IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2312.16927.html
   My bibliography  Save this paper

Development of Choice Model for Brand Evaluation

Author

Listed:
  • Marina Kholod
  • Nikita Mokrenko

Abstract

Consumer choice modeling takes center stage as we delve into understanding how personal preferences of decision makers (customers) for products influence demand at the level of the individual. The contemporary choice theory is built upon the characteristics of the decision maker, alternatives available for the choice of the decision maker, the attributes of the available alternatives and decision rules that the decision maker uses to make a choice. The choice set in our research is represented by six major brands (products) of laundry detergents in the Japanese market. We use the panel data of the purchases of 98 households to which we apply the hierarchical probit model, facilitated by a Markov Chain Monte Carlo simulation (MCMC) in order to evaluate the brand values of six brands. The applied model also allows us to evaluate the tangible and intangible brand values. These evaluated metrics help us to assess the brands based on their tangible and intangible characteristics. Moreover, consumer choice modeling also provides a framework for assessing the environmental performance of laundry detergent brands as the model uses the information on components (physical attributes) of laundry detergents.

Suggested Citation

  • Marina Kholod & Nikita Mokrenko, 2023. "Development of Choice Model for Brand Evaluation," Papers 2312.16927, arXiv.org.
  • Handle: RePEc:arx:papers:2312.16927
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2312.16927
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. John R. Hauser & Glen L. Urban, 1977. "A Normative Methodology for Modeling Consumer Response to Innovation," Operations Research, INFORMS, vol. 25(4), pages 579-619, August.
    2. Michelle Andrews & Xueming Luo & Zheng Fang & Anindya Ghose, 2016. "Mobile Ad Effectiveness: Hyper-Contextual Targeting with Crowdedness," Marketing Science, INFORMS, vol. 35(2), pages 218-233, March.
    3. Tauber, Edward M., 1981. "Brand franchise extension: New product benefits from existing Brand Names," Business Horizons, Elsevier, vol. 24(2), pages 36-41.
    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. Marina Kholod & Nikita Mokrenko & Alberto Celani & Valentina Puglisi, 2023. "Choice Modeling of Laundry Detergent Data for Sustainable Consumption," Sustainability, MDPI, vol. 15(24), pages 1-16, December.
    2. H. R., Ganesha & Aithal, Sreeramana & P., Kirubadevi, 2020. "Experimental Investigation of Cannibalisation by Introducing a Global Brand Abreast Existing Indian Store Brand," MPRA Paper 104028, University Library of Munich, Germany.
    3. Laurent Cavenaile & Pau Roldan-Blanco, 2021. "Advertising, Innovation, and Economic Growth," American Economic Journal: Macroeconomics, American Economic Association, vol. 13(3), pages 251-303, July.
    4. Steven M. Shugan, 2005. "Brand Loyalty Programs: Are They Shams?," Marketing Science, INFORMS, vol. 24(2), pages 185-193.
    5. Sandra J. Milberg, 2001. "Positive Feedback Effects Of Brand Extensions: Expanding Brand Meaning And The Range Of Extendibility," Abante, Escuela de Administracion. Pontificia Universidad Católica de Chile., vol. 4(1), pages 3-35.
    6. Dowling, Katharina & Manchanda, Puneet & Spann, Martin, 2021. "The existence and persistence of the pay-per-use bias in car sharing services," International Journal of Research in Marketing, Elsevier, vol. 38(2), pages 329-342.
    7. Ryo Kato & Takahiro Hoshino & Daisuke Moriwaki & Shintaro Okazaki, 2022. "Mobile Targeting: Exploring the Role of Area Familiarity, Store Knowledge, and Promotional Incentives," Discussion Paper Series DP2022-10, Research Institute for Economics & Business Administration, Kobe University.
    8. Jungju Yu, 2021. "A Model of Brand Architecture Choice: A House of Brands vs. A Branded House," Marketing Science, INFORMS, vol. 40(1), pages 147-167, January.
    9. Ketelaar, Paul E. & Bernritter, Stefan F. & van Woudenberg, Thabo J. & Rozendaal, Esther & Konig, Ruben P. & Hühn, Arief Ernst & Van Gisbergen, Marnix S. & Janssen, Loes, 2018. "“Opening” location-based mobile ads: How openness and location congruency of location-based ads weaken negative effects of intrusiveness on brand choice," Journal of Business Research, Elsevier, vol. 91(C), pages 277-285.
    10. Özge Sýðýrcý & A. Müge Yalçýn, 2010. "Factors Affecting Consumer Evaluations Of Brand Extensions," Bogazici Journal, Review of Social, Economic and Administrative Studies, Bogazici University, Department of Economics, vol. 24(1+2), pages 67-90.
    11. Verhoef, Peter C. & Stephen, Andrew T. & Kannan, P.K. & Luo, Xueming & Abhishek, Vibhanshu & Andrews, Michelle & Bart, Yakov & Datta, Hannes & Fong, Nathan & Hoffman, Donna L. & Hu, Mandy Mantian & No, 2017. "Consumer Connectivity in a Complex, Technology-enabled, and Mobile-oriented World with Smart Products," Journal of Interactive Marketing, Elsevier, vol. 40(C), pages 1-8.
    12. 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.
    13. Cruz Roche, Ignacio, 1997. "Strategic alliances with intangible assets : special reference to brand alllances," DEE - Working Papers. Business Economics. WB 7021, Universidad Carlos III de Madrid. Departamento de Economía de la Empresa.
    14. Lena Steinhoff & Denni Arli & Scott Weaven & Irina V. Kozlenkova, 2019. "Online relationship marketing," Journal of the Academy of Marketing Science, Springer, vol. 47(3), pages 369-393, May.
    15. Ahn, SooKyoung & Kim, HeaJung & Forney, Judith A., 2009. "Co-marketing alliances between heterogeneous industries: Examining perceived match-up effects in product, brand and alliance levels," Journal of Retailing and Consumer Services, Elsevier, vol. 16(6), pages 477-485.
    16. Cloarec, Julien, 2020. "The personalization–privacy paradox in the attention economy," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    17. John R. Hauser & Steven Shugan, 1978. "Intensity Measures of Consumer Preferences," Discussion Papers 291, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
    18. Chaab, Jafar & Salhab, Rabih & Zaccour, Georges, 2022. "Dynamic pricing and advertising in the presence of strategic consumers and social contagion: A mean-field game approach," Omega, Elsevier, vol. 109(C).
    19. Guodong (Gordon) Gao & Lorin M. Hitt, 2012. "Information Technology and Trademarks: Implications for Product Variety," Management Science, INFORMS, vol. 58(6), pages 1211-1226, June.
    20. Henrika Langen & Martin Huber, 2022. "How causal machine learning can leverage marketing strategies: Assessing and improving the performance of a coupon campaign," Papers 2204.10820, arXiv.org, revised Jun 2022.

    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:arx:papers:2312.16927. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.