IDEAS home Printed from https://ideas.repec.org/a/kap/qmktec/v10y2012i3p305-333.html
   My bibliography  Save this article

Investigating brand preferences across social groups and consumption contexts

Author

Listed:
  • Minki Kim
  • Pradeep Chintagunta

Abstract

Using a unique dataset on U.S. beer consumption, we investigate brand preferences of consumers across various social group and context related consumption scenarios (“scenarios”). As sufficient data are not available for each scenario, understanding these preferences requires us to share information across scenarios. Our proposed modeling framework has two main building blocks. The first is a standard continuous random coefficients logit model that the framework reduces to in the absence of information on social groups and consumption contexts. The second component captures variations in mean preferences across scenarios in a parsimonious fashion by decomposing the deviations in preferences from a base scenario into a low dimensional brand map in which the brand locations are fixed across scenarios but the importance weights vary by scenario. In addition to heterogeneity in brand preferences that is reflected in the random coefficients, heterogeneity in preferences across scenarios is accounted for by allowing the brand map itself to have a discrete heterogeneity distribution across consumers. Finally, heterogeneity in preferences within a scenario is accounted for by allowing the importance weights to vary across consumers. Together, these factors allow us to parsimoniously account for preference heterogeneity across brands, consumers and scenarios. We conduct a simulation study to reassure ourselves that using the kind of data that is available to us, our proposed estimator can recover the true model parameters from those data. We find that brand preferences vary considerably across the different social groups and consumption contexts as well as across different consumer segments. Despite the sparse data on specific brand-scenario combinations, our approach facilitates such an analysis and assessment of the relative strengths of brands in each of these scenarios. This could provide useful guidance to the brand managers of the smaller brands whose overall preference level might be low but which enjoy a customer franchise in a particular segment or in a particular context or a social group setting. Copyright Springer Science+Business Media, LLC 2012

Suggested Citation

  • Minki Kim & Pradeep Chintagunta, 2012. "Investigating brand preferences across social groups and consumption contexts," Quantitative Marketing and Economics (QME), Springer, vol. 10(3), pages 305-333, September.
  • Handle: RePEc:kap:qmktec:v:10:y:2012:i:3:p:305-333
    DOI: 10.1007/s11129-011-9117-0
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11129-011-9117-0
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s11129-011-9117-0?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Peter M. Guadagni & John D. C. Little, 1983. "A Logit Model of Brand Choice Calibrated on Scanner Data," Marketing Science, INFORMS, vol. 2(3), pages 203-238.
    2. Wayne S. DeSarbo & A. Selin Atalay & David LeBaron & Simon J. Blanchard, 2008. "Estimating Multiple Consumer Segment Ideal Points from Context-Dependent Survey Data," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 35(1), pages 142-153, March.
    3. Nevo, Aviv, 2001. "Measuring Market Power in the Ready-to-Eat Cereal Industry," Econometrica, Econometric Society, vol. 69(2), pages 307-342, March.
    4. Jerry A. Hausman, 1996. "Valuation of New Goods under Perfect and Imperfect Competition," NBER Chapters, in: The Economics of New Goods, pages 207-248, National Bureau of Economic Research, Inc.
    5. Sha Yang & Gerg M. Allenby & Geraldine Fennel, 2002. "Modeling Variation in Brand Preference: The Roles of Objective Environment and Motivating Conditions," Marketing Science, INFORMS, vol. 21(1), pages 14-31, May.
    6. Timothy F. Bresnahan & Robert J. Gordon, 1996. "The Economics of New Goods," NBER Books, National Bureau of Economic Research, Inc, number bres96-1.
    7. Bettman, James R & Luce, Mary Frances & Payne, John W, 1998. "Constructive Consumer Choice Processes," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 25(3), pages 187-217, December.
    8. Elrod, Terry & Keane, Michael, 1995. "A Factor-Analytic Probit Model for Representing the Market Structure in Panel Data," MPRA Paper 52434, University Library of Munich, Germany.
    9. Terry Elrod, 1988. "Choice Map: Inferring a Product-Market Map from Panel Data," Marketing Science, INFORMS, vol. 7(1), pages 21-40.
    10. Belk, Russell W, 1975. "Situational Variables and Consumer Behavior," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 2(3), pages 157-164, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lim, Jooyoung & Hahn, Minhi, 2020. "Regulatory focus and decision rules: Are prevention-focused consumers regret minimizers?," Journal of Business Research, Elsevier, vol. 120(C), pages 343-350.
    2. Yan Liu & Venkatesh Shankar, 2015. "The Dynamic Impact of Product-Harm Crises on Brand Preference and Advertising Effectiveness: An Empirical Analysis of the Automobile Industry," Management Science, INFORMS, vol. 61(10), pages 2514-2535, October.
    3. Andreea-Daniela, Gangone & Mihaela, Asandei, 2017. "Impact Of Green Marketing Practices On National Competitiveness In The European Union," Management Strategies Journal, Constantin Brancoveanu University, vol. 36(2), pages 6-14.
    4. Tahmid Nayeem & Nick Pawsey & Feisal Murshed & Lee Baumgartner & Craig Boys & Tom Rayner, 2023. "Modern Sustainable Fish Screens: A Study on Developing Effective Communication with Water Users," Sustainability, MDPI, vol. 15(9), pages 1-13, May.
    5. Sudhir Voleti & Praveen K. Kopalle & Pulak Ghosh, 2015. "An Interproduct Competition Model Incorporating Branding Hierarchy and Product Similarities Using Store-Level Data," Management Science, INFORMS, vol. 61(11), pages 2720-2738, November.
    6. Junghyun Park & Minki Kim & Pradeep K Chintagunta, 2022. "Mapping Consumers’ Context-Dependent Consumption Preferences: A Multidimensional Unfolding Approach [An Empirical Comparison of Logit Choice Models with Discrete versus Continuous Representations o," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 49(2), pages 202-228.
    7. Guofang Huang & Ahmed Khwaja & K. Sudhir, 2015. "Short-Run Needs and Long-Term Goals: A Dynamic Model of Thirst Management," Marketing Science, INFORMS, vol. 34(5), pages 702-721, September.
    8. Sinha, Priyank & Sainy, Romi, 2021. "How can Indian small-scale fashion retailers survive COVID-19 disruption?-A Brand Portfolio Optimization Perspective," Journal of Retailing and Consumer Services, Elsevier, vol. 62(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Junghyun Park & Minki Kim & Pradeep K Chintagunta, 2022. "Mapping Consumers’ Context-Dependent Consumption Preferences: A Multidimensional Unfolding Approach [An Empirical Comparison of Logit Choice Models with Discrete versus Continuous Representations o," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 49(2), pages 202-228.
    2. Yang Li & Asim Ansari, 2014. "A Bayesian Semiparametric Approach for Endogeneity and Heterogeneity in Choice Models," Management Science, INFORMS, vol. 60(5), pages 1161-1179, May.
    3. Joonwook Park & Priyali Rajagopal & Wayne DeSarbo, 2012. "A New Heterogeneous Multidimensional Unfolding Procedure," Psychometrika, Springer;The Psychometric Society, vol. 77(2), pages 263-287, April.
    4. Pradeep Chintagunta & Jean-Pierre Dubé & Vishal Singh, 2003. "Balancing Profitability and Customer Welfare in a Supermarket Chain," Quantitative Marketing and Economics (QME), Springer, vol. 1(1), pages 111-147, March.
    5. Nevo, Aviv, 2001. "Measuring Market Power in the Ready-to-Eat Cereal Industry," Econometrica, Econometric Society, vol. 69(2), pages 307-342, March.
    6. Durlauf, Steven N. & Navarro, Salvador & Rivers, David A., 2016. "Model uncertainty and the effect of shall-issue right-to-carry laws on crime," European Economic Review, Elsevier, vol. 81(C), pages 32-67.
    7. Lukasz Grzybowski & Frank Verboven, 2016. "Substitution between fixed-line and mobile access: the role of complementarities," Journal of Regulatory Economics, Springer, vol. 49(2), pages 113-151, April.
    8. Steven T. Berry & Philip A. Haile, 2021. "Foundations of Demand Estimation," Cowles Foundation Discussion Papers 2301, Cowles Foundation for Research in Economics, Yale University.
    9. Watanabe, Mariko, 2016. "Does market upgrading benefit farmers? : market differentiation, contract farming, and professional cooperatives in China's pork processing industry," IDE Discussion Papers 612, Institute of Developing Economies, Japan External Trade Organization(JETRO).
    10. Böheim, René & Hackl, Franz & Hölzl-Leitner, Michael, 2021. "The impact of price adjustment costs on price dispersion in e-commerce," International Journal of Industrial Organization, Elsevier, vol. 77(C).
    11. Federico Ciliberto & GianCarlo Moschini & Edward D. Perry, 2019. "Valuing product innovation: genetically engineered varieties in US corn and soybeans," RAND Journal of Economics, RAND Corporation, vol. 50(3), pages 615-644, September.
    12. Kim, Donghun, 2004. "Market Structure, Price Pass-Through and Welfare with Differentiated Products," Research Reports 25157, University of Connecticut, Food Marketing Policy Center.
    13. Dunn, Abe, 2016. "Health insurance and the demand for medical care: Instrumental variable estimates using health insurer claims data," Journal of Health Economics, Elsevier, vol. 48(C), pages 74-88.
    14. Thomas E. Guerrero & C. Angelo Guevara & Elisabetta Cherchi & Juan de Dios Ortúzar, 2021. "Addressing endogeneity in strategic urban mode choice models," Transportation, Springer, vol. 48(4), pages 2081-2102, August.
    15. Siotis, Georges & Ornaghi, Carmine & Castanheira, Micael, 2019. "Market Definition and Competition Policy Enforcement in the Pharmaceutical Industry," CEPR Discussion Papers 14035, C.E.P.R. Discussion Papers.
    16. Carlos Pérez Montes, 2013. "The impact of interbank and public debt markets on the competition for bank deposits," Working Papers 1319, Banco de España.
    17. Amit Khandelwal, 2010. "The Long and Short (of) Quality Ladders," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 77(4), pages 1450-1476.
    18. Steven T. Berry & Philip A. Haile, 2009. "Nonparametric Identification of Multinomial Choice Demand Models with Heterogeneous Consumers," NBER Working Papers 15276, National Bureau of Economic Research, Inc.
    19. Brooks, Leah & Gendron-Carrier, Nicolas & Rua, Gisela, 2021. "The local impact of containerization," Journal of Urban Economics, Elsevier, vol. 126(C).
    20. Robert Donnelly & Francisco J.R. Ruiz & David Blei & Susan Athey, 2021. "Counterfactual inference for consumer choice across many product categories," Quantitative Marketing and Economics (QME), Springer, vol. 19(3), pages 369-407, December.

    More about this item

    Keywords

    Heterogeneous brand preferences; Social group and consumption context; Random coefficients logit model; C51; D12; L66; M3;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • L66 - Industrial Organization - - Industry Studies: Manufacturing - - - Food; Beverages; Cosmetics; Tobacco
    • M3 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:kap:qmktec:v:10:y:2012:i:3:p:305-333. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.