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How will last-mile delivery be shaped in 2040? A Delphi-based scenario study

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  • Peppel, Marcel
  • Ringbeck, Jürgen
  • Spinler, Stefan

Abstract

Last-mile delivery (LMD) has experienced tremendous growth in recent years, primarily driven by e-commerce. The LMD sector is characterized by strong competition, with new entrants addressing unexplored business segments, while digitization and more sustainable operations are shifting current industry standards. This paper explores upcoming trends in the LMD sector using a Delphi-based scenario study for 2040. We develop projections of future consumer behavior, delivery technologies, delivery services, and regulation to validate them by conducting a two-round Delphi study among 36 experts from the LMD industry, academia, and politics. Based on the results, three future scenarios are identified by fuzzy c-means clustering, set within the context of innovation diffusion theory and the technology acceptance model. There is expert consensus on the scope of technologies that will be used in 2040 and how consumers’ preferences may change, but the future design of delivery services is less certain. The identified scenarios provide managerial and policy guidance for logistics service providers, suppliers, municipalities, and e-commerce retailers to adapt their long-term strategies.

Suggested Citation

  • Peppel, Marcel & Ringbeck, Jürgen & Spinler, Stefan, 2022. "How will last-mile delivery be shaped in 2040? A Delphi-based scenario study," Technological Forecasting and Social Change, Elsevier, vol. 177(C).
  • Handle: RePEc:eee:tefoso:v:177:y:2022:i:c:s0040162522000257
    DOI: 10.1016/j.techfore.2022.121493
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    as
    1. Schudy, Simeon & Utikal, Verena, 2017. "‘You must not know about me’—On the willingness to share personal data," Journal of Economic Behavior & Organization, Elsevier, vol. 141(C), pages 1-13.
    2. 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.
    3. Akkermans, Henk A. & Bogerd, Paul & Yucesan, Enver & van Wassenhove, Luk N., 2003. "The impact of ERP on supply chain management: Exploratory findings from a European Delphi study," European Journal of Operational Research, Elsevier, vol. 146(2), pages 284-301, April.
    4. Micha Hirschinger & Alexander Spickermann & Evi Hartmann & Heiko Gracht & Inga-Lena Darkow, 2015. "The Future of Logistics in Emerging Markets—Fuzzy Clustering Scenarios Grounded in Institutional and Factor-Market Rivalry Theory," Journal of Supply Chain Management, Institute for Supply Management, vol. 51(4), pages 73-93, October.
    5. Oliveira, Leise Kelli de & Morganti, Eleonora & Dablanc, Laetitia & Oliveira, Renata Lúcia Magalhães de, 2017. "Analysis of the potential demand of automated delivery stations for e-commerce deliveries in Belo Horizonte, Brazil," Research in Transportation Economics, Elsevier, vol. 65(C), pages 34-43.
    6. Fred D. Davis & Richard P. Bagozzi & Paul R. Warshaw, 1989. "User Acceptance of Computer Technology: A Comparison of Two Theoretical Models," Management Science, INFORMS, vol. 35(8), pages 982-1003, August.
    7. Liu, Chengxi & Wang, Qian & Susilo, Yusak O., 2019. "Assessing the impacts of collection-delivery points to individual’s activity-travel patterns: A greener last mile alternative?," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 121(C), pages 84-99.
    8. Ehmke, Jan Fabian & Campbell, Ann Melissa & Urban, Timothy L., 2015. "Ensuring service levels in routing problems with time windows and stochastic travel times," European Journal of Operational Research, Elsevier, vol. 240(2), pages 539-550.
    9. Boysen, Nils & Schwerdfeger, Stefan & Weidinger, Felix, 2018. "Scheduling last-mile deliveries with truck-based autonomous robots," European Journal of Operational Research, Elsevier, vol. 271(3), pages 1085-1099.
    10. Jiang, Ruth & Kleer, Robin & Piller, Frank T., 2017. "Predicting the future of additive manufacturing: A Delphi study on economic and societal implications of 3D printing for 2030," Technological Forecasting and Social Change, Elsevier, vol. 117(C), pages 84-97.
    11. Bokrantz, Jon & Skoogh, Anders & Berlin, Cecilia & Stahre, Johan, 2017. "Maintenance in digitalised manufacturing: Delphi-based scenarios for 2030," International Journal of Production Economics, Elsevier, vol. 191(C), pages 154-169.
    12. Giuseppe Aiello & Salvatore Quaranta & Antonella Certa & Rosalinda Inguanta, 2021. "Optimization of Urban Delivery Systems Based on Electric Assisted Cargo Bikes with Modular Battery Size, Taking into Account the Service Requirements and the Specific Operational Context," Energies, MDPI, vol. 14(15), pages 1-17, August.
    13. von der Gracht, Heiko A. & Darkow, Inga-Lena, 2010. "Scenarios for the logistics services industry: A Delphi-based analysis for 2025," International Journal of Production Economics, Elsevier, vol. 127(1), pages 46-59, September.
    14. Rowe, Gene & Wright, George, 1999. "The Delphi technique as a forecasting tool: issues and analysis," International Journal of Forecasting, Elsevier, vol. 15(4), pages 353-375, October.
    15. Lin, Yun Hui & Wang, Yuan & He, Dongdong & Lee, Loo Hay, 2020. "Last-mile delivery: Optimal locker location under multinomial logit choice model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 142(C).
    16. Schuckmann, Steffen W. & Gnatzy, Tobias & Darkow, Inga-Lena & von der Gracht, Heiko A., 2012. "Analysis of factors influencing the development of transport infrastructure until the year 2030 — A Delphi based scenario study," Technological Forecasting and Social Change, Elsevier, vol. 79(8), pages 1373-1387.
    17. Norman Dalkey & Olaf Helmer, 1963. "An Experimental Application of the DELPHI Method to the Use of Experts," Management Science, INFORMS, vol. 9(3), pages 458-467, April.
    18. Yael Deutsch & Boaz Golany, 2018. "A parcel locker network as a solution to the logistics last mile problem," International Journal of Production Research, Taylor & Francis Journals, vol. 56(1-2), pages 251-261, January.
    19. Belton, Ian & MacDonald, Alice & Wright, George & Hamlin, Iain, 2019. "Improving the practical application of the Delphi method in group-based judgment: A six-step prescription for a well-founded and defensible process," Technological Forecasting and Social Change, Elsevier, vol. 147(C), pages 72-82.
    20. Flostrand, Andrew & Pitt, Leyland & Bridson, Shannon, 2020. "The Delphi technique in forecasting– A 42-year bibliographic analysis (1975–2017)," Technological Forecasting and Social Change, Elsevier, vol. 150(C).
    21. Keller, Jonas & von der Gracht, Heiko A., 2014. "The influence of information and communication technology (ICT) on future foresight processes — Results from a Delphi survey," Technological Forecasting and Social Change, Elsevier, vol. 85(C), pages 81-92.
    22. Boysen, Nils & Schwerdfeger, Stefan & Weidinger, Felix, 2018. "Scheduling last-mile deliveries with truck-based autonomous robots," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 126189, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    23. Di Zio, Simone & Bolzan, Mario & Marozzi, Marco, 2021. "Classification of Delphi outputs through robust ranking and fuzzy clustering for Delphi-based scenarios," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    24. Förster, Bernadette & von der Gracht, Heiko, 2014. "Assessing Delphi panel composition for strategic foresight — A comparison of panels based on company-internal and external participants," Technological Forecasting and Social Change, Elsevier, vol. 84(C), pages 215-229.
    25. Beiderbeck, Daniel & Frevel, Nicolas & von der Gracht, Heiko A. & Schmidt, Sascha L. & Schweitzer, Vera M., 2021. "The impact of COVID-19 on the European football ecosystem – A Delphi-based scenario analysis," Technological Forecasting and Social Change, Elsevier, vol. 165(C).
    26. Gnyawali, Devi R. & Park, Byung-Jin (Robert), 2011. "Co-opetition between giants: Collaboration with competitors for technological innovation," Research Policy, Elsevier, vol. 40(5), pages 650-663, June.
    27. Roßmann, Bernhard & Canzaniello, Angelo & von der Gracht, Heiko & Hartmann, Evi, 2018. "The future and social impact of Big Data Analytics in Supply Chain Management: Results from a Delphi study," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 135-149.
    28. Paul Goodwin & George Wright, 2001. "Enhancing Strategy Evaluation in Scenario Planning: a Role for Decision Analysis," Journal of Management Studies, Wiley Blackwell, vol. 38(1), pages 1-16, January.
    29. 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.
    30. Schwerdfeger, Stefan & Boysen, Nils, 2020. "Optimizing the changing locations of mobile parcel lockers in last-mile distribution," European Journal of Operational Research, Elsevier, vol. 285(3), pages 1077-1094.
    31. Winkler, Jens & Moser, Roger, 2016. "Biases in future-oriented Delphi studies: A cognitive perspective," Technological Forecasting and Social Change, Elsevier, vol. 105(C), pages 63-76.
    32. Fritschy, Carolin & Spinler, Stefan, 2019. "The impact of autonomous trucks on business models in the automotive and logistics industry–a Delphi-based scenario study," Technological Forecasting and Social Change, Elsevier, vol. 148(C).
    33. von der Gracht, Heiko A., 2012. "Consensus measurement in Delphi studies," Technological Forecasting and Social Change, Elsevier, vol. 79(8), pages 1525-1536.
    34. Charrad, Malika & Ghazzali, Nadia & Boiteau, Véronique & Niknafs, Azam, 2014. "NbClust: An R Package for Determining the Relevant Number of Clusters in a Data Set," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 61(i06).
    35. Bonaccorsi, Andrea & Apreda, Riccardo & Fantoni, Gualtiero, 2020. "Expert biases in technology foresight. Why they are a problem and how to mitigate them," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
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