Choice Modeling of Laundry Detergent Data for Sustainable Consumption
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Oded Netzer & James M. Lattin & V. Srinivasan, 2008. "A Hidden Markov Model of Customer Relationship Dynamics," Marketing Science, INFORMS, vol. 27(2), pages 185-204, 03-04.
- He, Junnan & Calder, Bobby J., 2020.
"The experimental evaluation of brand strength and brand value,"
Journal of Business Research, Elsevier, vol. 115(C), pages 194-202.
- Junnan He & Bobby Calder, 2020. "The Experimental Evaluation of Brand Strength and Brand Value," Post-Print hal-03878387, HAL.
- Junnan He & Bobby Calder, 2020. "The Experimental Evaluation of Brand Strength and Brand Value," SciencePo Working papers Main hal-03878387, HAL.
- Maria Elena Saija & Sara Daniotti & Diego Bosco & Ilaria Re, 2023. "A Choice Experiment Model for Sustainable Consumer Goods: A Systematic Literature Review and Workflow Design," Sustainability, MDPI, vol. 15(17), pages 1-22, September.
- Tauber, Edward M., 1981. "Brand franchise extension: New product benefits from existing Brand Names," Business Horizons, Elsevier, vol. 24(2), pages 36-41.
- 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.
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.- 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.
- Marina Kholod & Nikita Mokrenko, 2023. "Development of Choice Model for Brand Evaluation," Papers 2312.16927, arXiv.org.
- 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.
- James Agarwal & Wayne DeSarbo & Naresh K. Malhotra & Vithala Rao, 2015. "An Interdisciplinary Review of Research in Conjoint Analysis: Recent Developments and Directions for Future Research," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 2(1), pages 19-40, March.
- Yanwen Wang & Chunhua Wu & Ting Zhu, 2019. "Mobile Hailing Technology and Taxi Driving Behaviors," Marketing Science, INFORMS, vol. 38(5), pages 734-755, September.
- Francesca Bassi & Fulvia Pennoni & Luca Rossetto, 2020. "The Italian market of sparkling wines: Latent variable models for brand positioning, customer loyalty, and transitions across brands' preferences," Agribusiness, John Wiley & Sons, Ltd., vol. 36(4), pages 542-567, October.
- Arun Gopalakrishnan & Zhenling Jiang & Yulia Nevskaya & Raphael Thomadsen, 2021. "Can Non-tiered Customer Loyalty Programs Be Profitable?," Marketing Science, INFORMS, vol. 40(3), pages 508-526, May.
- Durango-Cohen, Elizabeth J., 2013. "Modeling contribution behavior in fundraising: Segmentation analysis for a public broadcasting station," European Journal of Operational Research, Elsevier, vol. 227(3), pages 538-551.
- 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.
- Pau Roldan & Laurent Cavenaile, 2016. "Advertising, Innovation and Economic Growth," 2016 Meeting Papers 150, Society for Economic Dynamics.
- Laurent Cavenaile & Pau Roldan, 2019. "Advertising, innovation and economic growth," Working Papers 1902, Banco de España.
- Bernhard Baumgartner & Daniel Guhl & Thomas Kneib & Winfried J. Steiner, 2018. "Flexible estimation of time-varying effects for frequently purchased retail goods: a modeling approach based on household panel data," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 40(4), pages 837-873, October.
- Kinshuk Jerath & Anuj Kumar & Serguei Netessine, 2015. "An Information Stock Model of Customer Behavior in Multichannel Customer Support Services," Manufacturing & Service Operations Management, INFORMS, vol. 17(3), pages 368-383, July.
- Kappe, Eelco & Stadler Blank, Ashley & DeSarbo, Wayne S., 2018. "A random coefficients mixture hidden Markov model for marketing research," International Journal of Research in Marketing, Elsevier, vol. 35(3), pages 415-431.
- Steven M. Shugan, 2005. "Brand Loyalty Programs: Are They Shams?," Marketing Science, INFORMS, vol. 24(2), pages 185-193.
- 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.
- Phebo D. Wibbens, 2023. "A formal framework for the RBV: Resource dynamics as a Markov process," Strategic Management Journal, Wiley Blackwell, vol. 44(6), pages 1562-1586, June.
- Eva Ascarza & Bruce G. S. Hardie, 2013. "A Joint Model of Usage and Churn in Contractual Settings," Marketing Science, INFORMS, vol. 32(4), pages 570-590, July.
- Michael Löffler & Reinhold Decker, 2012. "Identifikation und praktische Nutzung von Mustern des Aufwärtskonsums," Schmalenbach Journal of Business Research, Springer, vol. 64(7), pages 722-746, November.
- Sha Yang & Yi Zhao & Ravi Dhar, 2010. "Modeling the Underreporting Bias in Panel Survey Data," Marketing Science, INFORMS, vol. 29(3), pages 525-539, 05-06.
- Alina Ferecatu & Arnaud Bruyn & Prithwiraj Mukherjee, 2024. "Silently killing your panelists one email at a time: The true cost of email solicitations," Journal of the Academy of Marketing Science, Springer, vol. 52(4), pages 1216-1239, July.
- Gui Liberali & Alina Ferecatu, 2022. "Morphing for Consumer Dynamics: Bandits Meet Hidden Markov Models," Marketing Science, INFORMS, vol. 41(4), pages 769-794, July.
More about this item
Keywords
brand (product) value; discrete choice models; probit model; hierarchical Bayes; “engineering” coefficients;All these keywords.
Statistics
Access and download statisticsCorrections
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:gam:jsusta:v:15:y:2023:i:24:p:16949-:d:1302552. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.