• KDI Journal of Economic Policy
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• v.16 no.1
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• pp.119-148
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• 1994

본(本) 연구(硏究) 1960년대말 이후 1980년대초 기간중에 민영화(民營化)된 공기업(公企業)에 대하여 민영화(民營化)가 개별기업(個別企業)의 생산효율성(生産效率性)에 미친 효과를 회귀분석모형(回歸分析模型)에 의하여 추정하고, 추정결과를 토대로 향후 정부의 바람직한 민영화정책의 방향을 제시하고자 한다. 본(本) 연구(硏究)의 분석결과(分析結果), 공기업민영화(公企業民營化)는 대한통운, 대한항공, 대한재보험, 그리고 대한석유공사의 경우 개별기업의 생산효율성(生産效率性) 증진(增進)에 긍정적인 효과를 미쳤으나, 5대(大) 시중은행(市中銀行)의 경우 공기업민영화(公企業民營化)가 기업(企業)의 생산효율성(生産效率性) 제고에 미친 효과가 미미하여 통계적 신뢰성이 낮게 나타나거나 부정적(否定的)인 효과(效果)가 추정(推定)되었다. 이러한 분석결과(分析結果)에 근거할 때, 기업민영화(公企業民營化)가 항상 기업(企業)의 생산효율성(生産效率性) 증가(增加)에 기여할 것이라는 일반적인 믿음은 현실적안 근거가 부족하며, 일정한 조건이 충족되어야 그러한 믿음이 현실화될 수 있음을 알 수 있다. 민영화(民營化)가 바람직한 정책효과(政策效果)를 나타내기 위해서는 공기업민영화시(公企業民營化時) 기업소유권(企業所有權)의 민간이전뿐만 아니라 실질적인 경영권(經營權)의 이전이 수반되어야 하며, 민영화(民營化)와 더불어 정부(政府)의 각종 규제(規制)와 간섭(干涉)이 배제되어야 한다.

• LOGISTICS
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• s.16
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• pp.25-27
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• 2006

국내의 주요 물류기업들 중 16개 기업이 '종합물류기업'이라는 인증을 받기위해 건설교통부로부터 심사를 받고 있다. 올 상반기중에 우리나라를 대표하는 종합물류기업이 탄생할 것으로 기대된다. 이들 기업을 비롯하여, 물류기업들이 국내시장 규모만을 바라보고 경쟁하기 보다는 보다 넓은 해외진출을 꾀하여 글로벌 물류기업으로 다시 태어나야 할 것이다. '물류'라는 단어가 우리나라에 들어온지 불과 30년도 채 안되는 시점에서 동북아 물류중심을 외치는 우리의 물류산업은 비약적인 발전을 이뤘으며, 국내 시장이 아닌 중국을 비로한 해외 각국으로 진출하는 국제물류에 대한 관심이 높아지고 있다. 최근 21세기에는 북한, 아시아, 중국의 항만, 도로, 철도 등 하부구조를 크게 성장시켜, 권역 운송을 광역화하고 복합운송을 발전시켜야 한다는 의견과 더불어 물류시장의 개방을 통한 외국 운송업체들의 참여를 유도하여 국내 업체의 경쟁력을 키워야 한다는 업계의 의견이 조심스럽게 흘러나오고 있다. "만약 물류시장이 개방될 경우 우리나라 물류기업은 생존 대응능력은 있는가!"하는 의문은 종합물류기업들을 보면 답이 나올 것이다. 해외시장 개척을 적극적으로 펼치면서 외국 물류기업과 어깨를 나란히 하고자 하는 국내의 우수 물류기업들이 많다. 그 중 몇몇 기업들을 살펴보면 대한통운, 글로비스, 한솔CSN, 현대택배, 한진, 현대상선 등은 해외현지법인화를 통하여 글로벌 물류기업으로 도약을 꾀하고 있는 기업도 많다. 이번호에는 "국내외 물류기업의 해외진출 방향, 전략 및 사례"를 통하여 글로벌 물류기업으로 성장하고 있는 업체들의 해외진출현황을 간략히 살펴보고, 전략에 대해 물류전문가로부터 의견을 들어본다.

• Journal of the Korean Solar Energy Society
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• v.39 no.3
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• pp.19-27
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• 2019

In commercial areas, outdoor units are typically installed close to one another in the narrow space between buildings due to insufficient regulations. This makes it difficult to ventilate the discharge airflow, which may lead to deterioration of the performance of outdoor units. This study conducted CFD simulation to analyze the thermal environment according to the installation distance of the outdoor unit. The outdoor unit was installed in the space between buildings, and the thermal environment was analyzed by changing installation distance and wind speed. The performance of the outdoor unit was evaluated by measuring the on-coil temperature. The results show that the closer the distance between outdoor units, the higher the condenser on-coil temperature. Also, the on-coil temperature appeared to rise dramatically at lower wind speed.

• Journal of Korea Port Economic Association
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• v.26 no.4
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• pp.1-18
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• 2010

The purpose of this paper is to evaluate the green logistics of Korea enterprises. According to participate pan-nationally about environment problems, the field of logistics is required to transfer green logistics like increase efficiency of using energy and construct economic systems. And also environment-friendly policies of enterprises are playing important role. So authors selected and analysed factors through precedent study and questionnaire. Selected factors are cultivation about environment-friendly policy awareness to employees, Utilization environment-friendly resources, decrease of atmosphere pollution substance, company's promotion of outside environment-friendly policy. In order to shed light on these problem, fuzzy AHP method is adopted and the factor of cultivation about environment-friendly policy awareness to employees is the highest weight. And also result of the highest weight between enterprises that set policies about green logistics and factors' are The Korean Air, Glovis, Korea Express synthetically.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.4
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• pp.9-21
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• 2018

In South Korea, Jeju Island has a role as a test bed for electric vehicles (EVs). All conventional cars on the island are supposed to be replaced with EVs by 2030. Accordingly, how to effectively set up EV charging stations (EVCSs) that can charge EVs is an urgent research issue. In this paper, we present a case study on planning the locations of EVCS for Jeju Island, South Korea. The objective is to determine where EVCSs to be installed so as to balance the load of EVCSs while satisfying demands. For a public service with EVCSs by some government or non-profit organization, load balancing between EVCS locations may be one of major measures to evaluate or publicize the associated service network. Nevertheless, this measure has not been receiving much attention in the related literature. Thus, we consider the measure as a constraint and an objective in a mixed integer programming model. The model also considers the maximum allowed distance that drivers would detour to recharge their EV instead of using the shortest path to their destination. To solve the problem effectively, we develop a heuristic algorithm. With the proposed heuristic algorithm, a variety of numerical analysis is conducted to identify effects of the maximum allowed detour distance and the tightness of budget for installing EVCSs. From the analysis, we discuss the effects and draw practical implications.

• 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 Korea Port Economic Association
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• v.31 no.3
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• pp.155-166
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• 2015

This study selected container terminals of Gwangyang and Busan Ports to evaluate the influence of efficient container terminals. For the study, after data envelopment analysis (DEA) using the CCR and BCC models, the decision-making unit (DMU) system was used to define nodes; and with the use of a reference group in DEA (BCC model) and a lambda value, this study created a social network and analyzed the influences of efficient DMUs through a centrality analysis of eigenvectors. The results are presented as follows: First, as a result of the DEA, CCR efficiencies in PNC, HJNC, and HPNT container terminals of Busan Port were 1 and BCC efficiencies at Singamman Terminal, Wooam Terminal, PNC, HJNC, HPNT, and BNCT container terminals of Busan Port were 1. Second, as a result of undertaking social network analysis (SNA), according to an eigenvector centrality analysis, HJNC Terminal was referred to the most (influence score of 0.515), which indicates that it is the most influential as a container terminal. The influence of PNC Terminal was 0.512, while that of Wooam Terminal was 0.379. CJ Korea Express in Gwangyang Port was ranked fourth in influence, but its influence score of 0.256 indicates that it was the most influential of the container terminals at Gwangyang Port.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.5
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• pp.109-126
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• 2023

Early detection of forest fires is essential in preventing large-scale forest fires. Predicting forest fires serves as a vital early detection method, leading to various related studies. However, many previous studies focused solely on climate and geographic factors, overlooking human factors, which significantly contribute to forest fires. This study aims to develop forest fire prediction models that take into account human, weather and geographical factors. This study conducted a comparative analysis of four machine learning models alongside the logistic regression model, using forest fire data from Gangwon-do spanning 2003 to 2020. The results indicate that XG Boost models performed the best (AUC=0.925), closely followed by Random Forest (AUC=0.920), both of which are machine learning techniques. Lastly, the study analyzed the relative importance of various factors through permutation feature importance analysis to derive operational insights. While meteorological factors showed a greater impact compared to human factors, various human factors were also found to be significant.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.5
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• pp.193-204
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• 2019

The explosion of data due to the improvement of sensor technology and computing performance has become the basis for analyzing the situation in the industrial fields, and various attempts to detect events based on such data are increasing recently. In particular, sound signals collected from sensors are used as important information to classify events in various application fields as an advantage of efficiently collecting field information at a relatively low cost. However, the performance of sound-event classification in the field cannot be guaranteed if noise can not be removed. That is, in order to implement a system that can be practically applied, robust performance should be guaranteed even in various noise conditions. In this study, we propose a system that can classify the sound event after generating the enhanced sound signal based on the deep learning algorithm. Especially, to remove noise from the sound signal itself, the enhanced sound data against the noise is generated using SEGAN applied to the GAN with a VAE technique. Then, an end-to-end based sound-event classification system is designed to classify the sound events using the enhanced sound signal as input data of CNN structure without a data conversion process. The performance of the proposed method was verified experimentally using sound data obtained from the industrial field, and the f1 score of 99.29% (railway industry) and 97.80% (livestock industry) was confirmed.

• Korean Journal of Construction Engineering and Management
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• v.25 no.3
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• pp.17-26
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• 2024

Quality management work at construction sites demands substantial time and effort, involving the preparation of documents in Excel, approval processes, and the execution of quality tests. These Excel-based tasks include printing quality test reports, performing quality tests, generating and approving test reports, and preparing management ledgers. This division of processes extends the duration of work and diminishes efficiency. Accordingly, a cloud-based construction site quality management system was developed to enhance the productivity of quality management work. The purpose of this study is to analyze the productivity of the construction site quality management system, which is in the early stages of implementation at construction sites. This study implemented the construction site quality management system at a road construction site and scrutinized subsequent alterations in the quality management workflow before and after the implementation. Additionally, a survey was conducted among quality control engineers to collect data on work time both before and after the introduction of the construction site quality management system. Based on the collected data, the Monte-Carlo simulation method was applied to analyze the productivity improvement effect of the construction site quality management system, and the results were presented. The results of this study can serve as foundational data for future research endeavors focused on the automation of quality management works.