IDEAS home Printed from https://ideas.repec.org/a/inm/ormksc/v30y2011i1p61-73.html
   My bibliography  Save this article

Identifying Unmet Demand

Author

Listed:
  • Sandeep R. Chandukala

    (Kelley School of Business, Indiana University, Bloomington, Indiana 47405)

  • Yancy D. Edwards

    (School of Business, Saint Leo University, Saint Leo, Florida 33574)

  • Greg M. Allenby

    (Fisher College of Business, Ohio State University, Columbus, Ohio 43210)

Abstract

Brand preferences and marketplace demand are a reflection of the importance of underlying needs of consumers and the efficacy of product attributes for delivering value. Dog owners, for example, may look to dog foods to provide specific benefits for their pets (e.g., shiny coats) that may not be available from current offerings. An analysis of consumer wants for these consumers would reveal weak demand for product attributes resulting from low efficacy, despite the presence of strong latent interest. The challenge in identifying such unmet demand is in distinguishing it from other reasons for weak preference, such as general noninterest in the category and heterogeneous tastes. We propose a model for separating out these effects within the context of conjoint analysis, and we demonstrate its value with data from a national survey of toothpaste preferences. Implications for product development and reformulation are explored.

Suggested Citation

  • Sandeep R. Chandukala & Yancy D. Edwards & Greg M. Allenby, 2011. "Identifying Unmet Demand," Marketing Science, INFORMS, vol. 30(1), pages 61-73, 01-02.
    • Handle: RePEc:inm:ormksc:v:30:y:2011:i:1:p:61-73
    DOI: 10.1287/mksc.1100.0589
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mksc.1100.0589
    Download Restriction: no
    File URL: https://libkey.io/10.1287/mksc.1100.0589?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
    ---><---

    References listed on IDEAS

    as
    1. Paul E. Green & Abba M. Krieger, 1995. "Attribute Importance Weights Modification in Assessing a Brand's Competitive Potential," Marketing Science, INFORMS, vol. 14(3), pages 253-270.
    2. Ravi Anupindi & Maqbool Dada & Sachin Gupta, 1998. "Estimation of Consumer Demand with Stock-Out Based Substitution: An Application to Vending Machine Products," Marketing Science, INFORMS, vol. 17(4), pages 406-423.
    3. Green, Paul E & Srinivasan, V, 1978. "Conjoint Analysis in Consumer Research: Issues and Outlook," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 5(2), pages 103-123, Se.
    4. 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.
    5. Brucks, Merrie, 1985. "The Effects of Product Class Knowledge on Information Search Behavior," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 12(1), pages 1-16, June.
    6. Rinus Haaijer & Michel Wedel & Marco Vriens & Tom Wansbeek, 1998. "Utility Covariances and Context Effects in Conjoint MNP Models," Marketing Science, INFORMS, vol. 17(3), pages 236-252.
    7. Dan Horsky & Sanjog Misra & Paul Nelson, 2006. "Observed and Unobserved Preference Heterogeneity in Brand-Choice Models," Marketing Science, INFORMS, vol. 25(4), pages 322-335, 07-08.
    8. Kirthi Kalyanam & Sharad Borle & Peter Boatwright, 2007. "Deconstructing Each Item's Category Contribution," Marketing Science, INFORMS, vol. 26(3), pages 327-341, 05-06.
    9. Peter J. Lenk & Wayne S. DeSarbo & Paul E. Green & Martin R. Young, 1996. "Hierarchical Bayes Conjoint Analysis: Recovery of Partworth Heterogeneity from Reduced Experimental Designs," Marketing Science, INFORMS, vol. 15(2), pages 173-191.
    10. Bettman, James R & Park, C Whan, 1980. "Effects of Prior Knowledge and Experience and Phase of the Choice Process on Consumer Decision Processes: A Protocol Analysis," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 7(3), pages 234-248, December.
    11. Duncan Fong & Wayne DeSarbo, 2007. "A Bayesian methodology for simultaneously detecting and estimating regime change points and variable selection in multiple regression models for marketing research," Quantitative Marketing and Economics (QME), Springer, vol. 5(4), pages 427-453, December.
    12. Peter Lenk & Wayne DeSarbo, 2000. "Bayesian inference for finite mixtures of generalized linear models with random effects," Psychometrika, Springer;The Psychometric Society, vol. 65(1), pages 93-119, March.
    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. Johannes Reichl & Sylvia Frühwirth-Schnatter, 2012. "A censored random coefficients model for the detection of zero willingness to pay," Quantitative Marketing and Economics (QME), Springer, vol. 10(2), pages 259-281, June.
    2. Hyowon Kim & Greg M. Allenby, 2022. "Integrating Textual Information into Models of Choice and Scaled Response Data," Marketing Science, INFORMS, vol. 41(4), pages 815-830, July.
    3. Marc R. Dotson & Joachim Büschken & Greg M. Allenby, 2020. "Explaining Preference Heterogeneity with Mixed Membership Modeling," Marketing Science, INFORMS, vol. 39(2), pages 407-426, March.
    4. Dellaert, Benedict G.C. & Arentze, Theo & Horeni, Oliver & Timmermans, Harry J.P., 2017. "Deriving attribute utilities from mental representations of complex decisions," Journal of choice modelling, Elsevier, vol. 22(C), pages 24-38.
    5. Wang, Xinfang (Jocelyn) & Curry, David J., 2012. "A robust approach to the share-of-choice product design problem," Omega, Elsevier, vol. 40(6), pages 818-826.

    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. Robert Zeithammer & Peter Lenk, 2006. "Bayesian estimation of multivariate-normal models when dimensions are absent," Quantitative Marketing and Economics (QME), Springer, vol. 4(3), pages 241-265, September.
    2. Olivier Toubia & Duncan I. Simester & John R. Hauser & Ely Dahan, 2003. "Fast Polyhedral Adaptive Conjoint Estimation," Marketing Science, INFORMS, vol. 22(3), pages 273-303.
    3. repec:cup:judgdm:v:4:y:2009:i:3:p:200-213 is not listed on IDEAS
    4. Peter E. Rossi & Greg M. Allenby, 2003. "Bayesian Statistics and Marketing," Marketing Science, INFORMS, vol. 22(3), pages 304-328, July.
    5. Oded Netzer & Olivier Toubia & Eric Bradlow & Ely Dahan & Theodoros Evgeniou & Fred Feinberg & Eleanor Feit & Sam Hui & Joseph Johnson & John Liechty & James Orlin & Vithala Rao, 2008. "Beyond conjoint analysis: Advances in preference measurement," Marketing Letters, Springer, vol. 19(3), pages 337-354, December.
    6. Anja Dieckmann & Katrin Dippold & Holger Dietrich, 2009. "Compensatory versus noncompensatory models for predicting consumer preferences," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 4(3), pages 200-213, April.
    7. Srinivasan, V. Seenu & Netzer, Oded, 2007. "Adaptive Self-Explication of Multi-attribute Preferences," Research Papers 1979, Stanford University, Graduate School of Business.
    8. Meng, Bo & Choi, Kyuhwan, 2016. "The role of authenticity in forming slow tourists' intentions: Developing an extended model of goal-directed behavior," Tourism Management, Elsevier, vol. 57(C), pages 397-410.
    9. John Liechty & Duncan Fong & Eelko Huizingh & Arnaud Bruyn, 2008. "Hierarchical Bayesian conjoint models incorporating measurement uncertainty," Marketing Letters, Springer, vol. 19(2), pages 141-155, June.
    10. Teichert, Thorsten Andreas, 1997. "Schätzgenauigkeit von Conjoint-Analysen," Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel 444, Christian-Albrechts-Universität zu Kiel, Institut für Betriebswirtschaftslehre.
    11. Shao, Wei & Lye, Ashley & Rundle-Thiele, Sharyn, 2009. "Different strokes for different folks: A method to accommodate decision -making heterogeneity," Journal of Retailing and Consumer Services, Elsevier, vol. 16(6), pages 495-501.
    12. Theodoros Evgeniou & Constantinos Boussios & Giorgos Zacharia, 2005. "Generalized Robust Conjoint Estimation," Marketing Science, INFORMS, vol. 24(3), pages 415-429, May.
    13. Ozer, Muammer, 2011. "Understanding the impacts of product knowledge and product type on the accuracy of intentions-based new product predictions," European Journal of Operational Research, Elsevier, vol. 211(2), pages 359-369, June.
    14. Yu-Cheng Ku & Tsun-Feng Chiang & Sheng-Mao Chang, 2017. "Is what you choose what you want?—outlier detection in choice-based conjoint analysis," Marketing Letters, Springer, vol. 28(1), pages 29-42, March.
    15. Paul E. Green & Abba M. Krieger & Yoram Wind, 2001. "Thirty Years of Conjoint Analysis: Reflections and Prospects," Interfaces, INFORMS, vol. 31(3_supplem), pages 56-73, June.
    16. Bosul Yoo & Sotaro Katsumata & Takeyasu Ichikohji, 2017. "The Impact of Customer Orientation on Quantity and Quality of User-Generated Content: A Multi-Country Case Study of Mobile Applications," Discussion Papers in Economics and Business 17-12, Osaka University, Graduate School of Economics.
    17. Davies, Antony & Cline, Thomas W., 2005. "A consumer behavior approach to modeling monopolistic competition," Journal of Economic Psychology, Elsevier, vol. 26(6), pages 797-826, December.
    18. Hein, Maren & Goeken, Nils & Kurz, Peter & Steiner, Winfried J., 2022. "Using Hierarchical Bayes draws for improving shares of choice predictions in conjoint simulations: A study based on conjoint choice data," European Journal of Operational Research, Elsevier, vol. 297(2), pages 630-651.
    19. Naderi, Iman & Paswan, Audhesh K. & Guzman, Francisco, 2018. "Beyond the shadow of a doubt: The effect of consumer knowledge on restaurant evaluation," Journal of Retailing and Consumer Services, Elsevier, vol. 45(C), pages 221-229.
    20. Giuseppe Festa & Giada Mainolfi, 2013. "Il comportamento del consumatore/degustatore nel Wine Marketing. Una prospettiva per l'Italian Way of Wine," ESPERIENZE D'IMPRESA, FrancoAngeli Editore, vol. 2013(1), pages 35-57.
    21. Adriane Hartmann & Henrik Sattler, 2004. "Wie robust sind Methoden zur Präferenzmessung?," Schmalenbach Journal of Business Research, Springer, vol. 56(1), pages 3-22, February.

    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:inm:ormksc:v:30:y:2011:i:1:p:61-73. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.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.