An Empirical Study on Supply Chain Management Performance Measurement through AHP

Abstract

Abstract - Supply chain management (SCM) performance evaluation has gained noteworthy considerations from researchers and practitioners in the manufacturing paradigms for improving organizational effectiveness that can be applied to pronounce and review the historical performance, as well as to set performance targets for the future. Precise diagnosis and analysis of SCM evaluation are imperative to attain and enhance organizational productivity and profitability through focusing strategic, tactical and operational planning as well as control. Enterprises scrutinize the best fit to evaluate the existing approaches of performance evaluation framework including financial and operational. The researchers investigate a multi-criteria decision analysis (MCDA) approach to demonstrate how analytic hierarchy process (AHP) is applied to select the best performance evaluation framework and illustrates a decision model to structure the problem related to select the supply chain performance evaluation system in a hierarchical form with substitutes to the decision maker. The study also illustrates that there are nine methods where supply chain performance could be evaluated. However, it is yet to establish and validate a comprehensive approach which can establish both qualitative and quantitative factors along with different decision-making levels and rank the decision preferences which constitutes a gap between the theory and their potential application. The study leads to the integrated SCPM model which could be a valuable contribution in order to measure SCPM in the manufacturing industry.