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Active Machine Learning for Consideration Heuristics

Citations

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Cited by:

  1. Rosales-Tristancho, Abel & Brey, Raúl & Carazo, Ana F. & Brey, J. Javier, 2022. "Analysis of the barriers to the adoption of zero-emission vehicles in Spain," Transportation Research Part A: Policy and Practice, Elsevier, vol. 158(C), pages 19-43.
  2. Bradlow, Eric T. & Gangwar, Manish & Kopalle, Praveen & Voleti, Sudhir, 2017. "The Role of Big Data and Predictive Analytics in Retailing," Journal of Retailing, Elsevier, vol. 93(1), pages 79-95.
  3. Hema Yoganarasimhan, 2020. "Search Personalization Using Machine Learning," Management Science, INFORMS, vol. 66(3), pages 1045-1070, March.
  4. Dongling Huang & Lan Luo, 2016. "Consumer Preference Elicitation of Complex Products Using Fuzzy Support Vector Machine Active Learning," Marketing Science, INFORMS, vol. 35(3), pages 445-464, May.
  5. 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.
  6. Maldonado, Sebastián & Montoya, Ricardo & Weber, Richard, 2015. "Advanced conjoint analysis using feature selection via support vector machines," European Journal of Operational Research, Elsevier, vol. 241(2), pages 564-574.
  7. 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.
  8. Olivier Toubia & Eric Johnson & Theodoros Evgeniou & Philippe Delquié, 2013. "Dynamic Experiments for Estimating Preferences: An Adaptive Method of Eliciting Time and Risk Parameters," Management Science, INFORMS, vol. 59(3), pages 613-640, June.
  9. Colin F. Camerer & Gideon Nave & Alec Smith, 2019. "Dynamic Unstructured Bargaining with Private Information: Theory, Experiment, and Outcome Prediction via Machine Learning," Management Science, INFORMS, vol. 65(4), pages 1867-1890, April.
  10. Bruno Jacobs & Dennis Fok & Bas Donkers, 2021. "Understanding Large-Scale Dynamic Purchase Behavior," Marketing Science, INFORMS, vol. 40(5), pages 844-870, September.
  11. Matthew J Salganik & Karen E C Levy, 2015. "Wiki Surveys: Open and Quantifiable Social Data Collection," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-17, May.
  12. Brighton, Henry & Gigerenzer, Gerd, 2015. "The bias bias," Journal of Business Research, Elsevier, vol. 68(8), pages 1772-1784.
  13. Hauser, John R., 2014. "Consideration-set heuristics," Journal of Business Research, Elsevier, vol. 67(8), pages 1688-1699.
  14. John Hauser, 2011. "A marketing science perspective on recognition-based heuristics (and the fast-and-frugal paradigm)," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 6(5), pages 396-408, July.
  15. repec:cup:judgdm:v:6:y:2011:i:5:p:396-408 is not listed on IDEAS
  16. Ma, Liye & Sun, Baohong, 2020. "Machine learning and AI in marketing – Connecting computing power to human insights," International Journal of Research in Marketing, Elsevier, vol. 37(3), pages 481-504.
  17. Shasha Lu & Li Xiao & Min Ding, 2016. "A Video-Based Automated Recommender (VAR) System for Garments," Marketing Science, INFORMS, vol. 35(3), pages 484-510, May.
  18. Asim Ansari & Yang Li & Jonathan Z. Zhang, 2018. "Probabilistic Topic Model for Hybrid Recommender Systems: A Stochastic Variational Bayesian Approach," Marketing Science, INFORMS, vol. 37(6), pages 987-1008, November.
  19. Yufeng Huang & Bart J. Bronnenberg, 2018. "Pennies for Your Thoughts: Costly Product Consideration and Purchase Quantity Thresholds," Marketing Science, INFORMS, vol. 37(6), pages 1009-1028, November.
  20. Daria Dzyabura & Srikanth Jagabathula & Eitan Muller, 2019. "Accounting for Discrepancies Between Online and Offline Product Evaluations," Marketing Science, INFORMS, vol. 38(1), pages 88-106, January.
  21. Falke Andreas & Hruschka Harald, 2016. "A Monte Carlo Study of Design Procedures for the Semi-parametric Mixed Logit Model," Review of Marketing Science, De Gruyter, vol. 14(1), pages 21-67, June.
  22. Andrea MAKINGS & Brian BARNARD, 2019. "The Heuristics of Entrepreneurs," Expert Journal of Business and Management, Sprint Investify, vol. 7(2), pages 179-203.
  23. Daniel R. Cavagnaro & Richard Gonzalez & Jay I. Myung & Mark A. Pitt, 2013. "Optimal Decision Stimuli for Risky Choice Experiments: An Adaptive Approach," Management Science, INFORMS, vol. 59(2), pages 358-375, February.
  24. Mengxia Zhang & Lan Luo, 2023. "Can Consumer-Posted Photos Serve as a Leading Indicator of Restaurant Survival? Evidence from Yelp," Management Science, INFORMS, vol. 69(1), pages 25-50, January.
  25. Denis Sauré & Juan Pablo Vielma, 2019. "Ellipsoidal Methods for Adaptive Choice-Based Conjoint Analysis," Operations Research, INFORMS, vol. 67(2), pages 315-338, March.
  26. Mingyu Joo & Michael L. Thompson & Greg M. Allenby6, 2019. "Optimal Product Design by Sequential Experiments in High Dimensions," Management Science, INFORMS, vol. 65(7), pages 3235-3254, July.
  27. Mele, Cristina & Russo Spena, Tiziana & Kaartemo, Valtteri & Marzullo, Maria Luisa, 2021. "Smart nudging: How cognitive technologies enable choice architectures for value co-creation," Journal of Business Research, Elsevier, vol. 129(C), pages 949-960.
  28. Ming-Hui Huang & Roland T. Rust, 2021. "A strategic framework for artificial intelligence in marketing," Journal of the Academy of Marketing Science, Springer, vol. 49(1), pages 30-50, January.
  29. Rust, Roland T., 2020. "The future of marketing," International Journal of Research in Marketing, Elsevier, vol. 37(1), pages 15-26.
  30. Hema Yoganarasimhan & Ebrahim Barzegary & Abhishek Pani, 2020. "Design and Evaluation of Personalized Free Trials," Papers 2006.13420, arXiv.org.
  31. Roland T. Rust & Ming-Hui Huang, 2014. "The Service Revolution and the Transformation of Marketing Science," Marketing Science, INFORMS, vol. 33(2), pages 206-221, March.
  32. Bremer, Lucas & Heitmann, Mark & Schreiner, Thomas F., 2017. "When and how to infer heuristic consideration set rules of consumers," International Journal of Research in Marketing, Elsevier, vol. 34(2), pages 516-535.
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