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Model and experimental development for Business Data Science

Author

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  • Newman, Russell
  • Chang, Victor
  • Walters, Robert John
  • Wills, Gary Brian

Abstract

While Data Science has become increasingly significant for business strategies, operations, performance, efficiency and prediction, there is little work on this to provide a detailed guideline. We have proposed a Business Data Science (BDS) model that focuses on the model and experimental development that allows different types of functions, processes and roles to work together collaboratively for efficiency and performance improvements. Details with examples have been illustrated to show that BDS model can be a robust model. Future directions have been discussed to ensure that business intelligence, security, analytics and research contributions to BDS can be achieved.

Suggested Citation

  • Newman, Russell & Chang, Victor & Walters, Robert John & Wills, Gary Brian, 2016. "Model and experimental development for Business Data Science," International Journal of Information Management, Elsevier, vol. 36(4), pages 607-617.
    • Handle: RePEc:eee:ininma:v:36:y:2016:i:4:p:607-617
    DOI: 10.1016/j.ijinfomgt.2016.04.004
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    References listed on IDEAS

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    1. Chang, Victor & Newman, Russell & Walters, Robert John & Wills, Gary Brian, 2016. "Review of economic bubbles," International Journal of Information Management, Elsevier, vol. 36(4), pages 497-506.
    2. Sahlman, William A. & Stevenson, Howard H., 1985. "Capital market myopia," Journal of Business Venturing, Elsevier, vol. 1(1), pages 7-30.
    3. Chang, Victor & Walters, Robert John & Wills, Gary Brian, 2016. "Organisational sustainability modelling—An emerging service and analytics model for evaluating Cloud Computing adoption with two case studies," International Journal of Information Management, Elsevier, vol. 36(1), pages 167-179.
    4. Chang, Victor & Walters, Robert John & Wills, Gary, 2013. "The development that leads to the Cloud Computing Business Framework," International Journal of Information Management, Elsevier, vol. 33(3), pages 524-538.
    5. Chang, Victor & Ramachandran, Muthu & Yao, Yulin & Kuo, Yen-Hung & Li, Chung-Sheng, 2016. "A resiliency framework for an enterprise cloud," International Journal of Information Management, Elsevier, vol. 36(1), pages 155-166.
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    Cited by:

    1. Larson, Deanne & Chang, Victor, 2016. "A review and future direction of agile, business intelligence, analytics and data science," International Journal of Information Management, Elsevier, vol. 36(5), pages 700-710.
    2. Yousafzai, Abdullah & Chang, Victor & Gani, Abdullah & Noor, Rafidah Md., 2016. "Directory-based incentive management services for ad-hoc mobile clouds," International Journal of Information Management, Elsevier, vol. 36(6), pages 900-906.

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