• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.2
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• pp.583-596
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• 2012

The researchers of the organizational behavior have been interested in the performances of transformational leadership in various environments and cultures. In this study, data were collected to find out the effects of professors' transformational leadership on students’ departmental identification, study engagement and organizational citizenship behavior to school. This study also tested indirect effect between transformational leadership and organizational citizenship behavior via departmental identification and study engagement. The results indicated significant direct relation between professors' transformational leadership and departmental identification, study engagement and citizenship behavior to school. But direct relation between study engagement and citizenship behavior was not found. Departmental identification was found as a mediator between transformational leadership and citizenship behavior. This study suggests that professors' transformational leadership is quite necessary for school, department and student.

• Korean Journal of Computational Design and Engineering
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• v.17 no.1
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• pp.26-34
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• 2012

Assembly scheduling in shipbuilding is responsible for determine assembly process orders and departmental production schedule for the block, the basic composite unit of ships. It is necessary much more information to decide production scheduling as the characteristic of shipbuilding which has been more complex and more various and also, a lot of waste of time and of human power is generated in the course of data processing. The target shipbuilding manufacturer of this study use empirical techniques, based on the user's discretion, to compile and to apply data which are scattered in DB storages separately. Because of that reason, the user should not only be performed identification and screening operations but also modification and verification for vast amounts of data, so it is hard to keep the consistency of the data and also the operation time is not constant. Accordingly, the object in this study is by presenting an efficient DB framework to reduce wasting time and man-hour at experienced-oriented process, abate user's manual operations and support an efficient scheduling in assembly processes.

• Korean Institute of Interior Design Journal
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• v.13 no.6
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• pp.123-131
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• 2004

The hospitals built In the seventies and eighties have gone through many different extensions and renovations. However, as there had been no prior projections of the future extensions, irrational processes in terms of interdepartmental functional relocations and space availability have recurred. As well, areas and departments are located in several wings, which bring about a decrease in interdepartmental functional linkage, causing a lot of confusion and trouble in hospital management. Through this research we acquire concluding remarks. 1) To restore functional linkage in the whole hospital, strategy of interdepartmental relocation with the clinic-in-the clinic concept is the measure to minimize the problems of the increase in interdepartmental functional linkage since the clinic-in-the clinic concepts minimize circulation and maximizes efficiency of hospital management by making all the dispersed wings as professional as possible. 2) The measure of smooth circulation in order to resolve the problems of patients' difficulty in identifying directions and in decrease in staff's work performance, which arises from the extensions without considering the traffic systems of the whole hospital involves introduction of linear circulation systems in which connections between departments or areas can be made centering main axes of circulation. It is also a responsive measure to enhance the functional linkage between buildings and efficiency of patient's ease in identification of directions.

• Journal of Preventive Medicine and Public Health
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• v.11 no.1
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• pp.123-127
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• 1978

The major objective of this research is to identify those hospital characteristics that best explain cost variation among hospitals and to formulate linear models that can predict hospital costs. Specific emphasis is placed on hospital output, that is, the identification of diagnosis related patient groups (DRGs) which are medically meaningful and demonstrate similar patterns of hospital resource consumption. A casemix index is developed based on the DRGs identified. Considering the common problems encountered in previous hospital cost research, the following study requirements are estab-lished for fulfilling the objectives of this research: 1. Selection of hospitals that exercise similar medical and fiscal practices. 2. Identification of an appropriate data collection mechanism in which demographic and medical characteristics of individual patients as well as accurate and comparable cost information can be derived. 3. Development of a patient classification system in which all the patients treated in hospitals are able to be split into mutually exclusive categories with consistent and stable patterns of resource consumption. 4. Development of a cost finding mechanism through which patient groups' costs can be made comparable across hospitals. A data set of Medicare patients prepared by the Social Security Administration was selected for the study analysis. The data set contained 27,229 record abstracts of Medicare patients discharged from all but one short-term general hospital in Connecticut during the period from January 1, 1971, to December 31, 1972. Each record abstract contained demographic and diagnostic information, as well as charges for specific medical services received. The 'AUT-OGRP System' was used to generate 198 DRGs in which the entire range of Medicare patients were split into mutually exclusive categories, each of which shows a consistent and stable pattern of resource consumption. The 'Departmental Method' was used to generate cost information for the groups of Medicare patients that would be comparable across hospitals. To fulfill the study objectives, an extensive analysis was conducted in the following areas: 1. Analysis of DRGs: in which the level of resource use of each DRG was determined, the length of stay or death rate of each DRG in relation to resource use was characterized, and underlying patterns of the relationships among DRG costs were explained. 2. Exploration of resource use profiles of hospitals; in which the magnitude of differences in the resource uses or death rates incurred in the treatment of Medicare patients among the study hospitals was explored. 3. Casemix analysis; in which four types of casemix-related indices were generated, and the significance of these indices in the explanation of hospital costs was examined. 4. Formulation of linear models to predict hospital costs of Medicare patients; in which nine independent variables (i. e., casemix index, hospital size, complexity of service, teaching activity, location, casemix-adjusted death. rate index, occupancy rate, and casemix-adjusted length of stay index) were used for determining factors in hospital costs. Results from the study analysis indicated that: 1. The system of 198 DRGs for Medicare patient classification was demonstrated not only as a strong tool for determining the pattern of hospital resource utilization of Medicare patients, but also for categorizing patients by their severity of illness. 2. The wei틴fed mean total case cost (TOTC) of the study hospitals for Medicare patients during the study years was $11,27.02 with a standard deviation of $117.20. The hospital with the highest average TOTC ($1538.15) was 2.08 times more expensive than the hospital with the lowest average TOTC ($743.45). The weighted mean per diem total cost (DTOC) of the study hospitals for Medicare patients during the sutdy years was $107.98 with a standard deviation of $15.18. The hospital with the highest average DTOC ($147.23) was 1.87 times more expensive than the hospital with the lowest average DTOC ($78.49). 3. The linear models for each of the six types of hospital costs were formulated using the casemix index and the eight other hospital variables as the determinants. These models explained variance to the extent of 68.7 percent of total case cost (TOTC), 63.5 percent of room and board cost (RMC), 66.2 percent of total ancillary service cost (TANC), 66.3 percent of per diem total cost (DTOC), 56.9 percent of per diem room and board cost (DRMC), and 65.5 percent of per diem ancillary service cost (DTANC). The casemix index alone explained approximately one half of interhospital cost variation: 59.1 percent for TOTC and 44.3 percent for DTOC. Thsee results demonstrate that the casemix index is the most importand determinant of interhospital cost variation Future research and policy implications in regard to the results of this study is envisioned in the following three areas: 1. Utilization of casemix related indices in the Medicare data systems. 2. Refinement of data for hospital cost evaluation. 3. Development of a system for reimbursement and cost control in hospitals.