• International Journal of Oral Biology
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• v.42 no.2
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• pp.79-83
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• 2017

Abnormal HLA-G expression occurs in various diseases such as melanoma, renal cell carcinoma, asthma, and classic Hodgkin's lymphoma. The purpose of this study was to determine whether HLA-G gene is linked with oral squamous cell carcinoma (OSCC). To investigate the possible link with susceptibility to OSCC, 54 OSCC patients and 120 healthy controls were enrolled in this study. HLA-G 14bp insertion/deletion polymorphism is in 3'-untranslated region of HLA-G gene. HLA-G 14bp insertion/deletion polymorphism was analyzed using the polymerase chain reaction (PCR) method. For the analysis of genetic data, SPSS18.0 program was used. Logistic regression models were performed for odds ratio (OR), 95 percent confidence interval (CI), and P value. There was a significant difference in distribution allele between OSCC patients and control subjects (OR=0.018, 95% CI=0.002-0.131, p<0.001). Our results suggest that HLA-G 14bp insertion/deletion polymorphism may be linked with susceptibility to OSCC in the Korean population.

• Journal of Korean Society for Quality Management
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• v.44 no.1
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• pp.109-120
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• 2016

Purpose: This study developed a method of determining priorities for evaluating and revising defense standards. Methods: The proposed data integration and refinement methods are used to obtain component reliability information and to determine the frequency of component citation based on Pareto analysis. Based on the reliability information and the frequency of cited components, the target components for quality improvement can be determined and improved using various methods, such as engineering changes, special meetings, additional training, and revising the maintenance manual. Results: Based on the proposed process, we identified components that need to be improved in order to enhance the quality and reliability. Conclusion: Our process will improve the quality and reliability of weapon systems. The proposed process can be adopted for various weapon systems to enhance their quality and reliability, and to reduce military spending.

• International journal of advanced smart convergence
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• v.10 no.4
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• pp.72-83
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• 2021

The use of the predictive analytics (PA) powered by the artificial intelligence (AI) is more important in the movie sector during the COVID-19 pandemic, because Hollywood witnessed the impact of the 'Netflix Effect' and began to invest in data and AI. Our purpose is to discover a few cases of the AI centered PA in the movie industry value chain based on five objectives of PA: Compete, grow, enforce, improve, and satisfy. Even if movie companies' interest is to predict future success for competing with over-the-tops (OTTs) at a first glance, it is observed, once they start to use the PA with the AI, they try to utilize the enhanced PA platforms for remaining four objectives. As a result, ScriptBook, Vault, Pilot, Cinelytic and Merlin Video (Merlin) are use cases for the objective 'compete.' Movio of Vista Group International and Datorama of Salesforce are use cases for the objective 'grow.' Industrial Light & Magic (ILM) and Geena Davis Institute on Gender in Media (GDI) with Disney are use cases for the objective 'enforce.' Watson, Benjamin, and Greenlight Essential are use cases for the objective 'improve.' Disney Research (DR) with Simon Fraser University and California Institute of Technology is the use case for the objective 'satisfy.'

• Journal of Korea Trade
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• v.24 no.5
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• pp.35-54
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• 2020

Purpose - It seems common sense that corporate social responsibility (CSR) is a key driver of business sustainability. Nevertheless, there has been little research on the performance of socially responsible activities, including economic and environmentally responsibility activities, in internationally diversified firms. Design/methodology - The purpose of this study was to evaluate the effects of CSR activities on management performance. For this evaluation, an empirical analysis was conducted with total of 2,520 cases, selected from companies listed on the Korea Composite Stock Price Index market for six years from 2013 to 2018. As proxies for management performance, financial data such as a total asset net profit ratio and a total asset operating ratio were used. A multivariate regression analysis was conducted to test hypotheses. Findings - The results of this analysis indicated that firms in the CSR outstanding group were ranked significantly higher than other groups in management performance. In addition, CSR activities of internationally diversified firms positively influenced the total asset net profit ratio and total asset operating ratio. Originality/value - The results suggest that the CSR activities of these firms can play a significant role in enhancing management performance in the economic status of Korea, where the degree of export dependency is high.

• The Journal of Economics, Marketing and Management
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• v.7 no.4
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• pp.1-5
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• 2019

Purpose - Along with the rapid growth of the economics and IT industry, E-commerce appears as the next potential area of world economics. For this no-entity shops commerce style, logistics is crucial for the success of E-commerce. Research design, data and methodology - In this paper, Dangdang.com, the largest online marketplace in China, is studied and a conceptual model is present, to develop a practical way to develop the logistics system in E-commerce situation. Results - This research finds that following 4 factors are critical success factors for E-commerce logistics: 1) logistics centres are very important to control the inventory management; 2) keep good cooperation with third-party logistics (3PL) can guarantee good quality shipping service and also can reduce delivery costs; 3) build strong information system; 4) quick response system also needed for an efficient logistics system. When E-commerce firms are developing their logistics systems, they should pay more attention to these 4 critical success factors. Conclusions - In summary, successful 3PL management is vital for competing regionally and globally throughout the logistics value chain. We see information system as an enabler in logistics management to get the right products to the right place in the right quantity at the right time and to provide quality services to satisfy the customer's needs.

• Journal of Home Health Care Nursing
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• v.28 no.2
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• pp.111-123
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• 2021

Purpose: This study aimed to present the management strategies necessary to improve the operational efficiency of visiting nurse centers and evaluate their effectiveness. Methods: The subjects of this study were visiting nurse centers registered as long-term care centers. Based on value chain analysis, cost information analysis, and data envelope analysis, the study was carried out according to the Magerison's management consulting procedure, for six months. This procedure comprised eight sub-steps of approach and application. Results: The following management strategies were agreed upon: establishment of a cooperative network with other visiting care centers, creation of high satisfaction of external customers by providing practical training to care workers, and making rehabilitation and exercise services as the core nursing activities to be focused on. Conclusion: The management consulting process and analysis method applied in this study can referred to as a useful methodological framework for revitalizing visiting nursing centers in the future.

• The Journal of Information Systems
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• v.31 no.1
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• pp.25-58
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• 2022

Purpose The purpose of this study is to analyzes the RPA fitting processes by the casese of manufacturing SMEs(Small and Medium-sized Enterprises) in an exploraty approach. Based on the findings on the RPA fitting processes, we intend to provide a cornerstone for developing a general-purpose RPA introduction model in the future. Design/methodology/approach In this study, empirical cases of RPA fitting processes were analyzed based on interviews with project managers of specialized IT suppliers in charge of RPA development and managers of IT departments of manufacturing SMEs that actually introduced RPA. In order to explore various RPA fitting process in the manufacturing value chain, a total of 7 manufacturing SMEs were interviewed, ranging from companies using a legacy system to companies without a legacy system. Over the primary and secondary activity processes, the details of RPA processes were analyzed in the steps of 'Frequency Identification, Input Processing, Source Identification, Inquiry and Processing, Information Registration, Result Reporting'. Findings From the analysis, we derived some exploratory results that the processes over 0.25 FTE and related with many suppliers and clients are fitting for RPA introduction in manufacturing SMEs Our results will provide basic data for the development of the future general-purpose RPA introduction model for manufacturing SMEs, providing practical reference for RPA introduction.

• Asian Journal of Innovation and Policy
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• v.12 no.1
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• pp.054-074
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• 2023

With the advent of the '4th Industrial Revolution', digitalization using AI (Artificial Intelligence), big data, IoT (Internet of Things), cloud computing and mobile is accelerating across all industries and global companies have fundamentally reorganized customer experiences, business models, and operations centering on digital transformation. Business innovation drives productivity improvement, process simplification, price, competitiveness and sustainable expansion. Whether digital transformation will be necessary for the current industrial environment is no longer important, and how quickly companies achieve digitalization has emerged as the utmost crucial element in industrial continuity. As non-face-to-face and remote technologies have begun in earnest, and accelerated in the pharmaceutical industry. They are looking for ways to provide value, generate profits, improve efficiency, and sustain the future. Compared to other industries, the pharmaceutical-related sectors have shown high interest in digital transformation especially to reduce costs and meet the challenge of delivering products during the pandemic environment.

• Journal of Distribution Science
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• v.21 no.9
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• pp.93-102
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• 2023

Purpose: This study attempts to analyze the current status of the railway logistics business and to seek ways to improve it by using the business model as an analytical framework. It was intended to reflect practical implications that could be applied to the field, by dealing with issues at the industrial site related to each component in the business model. Research design, data and methodology: This study was conducted through literature review and field research. We analyzed academic papers and industrial reports on the development of the railway logistics industry and interviewed various stakeholders in the railway logistics industry. Results: This study determined the factors that could be eliminated, raised, reduced, or created from the customer and product perspective, infrastructure management perspective, and financial perspective. Conclusions: The growth of existing business can be achieved by lowering service prices, improving service quality, and securing large-scale transportation capacity. The additional transportation of high value goods and cold chain commodities will be promising business opportunities. Existing services can be provided to new customers (large pre-shippers, forwarding customers, etc.) in order to increase the size of sales Urban delivery services and comprehensive logistics services based on complex logistics centers may open an avenue for new market. A more timetable and track capacity need to be assigned to logistics, which significantly improve the flexibility and the competency of railway logistics.

• Journal of information and communication convergence engineering
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• v.22 no.1
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• pp.44-55
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• 2024

High-utility itemset mining (HUIM) is a dominant technology that enables enterprises to make real-time decisions, including supply chain management, customer segmentation, and business analytics. However, classical support value-driven Apriori solutions are confined and unable to meet real-time enterprise demands, especially for large amounts of input data. This study introduces a groundbreaking model for top-N high utility itemset mining in real-time enterprise applications. Unlike traditional Apriori-based solutions, the proposed convolutional sequential embedding metrics-driven cosine-similarity-based multilayer perception learning model leverages global and contextual features, including semantic attributes, for enhanced top-N recommendations over sequential transactions. The MATLAB-based simulations of the model on diverse datasets, demonstrated an impressive precision (0.5632), mean absolute error (MAE) (0.7610), hit rate (HR)@K (0.5720), and normalized discounted cumulative gain (NDCG)@K (0.4268). The average MAE across different datasets and latent dimensions was 0.608. Additionally, the model achieved remarkable cumulative accuracy and precision of 97.94% and 97.04% in performance, respectively, surpassing existing state-of-the-art models. This affirms the robustness and effectiveness of the proposed model in real-time enterprise scenarios.