Abstract
Big data analytics is critical in modern operations management (OM). In this study, we first explore the existing big data-related analytics techniques, and identify their strengths, weaknesses as well as major functionalities. We then discuss various big data analytics strategies to overcome the respective computational and data challenges. After that, we examine the literature and reveal how different types of big data methods (techniques, strategies, and architectures) can be applied to different OM topical areas, namely forecasting, inventory management, revenue management and marketing, transportation management, supply chain management, and risk analysis. We also investigate via case studies the real-world applications of big data analytics in top branded enterprises. Finally, we conclude the study with a discussion of future research.
Original language | English |
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Pages (from-to) | 1868-1883 |
Number of pages | 16 |
Journal | Production and Operations Management |
Volume | 27 |
Issue number | 10 |
DOIs | |
Publication status | Published - 1 Oct 2018 |
Keywords
- applications and case studies
- Big data analytics
- big data methods
- data-driven optimization
- operations management
ASJC Scopus subject areas
- Management Science and Operations Research
- Industrial and Manufacturing Engineering
- Management of Technology and Innovation