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Altering Speed of Locomotion

Author

Listed:
  • Bram Van Den Bergh
  • Nico Heuvinck
  • Gaby A. C. Schellekens
  • Iris Vermeir

Abstract

Even though 80% of a shopper’s time in the store is spent moving from place to place, little is known about managing the pace of in-store traffic flow. Based on the store atmospherics literature, this article introduces interventions to optimize the pace of locomotion. A series of lab and field experiments demonstrates that changes in flooring affect customers’ walking speed. The number, the nature, and the relative salience of progress markers along a walking path toward a physical location communicate goal progress and thus the motivation to reach a particular destination. Consistent with a goal gradient account, customers walk faster when fewer progress markers are placed along the walking path to the goal. The effect of the number of progress markers diminishes when the markers are unrelated to the goal and reverses when the markers are relatively more salient than the goal. This article contributes to the goal literature by showing how markers affect perceptions of goal progress (i.e., level vs. rate of progress) and provides concrete insights to speed up and slow down customers’ walking speed in a retail environment.

Suggested Citation

  • Bram Van Den Bergh & Nico Heuvinck & Gaby A. C. Schellekens & Iris Vermeir, 2016. "Altering Speed of Locomotion," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 43(3), pages 407-428.
  • Handle: RePEc:oup:jconrs:v:43:y:2016:i:3:p:407-428.
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    File URL: http://hdl.handle.net/10.1093/jcr/ucw031
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    References listed on IDEAS

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    1. Rajesh Bagchi & Xingbo Li, 2011. "Illusionary Progress in Loyalty Programs: Magnitudes, Reward Distances, and Step-Size Ambiguity," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 37(5), pages 888-901.
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    5. Minjung Koo & Ayelet Fishbach, 2012. "The Small-Area Hypothesis: Effects of Progress Monitoring on Goal Adherence," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 39(3), pages 493-509.
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    Cited by:

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    2. Roggeveen, Anne L. & Grewal, Dhruv & Schweiger, Elisa B., 2020. "The DAST Framework for Retail Atmospherics: The Impact of In- and Out-of-Store Retail Journey Touchpoints on the Customer Experience," Journal of Retailing, Elsevier, vol. 96(1), pages 128-137.
    3. Larsen, Nils Magne & Sigurdsson, Valdimar & Breivik, Jørgen & Orquin, Jacob Lund, 2020. "The heterogeneity of shoppers’ supermarket behaviors based on the use of carrying equipment," Journal of Business Research, Elsevier, vol. 108(C), pages 390-400.
    4. Beziat, Adrien & Koning, Martin & Toilier, Florence, 2017. "Marginal congestion costs in the case of multi-class traffic: A macroscopic assessment for the Paris Region," Transport Policy, Elsevier, vol. 60(C), pages 87-98.
    5. Szocs, Courtney & Kim, Yeseul & Lim, Mikyoung & Mera, Christian Arroyo & Biswas, Dipayan, 2023. "The store of the future: Engaging customers through sensory elements, personalized atmospherics, and interpersonal interaction," Journal of Retailing, Elsevier, vol. 99(4), pages 605-620.
    6. Shandong Mou, 2022. "Integrated Order Picking and Multi-Skilled Picker Scheduling in Omni-Channel Retail Stores," Mathematics, MDPI, vol. 10(9), pages 1-19, April.

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