• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2007.11a
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• pp.652-655
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• 2007

Due to stagnation of domestic market, increasing number of domestic construction companies started to make inroads into foreign market recently. Yet compared to domestic market, there are much more risks in the foreign market which companies may confront. So deliberate and rational decision making skills are required. Accordingly, there has been many researches which analyzed the risk of individual markets and also studies covering decision support models. In this study, we suggest a model concerning financial issues when branching out into a new market, specially in the construction companies' point of view. For this we used a real options game which shows real competition status of a new market and deduced a feature of that market, Upon these results, we also suggest a model which helps firms to decide whether investing in the expansion is smart action or not. The model developed in this study is made in specific circumstances of limited conditions. The future study makes more realistic models considering subjects like disproportion in information and generalization of competing companies.

• Journal of the Korea Institute of Building Construction
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• v.22 no.3
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• pp.305-316
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• 2022

Domestic construction companies have difficulty in establishing strategies when entering overseas markets because they do not have an overseas construction economic sentiment index to refer to for data on overseas construction prospects. Considering that the fluctuation of overseas construction orders over the past decade has been substantial and large companies and SMEs are actively advancing overseas, this study developed an evaluation model for an overseas construction business sentiment index to grasp the economic experience of overseas construction companies. In 2021 Korean companies earned 30.6 billion in overseas construction contracts, 87% the level of the previous year, despite difficulties such as COVID-19 and low oil prices, thanks to efforts by construction companies to strengthen their strategies for entry, such as regional diversification, and government support for winning orders. Since the overseas construction industry fluctuates greatly due to changes in the international environment, it is necessary to investigate and analyze the economic sentiment index of overseas construction companies. In particular, despite the increase in overseas expansion of small and medium-sized construction companies and engineering companies, the provision of information on the overseas construction market sentiment index is insufficient, limiting the establishment of strategies for overseas construction expansion. Therefore, this study intends to develop an overseas construction market sentiment index model that can understand the economic sentiment of overseas construction companies, provide a forecast for overseas construction, and use it to establish overseas construction strategies and policies.

• Journal of the Korea Society of Computer and Information
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• v.26 no.10
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• pp.179-184
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• 2021

In this paper, we propose the deep learning-based neural network model to predict bunker price. In the shipping industry, since fuel oil accounts for the largest portion of ship operation costs and its price is highly volatile, so companies can secure market competitiveness by making fuel oil purchasing decisions based on rational and scientific method. In this paper, short-term predictive analysis of HSFO 380CST in Singapore is conducted by using three recurrent neural network models like RNN, LSTM, and GRU. As a result, first, the forecasting performance of RNN models is better than LSTM and GRUs using long-term memory, and thus the predictive contribution of long-term information is low. Second, since the predictive performance of recurrent neural network models is superior to the previous studies using econometric models, it is confirmed that the recurrent neural network models should consider nonlinear properties of bunker price. The result of this paper will be helpful to improve the decision quality of bunker purchasing.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.8 no.4
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• pp.67-79
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• 2013

A meta-analysis is a statistical literature synthesis method that provides the opportunity to view the research context by combining and analyzing the quantitative results of many empirical studies. The technology acceptance model (TAM) has been the subjects of a great deal of MIS research in the last two decades and now also has been continuously studied. Recently, the convergence of knowledge information society and information telecommunication technologies has a rapid impact on politics, economics and various fields. The biggest issue in the information communication and information systems fields is smart. Therefore, we conducted a meta-analysis research on the behavioral intention of smart phone users based on technology acceptance model. Also, this study was targeted a total of 50 research papers that are setting up the causal relationship in TAM among the research papers published in domestic academic journals since 2005. The result of the meta analysis, showed that the effect size was 0.48 in the path from perceived usefulness to behavioral intention, it showed that the effect size was 0.46 in the path from perceived ease of use to behavioral intention. And, it showed that the effect size was 0.46 in the path from perceived ease of use to perceived usefulness. Also, it showed that the effect size was 0.61 in the path from attitude to behavioral intention. Based on the results, it was discussed the difference through comparative analysis with previous research.

• Journal of Convergence Society for SMB
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• v.5 no.2
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• pp.15-20
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• 2015

Recently, as smart phone technology is developing, wearable devices is also accelerating. But, the wearable device is necessary to operated for a long time with a small electric power because werable device is made compact. In this paper, we design and implement efficient lithium polymer battery model suitable to miniaturized wearable device in oder to maximize ease of use. The proposed model is characterized by a compact size of the battery by applying a thermal element and a light-weight battery. Also, proposed model gives greatly improve the life of wearable devices because it uses a method using the characteristics of the Peltier device using the temperature difference between the room temperature and body temperature of a person to generate power for charging. In particular, the proposed model can be used for the wearable device, as well as auxiliary charging of the smart phone.

• Industry Promotion Research
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• v.7 no.1
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• pp.9-15
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• 2022

This study tried to analyze the growth background of Starbucks, a competitive company in the Korean coffee industry. Therefore, by using the STEEP analysis technique, each company's competitiveness was analyzed and the results were used to derive competitive factors. And the research results are as follows. Looking at the social aspect, economic activity has been a catalyst for women as the standard of living has increased due to economic growth. In addition, in the case of coffee culture in the past, Starbucks' response strategy, which has seen the transformation from vending machine mixed coffee culture to a consumer market that emphasizes cultural and spatial aspects, was effective. Looking at the technical aspect, the deviation has been reduced by securing uniform standardization of the taste of coffee beans at franchise stores, and the operation of a standardized operating system was possible by operating the store directly. And looking at the economic aspect, as the coffee consumption market continues to expand, the overall size of the market has also grown proportionally, creating a stable growth environment. Lastly, looking at the environmental and policy aspects, it is that the marketing strategy direction based on the policy activities as an eco-friendly company as a market leader has been the main focus of the recent policy direction emphasizing eco-friendliness.

• Knowledge Management Research
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• v.24 no.3
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• pp.127-148
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• 2023

Traditional Business Intelligence environment is limited to support the rapidly changing businesses and the exponential growth of data in both volume and complexity of data. Companies should shift their business intelligence environment into Self-Service Business Intelligence (SSBI) environment in order to make smarter and faster decisions. However, firms seem to face various challenges in implementing and leveraging the effective business intelligence system, and academics do not provide sufficient studies related including the success factors of SSBI. This study analyzes the three cases of Korean companies in depth, their development process and the assessment of business intelligence, based on the theoretical model on the key success factors of business intelligence systems. The comparative analysis of the three cases including project managers' interviews and performance evaluations provide rich implications for the successful adoption and the use of business intelligence systems of firms. The study is expected to provide useful references for firms to fully leverage the effects of business intelligence systems and upgrade towards self-service business intelligence systems.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.465-467
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• 2019

최근 많은 단체나 기업에서 다양하고 방대한 데이터를 요구로 하고, 그에 따라서 국가 공공데이터나 데이터 브로커등 데이터를 통해 직접 수집 하거나 구매해야 하는 경우가 많아지고 있다. 하지만 개인정보의 경우 개인의 동의 없이는 타인에게 양도가 불가능하여 이러한 데이터에 대한 연구에 어려움이 있다. 그래서 특정 개인을 추론할 수 없도록 하는 비식별 처리 기술이 연구되고 있다. 이러한 비식별화의 정도는 모델로 나타낼 수가 있는데, 현재 k-anonymity 와 l-diversity 모델 등이 많이 사용된다. 이 중에서 l-diversity 는 k-anonymity 의 만족 조건을 포함하고 있어 비식별화의 정도가 더욱 강하다. 이러한 l-diversity 모델을 만족하는 알고리즘은 The Hardness and Approximation, Anatomy 등이 있는데 본 논문에서는 일반화 과정을 거치지 않아 유용성이 높은 Anatomy 의 구현에 대해 연구하였다. 또한 비식별화 과정은 전체 데이터에 대한 특성을 고려해야 하기 때문에 데이터의 크기가 커짐에 따라 실질적인 처리량이 방대해지는데, 이러한 문제를 Spark 를 통해 데이터가 커짐에 따라서 최대한 안정적으로 대응하여 처리할 수 있는 시스템을 구현하였다.

• Journal of Convergence for Information Technology
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• v.10 no.10
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• pp.65-70
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• 2020

With the appearance of Bitcoin that builds peer-to-peer networks for transaction of digital content and issuance of cryptocurrency, lots of blockchain networks have been developed to improve transaction performance. Recently, Joseph Lubin discussed Decentralization Transaction per Second (DTPS) against alleviating the value of biased TPS. However, this Lubin's trust model did not enough consider a security issue in scalability trilemma. Accordingly, we proposed a trust metric based on blockchain size, stale block rate, and average block size, using a sigmoid function and convex optimization. Via numerical analysis, we presented the optimal blockchain size of popular blockchain networks and then compared the proposed trust metric with the Lubin's trust model. Besides, Bitcoin based blockchain networks such as Litecoin were superior to Ethereum for trust satisfaction and data volume.

• Journal of Convergence for Information Technology
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• v.11 no.9
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• pp.28-34
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• 2021

In the case of object detection using deep learning, both accuracy and real-time are required. However, it is difficult to use a deep learning model that processes a large amount of data in a limited resource environment. To solve this problem, this paper proposes an object detection model for small embedded devices. Unlike the general detection model, the model size was minimized by using a structure in which the pre-trained feature extractor was removed. The structure of the model was designed by repeatedly stacking lightweight convolution blocks. In addition, the number of region proposals is greatly reduced to reduce detection overhead. The proposed model was trained and evaluated using the public dataset PASCAL VOC. For quantitative evaluation of the model, detection performance was measured with average precision used in the detection field. And the detection speed was measured in a Raspberry Pi similar to an actual embedded device. Through the experiment, we achieved improved accuracy and faster reasoning speed compared to the existing detection method.