• Journal of Convergence for Information Technology
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• v.12 no.3
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• pp.85-107
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• 2022

This study is to analyze the induced effect, network connectivity, and network visualization of the water transportation industry on the overall economy in relation to all industries. For this, various inducement coefficients of the water transportation industry are analyzed using industry linkage analysis and unit structure matrix, and network visualization analysis is performed using network connectivity and NetDraw using Ucinet 6 that utilizes unit structure matrix and inverse matrix function. As a result of the study, analysis results of input coefficient, production inducement coefficient, value-added inducement coefficient, and inter-industry chain effect were presented as various inducement coefficients in the water transportation industry. content was presented. Through this study, the current position and status of the water transportation industry and its relationship with all industries were confirmed, and the strategic relationship with which industries it should be presented was presented. In the future, it is necessary to further analyze the current status and trends of various induced effects, connectivity (centrality), and network visualization analysis using industry-related analysis published since the 2000s.

• Journal of Navigation and Port Research
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• v.44 no.4
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• pp.319-325
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• 2020

The Korean government has been pursuing many supporting programs to enhance the competition of water transportation companies in recent years. To implement the policies effectively, which needs its monitering and evaluates about their business performance. The purpose of this study was to evaluate the business performance of water transportation company groups and determine the outranking between the groups using the Integrated Fuzzy AHP-PROMETHEE.. To achieve this purpose, first, the companies were classified into seven alternative company groups and the criteria for their evaluation was extracted Second, the weights of the criteria, by maritime and port expert survey, were calculated using the Fuzzy AHP. This paper, finally, determined the total priority orders of their company groups as the link Fuzzy PROMETHEE II with weights of the criteria and the local priority orders between them using the Fuzzy PROMETHEE I. In the proposal for this model, thus was collected four criteria such as growth ability, beneficial ability, technical ability, and productive ability. Through the result of this evaluation, the other marine transportation services group was determined as the highest outranking but the inland passenger & cargo transportation services group was lowest. Thus, the developing plan of the productive ability for the other marine transportation services group should be reviewed to continue its good performance, and all off the criteria for the inland passenger & cargo transportation services group to raise the performance should be reviewed.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.1338-1341
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• 2021

현재 대한민국 운송업에서 두 번째로 큰 비율(19.2%)을 차지하고 있는 수상 운송업에서는 연간 많은 재해가 발생하고 있으며 그 손해는 4백억 원에 달한다. 본 연구는 수상 운송업에서의 재해율과 경제적 손실을 최소화하기 위해 신체 측정기기 및 항만 작업 분배시스템을 설계하였다. 신체 측정기기는 심박, 알코올, 적외선 온도 센서 등을 활용하여 작업자의 신체 정보를 측정한다. 이 결과를 아두이노로 전송한 뒤 사용자의 집중도와 피로도를 분석하여 적절한 작업 분배 서비스를 제공한다.

• Journal of Korea Port Economic Association
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• v.38 no.4
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• pp.139-169
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• 2022

This study derived determinants of 'Decent Work' in the logistics industry and aims to use the analysis results as basic data for policymaking related to labor in the logistics industry and to prepare policies suitable for the characteristics of the logistics industry. As the dependent variable of the model, the Decent Job derived from the first study was used, and the target model was derived from panel data of whole industries to understand the unique characteristics of logistics industry jobs and applied to the logistics industry model. This study found that in the logistics industry, developing the expertise of the logistics industry through "vocational training" compared to whole industries is an important factor rather than raising the "academic level" through the regular curriculum. This seems to reflect the characteristics of the logistics industry as specialized vocational training is required in the case of "railway transportation", "inland water and port transportation", and "air cargo transportation", which have a high proportion of decent job workers among the detailed logistics industries analyzed in this study. Therefore, developing job expertise through additional manpower training programs such as vocational training as well as academic fields learned through regular curriculum is a very important factor in engaging in "Decent Work" not only in the logistics industry but also in other industries.

• Journal of Korea Port Economic Association
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• v.37 no.2
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• pp.133-152
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• 2021

The purpose of this study is to investigate the factors affecting the wages of workers in the logistics industry and to identify the current status of employment and wages in the logistics industry. Based on this, it sought to find analytical factors on the wages of workers in the logistics industry and explain their impact on the wage gap. The analysis data were interpreted as cross-sectional data from the National Statistical Office over the past decade and the analysis data were set to three types. The results of the analysis could be explained that three factors understood as wage discrimination factors that do not directly affect productivity generally have a significant impact on wage gap among workers in the logistics industry. Air and water transport industries received high salaries due to factors in the industry. The very low-paid sector for that was the land transport industry, and the courier industry as a detailed sector. Due to the nature of job factors, technicians and assistants received lower wages than other jobs. Due to the nature of the company's size factors, companies with 51 or more employees received higher wages than companies with 50 or less employees. In testing the effectiveness of multiple sources of ANOVA, the common 'industry × enterprise size' variable was explained to have a significant effect on gaps in wages for workers in the logistics industry. In addition, the comparison of the influence of the main effects of the three factors put into the analysis model shows that the industry has the most influence.