• Journal of Korea Society of Industrial Information Systems
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• v.15 no.1
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• pp.59-72
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• 2010

Competition among enterprises has been more intensified as one among supply chains in the rapidly changing environment. This study investigated the influence of the supply chain integration factors, such as integration of functions inside an enterprise, integration of suppliers, and integration of customers, on the internal and external visibility, and non-financial and financial performances of enterprises. To test these relationships, the survey was conducted on suppliers, manufacturers, and distributors in Korea which have been implementing SCM. Eighty-one questionnaires were collected and used for this study. The study results using the covariance structure analysis are showed as follows. First, the integration of suppliers had a significant influence on both the internal and the external visibility of enterprises, while the integration of functions inside an enterprise had a significant impact on only the internal visibility of enterprises, and the integration of customers on only the external visibility. Second, the internal and external visibility of enterprises had significant impacts on non-financial performance of enterprises. However, the internal and external visibility of enterprises didn't give any direct or indirect influence on the financial performance of enterprises. Third, the non-financial performance of enterprises had a significant impact on financial performance of enterprises.

• Journal of Korea Society of Industrial Information Systems
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• v.14 no.1
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• pp.1-8
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• 2009

The objective of this study is to design a system that automatically monitors the state of interior spaces like offices where lots of people are coming and going through image data and environment data, which includes temperature, humidity, and other conditions, and implement and test related application programs. In practice, there are lots of image data automatically obtained by unmanned equipments, such as certain types of CCTVs, for monitoring situation in usual interior spaces. This image data can be used as a more effective manner by establishing a system that recognizes situation in specific interior spaces based on the relationship between image and environment data. For instance, it is possible to perform unmanned on/off controls for various electronic equipments, such as air conditioners, lights, and other devices, through analyzing the data acquisited from environment sensors (temperature, humidity, and illumination) as dynamic states are not maintained for a specified period of time. For implementing these controls, this study analyzes environment data acquisited from temperature and humidity sensors and image data input from wireless cameras to recognize situation and that can be used to automatically control environment variables configured by users. Experiments were applied in a laboratory where unmanned controls were effectively performed as automatic on/off controls for the air conditioner and lights installed in the laboratory as certain motions were detected or undetected for a specified period of time.

• Journal of Korea Society of Industrial Information Systems
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• v.14 no.4
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• pp.163-182
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• 2009

The BSC(Balanced Scorecard), a strategic performance evaluation system, has drawn attention as an innovative tool for improving an organization's performance. Recently, the Korean government has recognized the advantages of the BSC and encouraged public enterprises to implement the BSC. However, it has been pointed out that many public enterprises have faced difficulties in constructing and operating the BSC due to lack of clear understanding, a complex environment of performance evaluation, and inherent features of organizational culture. Therefore, this study analyzed a project case of a public enterprise, Korea Southern Power (KSP), which has ever been assessed as an excellent organization in implementing BSC and managing performance. This paper provides procedures, activities, resources (manpower and time), and decision-making issues and criteria required for implementing BSC, along with real project outcomes of the company. Such project details are expected to be used as helpful guidelines for public or non-profit organizations's BSC implementation. Furthermore, the KSP's efforts to cope with its problems and implications derived from the efforts are also expected to help other organizations construct and operate the BSC effectively.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.4D
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• pp.433-441
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• 2009

In the coming ubiquitous society, the importance of developing advanced public transportation systems (APTS) corresponding to individuals' needs and useful in their daily life is profound. In these regards, the study proposed new APTS services: Free internet access service and On-board real time traffic information service in public modes. A stated preference (SP) survey was performed to investigate individual's preference and willingness-to-pay (WTP) for the proposed APTS services. Multinomial logit models (MNL) incorporating the heterogeneity of respondents were developed to analyze individuals' preference and the difference of WTP. Some results of the study showed that the respondents' preferences were significantly different by in-vehicle travel times (30 min, 60 min) and their socioeconomic background. More respondents prefer new APTS services when invehicle travel time takes longer. For the housewife and self-employed group, the mean WTP for on-board realtime traffic information was higher than that of free internet access services, while for the company employees and students group, the mean WTP was similar in both services.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.5
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• pp.15-30
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• 2023

Recently, generative models based on the Transformer architecture, such as ChatGPT, have been gaining significant attention. The Transformer architecture has been applied to various neural network models, including Google's BERT(Bidirectional Encoder Representations from Transformers) sentence generation model. In this paper, a method is proposed to create a text binary classification model for determining whether a comment on Korean movie review is positive or negative. To accomplish this, a pre-trained multilingual BERT sentence generation model is fine-tuned and transfer learned using a new Korean training dataset. To achieve this, a pre-trained BERT-Base model for multilingual sentence generation with 104 languages, 12 layers, 768 hidden, 12 attention heads, and 110M parameters is used. To change the pre-trained BERT-Base model into a text classification model, the input and output layers were fine-tuned, resulting in the creation of a new model with 178 million parameters. Using the fine-tuned model, with a maximum word count of 128, a batch size of 16, and 5 epochs, transfer learning is conducted with 10,000 training data and 5,000 testing data. A text sentiment binary classification model for Korean movie review with an accuracy of 0.9582, a loss of 0.1177, and an F1 score of 0.81 has been created. As a result of performing transfer learning with a dataset five times larger, a model with an accuracy of 0.9562, a loss of 0.1202, and an F1 score of 0.86 has been generated.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.5
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• pp.354-361
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• 2023

Big data analysis systems apply NoSQL databases like MongoDB to store, process, and analyze diverse forms of large-scale data. MongoDB offers scalability and fast data processing speeds through distributed processing and data replication, depending on its configuration. This paper investigates the suitable MongoDB environment configurations for implementing big data analysis systems. For performance evaluation, we configured both single-node and multi-node environments. In the multi-node setup, we expanded the number of data nodes from two to three and measured the performance in each environment. According to the analysis, the processing speeds for complex data structures with three or more dimensions are approximately 5.75% faster in the single-node environment compared to an environment with two data nodes. However, a setting with three data nodes processes data about 25.15% faster than the single-node environment. On the other hand, for simple one-dimensional data structures, the multi-node environment processes data approximately 28.63% faster than the single-node environment. Further research is needed to practically validate these findings with diverse data structures and large volumes of data.

• Information Systems Review
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• v.25 no.4
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• pp.291-314
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• 2023

The concept of Mydata emerged with the expansion of the data economy. MyData aims to empower individuals by enhancing their right to self-determination over their personal data. The use of MyData is expected to enable the provision of innovative service in various fields. Since 2022, MyData has been introduced and actively used in the financial sector. In the future, not only financial institutions but also Bigtech and Fintech companies are expected to actively join and demonstrate rapid expansion. To ensure steady growth for MyData in the financial sector, it is necessary to assess acceptance behaviors from multiple perspectives. However, the majority of existing research solely focuses on positive acceptance. This study analyzed the impact of users' personal characteristics and innovation characteristics on both innovation resistance and acceptance resistance. The analysis revealed that personal and innovation characteristics contribute to an increase in distrust and innovation resistance in the MyData service. In addition, it has been confirmed that it can lead to actions such as delayed acceptance and refusal to accept. The results of this study offer both theoretical and practical insights into user behavior within the MyData service market.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.6
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• pp.91-98
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• 2023

The amount of power generation of a solar plant has a high correlation with weather conditions, geographical conditions, and the installation conditions of solar panels. Previous studies have found the elements which impacts the amount of power generation. Some of them found the optimal conditions for solar panels to generate the maximum amount of power. Considering the realistic constraints when installing a solar power plant, it is very difficult to satisfy the conditions for the maximum power generation. Therefore, it is necessary to know how sensitive the solar power generation amount is to factors affecting the power generation amount, so that plant owners can predict the amount of solar power generation when examining the installation of a solar power plant. In this study, we propose a polynomial regression analysis method to analyze the relationship between solar power plant's power generation and related factors such as weather, location, and installation conditions. Analysis data were collected from 10 solar power plants installed and operated in Daegu and Gyeongbuk. As a result of the analysis, it was found that the amount of power generation was affected by panel type, amount of insolation and shade. In addition, the power generation was affected by interaction of the installation angle and direction of the panel.

• Information Systems Review
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• v.23 no.4
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• pp.183-198
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• 2021

Due to the Covid-19 pandemic, the home-training app market is growing rapidly and numerous apps are entering the market. It is becoming more difficult for an app to secure the profitability. In this study, by analyzing actual user data of a reward-based home-training app, we propose a model that predicts cash-cow users of the app. Cash-cow users are the users who watch in-stream ads to watch training videos although they cannot earn any rewards by doing so. Thus, these users make profits for the app yet do not incur any costs. The results of this study show that the users who irregularly watch training videos are more likely to be cash-cow users than the users who regularly watch training videos. This result suggests that, paradoxically, for sustainable profitability, home-training apps may need to find a way to retain the users who watch training videos irregularly so that they can be satisfied with the service and continue use the apps.

• Information Systems Review
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• v.23 no.3
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• pp.201-223
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• 2021

Smart home is an advanced Internet of Things (IoT) service that enhances the convenience of human daily life and improves the quality of life at home. Recently, with the emergence of smart home products and services to which artificial intelligence (AI) technology is applied, interest in smart home is increasing. To gain a competitive edge in the smart home market, companies are providing "personalized service" to users, which is a key service that can promote smart home use. This study investigates the factors affecting the value awareness of personalized service and intention to use smart home. This research focuses on four-dimensional motivated innovativeness (cognitive, functional, hedonic, and social innovativeness) and privacy risk awareness as key factors that influence the value awareness of personalized service of smart home. In particular, this study conducts a comparative analysis between the generation MZ (young people in late teens to 30s), who are showing socially differentiated characteristics, and the generation X and baby boomers in 40s to 50s or older. Based on the analysis results, this study derives the distinctive characteristics of generation MZ that are different from the older generation, and provides academic and practical implications for expanding the use of smart home services.