Editorial—Marketing Science and Big Data
Published Online:25 May 2016https://doi.org/10.1287/mksc.2016.0996
References
- (2016) Experimental designs and estimation for online display advertising attribution in marketplaces. Marketing Sci. 35(3):465–483.Link, Google Scholar
- (2016) Scalable rejection sampling for Bayesian hierarchical models. Marketing Sci. 35(3):427–444.Abstract, Google Scholar
- (2016) Mining brand perceptions from Twitter social networks. Marketing Sci. 35(3):343–362.Link, Google Scholar
- (2016) Consumer preference elicitation of complex products using fuzzy support vector machine active learning. Marketing Sci. 35(3):445–464.Link, Google Scholar
- (2016) Model-based purchase predictions for large assortments. Marketing Sci. 35(3):389–404.Link, Google Scholar
- (2016) A structured analysis of unstructured big data by leveraging cloud computing. Marketing Sci. 35(3):363–388.Link, Google Scholar
- (2016) A video-based automated recommender (VAR) system for garments. Marketing Sci. 35(3):484–510.Link, Google Scholar
- (2016) Visualizing asymmetric competition among more than 1,000 products using big search data. Marketing Sci. 35(3):511–534.Link, Google Scholar
- (2016) Customer acquisition via display advertising using multi-armed bandit experiments. Marketing Sci. Forthcoming.Google Scholar
- (2016) Crumbs of the cookie: User profiling in customer-base analysis and behavioral targeting. Marketing Sci. 35(3):405–426.Link, Google Scholar
- (2014) The History of Marketing Science (World Scientific Publishing Co., Singapore).Crossref, Google Scholar

