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Big data in managerial decision-making: concerns and concepts to reduce risk

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  • Jeffrey W. Alstete
  • E. Gregory M. Cannarozzi

Abstract

This concept paper examines issues concerning information accuracy and privacy that business managers should consider to reduce risks in decision-making when using the large volumes of data that is now readily available. Related literature on 'big data' and managerial decision-making concepts in relation to ethical and legal issues are considered and expounded. Previous decision-making schemas are surveyed and enhanced based on the analysis of current observations. A proposed model of managerial decision-making with big data that can help formulate more ethical and legally sound choices is presented in illustration with a detailed explanation. The limits of the ideas offered as well as recommendations for further research and policies on the usage and outcomes of big data's impact on organisational effectiveness are suggested.

Suggested Citation

  • Jeffrey W. Alstete & E. Gregory M. Cannarozzi, 2014. "Big data in managerial decision-making: concerns and concepts to reduce risk," International Journal of Business Continuity and Risk Management, Inderscience Enterprises Ltd, vol. 5(1), pages 57-71.
    • Handle: RePEc:ids:ijbcrm:v:5:y:2014:i:1:p:57-71
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    References listed on IDEAS

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    1. Mats Alvesson & Jörgen Sandberg, 2013. "Has Management Studies Lost Its Way? Ideas for More Imaginative and Innovative Research," Journal of Management Studies, Wiley Blackwell, vol. 50(1), pages 128-152, January.
    2. Paul C. Nutt, 2008. "Investigating the Success of Decision Making Processes," Journal of Management Studies, Wiley Blackwell, vol. 45(2), pages 425-455, March.
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    Cited by:

    1. A. R. Khasanov, 2018. "Impact Of Predictive Analytics On The Activities Of Companies," Strategic decisions and risk management, Real Economy Publishing House, issue 3.
    2. Weihong Xie & Qian Zhang & Yuyao Lin & Zhong Wang & Zhongshun Li, 2024. "The Effect of Big Data Capability on Organizational Innovation: a Resource Orchestration Perspective," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(1), pages 3767-3791, March.

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