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The method of policy capturing for the transportation disadvantaged: simulation results

机译:弱势交通运输政策捕捉方法:仿真结果

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In the previous study called "A Modelling Approach for the Transportation Disadvantaged", which was an experimental one calibrated in a small town in Turkey, it was observed that an integrated TPM for the disadvantaged category was probable, and the findings were observable at all stages of the sequential modelling, however, with slight differences compared to the Normal model's results. Following the previous one, this study shows the method of how "policy capturing" could be possible on the basis of these differences, which aims to help improve the adverse conditions of the disadvantaged. The method is sort of category analysis based on the cluster analysis results, since it is clearly verified that the "disadvantage indices" identified as the single-disadvantage groups match with the values of cluster centres. Using TRANUS software, three simulations are run for three dimensions of disadvantage: socio-economic (categorical), spatial and the positional. The simulation results, evaluated from different criteria, showed that socio-economic dimension was the most fruitful area for policy capturing.
机译:在先前的研究中,“在交通运输中处于不利地位的一种建模方法”是在土耳其的一个小镇上进行的一项实验性校准,发现有可能对弱势群体进行综合TPM,并且在各个阶段都可以观察到发现但是,与普通模型的结果相比,顺序建模的结果略有差异。在前一个研究的基础上,本研究显示了在这些差异的基础上如何实现“政策俘获”的方法,旨在帮助改善弱势群体的不利条件。该方法是一种基于聚类分析结果的类别分析,因为可以清楚地验证被识别为单劣组的“劣势指标”与聚类中心的值匹配。使用TRANUS软件,针对不利的三个维度进行了三个模拟:社会经济(分类),空间和位置。从不同标准进行评估的模拟结果表明,社会经济维度是最有效的政策制定领域。

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