Abstract
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.
Similar content being viewed by others
References
Aliakbari Nouri F, Shafiei Nikabadi M, Olfat L (2019) Developing the framework of sustainable service supply chain balanced scorecard (SSSC BSC). Int J Product Perform Manag 68(1):148–170
Amado CAF, Santos SP, Marques PM (2012) Integrating the Data Envelopment Analysis and the Balanced Scorecard approaches for enhanced performance assessment. Omega 40(3):390–403
Arash A, Samuel Y (2018) An integrated Taguchi loss function-fuzzy cognitive map-MCGP with utility function approach for supplier selection problem. Neural Comput Appl 31:1–20
Barnabè F, Busco C (2012) The causal relationships between performance drivers and outcomes: reinforcing balanced scorecards’ implementation through system dynamics models. J Account Organ Change. https://doi.org/10.1108/18325911211273518
Basso A, Casarin F, Funari S (2018) How well is the museum performing? A joint use of DEA and BSC to measure the performance of museums. Omega 81:67–84
Bénet N, Deville A, Naro G (2019) BSC inside a strategic management control package. J Appl Acc Res 20(1):120–132
Brewer PC, Speh TW (2001) Adapting the balanced scorecard to supply chain management. Supply Chain Manag Rev 5(2):48–56
Buttigieg SC, Dey PK, Cassar MR (2016) Combined quality function deployment and logical framework analysis to improve quality of emergency care in Malta. Int J Health Care Qual Assur. https://doi.org/10.1108/IJHCQA-04-2014-0040
Byun H-S, Lee S-H (2017) Design of a piston forging process using a hybrid Taguchi method and multiple criteria decision-making. J Mech Sci Technol 31(4):1869–1876
Carlson K, Pressnail KD (2018) Value impacts of energy efficiency retrofits on commercial office buildings in Toronto, Canada. Energy Build 162:154–162
Chang H-C, Chen H-Y (2014) Optimizing product form attractiveness using Taguchi method and TOPSIS algorithm: a case study involving a passenger car. Concurr Eng 22(2):135–147
Chavoshlou AS, Khamseh AA, Naderi B (2019) An optimization model of three-player payoff based on fuzzy game theory in green supply chain. Comput Ind Eng 128:782–794
Chen S-S, Lin C-Y, Tsai Y-C (2018) New product strategies and firm performance: CEO optimism. Int Rev Econ Finance. 55:37–53
Chen L et al (2019a) A game-theoretic approach for channel security against active time-varying attacks based on artificial noise. J Ambient Intell Human Comput, pp 1–10
Chen Y-S et al (2019b) A study for project risk management using an advanced MCDM-based DEMATEL-ANP approach. J Ambient Intell Human Comput 10(7):2669–2681
Chou S-Y, Chang Y-H, Shen C-Y (2008) A fuzzy simple additive weighting system under group decision-making for facility location selection with objective/subjective attributes. Eur J Oper Res 189(1):132–145
Chytas P, Glykas M, Valiris G (2011) A proactive balanced scorecard. Int J Inf Manag 31(5):460–468
Cui AS, Wu F (2016) Utilizing customer knowledge in innovation: antecedents and impact of customer involvement on new product performance. J Acad Mark Sci 44(4):516–538
Dincer H, Yuksel S (2019) Balanced scorecard-based analysis of investment decisions for the renewable energy alternatives: a comparative analysis based on the hybrid fuzzy decision-making approach. Energy 175:1259–1270
Dincer H, Yüksel S, Martinez L (2019) Balanced scorecard-based analysis about european energy investment policies: a hybrid hesitant fuzzy decision-making approach with Quality Function Deployment. Expert Syst Appl 115:152–171
Do TX et al (2018) Techno-economic analysis of fry-drying and torrefaction plant for bio-solid fuel production. Renew Energy 119:45–53
Dominici G (2011) Game theory as a marketing tool: uses and limitations. Gandolfo Dominici/elixir Mark 36:3524–3528
Elgammal A et al (2017) Design for customization: a new paradigm for product-service system development. Procedia Cirp 64:345–350
Eskafi S, Roghanian E, Jafari-Eskandari M (2015) Designing a performance measurement system for supply chain using balanced scorecard, path analysis, cooperative game theory and evolutionary game theory: A Case Study. Int J Ind Eng Comput 6(2):157–172
Eskandari M, Jalali-Naiini SGH, Aliahmadi AR, Sadjadi SJ (2010) Conceptual model of knowledge management performance evaluation based on the balanced scorecard and game theory in terms of uncertainty (Case Study: South Oil Company). J Appl Environ Biol Sci 5:34–41
Fraenkel S, Haftor DM, Pashkevich N (2016) Salesforce management factors for successful new product launch. J Bus Res 69(11):5053–5058
Goldman JE, Ahuja S (2009) Integration of COBIT, balanced scorecard & SSE-CMM as a strategic information security management (ISM) framework. In: Proceedings of the 10th Annual Information Security Symposium. CERIAS-Purdue University, p 19
Grimpe C, Sofka W, Bhargava M, Chatterjee R (2017) R&D, marketing innovation, and new product performance: a mixed methods study. J Prod Innov Manag 34(3):360–383
Han H, Hyun SS (2015) Customer retention in the medical tourism industry: impact of quality, satisfaction, trust, and price reasonableness. Tour Manag 46:20–29
Hashem O, Arash A, Ali E (2018) Finding the optimal combination of power plants alternatives: a multi response taguchi-neural network using topsis and fuzzy best-worst method. J Clean Prod 203:210–223
Hernández E, Barrientos A, Del Cerro J (2014) Selective Smooth Fictitious Play: an approach based on game theory for patrolling infrastructures with a multi-robot system. Expert Syst Appl 41(6):2897–2913
Ho L-H, Feng S-Y, Yen T-M (2014) A new methodology for customer satisfaction analysis: Taguchi’s signal-to-noise ratio approach. J Serv Sci Manag
Homburg C et al (2017) The contingent roles of R&D–sales versus R&D–marketing cooperation in new-product development of business-to-business firms. Int J Res Mark 34(1):212–230
Huang HC (2009) Designing a knowledge-based system for strategic planning: a balanced scorecard perspective. Expert Syst Appl 36(1):209–218
Ic YT, Yildirim S (2012) Improvement of a product design using multi criteria decision making methods with Taguchi method. J Fac Eng Arch Gazi Univ 27(2):447–458
Kajtazi M, Holmberg N (2019) IS education revisited: reflections on a BSc program in business information systems design. In: 2019 5th International Conference on Information Management (ICIM). IEEE, pp 144–149
Kaplan RS, Norton DP (1992) The balance scorecard–Measures that drive performance Harvard Business Review Jan-Feb. In: Materials of reports made at the international scientific-practical conference held at Paata Gugushvili Institute of Economics of Ivane Javakhishvili Tbilisi State University in 2011 (Vol. 70, No. 1, p. 322)
Kaplan RS, Norton DP (1996) Strategic learning & the balanced scorecard. Strategy Leader 24(5):18–24
Kaplan RS, Norton DP (2004) Focusing your organization on strategy-with the balanced scorecard. Harvard Business School Publishing, Cambridge
Laraki R, Renault J, Sorin S (2019) Mathematical foundations of game theory. Springer
Laury HA, Matondang N, Sembiring MT (2020) Balanced scorecard in the integration of corporate strategic planning and performance: a literature review. In: IOP Conference Series: Materials Science and Engineering. IOP Publishing, p 12135
Lee E, Seo Y-D, Kim Y-G (2019) A Nash equilibrium based decision-making method for internet of things. J Ambient Intell Human Comput, pp 1–9
Li Y, Liang L (2010) A Shapley value index on the importance of variables in DEA models. Expert Syst Appl 37(9):6287–6292
Li Y et al (2019) Allocating the fixed cost: an approach based on data envelopment analysis and cooperative game. Ann Oper Res 274(1–2):373–394
Lucas WF (1972) An overview of the mathematical theory of games. Manag Sci INFORMS 18(5-part-2):3–19
Marchioni A, Magni CA (2018) Investment decisions and sensitivity analysis: NPV-consistency of rates of return. Eur J Oper Res 268(1):361–372
Mendoza-Alonzo J, Zayas-Castro J, Charkhgard H (2019) ‘Office-based and home-care for older adults in primary care: A comparative analysis using the Nash bargaining solution’, Socio-Economic Planning Sciences. Elsevier
Modak M, Ghosh KK, Pathak K (2018) A BSC-ANP approach to organizational outsourcing decision support—a case study. J Bus Res 103:432–447
Montgomery DC (2017) Design and analysis of experiments. Wiley
Naini SGJ, Aliahmadi AR, Jafari-Eskandari M (2011) Designing a mixed performance measurement system for environmental supply chain management using evolutionary game theory and balanced scorecard: a case study of an auto industry supply chain. Resour Conserv Recycl 55(6):593–603
Narayanan A et al (2019) Feasibility of 100% renewable energy-based electricity production for cities with storage and flexibility. Renew Energy 134:698–709
Nash JF (1950) Equilibrium points in n-person games. Proc Natl Acad Sci 36(1):48–49
Nash J (1951) 19.96. Essays on game theory. Edward Elgar, Cheltenham, United Kindom
Omrani H, Alizadeh A, Emrouznejad A (2018) Finding the optimal combination of power plants alternatives: a multi response Taguchi-neural network using TOPSIS and fuzzy best-worst method. J Clean Prod 203:210–223
Osiro L, Lima-Junior FR, Carpinetti LCR (2018) A group decision model based on quality function deployment and hesitant fuzzy for selecting supply chain sustainability metrics. J Clean Prod 183:964–978
Otley D (1999) Performance management: a framework for management control systems research. Manag Account Res 10(4):363–382
Pakizehkar H et al (2016) The application of integration of Kano’s model, AHP technique and QFD matrix in prioritizing the bank’s substructions. Proc Soc Behav Sci 230:159–166
Pandey RK, Panda SS (2015) Multi-performance optimization of bone drilling using Taguchi method based on membership function. Measurement 59:9–13
Petit C, Vanzeveren E (2015) Adoption and use of flash profiling in daily new product development: a testimonial. In: Rapid sensory profiling techniques. Elsevier, pp 335–344. https://doi.org/10.1533/9781782422587.3.335
Pfeffer J, Sutton RI (2000) The knowing-doing gap: How smart companies turn knowledge into action. Harvard Business Press
Prasad S, Shankar R, Roy S (2019) Impact of bargaining power on supply chain profit allocation: a game-theoretic study. J Adv Manag Res. https://doi.org/10.1108/JAMR-10-2018-0096
Purnomo AB, Sutanto J (2019) Analysis for developing a clearing house of nuclear technology using SWOT-BSC strategies. J Phys Conf Ser 22:11. https://doi.org/10.1088/1742-6596/1198/2/022011/meta
Quezada LE, López-Ospina HA (2014) A method for designing a strategy map using AHP and linear programming. Int J Prod Econ 158:244–255
Safari G, Hafezalkotob A, Khalilzadeh M (2018) A Nash bargaining model for flow shop scheduling problem under uncertainty: a case study from tire manufacturing in Iran. Int J Adv Manuf Technol 96(1–4):531–546
Salavati M, Abdi F, TeymoorPayandeh A (2015) A structural equation modelling to investigate and analyze the relationships among new product development, disruptive innovation, fuzzy-front end, knowledge management, and team vision. Uncertain Supply Chain Manag 3(2):129–140
Sangaiah AK et al (2015) An ANFIS approach for evaluation of team-level service climate in GSD projects using Taguchi-genetic learning algorithm. Appl Soft Comput 30:628–635
Sangaiah AK et al (2020) Robust optimization and mixed-integer linear programming model for LNG supply chain planning problem. Soft Comput 24(11):7885–7905
Shan H, Yang K, Shi J (2019) A strategic perspective analysis for improving operational inefficiency of e-commerce based on integrated BSC and super-SBM model. In: Proceedings of the 2019 3rd International Conference on management engineering, software engineering and service sciences. ACM, pp 128–134
Sharma S, Balan S (2013) An integrative supplier selection model using Taguchi loss function, TOPSIS and multi criteria goal programming. J Intell Manuf 24(6):1123–1130
Shojaei P, Haeri SAS, Mohammadi S (2018) Airports evaluation and ranking model using Taguchi loss function, best-worst method and VIKOR technique. J Air Transp Manag 68:4–13
Sohn MH et al (2003) Corporate strategies, environmental forces, and performance measures: a weighting decision support system using the k-nearest neighbor technique. Expert Syst Appl 25(3):279–292
Sutono SB et al (2016) Fuzzy-based Taguchi method for multi-response optimization of product form design in Kansei engineering: a case study on car form design. J Adv Mech Des Syst Manuf. 10(9):JAMDSM0108
Taguchi G, Konishi S (1991) Signal-to-noise ratio for quality evaluation. ASI Press, Tokyo
Tang M, Wang T-D, Peng D-H (2020) An improved Taguchi multi-criteria decision-making method based on the hesitant fuzzy correlation coefficient and its application in quality evaluation. J Ambient Intell Human Comput. https://doi.org/10.1007/s12652-020-02558-y
Taylor M et al (2019) Game theory modelling of retail marketing discount strategies. Mark Intell Plan. https://doi.org/10.1108/MIP-11-2018-0489
Tukker A (2015) Product services for a resource-efficient and circular economy—a review. J Clean Prod 97:76–91
Vecchia P et al (2019) Application of game theory and evolutionary algorithm to the regional turboprop aircraft wing optimization. In: Evolutionary and deterministic methods for design optimization and control with applications to industrial and societal problems. Springer, pp 403–418. https://doi.org/10.1007/978-3-319-89890-2_26
Wang M (2018) A KPI-based approach to performance-oriented workplace e-learning. In: E-Learning in the workplace. Springer, pp 105–111. https://doi.org/10.1007/978-3-319-64532-2_10.
Wang M, Li Y (2014) Supplier evaluation based on Nash bargaining game model. Expert Syst Appl 41(9):4181–4185
Wood LC et al (2016) Green hospital design: integrating quality function deployment and end-user demands. J Clean Prod 112:903–913
Xiaohui N et al (2014) Predicting the protein solubility by integrating chaos games representation and entropy in information theory. Expert Syst Appl 41(4):1672–1679
Yang T, Wen Y-F, Wang F-F (2011) Evaluation of robustness of supply chain information-sharing strategies using a hybrid Taguchi and multiple criteria decision-making method. Int J Prod Econ 134(2):458–466
Yang J et al (2018) A bayesian game approach for noncooperative pricing among multiple utility companies in smart grid. IEEE Access 6:68576–68585
Yüksel İ, Dağdeviren M (2010) Using the fuzzy analytic network process (ANP) for Balanced Scorecard (BSC): a case study for a manufacturing firm. Expert Syst Appl 37(2):1270–1278
Zameer H et al (2018) A game-theoretic strategic mechanism to control brand counterfeiting. Mark Intell Plan 36(5):585–600
Zhang L et al (2018) Performance changes analysis of industrial enterprises under energy constraints. Resour Conserv Recycl 136:248–256
Acknowledgments
The authors would like to thank Mr. Amirhossein Karimpoor, Maryam Hejazy, Dr. Mohsen Alizadeh Bidgoli, the Editor in chief of Ambient Intelligence and Humanized Computing Review, and three anonymous reviewers for their insightful and constructive comments and suggestions, as results the paper has been improved substantially.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Abedian, M., Amindoust, A., Maddahi, R. et al. A Nash equilibrium based decision-making method for performance evaluation: a case study. J Ambient Intell Human Comput 13, 5563–5579 (2022). https://doi.org/10.1007/s12652-021-03188-8
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12652-021-03188-8