Abstract. The enhancement of the competitiveness of a construction company is one of the most important strategic objectives in construction industry. The company's management system, work organization and employment of available assets are some of the most important factors upon which overhead costs and the bidding price of a construction company depend directly. A statistical analysis of a homogenous group of construction companies reveals the company's overhead costs value distribution function, which can be used to evaluate the competitive advantages and disadvantages of a specific construction company. A detailed overhead costs categorization and the findings of a survey conducted among contractors influenced the selection of the principal parameters of the company's activity, on which the value of overhead costs depends; they are the number of company's head office employees and the area of company's facilities. The developed competitiveness evaluation methodology enables the construction managers to adequate and scientific position the company on the market of homogenous construction companies group, to estimate its activity as well as to evaluate the competitive advantages and disadvantages of bidding prices and certain costs in public tendering of construction operations and services.
The paper deals with important aspects of construction management key factors identification and their relative significance for the construction projects management effectiveness. The approach of artificial neural network allows the construction projects management effectiveness model to be built and to determine the key determinants from a host of possible management factors that influence the project effectiveness in terms of budget performance. A list of construction management factors was collected according to the results of past research and opinion of experienced construction management practitioners. A survey questionnaire was compiled and distributed to construction management companies in Lithuania and the USA. The historical data of construction projects performance have been used to build the neural network model. Altogether twelve key construction management factors were identified covering areas related to the project manager, project team, project planning, organization and control. Based on these factors, the construction projects management effectiveness model was established. The application algorithm of that model is presented. The established neural network model can be used during competitive bidding process to evaluate management risk of construction project and predict construction cost variation. The model allows the construction projects managers to focus on the key success factors and reduce the level of construction risk. The model can serve as the framework for further development of the construction management decision support system.
The article investigates the problems of technological decision modelling of wall insulation in dwelling houses. The system engineering is the base of that technology. The methodology represents and optimises the systems of complex building processes. After that it is possible to develop the alternatives.
On a systematic engineering methodological basis, there was created a technological network model of the decisions of wall insulation. This model has been constructed on the base of classical net model with a new modification for application provided.
The main stages of technological network model of wall insulation are:
formation of complex combination process;
establishment of possible variants of the partial process;
technological connection among those (b and c) processes.
The implementation alternatives of the analysed process have pointed out in the technological net model for the decisions of wall insulation. Such a model enables to analyse, to evaluate and to optimise the decisions of wall insulation.
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