• Asian Journal of Innovation and Policy
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• v.10 no.3
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• pp.380-403
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• 2021

Recently, smart factories have gained significant importance since the development of the fourth industrial revolution and the rise of global industrial competition. Therefore, the industries' survival to meet the global market trends requires accurate technological planning. Although, different works are available to investigate forecasting technologies and their influence on the smart factory. However, little significant work is available yet on the analysis of technological trends concerning the smart factory, which is the core focus herein. This work was performed to analyze the technological trends of the smart factory, followed by a detailed investigation of recent research hotspots/frontiers in the field. A well-known topic modeling technique, namely Latent Dirichlet Allocation (LDA), was employed for this study described above. The technological trends were further strengthened with the in-depth analysis of a smart factory-based case study. The findings produced the technological trends which possess significant potential in determining the technological strategies. Moreover, the results of this work may be helpful for researchers and enterprises in forecasting and planning future technological evolution.

• Journal of Information Technology Applications and Management
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• v.31 no.3
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• pp.93-104
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• 2024

This study conducts an in-depth analysis of user reviews from three leading metaverse platforms - Minecraft, Roblox, and Zepeto - using advanced topic modeling techniques to uncover key factors for business success. By examining a substantial dataset of user feedback, we identified and categorized the main themes and concerns expressed by users. Our analysis revealed that common issues across all platforms include technical functionality problems, user engagement and interest, payment concerns, and connection difficulties. Specifically, Minecraft users highlighted the importance of adventure and creativity, Roblox users expressed significant concerns about security and fraud, and Zepeto users focused heavily on the fairness of the in-game economy. The findings suggest that for metaverse platforms to achieve sustained success, they must prioritize the resolution of technical issues, enhance features that foster user engagement, ensure reliable connectivity, and address platform-specific concerns such as security for Roblox and payment fairness for Zepeto. These insights provide valuable guidance for developers and business strategists, emphasizing the need for robust technical infrastructure, engaging and diverse content, seamless user access, and transparent and fair economic systems. By addressing these key areas, metaverse platforms can improve user satisfaction, build a loyal user base, and secure long-term success in an increasingly competitive market.

• Korean System Dynamics Review
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• v.8 no.1
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• pp.187-209
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• 2007

This paper deals with the policy failure in housing markets. In order to understand basic mechanism leading to policy failure, systems thinking and system dynamics modeling is applied to housing markets and housing policy. This paper will show different set of causal maps on housing policy, and compare causal reasons of housing policy and its critics.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2001.10a
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• pp.246-249
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• 2001

In this study we propose a technology selection model, which captures technology seeds for new business area by a fuzzy structural modeling method and then, design a model, which evaluates the validity of New Business Development plans for the selected technology seeds with regard to the properties of manufacturing, product, market, and economy as well. Finally, a fuzzy inference system is designed in order to decide the degree of success of New Business Development plans based on the preceding validity evaluation.

• Knowledge Management Research
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• v.14 no.3
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• pp.1-13
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• 2013

This study investigates how relational activities within MNC network affect knowledge transfer and performance of subsidiary. We separated the possible relationships between headquarter and overseas subsidiaries by support level, interaction level, and conflict level, and compared the impact on knowledge transfer, and performance. To understand the knowledge sharing, development and performance, we use structural equation modeling to analyze data from subsidiaries in China.

• Journal of Broadcast Engineering
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• v.10 no.2
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• pp.156-165
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• 2005

This paper presents a new auto brighoess control algorithm fur adaptive background subtraction. The algorithm is designed to cope with the problem of auto-brightness adjustment feature of consumer-type cameras. The experimental results show the proposed method improves performance of the classification. This will be beneficial to many computer vision applications in term of reducing the cost of implementation and making them more available to the mass consumer market.

• Korean Journal of Construction Engineering and Management
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• v.13 no.6
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• pp.153-164
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• 2012

Since the sub-prime mortgage crisis from the US in 2008, Korean housing market has plummeted. However, Korean local lease contract, Chonsei, price has been increasing. This increase of Chonsei price can be a threat to the low-income people because most of them prefer to live at the house with a Chonsei contract. In order to solve this problem, the Korean Government implemented several Chonsei policies to secure low-incomers' residence by decreasing the price of Chonsei; however, due to the lack of understanding on housing and Chonsei market, Korean government policy seemed to fail on getting effective results. In the housing and Chonsei market, there are many stakeholders with their own interest, hence, simple thoughts about housing and Chonsei market, such as more house supply will decrease house price, would not work in a real complex housing market. In this research, we suggests system dynamics conceptual model which consists of causal-loop-diagrams for the Chonsei market as well as the housing market. In addition, we tries to explain why the policy did not work effectively using the examples from the government's past measures. In results, Chonsei price has its own homeostasis characteristic and different price movement with housing price in the short and long term period. Unless government does not have a structural causation mind in implementing policies in the real estate market, the government may not attain intended effectiveness on both markets.

• Journal of Environmental Policy
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• v.14 no.4
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• pp.23-44
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• 2015

The policy aimed at introducing a Bonus-Malus system to reduce GHG and raise the market share of small cars is scheduled to go into effect in South Korea in 2020. Although the policy was originally planned to be enforced from 2015, the Ministry of Trade, Industry and Energy argued that the system brings low reduction effect and relative disadvantage to domestic small cars and brought arguments in 2014. As a result, the enforcement was pushed back. Related studies are mainly focused on offering statistical estimation of the policy's effect to support the arguments, and few theoretical studies were published given that there was not enough time until 2015 back then. The author approached the issue with mathematical modeling in order to give theoretical basis for sophisticated empirical studies. If car suppliers have market power and strategically set their prices, the impact of Bouns-Malus on car prices would be lower than what was originally intended. In case only a part of the car market loses its market power, the effect of the policy would be improved. Assume that the Bonus-Malus is currently at an optimal level and the car market structure is undergoing changes, then the direction of the new optimal level would depend on the elasticity of demand of each market and substitute elasticity. For example, if the car market becomes more monopolistic while the demand for big cars is elastic, demand for small cars is inelastic and substitution elasticity is low, then the new optimal level of Bonus-Malus should be higher.

• The Journal of the Korea Contents Association
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• v.16 no.6
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• pp.726-738
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• 2016

This paper aims to examine structural relationship between the influence factors of customer loyalty, hypothesizing that m-CRM characteristics, market orientations, relationship quality and relationship length plays a crucial role in achieving customer loyalty in insurance companies. Total of 255 valid sample data were used to test study hypotheses. By using Structure Equation Modeling(SEM) method, the results show that m-CRM characteristics and customer orientation significantly influence to relationship quality except competitor orientation and all relationship quality are very significantly influence to customer loyalty being consisted of customer retention and word of mouth effect. In addition, the modulation effect of relationship length is confirmed about relationship between relationship quality and customer loyalty. A real situation we conducted our research may enable academics and practitioners to understand the antecedents and outcomes of m-CRM implementation in terms of market orientation.

• The Journal of the Korea Contents Association
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• v.12 no.2
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• pp.461-471
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• 2012

The purpose of this paper is to visualize the housing market dynamics with ESDA (Exploratory Spatial Data Analysis) using MATLAB toolbox, in terms of the modeling housing market dynamics in the Busan Metropolitan City. The data are used the real housing price transaction records in Busan from the first quarter of 2006 to the second quarter of 2009. Hedonic house price model, which is not reflecting spatial autocorrelation, has been a powerful tool in understanding housing market dynamics in urban housing economics. This study considers spatial autocorrelation in order to improve the traditional hedonic model which is based on OLS(Ordinary Least Squares) method. The study is, also, investigated the comparison in terms of $R^2$, Sigma Square(${\sigma}^2$), Likelihood(LR) among spatial econometrics models such as SAR(Spatial Autoregressive Models), SEM(Spatial Errors Models), and SAC(General Spatial Models). The major finding of the study is that the SAR, SEM, SAC are far better than the traditional OLS model, considering the various indicators. In addition, the SEM and the SAC are superior to the SAR.