• International conference on construction engineering and project management
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• 2005.10a
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• pp.1070-1075
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• 2005

The evaluation items to assess the consumer needs are thought to be varied depending on their age, education and income. It should be noted that consumer needs are getting too diversified to notice them in time due to the rapid economic, social and cultural development. It is, therefore, considered improper to try to assess the level of consumer satisfaction and correct consumer needs by employing one evaluation method for the vastly diversified consumer types. This research is going to conduct a written questionnaire survey to the apartment dwellers in order to identify like dweller groups according to their age, income and education. Then the scope of personal characteristics of each group will be identified and the importance assessment model will be developed. Then the items on the POE will be weighted according to the assessed importance. Finally a method of developing the customer satisfaction index will be produced to quantify how much the consumers are satisfied with the project.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.1
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• pp.233-247
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• 2011

With recent increase in growth without employment and unemployment rate, Business Incubator (BI), which is the birthplace of business start-up, is drawing much attention. Therefore, numerous studies had been carried out from the perspectives of efficient operation and performances of BI. Preceding studies at home and abroad were concentrated mainly on the effect of Critical Success Factors of BI on performance, or on internal operational programs or support services of BI. Recently, assertion that potential capacity of companies located in BI at the time of their commencement of occupancy imparts effect on the performance has been presented. Therefore, this Study, in order to pursue research on above issues, will, firstly, analyze the effect of the characteristics of evaluation of companies wishing to be located in BI conducted by each BI, and, secondly, regulation effect of characteristics of evaluation of companies wishing to be located in BI imparted on performance in connection with the work capabilities of BI and capabilities of manager. The results of analysis illustrated that the expertise, among the capabilities of CEO, imparts affirmative effect on the success rate of business start-up. Product competitiveness and marketability displayed affirmative effect on the success rate of business start-up when work capability (operational intensity) is applied. In particular, although the financing capability of CEO of the company located in BI, as an important factor, imparts negative effect on the success rate of business start-up, it implies affirmative regulation effect through the capabilities of manager.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.2
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• pp.29-43
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• 2023

It is necessary to grasp the characteristics of traffic flow passing through a specific road section and the topological structure of the road in advance in order to quickly prepare a movement management strategy in the event of a disaster or disaster. It is because it can be an essential basis for road managers to assess vulnerabilities by microscopic road units and then establish appropriate monitoring and management measures for disasters or disaster situations. Therefore, this study presented spatial density, time occupancy, and betweenness centrality index to evaluate vulnerabilities by road link in the city department and defined spatial-temporal and topological vulnerabilities by clustering analysis based on distance and density. From the results of this study, road administrators can manage vulnerabilities by characterizing each road link group. It is expected to be used as primary data for selecting priority control points and presenting optimal routes in the event of a disaster or disaster.

• 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.