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Going green: the effect of green labels on delivery time slot choices

Author

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  • Agatz, N.A.H.
  • Fan, Y.
  • Stam, D.A.

Abstract

In this paper, we study the effectiveness of incentives on delivery service time slot choices. In particular, we focus on the use of green labels that specify time slot as environmentally friendly and that intrinsically motivate customers to choose a specific delivery time slot in lieu of price incentives based on extrinsic motivation. We argue this is important since green labels’ intrinsic nature affects costumer choice in fundamentally different ways than price incentives. We conduct two experiments and two simulation studies to study effects of using green labels. Our experimental findings suggest that: (1) green labels are an effective tool to steer shoppers toward a certain delivery option, (2) green labels are more effective for people who are more eco-conscious, (3) green labels remain effective in the presence of price incentives, while price incentives offer little added value beyond that of just green labels, and (4) the effectiveness of green labels versus price discounts remains high when time slots are less appealing (longer). Our simulation findings suggest that green slots, compared to price incentives or no incentives, offer providers a way to effectively steer consumer time slot choices to yield shorter routes, fewer delivery vehicles used, and more per-customer revenue. We thus conclude that steering individuals to select delivery time slots through intrinsic motivation via green labels may be a promising, no-cost direction for (online) retailers and an important topic for research.

Suggested Citation

  • Agatz, N.A.H. & Fan, Y. & Stam, D.A., 2020. "Going green: the effect of green labels on delivery time slot choices," ERIM Report Series Research in Management ERS-2020-009-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    • Handle: RePEc:ems:eureri:128912
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    as
    1. Gneezy, Uri & Rustichini, Aldo, 2000. "A Fine is a Price," The Journal of Legal Studies, University of Chicago Press, vol. 29(1), pages 1-17, January.
    2. Lynham, John & Nitta, Kohei & Saijo, Tatsuyoshi & Tarui, Nori, 2016. "Why does real-time information reduce energy consumption?," Energy Economics, Elsevier, vol. 54(C), pages 173-181.
    3. Roe, Brian & Teisl, Mario F. & Levy, Alan & Russell, Matthew, 2001. "US consumers' willingness to pay for green electricity," Energy Policy, Elsevier, vol. 29(11), pages 917-925, September.
    4. Uri Gneezy & Stephan Meier & Pedro Rey-Biel, 2011. "When and Why Incentives (Don't) Work to Modify Behavior," Journal of Economic Perspectives, American Economic Association, vol. 25(4), pages 191-210, Fall.
    5. Oben Ceryan & Izak Duenyas & Ozge Sahin, 2018. "Dynamic Pricing and Replenishment with Customer Upgrades," Production and Operations Management, Production and Operations Management Society, vol. 27(4), pages 663-679, April.
    6. Yadav, Rambalak & Pathak, Govind S., 2017. "Determinants of Consumers' Green Purchase Behavior in a Developing Nation: Applying and Extending the Theory of Planned Behavior," Ecological Economics, Elsevier, vol. 134(C), pages 114-122.
    7. Buchanan, Kathryn & Russo, Riccardo & Anderson, Ben, 2015. "The question of energy reduction: The problem(s) with feedback," Energy Policy, Elsevier, vol. 77(C), pages 89-96.
    8. Rana, Jyoti & Paul, Justin, 2017. "Consumer behavior and purchase intention for organic food: A review and research agenda," Journal of Retailing and Consumer Services, Elsevier, vol. 38(C), pages 157-165.
    9. Xuanming Su, 2007. "Intertemporal Pricing with Strategic Customer Behavior," Management Science, INFORMS, vol. 53(5), pages 726-741, May.
    10. Ann Melissa Campbell & Martin W. P. Savelsbergh, 2005. "Decision Support for Consumer Direct Grocery Initiatives," Transportation Science, INFORMS, vol. 39(3), pages 313-327, August.
    11. Harwin de Vries & Joris van de Klundert & Albert P.M. Wagelmans, 2020. "The Roadside Healthcare Facility Location Problem A Managerial Network Design Challenge," Production and Operations Management, Production and Operations Management Society, vol. 29(5), pages 1165-1187, May.
    12. Ajzen, Icek, 1991. "The theory of planned behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 50(2), pages 179-211, December.
    13. Ming Chen & Zhi-Long Chen, 2015. "Recent Developments in Dynamic Pricing Research: Multiple Products, Competition, and Limited Demand Information," Production and Operations Management, Production and Operations Management Society, vol. 24(5), pages 704-731, May.
    14. Ann Melissa Campbell & Martin Savelsbergh, 2006. "Incentive Schemes for Attended Home Delivery Services," Transportation Science, INFORMS, vol. 40(3), pages 327-341, August.
    15. Mohsen Emadikhiav & David Bergman & Robert Day, 2020. "Consistent Routing and Scheduling with Simultaneous Pickups and Deliveries," Production and Operations Management, Production and Operations Management Society, vol. 29(8), pages 1937-1955, August.
    16. Nomura, Noboru & Akai, Makoto, 2004. "Willingness to pay for green electricity in Japan as estimated through contingent valuation method," Applied Energy, Elsevier, vol. 78(4), pages 453-463, August.
    17. Thunyarat (Bam) Amornpetchkul & Hyun‐Soo Ahn & Özge Şahin, 2018. "Conditional Promotions and Consumer Overspending," Production and Operations Management, Production and Operations Management Society, vol. 27(8), pages 1455-1475, August.
    18. Ehmke, Jan Fabian & Campbell, Ann Melissa, 2014. "Customer acceptance mechanisms for home deliveries in metropolitan areas," European Journal of Operational Research, Elsevier, vol. 233(1), pages 193-207.
    19. Marius M. Solomon, 1987. "Algorithms for the Vehicle Routing and Scheduling Problems with Time Window Constraints," Operations Research, INFORMS, vol. 35(2), pages 254-265, April.
    20. Ann Melissa Campbell & Martin Savelsbergh, 2004. "Efficient Insertion Heuristics for Vehicle Routing and Scheduling Problems," Transportation Science, INFORMS, vol. 38(3), pages 369-378, August.
    21. Qian Liu & Dan Zhang, 2013. "Dynamic Pricing Competition with Strategic Customers Under Vertical Product Differentiation," Management Science, INFORMS, vol. 59(1), pages 84-101, August.
    22. Steg, Linda & Lindenberg, Siegwart & Keizer, Kees, 2016. "Intrinsic Motivation, Norms and Environmental Behaviour: The Dynamics of Overarching Goals," International Review of Environmental and Resource Economics, now publishers, vol. 9(1-2), pages 179-207, July.
    23. Tore Ellingsen & Magnus Johannesson, 2007. "Paying Respect," Journal of Economic Perspectives, American Economic Association, vol. 21(4), pages 135-150, Fall.
    24. Niels Agatz & Ann Campbell & Moritz Fleischmann & Martin Savelsbergh, 2011. "Time Slot Management in Attended Home Delivery," Transportation Science, INFORMS, vol. 45(3), pages 435-449, August.
    25. Delmas, Magali A. & Fischlein, Miriam & Asensio, Omar I., 2013. "Information strategies and energy conservation behavior: A meta-analysis of experimental studies from 1975 to 2012," Energy Policy, Elsevier, vol. 61(C), pages 729-739.
    26. Yang, Xinan & Strauss, Arne K., 2017. "An approximate dynamic programming approach to attended home delivery management," European Journal of Operational Research, Elsevier, vol. 263(3), pages 935-945.
    27. Gleim, Mark R. & Smith, Jeffery S. & Andrews, Demetra & Cronin, J. Joseph, 2013. "Against the Green: A Multi-method Examination of the Barriers to Green Consumption," Journal of Retailing, Elsevier, vol. 89(1), pages 44-61.
    28. Sri Devi Duvvuri & Asim Ansari & Sunil Gupta, 2007. "Consumers' Price Sensitivities Across Complementary Categories," Management Science, INFORMS, vol. 53(12), pages 1933-1945, December.
    29. Xiaobei Shen & Yimin Yu, 2019. "Capacity Allocation with Multiple Suppliers and Multiple Demand Classes," Production and Operations Management, Production and Operations Management Society, vol. 28(11), pages 2792-2807, November.
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    Keywords

    customer behavior; green label; intrinsic incentive; attended home delivery;
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