• Korean Journal of Construction Engineering and Management
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• v.12 no.1
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• pp.62-72
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• 2011

Currently, The failure of construction project is increasing to be caused by a changing construction environment. According to this circumstances, Researches of project success factors affecting performance have been presented to develop strategies for efficient construction project management in the construction industry. However, Conducting efficient construction project management is difficult because project manager could not know which project success factors can be improved or not. Especially, although the project characteristics were derived the level of difficulty for performance, research of the project characteristics which could not be improved as influence factor to performance is lacking. Therefore, This paper has developed the Performance Predicting System(PPS) with Fuzzy set theory to establish. PPS has been developed to establish efficient project management strategies and to save time and effort. As Contractor inputs the project characteristics, PPS can predict the level of difficulty of performance.

• Korean Journal of Construction Engineering and Management
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• v.11 no.6
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• pp.78-88
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• 2010

Since the larger and complex construction projects are performed, project performance measurement is highlighting the importance to eliminate inefficiencies and plan to reasonable management practices. So many researchers are conducting research about the project critical sucess factor. But, these factors are mixed both management practices to improve performance and native project characteristics. Therefore performance measurement data couldn't apply to another project successfully. And the project characteristics affect project performance. But contractor couldn't change characteristics. This study provides a project characteristics's definition and classification. This study provides a quantitative level of performance improvement difficulty through out project manager survey. The contractor can estimate a level of performance difficulty through initial project information. With this, project contractor can more efficiently manage project.

• Korean Journal of Construction Engineering and Management
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• v.13 no.1
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• pp.3-13
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• 2012

The importance of project performance management as an alternative for solving problems is rising, which are followed by the hardships of managing construction project in the construction industry. This research classifies and applies the improvements made by the operator's work, in order to apply factors of success on the construction project, as performance management factors. In addition, in order to predict the results reflecting the project characteristic of performance management factor un-improvable by the operator in the initial stage of construction, the effect of project characteristic to the performance was drawn by performance difficulty. Also, in order to improve the predicted performance, researches on setting valid best practices according to the performance territory through a correlation analysis between the best practices improvable through the operator's work, and the performance was made.

• Korean Journal of Construction Engineering and Management
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• v.20 no.3
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• pp.122-133
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• 2019

In the construction industry, bidding competitiveness is the most basic and important competence of the company. Bidding competitiveness comes from competitive advantage, but the strategy of the company to capture bidding competitiveness varies with the characteristics of the project. In particular, overseas construction is where uniqueness of the construction industry and the specificity of international business coexist. This study analyzes the bidding success ratio and the level of bidding difficulty by project characteristics with 12,952 overseas construction bidding cases. Consequently, it was found that the bidding success ratio of Middle East and North Africa (MENA) and civil engineering was the lowest in each group of project characteristics, and therefore the level of bidding difficulty is high, respectively. In addition, it was confirmed that the bidding success ratio of small size or short duration project was relatively high, and the bidding success ratio of both the negotiated bidding in the bidding method group and the private sector in the client type group was respectively high. However, Kruskal-Wallis test in contract type and period shows that there is no statistically significant difference in the bidding success ratio by group.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2013.11a
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• pp.214-215
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• 2013

Recently, Construction industry has been trying to reduce environmental impacts reflecting the global trend 'Green Growth'. However most of previous studies focused on operation & maintenance phases and do not have been approached construction phases. In addition, environmental management factors by project participants are assessed with only weight of factors, overlooking these work difficulty. Therefore This study aims to deducted the critical environmental management factors by project participants considering work difficulty in plan, design and construction phase. The basis data is collected through literature reviews and interview targeting each project participant and analyze these data using importance-difficulty analysis(IDA).

• Proceedings of the Korea Information Processing Society Conference
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• 2008.05a
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• pp.300-303
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• 2008

IT 관련 프로젝트를 진행 시 프로젝트 진행 도중 예상치 못한 많은 문제에 봉착하게 된다. 본 논문에서는 IT 프로젝트 대부분이 도입, 사용하는 요구사항분석-설계-개발-테스트-배포-유지보수단계 중 개발단계 및 유지보수 단계에서 발생할 수 있는 문제점에 초점을 맞추었다. PMG 란 Project Management Negotiator 의 약자로서 개발 시 고객의 요구사항이 변경되면 고객과 개발자 간의 개발에 소요되는 난이도, 일정, 비용에 따른 관점이 다를 수 있으므로, 이러한 차이점을 서로 이해 할 수 있는 범위 내에서 감소시킬 수 있는 모델을 제시한다. 또한 제시한 모델에 근거한 매핑테이블과 프로세스를 개발하고 실제 pilot 시스템을 구축하여 효용성을 검증한다. 제시한 프로젝트 관리 협상 모델을 통하여 일정에 차질 없는 프로젝트가 수행 가능하며 비용절감 및 고객만족 효과를 거둘 수 있다. 결과적으로 일정, 비용 측면 및 고객 만족 세 가지 측면에서 기존의 프로젝트 개발 방법론보다 더 나은 일정준수, 효율성, 정확성 등의 정량적, 정성적 만족을 확보할 수 있다.

• The KIPS Transactions:PartD
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• v.13D no.1 s.104
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• pp.87-96
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• 2006

This paper focused on the method for customizing software development path, considering the project environments and characteristics. he selection standard of development path is composed of ten items, based on the process of ISO/IEC TR 15721 Information Technology Guide for ISO/IEC 12207 (Software Life Cycle Process) and ISO/IEC 15504 Information technology - Process assessment. The ten items were reflected the project environments and characteristics, at the same time the items conduct the adjustment item of selecting project development path. An algorithm for selecting software development path through items of the project environments and characteristics is presented. To test the algerian in this paper, a system for selecting development path, which reflected algorithm was developed. The development project for web-based system were also adopted to the system for selecting development path. In addition, provened hand-worked project path process differed from machine-worked project path process. The reason why it differs is that outputs were mixed or their names were changed. The effect is to select easily software development route suitable for project environment and characteristics.

• The KIPS Transactions:PartD
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• v.9D no.1
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• pp.75-80
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• 2002

Putnam develops SLIM (Software LIfecycle Management) model based upon the assumption that the manpower utilization during software project development is followed by a Rayleigh distribution. To obtain the manpower distribution, we have to be estimate the total development effort and difficulty ratio parameter. We need a way to accurately estimate these parameters early in the requirements and specification phase before investment decisions have to be made. Statistical tests show that system attributes are highly correlation (redundant) so that Putnam discards one and get a parameter estimator from the other attributes. But, different statistical method has different system attributes and presents different performance. To select the principle system attributes, this paper uses the principle component analysis (PCA) instead of Putnam's method. The PCA's results improve a 9.85 percent performance more than the Putnam's result. Also, this model seems to be simple and easily realize.

• Journal of the Korea Society of Computer and Information
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• v.14 no.6
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• pp.33-40
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• 2009

In this thesis, for the assessment of software development process for project complexity and project size : one of digital watermarking algorithm is selected and examined. Digital watermarking provides a solution to illegal copying of digital contents and has many other useful applications, including web broadcast monitoring, transaction tracking, authentication, copy control and device control. This thesis focused on the method for customizing software development path, considering the project environments and characteristics. The selection standard of software development path is composed of process items, based on the ISO/IEC 15721 Information Technology Guide for ISO/IEC 12207 (Software Life Cycle Process) and ISO/IEC 15504 Information technology - Process assessment. To evaluate the algorithm, a system for selecting development path, which reflected algorithm, was examined.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.6
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• pp.851-863
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• 2023

The mandatory use of BIM(Building Information Model) in larger Korean public construction projects necessitates participants to have a comprehensive understanding of the relevant procedures and technologies, especially during the bidding stage. However, most small and medium-sized construction and engineering companies possess limited BIM proficiency and understanding. This hampers their ability to recognize bidding requirements and make informed decisions. To address this challenge, our study introduces a method to gauge the complexity of BIM requirements in bidding documents. This is achieved by integrating a morphological analyzer, which encompasses BIM bidding terminology, with a deep learning model. We investigated the effects of the parameters in our proposed deep learning model and examined its predictive validity. The results revealed an F1-score of 0.83 for the test data, indicating that the model's predictions align closely with the actual BIM performance challenges.