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Risk Factor Assessment Improvement for China’s Cloud Computing Auditing Using a New Hybrid MADM Model

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  • Kuang-Hua Hu

    (School of Accounting, Guangdong University Finance and Economics, 21 Chisha Road, Haizhu District, Guangzhou 510320, P. R. China)

  • Wei Jianguo

    (#x2020;Accounting School, Nanfang College of Sun Yat-sen University, Wenquan Town, Conghua, Guangzhou 510970, P. R. China)

  • Gwo-Hshiung Tzeng

    (#x2021;Graduate Institute of Urban Planning, College of Public Affairs, National Taipei University, 151, University Rd., San Shia District, New Taipei City 23741, Taiwan)

Abstract

With the rapid growth of modern technology in all facets of trade and industry, traditional auditing systems can no longer meet today’s ever-increasing technological requirements; contemporary auditing is in urgent need of straightforward and quick cloud computing services to meet the needs of auditors. In keeping with current trends, auditors must be provided with the means of using data and auditing information stored in cloud systems for more efficient and elastic auditing. However, the risks involved in cloud computing auditing are widespread and complex. Dimensions should be established, a mutually influential relationship used to delineate the influence weights of the dimensions and criteria should be determined. To this end, a Multiple Attribute Decision Making (MADM) model can precisely solve multi-criteria problems simultaneously. Therefore, the main focus of this study is to determine how to assess and establish the best improvement strategies to achieve the aspiration level for cloud auditing risk factors, by using the opinions and practical experience of China’s accounting experts, applied with a Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique, DEMATEL-based ANP (DANP) and modified VIKOR method. The results provide cloud auditing risks with a knowledge-based understanding of the problem sources in order to establish the best improvement strategies for reducing risk-auditing performance gaps and attaining the aspiration levels. Based on the degree of impact of the dimensions/criteria on an Influence Network Relation Map (INRM), improvements should be prioritized as follows: system operations, technology risks, identity and access management and data protection.

Suggested Citation

  • Kuang-Hua Hu & Wei Jianguo & Gwo-Hshiung Tzeng, 2017. "Risk Factor Assessment Improvement for China’s Cloud Computing Auditing Using a New Hybrid MADM Model," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 16(03), pages 737-777, May.
  • Handle: RePEc:wsi:ijitdm:v:16:y:2017:i:03:n:s021962201750016x
    DOI: 10.1142/S021962201750016X
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    References listed on IDEAS

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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. Sheng-Hau Lin & Danyang Wang & Xianjin Huang & Xiaofeng Zhao & Jing-Chzi Hsieh & Gwo-Hshiung Tzeng & Jia-Hsuan Li & Jia-Tsong Chen, 2021. "A multi-attribute decision-making model for improving inefficient industrial parks," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(1), pages 887-921, January.

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