| مستخلص: |
The rapid growth of population and increasing complexity of urban infrastructure have led to even greater consideration of new methods of installing and commissioning underground facilities. These facilities and vital artery lines are implemented in various ways, the most important of which is the traditional open-trench and new trenchless technology. Many factors affect the selection of the best method of implementation, and the method and technology of implementation should be determined based on the conditions of the project and area of construction. In the present study, the factors affecting the acceptance and application of trenchless technology and open-trench method in Iran are evaluated using two techniques: analytic hierarchy process (AHP) and analytic network process (ANP), and the results are compared with each other. The statistical population for this research consisted of middle managers, contractors, and engineers from Iran's supervision and design body. For this purpose, factors such as technology, economic, environmental, project productivity, organizational, executive management, individual, and demographic are identified as effective factors in the evaluation of excavation technology using library studies and consulting with experts. The relevant decision-making model was then prepared via interviews with experts. Eventually, components and criteria affecting excavation technology were prioritized through pairwise comparisons and model solving. The results showed that, in the AHP technique, the principal components, i.e., economic, technology, and executive management factors, and the criteria section, direct cost, social costs, and competitive business environment factors, are ranked first to third. In the ANP technique, the principal components, i.e., economic, technology, project productivity factors, and in the criteria section, the factors of the competitive business environment, environment, and social costs, are ranked first to third. This comparison shows that the existence of dependencies between the principal components is effective in prioritizing the elements. [ABSTRACT FROM AUTHOR] |
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