Data envelopment analysis for performance evaluation of air conditioning and refrigeration industries in Thailand
Call Number: AIT Thesis no. ISE-97-44 Material type:
TextSeries: Asian Institute of Technology. Thesis ; no. ISE-97-44Publication details: Bangkok : Asian Institute of Technology, 1997Description: 92 p.: illSubject(s): Online resources: Dissertation note: Thesis (M.Eng.) - Asian Institute of Technology, 1997 Summary: Data Envelopment Analysis (DEA) has been applied to evaluate the efficiency of the Thai air conditioning and refrigeration industries. Eight input and output factors based on the five dimensions of manufacturing performance have been selected for DEA analysis. These factors have been determined by applying factor analysis on the data collected from a survey of the air conditioning and refrigeration industries in Thailand. The actual data for the inputs and outputs, as collected from the industries, have been used in DEA models. Detailed analysis of results has been done to see the effect of each factor on the efficiency scores. The targets for the inefficient industries have been set which would make them efficient. Finally, recommendations have been outlined for the industries and the future researchers on this topic.
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20-AIT Publication
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Asian Institute of Technology Library AIT Publications | AIT Thesis no. ISE-97-44 (Browse shelf(Opens below)) | 2 | Available | 30050121009616 |
Thesis (M.Eng.) - Asian Institute of Technology, 1997
A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering, School of Advanced Technologies
Data Envelopment Analysis (DEA) has been applied to evaluate the efficiency of the Thai air conditioning and refrigeration industries. Eight input and output factors based on the five dimensions of manufacturing performance have been selected for DEA analysis. These factors have been determined by applying factor analysis on the data collected from a survey of the air conditioning and refrigeration industries in Thailand. The actual data for the inputs and outputs, as collected from the industries, have been used in DEA models. Detailed analysis of results has been done to see the effect of each factor on the efficiency scores. The targets for the inefficient industries have been set which would make them efficient. Finally, recommendations have been outlined for the industries and the future researchers on this topic.
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