IDEAS home Printed from https://ideas.repec.org/a/eee/eejocm/v12y2014icp1-9.html
   My bibliography  Save this article

Finding items cannibalization and synergy by BWS data

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1755534514000359
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jocm.2014.08.001?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. 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. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. Louviere,Jordan J. & Hensher,David A. & Swait,Joffre D., 2000. "Stated Choice Methods," Cambridge Books, Cambridge University Press, number 9780521788304, September.
    18. 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.
    19. 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.
    20. 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.
    21. 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.
    22. Lee G. Cooper, 1988. "Competitive Maps: The Structure Underlying Asymmetric Cross Elasticities," Management Science, INFORMS, vol. 34(6), pages 707-723, June.
    23. Lipovetsky, Stan & Conklin, Michael, 2014. "Best-Worst Scaling in analytical closed-form solution," Journal of choice modelling, Elsevier, vol. 10(C), pages 60-68.
    24. Amos Tversky & Itamar Simonson, 1993. "Context-Dependent Preferences," Management Science, INFORMS, vol. 39(10), pages 1179-1189, October.
    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. Lipovetsky, Stan, 2018. "Quantum paradigm of probability amplitude and complex utility in entangled discrete choice modeling," Journal of choice modelling, Elsevier, vol. 27(C), pages 62-73.
    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.

    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. Lipovetsky, Stan, 2018. "Quantum paradigm of probability amplitude and complex utility in entangled discrete choice modeling," Journal of choice modelling, Elsevier, vol. 27(C), pages 62-73.
    2. Haghani, Milad & Bliemer, Michiel C.J. & Hensher, David A., 2021. "The landscape of econometric discrete choice modelling research," Journal of choice modelling, Elsevier, vol. 40(C).
    3. Helen Scarborough & Jeff Bennett, 2012. "Cost–Benefit Analysis and Distributional Preferences," Books, Edward Elgar Publishing, number 14376.
    4. Stan Lipovetsky & Igor Mandel, 2017. "Coefficients of Structural Association," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 16(02), pages 285-313, March.
    5. Miklós Pintér, 2011. "Regression games," Annals of Operations Research, Springer, vol. 186(1), pages 263-274, June.
    6. Lipovetsky, Stan & Conklin, Michael, 2014. "Best-Worst Scaling in analytical closed-form solution," Journal of choice modelling, Elsevier, vol. 10(C), pages 60-68.
    7. Joachim Marti, 2012. "Assessing preferences for improved smoking cessation medications: a discrete choice experiment," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 13(5), pages 533-548, October.
    8. Basu, Debasis & Hunt, John Douglas, 2012. "Valuing of attributes influencing the attractiveness of suburban train service in Mumbai city: A stated preference approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(9), pages 1465-1476.
    9. Solomon Tarfasa & Roy Brouwer, 2013. "Estimation of the public benefits of urban water supply improvements in Ethiopia: a choice experiment," Applied Economics, Taylor & Francis Journals, vol. 45(9), pages 1099-1108, March.
    10. Axsen, Jonn & Mountain, Dean C. & Jaccard, Mark, 2009. "Combining stated and revealed choice research to simulate the neighbor effect: The case of hybrid-electric vehicles," Resource and Energy Economics, Elsevier, vol. 31(3), pages 221-238, August.
    11. De Valck, Jeremy & Vlaeminck, Pieter & Liekens, Inge & Aertsens, Joris & Chen, Wendy & Vranken, Liesbet, 2012. "The sources of preference heterogeneity for nature restoration scenarios," Working Papers 146522, Katholieke Universiteit Leuven, Centre for Agricultural and Food Economics.
    12. Anastassiadis, Friederike & Liebe, Ulf & Musshoff, Oliver, 2012. "Finanzielle Flexibilität In Landwirtschaftlichen Investitionsentscheidungen: Ein Discrete Choice Experiment," 52nd Annual Conference, Stuttgart, Germany, September 26-28, 2012 137142, German Association of Agricultural Economists (GEWISOLA).
    13. Hackbarth, André & Madlener, Reinhard, 2016. "Willingness-to-pay for alternative fuel vehicle characteristics: A stated choice study for Germany," Transportation Research Part A: Policy and Practice, Elsevier, vol. 85(C), pages 89-111.
    14. Siikamaki, Juha & Layton, David F., 2007. "Discrete choice survey experiments: A comparison using flexible methods," Journal of Environmental Economics and Management, Elsevier, vol. 53(1), pages 122-139, January.
    15. Reema Bera & Bhargab Maitra, 2021. "Analyzing Prospective Owners’ Choice Decision towards Plug-in Hybrid Electric Vehicles in Urban India: A Stated Preference Discrete Choice Experiment," Sustainability, MDPI, vol. 13(14), pages 1-24, July.
    16. J Blasch & B van der Kroon & P van Beukering & R Munster & S Fabiani & P Nino & S Vanino, 2022. "Farmer preferences for adopting precision farming technologies: a case study from Italy," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 49(1), pages 33-81.
    17. Fabrice Defever, 2006. "Functional fragmentation and the location of multinational firms in the enlarged Europe," Post-Print halshs-00118808, HAL.
    18. Jose Blandon & Spencer Henson & Towhidul Islam, 2009. "Marketing preferences of small-scale farmers in the context of new agrifood systems: a stated choice model," Agribusiness, John Wiley & Sons, Ltd., vol. 25(2), pages 251-267.
    19. Mariel, Petr & Ayala, Amaya de & Hoyos, David & Abdullah, Sabah, 2013. "Selecting random parameters in discrete choice experiment for environmental valuation: A simulation experiment," Journal of choice modelling, Elsevier, vol. 7(C), pages 44-57.
    20. Cécile Détang-Dessendre & Florence Goffette-Nagot & Virginie Piguet, 2004. "Life-cycle position and migration to urban and rural areas: estimations of a mixed logit model on French data," Working Papers 0403, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.

    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:eee:eejocm:v:12:y:2014:i:c:p:1-9. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/journal-of-choice-modelling .

    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.