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A hybrid multi-criteria decision-making method for cloud adoption: Evidence from the healthcare sector

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  • Sharma, Mahak
  • Sehrawat, Rajat

Abstract

The purpose of this paper is to investigate the main determinants (criteria as well as sub-criteria) influencing the adoption decision of cloud computing (CC) in the healthcare sector. In the present study, qualitative interviews and the Delphi method are used to find the relevance of identified determinants (criteria and sub-criteria) from literature. Further, an integrated hybrid approach of interpretive structural modeling, analytic hierarchy process, and Technique for Order Preference by Similarity to Ideal Solution (ISM-AHP-TOPSIS) have been employed to identify interrelationships among criteria, rank critical criteria as well as subcriteria, and find the most suitable cloud service provider (CSP) respectively. This study analyses seven criteria and twenty-one sub-criteria that offers a roadmap to decision-makers before CC-adoption (CCA). The analysis of ISM and AHP revealed technology as the most critical and human-environment as the least critical criteria. The vital sub-criteria associated with each criterion are Management Strategic Planning (under Organisation), Government Policy (External Environment), Security (Technology), Financing of IT in Hospital (Economic), Perceived Visibility (Social), and Attitude of Colleagues about Cloud Computing (Human Environment). The results from TOPSIS revealed CSP5 being the most suitable service provider followed by CSP2. Finally, this research makes methodological contribution in terms of an integrated hybrid method, to select a suitable CSP for the healthcare sector and the theoretical contribution in terms of criteria & sub-criteria. This article answers an important question, i.e., whether the benefits of CCA outweighs its barriers, thereby exploring the potential (and future) of CC for the advancement of healthcare provision.

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  • Sharma, Mahak & Sehrawat, Rajat, 2020. "A hybrid multi-criteria decision-making method for cloud adoption: Evidence from the healthcare sector," Technology in Society, Elsevier, vol. 61(C).
    • Handle: RePEc:eee:teinso:v:61:y:2020:i:c:s0160791x19306724
    DOI: 10.1016/j.techsoc.2020.101258
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    References listed on IDEAS

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    Cited by:

    1. Sharma, Mahak & Antony, Rose & Sehrawat, Rajat & Cruz, Angel Contreras & Daim, Tugrul U., 2022. "Exploring post-adoption behaviors of e-service users: Evidence from the hospitality sector /online travel services," Technology in Society, Elsevier, vol. 68(C).
    2. Sami S. Binyamin & Md. Rakibul Hoque, 2020. "Understanding the Drivers of Wearable Health Monitoring Technology: An Extension of the Unified Theory of Acceptance and Use of Technology," Sustainability, MDPI, vol. 12(22), pages 1-20, November.
    3. Han, Yilong & Li, Yinbo & Li, Yongkui & Yang, Bin & Cao, Lingyan, 2023. "Digital twinning for smart hospital operations: Framework and proof of concept," Technology in Society, Elsevier, vol. 74(C).
    4. Sharma, Mahak & Singh, Anupama & Daim, Tugrul, 2023. "Exploring cloud computing adoption: COVID era in academic institutions," Technological Forecasting and Social Change, Elsevier, vol. 193(C).
    5. Kumar, Shashank & Raut, Rakesh D. & Agrawal, Nishant & Cheikhrouhou, Naoufel & Sharma, Mahak & Daim, Tugrul, 2022. "Integrated blockchain and internet of things in the food supply chain: Adoption barriers," Technovation, Elsevier, vol. 118(C).
    6. Sharma, Mahak & Sehrawat, Rajat & Daim, Tugrul & Shaygan, Amir, 2021. "Technology assessment: Enabling Blockchain in hospitality and tourism sectors," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
    7. Naeini, Ali Bonyadi & Zamani, Mehdi & Daim, Tugrul U. & Sharma, Mahak & Yalcin, Haydar, 2022. "Conceptual structure and perspectives on “innovation management”: A bibliometric review," Technological Forecasting and Social Change, Elsevier, vol. 185(C).
    8. Azadi, Majid & Yousefi, Saeed & Farzipoor Saen, Reza & Shabanpour, Hadi & Jabeen, Fauzia, 2023. "Forecasting sustainability of healthcare supply chains using deep learning and network data envelopment analysis," Journal of Business Research, Elsevier, vol. 154(C).
    9. Singh, Pratibha & Sharma, Mahak & Daim, Tugrul, 2024. "Envisaging AR travel revolution for visiting heritage sites: A mixed-method approach," Technology in Society, Elsevier, vol. 76(C).
    10. Yang, Chih-Hao & Hsu, Wei & Wu, Yong-Lin, 2022. "A hybrid multiple-criteria decision portfolio with the resource constraints model of a smart healthcare management system for public medical centers," Socio-Economic Planning Sciences, Elsevier, vol. 80(C).
    11. Xiaowei Guan & Jun Zhao, 2022. "A Two-Step Fuzzy MCDM Method for Implementation of Sustainable Precision Manufacturing: Evidence from China," Sustainability, MDPI, vol. 14(13), pages 1-27, July.
    12. Shahbaz, Muhammad & Zahid, Rimsha, 2022. "Probing the factors influencing cloud computing adoption in healthcare organizations: A three-way interaction model," Technology in Society, Elsevier, vol. 71(C).
    13. Naim Ahmad & Ayman Qahmash, 2021. "SmartISM: Implementation and Assessment of Interpretive Structural Modeling," Sustainability, MDPI, vol. 13(16), pages 1-27, August.
    14. Lin, Sheng-Hau & Zhang, Hejie & Li, Jia-Hsuan & Ye, Cheng-Zhou & Hsieh, Jing-Chzi, 2022. "Evaluating smart office buildings from a sustainability perspective: A model of hybrid multi-attribute decision-making," Technology in Society, Elsevier, vol. 68(C).
    15. Christine Abdalla Mikhaeil & Tabitha James, 2023. "Examining the case of French hesitancy toward IDaaS solutions: Technical and social contextual factors of the organizational IDaaS privacy calculus," Post-Print hal-04130774, HAL.
    16. Torkayesh, Ali Ebadi & Torkayesh, Sajjad Ebadi, 2021. "Evaluation of information and communication technology development in G7 countries: An integrated MCDM approach," Technology in Society, Elsevier, vol. 66(C).

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