DEA모형을 활용한 인증종합물류기업의 효율성 분석에 관한 연구

Abstract

Improving the efficiency of logistics companies and logistics industry has become the top priority to all decision-making units for the era of unlimited competition. The purpose of this paper is to analyze the efficiency of certified integrated-logistics companies and it is to solve the problem of the inefficiency of individual logistics companies. This study also suggests that logistics market share expanding and strategy for strengthening the competitiveness of the logistics industry. This paper analyzes the efficiency of 33 certified integrated-logistics Korean companies(CILKC) for 11 years from 2001 to 2011 by using DEA-CCR, DEA-BCC, and Malmquist models which come from DEA(Date Envelopment Analysis) model. According to Charnes, Cooper, and Rhodes(1978), DEA is an empirical procedure to estimate the relative efficiency of a particular company over time. Generally, DEA is a mathematical programming theory that evaluates the relative efficiency of decision making units(DMUs) in an environment of multiples inputs and outputs. DEA offers an alternative to classical in extracting information from sample observation. DEA optimizes each individual observation with the objective of calculating a discrete piece-wise frontier determined by the set of pareto efficient decision making units. DEA analysis can involve multiple inputs as well as multiple outputs in its efficiency valuation. This makes DEA analysis more suitable for port efficiency measurement because ports produce a number of different outputs. Furthermore, DEA provides the user with information about the efficient and inefficient units, as well as the efficiency scores and reference sets for inefficient units(Cai Rui 2009). To measure the efficiency, the selection of the input-output factors is based on a review of other previous studies with the frequency of use and importance. This paper used the numbers of employees, total assets, total liabilities, total equity as input factors and sales amounts, gross margin, operating profit, ordinary income, net profits as output factors. The empirical results are as follows. First, it showed a high correlation between input-output factors. In particular, the numbers of employees as input factors showed a high correlation with total assets, total liabilities, and total equity. Furthermore sales amounts showed a higher correlation with gross margin, operating profit, and ordinary income. Second, we use CCR, BCC models to evaluate the efficiency. The result shows that Dongjin, UCTC, Pantos, KMTC have average values of efficiency score 1 in CCR and Dongjin, UCTC, Glovis, Pantos, KMTC have average values of efficiency score 1 in BCC. Dongjin, KMTC, UCTC, Pantos, DTC, KUKBO, CKLINE, and KCTC whose average values of scale efficiency are 1. This means that those are operated by the economies of scale and effective management, compared to the other CILKC. The inefficient DMUs can derive benchmarking strategies from the efficient logistics companies. Third, the total factor productivity index is decomposed into the pure technical efficiency change, scale efficiency change, and pure technological change index to understand the reason of their productivity changes more specifically. The Malmquist analysis shows that the average total factor productivity index(0.994) was decreased by about 6% from 2001 to 2011, because of the retrogression of technical change in the logistic industry due the global economic recession. The policy suggestions are as follows to strengthen the competitiveness of the logistics industry. ① Scale expansion by revitalization of 3PL, ② achieving efficient logistics through mutual cooperation, ③ strengthening competitiveness of the logistics industry ④ comprehensive plan by government for logistics rationalization. The shippers and logistics companies are also required to adopt a paradigm shift from the cooperation modes of vertical integration among related firms to the strategic alliances based on the mutual trust and respect.