نوع مقاله : پژوهشی
دانشکده مدیریت و اقتصاد - دانشگاه تربیت مدرس
عنوان مقاله [English]
The balanced scorecard is a multidimensional model in organizational performance evaluation which creates a balance between financial and non-financial indicators, measurable and non-measurable criteria, internal and external aspects, performance drivers and results. Although numerous studies have been done in the field of performance evaluation and implementation of the BSC, in many of these studies, dynamic relationships and interdependencies between the dimensions of the BSC have been ignored.
In this study, both methods of the analytic hierarchy process (AHP) and the analytic network process (ANP) in implementation of the BSC have been used to evaluate banking performance. Applying these methods, the dependency effect between performance criteria will be studied. In this regard, using a questionnaire and expert opinions, the final criteria of performance evaluation in the BSC framework are determined, and, after identifying the relation between these criteria, the network model of this study is designed. Finally, the weights of model criteria and sub-criteria will be calculated using AHP and ANP methods by MATLAB and Expert Choice software. Comparing both methods shows that ANP is a robust and appropriate approach to facilitate the implementation of performance evaluation models, based on the balanced scorecard, and it can also integrate the quantitative and qualitative data. Likewise, investigating dependency between dimensions and also determining the weights of BSC dimensions and related criteria, two significant aspects of implementing BSC, are described in this model.Furthermore, these methods have been implemented in the fuzzy environment for dealing with uncertainty and achieving more realistic decisions. Results show that a fuzzy environment provides simple conditions for making decisions, and, compared to a crisp environment, is more compatible with real conditions.As a result, the network performance evaluation model is designed, based on a combination of FANP and BSC approaches, to provide a more accurate and effective tool for decision-making.