Abstract
It is a matter of common knowledge that the trucking industry has an important role in strengthening national competitiveness. Recently, in most countries, the trucking industry has faced the task of enhancing its efficiency. To achieve this, a detailed and objective assessment method for the efficiency of current trucking companies is required. This study suggests a network Data Envelopment Analysis (DEA) model for evaluating the efficiency of the trucking industry in Korea. The model was formulated by combining a network DEA model with a modified version of the Banker, Charnes, and Cooper (BCC) model. The proposed model can evaluate the management efficiency of the trucking industry by considering operation and profitability efficiencies sequentially. The model also considers both desirable and undesirable outputs, so it provides more information that can be used to evaluate the efficiency of the trucking industry than dose the traditional DEA model. The Korean trucking industry’s efficiency was analyzed using the model developed in this study. The results show that the large truck companies that use trucks of maximum loading capacities that exceed five tons have the highest efficiency and that the factors that have significant influence on efficiency are service performance, the number of transaction steps, and daily labor hours. The proposed model can contribute to the efficiency evaluation of the trucking industry and help the trucking companies direct their efforts more effectively.
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Hahn, JS., Sung, H.M., Park, M.C. et al. Empirical evaluation on the efficiency of the trucking industry in Korea. KSCE J Civ Eng 19, 1088–1096 (2015). https://doi.org/10.1007/s12205-012-1009-7
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DOI: https://doi.org/10.1007/s12205-012-1009-7