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An empirical study on business analytics affordances enhancing the management of cloud computing data security

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  • Wang, Zhiying
  • Wang, Nianxin
  • Su, Xiang
  • Ge, Shilun

Abstract

The mechanism of business analytics affordances enhancing the management of cloud computing data security is a key antecedent in improving cloud computing security. Based on information value chain theory and IT affordances theory, a research model is built to investigate the underlying mechanism of business analytics affordances enhancing the management of cloud computing data security. The model includes business analytics affordances, decision-making affordances of cloud computing data security, decision-making rationality of cloud computing data security, and the management of cloud computing data security. Simultaneously, the model considers the role of data-driven culture and IT business process integration. It is empirically tested using data collected from 316 enterprises by Partial Least Squares-based structural equation model. Without data-driven culture and IT business process integration, the results suggest that there is a process from business analytics affordances to decision-making affordances of cloud computing data security, decision-making rationality of cloud computing data security, and to the management of cloud computing data security. Moreover, Data-driven culture and IT business process integration have a positive mediation effect on the relationship between business analytics affordances and decision-making affordances of cloud computing data security. The conclusions in this study provide useful references for the enterprise to strengthen the management of cloud computing data security using business analytics.

Suggested Citation

  • Wang, Zhiying & Wang, Nianxin & Su, Xiang & Ge, Shilun, 2020. "An empirical study on business analytics affordances enhancing the management of cloud computing data security," International Journal of Information Management, Elsevier, vol. 50(C), pages 387-394.
    • Handle: RePEc:eee:ininma:v:50:y:2020:i:c:p:387-394
    DOI: 10.1016/j.ijinfomgt.2019.09.002
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    Citations

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    Cited by:

    1. Mohammad Taghi Taghavifard & Setareh Majidian, 2022. "Identifying Cloud Computing Risks based on Firm’s Ambidexterity Performance using Fuzzy VIKOR Technique," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 23(1), pages 113-133, March.
    2. Steffen Kurpiela & Frank Teuteberg, 2024. "Linking business analytics affordances to corporate strategic planning and decision making outcomes," Information Systems and e-Business Management, Springer, vol. 22(1), pages 33-60, March.
    3. Marina Proença & Tomas Sparano Martins, 2024. "The role of absorptive capacity in the use of digital marketing analytics for effective marketing decisions," Journal of Marketing Analytics, Palgrave Macmillan, vol. 12(3), pages 687-700, September.
    4. Shahriar Akter & Katina Michael & Muhammad Rajib Uddin & Grace McCarthy & Mahfuzur Rahman, 2022. "Transforming business using digital innovations: the application of AI, blockchain, cloud and data analytics," Annals of Operations Research, Springer, vol. 308(1), pages 7-39, January.
    5. Chaudhuri, Ranjan & Chatterjee, Sheshadri & Mariani, Marcello M. & Wamba, Samuel Fosso, 2024. "Assessing the influence of emerging technologies on organizational data driven culture and innovation capabilities: A sustainability performance perspective," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    6. D'Ambra, John & Akter, Shahriar & Mariani, Marcello, 2022. "Digital transformation of higher education in Australia: Understanding affordance dynamics in E-Textbook engagement and use," Journal of Business Research, Elsevier, vol. 149(C), pages 283-295.

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