DEA를 활용한 프랜차이즈 사업의 성과지표 개발 방법
How to Develop Performance Indicators Franchise Business using DEA
박형철(한양대학교 일반대학원 경영컨설팅학과); 한창희(한양대학교 ERICA 경영학부)
48권 3호, 49~60쪽
초록
‘Efficiency,’ a key performance factor of an organization, is affected by various factors in addition to ‘cost-benefit,’ which can be measured. Data Envelopment Analysis (DEA) is a method to evaluate the relative efficiency of an organization by simulta- neously considering various factors that are difficult to measure. The significance of this study is that it presents a ‘method for developing an efficiency performance indicator using DEA’ and provides a practical application plan for inefficient organizations (DMUs) to develop and manage appropriate performance indicators to improve efficiency. It presents a methodology for performing research procedures ranging from selection of input and output variables, correlation analysis, DEA execution, calculation of virtual efficiency units (VEUs) through the latent price of the reference group (DMU), and derivation of efficiency performance indicators of the organization.
Abstract
‘Efficiency,’ a key performance factor of an organization, is affected by various factors in addition to ‘cost-benefit,’ which can be measured. Data Envelopment Analysis (DEA) is a method to evaluate the relative efficiency of an organization by simulta- neously considering various factors that are difficult to measure. The significance of this study is that it presents a ‘method for developing an efficiency performance indicator using DEA’ and provides a practical application plan for inefficient organizations (DMUs) to develop and manage appropriate performance indicators to improve efficiency. It presents a methodology for performing research procedures ranging from selection of input and output variables, correlation analysis, DEA execution, calculation of virtual efficiency units (VEUs) through the latent price of the reference group (DMU), and derivation of efficiency performance indicators of the organization.
- 발행기관:
- 한국산업경영시스템학회
- 분류:
- 산업공학