• Journal of the Korean Society of Clothing and Textiles
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• v.28 no.1
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• pp.12-21
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• 2004

The purposes of this research were (1) to identify service quality and apparel quality in apparel stores, (2) to examine the influence of service quality, product quality and price on customer satisfaction, (3) to examine the influence of service quality, product quality, price and customer satisfaction on repurchase intention that is important feature of store patronage. The data was collected from 435 female students, career women, and house wives using questionnaire and analyzed by frequency analysis, factor analysis, reliability analysis and regression. The results of this research were as follows: (1) Service quality in apparel stores was divided into six factors: facilities and policy/ salesperson VMD/ after service/ impression and atmosphere/ promotion. (2) Product quality was divided into four factors: objective feature/ expressive feature/ wearing sensation/ fitness. (3) Service quality, product quality, price influenced customer satisfaction. (4) Product quality, price and customer satisfaction influenced repurchase intention directly, but service quality influenced repurchase intention indirectly. (5) Service quality factors that influenced customer to have repurchase intention were facilities and policy, salesperson, and VMD. (6) Product quality factors that influenced customer to have repurchase intention were objective feature and wearing sensation.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.3
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• pp.101-111
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• 2020

Companies struggle to make their best products with high quality and service at a competitive price in global markets. However, customer needs and requirements keep changing with a variety of situations. Companies that face the changes can not stay the same and make an effort to adapt themselves to new circumstances. They would probably review the overall management system that is currently implementing to improve management efficiency. Among other things, quality might be considered to be a crucial element if they are manufacturing industries to be sustained in global markets. KSA (Korean Standards Association) is a government-affiliated organization under the Ministry of Trade, Infrastructure, and Energy. It is a Korean standards provider for quality and service industry. KSA confers national commendations for organizations, quality circles, artisans, QCEC (Quality Competitive Excellent Company), and the most honorable KNQA (Korean National Quality Award) every year. KSA established KNQA on the basis of Malcom Baldrige National Quality Award, Deming Prize, and European Quality Award. Research on quality awards shows that there are many similarities in the framework. Although KSA summarizes two factors for 13 evaluation indicators in the quality competitive excellent model of QCEC, the categorization is ambiguous to explain them according to earlier studies. We performed a deep analysis of foreign quality awards and background for KNQA and QCEC. We conducted a content analysis of KNQA and QCEC and matched evaluation items that were closely related. We proposed a quality competitiveness model with three factors, Technology, System, and Tools, summarizing 13 evaluation indicators in QCEC. Based on audit data for six years from 2012 to 2017 we carried out a confirmatory factor analysis for the proposed model by examining the model validity and fitness.

• Environmental Engineering Research
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• v.19 no.3
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• pp.197-203
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• 2014

This study estimated spatial and seasonal variation of water quality to understand characteristics of Nakdong river basin, Korea. All together 11 parameters (discharge, water temperature, dissolved oxygen, 5-day biochemical oxygen demand, chemical oxygen demand, pH, suspended solids, electrical conductivity, total nitrogen, total phosphorus, and total organic carbon) at 22 different sites for the period of 2003-2011 were analyzed using multivariate statistical techniques (cluster analysis, principal component analysis and factor analysis). Hierarchical cluster analysis grouped whole river basin into three zones, i.e., relatively less polluted (LP), medium polluted (MP) and highly polluted (HP) based on similarity of water quality characteristics. The results of factor analysis/principal component analysis explained up to 83.0%, 81.7% and 82.7% of total variance in water quality data of LP, MP, and HP zones, respectively. The rotated components of PCA obtained from factor analysis indicate that the parameters responsible for water quality variations were mainly related to discharge and total pollution loads (non-point pollution source) in LP, MP and HP areas; organic and nutrient pollution in LP and HP zones; and temperature, DO and TN in LP zone. This study demonstrates the usefulness of multivariate statistical techniques for analysis and interpretation of multi-parameter, multi-location and multi-year data sets.

• Atmosphere
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• v.24 no.1
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• pp.77-87
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• 2014

The radar reflectivity is significantly affected by ground clutter, beam blockage, anomalous propagation (AP), birds, insects, chaff, etc. The quality of radar reflectivity is very important in quantitative precipitation estimation. Therefore, Weather Radar Center (WRC) of Korea Meteorological Administration (KMA) employed two quality control algorithms: 1) Open Radar Product Generator (ORPG) and 2) fuzzy quality control algorithm to improve quality of radar reflectivity. In this study, an occurrence of AP echoes and the performance of both quality control algorithms are investigated. Consequently, AP echoes frequently occur during the spring and fall seasons. Moreover, while the ORPG QC algorithm has the merit of removing non-precipitation echoes, such as AP echoes, it also removes weak rain echoes and snow echoes. In contrast, the fuzzy QC algorithm has the advantage of preserving snow echoes and weak rain echoes, but it eliminates the partial area of the contaminated echo, including the AP echoes.

• The Journal of Information Systems
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• v.26 no.4
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• pp.419-442
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• 2017

Purpose The purpose of this study is to explore the pattern of user response and it's duration time through social media content response analysis. We also analyze the characteristics of content quality factors which are associate with the user response pattern. The analysis results will provide some implications to develop strategies and schematic plans for the operator of regional marketing on the SNS. Design/methodology/approach This study used mixed methods to verify the effects and responses of social media contents on the users who have concerns about regional events such as local festival, cultural events, and city tours etc. Big data analysis was conducted with the quantitative data from regional government SNSs. The data was collected through web crawling in order to analyze the social media contents. We especially analyzed the contents duration time and peak level time. This study also analyzed the characteristics of contents quality factors using expert evaluation data on the social media contents. Finally, we verify the relationship between the contents quality factors and user response types by cross correlation analysis. Findings According to the big data analysis, we could find some content life cycle which can be explained through empirical distribution with peak time pattern and left skewed long tail. The user response patterns are dependent on time and contents quality. In addition, this study confirms that the level of quality of social media content is closely relate to user interaction and response pattern. As a result of the contents response pattern analysis, it is necessary to develop high quality contents design strategy and content posting and propagation tactics. The SNS operators need to develop high quality contents using rich-media technology and active response contents that induce opinion leader on the SNS.

• Quality Improvement in Health Care
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• v.8 no.2
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• pp.186-207
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• 2001

Background : This study presented an analysis of healthcare quality indicators using data mining and a development of decision support system for quality improvement. Method : Specifically, important factors influencing the key quality indicators were identified using a decision tree method for data mining based on 8,405 patients who discharged from a medical center during the period between December 1, 2000 and January 31, 2001. In addition, a decision support system was developed to analyze and monitor trends of these quality indicators using a Visual Basic 6.0. Guidelines and tutorial for quality improvement activities were also included in the system. Result : Among 12 selected quality indicators, decision tree analysis was performed for 3 indicators ; unscheduled readmission due to the same or related condition, unscheduled return to intensive care unit, and inpatient mortality which have a volume bigger than 100 cases during the period. The optimum range of target group in healthcare quality indicators were identified from the gain chart. Important influencing factors for these 3 indicators were: diagnosis, attribute of the disease, and age of the patient in unscheduled returns to ICU group ; and length of stay, diagnosis, and belonging department in inpatient mortality group. Conclusion : We developed a decision support system through analysis of healthcare quality indicators and data mining technique which can be effectively implemented for utilization review and quality management in a healthcare organization. In the future, further number of quality indicators should be developed to effectively support a hospital-wide Continuous Quality Improvement activity. Through these endevours, a decision support system can be developed and the newly developed decision support system should be well integrated with the hospital Order Communication System to support concurrent review, utilization review, quality and risk management.

• Journal of the Korean Society of Costume
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• v.55 no.2 s.92
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• pp.105-115
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• 2005

The purposes of this study were to identify the service quality, quality of relationship, and relationship continuity intention of rental clothing store. Questionnaires developed by researcher were collected from 212 consumers who experienced rental clothing. Data was analysed by use of factor analysis, path analysis, and covariance structure analysis. The results were; 1. Factors of service quality of clothing rental store were tangibility & promotion, shop assistant & store atmosphere, customer empathy, customer reliability strategy, customer management, and customer convenience. And factors of relationship quality were satisfaction, trust, emotional involvement, and calculational involvement, and factors of relationship continuity intention were longitudinal relationship propensity & word-of-mouth and rerental intention. 2. Service quality of rental store affected significantly on relationship quality, and relationship quality affected significantly on relationship continuity intention. And service qualify of rental store affected significantly on relationship continuity intention through relationship qualify.

• Journal of the Korean Society of Costume
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• v.52 no.5
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• pp.187-196
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• 2002

The purpose of this study was to clarify differences in their perceptions in relation to clothing quality and service quality of internet shopping mall according to classified consumer groups by clothing involvement. The 248 questionnaires were collected from female and male students of university who experienced browsing at the website for clothing shopping. Using SPSS Win package, Cronbach's $\alpha$, frequency. percentage, factor analysis, cluster analysis, ANOVA, SNK multiple range test and multiple regression analysis were performed. The results could be summarized as follows. First. the dimension of clothing involvement divided consumers into three different groups: fashion/importance group, pleasure group and symbol group. Second, the significant differences among the classified clothing involvement groups were found in the perceptions in relation to clothing product quality and service quality of internet shopping mall. Third. pleasure and symbol of clothing involvement, physical attributes and expressive goals of clothing quality, and product assortment and promotion of service quality in the internet shopping mall had an effect on the purchase intend of internet shopping mall.

• 한국경영정보학회:학술대회논문집
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• 2007.06a
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• pp.851-856
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• 2007

Continuously monitoring and improving information system (IS) performance is a major concern in organizations. Thanks to invisible characteristics of IS performance, this is still enduring research question. The purpose of this study is to examine and analyze factors influencing IS Performance in public sector. Influencing factors of IS performance include IS quality such as System Quality, Information Quality and IS Use. The data for analysis was collected from local official in Korea. We used PLS 3.00 Version for an analysis. Analysis revealed that Information Quality has directly influenced IS Use. But there were not Significant in relations between System Quality and IS Performance, System Quality and IS Use, System Quality and IS Performance, and IS Use and IS Performance.

• International Journal of Contents
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• v.18 no.3
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• pp.34-48
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• 2022

The purpose of this study was to develop indicators for quality management of educational institutions, and to achieve this, literature analysis and expert interviews were conducted. Through literature analysis, the components of TQM were derived focusing on factors to improve the quality of education, engineering education accreditation standards, and a representative education accreditation system, were considered. Additionally, seven areas as well as 32 indicators required for education quality management, were derived by comparing the EFQM excellence model and the MBNQA education model, applied for quality management of companies and institutions. By comparing and synthesizing these results, a draft was developed for the quality management index of educational institution. Next, opinions on correction and supplementation of quality management indicators derived from literature analysis, were collected from five education experts. From the comparisons and integration of these results, eight criteria (leadership, strategy, customers, people, facilities and environment, curriculum management, curriculum improvement, and performance management) and 34 indicators, were proposed for quality management indicators for educational institutions. Curriculum management, people, and performance management criteria were considered more significantly in quality management of educational institutions, and several implications are suggested based on the study results.