Developing a new multidimensional model for selecting strategic plans in balanced scorecard

Daniel, J; Merigó, JM

Developing a new multidimensional model for selecting strategic plans in balanced scorecard

Daniel, J Merigó, JM

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Publisher:: IOS Press
Publication Type:: Journal Article
Citation:: Journal of Intelligent and Fuzzy Systems, 2021, 40, (2), pp. 1817-1826
Issue Date:: 2021-02-02

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Field	Value	Language
dc.contributor.author	Daniel, J
dc.contributor.author	Merigó, JM
dc.date.accessioned	2022-04-14T07:32:40Z
dc.date.available	2022-04-14T07:32:40Z
dc.date.issued	2021-02-02
dc.identifier.citation	Journal of Intelligent and Fuzzy Systems, 2021, 40, (2), pp. 1817-1826
dc.identifier.issn	1064-1246
dc.identifier.issn	1875-8967
dc.identifier.uri	http://hdl.handle.net/10453/156266
dc.description.abstract	The main motivation of this research is to develop an innovative multidimensional model through multi attribute decision making (MADM) methods for strategic plans selection process in the Balanced Scorecard (BSC). The current study adopted MADM analytical methods including AHP, ELECTRE, BORDA, TOPSIS and SAW to rank the initiatives / strategic plans in BSC. Then the results of those methods were compared against each other in order to find a robust model for selecting strategic plans. The correlation coefficient between methods indicated that multidimensional and ELECTRE methods with 0.944 are the best performing and AHP with negative correlation (–0.455) is the worst performing method for selecting strategic plans in BSC. The high correlation demonstrates that the model can be a useful and effective tool to finding the critical aspects of evaluation criteria as well as the gaps to improve company performance for achieving desired level. Developing multidimensional model is the core model for the selection of strategic plans. This study addresses the problem and issues of group decision making process for selecting strategic plans in BSC. It has numerous contributions that particularly includes; 1) Determination of the explicit criteria sub-criteria and criteria to improve ranking strategic plans in BSC, 2) Adopting MADM analytical methods including AHP, ELECTRE, BORDA, TOPSIS and SAW for the selection of strategic plans decision problem in BSC, 3) Developing multidimensional model to address the selection of strategic plans problems in BSC. The proposed model will provide an approach to facilitate strategic plans decision problem in BSC.
dc.language	English
dc.publisher	IOS Press
dc.relation.ispartof	Journal of Intelligent and Fuzzy Systems
dc.relation.isbasedon	10.3233/jifs-189188
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0801 Artificial Intelligence and Image Processing, 1702 Cognitive Sciences
dc.subject.classification	Artificial Intelligence & Image Processing
dc.title	Developing a new multidimensional model for selecting strategic plans in balanced scorecard
dc.type	Journal Article
utslib.citation.volume	40
utslib.for	0801 Artificial Intelligence and Image Processing
utslib.for	1702 Cognitive Sciences
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/Faculty of Engineering and Information Technology/School of Computer Science
utslib.copyright.status	closed_access	*
pubs.consider-herdc	false
dc.date.updated	2022-04-14T07:32:39Z
pubs.issue	2
pubs.publication-status	Published
pubs.volume	40
utslib.citation.issue	2

Abstract:

The main motivation of this research is to develop an innovative multidimensional model through multi attribute decision making (MADM) methods for strategic plans selection process in the Balanced Scorecard (BSC). The current study adopted MADM analytical methods including AHP, ELECTRE, BORDA, TOPSIS and SAW to rank the initiatives / strategic plans in BSC. Then the results of those methods were compared against each other in order to find a robust model for selecting strategic plans. The correlation coefficient between methods indicated that multidimensional and ELECTRE methods with 0.944 are the best performing and AHP with negative correlation (–0.455) is the worst performing method for selecting strategic plans in BSC. The high correlation demonstrates that the model can be a useful and effective tool to finding the critical aspects of evaluation criteria as well as the gaps to improve company performance for achieving desired level. Developing multidimensional model is the core model for the selection of strategic plans. This study addresses the problem and issues of group decision making process for selecting strategic plans in BSC. It has numerous contributions that particularly includes; 1) Determination of the explicit criteria sub-criteria and criteria to improve ranking strategic plans in BSC, 2) Adopting MADM analytical methods including AHP, ELECTRE, BORDA, TOPSIS and SAW for the selection of strategic plans decision problem in BSC, 3) Developing multidimensional model to address the selection of strategic plans problems in BSC. The proposed model will provide an approach to facilitate strategic plans decision problem in BSC.

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http://hdl.handle.net/10453/156266