A Nash equilibrium based decision-making method for performance evaluation: a case study
In organizational management, selecting the most appropriate combination of balanced scorecard (BSC) indicators as an equilibrium point based on scientific methods is of great value. In this paper, a new approach based on the balanced scorecard and game theory has been developed for evaluating the p...
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Veröffentlicht in: | Journal of ambient intelligence and humanized computing 2022-12, Vol.13 (12), p.5563-5579 |
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description | In organizational management, selecting the most appropriate combination of balanced scorecard (BSC) indicators as an equilibrium point based on scientific methods is of great value. In this paper, a new approach based on the balanced scorecard and game theory has been developed for evaluating the performance of an Iranian company to determine the most appropriate combination of BSC indicators and to build an equilibrium point between financial and non-financial performance measures. The organization’s strategic objectives have been translated into a set of performance measures distributed among four perspectives of financial, customer, internal business processes, and learning and growth. Considering each perspective of BSC as a player in a four-person cooperative game, a bi-objective mathematical model of a finite-discrete game in normal form, based on the Nash solution, is proposed to specify the relationship among indicators in the strategy map, to determine the equilibrium points in the BSC, and to control the organizational costs. The results suggest that the proposed model successfully determines the best combination of indicators, and an equilibrium point in the BSC to minimize the costs and maximize perspectives’ payoff of the BSC without undertaking complicated mathematical computation. Adoption of four indicators of generating new R&D activities, consistency of the working team, growing satisfaction of existing customers, and potential growth in operating income by four players was suggested as the best combination of BSC indicators as an equilibrium point. The proposed model was validated using the Taguchi method to prove that it has been accurate and reliable. |
doi_str_mv | 10.1007/s12652-021-03188-8 |
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In this paper, a new approach based on the balanced scorecard and game theory has been developed for evaluating the performance of an Iranian company to determine the most appropriate combination of BSC indicators and to build an equilibrium point between financial and non-financial performance measures. The organization’s strategic objectives have been translated into a set of performance measures distributed among four perspectives of financial, customer, internal business processes, and learning and growth. Considering each perspective of BSC as a player in a four-person cooperative game, a bi-objective mathematical model of a finite-discrete game in normal form, based on the Nash solution, is proposed to specify the relationship among indicators in the strategy map, to determine the equilibrium points in the BSC, and to control the organizational costs. The results suggest that the proposed model successfully determines the best combination of indicators, and an equilibrium point in the BSC to minimize the costs and maximize perspectives’ payoff of the BSC without undertaking complicated mathematical computation. Adoption of four indicators of generating new R&D activities, consistency of the working team, growing satisfaction of existing customers, and potential growth in operating income by four players was suggested as the best combination of BSC indicators as an equilibrium point. The proposed model was validated using the Taguchi method to prove that it has been accurate and reliable.</description><identifier>ISSN: 1868-5137</identifier><identifier>EISSN: 1868-5145</identifier><identifier>DOI: 10.1007/s12652-021-03188-8</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Artificial Intelligence ; Balanced Scorecard ; Canonical forms ; Case studies ; Competition ; Competitive advantage ; Computational Intelligence ; Costs ; Customers ; Decision making ; Design of experiments ; Efficiency ; Energy industry ; Engineering ; Equilibrium ; Game theory ; Indicators ; Literature reviews ; Mathematical analysis ; Mathematical models ; Original Research ; Performance evaluation ; Robotics and Automation ; Strategic management ; Taguchi methods ; User Interfaces and Human Computer Interaction</subject><ispartof>Journal of ambient intelligence and humanized computing, 2022-12, Vol.13 (12), p.5563-5579</ispartof><rights>The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021</rights><rights>The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c319t-f0eeaf428251104552bd3792d3b4273ead7cb3dcc82139585bc807c9548719f53</citedby><cites>FETCH-LOGICAL-c319t-f0eeaf428251104552bd3792d3b4273ead7cb3dcc82139585bc807c9548719f53</cites><orcidid>0000-0002-7919-8616</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s12652-021-03188-8$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2919501032?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>314,778,782,21371,27907,27908,33727,41471,42540,43788,51302,64366,64370,72220</link.rule.ids></links><search><creatorcontrib>Abedian, Mansour</creatorcontrib><creatorcontrib>Amindoust, Atefeh</creatorcontrib><creatorcontrib>Maddahi, Reza</creatorcontrib><creatorcontrib>Jouzdani, Javid</creatorcontrib><title>A Nash equilibrium based decision-making method for performance evaluation: a case study</title><title>Journal of ambient intelligence and humanized computing</title><addtitle>J Ambient Intell Human Comput</addtitle><description>In organizational management, selecting the most appropriate combination of balanced scorecard (BSC) indicators as an equilibrium point based on scientific methods is of great value. In this paper, a new approach based on the balanced scorecard and game theory has been developed for evaluating the performance of an Iranian company to determine the most appropriate combination of BSC indicators and to build an equilibrium point between financial and non-financial performance measures. The organization’s strategic objectives have been translated into a set of performance measures distributed among four perspectives of financial, customer, internal business processes, and learning and growth. Considering each perspective of BSC as a player in a four-person cooperative game, a bi-objective mathematical model of a finite-discrete game in normal form, based on the Nash solution, is proposed to specify the relationship among indicators in the strategy map, to determine the equilibrium points in the BSC, and to control the organizational costs. The results suggest that the proposed model successfully determines the best combination of indicators, and an equilibrium point in the BSC to minimize the costs and maximize perspectives’ payoff of the BSC without undertaking complicated mathematical computation. Adoption of four indicators of generating new R&D activities, consistency of the working team, growing satisfaction of existing customers, and potential growth in operating income by four players was suggested as the best combination of BSC indicators as an equilibrium point. The proposed model was validated using the Taguchi method to prove that it has been accurate and reliable.</description><subject>Artificial Intelligence</subject><subject>Balanced Scorecard</subject><subject>Canonical forms</subject><subject>Case studies</subject><subject>Competition</subject><subject>Competitive advantage</subject><subject>Computational Intelligence</subject><subject>Costs</subject><subject>Customers</subject><subject>Decision making</subject><subject>Design of experiments</subject><subject>Efficiency</subject><subject>Energy industry</subject><subject>Engineering</subject><subject>Equilibrium</subject><subject>Game theory</subject><subject>Indicators</subject><subject>Literature reviews</subject><subject>Mathematical analysis</subject><subject>Mathematical models</subject><subject>Original Research</subject><subject>Performance evaluation</subject><subject>Robotics and Automation</subject><subject>Strategic management</subject><subject>Taguchi methods</subject><subject>User Interfaces and Human Computer Interaction</subject><issn>1868-5137</issn><issn>1868-5145</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp9kE1LAzEQhoMoWGr_gKeA52gm2TSJt1L8AtGLgreQTbLt1u5um-wK_fdGV_TmXN45PM8MvAidA70ESuVVAjYXjFAGhHJQiqgjNAE1V0RAIY5_dy5P0SylDc3DNQeACXpb4Ceb1jjsh3pbl7EeGlzaFDz2wdWp7lrS2Pe6XeEm9OvO46qLeBdijsa2LuDwYbeD7TN4jS12WcWpH_zhDJ1UdpvC7Cen6PX25mV5Tx6f7x6Wi0fiOOieVDQEWxVMMQFACyFY6bnUzPOyYJIH66UruXdOMeBaKFE6RaXTolASdCX4FF2Md3ex2w8h9WbTDbHNLw3ToAUFylmm2Ei52KUUQ2V2sW5sPBig5qtEM5Zoconmu0SjssRHKWW4XYX4d_of6xO96HPP</recordid><startdate>20221201</startdate><enddate>20221201</enddate><creator>Abedian, Mansour</creator><creator>Amindoust, Atefeh</creator><creator>Maddahi, Reza</creator><creator>Jouzdani, Javid</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>8FE</scope><scope>8FG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>P5Z</scope><scope>P62</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><orcidid>https://orcid.org/0000-0002-7919-8616</orcidid></search><sort><creationdate>20221201</creationdate><title>A Nash equilibrium based decision-making method for performance evaluation: a case study</title><author>Abedian, Mansour ; 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In this paper, a new approach based on the balanced scorecard and game theory has been developed for evaluating the performance of an Iranian company to determine the most appropriate combination of BSC indicators and to build an equilibrium point between financial and non-financial performance measures. The organization’s strategic objectives have been translated into a set of performance measures distributed among four perspectives of financial, customer, internal business processes, and learning and growth. Considering each perspective of BSC as a player in a four-person cooperative game, a bi-objective mathematical model of a finite-discrete game in normal form, based on the Nash solution, is proposed to specify the relationship among indicators in the strategy map, to determine the equilibrium points in the BSC, and to control the organizational costs. The results suggest that the proposed model successfully determines the best combination of indicators, and an equilibrium point in the BSC to minimize the costs and maximize perspectives’ payoff of the BSC without undertaking complicated mathematical computation. Adoption of four indicators of generating new R&D activities, consistency of the working team, growing satisfaction of existing customers, and potential growth in operating income by four players was suggested as the best combination of BSC indicators as an equilibrium point. The proposed model was validated using the Taguchi method to prove that it has been accurate and reliable.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1007/s12652-021-03188-8</doi><tpages>17</tpages><orcidid>https://orcid.org/0000-0002-7919-8616</orcidid></addata></record> |
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subjects | Artificial Intelligence Balanced Scorecard Canonical forms Case studies Competition Competitive advantage Computational Intelligence Costs Customers Decision making Design of experiments Efficiency Energy industry Engineering Equilibrium Game theory Indicators Literature reviews Mathematical analysis Mathematical models Original Research Performance evaluation Robotics and Automation Strategic management Taguchi methods User Interfaces and Human Computer Interaction |
title | A Nash equilibrium based decision-making method for performance evaluation: a case study |
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