• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.140-141
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• 2017

Big data analysis, in the large amount of data stored as the data warehouse which it refers the process of discovering meaningful new correlations, patterns, trends and creating new values. Thus, Big data analysis is an effective analysis of various big data that exist all over the world such as social big data, machine to machine (M2M) sensor data, and corporate customer relationship management data. In the big data era, it has become more important to effectively analyze not only structured data that is well organized in the database, but also unstructured big data such as the internet, social network services, and explosively generated web documents, e-mails, and social data in mobile environments. By the way, a meta analysis refers to a statistical literature synthesis method from the quantitative results of many known empirical studies. We reviewed a total of 750 samples among 50 studies published on the topic related as IDT between 2000 and 2017 in Korea.

• Journal of Korean Society of Rural Planning
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• v.22 no.2
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• pp.153-164
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• 2016

Developed countries in agriculture like Netherlands, Belgium and England, have managed Green Care policy and project during the last decades. The needs in Green Care is also increasing as new growth power in rural area of Korea. This study investigated sites which are already operating as complex with Green Care theme. This study surveyed the operating conditions like type, scale, location pattern, purpose, customer and finance for cases of the complex. The period of the survey is from 2015. 8. 11 to 2015. 09. 10 for the 24 activated cases in aspect of operation and management. Among the 24 cases, 16 cases were classified as Green Care Complex which facilities are aggregated a place, and the other 8 cases as Green Care Cluster which are distributed at several places. The analysis result showed that there were apparent distinction among cases in total budget, costs of construction, capacity for guest, and the total number of annual visitors. Despite of the type and scale the accommodation cost, the number of workers, and amount of sales have small deviation in distribution of values, although the cases have various type of contents and scale of space. The result of this study can be used as data of bench marking to develop the Green Care Complex or Cluster in rural area.

• Journal of Korea Trade
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• v.25 no.7
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• pp.75-91
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• 2021

Purpose - Social commerce (SC) is the growth of social media highlighting the e-commerce transactions and currently, the greatest challenges of e-commerce have attracted the influence of trust in social commerce intention (SCI). Based on the challenge, the study's purpose is to discover the effect of social support (informational and emotional support) on the SCI. The study also explores the mediation effect of trust and the moderation impact of culture between the USA and Korea. Design/methodology - This study used a sample of 482 surveys filled out by online shoppers from the US and Korea, two countries with divergent cultural values. Structural equation modelling (SEM) is used to analyze the hypothetical paths. In addition, bootstrapping and multi-group analysis are perform to view mediation and moderation effects respectively. Findings - The results of our study shows that both informational and emotional support significantly influences trust and SCI. Our results also supports the mediating effect of trust in social support and the moderating effect of culture in forming SCI. Originality/value - Our empirical results provide important information to businesses formulating cross-cultural SC strategies. This will help SC companies to analyze the aspects of customer trust through social support, which in turn will increase SCI and thereby established a competitive position for SCs. Our results will also be holistic directions for SC vendors in cross-cultural settings, which will offer important social and economic contributions to the sustainable growth of SC's business.

• Journal of Korean society of Dental Hygiene
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• v.19 no.5
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• pp.813-824
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• 2019

Objectives: The purpose of this study was to investigate the effects of emotional labor, organizational climate, and job involvement on turnover intention in Korean dental hygienists. Methods: A total of 806 dental hygienists were enrolled in this study. A self-administered questionnaire was used to evaluate the demographic and occupational characteristics, emotional labor, organizational climate, job involvement, and turnover intention of the subjects. A hierarchical multiple regression analysis was performed. All statistical analyses were performed using the Statistical Package for the Social Sciences for Windows (version 23.0) and p-values < 0.05 were considered significant. Results: Highly chronic exposure to emotional labor were more likely to increase the risk of turnover intention among dental hygienists, especially in the sub-scales of "over-load and conflict in customer service" (OR: 1.64; CI: 1.01-2.64), "organizational surveillance and monitoring" (OR: 1.76; 95% CI: 1.21-2.57), and "lack of a supportive and protective system in the organization" (OR: 1.76; 95% CI: 1.36-2.46). Job involvement (OR: 0.91; 95% CI: 0.86-0.96) and organizational climate (OR: 0.82; 95% CI: 0.75-0.90) were negatively associated with turnover intention among dental hygienists. Conclusions: Exposure to chronic and excessive emotional labor might be a contributing factor for turnover intention, and job involvement and a positive organizational climate contribute to protecting the negative impacts of emotional labor on turnover intention in dental hygienists.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.4
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• pp.15-22
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• 2020

Economic indicators are a factor that affects air cargo volume. This study analyzes the different factors affecting air cargo volume by each Chinese cities according to the main characteristics. The purpose of this study is to help companies related to China, airlines, and other stakeholders predict and prepare for the fluctuations in air cargo volume and make optimal decisions. To this end, 20 economic data were used, and the entire data was reduced to 5 dimensions through factor analysis to build a dataset necessary and evaluated the influencing factors by multi regression. The result shows that Macro-Economic Indicators, Production/Service indicators are significant for every cities and Chinese manufacture/Customer indicators, Korean manufacture/Oil Price indicators, Trade/Current indicators are significant for each other city. All adjusted R2 values are high enough to explain our model and the result showed excellent performance in terms of analyzing the different factors which affects air cargo volume. If companies that are currently doing business with China can identify factors affecting China's cargo volume, they can be flexible in response to changes in plans such as plans to enter China, production plans and inventory management, and marketing strategies, which can be of great help in terms of corporate operations.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.7
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• pp.827-833
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• 2020

In this paper, to reduce the unpaid rate of local governments, the internal data elements affecting the arrears in Water-INFOS are searched through interviews with meter readers in certain local governments. Candidate data affecting arrears from national statistical data were derived. The influence of the independent variable on the dependent variable was sampled by examining the disorder of the dependent variable in the data set called information gain. We also evaluated the higher prediction rates of decision tree and logistic regression using n-fold cross-validation. The results confirmed that the decision tree can find more accurate customer payment patterns than logistic regression. In the process of developing an analysis algorithm model using machine learning, the optimal values of two environmental variables, the minimum number of data and the maximum purity, which directly affect the complexity and accuracy of the decision tree, are derived to improve the accuracy of the algorithm.

• Fashion & Textile Research Journal
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• v.24 no.1
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• pp.117-126
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• 2022

This study aims to analyze the sizing information of women's ready-to-wear pants as indicated on online retail websites and to suggest better sizing communication that can assist customers in making successful apparel size selections. We gathered size specifications and size reference information for basic straight pants from 34 online apparel retail websites. Although the Korean standard recommends labeling the body dimension-based sizing code and specification, most websites preferred to use various types of sizing codes. Body measurements were only used by a few websites, and garment dimension descriptions were the most common method to indicate product size. Many websites provided size reference information through customer review boards and fit model images, however, there was insufficient body size information to allow customers to infer the fit of their body type. When using the size guidance tools, the major data input points were stature and weight measurements. However, the waist measurements of pants sizes guided only by stature and weight values revealed inconsistent ease allowance for corresponding body size populations, especially in the overweight group. Based on our findings, we propose a more effective method of communicating the size information of pants online. We expect that this will contribute to the efficiency of online apparel product display and build a better shopping environment that satisfies both sellers and consumers.

• Journal of the Korea Society of Computer and Information
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• v.14 no.4
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• pp.179-187
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• 2009

Most real world systems contain a series of dynamic and complex phenomena. One of common methods to understand these systems is to build a model and analyze the behavior of them. A two-step methodology comprised of clustering and then model creation is proposed for the analysis on time series data. An interface is designed for CRM(Customer Relationship Management) that provides user with 1:1 customized information using system modeling. It was confirmed from experiments that better clustering would be derived from model based approach than similarity based one. Clustering is followed by model creation over the clustered groups, by which future direction of time series data movement could be predicted. The effectiveness of the method was validated by checking how similarly predicted values from the models move together with real data such as stock prices.

• The Journal of Society for e-Business Studies
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• v.27 no.2
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• pp.137-152
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• 2022

Consumers' enhanced intention to adopt the Mydata service or their voluntary provision of personal information is a very essential element in the stable growth of the Mydata industry along with the creation of corporate values. The growing leakage of customer information according to the rising value of data can have negative impacts on the use of Mydata service and shrink quality custom service needs based on the personal information provided by financial consumers. This study set out to identify security risks that financial consumers could recognize and security factors that could supplement them and investigate the effects of these security factors on consumers' intention to adopt the Mydata service, thus providing useful implications for increasing the acceptance of financial consumers and finding a strategy to expand safe utilization. The findings raise a need to guarantee the stability and transparency of information provided by customers as information subjects, and they should be essential requirements for the Mydata service. The security factors applied to guarantee them should include convenience in terms of financial service.

• Journal of Korean Society for Quality Management
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• v.50 no.1
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• pp.153-167
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• 2022

Purpose: The purpose of this study is to guide the operation managers who plan daily production of large mass-processing facility that services multi-customers with multi-product, small-batch item characteristics by providing the practical best production quantity and the inventory allowed to build. Methods: Close observation of a subcontract paint-shop operator captured the daily decision process which was reflected in the subcontractor-unique mathematical model and the system dynamics simulation model. Multiple simulations were run to find the practical best production quantity and the maximum allowable stock level of inventory that did not undermine the profit from practical best daily production. Actual data and a few constant values were obtained from the firm under study. Results: While the inventory holding cost for the customer-owned material harms the total profit of the subcontractor, the running cost of the processing facility hinders production in small batches. This balances the maximum possible productions and results in practical best daily production which can be found through simulation runs with actual data. The maximum level of stocked inventory is deduced from the practical best daily production. Conclusion: To build a large volume that enables economy-of-scale production, operators should deal with multi-product small-batch items from multiple customers. When the planned schedule of the time and amount of material in-flow tend not to be reliable, operators can find it practical to execute level production across the planning horizon instead of adjusting to day-to-day in-flow fluctuations.