoint analysis with 193 respondents willing to participate in CSDs was conducted. Attributes' relative importance and part-worth utilities were calculated using Hierarchical Bayes estimation. Findings: Results show that differences in deviation of the original travel time and remuneration have the greatest impact on couriers' request selection, while the degree of familiarity with the recipient and parcel weight are less decisive. Additionally, it became apparent that couriers' sentimental traits of environmental concerns and extraversion affect the choice of a CSD request. Originality: The study contributes to the scarce literature on the promising concept of CSD to reduce logistics-related environmental externalities and strengthens the application of marketing-related methodologies in logistics research. For CSD platform providers, results enable higher competitiveness through a more individualized request for potential couriers.

Suggested Citation

  • 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.
    • Handle: RePEc:zbw:hiclch:249647
    DOI: 10.15480/882.3996
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/249647/1/hicl-2021-32-065.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.15480/882.3996?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
    ---><---

    References listed on IDEAS

    as
    1. Adriana Giret & Carlos Carrascosa & Vicente Julian & Miguel Rebollo & Vicente Botti, 2018. "A Crowdsourcing Approach for Sustainable Last Mile Delivery," Sustainability, MDPI, vol. 10(12), pages 1-17, December.
    2. Valentina Carbone & Aurélien Rouquet & Christine Roussat, 2017. "The Rise of Crowd Logistics: A New Way to Co‐Create Logistics Value," Post-Print hal-03118967, HAL.
    3. Marlin Ulmer & Martin Savelsbergh, 2020. "Workforce Scheduling in the Era of Crowdsourced Delivery," Transportation Science, INFORMS, vol. 54(4), pages 1113-1133, July.
    4. Apostolakis, George & van Dijk, Gert & Kraanen, Frido & Blomme, Robert J., 2018. "Examining socially responsible investment preferences: A discrete choice conjoint experiment," Journal of Behavioral and Experimental Finance, Elsevier, vol. 17(C), pages 83-96.
    5. Danielis, Romeo & Marcucci, Edoardo & Rotaris, Lucia, 2005. "Logistics managers' stated preferences for freight service attributes," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 41(3), pages 201-215, May.
    6. Hongyan Dai & Peng Liu, 2020. "Workforce planning for O2O delivery systems with crowdsourced drivers," Annals of Operations Research, Springer, vol. 291(1), pages 219-245, August.
    7. Kathan, Wolfgang & Matzler, Kurt & Veider, Viktoria, 2016. "The sharing economy: Your business model's friend or foe?," Business Horizons, Elsevier, vol. 59(6), pages 663-672.
    8. Lijuan Huang & Guojie Xie & John Blenkinsopp & Raoyi Huang & Hou Bin, 2020. "Crowdsourcing for Sustainable Urban Logistics: Exploring the Factors Influencing Crowd Workers’ Participative Behavior," Sustainability, MDPI, vol. 12(8), pages 1-20, April.
    9. 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).
    10. 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.
    11. Seokgi Lee & Yuncheol Kang & Vittaldas V. Prabhu, 2016. "Smart logistics: distributed control of green crowdsourced parcel services," International Journal of Production Research, Taylor & Francis Journals, vol. 54(23), pages 6956-6968, December.
    12. 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.
    13. 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.
    14. Alnaggar, Aliaa & Gzara, Fatma & Bookbinder, James H., 2021. "Crowdsourced delivery: A review of platforms and academic literature," Omega, Elsevier, vol. 98(C).
    15. 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.
    16. Belk, Russell, 2014. "You are what you can access: Sharing and collaborative consumption online," Journal of Business Research, Elsevier, vol. 67(8), pages 1595-1600.
    17. Spickermann, Alexander & Zimmermann, Martin & von der Gracht, Heiko A., 2014. "Surface- and deep-level diversity in panel selection — Exploring diversity effects on response behaviour in foresight," Technological Forecasting and Social Change, Elsevier, vol. 85(C), pages 105-120.
    18. Archetti, Claudia & Savelsbergh, Martin & Speranza, M. Grazia, 2016. "The Vehicle Routing Problem with Occasional Drivers," European Journal of Operational Research, Elsevier, vol. 254(2), pages 472-480.
    19. Mohamed Souka & Daniel Böger & Reinhold Decker & Christian Stummer & Alisa Wiemann, 2020. "Is more automation always better? An empirical study of customers' willingness to use autonomous vehicle functions," International Journal of Automotive Technology and Management, Inderscience Enterprises Ltd, vol. 20(1), pages 1-24.
    20. Maldonado, Sebastián & Montoya, Ricardo & Weber, Richard, 2015. "Advanced conjoint analysis using feature selection via support vector machines," European Journal of Operational Research, Elsevier, vol. 241(2), pages 564-574.
    21. Kafle, Nabin & Zou, Bo & Lin, Jane, 2017. "Design and modeling of a crowdsource-enabled system for urban parcel relay and delivery," Transportation Research Part B: Methodological, Elsevier, vol. 99(C), pages 62-82.
    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. 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.
    2. 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).
    3. Pourrahmani, Elham & Jaller, Miguel, 2021. "Crowdshipping in last mile deliveries: Operational challenges and research opportunities," Socio-Economic Planning Sciences, Elsevier, vol. 78(C).
    4. Boysen, Nils & Emde, Simon & Schwerdfeger, Stefan, 2022. "Crowdshipping by employees of distribution centers: Optimization approaches for matching supply and demand," European Journal of Operational Research, Elsevier, vol. 296(2), pages 539-556.
    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. Mancini, Simona & Gansterer, Margaretha, 2022. "Bundle generation for last-mile delivery with occasional drivers," Omega, Elsevier, vol. 108(C).
    8. 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.
    9. Marlin Ulmer & Martin Savelsbergh, 2020. "Workforce Scheduling in the Era of Crowdsourced Delivery," Transportation Science, INFORMS, vol. 54(4), pages 1113-1133, July.
    10. Kexin Bi & Mengke Yang & Latif Zahid & Xiaoguang Zhou, 2020. "A New Solution for City Distribution to Achieve Environmental Benefits within the Trend of Green Logistics: A Case Study in China," Sustainability, MDPI, vol. 12(20), pages 1-25, October.
    11. Wang, Li & Xu, Min & Qin, Hu, 2023. "Joint optimization of parcel allocation and crowd routing for crowdsourced last-mile delivery," Transportation Research Part B: Methodological, Elsevier, vol. 171(C), pages 111-135.
    12. Lin Zhou & Yanping Chen & Yi Jing & Youwei Jiang, 2021. "Evolutionary Game Analysis on Last Mile Delivery Resource Integration—Exploring the Behavioral Strategies between Logistics Service Providers, Property Service Companies and Customers," Sustainability, MDPI, vol. 13(21), pages 1-18, November.
    13. 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.
    14. Mario Binetti & Leonardo Caggiani & Rosalia Camporeale & Michele Ottomanelli, 2019. "A Sustainable Crowdsourced Delivery System to Foster Free-Floating Bike-Sharing," Sustainability, MDPI, vol. 11(10), pages 1-24, May.
    15. Agnieszka Szmelter-Jarosz & Jagienka Rześny-Cieplińska, 2019. "Priorities of Urban Transport System Stakeholders According to Crowd Logistics Solutions in City Areas. A Sustainability Perspective," Sustainability, MDPI, vol. 12(1), pages 1-19, December.
    16. Raúl Martín-Santamaría & Ana D. López-Sánchez & María Luisa Delgado-Jalón & J. Manuel Colmenar, 2021. "An Efficient Algorithm for Crowd Logistics Optimization," Mathematics, MDPI, vol. 9(5), pages 1-19, March.
    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. Marco Bortolini & Francesca Calabrese & Francesco Gabriele Galizia, 2022. "Crowd Logistics: A Survey of Successful Applications and Implementation Potential in Northern Italy," Sustainability, MDPI, vol. 14(24), pages 1-17, December.

    More about this item

    Keywords

    City Logistics;

    Statistics

    Access and download statistics

    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:zbw:hiclch:249647. 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: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://hicl.org/ .

    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.