Effective Decision Making: Data Envelopment Analysis for Efficiency Evaluation in the Cloud Computing Marketplaces
Assessing business performance is a critical issue for practicing managers, and business performance has always been of interest to managers and researchers. In recent years, the world has experienced a rapid growth in the cloud computing service sector thanks to its benefits to business organizatio...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-11-01
|
| Series: | Axioms |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-1680/10/4/309 |
| _version_ | 1797506598350880768 |
|---|---|
| author | Chia-Nan Wang Minh-Nhat Nguyen Thi-Duong Nguyen Hsien-Pin Hsu Thi-Hai-Yen Nguyen |
| author_facet | Chia-Nan Wang Minh-Nhat Nguyen Thi-Duong Nguyen Hsien-Pin Hsu Thi-Hai-Yen Nguyen |
| author_sort | Chia-Nan Wang |
| collection | DOAJ |
| description | Assessing business performance is a critical issue for practicing managers, and business performance has always been of interest to managers and researchers. In recent years, the world has experienced a rapid growth in the cloud computing service sector thanks to its benefits to business organizations and economic development. Therefore, the performance efficiency of this sector has been concerned as one of the keys in today’s economic environment. This study aimed to assess the performance efficiency of cloud computing service providers in the United States of America, one of the biggest global markets in terms of cloud computing, by applying the data envelopment analysis models. The efficiency of cloud computing providers was evaluated based on the assumption of the non-cooperative game among cloud computing providers in which providers selfishly choose the best strategy to maximize their payoff with three stages. In the first stage, the performance of these providers over the past period was measured by a super slack-based measure. In the second stage, the performance in the future period was predicted by the new data envelopment analysis model: the past–present–future model based on resampling. In the last stage, the efficiency improvement was investigated by adopting the Malmquist productivity index. The findings of this study indicated that the percentage of inefficient providers would increase from 10% in the period from 2017 to 2020 to 20% for 2021 and 2024. Moreover, 30% of providers showed a regress in performance efficiency over the research period of 2017 to 2024. The results of this study provide an insight picture to the decision-makers, and this research will fill the gap in the literature as the first study that measures and predicts the performance efficiency of cloud computing service providers, which will provide a helpful reference for future studies. |
| first_indexed | 2024-03-10T04:34:50Z |
| format | Article |
| id | doaj.art-89af0ea09a6a4b82be8c6525651a4d0d |
| institution | Directory Open Access Journal |
| issn | 2075-1680 |
| language | English |
| last_indexed | 2024-03-10T04:34:50Z |
| publishDate | 2021-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Axioms |
| spelling | doaj.art-89af0ea09a6a4b82be8c6525651a4d0d2023-11-23T03:49:52ZengMDPI AGAxioms2075-16802021-11-0110430910.3390/axioms10040309Effective Decision Making: Data Envelopment Analysis for Efficiency Evaluation in the Cloud Computing MarketplacesChia-Nan Wang0Minh-Nhat Nguyen1Thi-Duong Nguyen2Hsien-Pin Hsu3Thi-Hai-Yen Nguyen4Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung 80778, TaiwanDepartment of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung 80778, TaiwanThe International School, Duy Tan University, Danang 50000, VietnamDepartment of Supply Chain Management, National Kaohsiung University of Science and Technology, Kaohsiung 80778, TaiwanDepartment of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung 80778, TaiwanAssessing business performance is a critical issue for practicing managers, and business performance has always been of interest to managers and researchers. In recent years, the world has experienced a rapid growth in the cloud computing service sector thanks to its benefits to business organizations and economic development. Therefore, the performance efficiency of this sector has been concerned as one of the keys in today’s economic environment. This study aimed to assess the performance efficiency of cloud computing service providers in the United States of America, one of the biggest global markets in terms of cloud computing, by applying the data envelopment analysis models. The efficiency of cloud computing providers was evaluated based on the assumption of the non-cooperative game among cloud computing providers in which providers selfishly choose the best strategy to maximize their payoff with three stages. In the first stage, the performance of these providers over the past period was measured by a super slack-based measure. In the second stage, the performance in the future period was predicted by the new data envelopment analysis model: the past–present–future model based on resampling. In the last stage, the efficiency improvement was investigated by adopting the Malmquist productivity index. The findings of this study indicated that the percentage of inefficient providers would increase from 10% in the period from 2017 to 2020 to 20% for 2021 and 2024. Moreover, 30% of providers showed a regress in performance efficiency over the research period of 2017 to 2024. The results of this study provide an insight picture to the decision-makers, and this research will fill the gap in the literature as the first study that measures and predicts the performance efficiency of cloud computing service providers, which will provide a helpful reference for future studies.https://www.mdpi.com/2075-1680/10/4/309cloud computingdata envelopment analysisresampling modelMalmquist productivity indexdecision-making proceduresnon-cooperative game theory |
| spellingShingle | Chia-Nan Wang Minh-Nhat Nguyen Thi-Duong Nguyen Hsien-Pin Hsu Thi-Hai-Yen Nguyen Effective Decision Making: Data Envelopment Analysis for Efficiency Evaluation in the Cloud Computing Marketplaces Axioms cloud computing data envelopment analysis resampling model Malmquist productivity index decision-making procedures non-cooperative game theory |
| title | Effective Decision Making: Data Envelopment Analysis for Efficiency Evaluation in the Cloud Computing Marketplaces |
| title_full | Effective Decision Making: Data Envelopment Analysis for Efficiency Evaluation in the Cloud Computing Marketplaces |
| title_fullStr | Effective Decision Making: Data Envelopment Analysis for Efficiency Evaluation in the Cloud Computing Marketplaces |
| title_full_unstemmed | Effective Decision Making: Data Envelopment Analysis for Efficiency Evaluation in the Cloud Computing Marketplaces |
| title_short | Effective Decision Making: Data Envelopment Analysis for Efficiency Evaluation in the Cloud Computing Marketplaces |
| title_sort | effective decision making data envelopment analysis for efficiency evaluation in the cloud computing marketplaces |
| topic | cloud computing data envelopment analysis resampling model Malmquist productivity index decision-making procedures non-cooperative game theory |
| url | https://www.mdpi.com/2075-1680/10/4/309 |
| work_keys_str_mv | AT chiananwang effectivedecisionmakingdataenvelopmentanalysisforefficiencyevaluationinthecloudcomputingmarketplaces AT minhnhatnguyen effectivedecisionmakingdataenvelopmentanalysisforefficiencyevaluationinthecloudcomputingmarketplaces AT thiduongnguyen effectivedecisionmakingdataenvelopmentanalysisforefficiencyevaluationinthecloudcomputingmarketplaces AT hsienpinhsu effectivedecisionmakingdataenvelopmentanalysisforefficiencyevaluationinthecloudcomputingmarketplaces AT thihaiyennguyen effectivedecisionmakingdataenvelopmentanalysisforefficiencyevaluationinthecloudcomputingmarketplaces |