• Korea Journal of Hospital Management
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• v.26 no.2
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• pp.17-26
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• 2021

Purposes: This study aims to identify factors affecting dental university hospitals' profitability and understand recent their business condition. Methodology: Data from 2016 to 2019 was collected from financial statement, public open data in 8 dental university hospitals. For the study, multiple regression test with stepwise selection was applied. Findings: First of all, 9 out of 19 independent variables were selected by stepwise selection. As a result of multiple regression test with selected independent variables and the dependent variable(operating profit margin ratio), the factors affecting hospitals' profitability were the number of dental unit chair, hospital location, debt ratio, total capital turnover ratio, employment cost rate, material cost rate, management expense rate, the number of patient per a dentist. Practical Implication: To improve dental university hospitals' profitability, hospitals specifically analysis and manage their cost such as employment, material and management cost and seek effectiveness by managing the proper number of patient per a dentist.

• International Journal of Reliability and Applications
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• v.8 no.1
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• pp.67-82
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• 2007

This paper deals with the effectiveness analysis of an engineering system, which has two units of different strengths in parallel and one unit as a cold standby unit. Failure times for all the units have negative exponential distribution whereas their repair times have general distribution. Single server caters the need for the system. The effectiveness analysis of the system is done by using regenerative point technique. The different measures of effectiveness such as mean sojourn time, mean time to system failure, availability, busy period, etc, are derived. Cost factors also taken into consideration.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.494-496
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• 2013

Cost-Benefit Analysis (CBA) is a systematic optimization process that allows users to compare different alternatives and to determine if a project is a solid investment. Many state DOTs have included CBA in their pavement management systems (PMSs) to help allocate state funds for maintenance, rehabilitation, resurfacing, and reconstruction of pavements. In a typical CBA, each pavement type has an assigned weight factor which represents the level of importance of this pavement type. To conduct an accurate CBA, it is essential to select appropriate weight factors. Arbitrarily assigning weights factors to pavements can lead to biased and inaccurate funding allocation decisions. The purpose for this paper is to outline a method to develop an ideal set of weight factors that can be utilized to conduct more accurate CBA. To this end, a matrix of all possible weight factors sets was developed. CBA was conducted for each set of weight factors to obtain a population of possible optimization solutions. Then a regression analysis was performed to establish the relationship between benefit and weight factors. Finally, a multi-objective genetic algorithm was applied to select the optimal set of weight factors. The findings from this study can be used by state DOTs to strategically manage their roadway systems in a cost effective manner.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5D
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• pp.665-675
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• 2008

The objective of this paper is to provide an approximate cost estimating model for tunnel that can be utilized both in quick construction cost estimating for design alternatives, and in evaluating efficiently the cost effects according to the environmental changes during design and construction stage. To meet this requirement, this study analyzes critical cost factors influencing tunnel construction costs. The cost factors include 7 elements such as rock drilling method, advancing method, type of detonator, loader capacity, unit weight and soil volume change factor, length of tunnel. This paper investigates the cost variance according to the change of the cost factors. The result is expected to be used in formulating approximate tunnel cost estimating model.

• Journal of Korean Biological Nursing Science
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• v.21 no.2
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• pp.133-140
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• 2019

Purpose: The purpose of this study was to check the degree of residual microbial contamination after disinfection of reusable suction containers, used in an intensive care unit (ICU) and present basic data for efficient use through cost analysis in comparison to disposable suction containers. Methods: This study was conducted on 32 reusable suction containers used in an ICU on a selected specific day. After disinfection and washing, specimens were collected from the used containers and cultured to check for microbial contamination. Additionally, a comparative narrative study analyzes the cost of using reusable suction containers and disposable suction containers. Data were analyzed with the SPSS WIN 20.0 program using real numbers and percentage ${\chi}^2$-test. Results: As a result of the study, microorganisms were found in all samples where in 30 were gram-positive (62.5%) while 13 were gram-negative (27.1%). Based on level of contamination, microorganisms were less than 10CFU/ml in 18 samples (56.3%); 11-99CFU/ml in six samples (18.8%); and more than 100CFU/ml in eight samples (25%). Cost per day for a reusable suction container was $10,655+{\alpha}$ while cost per day for a disposable suction container was 10,666 won. Conclusion: This study found that reusable suction containers, even after disinfection, accounted for factors of potential infection as well as microbial contamination. So, disposable suction containers are superior in cost-effectiveness and highly efficient for use with infected patients.

• Journal of Korean Society for Quality Management
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• v.8 no.2
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• pp.15-22
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• 1980

This paper deals with the problem of determining a minimum cost sampling inspection plan for a single destructive testing by attribute. The cost for inspection lot is constructed by following three cost factors: (1) cost of inspection, (2) cost of accepted defective, (3) cost of rejected lot Using Hald's Bayesian approach in a single non-destructive testing, procedure's for finding the minimum cost single destructive sampling inspection plan by attribute are given. Assuming the uniform distribution as a prior-distribution and using numerical analysis by computer, a minimum cost single destructive sampling inspection plan by attribute for several lot sizes, unit cost, destructive testing cost, and salvage cost is given.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2011.11a
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• pp.11-12
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• 2011

The Construction Standard Production Unit(CSPU) has been used for the standard cost estimate in public and private construction projects. However, It is difficult to reflect the various site attributed variation in productivity using existing CSPU. The reason is that a criteria which site should be selection for enactment and/or revision of CSPU is not established. This study aims to provide essential data to be used for analyzing the labor factors in a way to secure efficiency and reliability of CSPU.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.12
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• pp.653-659
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• 2018

The accurate prediction of construction cost is a key factor in a project's success. However, it is hard to predict the construction costs in the planning stages rapidly and precisely when drawings, specifications, construction cost calculation statements are incomplete, among other factors. Accurate construction-cost prediction in the planning stage of a project is also important for project feasibility studies and successful completion. Therefore, various techniques have been applied to accurately predict construction costs at an early stage when project information is limited. There are many factors that affect the construction cost prediction. This paper presents a construction-cost prediction method as multiple regression model with seven construction factors as independent variables. The method was used to predict the construction cost of a local housing union project, and the error rate was 4.87%. It is not possible to compare the cost of the project at the planning stage of the local housing union project, but it has high prediction accuracy compared to the unit price of an existing unit area. It is likely to be applied in construction-cost calculation work and to contribute to the establishment of the budget for the local housing union project.

• Health Policy and Management
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• v.8 no.1
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• pp.1-14
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• 1998

Analysis of practice variations has been one of important issues in trying to contain costs as well as to manage quality in health care. This study was conducted to provide statistical model for analysing variations in inpatient costs by type of hospitals. Four K-DRGs including Cesarean section, appendectomy, cataract extraction, and pediatric pneumonia with CC class 0 were selected, and means and dispersions of inpatient procedure and operation costs were simultaneously compared between type of hospitals. The results indicated that joint modelling of means and dispersions by gamma distribution was a very useful analytic tool for identifying factors which might have relationship with variations in inpatient costs. This model can be expanded to test the significance of several independent variables in analysing cost variations. In surgical conditions, means and unit variations of procedure and operation costs showed consistent pattern which was tertiarty hospital, general hospital, and hospital in descending order. Different findings were identified in pediatric pneumonia, from which mean and unit variation of procedure and operation cost was the highest in general hospital. The practical implication of this difference could not be drawn from this study. It will be done by further sophisticated researches. In order to develop health policy for cost containment and quality management in Korea, it is essential to find out manageable factors affecting variations in practice patterns which include characteristics of population, providers, regions, and so on. The statistical model presented in this study will give health services researchers useful insights for future investigations in analysing cost variations.

• Management Science and Financial Engineering
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• v.21 no.1
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• pp.25-29
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• 2015

Recently much research efforts have focused on how to manage carbon emissions in logistics operations. This paper formulates a model to determine an optimal shipment size with aims to minimize the total cost consisting not only of inventory and transportation costs but also cost for carbon emissions. Unlike the literature assuming carbon emission factors as a given condition, we consider the emission factors as decision variables. It is allowed to make an investment in improving carbon emission factors. The optimal investment decision is shown to be of a threshold type with respect to unit investment costs. Moreover, the findings in this work provide insights on the various elements of the investment decision and their impacts.