• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.4
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• pp.614-623
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• 2017

The purpose of this study is to analyze the impact of the financial performance of regional public hospitals on their efficiency. In addition, the analysis of their efficiency using environmental factors, such as the market share, operating mode, and size of the regional public hospitals, as well as the factors influencing their efficiency, are selected by selecting the input and output factors of the hospitals and some differences were found between them. The DEA index and financial performance of the 31 regional public hospitals were calculated for the three years from 2012 to 2014. ANOVA and hierarchical regression analysis were used. As a result, there was a significant difference in their efficiency according to the environmental factors, such as the city scale of the regional public hospital, the number of hospital beds, and their business performance, productivity, and publicness. The medical profit margin (p<0.05), labor cost investment efficiency (p<0.05) and HHI (p<0.05) were found to affect the efficiency. In order to identify the inefficiencies of the regional public hospitals and increase their efficiency, it is necessary to measure the efficiency of the input resources and to reduce their cost. In addition, if the regional public hospitals were to provide specialized services, such as specialized functions of medical care that would give them a competitive advantage over private hospitals, their operational efficiency would be enhanced and they would be able to fulfill their role as public medical institutions.

• Journal of Auto-vehicle Safety Association
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• v.14 no.4
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• pp.43-52
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• 2022

Recently, the government has been expanding the supply of hydrogen vehicles according to the roadmap for vitalizing the hydrogen economy, but is developing safety assessment and inspection technology for the relevant vehicles. This study analyzed the prevention of hydrogen bus accidents' economic effect that arises from the application and development of large-capacity CHSS oil pressure repetition-test assessment technology, hydrogen bus internal chamber pressure transmission and emission volume inspection technology, among various technologies capable of assessing the safety of a hydrogen bus fuel system. To this end, the contingent valuation method (CVM), one of the value evaluation methods of non-market goods, was applied to investigate users' willingness to pay for each inspection technology. The survey for users' willingness to pay was conducted by attaching posters to promote surveys on the internet and within buses to the entire public. As a result of the analysis, the average WTP of the hydrogen bus internal chamber pressure transmission volume inspection technology was 25.3 KRW, the average WTP of the hydrogen bus internal chamber pressure emission volume inspection technology was 18.6 KRW, and the average WTP of the large-capacity CHSS oil pressure repetition-test assessment technology was measured at 16.7 KRW. In addition, the costs and benefits of the introduction of the relevant inspection technology were defined through the interviewing of experts at related research institutions and businesses. As a result of conducting an economic analysis (4.5% discount rate) according to the development of each inspection technology, economic feasibility was seen in all assessment and inspection technologies. As much as the technology is indispensable for the safe use of hydrogen buses, it shows that investment in related technology is very necessary in the future. However, because it was decided that the relevant analysis will differ according to the distribution rate of hydrogen buses, further analysis following this future distribution rate of hydrogen buses is needed, and future users should be made clearly aware of the safety and environmental nature of the technology.

• Asia Marketing Journal
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• v.6 no.3
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• pp.59-81
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• 2004

Store loyalty is increasingly being recognized as a path to long-term business profitability. Customer contact employees deliver a service firm's promises and create an important image for the firm. A major purpose of this study is to investigate the effects of customer service and product value on store loyalty. In order to test research hypotheses, data were collected through surveys administered to 300 apparel store customers. Two hundred thirty nine usable data were used for the analysis. The findings of this research are as follows: First, a employee's voluntary service(EVS) has a positive impact on interpersonal r elationship, which then affects switching barrier and store loyalty. Second, a employee's regular service(ERS) has an influence on store satisfaction, which in turn affect store loyalty. Third, product value is shown to be a significant antecedent to store satisfaction, which have a direct effect on store loyalty. The study concludes with implications, contributions, and limitations of the research and the empirical findings of this research should be beneficial to marketing practitioners and retailing businessmen in developing effective marketing strategies.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.432-438
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• 2011

The purpose of the present thesis is to develop bankruptcy prediction models capable of being applied to the Korean construction industry and to deduce an optimal model through comparative evaluation of final developed models. A study population was selected as general contractors in the Korean construction industry. In order to ease the sample securing and reliability of data, it was limited to general contractors receiving external audit from the government. The study samples are divided into a bankrupt company group and a non-bankrupt company group. The bankruptcy, insolvency, declaration of insolvency, workout and corporate reorganization were used as selection criteria of a bankrupt company. A company that is not included in the selection criteria of the bankrupt company group was selected as a non-bankrupt company. Accordingly, the study sample is composed of a total of 112 samples and is composed of 48 bankrupt companies and 64 non-bankrupt companies. A financial ratio was used as early predictors for development of an estimation model. A total of 90 financial ratios were used and were divided into growth, profitability, productivity and added value. The MDA (Multivariate Discriminant Analysis) model and BLRA (Binary Logistic Regression Analysis) model were used for development of bankruptcy prediction models. The MDA model is an analysis method often used in the past bankruptcy prediction literature, and the BLRA is an analysis method capable of avoiding equal variance assumption. The stepwise (MDA) and forward stepwise method (BLRA) were used for selection of predictor variables in case of model construction. Twenty two variables were finally used in MDA and BLRA models according to timing of bankruptcy. The ROC-Curve Analysis and Classification Analysis were used for analysis of prediction performance of estimation models. The correct classification rate of an individual bankruptcy prediction model is as follows: 1) one year ago before the event of bankruptcy (MDA: 83.04%, BLRA: 93.75%); 2) two years ago before the event of bankruptcy (MDA: 77.68%, BLRA: 78.57%); 3) 3 years ago before the event of bankruptcy (MDA: 84.82%, BLRA: 91.96%). The AUC (Area Under Curve) of an individual bankruptcy prediction model is as follows. : 1) one year ago before the event of bankruptcy (MDA: 0.933, BLRA: 0.978); 2) two years ago before the event of bankruptcy (MDA: 0.852, BLRA: 0.875); 3) 3 years ago before the event of bankruptcy (MDA: 0.938, BLRA: 0.975). As a result of the present research, accuracy of the BLRA model is higher than the MDA model and its prediction performance is improved.

• Journal of Korean Academy of Nursing Administration
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• v.2 no.1
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• pp.97-114
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• 1996

INSTRODUCTION Service quality is, unlike goods quality, an abstract and elusive constuct. Service quality and its requirements are not easily understood by consumers, and also present some critical research problems. However, quality is very important to marketers and consumers in that it has many strategic benefits in contributing to profitability of marketing activities and consumers' problem-solving activities. Moreover, despite the phenomenal growth of medical service sector, few researchers have attempted to define and model medical service quality. Especially, little research has focused on the evaluation of medical service quality and patient satisfaction from the perspectives of both the provider and the patient. As competition intensifies and patients are demanding higher quality of medical service, medical service quality and patient satisfaction has emerged as a critical research topic. The major purpose of this article is to explore the concept of medical service quality and its evaluation from both nurse and patient perspectives. This article attempts to achieve its purpose by (1)classfying critical service attibutes into threecategories(satisfiers, hygiene factors, and performance factors). (2)measuring the relative importance of need criteria, (3)evaluating SERVPERF model and SERVQUAL model in medical service sector, and (4)identifying the relationship between perceived quality and overall patient satisfaction. METHOD Data were gathered from a sample of 217 patients and 179 nurses in Seoul-area general hospitals. From the review of previous literature, 50 survey items representing various facets of the medical service quality were developed to form a questionnaire. A five-point scale ranging from "Strongly Agree"(5) to "Strongly Disagree"(1) accompanied each statement(expectation statements, perception statements, and importance statements). To measure overall satisfaction, a seven-point scale was used, ranging from "Very Satisfied"(7) to "Very Dissatisfied"(1) with no verbal labels for scale points 2 through 6 RESULTS In explaining the relationship between perceived performance and overall satisfaction, only 31 variables out of original 50 survey items were proven to be statistically significant. Hence, a penalty-reward analysis was performed on theses 31 critical attributes to find out 17 satisfiers, 8 hygiene factors, and 4 performance factors in patient perspective. The role(category) of each service quality attribute in relation to patient satisfaction was com pared across two groups, that is, patients and nurses. They were little overlapped, suggesting that two groups had different sets of 'perceived quality' attributes. Principal components factor analyses of the patients' and nurses' responses were performed to identify the underlying dimensions for the set of performance(experience) statements. 28 variables were analyzed by using a varimax rotation after deleting three obscure variables. The number of factors to be extracted was determined by evaluating the eigenvalue scores. Six factors wereextracted, accounting for 57.1% of the total variance. Reliability analysis was performed to refine the factors further. Using coefficient alpha, scores of .84 to .65 were obtained. Individual-item analysis indicated that all statements in each of the factors should remain. On 26 attributes of 31 critical service quality attributes, there were gaps between actual patient's importance of need criteria and nurse perceptions of them. Those critical attributes could be classified into four categories based on the relative importance of need criteria and perceived performance from the perspective of patient. This analysis is useful in developing strategic plans for performance improvement. (1) top priorities(high importance and low performance) (in this study)- more health-related information -accuracy in billing - quality of food - appointments at my convenience - information about tests and treatments - prompt service of business office -adequacy of accommodations(elevators, etc) (2) current strengths(high importance and high performance) (3)unnecessary strengths(low importance and high performance) (4) low priorities(low importance and low performance) While 26 service quality attributes of SERPERF model were significantly related to patient satisfation, only 13 attributes of SERVQUAL model were significantly related. This result suggested that only experience-based norms(SERVPERF model) were more appropriate than expectations to serve as a benchmark against which service experiences were compared(SERVQUAL model). However, it must be noted that the degree of association to overall satisfaction was not consistent. There were some gaps between nurse percetions and patient perception of medical service performance. From the patient's viewpoint, "personal likability", "technical skill/trust", and "cares about me" were most significant positioning factors that contributed patient satisfaction. DISCUSSION This study shows that there are inconsistencies between nurse perceptions and patient perceptions of medical service attributes. Also, for service quality improvement, it is most important for nurses to understand what satisfiers, hygiene factors, and performance factors are through two-way communications. Patient satisfaction should be measured, and problems identified should be resolved for survival in intense competitive market conditions. Hence, patient satisfaction monitoring is now becoming a standard marketing tool for healthcare providers and its role is expected to increase.

• Asia pacific journal of information systems
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• v.19 no.2
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• pp.157-178
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• 2009

Corporate credit rating is a very important factor in the market for corporate debt. Information concerning corporate operations is often disseminated to market participants through the changes in credit ratings that are published by professional rating agencies, such as Standard and Poor's (S&P) and Moody's Investor Service. Since these agencies generally require a large fee for the service, and the periodically provided ratings sometimes do not reflect the default risk of the company at the time, it may be advantageous for bond-market participants to be able to classify credit ratings before the agencies actually publish them. As a result, it is very important for companies (especially, financial companies) to develop a proper model of credit rating. From a technical perspective, the credit rating constitutes a typical, multiclass, classification problem because rating agencies generally have ten or more categories of ratings. For example, S&P's ratings range from AAA for the highest-quality bonds to D for the lowest-quality bonds. The professional rating agencies emphasize the importance of analysts' subjective judgments in the determination of credit ratings. However, in practice, a mathematical model that uses the financial variables of companies plays an important role in determining credit ratings, since it is convenient to apply and cost efficient. These financial variables include the ratios that represent a company's leverage status, liquidity status, and profitability status. Several statistical and artificial intelligence (AI) techniques have been applied as tools for predicting credit ratings. Among them, artificial neural networks are most prevalent in the area of finance because of their broad applicability to many business problems and their preeminent ability to adapt. However, artificial neural networks also have many defects, including the difficulty in determining the values of the control parameters and the number of processing elements in the layer as well as the risk of over-fitting. Of late, because of their robustness and high accuracy, support vector machines (SVMs) have become popular as a solution for problems with generating accurate prediction. An SVM's solution may be globally optimal because SVMs seek to minimize structural risk. On the other hand, artificial neural network models may tend to find locally optimal solutions because they seek to minimize empirical risk. In addition, no parameters need to be tuned in SVMs, barring the upper bound for non-separable cases in linear SVMs. Since SVMs were originally devised for binary classification, however they are not intrinsically geared for multiclass classifications as in credit ratings. Thus, researchers have tried to extend the original SVM to multiclass classification. Hitherto, a variety of techniques to extend standard SVMs to multiclass SVMs (MSVMs) has been proposed in the literature Only a few types of MSVM are, however, tested using prior studies that apply MSVMs to credit ratings studies. In this study, we examined six different techniques of MSVMs: (1) One-Against-One, (2) One-Against-AIL (3) DAGSVM, (4) ECOC, (5) Method of Weston and Watkins, and (6) Method of Crammer and Singer. In addition, we examined the prediction accuracy of some modified version of conventional MSVM techniques. To find the most appropriate technique of MSVMs for corporate bond rating, we applied all the techniques of MSVMs to a real-world case of credit rating in Korea. The best application is in corporate bond rating, which is the most frequently studied area of credit rating for specific debt issues or other financial obligations. For our study the research data were collected from National Information and Credit Evaluation, Inc., a major bond-rating company in Korea. The data set is comprised of the bond-ratings for the year 2002 and various financial variables for 1,295 companies from the manufacturing industry in Korea. We compared the results of these techniques with one another, and with those of traditional methods for credit ratings, such as multiple discriminant analysis (MDA), multinomial logistic regression (MLOGIT), and artificial neural networks (ANNs). As a result, we found that DAGSVM with an ordered list was the best approach for the prediction of bond rating. In addition, we found that the modified version of ECOC approach can yield higher prediction accuracy for the cases showing clear patterns.

• Journal of Distribution Science
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• v.10 no.7
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• pp.33-41
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• 2012

The purpose of this study is to analyse the state of the energy industry and to determine the efficiency of its functioning on the basis of energy conservation principle and application of innovative technologies aimed at improving the ecological modernisation of agricultural sectors of Kazakhstan. The research methodology is based on an integrated approach of financial and economic evaluation of the effectiveness of the investment project, based on calculation of elasticity, total costs and profitability, as well as on comparative, graphical and system analysis. The current stage is characterised by widely spread restructuring processes of electric power industry in many countries through introduction of new technical installations of energy facilities and increased government regulation in order to enhance the competitive advantage of electricity market. Electric power industry features a considerable value of creating areas. For example, by providing scientific and technical progress, it crucially affects not only the development but also the territorial organisation of productive forces, first of all the industry. In modern life, more than 90% of electricity and heat is obtained by Kazakhstan's economy by consuming non-renewable energy resources: different types of coal, oil shale, oil, natural gas and peat. Therefore, it is significant to ensure energy security, as the country faces a rapid fall back to mono-gas structure of fuel and energy balance. However, energy resources in Kazakhstan are spread very unevenly. Its main supplies are concentrated in northern and central parts of the republic, and the majority of consumers of electrical power live in the southern and western areas of the country. However, energy plays an important role in the economy of industrial production and to a large extent determines the level of competitive advantage, which is a promising condition for implementation of energy-saving and environmentally friendly technologies. In these circumstances, issues of modernisation and reforms of this sector in Kazakhstan gain more and more importance, which can be seen in the example of economically sustainable solutions of a large local monopoly company, significant savings in capital investment and efficiency of implementation of an investment project. A major disadvantage of development of electricity distribution companies is the prevalence of very high moral and physical amortisation of equipment, reaching almost 70-80%, which significantly increases the operating costs. For example, while an investment of 12 billion tenge was planned in 2009 in this branch, in 2012 it is planned to invest more than 17 billion. Obviously, despite the absolute increase, the rate of investment is still quite low, as the total demand in this area is at least more than 250 billion tenge. In addition, industrial infrastructure, including the objects of Kazakhstan electric power industry, have a tangible adverse impact on the environment. Thus, since there is a large number of various power projects that are sources of electromagnetic radiation, the environment is deteriorated. Hence, there is a need to optimise the efficiency of the organisation and management of production activities of energy companies, to create and implement new technologies, to ensure safe production and provide solutions to various environmental aspects. These are key strategic factors to ensure success of the modern energy sector of Kazakhstan. The contribution of authors in developing the scope of this subject is explained by the fact that there was not enough research in the energy sector, especially in the view of ecological modernisation. This work differs from similar works in Kazakhstan in the way that the proposed method of investment project calculation takes into account the time factor, which compares the current and future value of profit from the implementation of innovative equipment that helps to bring it to actual practise. The feasibility of writing this article lies in the need of forming a public policy in the industrial sector, including optimising the structure of energy disbursing rate, which complies with the terms of future modernised development of the domestic energy sector.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.23-46
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• 2017

Although there have been cases of evaluating the value of specific companies or projects which have centralized on developed countries in North America and Europe from the early 2000s, the system and methodology for estimating the economic value of individual technologies or patents has been activated on and on. Of course, there exist several online systems that qualitatively evaluate the technology's grade or the patent rating of the technology to be evaluated, as in 'KTRS' of the KIBO and 'SMART 3.1' of the Korea Invention Promotion Association. However, a web-based technology valuation system, referred to as 'STAR-Value system' that calculates the quantitative values of the subject technology for various purposes such as business feasibility analysis, investment attraction, tax/litigation, etc., has been officially opened and recently spreading. In this study, we introduce the type of methodology and evaluation model, reference information supporting these theories, and how database associated are utilized, focusing various modules and frameworks embedded in STAR-Value system. In particular, there are six valuation methods, including the discounted cash flow method (DCF), which is a representative one based on the income approach that anticipates future economic income to be valued at present, and the relief-from-royalty method, which calculates the present value of royalties' where we consider the contribution of the subject technology towards the business value created as the royalty rate. We look at how models and related support information (technology life, corporate (business) financial information, discount rate, industrial technology factors, etc.) can be used and linked in a intelligent manner. Based on the classification of information such as International Patent Classification (IPC) or Korea Standard Industry Classification (KSIC) for technology to be evaluated, the STAR-Value system automatically returns meta data such as technology cycle time (TCT), sales growth rate and profitability data of similar company or industry sector, weighted average cost of capital (WACC), indices of industrial technology factors, etc., and apply adjustment factors to them, so that the result of technology value calculation has high reliability and objectivity. Furthermore, if the information on the potential market size of the target technology and the market share of the commercialization subject refers to data-driven information, or if the estimated value range of similar technologies by industry sector is provided from the evaluation cases which are already completed and accumulated in database, the STAR-Value is anticipated that it will enable to present highly accurate value range in real time by intelligently linking various support modules. Including the explanation of the various valuation models and relevant primary variables as presented in this paper, the STAR-Value system intends to utilize more systematically and in a data-driven way by supporting the optimal model selection guideline module, intelligent technology value range reasoning module, and similar company selection based market share prediction module, etc. In addition, the research on the development and intelligence of the web-based STAR-Value system is significant in that it widely spread the web-based system that can be used in the validation and application to practices of the theoretical feasibility of the technology valuation field, and it is expected that it could be utilized in various fields of technology commercialization.

• Journal of Distribution Science
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• v.9 no.1
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• pp.17-27
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• 2011

As the world becomes more globalized, business competition becomes fiercer, while consumers' needs for less expensive quality products are on the increase. Business operations make an effort to secure a competitive edge in costs and services, and the logistics industry, that is, the industry operating the storing and transporting of goods, once thought to be an expense, begins to be considered as the third cash cow, a source of new income. Logistics centers are central to storage, loading and unloading of deliveries, packaging operations, and dispensing goods' information. As hubs for various deliveries, they also serve as a core infrastructure to smoothly coordinate manufacturing and selling, using varied information and operation systems. Logistics centers are increasingly on the rise as centers of business supply activities, growing beyond their previous role of primarily storing goods. They are no longer just facilities; they have become logistics strongholds that encompass various features from demand forecast to the regulation of supply, manufacturing, and sales by realizing SCM, taking into account marketability and the operation of service and products. However, despite these changes in logistics operations, some centers have been unable to shed their past roles as warehouses. For the continuous development of logistics centers, various measures would be needed, including a revision of current supporting policies, formulating effective management plans, and establishing systematic standards for founding, managing, and controlling logistics centers. To this end, the research explored previous studies on the use and effectiveness of logistics centers. From a theoretical perspective, an evaluation of the overall introduction, purposes, and transitions in the use of logistics centers found issues to ponder and suggested measures to promote and further advance logistics centers. First, a fact-finding survey to establish demand forecast and standardization is needed. As logistics newspapers predicted that after 2012 supply would exceed demand, causing rents to fall, the business environment for logistics centers has faltered. However, since there is a shortage of fact-finding surveys regarding actual demand for domestic logistic centers, it is hard to predict what the future holds for this industry. Accordingly, the first priority should be to get to the essence of the current market situation by conducting accurate domestic and international fact-finding surveys. Based on those, management and evaluation indicators should be developed to build the foundation for the consistent advancement of logistics centers. Second, many policies for logistics centers should be revised or developed. Above all, a guideline for fair trade between a shipper and a commercial logistics center should be enacted. Since there are no standards for fair trade between them, rampant unfair trades according to market practices have brought chaos to market orders, and now the logistics industry is confronting its own difficulties. Therefore, unfair trade cases that currently plague logistics centers should be gathered by the industry and fair trade guidelines should be established and implemented. In addition, restrictive employment regulations for foreign workers should be eased, and logistics centers should be charged industry rates for the use of electricity. Third, various measures should be taken to improve the management environment. First, we need to find out how to activate value-added logistics. Because the traditional purpose of logistics centers was storage and loading/unloading of goods, their profitability had a limit, and the need arose to find a new angle to create a value added service. Logistic centers have been perceived as support for a company's storage, manufacturing, and sales needs, not as creators of profits. The center's role in the company's economics has been lowering costs. However, as the logistics' management environment spiraled, along with its storage purpose, developing a new feature of profit creation should be a desirable goal, and to achieve that, value added logistics should be promoted. Logistics centers can also be improved through cost estimation. In the meantime, they have achieved some strides in facility development but have still fallen behind in others, particularly in management functioning. Lax management has been rampant because the industry has not developed a concept of cost estimation. The centers have since made an effort toward unification, standardization, and informatization while realizing cost reductions by establishing systems for effective management, but it has been hard to produce profits. Thus, there is an urgent need to estimate costs by determining a basic cost range for each division of work at logistics centers. This undertaking can be the first step to improving the ineffective aspects of how they operate. Ongoing research and constant efforts have been made to improve the level of effectiveness in the manufacturing industry, but studies on resource management in logistics centers are hardly enough. Thus, a plan to calculate the optimal level of resources necessary to operate a logistics center should be developed and implemented in management behavior, for example, by standardizing the hours of operation. If logistics centers, shippers, related trade groups, academic figures, and other experts could launch a committee to work with the government and maintain an ongoing relationship, the constraint and cooperation among members would help lead to coherent development plans for logistics centers. If the government continues its efforts to provide financial support, nurture professional workers, and maintain safety management, we can anticipate the continuous advancement of logistics centers.