DEA 모형을 이용한 마른김 가공업체의 경영효율성 분석

Abstract

The purpose of this paper is to analyze the relative efficiency of dried laver processing companies in Korea and provide the development direction and improvement plan for the dried laver industry. For a long time laver has not been considered as a food by many people across the world. However, the world market has discovered laver as a health food thus expanding consumption of it from Asian countries into the Northern Hemisphere, therefore the laver industry is expected continuously to grow. To have export competitiveness in exports, we need to focus on dried laver industry first. To measure the efficiency, Data Envelopment Analysis Model was used which is non-parametric efficiency measurement and input- oriented BCC model suggested by Banker, Charnes, and Cooper(1984). Also Rank-sum test suggested by Wilcoxon-Mann-Whitney was used to see if there is difference between exporting companies and non- exporting companies. Data on 76 dried laver processing companies, out of 82 companies, by excluding 6 companies with inaccurate data, based on survey results were selected as the subjects for DEA and used EnPAS 1.0 introduced by Man-hee Park(2008). In this study, the following elements were used : the number of days for factory utilization, watery laver input, size of laver drying machine, the number of employees and facility investment as the input variables, annual production and annual sales as the output variables. This paper estimated the technical efficiency, pure technical efficiency and scale efficiency of dried laver processing companies and investigated the factors influencing the performance of them. As a result of DEA, the average efficiency rate is shown that the technical efficiency is 84.90%, the pure technical efficiency is 93.83%, and the scale efficiency is 86.65%. And based on BCC results, 38 companies are relatively efficient. Comparing pure technical efficiency and scale efficiency, it showed that inefficiencies caused by scale of the company was greater than inefficiencies caused by the scale of technical matter. It implies that expanding the size is essential for achieving high-efficiency of dried laver processing company. DEA also provides a reference set which is valuable information for inefficient companies to find benchmarking companies and to improve their efficiency. Based on the results, I did additional interviews with inefficient companies and could find factors causing inefficiency in the processing and distribution.