Impact of different types of in-store displays on consumer purchase behavior
Research on consumer in-store shopping behavior does not account for the existence of different types of display locations (e.g. storefront, store rear, secondary, front end cap, rear end cap, and shelf displays). This article focuses on accounting for and understanding the impact of various display...
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sg-smu-ink.lkcsb_research-79142022-12-19T03:56:14Z Impact of different types of in-store displays on consumer purchase behavior HAN, Yoonju CHANDUKALA, Sandeep R. LI, Shibo Research on consumer in-store shopping behavior does not account for the existence of different types of display locations (e.g. storefront, store rear, secondary, front end cap, rear end cap, and shelf displays). This article focuses on accounting for and understanding the impact of various displays on consumer purchase behavior based on the Stimulus-Organism-Response (SOR) theory. Specifically, we study how displays closer to and farther from the main location of the focal category influence consumer purchase behavior. Furthermore, within the different types of displays we investigate the impact of specific types of displays on consumer's category purchase and brand choice and the moderating role of price and discounts. A hierarchical Bayesian model is estimated using scanner panel data for a large U.S. grocery chain that contains unique information on the number of product facings at multiple display locations within a store. We find that displays closer to the focal category have a larger impact, with front end cap displays having the largest impact on category purchase and shelf displays having the largest impact on brand choice. We also demonstrate the synergistic impact of price and discounts in enhancing the impact of displays on consumer purchase behavior and brand choice. Equipped with these findings we propose a display allocation optimization that results in an average increase in revenue of about 11.15% and a strategy to distribute displays across all locations in the store rather than letting one location dominate. 2021-10-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/lkcsb_research/6915 info:doi/10.1016/j.jretai.2021.10.002 https://ink.library.smu.edu.sg/context/lkcsb_research/article/7914/viewcontent/DisplayOct2021_sv.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection Lee Kong Chian School Of Business eng Institutional Knowledge at Singapore Management University Displays Bayesian hierarchical models Optimization Marketing Sales and Merchandising |
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Displays Bayesian hierarchical models Optimization Marketing Sales and Merchandising HAN, Yoonju CHANDUKALA, Sandeep R. LI, Shibo Impact of different types of in-store displays on consumer purchase behavior |
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Research on consumer in-store shopping behavior does not account for the existence of different types of display locations (e.g. storefront, store rear, secondary, front end cap, rear end cap, and shelf displays). This article focuses on accounting for and understanding the impact of various displays on consumer purchase behavior based on the Stimulus-Organism-Response (SOR) theory. Specifically, we study how displays closer to and farther from the main location of the focal category influence consumer purchase behavior. Furthermore, within the different types of displays we investigate the impact of specific types of displays on consumer's category purchase and brand choice and the moderating role of price and discounts. A hierarchical Bayesian model is estimated using scanner panel data for a large U.S. grocery chain that contains unique information on the number of product facings at multiple display locations within a store. We find that displays closer to the focal category have a larger impact, with front end cap displays having the largest impact on category purchase and shelf displays having the largest impact on brand choice. We also demonstrate the synergistic impact of price and discounts in enhancing the impact of displays on consumer purchase behavior and brand choice. Equipped with these findings we propose a display allocation optimization that results in an average increase in revenue of about 11.15% and a strategy to distribute displays across all locations in the store rather than letting one location dominate. |
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text |
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HAN, Yoonju CHANDUKALA, Sandeep R. LI, Shibo |
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HAN, Yoonju CHANDUKALA, Sandeep R. LI, Shibo |
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HAN, Yoonju |
title |
Impact of different types of in-store displays on consumer purchase behavior |
title_short |
Impact of different types of in-store displays on consumer purchase behavior |
title_full |
Impact of different types of in-store displays on consumer purchase behavior |
title_fullStr |
Impact of different types of in-store displays on consumer purchase behavior |
title_full_unstemmed |
Impact of different types of in-store displays on consumer purchase behavior |
title_sort |
impact of different types of in-store displays on consumer purchase behavior |
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Institutional Knowledge at Singapore Management University |
publishDate |
2021 |
url |
https://ink.library.smu.edu.sg/lkcsb_research/6915 https://ink.library.smu.edu.sg/context/lkcsb_research/article/7914/viewcontent/DisplayOct2021_sv.pdf |
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