A Study on the Non-productive Movement in Container Terminal

The container liners have strived in order to survive from persistence crisis by seeking the most efficient vessel operation with different ways such as Merger & Acquisition (M&A), reorganizing the alliance, awarding mega vessel and so on since 2010. On this fierce competition the largest shipping line in Korea, Han-jin Shipping Line, went into receivership and drove the company into bankruptcy. On the other hand, the larger shipping line which succeed to survive from the game have consistently been forcing the terminal operator to achieve the lower tariff with better service. In order to break through, terminal operators have reinforced investment with improving terminal system and automation with high-tech equipment. With those tremendous efforts, however, terminal operators are still confronting difficulties including “Non-productive Movement” which is one of the biggest challenge in operation. In this thesis, we verify the definition of non-productive movement, proportion and effect in real operation by analyzing the cases. To address non-productive movement in operation, we've analyzed A container terminal's actual case. As a result, we could identify that those cases are composed of vessel operation(Loading/unloading), In/outbound operation, other terminal operations and unproductive operation which resulted from terminal structure. By this research, we could connect the dots that how the unproductive operations account for overall terminal operation and identify opportunities of improvement for service quality and competitiveness of terminal by improving those problems. However, this thesis aims at justifying the necessity of process improvement for terminal stakeholder such as shipping lines, transportation company and external truck drivers as it's strongly bonded to their benefits as well as terminal operative efficiency improvement provided that terminal's unproductive operation was removed.List of Tables ⅱ List of Figures ⅲ Abstract ⅳ 제 1 장 서 론 1 1.1 연구배경 1 1.2 연구목적 2 1.3 연구내용 및 방법 4 제 2 장 선행연구 고찰 연구 5 2.1 국내문헌 연구 5 2.2 국외문헌 연구 10 제 3 장 컨테이너 터미널 일반 및 사례분석 대상 소개 12 3.1 컨테이너 터미널의 정의 12 3.2 컨테이너 터미널의 시설 및 장비 13 3.3 컨테이너 터미널의 하역시스템의 종류 19 3.4 사례분석 대상 컨테이너 터미널 21 제 4 장 컨테이너 터미널 사례조사 및 분석 27 4.1 비생산성 활동의 정의 및 발생원인 27 4.2 P 터미널의 비생산성 활동 분석 28 4.3 벤치마킹 해외 터미널 및 P 터미널과의 비교분석 35 4.4 비생산성 활동의 연구범위 41 4.5 비생산성 활동의 상관관계 분석 47 4.6 시사점 분석 49 제 5 장 결 론 51 5.1 결론 51 5.2 연구의 한계점 및 향후과제 52 참고문헌 54 별첨 56Maste

Analysis of Developmental Trajectories of Career Maturity in College Students

본 연구의 목적은 우리나라 대학생의 시간적 경과에 따른 진로성숙도의 유형별 변화궤적을 파악하고, 진로성숙도의 유형별 변화궤적에 영향을 미치는 요인이 무엇인지 구명하는 것이다. 이 연구에서는 ‘한국교육종단2005’의 5차년도(2009년), 7차년도(2011년), 9차년도(2014년) 세 시점의 자료를 이용하였다. 5차년도는 표본이 고등학교 2학년인 해이고, 7차년도는 표본이 고등학교를 졸업하고 대학에 입학하는 해이며, 9차년도는 표본이 고등학교를 졸업하고 4년이 되는 해였다. 최종적으로 9차년도 기준 4년제 대학에 재학 중이며 대학생용 설문에 응답한 1,390명의 자료를 분석하였다. 진로성숙도 변화궤적의 수와 특성을 분석하기 위해서는 성장혼합모형 분석을, 진로성숙도 궤적집단의 결정요인을 파악하기 위해서는 다항로지스틱 회귀분석을 이용하였다. 주요 연구결과는 다음과 같다. 첫째, 우리나라 대학생의 진로성숙도 변화궤적은 고수준유지형, 중수준유지형, 저수준증가형의 세 개로 확인되었다. 둘째, 개인 특성에서는 성별, 학문적 자아개념, 비학문적 자아개념, 자기주도학습이, 가정 특성에서는 부모학력, 고등학교생활 시 부모의 정서적 지원이, 학교 특성에서는 대학생활적응이 저수준증가형 대비 고수준유지형과 중수준유지형의 진로성숙도 변화궤적을 결정하는 공통 요인으로 나타났다.The purpose of this study was to identify the developmental trajectories of career maturity among college students in Korea and to examine relevant variables that have significant effects on the trajectory groups of career maturity. This study used three waves of data from Korean Education Longitudinal Study 2005 (KELS 2005): 5th year (2009), 7th year (2011) and 9th year (2014). A total of 1,390 students who are enrolled in four-year college based on 9th year study were analyzed. They were categorized into male(545) and female(845) to be analyzed. The Growth Mixture Model(GMM) and the multinomial logistic regression model were mainly used for data analysis. The major findings were as follows: First, three distinct trajectories of career maturity were found; high-level maintaining, mid-level maintaining and low-level increasing groups. Second, the variables that had significant effects on trajectory groups of career maturity for all students were gender, academic self-concept, non-academic self-concept, self-directed learning, academic background of parents, emotional support from parents in high-school, and college life adjustments