• Journal of the Korean Society of Marine Environment & Safety
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• v.23 no.2
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• pp.161-167
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• 2017

This paper measured and evaluated the technical efficiency, pure technical efficiency and scale efficiency of port labor via three inputs and three outputs using Data Envelopment Analysis (DEA). First, the average overall technical efficiency measured about 94.18 %, with 100 % pure technical efficiency being larger than 94.18% scale efficiency. As a result, 7 ports were identified as efficient, and 4 ports were identified as inefficient. Among the 4 ineffiecient ports, Donghae had the highest Increasing Return to Scale (IRS). However, the inefficient ports were all found to be less efficient in terms of resource operation than production scale. On the other hand, the efficient ports established priorities using the super efficiency method. As a result, port efficiency was highest for Incheon, Mokpo, Pyeongtaek-Dangjin, Masan, Yeosu Gwangyang, Jeju, and Gunsan-Daesan Ports, in order. In particular, Busan Port, found to be inefficient, would benefit from using Mokpo Port and Incheon Port as benchmarks to increase trade volume and modernize equipment for full-scale commercialization to improve labor efficiency.

• Journal of Korea Port Economic Association
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• v.29 no.2
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• pp.159-171
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• 2013

This paper aims to analyse the relative efficiency of logistics facilities and suggest the policy alternatives for exploring and activating them. This study also divides the logistics facilities into airport terminals, logistics complexes, container terminals, and trucking freight terminals. For this purpose, the CCR-DEA as well as the BCC-DEA techniques are employed to show which part explains the primary cause of inefficiencies of each DMU(Decision Making Unit). The empirical results indicate that the efficiency of logistics complex is the lowest of all, while freight trucking terminal has the highest efficiency. This study also reveals that operation inefficiency is greater than scale inefficiency in most of DMUs, showing that much more effort be done for alleviating the cost resulting from irrational management.

• Journal of Korean Society of Forest Science
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• v.103 no.4
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• pp.639-645
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• 2014

This study was conducted to evaluate the management efficiency of oak mushroom farms in Korea using the Data Envelopment Analysis (DEA), which is one of the non-parametric estimation methods. The data that was analyzed in this study was from the result of 2013 survey entitled "Standard Diagnostic Table for Oak Mushroom Management", which was conducted from March 2012 to October 2012. This survey was based on the inputs and outputs of 20 oak mushroom farms. Specifically, this study analyzed the technical efficiency, pure-technical efficiency and scale efficiency using CCR and BCC model of the DEA methods. Furthermore, this study compares the management efficiency between the full time oak mushroom production farms and part time oak mushroom production farms. Results showed that mean value for the technical efficiency was 0.655 which is considered as inefficient in general. For the pure-technical efficiency and scale efficiency, the mean values were 0.830 and 0.747, respectively which showed that inefficiency in the management was observed in the mushroom farms. Results also showed that there were seven farms with a total efficiency of 1, namely Decision Making Unit(DMU)2, DMU5, DMU6, DMU8, DMU10, DMU15 and DMU20. The management efficiency of DMU7 specifically the inputs for production was analyzed and compared to DMU5 and DMU6 and results showed that the DMU7 had an excessive inoculation and site development cost. Lastly, it was also observed that the full time mushroom production farms were more efficient as compared to the part time mushroom farms because of the lower scale efficiency value or smaller area for mushroom production allotted in the part time farms.

• Journal of Digital Convergence
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• v.19 no.5
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• pp.353-363
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• 2021

This study analyzed to provide information for business improvement by analyzing the management efficiency of start-up investment companies so that startup investment companies can operate efficiently and by presenting information on inefficient factors. From 2014 to 2018, 83 start-up investment companies were analyzed using the DEA model. Input variables were he number of employees, capital, and output variables were selected for start-up investment assets, operating income, and net profit. As a result of the analysis, technical efficiency and pure technical efficiency showed a pattern with an increase in average, but scale efficiency repeatedly increased and decreased. It is believed that the decline in technology efficiency was due to the decrease in pure technology efficiency, and the inefficiency of start-up investment companies seems to have influenced the inefficiency of start-up investment companies rather than the inefficiency of scale. In addition, the size revenue shows that the DRS value is gradually decreasing, and the IRS value is generally increasing. It is believed that efficiency can be improved if operational inefficiency is improved based on the results and efficiency measures are established through scale expansion.

• The Korean Journal of Financial Management
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• v.20 no.2
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• pp.263-291
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• 2003

The purpose of this paper is to analyse the change in the productivity of Korean life insurance industry by Generalized Malmquist productivity indices. Generalized Malmquist indices will be decomposed into three components such as pure efficiency change, scale efficiency change, and technical change. The principal findings indicate an overall increase in productivity driven more by technical progress than pure technical efficiency and scale efficiency.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.2
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• pp.767-776
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• 2014

This study estimated productivity change and RTS using Parametric and Non-Parametric approach with 5 year annual data from 2006 to 2010 of 20 public general hospitals in Vietnam collected from Ho Chi Min City Health Department of Health Database. The results could be summarized as follows; First, by the Non-Parametric approach. cumulated productivity growth of 5 years was increased by 2.8% due to regress 5.2% of technical efficiency, 0.3% of pure technical efficiency, but scale efficiency was decreased 5.1% Second, by the Non-Parametric approach, cumulated productivity growth was decreased by 12.8% to due to drop of 17.1% of technical change, 9.1% of scale efficiency. In conclusion, the common result of both approaches was that scale inefficiencies occurs in public hospitals in Vietnam, and they affected productivity change of public hospitals in Vietnam. Namely, 70% to 80% of the analyzed Vietnam public hospitals were at the status of DRS(decreased returns to scale), which suggested that they had oversupply beds relative to the number of occupied patients, it was meaningful that this study was the first study in Korea to measure efficiency and productivity change of Vietnamese public general hospitals and so it could be utilized as the basic information needed to enter hospital industry of Vietnam in the future.

• Journal of Korea Port Economic Association
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• v.26 no.4
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• pp.188-206
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• 2010

Data Envelopment Analysis(DEA) is an operations research-based method for measuring the performance efficiency of decision units that are characterized by multiple inputs and outputs. DEA has been applied successfully as a performance evaluation tool in many fields. However, it has not been extensively applied in the shipbuilding industry. This paper applied the input-oriented DEA model, and Malmquist indices to the 7 shipbuilding firms to measure the efficiency and productivity changes during the period of 2004 to 2009. The Malmquist indices will be decomposed into three components such as pure efficiency change, scale efficiency change, and technical change. The empirical results show the following findings. First, the DEA findings indicate that main source of inefficiency is scale rather than pure technical. Second, the Malmquist indices show that an overall decrease in productivity.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.247-247
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• 2019

수력발전 사업에 있어 Desander 구조물은 주로 고산지대 수력발전댐의 Run-of-river 형식의 발전방식에서 유사로 인한 터빈의 손상을 방지하기 위한 목적으로 설치된다. Desander의 적정 규모는 터빈의 손상을 일으킬 수 있는 유사 입경에 대해 안정적으로 침전을 시킬 수 있는 폭/길이/깊이로 평가할 수 있으며 상대적으로 Desander의 규모가 크게 설계된 경우 초기 공사비 증가하고 반대로 규모가 작게 설계된 경우 터빈의 교체 주기 단축으로 인한 유지관리비가 증가된다. 현재까지 일반적인 Desander 구조물의 설계 방식은 제거 입경의 침전 속도, 유입유량 및 깊이를 변수로 사용하여 경험식(L. Sudry method, Guicciardis method 및 Rouse method)을 통해 규모를 결정해 왔다. 하지만, 3-D 전산유체해석을 통해 유속 흐름 분석으로 직 간접적 Desander 규모의 적정성을 평가할 수 있는 현 시점에서 경험식으로부터 도출된 결과의 신뢰성과 객관성을 검증할 필요가 있다고 판단된다. 본 연구에서는 노르웨이 NSTU에서 개발한 유사의 이송 및 확산해석 기능이 내장된 범용 소프트웨어인 SSIIM을 이용하였다. SSIIM(Simulation of Sediment movements In water Intakes with Multiblock)은 개수로 흐름 상태에서 유사 이동 및 하상 변동을 분석할 수 있도록 개발된 3-D 해석 프로그램이다. SSIIM은 수치해석 방법으로 유한체적법(Finite Volume Method)를 채택하였으며 Navier-Stokes equations을 통해 유체의 흐름을 해석한다. 입력 자료는 유입 유량($m^3/sec$), 유입 유사량(kg/sec), 유출부 수위 및 해당 Desander Structure grid 자료가 사용되며 해석 결과로 Desander 내 grid 별 유속, 수위, 유사 농도 변화 등을 제공한다. 본 연구에서는 SSIIM을 이용하여 제거 목표 유사 입경의 차집 효율(Trap efficiency)로 Desander의 적정 규모를 평가 할 수 있는 설계법을 제안하며 설계 단계에서 결정되는 최소 제거유사 입자와 차집 효율에 의한 Desander의 적정 규모 평가 분석을 파키스탄 A 프로젝트를 대상으로 수행하였다. 연구 성과로 (1)SSIIM을 통해 해석된 차집 효율을 기초로 Desander의 적정 규모를 계획할 경우 경험적 방식에 비해 설계의 객관성과 신뢰성을 제고할 수 있으며 (2)3-D 수치해석을 통해 grid 별 유사농도를 확인 할 수 있어 Desander 형상과 규모에 대한 평가가 가능하다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.55-56
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• 2023

항만배후단지는 항만과 인접한 배후공간으로 항만의 기능이 더욱 활성화될 수 있도록 지원한다. 하지만, 국내 항만배후단지는 단순한 항만물류지원기능에 국한되어 있으며 인프라 시설, 정책 및 지원, 투자 미흡 등으로 인하여 항만배후단지 활성화에 어려움을 겪고 있다. 이에 본 논문은 국내 항만배후단지 업체별 내부자료를 바탕으로 DEA 분석 및 생산성 분석을 진행하여 국내 항만배후단지의 종합적인 정책방향을 도출하고자 하였다. DEA 분석결과 창고업의 경우 광양항 서측, 인천항 북항 항만배후단지가 효율적인 것으로 나타났으며, 제조업의 경우 인천항 북항, 울산항 1공구 항만배후단지가 효율적으로 나타났다. 또한, 외국인 투자규모별 생산성의 경우 광양항 서측, 평택당진항 1단계 항만배후단지가 높게 나타났으며, 시설 투자규모별 생산성은 광양항 서측, 인천항 북항 항만배후단지가 높은 생산성을 보였다. 마지막으로, 노동생산성은 인천항 북항, 부산항 웅동 항만배후단지가 가장 높은 생산성을 보였다. 이러한 결과는 항만배후단지 입주기업 선정 시 취급품목이 효율성에 중요한 영향을 주며, 외국인 투자규모, 시설 투자규모, 종업원 수가 항만배후단지의 생산성 향상으로 직결되고 있지 않다는 것을 나타낸다.

• Journal of Korea Port Economic Association
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• v.24 no.4
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• pp.47-70
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• 2008

The purpose of this study is to estimate total factor productivity(TFP) growth by stochastic frontier function and to grasp contributing factors of its growth rate by decomposing the total factor productivity into efficiency change, technical progress, scale change, and allocation change. Annual growth rate of total factor productivity for 1990-2003 is 0.019 (1.9%), higher than that of overall industry (0.010). The main component of TFP growth is not efficiency change but technical progress. Contributing factors of total factor productivity growth are change of allocation efficiency in port industry, technical progress in sea-transportation industry, and change of scale efficiency in transportation-equipment industry. The change of total factor productivity shows a decreasing trend since late in the 1990s. The annual technical efficiency of port-logistics industry is less than that of overall industry. Capital elasticity for output (0.391) is higher than labor elasticity (0.227), but scale economy of port-logistics industry is 0.618, which is far from optimal scale economy.