Intelligent EFQM on DEA based model handing principal component analysis and simulation with Rejection Method (Automotive Industry Performance, Benchmarking & Efficiency Measurement in Tehran, Iran)

Purpose – Measurement is one of the main components of productivity cycle, regulating the other parts as well. The present paper aims both to evaluate the relative efficiency of 27 companies in Tehran Province and to propose an approach that incorporates the European Foundation for Quality Management Excellence Model (EFQM) and Data Envelopment Analysis (DEA) handing principal component analysis and simulation with Rejection Method in order to measure the efficiency of the Automotive Industry. Design/methodology – This study is descriptive-analytic in design; it evaluates the efficiency of 27 companies, associated with Automotive Company, using an integrated DEA-EFQM model and simulated decision-making units (DMUs) to do so. In order to design the measurements, needed for evaluating the performance, EFQM has been used, while DEA is employed to evaluate the performance, itself, along with its ranking and principal component analysis (PCA) is utilized to reduce the number of variables under study and for the analysis of DMUs. Findings – The studied companies gave an average of 77.98 for their relative efficiency with 5, out of all 27 companies, ending up on the frontier curve, while the remaining 22 showed an efficiency of less than 1. Originality/value – Integrating DEA and EFQM with simulated DMU; this study was concerned with identifying the measures of performance evaluation and efficiency measurement for a group of similar units. It designed a reference set for all inefficient companies, whose aid enables each of them to improve their efficiency. Moreover it provided target performance for each company. Not only had this integration remedied the deficiencies of both models, improving their merits, but it offered a comprehensive model to evaluate companies‟ performance.

Keywords:

Data envelopment analysis , European Foundation for Quality Management , performance measurement , principal component analysis , simulation