Performance Evaluation Using Input-Oriented DEA Envelopment Model: A Case Study of Warehousing, Expedition, and Courier Companies in Indonesia
Abstract
In order to gather information on business decisions and to evaluate the economy and efficiency of current operations, companies require performance evaluation. In the absence of standards or benchmarks for assessment, performance evaluation plays a crucial role in enhancing the business's operational procedures. Data envelopment analysis (DEA) is a tool for measuring performance. The objectives of this study are to measure the efficiency of warehousing, expedition, and courier companies using the input-oriented DEA envelopment model; to analyze the DEA efficiency scores of each decision-making unit (DMU); to identify the efficient and inefficient status of each DMU; and to provide recommendations for development strategies to improve the efficiency of these companies. The results of the study indicate that the inefficient DMU has a presentation of 60%. This value is 20% greater than the efficient DMU (40%). Based on the fluctuation of DEA efficiency score distribution in each DMU, there are 6 DMU efficiency groups. These are Group 1 (ES = 1, Very Efficient), Group 2 (ES = 0.90 - 0.99, Highly Efficient), Group 3 (ES = 0.80 - 0.89, Quite Efficient), Group 4 (ES = 0.60 - 0.79, Less Efficient), Group 5 (ES = 0.41 - 0.59, Inefficient), and Group 6 (ES = 0 - 0.40, Very Inefficient). Group 1 ranks first with the largest percentage (40%). The second and third ranks are Group 3 (30%) and Group 4 (20%). The fourth rank is Group 2 (1%). This study does not have DMU with 2 efficient categories, namely: Group 5 and Group 6.Downloads
References
BPS, “Statistik Pergudangan, Ekspedisi, dan Kurir 2024,” Badan Pusat Statistik, 2024.
E. P. Putri and C. Kusoncum, “Performance evaluation using PCA-CRS input-oriented DEA method. A case study of East Java exports in Indonesia to ASEAN countries,” in Proceedings of the 2019 International Conference on Physics and Mechanics of New Materials and Their Applications, Nova Science, New York, USA, pp. 425-432, 2020.
E. P. Putri, E. Widodo, J. Purnama, B. R. S. P., A. H. A Puteri, “Performance Evaluation of Micro and Small Industries in East Java Province, Indonesia Using SMA and DEA: A Case Study,” International Journal of Industrial Engineering & Production Research, vol. 36, no. 1, pp. 1-16, 2025, doi: 10.22068/ijiepr.36.1.2022.
M. Hamid, M. M. Nairi, and M. Ebrahimnia, “Improvement of Operating Room Performance Using a Multi-Objective Mathematical Model and Data Envelopment Analysis: A Case Study,” International Journal of Industrial Engineering & Production Research, vol. 29, no. 2, pp. 117-132, 2018, doi: 10.22068/ijiepr.29.2.117.
M. Afsharian, H. Ahn, S. Kamali, “Performance Analytics in Incentive Regulation: A Literature Review of DEA Publications,” Decision Analytics Journal, vol. 24, pp. 1-9, 2022, doi: 10.1016/j.dajour.2022.100079.
K. Krajčo, J. Habánik, and A. Grenčíková, “DEA Models as A Tool for Evaluating and Measuring the Efficiency of Public Universities,” Econ. Sociol., vol. 17, no. 1, pp. 166–181, 2024, doi: 10.14254/2071-789X.2024/17-1/11.
E. P. Putri and A. S. Plando, “Optimizing Classroom Performance in Higher Education: Efficiency Study with Data Envelopment Analysis Method,” Heuristic, vol. 21, no. 2, pp. 229-242, 2025, doi: 10.30996/heuristic.v21i2.12240.
M. Farrell, “The Measurement of Productive Efficiency,” Journal of the Royal Statistical Society. Series A (General), vol. 120, no. 3, pp. 253-290, 1957, doi: 10.1016/j.procs.2022.01.085.
A. S. Oliveira, C. F. S. Gomes, C. T. Clarkson, A. M. Sanseverino, M. R. S. Barcelos, I. P. A. Costa, M. Santos, “Multiple Criteria Decision Making and Prospective Scenarios Model for Selection of Companies to be Incubated,” Algorithms, vol. 14, no. 4, pp. 111, 2021, doi: 10.3390/a14040111.
M. A. L. Moreira, C. F. S. Gomes, M. Dos Santos, M. Do Carmo Silva, J. V. G. A. Araujo, “PROMETHEE-SAPEVO-M1 a Hybrid Modeling Proposal: Multicriteria Evaluation of Drones for Use in Naval Warfare,” in A. M. T. Thome, R. G. Barbastefano, L. F. Scavarda, J. C. G. Dos Reis, M. P. C. Amorim (Eds.), Industrial Engineering and Operations Management, Springer Internasional Publishing, Cham, pp. 381–393, 2020.
M. L. Moreira, I. P. De Araujo Costa, M. T. Pereira, M. Dos Santos, C. F. S. Gomes, F. M. Muradas, “PROMETHEE-SAPEVO-M1 a Hybrid Approach Based on Ordinal and Cardinal Inputs: Multi-Criteria Evaluation of Helicopters to Support Brazilian Navy Operations,” Algorithms, vol. 14, no. 5, pp. 140, 2021, doi: 10.3390/a14050140.
C. F. S. A. Gomes, M. d. Santos, L. F. H. A. d. S. d. B. Teixeira, A. M. Sanseverino, M. R. d. S. Barcelos, “SAPEVO-M: A Group Multicriteria Ordinal Ranking Method,” Pesqui. Oper., vol. 40, 2020, doi: 10.1590/0101-7438.2020.040.00226524.
W. Cooper, L. Seiford, K. Tone, “Introduction to Data Envelopment Analysis and Its Uses: With DEA-Solver Software and References,” Springer New York, New York, USA, 2006. doi: 10.1007/0-387-29122-9
L. S. Rodrigues, M. dos Santos, C de S. R. Junior, “Application of DEA and Group Analysis using K-means; Compliance in the Context of the Performance Evaluation of School Networks,” Procedia Computer Science, vol. 199, pp. 687-696, 2022, doi: 10.1016/j.procs.2022.01.085.
J. L. Ruiz and I. Sirvent, “Performance Evaluation through DEA Benchmarking Adjusted to Goals,” Omega, vol. 87, pp. 150-157, 2019, doi: 10.1016/j.omega.2018.08.014.
M. Z.-Seresht, S. Khosravi, J. Jablonsky, and P. Zykova, “A Data Envelopment Analysis Model for Performance Evaluation and Ranking of DMUs with Alternative Scenarios,” Computers & Industrial Engineering, vol. 152, 107002, 2021, doi: 10.1016/j.cie.2020.107002.
W. D. Cook and J. Zhu, “Data Envelopment Analysis: Modeling Operational Processes and Measuring Productivity,” CreateSpace, 2008.
E. P. Putri, Z. Arief, and I. Yuwono, “Performance evaluation using input-oriented envelopment DEA method: A case study of micro and small industry in Indonesia,” in Physics and Mechanics of New Materials and Their Applications (2021-2022), Nova Science, New York, pp. 289–304, 2023.
W. W. Cooper, L. M. Seiford, and K. Tone, “Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References, and DEA-Solver Software,” 2nd ed., Springer, 2007. doi: 10.1007/978-0-387-45283-8.
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