IDEAS home Printed from https://ideas.repec.org/a/now/fntmkt/1700000060.html
   My bibliography  Save this article

Structural Models of the Prescription Drug Market

Author

Listed:
  • Iacobucci, Dawn

Abstract

This monograph describes the marketing research that has been published in the top marketing journals since their inception relating to health care, broadly defined. Over 1,000 articles are summarized across the chapters relating to consumer behavior and food, consumer behavior and other consumption, and business marketing issues. Research from outside of marketing is also briefly reviewed. This monograph celebrates the research that has been accomplished and closes with suggestions for future research.

Suggested Citation

  • Iacobucci, Dawn, 2019. "Structural Models of the Prescription Drug Market," Foundations and Trends(R) in Marketing, now publishers, vol. 13(2-4), pages 1-77–529, December.
    • Handle: RePEc:now:fntmkt:1700000060
    DOI: 10.1561/1700000060
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1561/1700000060
    Download Restriction: no
    File URL: https://libkey.io/10.1561/1700000060?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. Nan Yang, 2018. "An Empirically Tractable Dynamic Oligopoly Model: Application to Store Entry and Exit in Dutch Grocery Retail," Marketing Science, INFORMS, vol. 37(6), pages 1029-1049, November.
    2. Juanjuan Zhang, 2010. "The Sound of Silence: Observational Learning in the U.S. Kidney Market," Marketing Science, INFORMS, vol. 29(2), pages 315-335, 03-04.
    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. Liang Guo & Xiangyi Meng, 2015. "Digital Content Provision and Optimal Copyright Protection," Management Science, INFORMS, vol. 61(5), pages 1183-1196, May.
    2. Tat Y. Chan & Jia Li & Lamar Pierce, 2014. "Learning from Peers: Knowledge Transfer and Sales Force Productivity Growth," Marketing Science, INFORMS, vol. 33(4), pages 463-484, July.
    3. Vishal Narayan & Vithala R. Rao & Carolyne Saunders, 2011. "How Peer Influence Affects Attribute Preferences: A Bayesian Updating Mechanism," Marketing Science, INFORMS, vol. 30(2), pages 368-384, 03-04.
    4. Stephanie De Mel & Kaivan Munshi & Soenje Reiche & Hamid Sabourian, 2021. "Herding with Heterogeneous Ability: An Application to Organ Transplantation," Cowles Foundation Discussion Papers 2308, Cowles Foundation for Research in Economics, Yale University.
    5. Anna K. Edenbrandt & Christian Gamborg & Bo Jellesmark Thorsen, 2020. "Observational learning in food choices: The effect of product familiarity and closeness of peers," Agribusiness, John Wiley & Sons, Ltd., vol. 36(3), pages 482-498, June.
    6. Liangfei Qiu & Arunima Chhikara & Asoo Vakharia, 2021. "Multidimensional Observational Learning in Social Networks: Theory and Experimental Evidence," Information Systems Research, INFORMS, vol. 32(3), pages 876-894, September.
    7. 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.
    8. Yan Huang & Param Vir Singh & Kannan Srinivasan, 2014. "Crowdsourcing New Product Ideas Under Consumer Learning," Management Science, INFORMS, vol. 60(9), pages 2138-2159, September.
    9. Catherine Tucker & Juanjuan Zhang, 2011. "How Does Popularity Information Affect Choices? A Field Experiment," Management Science, INFORMS, vol. 57(5), pages 828-842, May.
    10. Jurui Zhang & Yong Liu & Yubo Chen, 2015. "Social Learning in Networks of Friends versus Strangers," Marketing Science, INFORMS, vol. 34(4), pages 573-589, July.
    11. Nikhil Agarwal & Itai Ashlagi & Michael A. Rees & Paulo Somaini & Daniel Waldinger, 2021. "Equilibrium Allocations Under Alternative Waitlist Designs: Evidence From Deceased Donor Kidneys," Econometrica, Econometric Society, vol. 89(1), pages 37-76, January.
    12. 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.
    13. André Bonfrer & Pradeep K. Chintagunta & John H. Roberts & David Corkindale, 2020. "Assessing the Sales Impact of Plain Packaging Regulation for Cigarettes: Evidence from Australia," Marketing Science, INFORMS, vol. 39(1), pages 234-252, January.
    14. Dina Mayzlin & Hema Yoganarasimhan, 2012. "Link to Success: How Blogs Build an Audience by Promoting Rivals," Management Science, INFORMS, vol. 58(9), pages 1651-1668, September.
    15. Shijie Lu & Dai Yao & Xingyu Chen & Rajdeep Grewal, 2021. "Do Larger Audiences Generate Greater Revenues Under Pay What You Want? Evidence from a Live Streaming Platform," Marketing Science, INFORMS, vol. 40(5), pages 964-984, September.
    16. Zheyin (Jane) Gu & Yunchuan Liu, 2014. "Consumer Learning on Social Networks and Retailer Digital Platform Strategies Access," Working Papers 14-02, NET Institute.
    17. Yuetao Gao, 2018. "On the Use of Overt Anti-Counterfeiting Technologies," Marketing Science, INFORMS, vol. 37(3), pages 403-424, May.
    18. repec:wyi:journl:002151 is not listed on IDEAS
    19. Qiaowei Shen & Ping Xiao, 2014. "McDonald's and KFC in China: Competitors or Companions?," Marketing Science, INFORMS, vol. 33(2), pages 287-307, March.
    20. Dmitri Kuksov & Kangkang Wang, 2013. "A Model of the "It" Products in Fashion," Marketing Science, INFORMS, vol. 32(1), pages 51-69, July.

    More about this item

    Keywords

    Health care marketing; marketing research;

    JEL classification:

    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing

    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:now:fntmkt:1700000060. 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: Lucy Wiseman (email available below). General contact details of provider: http://www.nowpublishers.com/ .

    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.