Integration of analytic hierarchy process and data envelopment analysis for assessment and optimization of personnel productivity in a large industrial bank
This paper presents an integration of analytical hierarchy process (AHP) and data envelopment analysis (DEA) for assessment and optimization of personnel productivity in a large private bank. In this algorithm the effective personnel operation indicators are evaluated by the management which is usually in qualitative forms and converted to quantitative forms by using AHP. Then, the ranking and efficiency of the organization will be assessed and optimized by DEA. Principal components analysis (PCA) and numeral taxonomy (NT) are applied to verify and validate the ranking results of the DEA method. We applied this algorithm in various branches of the Bank of Industry and Mine in Iran. The proposed framework may be used to study and optimize personnel productivity in large banks. This is the first study that integrated DEA and AHP for optimization of personnel productivity in large banks based on both qualitative and quantitative indicators.
optimization personnel productivity industrial banks analytical hierarchy process (ahp) data envelopment analysis (dea) principal component analysis (pca) numerical taxonomy