• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.3
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• pp.18-26
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• 2017

Defense industries which require high reliability need an optimized quality management system with well-planned implementation. And the government should examine the overall status of defense industries, then establish practical policies with a proper support plan in required areas to upgrade the quality management level of manufacturers. Thus, DTaQ developed the model for 2 years from 2014, which specialized in quality management level analysis for defense industries. And a survey has been undertaken with that model by DTaQ and Korea Research Center in 2016. The surveyed companies randomly sampled among those which have more than 30 employees and delivery history over past 3 years, and finally 106 defense industries were selected. This paper present survey method and indexes for survey of defense industry quality management level. The survey was conducted in the order of planning, data collection and data processing, and the validity and reliability of the data were verified to increase objectivity of survey results. The survey contents mainly consist of system quality and management quality. System quality includes Product Development Management, Production Operation Management, supply chain quality management, Safety & Environment Management and Reliability Management, on the other hand, management quality includes Strategic Leadership, Human Resource Management, Customer Market Management and Information & Knowledge Management. Thus this proposes the current overall quality management status of the 106 defense industries and shows level differences by company sizes and manufacturing sectors based on the result of survey. Specifically, this paper enables to track the areas which need prompt government support with the policy directions to make quality management level higher. Therefore, it is expected that this can be used as reference data in establishing quality policies for military supplies in the future.

• Proceedings of the Korean Reliability Society Conference
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• 2005.06a
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• pp.141-145
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• 2005

Nowadays, most industries take $B_{6\sigma}$ quality level as a goal of the ultimate quality level of their products. On the other hand, $B_{10}$ to life indicates the time that $10\%$ of products are failed. There is no relation between the $B_{6\sigma}$ quality level and the $B_{10}$ to life. Therefore, some industries perform their quality control activities and reliability engineering activities separately. So I propose one measure which can express quality and reliability level simultaneously for the products to pursue quality and reliability activities together in the industry.

• Journal of Korean Society for Quality Management
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• v.30 no.2
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• pp.130-151
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• 2002

This paper investigates the relation between the Process capability index(PCI) and the quality assurance level under various conditions. The effect of the off-targetness of the process mean, deviation from the nomality, the estimation error, and tile measurement error on the quality assurance level is evaluated. Various distributions such as the Student-t, the chi-square, the gamma, the Weibull, and the log-normal distributions are considered to evaluate the deviation from the nomality. The quality levels under abnormal conditions turn out to be severely different from that under the standard condition. We provide tables and graphs of the quality assurance level on various abnormal conditions. In order for the industry users to use the PCI properly, they should refer to the tables and graphs, especially when they are not certain about the standard assumptions on which the PCI depends.

• Journal of the Korea Safety Management & Science
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• v.5 no.4
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• pp.169-185
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• 2003

Recently many researchers contributed to the understanding of Quality Control System, but the use of economics in the design of quality assurance system is limited in treatment of the relationship between the average incoming quality level (or average process quality level) of the incoming lot and the average outgoing quality level of this lot. In this study, a traditional concept of sampling inspection plan for the quality assurance system is extended to a consideration of economic aspects in total production system by representing and analyzing the effects between proceeding and succeeding production process including inspection process. This approach recognizes that the decision at each manufacturing process (or assembly process), is to be determined not only by the cost and the average outgoing quality level of that process, but also by the input parameters of the cost and the incoming quality to the succeeding process. By analyzing the effects of the average incoming and outgoing quality, manufacturing or assembly process quality level and sampling inspection plan on the production system, mathematical models and solution technique to minimize the total production cost for a general product manufacturing system with specified average outgoing quality limit are suggested.

• Journal of Korean Society for Quality Management
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• v.19 no.2
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• pp.158-165
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• 1991

The Q-cost has been used in the manufacturing company to decide the optimal level of company's product quality, and to evaluate the effect of company's quality control system since the advent of Q-cost theory. In spite of the following costs are generated in the user side, owing to an unsuitable level of product quality and inadequacy of company's quality control system, these costs are not usually included in the company's Q-cost : (1) the cost generated in relation to a claim proposal as traffic expeneses and transpotation of the product. (2) the cost of maintenance through the useful life of the product, especially accured after quality warranty period. (3) the cost related to the economical efficiency in using the product. (4) the cost ralated to a customer dissatisfaction for the product quality. In this point of view, the contents of user side Q-cost, and the relations between the user side Q-cost and the level of company's product quality are discussed. And then the importance of user side Q-cost in order to determine the optimal quality level is discussed.

• Asia Marketing Journal
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• v.21 no.2
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• pp.21-49
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• 2019

This study examines a model which simultaneously contains two paths between waiting line and purchase intention: one tested the positive effect of waiting line through consumers' perceived quality, whereas another one go through consumers' emotional state to test the negative effect of waiting line on purchase intention. To further understand perceived quality, the study divided perceived quality into perceived product quality and perceived service quality. The study used restaurants in the experiment. Results indicated that although long waits in line will directly increase both consumers' product quality perception and negative emotions, the total indirect effects on purchase intention are still significantly positive. For consumers' perceived service quality, long waiting situations have no such effect on it. Significant results from a moderation analysis also shown that consumers in low-level knowledge settings are more influenced by waiting lines than those in high-level knowledge settings when they make the product's quality-related judgment. However, the level of consumer knowledge does not moderate the relationship between waiting lines and service quality.

• Journal of Korean Academy of Nursing
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• v.30 no.3
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• pp.670-681
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• 2000

The purpose of this study was to identity the level of burden, social support and quality of life of the subjects. The subjects of this study were 68 mothers of nephrotic syndrome patients whose children were hospitalized in one pediatric ward of the University Hospital in Seoul. The data was collected using questionnaires, and the period of the data collection was from Nov. 15 to Dec. 31, 1999. The instruments used for this study were the Burden Measurement Instrument developed by Montgomery et. al(1985), social support measurement instrument designed Brandt an Weinert(1978) and Quality of life scale designed by Ro,Yoo JA(1988). The data analysis was done by SPSS, t-test, ANOVA and the Pearson correlation coefficient. The results of were as follows. 1. The level of burden showed a mean score of 54.47, the level of social support, a mean score of 86.00 and the level quality of life, a mean score of 140.20. 2. The level of burden differed according to mother's religion, patient's purpose for admission and perceived patient's condition by mothers. 3. The level of social support and the level of quality of life differed according to perceived patient's condition by mothers. 4. There was a negative correlation between burden and social support(r=-.348, p<.001). Also, burden was negatively related with quality of life(r=-3.97, p<.001). Social support was positively related with quality of life(r=.064, p<.001).

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.21-32
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• 2021

This paper aims to investigate the relationship between country-level institutional quality and public debt in the context of Pakistan. The hypotheses of this study were assessed by using the country-level institutional quality data for Pakistan throughout the years from 1996 to 2018. Data came from the World Databank, IMF and Worldwide Governance Indicators databases. For the analysis, ordinary least square, quantile regression and robust regression were employed to assess the factors influencing the public debt. The results of this study indicate that the factors of voice and accountability, regulatory quality, and control of corruption have a positive and significant relationship with public debt, while political stability, government effectiveness, and the rule of law have a negative and significant effect on public debt. Based on the findings, a weak country-level institutional quality poses a substantial market risk as it signals the existence of an unfavorable economic condition that raises public debt. It was also revealed that an improved performance of country-level institutional quality can lead to the improvement of financial market transparency, hence reduce public debt. In contrast to previous studies, the present study will be breaking ground in enhancing public insight regarding the impact of country-level institutional quality on Pakistan's public debt.

• International Journal of Quality Innovation
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• v.10 no.2
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• pp.97-108
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• 2009

This paper is to develop a quality measure to evaluate the quality level of child care service in the regional level. By utilizing the biannual intensive child care statistical reports, ten variables are integrated and summarized as a quality measure for child care service in regional level by employing Principal Component Analysis (PCA). Conclusively, it is possible to get a comprehensive measure and the measure obtained from data between 2003 and 2008 illustrates the difference in child care service quality among regions over years. With the measure developed by this research, each region can also get very good insight into what kinds of factors of child care service should be paid more attention to in order to improve the quality of its child care service. Moreover, the measure obtained in this paper is proven reliable and robust in that it reflects the quality of child care service in each region and gives us statistically uniform quality scores with a different data set.

• International Journal of Quality Innovation
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• v.8 no.2
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• pp.20-31
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• 2007

Moral hazard and adverse selection often exist in asymmetric information environment. In this paper, quality investment decision problem is studied under moral hazard. A basic model for quality investment level decision is developed with the supplier as a principal and the buyer as an agent. And then we regard the supplier and the buyer's rational limitations to set up a model when the buyer's quality evaluation and processing activities are hidden. The model is optimized and the results under different backgrounds are discussed and compared. Results show that the buyer's quality evaluation level and processing level are mostly influenced by the supplier's quality assurance payment. Both the supplier and the buyer choose different quality investment levels under moral hazard because of the supplier's payment to the buyer in case of internal failure and external failure.