Abstract
An increasing number of organizations and businesses around the world use cloud computing services to improve their performance in the competitive marketplace. However, one of the biggest challenges in using cloud computing services is performance measurement and the selection of the best cloud service providers (CSPs) based on quality of service (QoS) requirements (Duan, 2017). To address this shortcoming in this article we propose a network data envelopment analysis (DEA) method in measuring the efficiency of CSPs. When network dimensions are taken into consideration, a more comprehensive analysis is enabled where divisional efficiency is reflected in overall efficiency estimates. This helps managers and decision makers in organizations to make accurate decisions in selecting cloud services. In the current study, variable returns to scale (VRS), the non-oriented network slacks-based measure (SBM) model and input-oriented and output-oriented SBM models are applied to measure the performance of 18 CSPs. The obtained results show the superiority of the network DEA model and they also demonstrate that the proposed model can evaluate and rank CSPs much better than compared to traditional DEA models.
Original language | English |
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Journal | IEEE Transactions on Cloud Computing |
Early online date | 9 Jul 2019 |
DOIs | |
Publication status | E-pub ahead of print - 9 Jul 2019 |
Bibliographical note
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- Analytical models
- Cloud computing
- Cloud service providers (CSPs)
- Computational modeling
- Data Envelopment Analysis
- Data envelopment analysis
- Efficiency measurement
- Information technology
- Measurement
- Network slacks-based measure (SBM) model
- Performance measures
- Quality of service