• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.1-7
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• 2023

Demand prediction is an essential component of any business or supply chain. Large retailers need to keep track of tens of millions of items flows each day to ensure smooth operations and strong margins. The demand prediction is in the epicenter of this planning tornado. For business processes in retail companies that deal with a variety of products with short shelf life and foodstuffs, forecast accuracy is of the utmost importance due to the shifting demand pattern, which is impacted by an environment of dynamic and fast response. All sectors strive to produce the ideal quantity of goods at the ideal time, but for retailers, this issue is especially crucial as they also need to effectively manage perishable inventories. In light of this, this research aims to show how Machine Learning approaches can help with demand forecasting in retail and future sales predictions. This will be done in two steps. One by using historic data and another by using open data of weather conditions, fuel, Consumer Price Index (CPI), holidays, any specific events in that area etc. Several machine learning algorithms were applied and compared using the r-squared and mean absolute percentage error (MAPE) assessment metrics. The suggested method improves the effectiveness and quality of feature selection while using a small number of well-chosen features to increase demand prediction accuracy. The model is tested with a one-year weekly dataset after being trained with a two-year weekly dataset. The results show that the suggested expanded feature selection approach provides a very good MAPE range, a very respectable and encouraging value for anticipating retail demand in retail systems.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.210-216
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• 2023

Demand prediction is an essential component of any business or supply chain. Large retailers need to keep track of tens of millions of items flows each day to ensure smooth operations and strong margins. The demand prediction is in the epicenter of this planning tornado. For business processes in retail companies that deal with a variety of products with short shelf life and foodstuffs, forecast accuracy is of the utmost importance due to the shifting demand pattern, which is impacted by an environment of dynamic and fast response. All sectors strive to produce the ideal quantity of goods at the ideal time, but for retailers, this issue is especially crucial as they also need to effectively manage perishable inventories. In light of this, this research aims to show how Machine Learning approaches can help with demand forecasting in retail and future sales predictions. This will be done in two steps. One by using historic data and another by using open data of weather conditions, fuel, Consumer Price Index (CPI), holidays, any specific events in that area etc. Several machine learning algorithms were applied and compared using the r-squared and mean absolute percentage error (MAPE) assessment metrics. The suggested method improves the effectiveness and quality of feature selection while using a small number of well-chosen features to increase demand prediction accuracy. The model is tested with a one-year weekly dataset after being trained with a two-year weekly dataset. The results show that the suggested expanded feature selection approach provides a very good MAPE range, a very respectable and encouraging value for anticipating retail demand in retail systems.

• Korea Journal of Hospital Management
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• v.27 no.4
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• pp.36-55
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• 2022

Purpose: This study explores the diffusion factors of corporate entrepreneurship among members of medical institutions. Methodology/Approach: The study explores the case of Granum Sinapis Center at Seoul St. Mary's Hospital, the first medical institution to establish a support organization for "innovation and start-up" as well as examines the changes in individual perceptions of participants in the institution's in-house contest. Among the 140 participants in the 2nd Contest held in 2022, seven participants were selected for interview in consideration of their job occupation and years of service. In-depth interviews were conducted for each individual. Findings: The participants applied for the contest under the direct and indirect influence of co-workers as well as compensatory factors. An individual's corporate entrepreneurial characteristics can be innate or acquired. The participants of the in-house contest had a positive experience in contrast to the existing organizational culture. The results reveal that emotional support from top and middle managers, along with the role of dedicated departments, can affect innovative behavior. Practical Implications: Contest participants reported personal growth, improved job satisfaction, and a change in perception of the organizational culture; they expressed their willingness to recommend. The results confirm the need to support such systems and shift focus to managerial (emotional) support and dedicated resources for developing individual entrepreneurship.

• Journal of Korea Trade
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• v.26 no.3
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• pp.45-62
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• 2022

Purpose - Using unexpected changes in geopolitical tensions on the Korean peninsula as a quasi-natural experimental setting, we examine whether and how geopolitical risks travel across borders through firm-level imports and exports linkages. We also test whether the effects are driven by either imports or exports and assess whether firms can effectively hedge themselves against geopolitical risks. Design/methodology - We focus on a series of unanticipated geopolitical events taken place in Korea in 2018. Making use of the shocks to geopolitical climate, we identify five milestone events toward peace talks. We employ the event studies methodology. We examine heterogenous firm-level stock price reactions around key event dates depending on firms' exposure to geopolitical risks. As a measure of firms' exposure to geopolitical risks in Korea, we utilize a text-based measure of firm-level trade links. When a firm announces and discusses its purchase of inputs from Korea or sales of outputs to Korea in their annual disclosure filings, we define a firm to have a trade relationship with Korea and have exposure to Korean geopolitical risks. Similarly, we use a measure of a firm's hedging policies based on a firm's textual mention of the use of foreign exchange derivatives in their annual disclosure. Findings - We find that U.S. firms that have direct trade links to Korea gained significantly more value when the intensity of geopolitical risks drops compared to firms without such trade links to Korea. The effects are pronounced for firms purchasing inputs from or selling outputs to Korea. We find that the effectiveness of foreign exchange hedging against geopolitical risks is limited. Originality/value - We document the international transmission of geopolitical uncertainty through trade linkages. Export links as well as import links serve as important nexus of transmission of geopolitical risks across borders. Hedging strategies involving foreign-exchanges derivatives do not seem to insulate firms again geopolitical risks. With the recent movements of localization and reshuffling of the global value chain, our results suggest a significant impact of geopolitical risks in Korea on the construction of the global value chain.

• Journal of the Korea Convergence Society
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• v.13 no.1
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• pp.365-373
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• 2022

The purpose of this study is to determine the effect of concurrent appointment as a director on the quality of the internal accounting management system (IACS). For analysis, 9,343 KOSPI & KOSDAQ company-year data from 2014-2019, excluding the financial industry, were used. As a result of the analysis, it was confirmed that the quality of IACS decreased as the number of multiple positions in the director increased. Although there is a difference in the roles of inside and outside directors, it was found that the quality of IACS decreases equally as the number of board members. According to the business hypothesis, this can be said to be the result of the agency problem within the company because directors, who were more busy with concurrent positions as directors, did not put sufficient effort into their work. This study suggests that information on the concurrent position of directors can be a new indicator that reflects the characteristics of the board in evaluating the effectiveness of corporate governance.

• Journal of Digital Convergence
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• v.20 no.3
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• pp.181-189
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• 2022

The purpose of this study is to investigate the innovation of business model and the effectiveness of the data-driven model. the main concepts and policies related to the data economy are reviewed, and implications are drawn through the analysis of data-based convergence service creation cases. This study identified the existing data-driven business model of the creation of MyData service industry in the financial industry and concept of the data economy. According to the empirical analysis result, this study confirmed that t considering the mobile environment and consumer acceptance of data portability, the ripple effect of the implementation of My Data on the financial industry is expected to be significant.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.5
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• pp.273-283
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• 2022

Banking and finance is a broad term that incorporates a variety of smaller, more specialized subjects such as corporate finance, tax finance, and insurance finance. A virtual assistant that assists users in searching for information about banking and finance terms might be an extremely beneficial tool for users. In this study, we explored the process of searching for information, seeking opportunities, and developing a virtual assistant in the first stages of starting learning and understanding Vietnamese to increase effectiveness and save time, which is also an innovative business practice in Use-case Vietnam. We built the FIBA2020 dataset and proposed a pipeline that used Natural Language Processing (NLP) inclusive of Natural Language Understanding (NLU) algorithms to build chatbot applications. The open-source framework RASA is used to implement the system in our study. We aim to improve our model performance by replacing parts of RASA's default tokenizers with Vietnamese tokenizers and experimenting with various language models. The best accuracy we achieved is 86.48% and 70.04% in the ideal condition and worst condition, respectively. Finally, we put our findings into practice by creating an Android virtual assistant application using the model trained using Whitespace tokenizer and the pre-trained language m-BERT.

• The Journal of the Korea Contents Association
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• v.22 no.5
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• pp.155-164
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• 2022

The purpose of this study is to understand the brand effectiveness of the small enterprise succession policy. small enterprise have a close relationship with consumers, it is necessary to examine the consumer effects of authentication policies. Therefore, the policy itself was identified as a brand, and the influence between brand image, attitude, and loyalty was attempted. As a result of the study, it was found that the brand image of the two factors of the policy had a positive effect on attitude and loyalty. Based on the research results, the necessity of evaluating policies from a business perspective was suggested. Above all, it will be meaningful in applying the concept of a brand to the policies used by consumers and examining the effects.

• Journal of Fashion Business
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• v.26 no.2
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• pp.129-142
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• 2022

The purpose of this study is to develop socks to check the range of ankle movement during squats for men in their late 20s. Sensors of 6, 8, and 12 mm were selected, and each sample was impregnated 1 to 3 times. It was prepared using a CNT dispersion, and the GF value was measured using UTM. Among them, the sample with 2 impregnation showed the best GF value. As a result of applying each sample to the socks, the 12 mm sensor was wider than the area of the Achilles tendon, resulting in noise, and the 8 mm sensor was higher than the tensile strength of the socks, resulting in a decrease in the graph. Therefore, testing was performed using a 6 mm sensor. In order to determine the effectiveness of the sensor, the normal operating range was checked through squats, and significant changes were confirmed when the operating range was checked again through squats by performing operations that can increase the operating range through Gastrocnemius, Soleus stretching, and low lunge. Using the results of this study, it is expected that the average value of the ankle movement range of the user is checked prevent injury, to be provided as basic data for the production of shoe products and the promotion of physical health.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.201-206
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• 2020

Diversification of project delivery methods (PDM) under ever-changing construction business environment has significantly changed the role of project participants. Active efforts to effectively sharing the roles and responsibilities have been observed in the project management offices (PMOs) among owner/operator organizations as well as engineering, procurement, construction and maintenance (EPCM) firms. In order for being effective in a holistic way throughout the project life-cycle, a PMO needs to have 'adequate management skills' as well as 'essential technical capabilities' in cooperating with many different participants. One of the well-known examples of the PMO's tool to support these skills and capabilities is the effective 'work packaging (WP)' that serves as a common basis integrating all relevant information in a structured manner. In an attempt to enhance the construction productivity, the concept of 'advanced work packing (AWP)' has been introduced by Construction Industry Institute (CII). The AWP enables productivity to be improved by early planning of construction packages in the design phase "with the end in mind". The purpose of this study is to identify and evaluate the 'variables' of advanced work packing (AWP) for life-cycle information integration. Firstly, an extended concept of advanced WP based on the CII AWP was defined in order to comprehend many different issues of business functions (e.g. cost, schedule, quality, etc.). A structured list of major components and variables of AWP were then identified and examined for practical viability with real-world examples. Strategic fits and managerial effectiveness were stressed throughout the analyses. Findings, implications and lessons learned are briefly discussed as well.