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A Structured Analysis of Unstructured Big Data by Leveraging Cloud Computing

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  1. Shuyun Ren & Hau-Ling Chan & Tana Siqin, 2020. "Demand forecasting in retail operations for fashionable products: methods, practices, and real case study," Annals of Operations Research, Springer, vol. 291(1), pages 761-777, August.
  2. Martin, Simon & Rasch, Alexander, 2024. "Demand forecasting, signal precision, and collusion with hidden actions," International Journal of Industrial Organization, Elsevier, vol. 92(C).
  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. Fernando, Angeline Gautami & Aw, Eugene Cheng-Xi, 2023. "What do consumers want? A methodological framework to identify determinant product attributes from consumers’ online questions," Journal of Retailing and Consumer Services, Elsevier, vol. 73(C).
  5. Xiaodan Zhu & Anh Ninh & Hui Zhao & Zhenming Liu, 2021. "Demand Forecasting with Supply‐Chain Information and Machine Learning: Evidence in the Pharmaceutical Industry," Production and Operations Management, Production and Operations Management Society, vol. 30(9), pages 3231-3252, September.
  6. Ratchford, Brian & Soysal, Gonca & Zentner, Alejandro & Gauri, Dinesh K., 2022. "Online and offline retailing: What we know and directions for future research," Journal of Retailing, Elsevier, vol. 98(1), pages 152-177.
  7. Zhepeng Lv & Yue Jin & Jinghua Huang, 2021. "MGC, consumers’ engagement with MGC, WOM and consumers’ purchase intention: the case of Weibo platform," Information Systems and e-Business Management, Springer, vol. 19(2), pages 495-516, June.
  8. 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.
  9. Ayat Zaki Ahmed & Manuel Rodríguez Díaz, 2022. "A Methodology for Machine-Learning Content Analysis to Define the Key Labels in the Titles of Online Customer Reviews with the Rating Evaluation," Sustainability, MDPI, vol. 14(15), pages 1-31, July.
  10. Bag, Sujoy & Tiwari, Manoj Kumar & Chan, Felix T.S., 2019. "Predicting the consumer's purchase intention of durable goods: An attribute-level analysis," Journal of Business Research, Elsevier, vol. 94(C), pages 408-419.
  11. Schaer, Oliver & Kourentzes, Nikolaos & Fildes, Robert, 2019. "Demand forecasting with user-generated online information," International Journal of Forecasting, Elsevier, vol. 35(1), pages 197-212.
  12. Huang, Ming-Hui & Rust, Roland T., 2022. "A Framework for Collaborative Artificial Intelligence in Marketing," Journal of Retailing, Elsevier, vol. 98(2), pages 209-223.
  13. Li, Xi & Shi, Mengze & Wang, Xin (Shane), 2019. "Video mining: Measuring visual information using automatic methods," International Journal of Research in Marketing, Elsevier, vol. 36(2), pages 216-231.
  14. Mustak, Mekhail & Salminen, Joni & Plé, Loïc & Wirtz, Jochen, 2021. "Artificial intelligence in marketing: Topic modeling, scientometric analysis, and research agenda," Journal of Business Research, Elsevier, vol. 124(C), pages 389-404.
  15. Bitty Balducci & Detelina Marinova, 2018. "Unstructured data in marketing," Journal of the Academy of Marketing Science, Springer, vol. 46(4), pages 557-590, July.
  16. Fay, Scott & Feng, Cong & Patel, Pankaj C., 2022. "Staying small, staying strong? Retail store underexpansion and retailer profitability," Journal of Business Research, Elsevier, vol. 144(C), pages 663-678.
  17. Johnson, Bethany & Munch, Stephan B., 2022. "An empirical dynamic modeling framework for missing or irregular samples," Ecological Modelling, Elsevier, vol. 468(C).
  18. 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.
  19. Zhao, Yan & Wen, Lingling & Feng, Xiangnan & Li, Ran & Lin, Xiaolin, 2020. "How managerial responses to online reviews affect customer satisfaction: An empirical study based on additional reviews," Journal of Retailing and Consumer Services, Elsevier, vol. 57(C).
  20. Dawn Iacobucci & Maria Petrescu & Anjala Krishen & Michael Bendixen, 2019. "The state of marketing analytics in research and practice," Journal of Marketing Analytics, Palgrave Macmillan, vol. 7(3), pages 152-181, September.
  21. Shijie Lu & Koushyar Rajavi & Isaac Dinner, 2021. "The Effect of Over-the-Top Media Services on Piracy Search: Evidence from a Natural Experiment," Marketing Science, INFORMS, vol. 40(3), pages 548-568, May.
  22. Jeeyoung Lim & Joseph J. Kim & Sunkuk Kim, 2021. "A Holistic Review of Building Energy Efficiency and Reduction Based on Big Data," Sustainability, MDPI, vol. 13(4), pages 1-18, February.
  23. 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.
  24. 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.
  25. Airani, Rajeev & Karande, Kiran, 2022. "How social media effects shape sentiments along the twitter journey?A Bayesian network approach," Journal of Business Research, Elsevier, vol. 142(C), pages 988-997.
  26. Djonata Schiessl & Helison Bertoli Alves Dias & José Carlos Korelo, 2022. "Artificial intelligence in marketing: a network analysis and future agenda," Journal of Marketing Analytics, Palgrave Macmillan, vol. 10(3), pages 207-218, September.
  27. Beth L. Fossen & Alexander Bleier, 2021. "Online program engagement and audience size during television ads," Journal of the Academy of Marketing Science, Springer, vol. 49(4), pages 743-761, July.
  28. Morgan Swink & Kejia Hu & Xiande Zhao, 2022. "Analytics applications, limitations, and opportunities in restaurant supply chains," Production and Operations Management, Production and Operations Management Society, vol. 31(10), pages 3710-3726, October.
  29. Sheng, Jie & Amankwah-Amoah, Joseph & Wang, Xiaojun, 2017. "A multidisciplinary perspective of big data in management research," International Journal of Production Economics, Elsevier, vol. 191(C), pages 97-112.
  30. Jang, Seongsoo & Chung, Jaihak & Rao, Vithala R., 2021. "The importance of functional and emotional content in online consumer reviews for product sales: Evidence from the mobile gaming market," Journal of Business Research, Elsevier, vol. 130(C), pages 583-593.
  31. Mehdi Nezami & Kapil R. Tuli & Shantanu Dutta, 2022. "Shareholder wealth implications of software firms’ transition to cloud computing: a marketing perspective," Journal of the Academy of Marketing Science, Springer, vol. 50(3), pages 538-562, May.
  32. Pradeep Chintagunta & Dominique M. Hanssens & John R. Hauser, 2016. "Editorial—Marketing Science and Big Data," Marketing Science, INFORMS, vol. 35(3), pages 341-342, May.
  33. 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).
  34. Venkatesh Shankar & Sohil Parsana, 2022. "An overview and empirical comparison of natural language processing (NLP) models and an introduction to and empirical application of autoencoder models in marketing," Journal of the Academy of Marketing Science, Springer, vol. 50(6), pages 1324-1350, November.
  35. Feng, Cong & Xiang, Kexin, 2023. "Structural power of female executives and retailer profitability: A contingent resource-based perspective," Journal of Business Research, Elsevier, vol. 168(C).
  36. Xuan Bi & Gediminas Adomavicius & William Li & Annie Qu, 2022. "Improving Sales Forecasting Accuracy: A Tensor Factorization Approach with Demand Awareness," INFORMS Journal on Computing, INFORMS, vol. 34(3), pages 1644-1660, May.
  37. Acciarini, Chiara & Cappa, Francesco & Boccardelli, Paolo & Oriani, Raffaele, 2023. "How can organizations leverage big data to innovate their business models? A systematic literature review," Technovation, Elsevier, vol. 123(C).
  38. 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.
  39. 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.
  40. Zhen Yan & Xiao Zhou & Rong Du, 2024. "An enhanced SIR dynamic model: the timing and changes in public opinion in the process of information diffusion," Electronic Commerce Research, Springer, vol. 24(3), pages 2021-2044, September.
  41. Khai Xiang Chiong & Matthew Shum, 2019. "Random Projection Estimation of Discrete-Choice Models with Large Choice Sets," Management Science, INFORMS, vol. 65(1), pages 256-271, January.
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