• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2008.11a
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• pp.202-206
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• 2008

Recently, as high level of interest for the city regeneration, large-scale projects are planned or being performed such as reconstruction project. These mesa-projects have different characteristics from a single project in the design phase. It is a number of companies involved in design phase of mega-project and principal decision-making entity manage the project from the initial stage of an ongoing business by coordinating an opinions between design companies. The absence of a decision making support system reflected those characteristic causes a variety of problems such as a loss of cost and schedule. Therefore the final object of this paper is to propose a decision making support tool and system interface.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.45-66
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• 2018

Crowdfunding has become more popular than angel funding for fundraising by venture companies. Identification of success factors may be useful for fundraisers and investors to make decisions related to crowdfunding projects and predict a priori whether they will be successful or not. Recent studies have suggested several numeric factors, such as project goals and the number of associated SNS, studying how these affect the success of crowdfunding campaigns. However, prediction of the success of crowdfunding campaigns via non-numeric and unstructured data is not yet possible, especially through analysis of structural characteristics of documents introducing projects in need of funding. Analysis of these documents is promising because they are open and inexpensive to obtain. We propose a novel method to predict the success of a crowdfunding project based on the introductory text. To test the performance of the proposed method, in our study, texts related to 1,980 actual crowdfunding projects were collected and empirically analyzed. From the text data set, the following details about the projects were collected: category, number of replies, funding goal, fundraising method, reward, number of SNS followers, number of images and videos, and miscellaneous numeric data. These factors were identified as significant input features to be used in classification algorithms. The results suggest that the proposed method outperforms other recently proposed, non-text-based methods in terms of accuracy, F-score, and elapsed time.

• Journal of the Korea Institute of Building Construction
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• v.24 no.3
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• pp.381-391
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• 2024

This study examined the factors influencing safety scores in air conditioning installation projects, with a specific focus on the characteristics of safety managers and project-specific details. Given the increase in industrial accidents within this sector and the lack of research on smaller-scale operations, this analysis of 7,046 safety data records from Company A aimed to address this gap. The results indicate that the month of project commencement has the most significant impact on safety scores(correlation coefficient of 0.21), followed by the age of the safety manager(correlation coefficient of 0.06). Interestingly, the educational background of the managers did not appear to influence safety outcomes. Furthermore, project cost was found to have a negative correlation with safety scores(-0.1), suggesting that lower-cost projects may be associated with higher risk levels. These findings underscore the importance of developing tailored safety checklists that take into account the specific timing and scale of air conditioning installation projects. Additionally, the results suggest that incorporating both experienced(older) and less experienced(younger) safety managers into safety strategies may be beneficial for achieving optimal safety outcomes. This balanced approach could leverage the strengths of both groups, potentially enhancing overall risk assessment and mitigation efforts.

• Korean Journal of Construction Engineering and Management
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• v.6 no.5 s.27
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• pp.89-101
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• 2005

The early phase of construction projects, communication among the related participants has great influence on the further transaction of the projects. However, important decision making are made by the experience of the field managers in practice without the method for systematic analysis. For example, in building construction project, selection process for construction method has been executed by decision making of some architects dependent on their experience. As a result, there have been frequent construction method alterations during the construction process and delay of duration, addition of cost, etc have followed accordingly. The main reasons of such a mal-functional transaction are due to the absent of the reasonal procedure of decision making reflecting the characteristics of construction project. Therefore, there is a need for an supporting tool and production design for the selection of rational construction method. The objective of this study is to propose production design process and decision making model in relation to various influent factors at the early phase of construction projects. To achieve these objectives, this study 1)analyzes the prior theory about production design, 2)we have studied about selection process for optimal construction method through constraint analysis in structural works, 3)performs a case study to embody the problems of the production design, and 4)proposes a cooperative committee model for supporting production design by analyzing the results of case study and interviewing experts. It is anticipated that the effective tool of proposed model would be able to improve communication among the related participants and systematically accumulate data that might be used in similar construction projects.

• Informatization Policy
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• v.21 no.4
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• pp.3-19
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• 2014

Crowd-funding platforms, which enable to collect funds from individuals, have recently gained growing interests around the world. This study intends to provide future research directions for the crowd-funding by reviewing past research works. For this purpose, two research themes are selected - (1) motivations to participate in crowd-funding and (2) critical success factors for the project funding. The motivations are analyzed from both perspectives of fund demanders and suppliers. The critical success factors are investigated by using four dimensions: fund demanders, fund suppliers, relationships between demanders and suppliers, and project characteristics. Using the implications found from the past research, this paper offers future research issues necessary for the growth of crowd-funding platforms.

• Korean Journal of Construction Engineering and Management
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• v.6 no.4 s.26
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• pp.80-90
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• 2005

Activity durations retain probabilistic and stochastic natures due to diverse factors causing the delay or acceleration of activity completion. These natures make the final project duration to be a random variable. These factors are the major source of financial risk. Extending the Stochastic Project Scheduling Simulation system (SPSS) developed in previous research; this research presents a method to estimate how the final project duration behaves when activity durations change randomly. The final project cost is estimated by considering the fluctuation of indirect cost, which occurs due to the delay or acceleration of activity completion, along with direct cost assigned to an activity. The final project cost is estimated by considering how indirect cost behaves when activity duration change. The method quantifies the amount of contingency to cover the expected delay of project delivery. It is based on the quantitative analysis to obtain the descriptive statistics from the simulation outputs (final project durations). Existing deterministic scheduling method apply an arbitrary figures to the amount of delay contingency with uncertainty. However, the stochastic method developed in this research allows computing the amount of delay contingency with certainty and certain degree of confidence. An example project is used to illustrate the quantitative analysis method using simulation. When the statistical location and shape of probability distribution functions defining activity durations change, how the final project duration and cost behave are ascertained using automated sensitivity analysis method

• The Journal of Society for e-Business Studies
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• v.21 no.2
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• pp.23-46
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• 2016

With the increasing socio-economic value of an open collaboration over the Internet, it has become significantly important to successfully manage open source software development program. Most of the previous research have focused on various factors that influence the performance of the project, but studies on how the project owners recognized as "leader" affect the outcome of the project are very limited. This research investigates how individual and governance characteristics of an owner influences the performance of project based on impression formation and social capital theory. For a data set, we collect 611 Repositories and the owner's data from the open source development platform Github, and we form knowledge sharing network of an each repository by using social network analysis. We use hierarchical regression analysis, and our results show that a leader, who exposes a lot of one's personal information or who has actively followed and showed interests to communicate with other developers, affects positive impacts on project performance. A leader who has a high centrality in knowledge sharing network also positively affects on project performance. On the other hand, if a leader was highly willing to accept external knowledge or is recognized as an expert in the community with large numbers of followers, the result show negative impacts on project performance. The research may serve as a useful guideline not only for the future open source software projects but also for the effective management of different types of open collaboration.

• Information and Communications Magazine
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• v.31 no.11
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• pp.14-26
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• 2014

본고는 빅데이터 시대에 새로운 가치를 창출할 수 있는 정보 분석을 위한 기계학습을 설명하고자 한다. 기계학습의 일반적 정의와 특성, 그리고 빅데이터 특성에 의한 기계학습의 변화를 확인하고 특별히 다양한 변화 중에서 분산 및 병렬화를 통한 스케일러블 기계학습을 중점으로 주어진 빅데이터를 효율적으로 분석할 수 있는 다양한 플랫폼들과 프레임워크들을 설명한다. 더불어 실제 다양한 응용 활용을 제공하고 있는 Google API 같은 빅데이터 분석 기계학습 프로젝트들을 통해서 기계학습을 통한 빅데이터 분석에 대한 폭넓은 이해를 전달하고자 한다.

• Journal of Digital Convergence
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• v.14 no.10
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• pp.183-193
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• 2016

Recently, collaborations through MCS use in team projects are frequently conducted. This study developed a research model to examine the impact of collaboration through MCS on project performance. Team commitment and team trust regarded as the key drivers of enhancing project performance. Moreover, we also investigated the effect of usefulness of MCS on project performance. We posit ubiquity, polychronic use, and ease of use as the key antecedents of usefulness of MCS. The proposed theoretical framework was tested by using survey data collected from 116 university students who have rich experience with collaboration through MCS. PLS was employed for the analysis of the data. The analysis results showed that team trust significantly influences team commitment and project performance, respectively. However, usefulness of MCS is not significantly related to team commitment, while it play a prominent role in enhancing project performance. The results reveals that ease of use has a significant effect on usefulness of MCS, whereas ubiquity and polychronic use are not significantly related to it. From theoretical and practical perspective, this paper can provide in-depth knowledge of the effects of collaboration via MCS on project performance.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.07a
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• pp.305-306
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• 2019

대학의 게임개발 프로젝트는 학기라는 시간적 제약아래 게임 기획, 그래픽, 프로그래밍, QA 등 다양한 전공의 학생들이 팀을 이루고 진행한다. 게임 개발은 특성상 폭포수 개발과 같은 전통적인 개발방법론보다는 애자일 방법론이 보다 적합할 수 있다. 본 논문에서는 애자일 방법론 적용을 시도한 졸업작품팀의 개발자를 인터뷰하여 진행과정과 실패 요인에 대한 정보를 수집하여 분석하고, 애자일 방법론을 적용하기 위한 방안을 제시하였다.