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The Effect of Calorie Posting Regulation on Consumer Opinion: A Flexible Latent Dirichlet Allocation Model with Informative Priors

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  1. Sotaro Katsumata & Seungjin Kim, 2020. "The Text-Score Allocation Model: Finding Latent Topics of Online Review Documents and Multi-Item Ratings," Discussion Papers in Economics and Business 20-01, Osaka University, Graduate School of Economics.
  2. Alantari, Huwail J. & Currim, Imran S. & Deng, Yiting & Singh, Sameer, 2022. "An empirical comparison of machine learning methods for text-based sentiment analysis of online consumer reviews," International Journal of Research in Marketing, Elsevier, vol. 39(1), pages 1-19.
  3. Yi Yang & Kunpeng Zhang & Yangyang Fan, 2023. "sDTM: A Supervised Bayesian Deep Topic Model for Text Analytics," Information Systems Research, INFORMS, vol. 34(1), pages 137-156, March.
  4. Soumya Mukhopadhyay & V Kumar & Amalesh Sharma & Tuck Siong Chung, 2022. "Impact of review narrativity on sales in a competitive environment," Production and Operations Management, Production and Operations Management Society, vol. 31(6), pages 2538-2556, June.
  5. Hyowon Kim & Greg M. Allenby, 2022. "Integrating Textual Information into Models of Choice and Scaled Response Data," Marketing Science, INFORMS, vol. 41(4), pages 815-830, July.
  6. Robert W. Palmatier & Andrew T. Crecelius, 2019. "The “first principles” of marketing strategy," AMS Review, Springer;Academy of Marketing Science, vol. 9(1), pages 5-26, June.
  7. Yash Raj Shrestha & Vivianna Fang He & Phanish Puranam & Georg von Krogh, 2021. "Algorithm Supported Induction for Building Theory: How Can We Use Prediction Models to Theorize?," Organization Science, INFORMS, vol. 32(3), pages 856-880, May.
  8. Arianna Marchetti & Phanish Puranam, 2022. "Organizational cultural strength as the negative cross-entropy of mindshare: a measure based on descriptive text," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-14, December.
  9. Jiawei Chen & Yinghui (Catherine) Yang & Hongyan Liu, 2021. "Mining Bilateral Reviews for Online Transaction Prediction: A Relational Topic Modeling Approach," Information Systems Research, INFORMS, vol. 32(2), pages 541-560, June.
  10. Oetzel, Sebastian & Graf, Denise, 2023. "Fragen oder Zuhören? Ein Vergleich von Kundenbefragungen und User Generated Content," PraxisWISSEN Marketing: German Journal of Marketing, AfM – Arbeitsgemeinschaft für Marketing, vol. 8(01/2023), pages 91-107.
  11. Hartmann, Jochen & Huppertz, Juliana & Schamp, Christina & Heitmann, Mark, 2019. "Comparing automated text classification methods," International Journal of Research in Marketing, Elsevier, vol. 36(1), pages 20-38.
  12. Dinesh Puranam & Vrinda Kadiyali & Vishal Narayan, 2021. "The Impact of Increase in Minimum Wages on Consumer Perceptions of Service: A Transformer Model of Online Restaurant Reviews," Marketing Science, INFORMS, vol. 40(5), pages 985-1004, September.
  13. Bruno Jacobs & Dennis Fok & Bas Donkers, 2021. "Understanding Large-Scale Dynamic Purchase Behavior," Marketing Science, INFORMS, vol. 40(5), pages 844-870, September.
  14. Saridakis, Charalampos & Katsikeas, Constantine S. & Angelidou, Sofia & Oikonomidou, Maria & Pratikakis, Polyvios, 2023. "Mining Twitter lists to extract brand-related associative information for celebrity endorsement," European Journal of Operational Research, Elsevier, vol. 311(1), pages 316-332.
  15. Maximilian Matthe & Daniel M. Ringel & Bernd Skiera, 2023. "Mapping Market Structure Evolution," Marketing Science, INFORMS, vol. 42(3), pages 589-613, May.
  16. Feifei Wang & Yang Yang & Geoffrey K. F. Tso & Yang Li, 2019. "Analysis of launch strategy in cross-border e-Commerce market via topic modeling of consumer reviews," Electronic Commerce Research, Springer, vol. 19(4), pages 863-884, December.
  17. Ning Zhong & David A. Schweidel, 2020. "Capturing Changes in Social Media Content: A Multiple Latent Changepoint Topic Model," Marketing Science, INFORMS, vol. 39(4), pages 827-846, July.
  18. Zhang, Min & Sun, Lin & Wang, G. Alan & Li, Yuzhuo & He, Shuguang, 2022. "Using neutral sentiment reviews to improve customer requirement identification and product design strategies," International Journal of Production Economics, Elsevier, vol. 254(C).
  19. Marit Hinnosaar, 2023. "The Persistence of Healthy Behaviors in Food Purchasing," Marketing Science, INFORMS, vol. 42(3), pages 521-537, May.
  20. Ishita Chakraborty & Minkyung Kim & K. Sudhir, 2019. "Attribute Sentiment Scoring With Online Text Reviews : Accounting for Language Structure and Attribute Self-Selection," Cowles Foundation Discussion Papers 2176, Cowles Foundation for Research in Economics, Yale University.
  21. Schauerte, Nico & Becker, Maren & Imschloss, Monika & Wichmann, Julian R.K. & Reinartz, Werner J., 2023. "The managerial relevance of marketing science: Properties and genesis," International Journal of Research in Marketing, Elsevier, vol. 40(4), pages 801-822.
  22. Ishita Chakraborty & Minkyung Kim & K. Sudhir, 2019. "Attribute Sentiment Scoring With Online Text Reviews : Accounting for Language Structure and Attribute Self-Selection," Cowles Foundation Discussion Papers 2176R, Cowles Foundation for Research in Economics, Yale University, revised Sep 2020.
  23. Alzate, Miriam & Arce-Urriza, Marta & Cebollada, Javier, 2022. "Mining the text of online consumer reviews to analyze brand image and brand positioning," Journal of Retailing and Consumer Services, Elsevier, vol. 67(C).
  24. Wei Chen & Karen Xie & Jianwei Liu & Yong Liu, 2019. "How Incumbents Beat Disruptors? Evidence from Hotels’ Responses to Home-sharing Rivals," Working Papers 19-11, NET Institute.
  25. Piyush Anand & Clarence Lee, 2023. "Using Deep Learning to Overcome Privacy and Scalability Issues in Customer Data Transfer," Marketing Science, INFORMS, vol. 42(1), pages 189-207, January.
  26. Liu, Yezheng & Qian, Yang & Jiang, Yuanchun & Shang, Jennifer, 2020. "Using favorite data to analyze asymmetric competition: Machine learning models," European Journal of Operational Research, Elsevier, vol. 287(2), pages 600-615.
  27. Kathleen T. Li, 2024. "Frontiers: A Simple Forward Difference-in-Differences Method," Marketing Science, INFORMS, vol. 43(2), pages 267-279, March.
  28. 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.
  29. Linda Hagen & Kosuke Uetake & Nathan Yang & Bryan Bollinger & Allison J. B. Chaney & Daria Dzyabura & Jordan Etkin & Avi Goldfarb & Liu Liu & K. Sudhir & Yanwen Wang & James R. Wright & Ying Zhu, 2020. "How can machine learning aid behavioral marketing research?," Marketing Letters, Springer, vol. 31(4), pages 361-370, December.
  30. Ishita Chakraborty & Minkyung Kim & K. Sudhir, 2019. "Attribute Sentiment Scoring With Online Text Reviews : Accounting for Language Structure and Attribute Self-Selection," Cowles Foundation Discussion Papers 2176R2, Cowles Foundation for Research in Economics, Yale University, revised Jun 2021.
  31. S. Sajeesh & Ozgur M. Araz & Terry T.‐K. Huang, 2022. "Market positioning in food industry in response to public health policies," Production and Operations Management, Production and Operations Management Society, vol. 31(7), pages 2962-2981, July.
  32. Kim, Jong Min & Park, Keeyeon Ki-cheon & Mariani, Marcello M., 2023. "Do online review readers react differently when exposed to credible versus fake online reviews?," Journal of Business Research, Elsevier, vol. 154(C).
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