The Role of Big Data and Predictive Analytics in Retailing

Bradlow, E T and Gangwar, M and Kopalle, P and Voleti, S (2017) The Role of Big Data and Predictive Analytics in Retailing. Journal of Retailing, 93 (1). pp. 79-95.

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Abstract

The paper examines the opportunities in and possibilities arising from big data in retailing, particularly along five major data dimensions—data pertaining to customers, products, time, (geo-spatial) location and channel. Much of the increase in data quality and application possibilities comes from a mix of new data sources, a smart application of statistical tools and domain knowledge combined with theoretical insights. The importance of theory in guiding any systematic search for answers to retailing questions, as well as for streamlining analysis remains undiminished, even as the role of big data and predictive analytics in retailing is set to rise in importance, aided by newer sources of data and large-scale correlational techniques. The Statistical issues discussed include a particular focus on the relevance and uses of Bayesian analysis techniques (data borrowing, updating, augmentation and hierarchical modeling), predictive analytics using big data and a field experiment, all in a retailing context. Finally, the ethical and privacy issues that may arise from the use of big data in retailing are also highlighted.

Affiliation: Indian School of Business
ISB Creators:
ISB CreatorsORCiD
Gangwar, MUNSPECIFIED
Voleti, SUNSPECIFIED
Item Type: Article
Uncontrolled Keywords: Big data; Predictive analytics; Retailing; Pricing
Subjects: Business Analytics
Business and Management
Depositing User: Veeramani R
Date Deposited: 31 Mar 2017 01:36
Last Modified: 31 Mar 2017 01:36
URI: http://eprints.exchange.isb.edu/id/eprint/522
Publisher URL: http://dx.doi.org/10.1016/j.jretai.2016.12.004
Publisher OA policy: http://www.sherpa.ac.uk/romeo/issn/0022-4359/
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