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Finding items cannibalization and synergy by BWS data

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  • Lipovetsky, Stan
  • Conklin, Michael

Abstract

Best-Worst Scaling (BWS) modeling is widely used for finding probabilities of choice among multiple items. The paper considers how to apply BWS data to another problem – of finding the items׳ cannibalization and synergy. For a product of primary interest, we estimate its probability to be chosen as the best one out of all the data, and also conditionally to each product׳s presence or absence. For a given product, each other one behaves as a catalyzer or inhibitor of the choice. Constructing the entire matrix of such relations for all the products, we compare its symmetrical elements for each pair of products. It shows which pairs of products are mutually synergic, or complementary, so their chances to be chosen as the best ones are higher in the presence of each other. In other cases, the products can be of negative impact on one another, so one is a cannibalizer of another; or both products suppress each other. Estimations on real marketing data are considered, including the Shapley value for key driver analysis.

Suggested Citation

  • Lipovetsky, Stan & Conklin, Michael, 2014. "Finding items cannibalization and synergy by BWS data," Journal of choice modelling, Elsevier, vol. 12(C), pages 1-9.
    • Handle: RePEc:eee:eejocm:v:12:y:2014:i:c:p:1-9
    DOI: 10.1016/j.jocm.2014.08.001
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    1. Brownstone, David & Train, Kenneth, 1998. "Forecasting new product penetration with flexible substitution patterns," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 109-129, November.
    2. Hausman, Jerry & McFadden, Daniel, 1984. "Specification Tests for the Multinomial Logit Model," Econometrica, Econometric Society, vol. 52(5), pages 1219-1240, September.
    3. Swait, Joffre, 2001. "Choice set generation within the generalized extreme value family of discrete choice models," Transportation Research Part B: Methodological, Elsevier, vol. 35(7), pages 643-666, August.
    4. Wernerfelt, Birger, 1995. "A Rational Reconstruction of the Compromise Effect: Using Market Data to Infer Utilities," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 21(4), pages 627-633, March.
    5. A. S. C. Ehrenberg, 1959. "The Pattern of Consumer Purchases," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 8(1), pages 26-41, March.
    6. Louviere, Jordan & Lings, Ian & Islam, Towhidul & Gudergan, Siegfried & Flynn, Terry, 2013. "An introduction to the application of (case 1) best–worst scaling in marketing research," International Journal of Research in Marketing, Elsevier, vol. 30(3), pages 292-303.
    7. Louviere,Jordan J. & Hensher,David A. & Swait,Joffre D. With contributions by-Name:Adamowicz,Wiktor, 2000. "Stated Choice Methods," Cambridge Books, Cambridge University Press, number 9780521788304, October.
    8. Lipovetsky, Stan & Conklin, W. Michael, 2006. "Data aggregation and Simpson's paradox gauged by index numbers," European Journal of Operational Research, Elsevier, vol. 172(1), pages 334-351, July.
    9. Stan Lipovetsky & Michael Conklin, 2001. "Analysis of regression in game theory approach," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 17(4), pages 319-330, October.
    10. Adrian Vasile & Carmen Eugenia Costea & Tania Georgia Viciu, 2012. "An Evolutionary Game Theory Approach To Market Competition And Cooperation," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 15(supp0), pages 1-15.
    11. Stan Lipovetsky, 2008. "Surf — Structural Unduplicated Reach And Frequency: Latent Class Turf And Shapley Value Analyses," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 7(02), pages 203-216.
    12. Asher Tishler & Stan Lipovetsky, 1997. "The Flexible Ces-Gbc Family Of Cost Functions: Derivation And Application," The Review of Economics and Statistics, MIT Press, vol. 79(4), pages 638-646, November.
    13. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387, October.
    14. Conklin, Michael & Powaga, Ken & Lipovetsky, Stan, 2004. "Customer satisfaction analysis: Identification of key drivers," European Journal of Operational Research, Elsevier, vol. 154(3), pages 819-827, May.
    15. W. Michael Conklin & Stan Lipovetsky, 2005. "Marketing Decision Analysis By Turf And Shapley Value," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 4(01), pages 5-19.
    16. Jordan J. Louviere, 2013. "Modeling single individuals: the journey from psych lab to the app store," Chapters, in: Stephane Hess & Andrew Daly (ed.), Choice Modelling, chapter 1, pages 1-47, Edward Elgar Publishing.
    17. Asher Tishler & Stan Lipovetsky, 2000. "A globally concave, monotone and flexible cost function: derivation and application," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 16(4), pages 279-296, October.
    18. Lee G. Cooper, 1988. "Competitive Maps: The Structure Underlying Asymmetric Cross Elasticities," Management Science, INFORMS, vol. 34(6), pages 707-723, June.
    19. Lipovetsky, Stan & Conklin, Michael, 2014. "Best-Worst Scaling in analytical closed-form solution," Journal of choice modelling, Elsevier, vol. 10(C), pages 60-68.
    20. Marley, A. A. J., 1991. "Context dependent probabilistic choice models based on measures of binary advantage," Mathematical Social Sciences, Elsevier, vol. 21(3), pages 201-231, June.
    21. Amos Tversky & Itamar Simonson, 1993. "Context-Dependent Preferences," Management Science, INFORMS, vol. 39(10), pages 1179-1189, October.
    22. Timmermans, Harry & Borgers, Aloys & van der Waerden, Peter, 1991. "Mother logit analysis of substitution effects in consumer shopping destination choice," Journal of Business Research, Elsevier, vol. 23(4), pages 311-323, December.
    23. Jordan Louviere, 2006. "What You Don’t Know Might Hurt You: Some Unresolved Issues in the Design and Analysis of Discrete Choice Experiments," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 34(1), pages 173-188, May.
    24. David A. Schweidel & Natasha Zhang Foutz & Robin J. Tanner, 2014. "Synergy or Interference: The Effect of Product Placement on Commercial Break Audience Decline," Marketing Science, INFORMS, vol. 33(6), pages 763-780, November.
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    Cited by:

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    2. Marije Schaafsma & Roy Brouwer, 2020. "Substitution Effects in Spatial Discrete Choice Experiments," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 75(2), pages 323-349, February.

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