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Evaluating efficiency of cloud service providers in era of digital technologies

Author

Listed:
  • Majid Azadi

    (Aston University)

  • Mehdi Toloo

    (University of Surrey
    Technical University of Ostrava
    Czech Republic, Sultan Qaboos University)

  • Fahimeh Ramezani

    (University of Technology Sydney)

  • Reza Farzipoor Saen

    (Sultan Qaboos University)

  • Farookh Khadeer Hussain

    (University of Technology Sydney)

  • Hajar Farnoudkia

    (Baskent University)

Abstract

The rapid growth of advanced technologies such as cloud computing in the Industry 4.0 era has provided numerous advantages. Cloud computing is one of the most significant technologies of Industry 4.0 for sustainable development. Numerous providers have developed various new services, which have become a crucial ingredient of information systems in many organizations. One of the challenges for cloud computing customers is evaluating potential providers. To date, considerable research has been undertaken to solve the problem of evaluating the efficiency of cloud service providers (CSPs). However, no study addresses the efficiency of providers in the context of an entire supply chain, where multiple services interact to achieve a business objective or goal. Data envelopment analysis (DEA) is a powerful method for efficiency measurement problems. However, the current models ignore undesirable outputs, integer-valued, and stochastic data which can lead to inaccurate results. As such, the primary objective of this paper is to design a decision support system that accurately evaluates the efficiency of multiple CSPs in a supply chain. The current study incorporates undesirable outputs, integer-valued, and stochastic data in a network DEA model for the efficiency measurement of service providers. The results from a case study illustrate the applicability of our new system. The results also show how taking undesirable outputs, integer-valued, and stochastic data into account changes the efficiency of service providers. The system is also able to provide the optimal composition of CSPs to suit a customer’s priorities and requirements.

Suggested Citation

  • Majid Azadi & Mehdi Toloo & Fahimeh Ramezani & Reza Farzipoor Saen & Farookh Khadeer Hussain & Hajar Farnoudkia, 2024. "Evaluating efficiency of cloud service providers in era of digital technologies," Annals of Operations Research, Springer, vol. 342(2), pages 1049-1078, November.
  • Handle: RePEc:spr:annopr:v:342:y:2024:i:2:d:10.1007_s10479-023-05257-x
    DOI: 10.1007/s10479-023-05257-x
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    References listed on IDEAS

    as
    1. Toloo, Mehdi & Hančlová, Jana, 2020. "Multi-valued measures in DEA in the presence of undesirable outputs," Omega, Elsevier, vol. 94(C).
    2. Aitor Ardanza & Aitor Moreno & Álvaro Segura & Mikel de la Cruz & Daniel Aguinaga, 2019. "Sustainable and flexible industrial human machine interfaces to support adaptable applications in the Industry 4.0 paradigm," International Journal of Production Research, Taylor & Francis Journals, vol. 57(12), pages 4045-4059, June.
    3. Kao, Chiang & Liu, Shiang-Tai, 2009. "Stochastic data envelopment analysis in measuring the efficiency of Taiwan commercial banks," European Journal of Operational Research, Elsevier, vol. 196(1), pages 312-322, July.
    4. Mehdi Toloo & Mona Barat, 2015. "On considering dual-role factor in supplier selection problem," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 82(1), pages 107-122, August.
    5. Jie Wu & Zhixiang Zhou, 2015. "A mixed-objective integer DEA model," Annals of Operations Research, Springer, vol. 228(1), pages 81-95, May.
    6. Tone, Kaoru & Tsutsui, Miki, 2009. "Network DEA: A slacks-based measure approach," European Journal of Operational Research, Elsevier, vol. 197(1), pages 243-252, August.
    7. Tone, Kaoru & Toloo, Mehdi & Izadikhah, Mohammad, 2020. "A modified slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 287(2), pages 560-571.
    8. Kao, Chiang, 2016. "Efficiency decomposition and aggregation in network data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 255(3), pages 778-786.
    9. Cooper, William W. & Deng, H. & Huang, Zhimin & Li, Susan X., 2004. "Chance constrained programming approaches to congestion in stochastic data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 155(2), pages 487-501, June.
    10. Li, Wanghong & Li, Zhepeng & Liang, Liang & Cook, Wade D., 2017. "Evaluation of ecological systems and the recycling of undesirable outputs: An efficiency study of regions in China," Socio-Economic Planning Sciences, Elsevier, vol. 60(C), pages 77-86.
    11. Basaure, Arturo & Vesselkov, Alexandr & Töyli, Juuso, 2020. "Internet of things (IoT) platform competition: Consumer switching versus provider multihoming," Technovation, Elsevier, vol. 90.
    12. Kao, Chiang, 2014. "Network data envelopment analysis: A review," European Journal of Operational Research, Elsevier, vol. 239(1), pages 1-16.
    13. Du, Juan & Chen, Chien-Ming & Chen, Yao & Cook, Wade D. & Zhu, Joe, 2012. "Additive super-efficiency in integer-valued data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 218(1), pages 186-192.
    14. Benedikt Martens & Frank Teuteberg, 2012. "Decision-making in cloud computing environments: A cost and risk based approach," Information Systems Frontiers, Springer, vol. 14(4), pages 871-893, September.
    15. Liu, Wenbin & Zhou, Zhongbao & Ma, Chaoqun & Liu, Debin & Shen, Wanfang, 2015. "Two-stage DEA models with undesirable input-intermediate-outputs," Omega, Elsevier, vol. 56(C), pages 74-87.
    16. Mirhedayatian, Seyed Mostafa & Azadi, Majid & Farzipoor Saen, Reza, 2014. "A novel network data envelopment analysis model for evaluating green supply chain management," International Journal of Production Economics, Elsevier, vol. 147(PB), pages 544-554.
    17. Özden Tozanlı & Elif Kongar & Surendra M. Gupta, 2020. "Trade-in-to-upgrade as a marketing strategy in disassembly-to-order systems at the edge of blockchain technology," International Journal of Production Research, Taylor & Francis Journals, vol. 58(23), pages 7183-7200, December.
    18. Huang, Chin-wei, 2018. "Assessing the performance of tourism supply chains by using the hybrid network data envelopment analysis model," Tourism Management, Elsevier, vol. 65(C), pages 303-316.
    19. Fazlollahi, Ariyan & Franke, Ulrik, 2018. "Measuring the impact of enterprise integration on firm performance using data envelopment analysis," International Journal of Production Economics, Elsevier, vol. 200(C), pages 119-129.
    20. Chen, Lei & Wang, Ying-Ming & Lai, Fujun, 2017. "Semi-disposability of undesirable outputs in data envelopment analysis for environmental assessments," European Journal of Operational Research, Elsevier, vol. 260(2), pages 655-664.
    21. Kazemi Matin, Reza & Kuosmanen, Timo, 2009. "Theory of integer-valued data envelopment analysis under alternative returns to scale axioms," Omega, Elsevier, vol. 37(5), pages 988-995, October.
    22. Ramachandran, Muthu & Chang, Victor, 2016. "Towards performance evaluation of cloud service providers for cloud data security," International Journal of Information Management, Elsevier, vol. 36(4), pages 618-625.
    23. Chiang Kao, 2014. "Efficiency Decomposition in Network Data Envelopment Analysis," International Series in Operations Research & Management Science, in: Wade D. Cook & Joe Zhu (ed.), Data Envelopment Analysis, edition 127, chapter 0, pages 55-77, Springer.
    24. Jie Wu & Qingyuan Zhu & Junfei Chu & Qingxian An & Liang Liang, 2016. "A DEA-based approach for allocation of emission reduction tasks," International Journal of Production Research, Taylor & Francis Journals, vol. 54(18), pages 5618-5633, September.
    25. Talluri, Srinivas & Narasimhan, Ram & Nair, Anand, 2006. "Vendor performance with supply risk: A chance-constrained DEA approach," International Journal of Production Economics, Elsevier, vol. 100(2), pages 212-222, April.
    26. W W Cooper & H Deng & Z Huang & S X Li, 2002. "Chance constrained programming approaches to technical efficiencies and inefficiencies in stochastic data envelopment analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(12), pages 1347-1356, December.
    27. Seiford, Lawrence M. & Zhu, Joe, 2002. "Modeling undesirable factors in efficiency evaluation," European Journal of Operational Research, Elsevier, vol. 142(1), pages 16-20, October.
    28. Jie Wu & Junfei Chu & Qingyuan Zhu & Pengzhen Yin & Liang Liang, 2016. "DEA cross-efficiency evaluation based on satisfaction degree: an application to technology selection," International Journal of Production Research, Taylor & Francis Journals, vol. 54(20), pages 5990-6007, October.
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