IDEAS home Printed from https://ideas.repec.org/p/ise/isegwp/wp022022.html
   My bibliography  Save this paper

Details and Big Pictures: Consumer Use of Actual Prices and Price Images When Choosing a Store

Author

Listed:
  • Carlos Lourenco
  • Els Gijsbrechts

Abstract

In this paper, we develop a model of consumer patronage decisions to evaluate the effect of store price images vis-a-vis that of objective basket prices. Within this dual retail price model, the two types of price information are linked through the dynamic formation of price images over time, itself based on actual prices. We show that not accounting for the effect of (dynamic) price perceptions may seriously bias store traffic estimation in response to price changes. Finally, we explore which demographic and shopping characteristics of consumers may explain or shed light on differences in sensitivity to different price information.

Suggested Citation

  • Carlos Lourenco & Els Gijsbrechts, 2022. "Details and Big Pictures: Consumer Use of Actual Prices and Price Images When Choosing a Store," Working Papers Department of Economics 2022/02, ISEG - Lisbon School of Economics and Management, Department of Economics, Universidade de Lisboa.
    • Handle: RePEc:ise:isegwp:wp022022
    as

    Download full text from publisher

    File URL: https://depeco.iseg.ulisboa.pt/wp/wp022022.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Gustav Feichtinger & Alfred Luhmer & Gerhard Sorger, 1988. "Optimal Price and Advertising Policy for a Convenience Goods Retailer," Marketing Science, INFORMS, vol. 7(2), pages 187-201.
    2. Finn, Adam & Louviere, Jordan, 1990. "Shopping-center patronage models : Fashioning a consideration set segmentation solution," Journal of Business Research, Elsevier, vol. 21(3), pages 259-275, November.
    3. Kirthi Kalyanam & Rajiv Lal & Gerd Wolfram, 2006. "Future Store Technologies and Their Impact on Grocery Retailing," Springer Books, in: Manfred Krafft & Murali K. Mantrala (ed.), Retailing in the 21st Century, pages 95-112, Springer.
    4. Finn, Adam & Louviere, Jordan J., 1996. "Shopping center image, consideration, and choice: Anchor store contribution," Journal of Business Research, Elsevier, vol. 35(3), pages 241-251, March.
    5. Tülin Erdem & Michael P. Keane & Baohong Sun, 2008. "A Dynamic Model of Brand Choice When Price and Advertising Signal Product Quality," Marketing Science, INFORMS, vol. 27(6), pages 1111-1125, 11-12.
    6. Tülin Erdem & Michael P. Keane, 1996. "Decision-Making Under Uncertainty: Capturing Dynamic Brand Choice Processes in Turbulent Consumer Goods Markets," Marketing Science, INFORMS, vol. 15(1), pages 1-20.
    7. Alba, Joseph W, et al, 1994. "The Influence of Prior Beliefs, Frequency Cues, and Magnitude Cues on Consumers' Perceptions of Comparative Price Data," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 21(2), pages 219-235, September.
    8. McCulloch, Robert & Rossi, Peter E., 1994. "An exact likelihood analysis of the multinomial probit model," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 207-240.
    9. Andrew T. Ching & Tülin Erdem & Michael P. Keane, 2013. "Learning Models: An Assessment of Progress, Challenges and New Developments," Economics Papers 2013-W07, Economics Group, Nuffield College, University of Oxford.
    10. Gijsbrechts, Els & Campo, Katia & Nisol, Patricia, 2008. "Beyond promotion-based store switching: Antecedents and patterns of systematic multiple-store shopping," International Journal of Research in Marketing, Elsevier, vol. 25(1), pages 5-21.
    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. Jie Bai, 2016. "Melons as Lemons: Asymmetric Information, Consumer Learning and Seller Reputation," Natural Field Experiments 00540, The Field Experiments Website.
    2. Ching, Andrew T. & Erdem, Tülin & Keane, Michael P., 2014. "A simple method to estimate the roles of learning, inventories and category consideration in consumer choice," Journal of choice modelling, Elsevier, vol. 13(C), pages 60-72.
    3. Andrew T. Ching & Tülin Erdem & Michael P. Keane, 2017. "Empirical Models of Learning Dynamics: A Survey of Recent Developments," International Series in Operations Research & Management Science, in: Berend Wierenga & Ralf van der Lans (ed.), Handbook of Marketing Decision Models, edition 2, chapter 0, pages 223-257, Springer.
    4. Xu, Yan, 2017. "Essays on preference formation and home production," Other publications TiSEM b028fd7e-53ba-4ff6-97eb-4, Tilburg University, School of Economics and Management.
    5. Song Lin & Juanjuan Zhang & John R. Hauser, 2015. "Learning from Experience, Simply," Marketing Science, INFORMS, vol. 34(1), pages 1-19, January.
    6. Andrew T. Ching & Tülin Erdem & Michael P. Keane, 2020. "How much do consumers know about the quality of products? Evidence from the diaper market," The Japanese Economic Review, Springer, vol. 71(4), pages 541-569, October.
    7. Guofang Huang & Hong Luo & Jing Xia, 2019. "Invest in Information or Wing It? A Model of Dynamic Pricing with Seller Learning," Management Science, INFORMS, vol. 65(12), pages 5556-5583, December.
    8. Hai Che & Tülin Erdem & T. Sabri Öncü, 2015. "Consumer learning and evolution of consumer brand preferences," Quantitative Marketing and Economics (QME), Springer, vol. 13(3), pages 173-202, September.
    9. Chunhua Wu & Hai Che & Tat Y. Chan & Xianghua Lu, 2015. "The Economic Value of Online Reviews," Marketing Science, INFORMS, vol. 34(5), pages 739-754, September.
    10. van Ewijk, Bernadette J. & Gijsbrechts, Els & Steenkamp, Jan-Benedict E.M., 2022. "The dark side of innovation: How new SKUs affect brand choice in the presence of consumer uncertainty and learning," International Journal of Research in Marketing, Elsevier, vol. 39(4), pages 967-987.
    11. Zhu, Z.;, 2023. "The Value of Patients: Heterogenous Physician Learning and Generic Drug Diffusion," Health, Econometrics and Data Group (HEDG) Working Papers 23/12, HEDG, c/o Department of Economics, University of York.
    12. Mandy Mantian Hu & Sha Yang & Daniel Yi Xu, 2019. "Understanding the Social Learning Effect in Contagious Switching Behavior," Management Science, INFORMS, vol. 65(10), pages 4771-4794, October.
    13. Michał Kot, 2022. "An agent-based model of consumer choice. An evaluation of the strategy of pricing and advertising," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 32(1), pages 73-95.
    14. Lourenço, Carlos J.S. & Gijsbrechts, Els, 2013. "The impact of national brand introductions on hard-discounter image and share-of-wallet," International Journal of Research in Marketing, Elsevier, vol. 30(4), pages 368-382.
    15. Li, Dong & Nagurney, Anna & Yu, Min, 2018. "Consumer learning of product quality with time delay: Insights from spatial price equilibrium models with differentiated products," Omega, Elsevier, vol. 81(C), pages 150-168.
    16. Hai Che & Tülin Erdem & T. Öncü, 2015. "Consumer learning and evolution of consumer brand preferences," Quantitative Marketing and Economics (QME), Springer, vol. 13(3), pages 173-202, September.
    17. Michael P. Keane, 2013. "Panel data discrete choice models of consumer demand," Economics Papers 2013-W08, Economics Group, Nuffield College, University of Oxford.
    18. Haijing Hao & Rema Padman & Baohong Sun & Rahul Telang, 2019. "Modeling social learning on consumers’ long-term usage of a mobile technology: a Bayesian estimation of a Bayesian learning model," Electronic Commerce Research, Springer, vol. 19(1), pages 1-21, March.
    19. Martinovici, A., 2019. "Revealing attention - how eye movements predict brand choice and moment of choice," Other publications TiSEM 7dca38a5-9f78-4aee-bd81-c, Tilburg University, School of Economics and Management.
    20. Andrew Ching & Susumu Imai & Masakazu Ishihara & Neelam Jain, 2012. "A practitioner’s guide to Bayesian estimation of discrete choice dynamic programming models," Quantitative Marketing and Economics (QME), Springer, vol. 10(2), pages 151-196, June.

    More about this item

    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:ise:isegwp:wp022022. 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: Vitor Escaria (email available below). General contact details of provider: https://aquila.iseg.ulisboa.pt/aquila/departamentos/EC .

    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.