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A Decision-Making Model for Adopting a Cloud Computing System

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  • Seok-Keun Yoo

    (Seoul Business School, Seoul School of Sciences and Technologies (aSSIST), Seoul 03767, Korea)

  • Bo-Young Kim

    (Seoul Business School, Seoul School of Sciences and Technologies (aSSIST), Seoul 03767, Korea)

Abstract

The use of big data, artificial intelligence, and new information and communication technologies has led to sustainable developments and improved business competitiveness. Until recently cloud services were classified as having special system requirements for a business organization, and was represented by different cloud computing architecture layers like infrastructure, platform, or software as a service. However, as the environment of IT services undergoes successive changes, companies have been required to reconsider their business models and consider adopting a cloud computing system, which can bring on business achievements and development. Regarding a decision-making model for adopting a cloud computing system, this paper analyzes critical variables in a hierarchical structure of decision areas: technology, organization, and environment, as well as seven factors and 23 attributes based on underlying decision factors of cloud computing adoption by AHP (Analytic Hierarchy Process) and Delphi analysis. Furthermore, this research explores a comparative analysis between demanders and providers of cloud computing adoption. Resultantly, this study suggests several important factors for adopting a cloud computing system: top management support, competitive pressure, and compatibility. From the demander side, the high priority factor was compatibility and competitive pressure; in contrast, related advantage and top management support were regarded as priority factors for providers to service their cloud computing systems.

Suggested Citation

  • Seok-Keun Yoo & Bo-Young Kim, 2018. "A Decision-Making Model for Adopting a Cloud Computing System," Sustainability, MDPI, vol. 10(8), pages 1-15, August.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:8:p:2952-:d:164649
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    References listed on IDEAS

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    3. Yuquan Meng & Yuhang Yang & Haseung Chung & Pil-Ho Lee & Chenhui Shao, 2018. "Enhancing Sustainability and Energy Efficiency in Smart Factories: A Review," Sustainability, MDPI, vol. 10(12), pages 1-28, December.
    4. Darell Edmond & Vijay Prakash & Lalit Garg & Seema Bawa, 2022. "Adoption of Cloud Services in Central Banks: Hindering Factors and the Recommendations for Way Forward," Journal of Central Banking Theory and Practice, Central bank of Montenegro, vol. 11(2), pages 123-143.
    5. Di Vaio, Assunta & Palladino, Rosa & Hassan, Rohail & Escobar, Octavio, 2020. "Artificial intelligence and business models in the sustainable development goals perspective: A systematic literature review," Journal of Business Research, Elsevier, vol. 121(C), pages 283-314.
    6. Muhammad Janas Khan & Fasee Ullah & Muhammad Imran & Jahangir Khan & Arshad Khan & Ahmed S. AlGhamdi & Sultan S. Alshamrani, 2022. "Identifying Challenges for Clients in Adopting Sustainable Public Cloud Computing," Sustainability, MDPI, vol. 14(16), pages 1-27, August.
    7. Chang Hee Yoon & Francis Joseph Costello & Cheong Kim, 2019. "Assisting Sustainable Entrepreneurial Activities Through the Analysis of Mobile IT Services’ Success and Failure Factors," Sustainability, MDPI, vol. 11(20), pages 1-22, October.
    8. Manideep Yenugula & Shankha Shubhra Goswami & Subramaniam Kaliappan & Rengaraj Saravanakumar & Areej Alasiry & Mehrez Marzougui & Abdulaziz AlMohimeed & Ahmed Elaraby, 2023. "Analyzing the Critical Parameters for Implementing Sustainable AI Cloud System in an IT Industry Using AHP-ISM-MICMAC Integrated Hybrid MCDM Model," Mathematics, MDPI, vol. 11(15), pages 1-35, August.
    9. Osama Abied & Othman Ibrahim & Siti Nuur-Ila Mat Kamal & Ibrahim M. Alfadli & Weam M. Binjumah & Norafida Ithnin & Maged Nasser, 2022. "Probing Determinants Affecting Intention to Adopt Cloud Technology in E-Government Systems," Sustainability, MDPI, vol. 14(23), pages 1-29, November.
    10. Agata Sudolska & Andrzej Lis & Róża Błaś, 2019. "Cloud Computing Research Profiling: Mapping Scholarly Community and Identifying Thematic Boundaries of the Field," Social Sciences, MDPI, vol. 8(4), pages 1-20, April.
    11. Johannes Enzmann & Marc Ringel, 2020. "Reducing Road Transport Emissions in Europe: Investigating A Demand Side Driven Approach †," Sustainability, MDPI, vol. 12(18), pages 1-31, September.
    12. Assunta Di Vaio & Flavio Boccia & Loris Landriani & Rosa Palladino, 2020. "Artificial Intelligence in the Agri-Food System: Rethinking Sustainable Business Models in the COVID-19 Scenario," Sustainability, MDPI, vol. 12(12), pages 1-12, June.
    13. Hiran, Kamal Kant & Dadhich, Manish, 2024. "Predicting the core determinants of cloud-edge computing adoption (CECA) for sustainable development in the higher education institutions of Africa: A high order SEM-ANN analytical approach," Technological Forecasting and Social Change, Elsevier, vol. 199(C).

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