• International conference on construction engineering and project management
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• 2013.01a
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• pp.133-140
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• 2013

The purpose of this study is identifying the relationship among the business strategy, order receiving capability and leverage variables of a construction company using industry characteristic variables, in addition to the explanation variables used in the previous studies. The samples of this study were limited to the construction companies listed in Korean stock market. This study built multiple regression analysis models, which have been frequently used in traditional previous studies, in the explanation of company capital structure. Empirical analysis on Static Trade-off Theory and Pecking Order Theory was done by the built model. The study results suggested that the capital structure determination behavior of a construction company generally follows Static Trade-off Theory; however, profitability was found to follow Pecking Order Theory. The explanation variables used in the previous capital structure studies mostly produced significant results; however, the variables, which this study experimentally used, did not produce significant results. It is believed that it implies that additional studies are required in the selection of variables and study methodology. Consequently, a case that unconditionally supports a particular theory is scarce. It has been also found that a case can support both theories at the same time. Therefore, it is believed that development study methodology or introduction of new study methodology that can identify the dynamic characteristic of construction company capital structure formation is required.

• Asia-Pacific Journal of Business
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• v.14 no.4
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• pp.87-113
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• 2023

Purpose - Focusing on Haier, a successful corporate venture in China, we analyse the operating mechanism and success factors of corporate venture, and reveal the necessary factors for the successful implementation of corporate venture. Design/methodology/approach - This study is a single case study centred on Haier, a successful corporate venture in China. Findings - The operational process of Haier's corporate venture includes six key aspects: project selection, team building, resource allocation and support, project implementation, risk control measures, performance evaluation and rewards. In terms of success factors, the support of top management with leadership capability of value creation and sharing is very important for the success of corporate venture. Secondly, a multi reward mechanism can be introduced to motivate employees and improve performance. Thirdly, it is important to integrate corporate culture into the operating mechanism of an corporate venture. Fourthly, flexible operations that break down rigid organisational boundaries and transform the organisation into a more open platform for entrepreneurship can increase the likelihood of success. Finally, empowering employees with operational discretion can also have a positive impact on the success of an Corporate Venture. Research implications or Originality - This study contributes to theory and practice by analysing the success conditions of corporate venture, providing new understanding and drawing new perspectives, especially from the experience of Haier. The results suggest strategies and flexibility for successfully pursuing corporate venture, and provide important experience for international companies to help them gain competitive advantage in global competition. It also helps corporate leaders to promote new directions and innovations and improve their strategies to respond to dynamic environments.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.2
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• pp.65-80
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• 2022

Despite the uncertainty and risky factors of startups, the special and critical role of accelerators in carrying out professional nurturing and investment for them is becoming increasingly significant in the startup social-system. However, academic research on investment determinants that have a profound impact on the survival of accelerators is lacking, and there are only a few empirical studies on the classification and importance of factors, and they do not enjoy the benefits of theoretical studies. This study proposes a business model innovation framework based on the business model innovation theory that reflects the nature and properties of startups that are investment targets of accelerators and derives 12 investment decision factors. The framework defines that the target, direction, and performable force of startup innovation are a business model, strategy, and dynamic capability. Besides, the framework analyzes the investment decision factors of the existing accelerators based on the business model innovation framework to verify the suitability and sufficiency of the composition. As a result of the analysis, first, most of the items were faithfully composed from a static point of view of business model innovation, but it was found that the factors related to the core activities to evaluate the activity and customer relationship were insufficient. Second, from the strategic point of view, the necessity of developing factors that can encompass the definition and content of core resources, which are internal strategic factors, was raised. Third, from the dynamic point of view, it was found that many of the investment determinants of accelerators were concentrated on the lower level of dynamic competencies. This can be judged as a result of reflecting the characteristics of a startup that needs to develop a solution with few resources and a small number of team members. In addition, the roles and interrelationships between each factor are not clear, thus it was found as a limiting point for startups to view and evaluate the direction and process in which startups dynamically innovate their business models. This study is considerably differentiated in that it provides a business model innovation framework and offers a theoretical basis for investment determinants by deriving the investment determinants of accelerators based on the framework and design the foundation for subsequent research. The business model innovation framework presented in this study has great implications in that it contributes to the achievement of startups, accelerators, and startup support organizations.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.57-84
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• 2023

With the development of information and communications technology (ICT) and big data technology, anyone can easily obtain and utilize vast amounts of data through the Internet. Therefore, the capability of selecting high-quality data from a large amount of information is becoming more important than the capability of just collecting them. This trend continues in academia; literature reviews, such as systematic and non-systematic reviews, have been conducted in various research fields to construct a healthy knowledge structure by selecting high-quality research from accumulated research materials. Meanwhile, after the COVID-19 pandemic, remote healthcare services, which have not been agreed upon, are allowed to a limited extent, and new healthcare services such as health recommender systems (HRS) equipped with artificial intelligence (AI) and big data technologies are in the spotlight. Although, in practice, HRS are considered one of the most important technologies to lead the future healthcare industry, literature review on HRS is relatively rare compared to other fields. In addition, although HRS are fields of convergence with a strong interdisciplinary nature, prior literature review studies have mainly applied either systematic or non-systematic review methods; hence, there are limitations in analyzing interactions or dynamic relationships with other research fields. Therefore, in this study, the overall network structure of HRS and surrounding research fields were identified using citation network analysis (CNA). Additionally, in this process, in order to address the problem that the latest papers are underestimated in their citation relationships, the GraphSAGE algorithm was applied. As a result, this study identified 'recommender system', 'wireless & IoT', 'computer vision', and 'text mining' as increasingly important research fields related to HRS research, and confirmed that 'personalization' and 'privacy' are emerging issues in HRS research. The study findings would provide both academic and practical insights into identifying the structure of the HRS research community, examining related research trends, and designing future HRS research directions.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.3 no.1 s.4
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• pp.31-44
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• 2004

The study of Estimation model for the short-term travel time prediction. There is a different solution which has predicted the link travel time to solve this problem. By using this solution, the link travel time is predicted based on link conditions from time to time. The predicated link travel time is used to search the shortest path. Before providing a dynamic shortest path finding, the prediction model should be verified. To verify the prediction model, three models such as Kalman filtering, Stochastic Process, ARIMA. The ARIMA model should adjust optimal parameters according to the traffic conditions. It requires a frequent adjustment process of finding optimal parameters. As a result of these characteristics, It is difficult to use the ARIMA model as a prediction. Kalman Filtering model has a distinguished prediction capability. It is due to the modification of travel time predictive errors in the gaining matrix. As a result of these characteristics, the Kalman Filtering model is likely to have a non-accumulative errors in prediction. Stochastic Process model uses the historical patterns of travel time conditions on links. It if favorably comparable with the other models in the sense of the recurrent travel time condition prediction. As a result, for the travel time estimation, Kalman filtering model is the better estimation model for the short-term estimation, stochastic process is the better for the long-term estimation.

• Journal of Engineering Education Research
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• v.10 no.2
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• pp.44-61
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• 2007

The present investigation is concerned chiefly with new curriculum development at the Department of Mechanical System & Design Engineering at Hongik University with the aim of enhancing creativity, team working and communication capability which modern engineering education is emphasizing on. 'Mechanical System & Design Engineering' department equipped with new curriculum emphasizing engineering design is new name for mechanical engineering department in Hongik University. To meet radically changing environment and demands of industries toward engineering education, the department has shifted its focus from analog-based and machine-centered hard approach to digital-based and human-centered soft approach. Three new programs of Introduction to Mechanical System & Design Engineering, Creative Engineering Design and Product Design emphasize hands-on experiences through project-based team working. Sketch model and prototype making process is strongly emphasized and cardboard, poly styrene foam and foam core plate are provided as working material instead of traditional hard engineering material such as metals material because these three programs focus more on creative idea generation and dynamic communication among team members rather than the end results. With generative, visual and concrete experiences that can compensate existing engineering classes with traditional focus on analytic, mathematical and reasoning, hands-on experiences can play a significant role for engineering students to develop creative thinking and engineering sense needed to face ill-defined real-world design problems they are expected to encounter upon graduation.

• Applied Chemistry for Engineering
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• v.29 no.3
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• pp.278-282
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• 2018

The development of treatment technologies for recycling waste woods generated from tree pruning is required in Gangwon province forest. In this study, according to adsorption experiments using three types (Larix kaemoferi, Juniperus chinensis, Pinus densiflora) of waste woods, Juniperus chinensis as a biosorbent showing an excellent removal ability was selected for the removal of methylene blue in an aqueous phase. When 0.4 g/100 mL of Juniperus chinensis was used to improve the removal efficiency of methylene blue for 4 h, each 100, 200 and 300 mg/L of methylene blue dissolved in the aqueous phase were removed to 98, 93, and 81%, respectively. The adsorption equilibrium data obtained by changing adsorbent concentrations was found to be more consistent with the Langmuir than the Freundlich equation. In addition, based on dynamic experiments by changing the methylene blue concentration, the biosorption kinetics equation was more suitable for a pseudo-second order model. In order to enhance the removal capability of highly concentrated methylene blue, 300 and 400 mg/L of methylene blue were operated for 4 h under 210 rpm of agitation velocity and removal efficiencies were 92 and 76%, respectively. Consequently, these experimental results can be effectively utilized as a new biosorption technology for economically treating methylene blue dissolved in an aqueous phase.

• Science of Emotion and Sensibility
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• v.13 no.3
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• pp.467-474
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• 2010

Recently, Study of functional clothing for Vital sensing is focused on reducing artifact by human motions, in order to enhance the electrocardiogram(ECG) sensing accuracy. In this study, considering the factors for each element found from the analysis, a 3-lead electrode inside textile embroidered with silver yarn was developed, and draft designs off our types of vital-signal sensing garments, which are 'chest-belt typed' garment, 'cross-typed' garment 'x-typed' garment and 'curved x-typed' garment, were prepared. The draft designs were implemented on a sleeveless male shirt made of an elastic material so that the garment and the electrodes can remain closely attached along the contour of the human body, and the acquired data was sent to the main computer over a wireless network. In order to evaluate the effects caused by body movements and the ECG-sensing capability for each type in static and dynamic states, displacements were measured from one and two dimensional perspectives. ECG measurement evaluation was also performed for Signal-to-noise ratio(SNR) analysis. Applying the experimental results, the draft garment designs were modified and complemented to produce two types of modular approaches 'continuous-attached' and 'insertion-detached' for the ECG-sensing smart clothing.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.7
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• pp.993-1000
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• 2002

In this paper, we design the CORBA-based Mobile Agent Model (CMAM) which has the capability of the efficient work processing in distributed environment through sensing network traffic and searching the optimal path for migration nodes of mobile agent. In case existing mobile agent model is given various works from user, the network overhead and traffic are increased by increasing of execution module size. Also, if it happens a large quantity of traffics due to migration of nodes according to appointment of the passive host(below node) routing schedule by user, it needs much cost for node search time by traffic. Therefore, in this paper, we design a new mobile agent m()del that assures the reliability of agent's migration through dynamic act on the specific situation according to appointment of the active routing schedule and can minimize agent's work processing time through optimal path search. The proposed model assigns routing schedule of the migration nodes actively using an extended MAFFinder. Also, for decreasing overhead of network by agent's size, it separates the existing mobile agent object by mobile agent including only agent calling module and push agent with work executing module based on distributed object type of CORBA. Also, it reduces the required time for round works of mobile agent through the optimal path search of migration nodes.

• Journal of the Korean Society of Hazard Mitigation
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• v.5 no.2 s.17
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• pp.9-16
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• 2005

This paper presents the use of an Artificial Neural Network (ANN) as a viable means of forecasting Inundation Damage Area (IDA) in many watersheds. In order to develop the forecasting model with various environmental factors, we selected 108 watershed areas in South Korea and collected 49 damage data sets from 1990 to 2000, of which each set is composed of 27 parameters including the IDA, rainfall amount, and land use. After successful training processes of the ANN, a good agreement (R=0.92) is obtained (under present conditions) between the measured values of the IDA and those predicted by the developed ANN using the remaining 26 data sets as input parameters. The results indicate that the inundation damage is affected by not only meteorological information such as the rainfall amount, but also various environmental characteristics of the watersheds. So, the ANN proves its present ability to predict the IDA caused by an event of complex factors in a specific watershed area using accumulated temporal-spatial information, and it also shows a potential capability to handle complex non-linear dynamic phenomena of environmental changes. In this light, the ANN can be further harnessed to estimate the importance of certain input parameters to an output (e.g., the IDA in this study), quantify the significance of parameters involved in pre-existing models, and contribute to the presumption, selection, and calibration of input parameters of conventional models.