1. Modeling and significance assessment of road construction participant and user benefits using expert evaluation methods
- Author
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Henrikas Sivilevičius, Audrius Vaitkus, and Donatas Čygas
- Subjects
road engineers ,road users ,benefits ,modelling ,expert evaluation ,criteria weighting ,Economic growth, development, planning ,HD72-88 ,Business ,HF5001-6182 - Abstract
Human activities are related to obtain economic, technical, social and environmental benefits. The road construction process participants and road users have direct or indirect benefits from elaboration of new infrastructure. The number of the benefits received by individual entities is publicly discussed by politicians, lobbyists, experts and other decision-makers without having quantitative estimates of benefits, i.e., often relying on intuition or considering theoretical reasoning. The paper suggests a system of 19 benefit entities (criteria) assigned the ranks given by experts. The study involved three categories of experts, including 35 road engineers, 36 transport engineers and 61 road users. The values of the concordance coefficients obtained as a result of the conducted research were found significantly higher than critical values and showed that the opinions of the experts in each category were consistent (not contradictory). This made it possible to consider the average of the opinions of the expert group as a reliable result of solving the problem. Rank averages were replaced by the normalized weights of criteria using Average Rank Transformation into Weight-Linear (ARTIW-L) and – Nonlinear (ARTIW-N) methods. The global averages of criterion weights were used employing the Inverse Hierarchy for Assessment Main Criteria Importance (IHAMCI) method thus calculating the normalized weights of the road-related classified entities (three main criteria). The findings prove that road users benefit the most (weight 0.3485), the road construction contractor (weight 0.3325) is in the next position and the road owner (investor) takes the weight equal to 0.3190. The generated research data can be used for justifying the rationality of road investment.
- Published
- 2024
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