Big Data Analytics in Operations Management

被引:372
作者
Choi, Tsan-Ming [1 ]
Wallace, Stein W. [2 ]
Wang, Yulan [3 ]
机构
[1] Hong Kong Polytech Univ, Fac Appl Sci & Text, Inst Text & Clothing, Business Div, Kowloon, Hong Kong, Peoples R China
[2] NHH Norwegian Sch Econ, Dept Business & Management Sci, NO-5045 Bergen, Norway
[3] Hong Kong Polytech Univ, Fac Business, Kowloon, Hong Kong, Peoples R China
关键词
Big data analytics; big data methods; operations management; data-driven optimization; applications and case studies; SUPPLY CHAINS; DATA SCIENCE; CLOUD; RESILIENCE; REVOLUTION; SYSTEMS; DEMAND; DESIGN;
D O I
10.1111/poms.12838
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
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.
引用
收藏
页码:1868 / 1883
页数:16
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