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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

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  • 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
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    References listed on IDEAS

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    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.
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