عنوان مقاله [English]
The purpose of this study was to rank the indices of BSC (financial, customer, growth, learning, and internal processes) through using the Fuzzy Hierarchy Process (FAHP) approach in order to reduce the subjective and selective approach of individuals in performance evaluation. The research methodology is applied in terms of its purpose and the researchers have applied a descriptive approach in which the required data has collected by employing the questionnaire and survey. The statistical population of this research includes managers and heads of departments in Yazd Electric Distribution Company. Sampling was done using the purposeful method. The results show that the customer’s criteria and growth and learning have the highest weight among the criteria, respectively. Also, customer satisfaction indices, employee satisfaction, production efficiency and net profit are found significances in prioritizing indices.
1- Taghizzadeh, R., Fazli, P. (2011). Measurement method for companies using the Hybrid Relationship Analysis of Fuzzy Gray and Topaz Relationships, Industrial Management Outlook, 2, 125-150
2- Tahami, M. (2011). Evaluation of Performance Measurement Criteria in Iranian Power Generation Companies and its Compatibility with Balanced Assessment Techniques. Thesis, Islamic Azad University, Yazd Branch.
3- Chainsaw, M. (2013). Fuzzy Analytical Hierarchy Process. Tehran: First edition, Star of Green.
4- Creamer, G., Freund, Y. (2010). Learning a board Balance Scorecard to improve corporate performance ,Decision Support System, 365–385.
5- Davis, D., Fisher, T. (2003). Attitudes of middle managers to quality-based organizational change, Managing Service Quality, 12, 405-413.
6- Dominique B., C.Richard B. (2005). The French tableau de bord and the American Balanced scorecard: a critical analysis. Critical perspectives on accounting. 16, 645-664.
7- Huang, Ch.)2009). Designing a knowledge-based system for strategic planning: A balanced scorecard perspective, www. elsevier.com/locate/eswa Available online at www.sciencedirect. com, 209-218.
8- Huang, Y., Hshiung Tzeng, G., Hsuan Chen, Y. (2009). A fuzzy MCDM approach for evaluating banking performance based on BSC, Contents lists available at Science Direct ; 10135–10147.
9- Kaplan, R.,. Norton, D.)1996). The balanced scorecard-translating starting into action; Harvard Business School Press.
10-Lee, A. H.I., Chen, W.C., & Chang, C.J. (2008). A fuzzy AHP and BSC approach for evaluating performance of IT department in the manufacturing industry in Taiwan. Expert Systems with Applications, 34, 96–107.
11-Marlys G., Steven S. (2002). A note on the judgmental effects of the balanced scorecards information organization .Accounting, organizations and society, 27.
12-Nam S., LiLi E., Mak, C., & Leong C. (2003). Performance measures in the media and software division of Kao (singapor) private limited. J.of Acc. Ed.21.
13-Paul, R. N. )2002). Balanced scorecard step-by-step: Maximizing performance &maintaining results; Published Simultaneously In Canada, HD 58.9, 58.
14-Paula v., & Martin, W. (2003). meshing critical success factors with the balanced scorecard. Long range planning. 35, 407-427.
15-Ricciardi, E. )2005). Balanced Scorecard and its Information System: the Performance Data Warehouse, 17 thannual Meeting on Socio-Economics central European University and Corvinus University of Budapedt Budapest.
16-Saaty, T. L. (1994). How to make a decision: the analytic hierarchy process.Interfaces, 24 (6), 19–43.
17-Stewart, R.A., Mohamed S.) .2001). Utilizing the Balanced Scorecard for IT/IS Performance Evaluation in Construction, Construction innovation. 147-193
18-Tsaur, S. H., Chang, T. Y., & Yen, C. H. (2002). The evaluation of airline service quality by fuzzy MCDM. Tourism Management, 23, 107–115.
19-Tzeng, G.-H., Chiang, C.-H. & Li, C.W. (2006). Evaluating intertwined effects in e-learning programs: A novel hybrid MCDM model based on factor analysis and DEMATEL. Expert Systems with Applications, published on line. Available from:http://www. sciencedirect.com/science/journal/09574174.
20-Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8, 338–353.