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Cross-price elasticities and their determinants: a meta-analysis and new empirical generalizations

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Abstract

In recent decades, the competitive landscape in many markets (e.g., retailing) and the methods that researchers use to analyze these markets have changed heavily. This has resulted in updates of empirical generalizations in many areas. For cross-price elasticities, however, this update is pending. Hence, it is unclear how these changes have affected cross-price elasticities, a key measure of competitive interaction. To address this void, we conduct a meta-analysis of prior econometric estimates and consider a broad set of determinants that have not been analyzed before in the context of cross-price elasticities. Using 7,264 estimates from 115 studies, we identify six new main empirical generalizations. (1) The mean cross-price elasticity is .26 (median =.10), which is half the magnitude of the previous meta-analytic mean. (2) Cross-price elasticities have decreased over time, and (3) they decrease over the product life cycle. (4) High-stockpiling groceries have the highest cross-price elasticities. (5) Long-term cross-price elasticities are larger than short-term cross-price elasticities. (6) The asymmetric share effect only holds in high-share tiers. We derive implications based on these empirical generalizations.

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Notes

  1. We use the term price changing brand to refer to the brand that changes its price (Horváth and Fok 2013 use the term “attacker brand”), and we refer to the brand that is affected by the rival’s price change as the demand changing brand (Horváth and Fok 2013 use the term “victim brand”). We opted for this more generic terminology because it encompasses both price increases as well as decreases of the price-changing brand, whereas attacker/victim tend to imply a competitive attack through a price reduction.

  2. We use the abbreviation CPE to refer to cross-price elasticities, and ACPE to refer to the absolute cross-price effect, which we will formally define below.

  3. We used the following keywords: cross price elasticity, cross price elasticities, cross price effect, cross price effects, cross-price.

  4. The majority of papers that we obtained from SSRN are working papers that are later published in a journal that we cover. We were able to identify 1 otherwise unpublished working paper.

  5. We analyze both cross-price elasticities between different brands and elasticities between SKUs of the same brand. As the majority of our elasticities is derived from competition between brands, we subsequently use the term brand elasticity.

  6. In addition, we collected information on distribution, data source, and estimation method. These variables, however, caused collinearity problems in the estimation (high correlations and high variance inflation factors in auxiliary OLS regressions; Köhler et al. 2017). We therefore omitted these variables from further consideration.

  7. We cannot exactly replicate their results because their analysis does not only rely on published studies but also includes additional, non-public data.

  8. Constrained elasticities derived from, e.g., multinomial logit models are by construction not independent from each other. Therefore, we assessed the effect of the category mean own price elasticity and not the effect of the focal brand’s own price elasticity.

  9. A 1% price change of a brand in a high price tier is larger in terms of dollars compared to a 1% change in a low price tier. This difference in dollars itself can lead to higher cross-price effects (Sethuraman et al. 1999).

  10. We analyzed the variable Relative Price only as a moderating and not as a direct effect to make the results comparable to the findings by Sethuraman et al. (1999).

  11. The “direct effect” in rows 1 and 2 of Table 5 is—because of the presence of the interaction—the effect of the base level of the market share tier, which is the low market share tier.

  12. If we change the base of the interaction, the “direct effect” of Asymmetric Share (in high market share tier) is significant.

References

  • Aggarwal, P., & Cha, T. (1998). Asymmetric price competition and store vs national brand choice. Journal of Product & Brand Management, 7(3), 244–253.

    Article  Google Scholar 

  • Ailawadi, K. L., Gedenk, K., & Neslin, S. A. (1999). Heterogeneity and purchase event feedback in choice models: An empirical analysis with implications for model building. International Journal of Research in Marketing, 16(3), 177–198.

    Article  Google Scholar 

  • Albers, S., Mantrala, M. K., & Sridhar, S. (2010). Personal Selling Elasticities: A Meta-Analysis. Journal of Marketing Research, 47(5), 840–853.

    Article  Google Scholar 

  • Allenby, G. M., & Rossi, P. E. (1991). Quality Perceptions and Asymmetric Switching Between Brands. Marketing Science, 10(3), 185–204.

    Article  Google Scholar 

  • Assmus, G., Farley, J. U., & Lehmann, D. R. (1984). How Advertising Affects Sales: Meta-Analysis of Econometric Results. Journal of Marketing Research, 21(1), 65–74.

    Article  Google Scholar 

  • Barrena, R., & Sánchez, M. (2009). Using emotional benefits as a differentiation strategy in saturated markets. Psychology & Marketing, 26(11), 1002–1030.

    Article  Google Scholar 

  • Bijmolt, T. H. A., & Pieters, R. G. M. (2001). Meta-Analysis in Marketing when Studies Contain Multiple Measurements. Marketing Letters, 12(2), 157–169.

    Article  Google Scholar 

  • Bijmolt, T. H. A., Van Heerde, H. J., & Pieters, R. G. M. (2005). New Empirical Generalizations on the Determinants of Price Elasticity. Journal of Marketing Research, 42(2), 141–156.

    Article  Google Scholar 

  • Blattberg, R. C., & Wisniewski, K. J. (1989). Price-Induced Patterns of Competition. Marketing Science, 8(4), 291–309.

    Article  Google Scholar 

  • Blattberg, R. C., Briesch, R., & Fox, E. J. (1995). How Promotions Work. Marketing Science, 14(3 supplement), G122–G132.

    Article  Google Scholar 

  • Bronnenberg, B. J., & Wathieu, L. (1996). Asymmetric promotion effects and brand positioning. Marketing Science, 15(4), 379–394.

    Article  Google Scholar 

  • Choi, B., & Ahluwalia, R. (2013). Determinants of brand switching: the role of consumer inferences, brand commitment, and perceived risk. Journal of Applied Social Psychology, 43(5), 981–991.

    Article  Google Scholar 

  • Danaher, P. J., & Brodie, R. J. (2000). Understanding the Characteristics of Price Elasticities for Frequently Purchased Packaged Goods. Journal of Marketing Management, 16(8), 917–936.

    Article  Google Scholar 

  • Edeling, A., & Fischer, M. (2016). Marketing’s Impact on Firm Value: Generalizations from a Meta-Analysis. Journal of Marketing Research, 53(4), 515–534.

    Article  Google Scholar 

  • Edeling, A., & Himme, A. (2018). When Does Market Share Matter? New Empirical Generalizations from a Meta-Analysis of the Market Share–Performance Relationship. Journal of Marketing, 82(3), 1–24.

    Article  Google Scholar 

  • Eisend, M. (2014). Shelf space elasticity: A meta-analysis. Journal of Retailing, 90(2), 168–181.

    Article  Google Scholar 

  • Eisend, M. (2015). Have We Progressed Marketing Knowledge? A Meta-Meta-Analysis of Effect Sizes in Marketing Research. Journal of Marketing, 79(3), 23–40.

    Article  Google Scholar 

  • Estelami, H., Lehmann, D. R., & Holden, A. C. (2001). Macro-economic determinants of consumer price knowledge: A meta-analysis of four decades of research. International Journal of Research in Marketing, 18(4), 341–355.

    Article  Google Scholar 

  • Fok, D., Horváth, C., Paap, R., & Franses, P. H. (2006). A Hierarchical Bayes Error Correction Model to Explain Dynamic Effects of Price Changes. Journal of Marketing Research (JMR), 43(3), 443–461. https://doi.org/10.1509/jmkr.43.3.443

  • Gelman, A., & Rubin, D. B. (1992). Inference from Iterative Simulation Using Multiple Sequences. Statistical Science, 7(4), 457–472.

    Article  Google Scholar 

  • Germann, F., Ebbes, P., & Grewal, R. (2015). The Chief Marketing Officer Matters! Journal of Marketing, 79(3), 1–22.

    Article  Google Scholar 

  • Grewal, D., Puccinelli, N., & Monroe, K. B. (2018). Meta-analysis: integrating accumulated knowledge. Journal of the Academy of Marketing Science, 46(1), 9–30.

    Article  Google Scholar 

  • Hanssens, D. M. (2015). Empirical Generalizations about Marketing Impact (2nd ed.). Cambridge: Marketing Science Institute.

    Google Scholar 

  • Horváth, C., & Fok, D. (2013). Moderating Factors of Immediate, Gross, and Net Cross-Brand Effects of Price Promotions. Marketing Science, 32(1), 127–152.

    Article  Google Scholar 

  • Ioannidis, J. P. A., & Trikalinos, T. A. (2005). Early extreme contradictory estimates may appear in published research: The Proteus phenomenon in molecular genetics research and randomized trials. Journal of Clinical Epidemiology, 58(6), 543–549.

    Article  Google Scholar 

  • Kacen, J. J., & Lee, J. A. (2002). The Influence of Culture on Consumer Impulsive Buying Behavior. Journal of Consumer Psychology, 12(2), 163–176.

    Article  Google Scholar 

  • Kamakura, W. A., & Russell, G. J. (1989). A Probabilistic Choice Model for Market Segmentation and Elasticity Structure. Journal of Marketing Research, 26(4), 379–390.

    Article  Google Scholar 

  • Keller, K. L., & Lehmann, D. R. (2006). Brands and Branding: Research Findings and Future Priorities. Marketing Science, 25(6), 740–759.

    Article  Google Scholar 

  • Köhler, C., Mantrala, M. K., Albers, S., & Kanuri, V. K. (2017). A Meta-Analysis of Marketing Communication Carryover Effects. Journal of Marketing Research, 54(6), 990–1008.

    Article  Google Scholar 

  • Lehmann, D. R., McAlister, L., & Staelin, R. (2011). Sophistication in Research in Marketing. Journal of Marketing, 75(4), 155–165.

    Article  Google Scholar 

  • Li, Y., & Ansari, A. (2014). A Bayesian Semiparametric Approach for Endogeneity and Heterogeneity in Choice Models. Management Science, 60(5), 1161–1179.

    Article  Google Scholar 

  • Mela, C. F., Gupta, S., & Lehmann, D. R. (1997). The Long-Term Impact of Promotion and Advertising on Consumer Brand Choice. Journal of Marketing Research, 34(2), 248–261.

    Article  Google Scholar 

  • Mela, C. F., Jedidi, K., & Bowman, D. (1998). The Long-Term Impact of Promotions on Consumer Stockpiling Behavior. Journal of Marketing Research, 35(2), 250–262.

    Article  Google Scholar 

  • Narasimhan, C., Neslin, S. A., & Sen, S. K. (1996). Promotional Elasticities and Category Characteristics. Journal of Marketing, 60(2), 17–30.

    Article  Google Scholar 

  • Parker, P. M., & Neelamegham, R. (1997). Price Elasticity Dynamics over the Product Life Cycle: A Study of Consumer Durables. Marketing Letters, 8(2), 205–216.

    Article  Google Scholar 

  • Perreault, W. D., & Leigh, L. E. (1989). Reliability of Nominal Data Based on Qualitative Judgments. Journal of Marketing Research, 26(2), 135–148.

    Article  Google Scholar 

  • Schooler, J. (2011). Unpublished results hide the decline effect. Nature, 470(7335), 437–438.

    Article  Google Scholar 

  • Sethuraman, R. (1995). A meta-analysis of national brand and store brand cross-promotional price elasticities. Marketing Letters, 6(4), 275–286.

    Article  Google Scholar 

  • Sethuraman, R., & Srinivasan, V. (2002). The Asymmetric Share Effect: An Empirical Generalization on Cross-Price Effects. Journal of Marketing Research, 39(3), 379–386.

    Article  Google Scholar 

  • Sethuraman, R., Srinivasan, V., & Kim, D. (1999). Asymmetric and Neighborhood Cross-Price Effects: Some Empirical Generalizations. Marketing Science, 18(1), 23–41.

    Article  Google Scholar 

  • Sethuraman, R., Tellis, G. J., & Briesch, R. A. (2011). How Well Does Advertising Work? Generalizations from Meta-Analysis of Brand Advertising Elasticities. Journal of Marketing Research, 48(3), 457–471.

    Article  Google Scholar 

  • Shocker, A. D., Bayus, B. L., & Kim, N. (2004). Product Complements and Substitutes in the Real World: The Relevance of “Other Products”. Journal of Marketing, 68(1), 28–40.

    Article  Google Scholar 

  • Simon, H. (1979). Dynamics of Price Elasticity and Brand Life Cycles: An Empirical Study. Journal of Marketing Research, 16(4), 439–452.

    Article  Google Scholar 

  • Sivakumar, K., & Raj, S. P. (1997). Quality Tier Competition: How Price Change Influences Brand Choice and Category Choice. Journal of Marketing, 61(3), 71–84.

    Article  Google Scholar 

  • Song, I. (2010). Item Aggregates and Price Elasticity. Seoul Journal of Business, 16(1), 45–63.

    Article  Google Scholar 

  • Srinivasan, S., Popkowski Leszczyc, P. T. L., & Bass, F. M. (2000). Market share response and competitive interaction: The impact of temporary, evolving and structural changes in prices. International Journal of Research in Marketing, 17(4), 281–305.

    Article  Google Scholar 

  • Stan Development Team (2017). RStanArm: Bayesian applied regression modeling via Stan. R package version 2.15.3. http://mc-stan.org

  • Steenkamp, J.-B. E. M., Nijs, V. R., Hanssens, D. M., & Dekimpe, M. G. (2005). Competitive Reactions to Advertising and Promotion Attacks. Marketing Science, 24(1), 35–54.

    Article  Google Scholar 

  • Steenkamp, J.-B. E., Van Heerde, H. J., & Geyskens, I. (2010). What Makes Consumers Willing to Pay a Price Premium for National Brands over Private Labels? Journal of Marketing Research, 47(6), 1011–1024.

    Article  Google Scholar 

  • Tellis, G. J. (1988). The Price Elasticity of Selective Demand: A Meta-Analysis of Econometric Models of Sales. Journal of Marketing Research, 25(4), 331–341.

    Article  Google Scholar 

  • van Heerde, H. J., Leeflang, P. S. H., & Wittink, D. R. (2000). The Estimation of Pre- and Postpromotion Dips with Store-Level Scanner Data. Journal of Marketing Research, 37(3), 383–395.

    Article  Google Scholar 

  • van Heerde, H. J., Gupta, S., & Wittink, D. R. (2003). Is 75% of the Sales Promotion Bump Due to Brand Switching? No, Only 33% Is. Journal of Marketing Research, 40(4), 481–491.

  • Villas-Boas, J. M., & Winer, R. S. (1999). Endogeneity in Brand Choice Models. Management Science, 45(10), 1324–1338.

    Article  Google Scholar 

  • Völckner, F., & Sattler, H. (2006). Drivers of Brand Extension Success. Journal of Marketing, 70(2), 18–34.

    Article  Google Scholar 

  • Wakefield, K. L., & Inman, J. J. (2003). Situational price sensitivity: the role of consumption occasion, social context and income. Journal of Retailing, 79(4), 199–212.

    Article  Google Scholar 

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Acknowledgements

The authors thank Harald van Heerde and participants at the 2016 ISMS Marketing Science Conference in Shanghai, and participants at the 2017 Annual Conference of the European Marketing Academy in Groningen for valuable comments. The authors gratefully acknowledge the helpful and constructive input by the editors, the AE and two anonymous reviewers.

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  1. School of Business and Economics, University of Tuebingen, Nauklerstr. 47, 72074, Tuebingen, Germany

    Johannes Auer & Dominik Papies

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Auer, J., Papies, D. Cross-price elasticities and their determinants: a meta-analysis and new empirical generalizations. J. of the Acad. Mark. Sci. 48, 584–605 (2020). https://doi.org/10.1007/s11747-019-00642-0

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