My bibliography
Save this item
Identifying Customer Needs from User-Generated Content
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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).
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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).
- 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).
- 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.
- 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.
- 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).
- 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.
- Alex Burnap & John R. Hauser & Artem Timoshenko, 2019. "Product Aesthetic Design: A Machine Learning Augmentation," Papers 1907.07786, arXiv.org, revised Nov 2022.
- 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.
- 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).
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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).
- 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).
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- Yan Song & Xin Tian, 2020. "Managerial Responses and Customer Engagement in Crowdfunding," Sustainability, MDPI, vol. 12(8), pages 1-13, April.
- 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.
- 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.
- 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.
- 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.
- 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.
- Yi Liu & Pinar Yildirim & Z. John Zhang, 2021. "Social Media, Content Moderation, and Technology," Papers 2101.04618, arXiv.org, revised Jan 2021.
- 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.
- 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.
- Rust, Roland T., 2020. "The future of marketing," International Journal of Research in Marketing, Elsevier, vol. 37(1), pages 15-26.
- 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.
- Han, Jie & Jiang, Cailou & Liu, Rong, 2023. "Does intelligent transformation trigger technology innovation in China's NEV enterprises?," Energy, Elsevier, vol. 270(C).
- 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.
- Liu Liu & Daria Dzyabura & Natalie Mizik, 2017. "Visual Listening In: Extracting Brand Image Portrayed on Social Media," Working Papers w0258, New Economic School (NES).