Journal of Korean Society for Quality Management (품질경영학회지)

Korean Society for Quality Management (한국품질경영학회)
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A Study on DEA-based Stepwise Benchmarking Target Selection Considering Resource Improvement Preferences

DEA 기반의 자원 개선 선호도를 고려한 단계적 벤치마킹 대상 탐색 연구

  • Park, Jaehun (Major in Industrial Quality Engineering, Daegu Haany University) ;
  • Sung, Si-Il (Department of Industrial Management Engineering, Kyonggi University)
  • 박재훈 (대구한의대학교 화장품공학부 산업품질공학전공) ;
  • 성시일 (경기대학교 산업경영공학과)
  • Received : 2019.02.02
  • Accepted : 2019.02.20
  • Published : 2019.03.31
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Abstract

Purpose: This study proposed a DEA (Data Envelopment Analysis)-based stepwise benchmarking target selection for inefficient DMU (Decision Making Unit) to improve its efficiency gradually to reach most efficient frontier considering resource (DEA inputs and outputs) improvement preferences. Methods: The proposed method proceeded in two steps. First step evaluates efficiency of DMUs by using DEA, and an evaluated DMU selects benchmarking targets of HCU (Hypothesis Composit Unit) or RU (Real Unit) considering resource improvement preferences. Second step selects stepwise benchmarking targets of the inefficient DMU. To achieve this, this study developed a new DEA model, which can select a benchmarking target of an inefficient DMU in considering inputs or outputs improvement preference, and suggested an algorithm, which can select stepwise benchmarking targets of the inefficient DMU. Results: The proposed method was applied to 34 international ports for validation. In efficiency evaluation, five ports was evaluated as most efficient port, and the remaining 29 ports was evaluated as relative inefficient port. When port 34 was supposed as evaluated DMU, its can select its four stepwise benchmarking targets in assigning the preference weight to inputs (berth length, total area of pier, CFS, number of loading machine) as (0.82, 1.00, 0.41, 0.00). Conclusion: For the validation of the proposed method, it applied to the 34 major ports around the world and selected stepwise benchmarking targets for an inefficient port to improve its efficiency gradually. We can say that the proposed method enables for inefficient DMU to establish more effective and practical benchmarking strategy than the conventional DEA because it considers the resource (inputs or outputs) improvement preference in selecting benchmarking targets gradually.

Keywords

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Figure 1. Benchmarking targets of DMU I according to the change of the weights

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Figure 2. Results of stratification and stepwise benchmarking targets for DMU I

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Figure 3. Stratification result of 34 ports

Table 1. Sample data

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Table 2. Descriptive statistics for inputs and outputs of 34 ports

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Table 3. Relative efficiency result of 34 ports

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Table 4. The preference weight assigned to the inputs

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Table 5. Result of stepwise benchmarking targets(HCU and RU) for port 34

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