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The Role of Big Data and Predictive Analytics in Retailing
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“Nevertheless, the benefits of big data analytics appear not to be derived from the enormous size of the data, but only emerge when working with fine-grained data (Bradlow et al., 2017;Martens et al., 2016).”
From COVID‐19 Pandemic in the New Era of Big Data Analytics: Methodological Innovations and Future Research Directions (2021) · cites this paper as Bradlow et al., 2017
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Metadata
- Authors
- Bradlow, E. T., Gangwar, M., Kopalle, P., & Voleti, S.
- Affiliations
- University of Pennsylvania (US)
- Indian School of Business (IN)
- Dartmouth College (US)
- Corresponding author
- Kopalle, Praveen
- Venue
- Journal of Retailing
- Publisher
- Elsevier BV
- Published
- 2017-03
- Volume
- 93
- Issue
- 1
- Pages
- 79-95
- ISSN
- 0022-4359 (ISSN-L)
- OpenAlex
- W2599766447
- Cited by
- 516
- References
- 86
- Citations by year
- 2026: 39 · 2025: 59 · 2024: 62 · 2023: 57 · 2022: 71 · 2021: 81 · 2020: 63 · 2019: 47 · 2018: 35 · 2017: 2
- FWCI
- 68.71
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Retailing (publishedVersion)
- Digital Eprints Services at ISB (DESI) (Indian School of Business) (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Social Sciences › Business, Management and Accounting › Management Information Systems › Big Data and Business Intelligence
- Social Sciences › Business, Management and Accounting › Marketing › Consumer Market Behavior and Pricing
- Social Sciences › Decision Sciences › Information Systems and Management › Big Data Technologies and Applications
- Keywords
- big data, predictive analytics, retail trade, customer data, product data, geospatial data, retail channels, Bayesian analysis, hierarchical models, data augmentation, field experiments, data quality, privacy, data ethics
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