This research investigates how a price promotion on a fast-moving consumer good influences the sales of substitute products in a retail shelf or online display. An analysis of supermarket yogurt data finds that when nonpromoted products are strong substitutes for the promoted product, a 1% decrease in the price of the promoted product results in a .25% decrease in the sales of proximal products but no change in the sales of distal products—a negative promotion-proximity effect. However, when nonpromoted products are weak substitutes for the promoted product, a 1% decrease in the price of the promoted product results in a .10% increase in the sales of proximal products but no change in sales for distal products—a positive promotion-proximity effect. Subsequent studies show that these effects occur because a proximal strong substitute is more likely to enter a consideration set with the promoted product (negative promotion-proximity effect) and a proximal weak substitute is more likely to be seen and considered by a consumer who is not interested in the promoted product (positive promotion-proximity effect).
AuerJohannesPapiesDominik (2020), “Cross-Price Elasticities and Their Determinants: A Meta-Analysis and New Empirical Generalizations,” Journal of the Academy of Marketing Science, 48 (3), 584–605.
2.
BaltagiB.H. (2005), Econometric Analysis of Panel Data, 3rd ed. John Wiley & Sons.
3.
BellDavid R.ChiangJeongwenPadmanabhanV. (1999), “The Decomposition of Promotional Response: An Empirical Generalization,” Marketing Science, 18 (4), 504–26.
4.
BettmanJames R. (1979), “Memory Factors in Consumer Choice: A Review,” Journal of Marketing, 43 (2), 37–53.
5.
BlattbergRobert C.NeslinScott A. (1990), Sales Promotion, Concepts, Methods and Strategies. Prentice-Hall.
6.
BogomolovaSvetlanaOppewalHarmenCohenJustinYaoJun (2020), “How the Layout of a Unit Price Label Affects Eye-Movements and Product Choice: An Eye-Tracking Investigation,” Journal of Business Research, 111, 102–16.
7.
BurkeRaymond R.LeykinAlex (2014), “Identifying the Drivers of Shopper Attention, Engagement, and Purchase,” in Shopper Marketing and the Role of In-Store Marketing, Review of Marketing Research Vol. 11. Emerald Publishing, 147–87.
8.
ChakravartiAmitavJaniszewskiChris (2003), “The Influence of Macro-Level Motives on Consideration Set Composition in Novel Purchase Situations,” Journal of Consumer Research, 30 (2), 244–58.
9.
ChandonPierreHutchinsonJ. WesleyBradlowEric T.YoungScott H. (2009), “Does In-Store Marketing Work? Effects of the Number and Position of Shelf Facings on Brand Attention and Evaluation at the Point of Purchase,” Journal of Marketing, 73 (6), 1–17.
10.
DrèzeXavierHochStephen J.PurkMary E. (1994), “Shelf Management and Space Elasticity,” Journal of Retailing, 70 (4), 301–26.
11.
HeilmanCarrie M.NakamotoKentRaoAmbar G. (2002), “Pleasant Surprises: Consumer Response to Unexpected In-Store Coupons,” Journal of Marketing Research, 39, 242–52.
12.
InmanJ. JeffreyMcAlisterLeighHoyerWayne D. (1990), “Promotion Signal: Proxy for a Price Cut?” Journal of Consumer Research, 17 (1), 74–81.
13.
JaniszewskiChris (1998), “The Influence of Display Characteristics on Visual Exploratory Search Behavior,” Journal of Consumer Research, 25 (3), 290–301.
14.
KumarV.LeoneRobert P. (1988), “Measuring the Effect of Retail Store Promotions on Brand and Store Substitution,” Journal of Marketing Research, 25 (2), 178–85.
15.
LeeflangPeter S.Parreño-SelvaJosefa (2012), “Cross-Category Demand Effects of Price Promotions,” Journal of the Academy of Marketing Science, 40 (4), 572–86.
16.
LiuYanBalachanderSubramanian (2014), “How Long Has It Been Since the Last Deal? Consumer Promotion Timing Expectations and Promotional Response,” Quantitative Marketing and Economics, 12 (1), 85–126.
17.
LiuLinDukesAnthony (2013), “Consideration Set Formation with Multiproduct Firms: The Case of Within-Firm and Across-Firm Evaluation Costs,” Management Science, 59 (8), 1871–86.
18.
MehtaNitinRajivSurendraSrinivasanKannan (2003), “Price Uncertainty and Consumer Search: A Structural Model of Consideration Set Formation,” Marketing Science, 22 (1), 58–84.
19.
MilosavljevicMilicaNavalpakkamVidhyaKochChristofRangelAntonio (2012), “Relative Visual Saliency Differences Induce Sizable Bias in Consumer Choice,” Journal of Consumer Psychology, 22 (1), 67–74.
20.
NedungadiPrakash (1990), “Recall and Consumer Consideration Sets: Influencing Choice Without Altering Brand Evaluations,” Journal of Consumer Research, 17 (3), 263–76.
21.
NordfältJens (2011), “Improving the Attention-Capturing Ability of Special Displays with the Combination Effect and Design Effect,” Journal of Retailing Consumer Services, 18 (3), 169–73.
22.
OrquinJacob L.LooseSimone Mueller (2013), “Attention and Choice: A Review on Eye Movements in Decision Making,” Acta Psychologica, 144 (1), 190–206.
23.
ParkSunghoGuptaSachin (2012), “Handling Endogenous Regressors by Joint Estimation Using Copulas,” Marketing Science, 31 (4), 567–86.
24.
PietersRikWedelMichel (2004), “Attention Capture and Transfer in Advertising: Brand, Pictorial, and Text-Size Effects,” Journal of Marketing, 68 (2), 36–50.
25.
PunjGirishMooreRobert (2009), “Information Search and Consideration Set Formation in a Web-Based Store Environment,” Journal of Business Research, 62 (6), 644–50.
26.
RatnerRebecca K.KahnBarbara E.KahnemanDaniel (1999), “Choosing Less-Preferred Experiences for the Sake of Variety,” Journal of Consumer Research, 26 (1), 1–15.
27.
RatneshwarS.PechmannCorneliaShockerAllan D. (1996), “Goal-Derived Categories and the Antecedents of Across-Category Consideration,” Journal of Consumer Research, 23 (3), 240–50.
28.
RobertsJohn H.LattinJames M. (1991), “Development and Testing of a Model of Consideration Set Composition,” Journal of Marketing Research, 28 (4), 429–40.
RossiPeter E.AllenbyGreg M.McCullochRobert (2005), Bayesian Statistics and Marketing. John Wiley & Sons.
31.
SethuramanRajSrinivasanV.KimDoyle (1999), “Asymmetric and Neighborhood Cross-Price Effects: Some Empirical Generalizations,” Marketing Science, 18 (1), 23–41.
32.
ShimojoShinsukeSimionClaudiuShimojoEikoScheierChristian (2003), “Gaze Bias Both Reflects and Influences Preference,” Nature Neuroscience, 6 (12), 1317–22.
33.
ShockerAllan D.Ben-AkivaMosheBoccaraBrunoNedungadiPrakash (1991), “Consideration Set Influences on Consumer Decision-Making and Choice: Issues, Models, and Suggestions,” Marketing Letters, 2 (3), 181–97.
34.
SimonsonItamar (1990), “The Effect of Purchase Quantity and Timing on Variety-Seeking Behavior,” Journal of Marketing Research, 27 (2), 150–62.
35.
SpiegelhalterDavid J.BestNicola G.CarlinBradley P.van der LindeAngelika (2002), “Bayesian Measures of Model Complexity and Fit,” Journal of the Royal Statistical Society: Series B (Statistical Methodology), 64 (4), 583–639.
36.
StreicherMathias C.EstesZacharyButtnerOliver B. (2021), “Exploratory Shopping: Attention Affects In-Store Exploration and Unplanned Purchasing,” Journal of Consumer Research, 48 (1), 51–76.
TreismanAnne (1998), “Feature Binding, Attention and Object Perception,” Philosophical Transactions of the Royal Society of London: Biological Sciences, 353, 1295–1306.
39.
Van der LansRalf (2018), “A Simultaneous Model of Multiple-Discrete Choices of Variety and Quantity,” International Journal of Research in Marketing, 35 (2), 242–57.
40.
Van der LansRalfPietersRikWedelMichel (2008), “Competitive Brand Salience,” Marketing Science, 27 (5), 922–31.
41.
Van HeerdeHarald J.GuptaSachinWittinkDick R. (2003), “Is 75% of the Sales Promotion Bump Due to Brand Switching? No, Only 33% Is,” Journal of Marketing Research, 40 (4), 481–91.
42.
Van HeerdeHarald J.LeeflangPeter. S.H.WittinkDick R. (2002), “How Promotions Work: SCAN*PRO-Based Evolutionary Model Building,” Schmalenbach Business Review, 54 (3), 198–220.
WästlundErikShamsPojaOtterbringTobias (2018), “Unsold Is Unseen … Or Is It? Examining the Role of Peripheral Vision in the Consumer Choice Process Using Eye-Tracking Methodology,” Appetite, 120 (January), 49–56.
45.
WinerBenjamin J.BrownDonald R.MichelsKenneth M. (1991), Statistical Principles in Experimental Design. McGraw-Hill.
46.
WolfeJeremy M. (1994), “Guided Search 2.0: A Revised Model of Visual Search,” Psychonomic Bulletin & Review, 1 (2), 202–38.
47.
WooldridgeJeffrey (2010), Econometric Analysis of Cross Section and Panel Data. MIT Press.
48.
YuHanJiangShanheLandKenneth C. (2015), “Multicollinearity in Hierarchical Linear Models,” Social Science Research, 53 (September), 118–36.
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