IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v214y2011i2p340-347.html
   My bibliography  Save this article

The nested consideration model: Investigating dynamic store consideration sets and store competition

Author

Listed:
  • Pancras, Joseph

Abstract

The nested logit model has been widely used to study nested choice. A typical example of such nested choice is store patronage and brand choice. An important limitation of the nested logit model is that it assumes that all alternatives at both levels of the nest are available in the choice set of the consumer. While there is a wide literature on the incorporation of restricted choice sets into the logit model, the logical extension of this analysis to nested restricted choice sets has not been pursued in the literature. In this study we develop a nested consideration model that integrates store choice and brand choice incorporating the formation of dynamic restricted choice sets of both stores and brands. We term the model the nested consideration model and derive the related probabilities in a manner analogous to the well-known nested logit model. In an empirical illustration, we find that the nested consideration model shows better prediction than nested logit models (with the same explanatory variables). We find that it is important to account for dynamic store consideration sets rather than static sets or store loyalty measures. We also conduct simulations to demonstrate the importance of the nested consideration set model for correct pricing and store location decisions of business managers.

Suggested Citation

  • Pancras, Joseph, 2011. "The nested consideration model: Investigating dynamic store consideration sets and store competition," European Journal of Operational Research, Elsevier, vol. 214(2), pages 340-347, October.
  • Handle: RePEc:eee:ejores:v:214:y:2011:i:2:p:340-347
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221711003717
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. Joseph Pancras, 2010. "A Framework to Determine the Value of Consumer Consideration Set Information for Firm Pricing Strategies," Computational Economics, Springer;Society for Computational Economics, vol. 35(3), pages 269-300, March.
    2. Baltas, George, 2004. "A model for multiple brand choice," European Journal of Operational Research, Elsevier, vol. 154(1), pages 144-149, April.
    3. David R. Bell & James M. Lattin, 1998. "Shopping Behavior and Consumer Preference for Store Price Format: Why “Large Basket” Shoppers Prefer EDLP," Marketing Science, INFORMS, vol. 17(1), pages 66-88.
    4. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387.
    5. Kalouptsidis, N. & Koutroumbas, K. & Psaraki, V., 2007. "Classification methods for random utility models with i.i.d. disturbances under the most probable alternative rule," European Journal of Operational Research, Elsevier, vol. 176(3), pages 1778-1794, February.
    6. A. Stewart Fotheringham, 1988. "Note—Consumer Store Choice and Choice Set Definition," Marketing Science, INFORMS, vol. 7(3), pages 299-310.
    7. P. K. Kannan & Gordon P. Wright, 1991. "Modeling and Testing Structured Markets: A Nested Logit Approach," Marketing Science, INFORMS, vol. 10(1), pages 58-82.
    8. Shlomo Bekhor & Moshe Ben-Akiva & M. Ramming, 2006. "Evaluation of choice set generation algorithms for route choice models," Annals of Operations Research, Springer, vol. 144(1), pages 235-247, April.
    9. Schön, Cornelia, 2010. "Optimal dynamic price selection under attraction choice models," European Journal of Operational Research, Elsevier, vol. 205(3), pages 650-660, September.
    Full references (including those not matched with items on IDEAS)

    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. Suel, Esra & Polak, John W., 2017. "Development of joint models for channel, store, and travel mode choice: Grocery shopping in London," Transportation Research Part A: Policy and Practice, Elsevier, vol. 99(C), pages 147-162.
    2. Sutthipong Meeyai, 2015. "Modeling Store Patronage: A Systematic Review," International Conference on Marketing and Business Development Journal, The Bucharest University of Economic Studies, vol. 1(1), pages 40-48, July.
    3. Printezis, Iryna & Grebitus, Carola, 2018. "Marketing Channels for Local Food," Ecological Economics, Elsevier, vol. 152(C), pages 161-171.
    4. Bhat, Chandra R., 2005. "A multiple discrete-continuous extreme value model: formulation and application to discretionary time-use decisions," Transportation Research Part B: Methodological, Elsevier, vol. 39(8), pages 679-707, September.
    5. Kim, Chul & Jun, Duk Bin & Park, Sungho, 2018. "Capturing flexible correlations in multiple-discrete choice outcomes using copulas," International Journal of Research in Marketing, Elsevier, vol. 35(1), pages 34-59.
    6. Richards, Timothy J. & Hamilton, Stephen F. & Yonezawa, Koichi, 2018. "Retail Market Power in a Shopping Basket Model of Supermarket Competition," Journal of Retailing, Elsevier, vol. 94(3), pages 328-342.
    7. Guyt, Jonne & Gijsbrechts, Els, 2018. "On consumer choice patterns and the net impact of feature promotions," International Journal of Research in Marketing, Elsevier, vol. 35(3), pages 490-508.
    8. Bhat, Chandra R., 2008. "The multiple discrete-continuous extreme value (MDCEV) model: Role of utility function parameters, identification considerations, and model extensions," Transportation Research Part B: Methodological, Elsevier, vol. 42(3), pages 274-303, March.
    9. Sofia Berto Villas-Boas, 2007. "Vertical Relationships between Manufacturers and Retailers: Inference with Limited Data," Review of Economic Studies, Oxford University Press, vol. 74(2), pages 625-652.
    10. Anoop Kumar Gupta & A.V. Shukla, 2015. "Store Choice Behaviour for Consumer Durables in NCT-Delhi," Paradigm, , vol. 19(2), pages 152-169, December.
    11. Yina Lu & Andrés Musalem & Marcelo Olivares & Ariel Schilkrut, 2013. "Measuring the Effect of Queues on Customer Purchases," Management Science, INFORMS, vol. 59(8), pages 1743-1763, August.
    12. Yonezawa, Koichi & Richards, Timothy J., 2016. "Competitive Package Size Decisions," Journal of Retailing, Elsevier, vol. 92(4), pages 445-469.
    13. A. Gürhan Kök & Yi Xu, 2011. "Optimal and Competitive Assortments with Endogenous Pricing Under Hierarchical Consumer Choice Models," Management Science, INFORMS, vol. 57(9), pages 1546-1563, February.
    14. Kim, Hyunchul & Kim, Kyoo il, 2017. "Estimating store choices with endogenous shopping bundles and price uncertainty," International Journal of Industrial Organization, Elsevier, vol. 54(C), pages 1-36.
    15. Yuri Park & Hyunnam Kim & Jongsu Lee, 2009. "Model for Studying Commodity Bundling with a Focus on Consumer Preference," TEMEP Discussion Papers 200935, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Nov 2009.
    16. Syed Akif Hasan & Hammad Ur Rehman, 2007. "Relationship between Store Characteristics and Store Choice," South Asian Journal of Management Sciences (SAJMS), Iqra University, Iqra University, vol. 1(1), pages 1-10, Spring.
    17. Teller, Christoph & Reutterer, Thomas, 2008. "The evolving concept of retail attractiveness: What makes retail agglomerations attractive when customers shop at them?," Journal of Retailing and Consumer Services, Elsevier, vol. 15(3), pages 127-143.
    18. Bonnet, Céline & Richards, Timothy J., 2016. "Models of Consumer Demand for Differentiated Products," TSE Working Papers 16-741, Toulouse School of Economics (TSE).
    19. Timothy J. Richards & Stephen F. Hamilton & Koichi Yonezawa, 2017. "Variety and the Cost of Search in Supermarket Retailing," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 50(3), pages 263-285, May.
    20. Papola, Andrea & Tinessa, Fiore & Marzano, Vittorio, 2018. "Application of the Combination of Random Utility Models (CoRUM) to route choice," Transportation Research Part B: Methodological, Elsevier, vol. 111(C), pages 304-326.

    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:ejores:v:214:y:2011:i:2:p:340-347. 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.elsevier.com/locate/eor .

    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.