IDEAS home Printed from https://ideas.repec.org/p/tin/wpaper/20030079.html
   My bibliography  Save this paper

Which Brands gain Share from which Brands? Inference from Store-Level Scanner Data

Author

Listed:
  • Rutger van Oest

    (Tilburg University)

  • Philip Hans Franses

    (Faculty of Economics, Erasmus Universiteit Rotterdam)

Abstract

Market share models for weekly store-level data are useful to understand competitive structures by delivering own and cross price elasticities. These models can however not be used to examine which brands lose share to which brands during a specificperiod of time. It is for this purpose that we propose a new model, which does allow for such an examination. We illustrate the model for two product categories in two markets, and we show that our model has validity in terms of both in-sample fit and out-of-sample forecasting. We also demonstrate how our model can be used to decompose own and cross price elasticities to get additional insights into the competitive structure.

Suggested Citation

  • Rutger van Oest & Philip Hans Franses, 2003. "Which Brands gain Share from which Brands? Inference from Store-Level Scanner Data," Tinbergen Institute Discussion Papers 03-079/4, Tinbergen Institute.
    • Handle: RePEc:tin:wpaper:20030079
    as

    Download full text from publisher

    File URL: https://papers.tinbergen.nl/03079.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Moshe Givon, 1984. "Variety Seeking Through Brand Switching," Marketing Science, INFORMS, vol. 3(1), pages 1-22.
    2. Greg M. Allenby & Peter E. Rossi, 1991. "Quality Perceptions and Asymmetric Switching Between Brands," Marketing Science, INFORMS, vol. 10(3), pages 185-204.
    3. Chen, Youhua & Kanetkar, Vinay & Weiss, Doyle L., 1994. "Forecasting market shares with disaggregate or pooled data: a comparison of attraction models," International Journal of Forecasting, Elsevier, vol. 10(2), pages 263-276, September.
    4. Bart J. Bronnenberg & Luc Wathieu, 1996. "Asymmetric Promotion Effects and Brand Positioning," Marketing Science, INFORMS, vol. 15(4), pages 379-394.
    5. Randolph E. Bucklin & James M. Lattin, 1991. "A Two-State Model of Purchase Incidence and Brand Choice," Marketing Science, INFORMS, vol. 10(1), pages 24-39.
    6. V. Kumar & Timothy B. Heath, 1990. "A comparative study of market share models using disaggregate data," Post-Print hal-00670544, HAL.
    7. Rajiv Lal & V. Padmanabhan, 1995. "Competitive Response and Equilibria," Marketing Science, INFORMS, vol. 14(3_supplem), pages 101-108.
    8. Robert C. Blattberg & Kenneth J. Wisniewski, 1989. "Price-Induced Patterns of Competition," Marketing Science, INFORMS, vol. 8(4), pages 291-309.
    9. 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.
    10. Wayne S. Desarbo & Ajay K. Manrai, 1992. "A New Multidimensional Scaling Methodology for the Analysis of Asymmetric Proximity Data in Marketing Research," Marketing Science, INFORMS, vol. 11(1), pages 1-20.
    11. McAlister, Leigh & Pessemier, Edgar, 1982. "Variety Seeking Behavior: An Interdisciplinary Review," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 9(3), pages 311-322, December.
    12. Lee G. Cooper, 1988. "Competitive Maps: The Structure Underlying Asymmetric Cross Elasticities," Management Science, INFORMS, vol. 34(6), pages 707-723, June.
    13. Kumar, V. & Heath, Timothy B., 1990. "A comparative study of market share models using disaggregate data," International Journal of Forecasting, Elsevier, vol. 6(2), pages 163-174, July.
    14. Bruce G. S. Hardie & Eric J. Johnson & Peter S. Fader, 1993. "Modeling Loss Aversion and Reference Dependence Effects on Brand Choice," Marketing Science, INFORMS, vol. 12(4), pages 378-394.
    15. Raj Sethuraman & V. Srinivasan & Doyle Kim, 1999. "Asymmetric and Neighborhood Cross-Price Effects: Some Empirical Generalizations," Marketing Science, INFORMS, vol. 18(1), pages 23-41.
    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. Marusia Ivanova, 2007. "Genesis and Evolution of Market Share Predictive Models," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 2, pages 117-148.
    2. Eric Anderson & Nanda Kumar, 2007. "Price competition with repeat, loyal buyers," Quantitative Marketing and Economics (QME), Springer, vol. 5(4), pages 333-359, December.

    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. Rutger Oest, 2005. "Which Brands Gain Share from Which Brands? Inference from Store-Level Scanner Data," Quantitative Marketing and Economics (QME), Springer, vol. 3(3), pages 281-304, September.
    2. Ó González-Benito & M P Martínez-Ruiz & A Molla-Descals, 2009. "Spatial mapping of price competition using logit-type market share models and store-level scanner-data," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(1), pages 52-62, January.
    3. Klapper, Daniel & Herwartz, Helmut, 1998. "Forecasting performance of market share attraction models: A comparison of different models assuming that competitors' actions are forecasts," SFB 373 Discussion Papers 1998,103, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    4. Klapper, Daniel & Herwartz, Helmut, 2000. "Forecasting market share using predicted values of competitive behavior: further empirical results," International Journal of Forecasting, Elsevier, vol. 16(3), pages 399-421.
    5. Raj Sethuraman & V. Srinivasan & Doyle Kim, 1999. "Asymmetric and Neighborhood Cross-Price Effects: Some Empirical Generalizations," Marketing Science, INFORMS, vol. 18(1), pages 23-41.
    6. Csilla Horváth & Dennis Fok, 2013. "Moderating Factors of Immediate, Gross, and Net Cross-Brand Effects of Price Promotions," Marketing Science, INFORMS, vol. 32(1), pages 127-152, July.
    7. Steenkamp, J-B.E.M. & Nijs, V.R. & Hanssens, D.M. & Dekimpe, M.G., 2002. "Competitive Reactions and the Cross-Sales Effects of Advertising and Promotion," ERIM Report Series Research in Management ERS-2002-20-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    8. Sivakumar, K., 2003. "Price-tier competition: Distinguishing between intertier competition and intratier competition," Journal of Business Research, Elsevier, vol. 56(12), pages 947-959, December.
    9. Agarwal, Manoj K., 2002. "Asymmetric price effects in the telecommunications services markets," Journal of Business Research, Elsevier, vol. 55(8), pages 671-677, August.
    10. Baltas, George & Doyle, Peter, 2001. "Random utility models in marketing research: a survey," Journal of Business Research, Elsevier, vol. 51(2), pages 115-125, February.
    11. Greg M. Allenby & Thomas S. Shively & Sha Yang & Mark J. Garratt, 2004. "A Choice Model for Packaged Goods: Dealing with Discrete Quantities and Quantity Discounts," Marketing Science, INFORMS, vol. 23(1), pages 95-108, June.
    12. Serdar Sayman & Stephen J. Hoch & Jagmohan S. Raju, 2002. "Positioning of Store Brands," Marketing Science, INFORMS, vol. 21(4), pages 378-397, June.
    13. Shi, Lijia & Gao, Zhifeng & Chen, Xuqi, 2014. "The cross-price effect on willingness-to-pay estimates in open-ended contingent valuation," Food Policy, Elsevier, vol. 46(C), pages 13-21.
    14. Randolph E. Bucklin & Sunil Gupta, 1999. "Commercial Use of UPC Scanner Data: Industry and Academic Perspectives," Marketing Science, INFORMS, vol. 18(3), pages 247-273.
    15. Chen Zhou & Shrihari Sridhar & Rafael Becerril-Arreola & Tony Haitao Cui & Yan Dong, 2019. "Promotions as competitive reactions to recalls and their consequences," Journal of the Academy of Marketing Science, Springer, vol. 47(4), pages 702-722, July.
    16. Chadwick J. Miller & Daniel C. Brannon & Jim Salas & Martha Troncoza, 2021. "Advertising, incentives, and the upsell: how advertising differentially moderates customer- vs. retailer-directed price incentives’ impact on consumers’ preferences for premium products," Journal of the Academy of Marketing Science, Springer, vol. 49(6), pages 1043-1064, November.
    17. Moon, Sangkil & Voss, Glenn, 2009. "How do price range shoppers differ from reference price point shoppers?," Journal of Business Research, Elsevier, vol. 62(1), pages 31-38, January.
    18. Kumar, V. & Pereira, Arun, 1997. "Assessing the Competitive Impact of Type, Timing, Frequency, and Magnitude of Retail Promotions," Journal of Business Research, Elsevier, vol. 40(1), pages 1-13, September.
    19. Necati Tereyağoğlu & Peter S. Fader & Senthil Veeraraghavan, 2018. "Multiattribute Loss Aversion and Reference Dependence: Evidence from the Performing Arts Industry," Management Science, INFORMS, vol. 64(1), pages 421-436, January.
    20. Deleersnyder, B. & Dekimpe, M.G. & Steenkamp, J.E.B.M. & Koll, O., 2007. "Win-win strategies at discount stores," Other publications TiSEM 34fbe624-0ee7-4c52-b640-7, Tilburg University, School of Economics and Management.

    More about this item

    Keywords

    competitive structure; elasticity decomposition; market shares; share-switching; store-level scanner data;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:tin:wpaper:20030079. 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: Tinbergen Office +31 (0)10-4088900 (email available below). General contact details of provider: https://edirc.repec.org/data/tinbenl.html .

    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.