Big Data Analytics in Operations Management

Tsan-Ming Choi; Stein W. Wallace; Yulan Wang

doi:10.1111/poms.12838

Big Data Analytics in Operations Management

Tsan-Ming Choi¹; Stein W. Wallace²; Yulan Wang³

¹ Business Division, Institute of Textiles and Clothing, Faculty of Applied Science and Textiles, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong · ² Department of Business and Management Science, NHH Norwegian School of Economics, NO‐5045, Bergen, Norway · ³ Faculty of Business, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong

Production and Operations Management 2018

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.

DOI: 10.1111/poms.12838
Volume: 27 (10)
Pages: 1868-1883
Language: en
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