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Evaluation of cloud service industry with dynamic and network DEA models

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  • Kao, Han-Ying
  • Wu, Dong-Jyun
  • Huang, Chia-Hui

Abstract

Recently, cloud services and computing have revolutionized both academic research and industrial practices. Numerous hardware and software providers have joined the intensely competitive cloud services market. At the same time, a corresponding focus on evaluation of the industry is growing apace. Investigations are currently under way into how to incorporate the dynamic and intermediate processes in cloud service companies' business models. This paper intends to develop some alternative models of network data envelopment analysis (NDEA) for evaluating cloud service businesses. By considering various internal functions and processes of the services in multi-period settings, we design three evaluation models: (1) dynamic black-box data envelopment analysis (DBDEA); (2) static network data envelopment analysis (SNDEA); and (3) dynamic network data envelopment analysis (DNDEA). Using multi-objective programming (MOP) techniques, the three NDEA models are formulated and solved for the cloud service industry. An empirical study is conducted to evaluate the performance of the cloud service industry.

Suggested Citation

  • Kao, Han-Ying & Wu, Dong-Jyun & Huang, Chia-Hui, 2017. "Evaluation of cloud service industry with dynamic and network DEA models," Applied Mathematics and Computation, Elsevier, vol. 315(C), pages 188-202.
    • Handle: RePEc:eee:apmaco:v:315:y:2017:i:c:p:188-202
    DOI: 10.1016/j.amc.2017.07.059
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    References listed on IDEAS

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