• Journal of Distribution Science
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• v.12 no.7
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• pp.23-35
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• 2014

Purpose - This study aims to explore the effects of social responsibility activities and business ethics practices on corporate trust and loyalty in the context of a large retail distribution business. Research design, data, and methodology - The data collected was analyzed using PASW Statistics 18.0. In order to verify the demographic characteristics, frequency analysis was conducted on the data. Results - The results of the study were as follows. First, social responsibility activities had a significant effect on corporate trust. Second, both corporate social responsibility activities and business ethics practices had significant effects on loyalty. Third, corporate trust had a significant effect on loyalty. Fourth, corporate social responsibility activities and consumer protection activities had a partial mediation effect, while environmental protection activities and social contribution activities had complete mediation effects. Conclusions - This study clarified and explained the factors of corporate social responsibility activities and business ethics practices that customers value, and analyzed the influence of these factors on corporate trust and loyalty.

• Journal of Distribution Science
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• v.21 no.5
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• pp.43-51
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• 2023

Purpose: The current research investigates the beneficial impacts of supply chain innovation and risk management on the competitive advantage of organizations, based on the resource-based theory (RBT) framework. Research Design, Data, and Methodology: 14 survey items were included in the study's questionnaire, utilizing a random sampling technique to gather data from 239 leaders and managers employed by various steel trading firms in Vietnam. In order to validate the data and examine relationships, the collected data is analyzed using structural equation modeling, confirmatory factor analysis, and reliability analysis via SPSS 22.0 and AMOS 22.0 software. A fictitious system has been suggested. Results: According to the findings, the most positive influence on competitive advantage is supply chain innovation, followed by risk management capability, having the second greatest positive influence. Conclusions: Some conclusions are drawn based on the research's findings in order to assist managers in realizing the significance and necessity of giving attention to supply chain innovation and improving risk management capabilities, both of which are essential components for achieving the competitive advantage of an organization.

• Journal of Distribution Science
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• v.19 no.5
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• pp.5-12
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• 2021

Purpose: Research on supply chain sustainability is important for exporters When the factor of sustainable development is considered by the businesses as well as governments of all countries. Research on supply chain sustainability is important for exporters. Sustainable supply chain management and supply chain dynamics will help enterprises adapt to changes in the business environment. This study analyzes the impact of sustainable supply chain management, and supply chain dynamic capabilities on the sustainable development of exporting enterprises in Vietnam. Research design, data, and methodology: The research model and survey are designed based on previous studies after surveying export enterprises. With 185 samples collected from export enterprises. The Structural Equation Modeling (SEM) analysis technique is used. Data analysis is performed on SPSS and AMOS software (Reliability test, Confirmatory Factor Analysis, SEM). Results: Sustainable supply chain management and supply chain dynamic capabilities all have positive effects on the sustainable development of businesses (sustainable development is measured by distribution: measuring economic efficiency, social efficiency, and environmental performance). Conclusions: From the results of this study, the authors also made several recommendations to help export enterprises develop sustainability based on sustainable supply chain management and supply chain dynamic capabilities.

• Journal of the Korea Safety Management & Science
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• v.9 no.3
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• pp.165-171
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• 2007

Dependent models in quality statistics are classified as serially autocorrelated model, multivariate model and dependent sample model. Dependent sample model is most efficient in time and cost to obtain samples among the above models. This paper proposes to implement parametric and nonparametric models into production system depended on demand pattern. Nonparametric models have distribution free and asymptotic distribution free techniques. Quality statistical models are classified into two categories ; the number of dependent sample and the type of data. The type of data consists of nominal, ordinal, interval and ratio data. The number of dependent sample divides into 2 samples and more than 3 samples.

• Journal of Distribution Science
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• v.20 no.10
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• pp.11-17
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• 2022

Purpose: This research aims to find the link between public service Distribution and individual job performance in the provincial municipality. Research design, data, and methodology: This is a quantitative approach study with a non-experimental and correlational design. The sample consisted of 140 employees appointed and hired by the provincial municipality of Huaraz. For data collection, Two questionnaires with an ordinal Likert-type scale and the Rho Spearman correlation coefficient were used to assess the link between the research variables., For Analysis: two questionnaires with an ordinal Likert-type scale and the Rho Spearman correlation coefficient were used to determine the connection between the research variables. Results: It was determined that both variables have a high degree of correlation (0.725), indicating a direct and significant relationship between the Distribution of public service and skill performance in the provincial municipality (0.614). Conclusion: Finally, this allows us to conclude that the institutional context is essential; that is, there is a significant correlation between the PSM and contextual performance in the provincial municipality of Huaraz, which has a Rho Spearman value of 0.723.

• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.4
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• pp.19-29
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• 2019

Recently, with the rise of environmental issues and the change of government policy (Renewable Energy 3020 Implementation Plan), a large amount of renewable energy such as solar and wind power is connected to the power system, and most of the renewable energy is concentrated in the power distribution network. This causes many problems with the voltage management and the protection coordination of the grid due to the its intermittent power generation. In order to effectively operate the distribution network, it is necessary to deploy more intelligent terminal devices in the field to measure the status of the distribution network and develop various operation functions such as visualization and big data analysis to support the power distribution system operators. In addition, the failover technology must be supported for the non-stop operation of the power distribution system. This paper proposes the system architecture of new power distribution management system to cope with high penetration of renewable energy. To verify the proposed system architecture, the functional unit test and performance measurement were performed.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.678-685
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• 2005

Estimating parameters of the lifetime distribution is investigated when field failure data are not completely reported. To take into account the reality and the accuracy of the estimates in such a case, the failure reporting probability is incorporated in estimating parameters. Firstly, method of maximum likelihood estimate(MLE) is used to estimate parameters of the lifetime distribution when failure reporting probability is known. Secondly, Expectation and Maximization(EM) algorithm is used to estimate the failure reporting probability and parameters of the lifetime distribution simultaneously when failure reporting probability is unknown. For both case, procedures of estimation are illustrated for single Weibull distribution and mixed Weibull distribution. Simulation results show that MLE obtained by the proposed method is more accurate than the conventional MLE.

• Journal of Distribution Science
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• v.12 no.11
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• pp.5-13
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• 2014

Purpose - This study traces the determinants of key account management performance in the garments industry in Bangladesh. The key account management approach involves significant challenges for marketers to manage their strategically important customers and use this approach as a strategic weapon in their selling efforts. This study examines three categories of determinants of key account management performance including operational variables, organizational variables, and relational variables by exploring data from 100% export oriented readymade garments companies in Bangladesh. Research design, data, and methodology - Data were collected from 30 readymade garments manufacturers, considering a company as a unit of analysis. Using the data, instrument validity and reliability and, subsequently, data normality were examined using the Statistical Package for the Social Sciences (SPSS) software to isolate the important determinants of key account management performance. Results - The instruments are reliable and the data are reasonably normal. Conclusion - The study explored and validated the adapted instruments of various operational, organizational, and relational antecedent factors of key account management performance, most of which were thus far ignored.

• The Journal of Industrial Distribution & Business
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• v.11 no.12
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• pp.7-15
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• 2020

Purpose: This study aims to explore the feasibility of expanding complex wards to provide efficient hospital management and high-quality medical services to local residents of Gangneung Medical Center (GMC). Research Design, Data and Methodology: There are four research designs to achieve the research objectives. We analyzed Big Data for 3 months on Social Network Services (SNS). A questionnaire survey conducted on 219 patients visiting the GMC. Surveys of 20 employees of the GMC applied. The feasibility to expand the GMC ward measured through Focus Group Interview by 12 internal and external experts. Data analysis methods derived from various surveys applied with data mining technique, frequency analysis, and Importance-Performance Analysis methods, and IBM SPSS statistical package program applied for data processing. Results: In the result of the big data analysis, the GMC's recognition on SNS is high. 95.9% of the residents and 100.0% of the employees required the need for the complex ward extension. In the analysis of expert opinion, in the future functions of GMC, specialized care (△3.3) and public medicine (△1.4) increased significantly. Conclusion: GMC's complex ward extension is an urgent and indispensable project to provide efficient hospital management and service quality.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.5
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• pp.400-405
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• 2013

The purpose of this study is to develop a composite platform for knowledge extractions, visualizations, and inference. Generally, the big data sets were frequently used in the healthcare and medical area. To help the knowledge managers/users working in the field, this study is focused on knowledge management (KM) based on Data Mining (DM), Knowledge Distribution Map (KDM), Decision Tree (DT), RDBMS, and SQL-inference. The proposed mechanism is composed of five key processes. Firstly, in Knowledge Parsing, it extracts logical rules from a big data set by using DM technology. Then it transforms the rules into RDB tables. Secondly, through Knowledge Maintenance, it refines and manages the knowledge to be ready for the computing of knowledge distributions. Thirdly, in Knowledge Distribution process, we can see the knowledge distributions by using the DT mechanism.Fourthly, in Knowledge Hierarchy, the platform shows the hierarchy of the knowledge. Finally, in Inference, it deduce the conclusions by using the given facts and data.This approach presents the advantages of diversity in knowledge representations and inference to improve the quality of computer-based medical diagnosis.