Automated Product Recommendations with Preference-Based Explanations
Author
Abstract
Suggested Citation
DOI: 10.1016/j.jretai.2020.01.001
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Bleier, Alexander & Eisenbeiss, Maik, 2015. "The Importance of Trust for Personalized Online Advertising," Journal of Retailing, Elsevier, vol. 91(3), pages 390-409.
- Clement, Michel & Wu, Steven & Fischer, Marc, 2014. "Empirical generalizations of demand and supply dynamics for movies," International Journal of Research in Marketing, Elsevier, vol. 31(2), pages 207-223.
- Dokyun Lee & Kartik Hosanagar, 2019. "How Do Recommender Systems Affect Sales Diversity? A Cross-Category Investigation via Randomized Field Experiment," Service Science, INFORMS, vol. 30(1), pages 239-259, March.
- Niladri B. Syam & Nanda Kumar, 2006. "On Customized Goods, Standard Goods, and Competition," Marketing Science, INFORMS, vol. 25(5), pages 525-537, September.
- Daniel Fleder & Kartik Hosanagar, 2009. "Blockbuster Culture's Next Rise or Fall: The Impact of Recommender Systems on Sales Diversity," Management Science, INFORMS, vol. 55(5), pages 697-712, May.
- Quentin André & Ziv Carmon & Klaus Wertenbroch & Alia Crum & Douglas Frank & William Goldstein & Joel Huber & Leaf Boven & Bernd Weber & Haiyang Yang, 2018. "Consumer Choice and Autonomy in the Age of Artificial Intelligence and Big Data," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 5(1), pages 28-37, March.
- Tuck Siong Chung & Roland T. Rust & Michel Wedel, 2009. "My Mobile Music: An Adaptive Personalization System for Digital Audio Players," Marketing Science, INFORMS, vol. 28(1), pages 52-68, 01-02.
- Gavan J. Fitzsimons & Donald R. Lehmann, 2004. "Reactance to Recommendations: When Unsolicited Advice Yields Contrary Responses," Marketing Science, INFORMS, vol. 23(1), pages 82-94, September.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Zhang, Junhui & Balaji, M.S. & Luo, Jun & Jha, Subhash, 2022. "Effectiveness of product recommendation framing on online retail platforms," Journal of Business Research, Elsevier, vol. 153(C), pages 185-197.
- Yang, Defeng & Zhang, Jiaen & Sun, Yu & Huang, Zan, 2024. "Showing usage behavior or not? The effect of virtual influencers’ product usage behavior on consumers," Journal of Retailing and Consumer Services, Elsevier, vol. 79(C).
- Battisti, Sandro & Agarwal, Nivedita & Brem, Alexander, 2022. "Creating new tech entrepreneurs with digital platforms: Meta-organizations for shared value in data-driven retail ecosystems," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
- Wang, Xin (Shane) & Ryoo, Jun Hyun (Joseph) & Bendle, Neil & Kopalle, Praveen K., 2021. "The role of machine learning analytics and metrics in retailing research," Journal of Retailing, Elsevier, vol. 97(4), pages 658-675.
- Martin Eling & Davide Nuessle & Julian Staubli, 2022. "The impact of artificial intelligence along the insurance value chain and on the insurability of risks," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 47(2), pages 205-241, April.
- Guyt, Jonne Y. & Datta, Hannes & Boegershausen, Johannes, 2024. "Unlocking the Potential of Web Data for Retailing Research," Journal of Retailing, Elsevier, vol. 100(1), pages 130-147.
- Huang, Ming-Hui & Rust, Roland T., 2022. "A Framework for Collaborative Artificial Intelligence in Marketing," Journal of Retailing, Elsevier, vol. 98(2), pages 209-223.
- Blut, Markus & Ghiassaleh, Arezou & Wang, Cheng, 2023. "Testing the performance of online recommendation agents: A meta-analysis," Journal of Retailing, Elsevier, vol. 99(3), pages 440-459.
- Manis, K.T. & Madhavaram, Sreedhar, 2023. "AI-Enabled marketing capabilities and the hierarchy of capabilities: Conceptualization, proposition development, and research avenues," Journal of Business Research, Elsevier, vol. 157(C).
- Liao, Shu-Hsien & Widowati, Retno & Hsieh, Yu-Chieh, 2021. "Investigating online social media users’ behaviors for social commerce recommendations," Technology in Society, Elsevier, vol. 66(C).
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.- Lena Bjørlo & Øystein Moen & Mark Pasquine, 2021. "The Role of Consumer Autonomy in Developing Sustainable AI: A Conceptual Framework," Sustainability, MDPI, vol. 13(4), pages 1-18, February.
- Darima Fotheringham & Michael A. Wiles, 2023. "The effect of implementing chatbot customer service on stock returns: an event study analysis," Journal of the Academy of Marketing Science, Springer, vol. 51(4), pages 802-822, July.
- Miguel Godinho de Matos & Pedro Ferreira, 2020. "The Effect of Binge-Watching on the Subscription of Video on Demand: Results from Randomized Experiments," Information Systems Research, INFORMS, vol. 31(4), pages 1337-1360, December.
- Nasim Mousavi & Panagiotis Adamopoulos & Jesse Bockstedt, 2023. "The Decoy Effect and Recommendation Systems," Information Systems Research, INFORMS, vol. 34(4), pages 1533-1553, December.
- Xitong Li & Jörn Grahl & Oliver Hinz, 2022.
"How Do Recommender Systems Lead to Consumer Purchases? A Causal Mediation Analysis of a Field Experiment,"
Information Systems Research, INFORMS, vol. 33(2), pages 620-637, June.
- Xitong Li & Jörn Grahl & Oliver Hinz, 2021. "How Do Recommender Systems Lead to Consumer Purchases? A Causal Mediation Analysis of a Field Experiment," Working Papers hal-03869071, HAL.
- Anuj Kumar & Kartik Hosanagar, 2019. "Measuring the Value of Recommendation Links on Product Demand," Information Systems Research, INFORMS, vol. 30(3), pages 819-838, September.
- Joan Calzada & Nestor Duch-Brown & Ricard Gil, 2021.
"Do search engines increase concentration in media markets?,"
UB School of Economics Working Papers
2021/415, University of Barcelona School of Economics.
- Joan Calzada & Nestor Duch-Brown & Ricard Gil, 2023. "Do Search Engines Increase Concentration in Media Markets?," CESifo Working Paper Series 10671, CESifo.
- Xuan Bi & Gediminas Adomavicius & William Li & Annie Qu, 2022. "Improving Sales Forecasting Accuracy: A Tensor Factorization Approach with Demand Awareness," INFORMS Journal on Computing, INFORMS, vol. 34(3), pages 1644-1660, May.
- Dokyun Lee & Kartik Hosanagar, 2021. "How Do Product Attributes and Reviews Moderate the Impact of Recommender Systems Through Purchase Stages?," Management Science, INFORMS, vol. 67(1), pages 524-546, January.
- Neeraj Arora & Xavier Dreze & Anindya Ghose & James Hess & Raghuram Iyengar & Bing Jing & Yogesh Joshi & V. Kumar & Nicholas Lurie & Scott Neslin & S. Sajeesh & Meng Su & Niladri Syam & Jacquelyn Thom, 2008. "Putting one-to-one marketing to work: Personalization, customization, and choice," Marketing Letters, Springer, vol. 19(3), pages 305-321, December.
- Marc Bourreau & Germain Gaudin, 2022.
"Streaming platform and strategic recommendation bias,"
Journal of Economics & Management Strategy, Wiley Blackwell, vol. 31(1), pages 25-47, February.
- Marc Bourreau & Germain Gaudin, 2018. "Streaming Platform and Strategic Recommendation Bias," CESifo Working Paper Series 7390, CESifo.
- Marc Bourreau & Germain Gaudin, 2021. "Streaming platform and strategic recommendation bias," Post-Print halshs-03352447, HAL.
- Guy Aridor & Duarte Goncalves & Daniel Kluver & Ruoyan Kong & Joseph Konstan, 2022.
"The Economics of Recommender Systems: Evidence from a Field Experiment on MovieLens,"
Papers
2211.14219, arXiv.org.
- Guy Aridor & Duarte Gonçalves & Daniel Kluver & Ruoyan Kong & Joseph Konstan, 2022. "The Economics of Recommender Systems: Evidence from a Field Experiment on MovieLens," CESifo Working Paper Series 10129, CESifo.
- Klaus Wertenbroch & Rom Y. Schrift & Joseph W. Alba & Alixandra Barasch & Amit Bhattacharjee & Markus Giesler & Joshua Knobe & Donald R. Lehmann & Sandra Matz & Gideon Nave & Jeffrey R. Parker & Stefa, 2020. "Autonomy in consumer choice," Marketing Letters, Springer, vol. 31(4), pages 429-439, December.
- Dongwon Lee & Anandasivam Gopal & Sung-Hyuk Park, 2020. "Different but Equal? A Field Experiment on the Impact of Recommendation Systems on Mobile and Personal Computer Channels in Retail," Information Systems Research, INFORMS, vol. 31(3), pages 892-912, September.
- Bruno J.D. Jacobs & Bas Donkers & Dennis Fok, 2016.
"Model-Based Purchase Predictions for Large Assortments,"
Marketing Science, INFORMS, vol. 35(3), pages 389-404, May.
- Jacobs, B.J.D. & Donkers, A.C.D. & Fok, D., 2016. "Model-based Purchase Predictions for Large Assortments," ERIM Report Series Research in Management ERS-2014-007-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
- Yuanchun Jiang & Jennifer Shang & Chris F. Kemerer & Yezheng Liu, 2011. "Optimizing E-tailer Profits and Customer Savings: Pricing Multistage Customized Online Bundles," Marketing Science, INFORMS, vol. 30(4), pages 737-752, July.
- Krafft, Manfred & Arden, Christine M. & Verhoef, Peter C., 2017. "Permission Marketing and Privacy Concerns — Why Do Customers (Not) Grant Permissions?," Journal of Interactive Marketing, Elsevier, vol. 39(C), pages 39-54.
- Vivek F. Farias & Andrew A. L, 2019. "Learning Preferences with Side Information," Management Science, INFORMS, vol. 65(7), pages 3131-3149, July.
- Tobias Kretschmer & Christian Peukert, 2020.
"Video Killed the Radio Star? Online Music Videos and Recorded Music Sales,"
Information Systems Research, INFORMS, vol. 31(3), pages 776-800, September.
- Kretschmer, Tobias & Peukert, Christian, 2019. "Video Killed the Radio Star? Online Music Videos and Recorded Music Sales," CEPR Discussion Papers 14038, C.E.P.R. Discussion Papers.
- Abhijeet Ghoshal & Subodha Kumar & Vijay Mookerjee, 2020. "Dilemma of Data Sharing Alliance: When Do Competing Personalizing and Non‐Personalizing Firms Share Data," Production and Operations Management, Production and Operations Management Society, vol. 29(8), pages 1918-1936, August.
More about this item
Keywords
Recommender systems; Recommendation explanations; Decision support systems; Consumer preferences; Netflix; MoviePilot;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:eee:jouret:v:96:y:2020:i:3:p:328-343. 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: https://www.journals.elsevier.com/journal-of-retailing .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.