If it ain’t broke, should you still fix it? Effects of incorporating user feedback in product development on mobile application ratings
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DOI: 10.1016/j.ijresmar.2024.10.004
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- Artem Timoshenko & John R. Hauser, 2019. "Identifying Customer Needs from User-Generated Content," Marketing Science, INFORMS, vol. 38(1), pages 1-20, January.
- Zeynep Aydin-Gokgoz & M. Berk Ataman & Gerrit van Bruggen, 2022. "The Rise of Mobile Marketing: A Decade of Research in Review," Foundations and Trends(R) in Marketing, now publishers, vol. 17(3), pages 140-226, November.
- Dhar, Vasant & Chang, Elaine A., 2009. "Does Chatter Matter? The Impact of User-Generated Content on Music Sales," Journal of Interactive Marketing, Elsevier, vol. 23(4), pages 300-307.
- Michael Anderson & Jeremy Magruder, 2012.
"Learning from the Crowd: Regression Discontinuity Estimates of the Effects of an Online Review Database,"
Economic Journal, Royal Economic Society, vol. 122(563), pages 957-989, September.
- Anderson, Michael & Magruder, Jeremy, 2012. "Learning from the Crowd: Regression Discontinuity Estimates of the Effects of an Online Review Database," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt1t74q5qt, Department of Agricultural & Resource Economics, UC Berkeley.
- Ashlee Humphreys & Rebecca Jen-Hui Wang & Eileen FischerEditor & Linda PriceAssociate Editor, 2018. "Automated Text Analysis for Consumer Research," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 44(6), pages 1274-1306.
- Anindya Ghose & Sang Pil Han, 2014. "Estimating Demand for Mobile Applications in the New Economy," Management Science, INFORMS, vol. 60(6), pages 1470-1488, June.
- Torsten Bornemann & Cornelia Hattula & Stefan Hattula, 2020. "Successive product generations: financial implications of industry release rhythm alignment," Journal of the Academy of Marketing Science, Springer, vol. 48(6), pages 1174-1191, November.
- Oded Netzer & Ronen Feldman & Jacob Goldenberg & Moshe Fresko, 2012. "Mine Your Own Business: Market-Structure Surveillance Through Text Mining," Marketing Science, INFORMS, vol. 31(3), pages 521-543, May.
- Abbie Griffin & John R. Hauser, 1993.
"The Voice of the Customer,"
Marketing Science, INFORMS, vol. 12(1), pages 1-27.
- Griffin, Abbie. & Hauser, John R., 1991. "The voice of the customer," Working papers #56-91. Working paper (Sl, Massachusetts Institute of Technology (MIT), Sloan School of Management.
- Liang Chen & Pengxiang Zhang & Sali Li & Scott F. Turner, 2022. "Growing pains: The effect of generational product innovation on mobile games performance," Strategic Management Journal, Wiley Blackwell, vol. 43(4), pages 792-821, April.
- Davide Proserpio & Georgios Zervas, 2017. "Online Reputation Management: Estimating the Impact of Management Responses on Consumer Reviews," Marketing Science, INFORMS, vol. 36(5), pages 645-665, September.
- Ron S. Kenett & Silvia Salini, 2011. "Rejoinder to ‘Modern analysis of customer satisfaction surveys: comparison of models and integrated analysis’," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 27(5), pages 484-486, September.
- Joachim Büschken & Greg M. Allenby, 2016. "Sentence-Based Text Analysis for Customer Reviews," Marketing Science, INFORMS, vol. 35(6), pages 953-975, November.
- Park, Jeongeun & Yang, Donguk & Kim, Ha Young, 2023. "Text mining-based four-step framework for smart speaker product improvement and sales planning," Journal of Retailing and Consumer Services, Elsevier, vol. 71(C).
- Nikolay Archak & Anindya Ghose & Panagiotis G. Ipeirotis, 2011. "Deriving the Pricing Power of Product Features by Mining Consumer Reviews," Management Science, INFORMS, vol. 57(8), pages 1485-1509, August.
- Eugene W. Anderson & Mary W. Sullivan, 1993. "The Antecedents and Consequences of Customer Satisfaction for Firms," Marketing Science, INFORMS, vol. 12(2), pages 125-143.
- Chris Forman & Anindya Ghose & Batia Wiesenfeld, 2008. "Examining the Relationship Between Reviews and Sales: The Role of Reviewer Identity Disclosure in Electronic Markets," Information Systems Research, INFORMS, vol. 19(3), pages 291-313, September.
- Pasquale Del Vecchio & Gioconda Mele & Giuseppina Passiante & Donata Serra, 2023. "Knowledge generation from Big Data for new product development: a structured literature review," Knowledge Management Research & Practice, Taylor & Francis Journals, vol. 21(4), pages 892-907, July.
- Choi, Jaewoong & Oh, Seunghyun & Yoon, Janghyeok & Lee, Jae-Min & Coh, Byoung-Youl, 2020. "Identification of time-evolving product opportunities via social media mining," Technological Forecasting and Social Change, Elsevier, vol. 156(C).
- Ron S. Kenett & Silvia Salini, 2011. "Modern analysis of customer satisfaction surveys: comparison of models and integrated analysis," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 27(5), pages 465-475, September.
- Lara Stocchi & Naser Pourazad & Nina Michaelidou & Arry Tanusondjaja & Paul Harrigan, 2022. "Marketing research on Mobile apps: past, present and future," Journal of the Academy of Marketing Science, Springer, vol. 50(2), pages 195-225, March.
- Judith A. Chevalier & Yaniv Dover & Dina MayzlinDina Mayzlin, 2018.
"Channels of Impact: User Reviews When Quality Is Dynamic and Managers Respond,"
Marketing Science, INFORMS, vol. 37(5), pages 688-709, September.
- Judith A. Chevalier & Yaniv Dover & Dina Mayzlin, 2017. "Channels of Impact: User Reviews when Quality is Dynamic and Managers Respond," NBER Working Papers 23299, National Bureau of Economic Research, Inc.
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