On the Efficiency of Cloud Providers: A DEA Approach Incorporating Categorical Variables

Filiopoulou, Evangelia; Mitropoulou, Persefoni; Lionis, Nikolas E.; Michalakelis, Christos

doi:10.1109/tcc.2018.2850889

Cited by 10 publications

(5 citation statements)

References 14 publications

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“…They address the issue of missing values in CSP rankings with an expectationmaximization algorithm and arithmetic residue. Filiopoulou et al (2018) suggested a DEA approach to evaluate the performance of CSPs. Azadi et al (2020) (Barkhi & Kao, 2010), evaluating supply chain management (Toloo, 2014;Toloo & Barat, 2015;Mirhedayatian et al 2014), efficiency evaluation of sustainable suppliers (Azadi et al 2015), technology selection (Wu et al 2016a), allocation of emission reduction tasks (Wu et al 2016b), measuring the performance of humanitarian supply chains (Izadikhah et al (2019), and measuring the impact of enterprise integration on firm performance (Fazlollahi & Franke, 2018).…”

Section: Sustainability and Industry 40 Technologiesmentioning

confidence: 99%

Evaluating efficiency of cloud service providers in era of digital technologies

et al. 2023

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Section: Sustainability and Industry 40 Technologiesmentioning

confidence: 99%

Evaluating efficiency of cloud service providers in era of digital technologies

et al. 2023

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“…There are research on the comparison of cloud computing, such as research conducted by Maurizio Naldi and the team shows a comparison method of cloud computing providers based on the price of the services provided [10]. Meanwhile, research published by Filiopoulou [11] presents an approach that focuses on calculating service efficiencies such as computation optimized instances, memory optimized instances, and storage optimized instances [11]. Other publications conducted by Junjie Peng use the functional requirements of the cloud computing services provided [12].…”

Section: Introductionmentioning

confidence: 99%

Comparison of cloud computing providers for development of big data and internet of things application

Falah

Panduman

Sukaridhoto

et al. 2021

IJEECS

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The improved technology of big data and the internet of things (IoT) increases the number of developments in the application of smart city and Industry 4.0. Thus, the need for high-performance cloud computing is increasing. However, the increase in cloud computing service providers causes difficulties in determining the chosen service provider. Therefore, the purpose of this study is to make comparisons to determine the criteria for selecting cloud computing services following the system architecture and services needed to develop IoT and big data applications. We have analyzed several parameters such as technology specifications, model services, data center location, big data service, internet of things, microservices architecture, cloud computing management, and machine learning. We use these parameters to compare several cloud computing service providers. The results present that the parameters able to use as a reference for choosing cloud computing for the implementation of IoT and big data technology.

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“…al. [2] used DEA to analyses the operational efficiency of the research aspect of the graduate university, In addition, there are some other studies that use DEA in efficiency evaluation in different fields [3,4]. However, traditional DEA models, i.e., CCR and BCC models [1,5], turned out to be defective in ranking DMUs, as they lacked discrimination of DEA efficient DMUs.…”

Section: Iintroductionmentioning

confidence: 99%

Environmental Efficiency Evaluation of the Xiangjiang River Basin: A DEA Cross-Efficiency Approach With Social Network

Cheng

Tao

2021

IEEE Access

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Cross-efficiency in data envelopment analysis is widely used for performance evaluation of decision-making units (DMUs), but it neglects the reference relationship between each pair of DMUs. In order to address the problem, this paper introduces the concept of social network to clearly describe the reference relationship between DMUs and then a fully ranking can be made. A novel cross-efficiency approach is developed by integrating social network analysis in this study. Firstly, we propose a pairwise comparison model based on cross-efficiency evaluation to identify the superiority and inferiority between any pair of DMUs. Secondly, based on pairwise comparison, we build a non-weighted directed social network where a direction generates from one DMU to another DMU if the former one references the latter one. Each edge in the unweighted social network captures the learning procedure from worse-performance DMU to better-performance DMU. Comparing with traditional cross-efficiency approaches, our proposed approach considers the reference relationship among DMUs rather than only cross-efficiency scores. Thus, the importance of each DMU in the network can be measured by its centrality. Finally, the proposed approach is employed to environmental efficiency evaluation of the cities along the Xiangjiang River Basin, then, some beneficial universal policies have been summarized.

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On the Efficiency of Cloud Providers: A DEA Approach Incorporating Categorical Variables

Cited by 10 publications

References 14 publications

Evaluating efficiency of cloud service providers in era of digital technologies

Evaluating efficiency of cloud service providers in era of digital technologies

Comparison of cloud computing providers for development of big data and internet of things application

Environmental Efficiency Evaluation of the Xiangjiang River Basin: A DEA Cross-Efficiency Approach With Social Network

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