Malmquist Productivity Index Using Two-stage DEA Model in Heart Hospitals
محورهای موضوعی : Data Envelopment AnalysisAlireza Alinezhad 1 , Mirpoya Mirmozaffari 2
1 - Associate Professor, Department of Industrial Engineering, Faculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
2 - PhD Candidate, Department of Computer Science, Montana State University, Bozman
کلید واژه: Keywords: DEA, MPI, Intermediate element, Two-stage model,
چکیده مقاله :
Abstract Heart patients displays several symptoms and it is hard to point them. Data envelopment analysis (DEA) provides a comparative efficiency degree for each decision-making units (DMUs) with several inputs and outputs. Evaluating of hospitals is one of the major applications in DEA. In this study, a comparison of additive model with standard input oriented and output oriented Malmquist productivity index (MPI) are used. The MPI is calculated to measure productivity growth relative to a reference technology. Two primary subjects are addressed in computation of MPI growth. What are generally referred to as a “catching-up” effect or technical efficiency change (TEC) and a “frontier shift” effect or technological change (TC). The data covers a six-year span from 2011 to 2016 for 15 local heart hospitals. Two inputs, one intermediate element and two outputs are chosen in two-stage model and these factors reflect the main function of hospitals. Conversion of two-stage to single-stage model is introduced. This model is proposed to fix the efficiency of a two-stage process, and avoid the dependence to various weights. Finally, the results indicated that geometry average of MPI in input oriented pure technical efficiency (PTE) in the tenth Hospital (2.1517) is introduced as the highest performance hospital with highest productivity growth.
Abstract Heart patients displays several symptoms and it is hard to point them. Data envelopment analysis (DEA) provides a comparative efficiency degree for each decision-making units (DMUs) with several inputs and outputs. Evaluating of hospitals is one of the major applications in DEA. In this study, a comparison of additive model with standard input oriented and output oriented Malmquist productivity index (MPI) are used. The MPI is calculated to measure productivity growth relative to a reference technology. Two primary subjects are addressed in computation of MPI growth. What are generally referred to as a “catching-up” effect or technical efficiency change (TEC) and a “frontier shift” effect or technological change (TC). The data covers a six-year span from 2011 to 2016 for 15 local heart hospitals. Two inputs, one intermediate element and two outputs are chosen in two-stage model and these factors reflect the main function of hospitals. Conversion of two-stage to single-stage model is introduced. This model is proposed to fix the efficiency of a two-stage process, and avoid the dependence to various weights. Finally, the results indicated that geometry average of MPI in input oriented pure technical efficiency (PTE) in the tenth Hospital (2.1517) is introduced as the highest performance hospital with highest productivity growth.
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