• Korean Journal of Construction Engineering and Management
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• v.13 no.5
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• pp.94-102
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• 2012

Recently, the global financial crisis and the increasing number of unsold houses in Korea are construction companies to assess their efficiency. The most important factor in analyzing the efficiency of a company is the input-output variable. However, systematic stud the core input-output variables, which have a great influence on the efficiency analysis. Thus, to the core input-output variables for efficiency analysis of construction companies, this study propose a model that includes all combinations of input-output variables and to find the core input-output variables using the Data Envelopment Analysis(DEA) model and Principal Component Analysis(PCA). Existing research and theories were studied variables and 21 models were established to measure efficiency. were obtained that the core input and output variable in 2006 the number of employees and sales. For 2008, the core input variable was capital stock and the core output variable was quarterly net profit. For 2010, the core input variable was fixed asset and the core output variable was sales. Through obtaining the variables that greatly affect the efficiency of construction companies, it is considered that individual construction companies will be able to prepare a priority strategy to enhance efficiency.

• Journal of Navigation and Port Research
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• v.30 no.10 s.116
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• pp.793-800
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• 2006

The purpose of this paper is to show a way for extracting the core input and output variable in Korean seaports by using principal component analysis and DEA(data envelopment analysis). Two inputs(birthing capacity, and cargo handling capacity) and three outputs(export cargo handling amount, import cargo handling amount, and number of ship calls), and three cross sectional data(1995, 2000, and 2004) for 26 Korean seaports are considered for measuring the efficiencies of 21 DEA models. 21 models can be treated as variables and efficiencies as observations for extracting the core inputs and outputs variables by using principal component analysis. An empirical main result indicates that core input variable is cargo handling capacity, and core output is the number of ship calls. The Korean seaport authority can adopt the DEA and principal component analysis for deciding the development and investment to each seaport.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.5
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• pp.3169-3175
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• 2014

In this paper, we have established the procedures for $CO_2$ emission estimation BIM libraries by using the material takeoff function that BIM tools fundamentally provide, and verified its availability by applying to steel structures. The BIM library set-up procedures were made up of $CO_2$ emission coefficients and parameter extraction, project unit setting, parameter setting, and $CO_2$ emission quantity calculation formula set-up. We used Revit Architecture 2013 as BIM tool, and established the steel members' family libraries as BIM libraries. It is possible to calculate the $CO_2$ emission quantity by following the proposed BIM library set-up procedures, and users have only to input the $CO_2$ emission coefficients and unit weights of steel members being used. We expect that the results contribute to practical use of BIM in field, and vitalizations of the eco-friendly construction.

• Management & Information Systems Review
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• v.31 no.1
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• pp.273-292
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• 2012

This paper attempts to analyze the efficiency of Korean Materials and Components Industry. 48 sample companies are extracted and efficiency analysis for them are accomplished by using DEA model. We use both CCR-I model and BCC-I model and classify the 48 companies into two groups; efficient and inefficient companies. We find the reference set which inefficient companies should benchmark in order to achieve efficiency and present the improving values for input and output variables. We analyze whether the inefficiencies come from scale or inefficient operation by measuring the scale efficiency. Finally the ranking among the efficient companies is derived through the super-efficiency analysis.