A mixed ideal and anti-ideal DEA model: An application to evaluate cloud service providers

Azadi, M; Izadikhah, M; Ramezani, F; Khadeer, FH

A mixed ideal and anti-ideal DEA model: An application to evaluate cloud service providers

Azadi, M Izadikhah, M Ramezani, F

Khadeer, FH

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Publisher:: Oxford University Press (OUP)
Publication Type:: Journal Article
Citation:: IMA Journal of Management Mathematics, 2020, 31, (2), pp. 233-256
Issue Date:: 2020-04-01

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Field	Value	Language
dc.contributor.author	Azadi, M
dc.contributor.author	Izadikhah, M
dc.contributor.author	Ramezani, F https://orcid.org/0000-0002-0368-321X
dc.contributor.author	Khadeer, FH
dc.date.accessioned	2021-03-28T07:26:17Z
dc.date.available	2021-03-28T07:26:17Z
dc.date.issued	2020-04-01
dc.identifier.citation	IMA Journal of Management Mathematics, 2020, 31, (2), pp. 233-256
dc.identifier.issn	1471-678X
dc.identifier.issn	1471-6798
dc.identifier.uri	http://hdl.handle.net/10453/147566
dc.description.abstract	The rapid development of cloud computing and the sharp increase in the number of cloud service providers (CSPs) have resulted in many challenges in the suitability and selection of the best CSPs according to quality of service requirements. The main objective of this study is to propose three novel models based on the enhanced Russell model to increase the discrimination power in the evaluation and selection of CSPs. The proposed models are designed based on the distances to two special decisionmaking units (DMUs), namely the ideal DMU and the anti-ideal DMU. There are two advantages to the proposed ranking methods. First, they consider both pessimistic and optimistic scenarios of data envelopment analysis, so they are more equitable than methods that are based on only one of these scenarios. The second strength of this approach is its discrimination power, enabling it to provide a complete ranking for all CSPs. The proposed method can help customers to choose the most appropriate CSP while at the same time, it helps software developers to identify inefficient CSPs in order to improve their performance in the marketplace.
dc.language	en
dc.publisher	Oxford University Press (OUP)
dc.relation.ispartof	IMA Journal of Management Mathematics
dc.relation.isbasedon	10.1093/imaman/dpz012
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0102 Applied Mathematics, 1502 Banking, Finance and Investment
dc.title	A mixed ideal and anti-ideal DEA model: An application to evaluate cloud service providers
dc.type	Journal Article
utslib.citation.volume	31
utslib.for	0102 Applied Mathematics
utslib.for	1502 Banking, Finance and Investment
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - AAII - Australian Artificial Intelligence Institute
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
utslib.copyright.status	closed_access	*
dc.date.updated	2021-03-28T07:26:14Z
pubs.issue	2
pubs.publication-status	Published
pubs.volume	31
utslib.citation.issue	2

Abstract:

The rapid development of cloud computing and the sharp increase in the number of cloud service providers (CSPs) have resulted in many challenges in the suitability and selection of the best CSPs according to quality of service requirements. The main objective of this study is to propose three novel models based on the enhanced Russell model to increase the discrimination power in the evaluation and selection of CSPs. The proposed models are designed based on the distances to two special decisionmaking units (DMUs), namely the ideal DMU and the anti-ideal DMU. There are two advantages to the proposed ranking methods. First, they consider both pessimistic and optimistic scenarios of data envelopment analysis, so they are more equitable than methods that are based on only one of these scenarios. The second strength of this approach is its discrimination power, enabling it to provide a complete ranking for all CSPs. The proposed method can help customers to choose the most appropriate CSP while at the same time, it helps software developers to identify inefficient CSPs in order to improve their performance in the marketplace.

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http://hdl.handle.net/10453/147566