December 22, 2024
Ahmad Ghorbanpour

Ahmad Ghorbanpour

Academic Rank: Assistant professor
Address:
Degree: Ph.D in Industrial management
Phone: 09112919807
Faculty: School of Business and Economics

Research

Title
Presenting a Method for Applying Data Envelopment Analysis Technique to Evaluate the Performance of Bushehr Public High Schools with Emphasis on the FewDecision Making Units
Type Thesis
Keywords
تحليل پوششي داده ها، تحليل مؤلفه هاي اصلي، ارزيابي عملكرد، واحدهاي تصميم گيري، بوشهر
Researchers mostafa foladi (Student) , Hamid Shahbandarzadeh (Primary advisor) , Ahmad Ghorbanpour (Advisor)

Abstract

Evaluating the performance of organizations and selecting the right tools and methods for performance evaluation can have a great role in improving their performance. The purpose of this study is to present a method for using data envelopment analysis technique to evaluate performance under the limited number of decision units so that the model can distinguish and rank the decision units more efficiently. To do more precise sorting.The statistical population of the study consisted of secondary schools in Bushehr city. Twelve schools of this statistical population were selected as sample according to licensing assessment and data collection. After studying a number of researches in the field of school performance evaluation, at first indicators were selected and with the opinionof educational experts the selected indicators were categorized. Using statistical methods and decision making techniques, the indices were refined and weighted, which resulted in input and output indices. The schools surveyed were initially evaluated using Data Envelopment Analysis (DEA) techniques, of which were identified as efficient and inefficient. Subsequently, by incorporating the indicators into the Principal Component Analysis (PCA) method and performing the process, the principal components were extracted and put into the DEA technique, evaluating the efficiency and ranking the units. After applying the PCA-DEA integrated model, the number of efficient units was reduced to unit, thus demonstrating the ability of the integrated methodin identifying, separating and differentiating units.Turning to the above, it can be concluded that by applying the PCA-DEA integrated method, the DEA can significantly differentiate between the evaluated units (when the rule is greater than three timesthe sum of inputs). Increased outputs and outputs.