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Identifying Customer Needs from User-Generated Content

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Cited by:

  1. Ho-Dac, Nga N., 2020. "The value of online user generated content in product development," Journal of Business Research, Elsevier, vol. 112(C), pages 136-146.
  2. Jonah Berger & Grant Packard & Reihane Boghrati & Ming Hsu & Ashlee Humphreys & Andrea Luangrath & Sarah Moore & Gideon Nave & Christopher Olivola & Matthew Rocklage, 2022. "Marketing insights from text analysis," Marketing Letters, Springer, vol. 33(3), pages 365-377, September.
  3. Garner, Benjamin & Thornton, Corliss & Luo Pawluk, Anita & Mora Cortez, Roberto & Johnston, Wesley & Ayala, Cesar, 2022. "Utilizing text-mining to explore consumer happiness within tourism destinations," Journal of Business Research, Elsevier, vol. 139(C), pages 1366-1377.
  4. Roelen-Blasberg, Tobias & Habel, Johannes & Klarmann, Martin, 2023. "Automated inference of product attributes and their importance from user-generated content: Can we replace traditional market research?," International Journal of Research in Marketing, Elsevier, vol. 40(1), pages 164-188.
  5. Enrique Bigne & Carla Ruiz & Carmen Perez-Cabañero & Antonio Cuenca, 2023. "Are customer star ratings and sentiments aligned? A deep learning study of the customer service experience in tourism destinations," Service Business, Springer;Pan-Pacific Business Association, vol. 17(1), pages 281-314, March.
  6. Yucheng Zhang & Zhiling Wang & Lin Xiao & Lijun Wang & Pei Huang, 2023. "Discovering the evolution of online reviews: A bibliometric review," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-22, December.
  7. Jifeng Mu & Jonathan Z. Zhang, 2021. "Seller marketing capability, brand reputation, and consumer journeys on e-commerce platforms," Journal of the Academy of Marketing Science, Springer, vol. 49(5), pages 994-1020, September.
  8. 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.
  9. 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).
  10. Subrahmanyam Aditya Karanam & Ashish Agarwal & Anitesh Barua, 2023. "Design for Social Sharing: The Case of Mobile Apps," Information Systems Research, INFORMS, vol. 34(2), pages 721-743, June.
  11. Cheng Chai & Yao Song & Zhenzhen Qin, 2021. "A Thousand Words Express a Common Idea? Understanding International Tourists’ Reviews of Mt. Huangshan, China, through a Deep Learning Approach," Land, MDPI, vol. 10(6), pages 1-15, May.
  12. Fei Li & Yang Zhao & Jaime Ortiz & Yan Chen, 2023. "How Does Digital Technology Innovation Affect the Internationalization Performance of Chinese Enterprises? The Moderating Effect of Sustainability Readiness," Sustainability, MDPI, vol. 15(14), pages 1-25, July.
  13. Hartmann, Jochen & Heitmann, Mark & Siebert, Christian & Schamp, Christina, 2023. "More than a Feeling: Accuracy and Application of Sentiment Analysis," International Journal of Research in Marketing, Elsevier, vol. 40(1), pages 75-87.
  14. Fangfang Li & Jorma Larimo & Leonidas C. Leonidou, 2021. "Social media marketing strategy: definition, conceptualization, taxonomy, validation, and future agenda," Journal of the Academy of Marketing Science, Springer, vol. 49(1), pages 51-70, January.
  15. Ying Qian & Xiao-ying Liu & Bing Fang & Fan Zhang & Rui Gao, 2020. "Investigating Fertility Intentions for a Second Child in Contemporary China Based on User-Generated Content," IJERPH, MDPI, vol. 17(11), pages 1-15, May.
  16. Melović, Boban & Jocović, Mijat & Dabić, Marina & Vulić, Tamara Backović & Dudic, Branislav, 2020. "The impact of digital transformation and digital marketing on the brand promotion, positioning and electronic business in Montenegro," Technology in Society, Elsevier, vol. 63(C).
  17. C, Deep Prakash & Majumdar, Adrija, 2023. "Predicting sports fans’ engagement with culturally aligned social media content: A language expectancy perspective," Journal of Retailing and Consumer Services, Elsevier, vol. 75(C).
  18. Erik Hermann, 2022. "Leveraging Artificial Intelligence in Marketing for Social Good—An Ethical Perspective," Journal of Business Ethics, Springer, vol. 179(1), pages 43-61, August.
  19. 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.
  20. Morimura, Fumikazu & Sakagawa, Yuji, 2023. "The intermediating role of big data analytics capability between responsive and proactive market orientations and firm performance in the retail industry," Journal of Retailing and Consumer Services, Elsevier, vol. 71(C).
  21. Sebastian Gabel & Artem Timoshenko, 2022. "Product Choice with Large Assortments: A Scalable Deep-Learning Model," Management Science, INFORMS, vol. 68(3), pages 1808-1827, March.
  22. Alex Burnap & John R. Hauser & Artem Timoshenko, 2019. "Product Aesthetic Design: A Machine Learning Augmentation," Papers 1907.07786, arXiv.org, revised Nov 2022.
  23. Martin Reisenbichler & Thomas Reutterer & David A. Schweidel & Daniel Dan, 2022. "Frontiers: Supporting Content Marketing with Natural Language Generation," Marketing Science, INFORMS, vol. 41(3), pages 441-452, May.
  24. von Hippel, Eric & Kaulartz, Sandro, 2021. "Next-generation consumer innovation search: Identifying early-stage need-solution pairs on the web," Research Policy, Elsevier, vol. 50(8).
  25. Elliot Shin Oblander & Sunil Gupta & Carl F. Mela & Russell S. Winer & Donald R. Lehmann, 2020. "The past, present, and future of customer management," Marketing Letters, Springer, vol. 31(2), pages 125-136, September.
  26. David A. Schweidel & Yakov Bart & J. Jeffrey Inman & Andrew T. Stephen & Barak Libai & Michelle Andrews & Ana Babić Rosario & Inyoung Chae & Zoey Chen & Daniella Kupor & Chiara Longoni & Felipe Thomaz, 2022. "How consumer digital signals are reshaping the customer journey," Journal of the Academy of Marketing Science, Springer, vol. 50(6), pages 1257-1276, November.
  27. Zelin Zhang & Kejia Yang & Jonathan Z. Zhang & Robert W. Palmatier, 2023. "Uncovering Synergy and Dysergy in Consumer Reviews: A Machine Learning Approach," Management Science, INFORMS, vol. 69(4), pages 2339-2360, April.
  28. 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.
  29. Uttara Ananthakrishnan & Davide Proserpio & Siddhartha Sharma, 2023. "I Hear You: Does Quality Improve with Customer Voice?," Marketing Science, INFORMS, vol. 42(6), pages 1143-1161, November.
  30. Eleanor Kohler & Emmanuel Mogaji & İsmail Erkan, 2023. "Save the Trip to the Store: Sustainable Shopping, Electronic Word of Mouth on Instagram and the Impact on Cosmetic Purchase Intentions," Sustainability, MDPI, vol. 15(10), pages 1-18, May.
  31. Ning Wang & Can Wang & Limin Hou & Bing Fang, 2021. "Investigating Young Employee Stressors in Contemporary Society Based on User-Generated Contents," IJERPH, MDPI, vol. 18(24), pages 1-19, December.
  32. Steven Shepherd & Ted Matherly, 2021. "Racialization of peer‐to‐peer transactions: Inequality and barriers to legitimacy," Journal of Consumer Affairs, Wiley Blackwell, vol. 55(2), pages 417-444, June.
  33. Li, Yiling & Kim, Hye-jin & Do, Boram & Choi, Jeonghye, 2022. "The effect of emotion in thumbnails and titles of video clips on pre-roll advertising effectiveness," Journal of Business Research, Elsevier, vol. 151(C), pages 232-243.
  34. Carlson, Keith & Kopalle, Praveen K. & Riddell, Allen & Rockmore, Daniel & Vana, Prasad, 2023. "Complementing human effort in online reviews: A deep learning approach to automatic content generation and review synthesis," International Journal of Research in Marketing, Elsevier, vol. 40(1), pages 54-74.
  35. Paramveer S. Dhillon & Sinan Aral, 2021. "Modeling Dynamic User Interests: A Neural Matrix Factorization Approach," Marketing Science, INFORMS, vol. 40(6), pages 1059-1080, November.
  36. Xueling Li & Xiaoyan Zhang & Yuan Liu & Yuanying Mi & Yong Chen, 2022. "The impact of artificial intelligence on users' entrepreneurial activities," Systems Research and Behavioral Science, Wiley Blackwell, vol. 39(3), pages 597-608, May.
  37. Yi Liu & Pinar Yildirim & Z. John Zhang, 2022. "Implications of Revenue Models and Technology for Content Moderation Strategies," Marketing Science, INFORMS, vol. 41(4), pages 831-847, July.
  38. Jianhong Luo & Shifen Qiu & Xuwei Pan & Ke Yang & Yuanqingqing Tian, 2022. "Exploration of Spa Leisure Consumption Sentiment towards Different Holidays and Different Cities through Online Reviews: Implications for Customer Segmentation," Sustainability, MDPI, vol. 14(2), pages 1-16, January.
  39. Davide Proserpio & John R. Hauser & Xiao Liu & Tomomichi Amano & Alex Burnap & Tong Guo & Dokyun (DK) Lee & Randall Lewis & Kanishka Misra & Eric Schwarz & Artem Timoshenko & Lilei Xu & Hema Yoganaras, 2020. "Soul and machine (learning)," Marketing Letters, Springer, vol. 31(4), pages 393-404, December.
  40. Ngai, Eric W.T. & Wu, Yuanyuan, 2022. "Machine learning in marketing: A literature review, conceptual framework, and research agenda," Journal of Business Research, Elsevier, vol. 145(C), pages 35-48.
  41. 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).
  42. Kullak, Franziska S. & Baier, Daniel & Woratschek, Herbert, 2023. "How do customers meet their needs in in-store and online fashion shopping? A comparative study based on the jobs-to-be-done theory," Journal of Retailing and Consumer Services, Elsevier, vol. 71(C).
  43. Erick Kauffmann & Jesús Peral & David Gil & Antonio Ferrández & Ricardo Sellers & Higinio Mora, 2019. "Managing Marketing Decision-Making with Sentiment Analysis: An Evaluation of the Main Product Features Using Text Data Mining," Sustainability, MDPI, vol. 11(15), pages 1-19, August.
  44. Villarroel Ordenes, Francisco & Silipo, Rosaria, 2021. "Machine learning for marketing on the KNIME Hub: The development of a live repository for marketing applications," Journal of Business Research, Elsevier, vol. 137(C), pages 393-410.
  45. Siqing Shan & Qi Yan & Yigang Wei, 2020. "Infectious or Recovered? Optimizing the Infectious Disease Detection Process for Epidemic Control and Prevention Based on Social Media," IJERPH, MDPI, vol. 17(18), pages 1-25, September.
  46. 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.
  47. Shimi Naurin Ahmad & Michel Laroche, 2023. "Extracting marketing information from product reviews: a comparative study of latent semantic analysis and probabilistic latent semantic analysis," Journal of Marketing Analytics, Palgrave Macmillan, vol. 11(4), pages 662-676, December.
  48. Jeffrey D. Shulman & Olivier Toubia & Raena Saddler, 2023. "Editorial: Marketing’s Role in the Evolving Discipline of Product Management," Marketing Science, INFORMS, vol. 42(1), pages 1-5, January.
  49. Yan Song & Xin Tian, 2020. "Managerial Responses and Customer Engagement in Crowdfunding," Sustainability, MDPI, vol. 12(8), pages 1-13, April.
  50. Shuili Du & Assaad El Akremi & Ming Jia, 2023. "Quantitative Research on Corporate Social Responsibility: A Quest for Relevance and Rigor in a Quickly Evolving, Turbulent World," Journal of Business Ethics, Springer, vol. 187(1), pages 1-15, September.
  51. Anning Wang & Qiang Zhang & Shuangyao Zhao & Xiaonong Lu & Zhanglin Peng, 2020. "A review-driven customer preference measurement model for product improvement: sentiment-based importance–performance analysis," Information Systems and e-Business Management, Springer, vol. 18(1), pages 61-88, March.
  52. Jiyeon Hong & Paul R. Hoban, 2022. "Writing More Compelling Creative Appeals: A Deep Learning-Based Approach," Marketing Science, INFORMS, vol. 41(5), pages 941-965, September.
  53. Hasmat Malik & Asyraf Afthanorhan & Noor Aina Amirah & Nuzhat Fatema, 2021. "Machine Learning Approach for Targeting and Recommending a Product for Project Management," Mathematics, MDPI, vol. 9(16), pages 1-29, August.
  54. 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.
  55. Yi Liu & Pinar Yildirim & Z. John Zhang, 2021. "Social Media, Content Moderation, and Technology," Papers 2101.04618, arXiv.org, revised Jan 2021.
  56. Boegershausen, Johannes & Datta, Hannes & Borah, Abhishek & Stephen, Andrew, 2022. "Fields of Gold: Web Scraping and APIs for Impactful Marketing Insights," Other publications TiSEM 5f1ed70a-48c3-422c-bc10-0, Tilburg University, School of Economics and Management.
  57. 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.
  58. Rust, Roland T., 2020. "The future of marketing," International Journal of Research in Marketing, Elsevier, vol. 37(1), pages 15-26.
  59. Kejia Chen & Jian Jin & Zheng Zhao & Ping Ji, 2022. "Understanding customer regional differences from online opinions: a hierarchical Bayesian approach," Electronic Commerce Research, Springer, vol. 22(2), pages 377-403, June.
  60. Han, Jie & Jiang, Cailou & Liu, Rong, 2023. "Does intelligent transformation trigger technology innovation in China's NEV enterprises?," Energy, Elsevier, vol. 270(C).
  61. Liu Liu & Daria Dzyabura & Natalie Mizik, 2020. "Visual Listening In: Extracting Brand Image Portrayed on Social Media," Marketing Science, INFORMS, vol. 39(4), pages 669-686, July.
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