Analysis of passenger car performances by data envelopment analysis

Analysis of Passenger Car Performances by Data Envelopment Analysis Data Envelopment Analysis (DEA) is a nonparametric method used to examine the relative efficiencies of Decision Making Units (DMUs) on conditions where there are multiple inputs and multiple outputs. It was first published in 1957 by Farrell in the literature and in the following years different researchers tried to be developed. In 1978 Charnes, Cooper and Rhodes studied it in detail. In this study, the performances of the DMU of the automobiles will examine using the Classical Data Envelopment Analysis approach. In this direction, it is aimed to assist consumers in purchasing to consumers by calculating the relative effiencies of automobile models according to the wishes of the consumers by determining effective and ineffective DMUs. In classical Data Envelopment Analysis models, sales price, fuel consumption are considered as input variables; maximum speed, cylinder volume, horsepower, maximum torque, luggage volume and acceleration time from 0 to 100 km are determined as output variables. As in all sectors, it is very important for the automotive sector to operate effectively. Therefore, it is also important to measure the efficiency and find the source of the inefficiency. Data envelopment analysis, which is a linear programming based method, is frequently used when efficiency is measured. The purpose of this study is to develop a decision support system that can calculate the relative efficiency of the automobile models according to the consumer perspective, to determine the effective and ineffective units, and to assist consumers in purchasing decisions. Keywords: Data Envelopment Analysis, Super-Efficiency, Efficiency, Automotive Industry.