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Introduction to the Special Issue on Perspectives on Big Data

Author

Listed:
  • Kalyan Singhal
  • Qi Feng
  • Ram Ganeshan
  • Nada R. Sanders
  • J. George Shanthikumar

Abstract

Big data has the potential of offering valuable insights into the way organizations function, and it is changing the way organizations make decisions. Nine invited essays provide a wide range of perspectives on the role of big data in customer‐driven supply chains, healthcare operations, retail operations, demand planning and manufacturing, environmental and social issues, humanitarian operations, agriculture supply chains, and service operations. Decision makers should have clean, valid, and reliable data, and they should have a thorough understanding of the contexts of applications. Big data shorten virtual distance to customers, and thus facilitate personalization of products and services. Successful implementation of big data applications requires sharing the data with appropriate stakeholders.

Suggested Citation

  • Kalyan Singhal & Qi Feng & Ram Ganeshan & Nada R. Sanders & J. George Shanthikumar, 2018. "Introduction to the Special Issue on Perspectives on Big Data," Production and Operations Management, Production and Operations Management Society, vol. 27(9), pages 1639-1641, September.
    • Handle: RePEc:bla:popmgt:v:27:y:2018:i:9:p:1639-1641
    DOI: 10.1111/poms.12939
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    Cited by:

    1. Chen-Hao Xue & Yong-Ping Bai, 2023. "Spatiotemporal Characteristics and Factors Influencing Urban Tourism Market Network in Western China: Taking Chengdu as an Example," Sustainability, MDPI, vol. 15(10), pages 1-21, May.
    2. Choi, Tsan-Ming & Guo, Shu & Luo, Suyuan, 2020. "When blockchain meets social-media: Will the result benefit social media analytics for supply chain operations management?," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 135(C).
    3. Chuan Lin & Haomiao Zhai & Yanqiu Zhao, 2022. "Industrial Poverty Alleviation, Digital Innovation and Regional Economically Sustainable Growth: Empirical Evidence Based on Local State-Owned Enterprises in China," Sustainability, MDPI, vol. 14(23), pages 1-22, November.
    4. Zhe (James) Zhang & Shivendu Shivendu & Peng Wang, 2021. "Is Investment in Data Analytics Always Profitable? The Case of Third‐Party‐Online‐Promotion Marketplace," Production and Operations Management, Production and Operations Management Society, vol. 30(7), pages 2321-2337, July.
    5. Tomer Geva & Maytal Saar‐Tsechansky, 2021. "Who Is a Better Decision Maker? Data‐Driven Expert Ranking Under Unobserved Quality," Production and Operations Management, Production and Operations Management Society, vol. 30(1), pages 127-144, January.
    6. Sushil Gupta & Medha Tekriwal & Carlos M. Parra, 2022. "Permeation of the term “analytics” in production and operations management research," Production and Operations Management, Production and Operations Management Society, vol. 31(10), pages 3651-3667, October.
    7. Sriram Somanchi & Idris Adjerid & Ralph Gross, 2022. "To Predict or Not to Predict: The Case of the Emergency Department," Production and Operations Management, Production and Operations Management Society, vol. 31(2), pages 799-818, February.
    8. Eva Labro & Mark Lang & Jim Omartian, 2019. "Predictive Analytics and Organizational Architecture: Plant-Level Evidence from Census Data," Working Papers 19-02, Center for Economic Studies, U.S. Census Bureau.
    9. Xiangyu Chang & Yinghui Huang & Mei Li & Xin Bo & Subodha Kumar, 2021. "Efficient Detection of Environmental Violators: A Big Data Approach," Production and Operations Management, Production and Operations Management Society, vol. 30(5), pages 1246-1270, May.
    10. Ren, Ting-hai & Zeng, Neng-min & Wang, Da-fei & Yuan, Kai-fu, 2023. "Authorization or encroachment: Effects of channel encroachment on decisions and performance in software service supply chains," International Journal of Production Economics, Elsevier, vol. 257(C).
    11. Rahul Basole & Elliot Bendoly & Aravind Chandrasekaran & Kevin Linderman, 2022. "Visualization in Operations Management Research," INFORMS Joural on Data Science, INFORMS, vol. 1(2), pages 172-187, October.

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