• Korean Journal of Construction Engineering and Management
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• v.4 no.1 s.13
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• pp.81-89
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• 2003

This research suggests the FD-AHP decision making model for Construction Projects which is composed of two main method to prevent a ranking invert situation ; First, to make the consensus of the experts consistent, we utilize Fuzzy-Delphi method to adjust the fuzzy rating of every expert to achive the consensus condition with the fuzzy linguistic presentation. Second, to handle vague linguistic presentation caused by expert's experiences and subjective judgement, we propose Fuzzy-AHP which is able to enhance precision of construction projects decision mating situation. Moreover, with the correlation analysis, we show that the validity of the FD-AHP model under a decision making task specially on where highly demanded expert's experiences and intuition.

• KIEAE Journal
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• v.10 no.3
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• pp.3-10
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• 2010

As indoor air quality directly affects health and comforts of the residents, researchers from different countries have continued to explore criteria by which indoor air quality can be indicated in a scientific and quantitative manner over the past several decades. However, there are many possibilities that can deteriorate indoor air quality. Due to the uncertainty of influence factors, it is quite difficult to develop a correct evaluation model and quantitative method. Furthermore, the effects from the indoor air pollutants have different levels, leading to the difficulties to apply the regular standard. This study aims to propose evaluation criteria by using the FD-AHP analysis. Obtained findings will be beneficial to construct apartment buildings, commercial buildings and others health performance evaluation framework.

• Journal of the Korea Institute of Building Construction
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• v.13 no.4
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• pp.424-433
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• 2013

There have been few attempts made to perform a systematic analysis of the various risk influence factors in building development projects. This study suggests an analysis of the risk influence factors in the process of feasibility studies for apartment building development projects. To reflect the voice of professionals, surveys were carried out. In addition, an FD-AHP method was applied to identify the importance of the risk influence factors. Through the surveys, major risk factors were separately identified as direct and/or indirect elements. An analysis of risk influence factors supports an effective feasibility study of apartment building development projects.

• Journal of the Korea Institute of Building Construction
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• v.13 no.6
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• pp.530-540
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• 2013

The business environment that affects the management performance can be characterized by each Strategic Business Unit (SBU) since construction companies win overseas contracts due to the fairly good construction situations while experience a decline in the local housing market. Environmental changes can alter the strategic importance of the SBU when measuring the management performance. However, large construction companies apply BSC (Balanced Score Card) for collective calculation to determine the management performance, making it difficult to reflect the strategic importance of SBU. This method may create a distorted image of management performance that fails to take environmental changes into consideration, and as such it needs to be improved. Yet, there are no studies on the weight of each SBU considering environmental changes. Thus, the current study intends to analyze the weight of SBU for company-wide measurement of the performance of large construction companies. In addition, a model for analysis of SBU importance is proposed to respond to the constantly changing environmental situations and to modify the weight. For analysis of SBU weight, a questionnaire was conducted with 23 experts and hands-on workers, and the questionnaire result was quantitatively analyzed by applying the FD-AHP method. It is expected that the result will enable a model to be proposed to calculate the weight per division in a manner that reflects environmental changes and minimizes strategic distortion when measuring the management performance of large construction companies.