ترجمه مقاله نقش ضروری ارتباطات 6G با چشم انداز صنعت 4.0
- مبلغ: ۸۶,۰۰۰ تومان
ترجمه مقاله پایداری توسعه شهری، تعدیل ساختار صنعتی و کارایی کاربری زمین
- مبلغ: ۹۱,۰۰۰ تومان
Abstract
In this study, a fuzzy technique is proposed for order preference based on the similarity to an ideal solution for the personalized ranking of projects in a participatory budget (PB). A PB is a group decision-making process where citizens distribute public resources among a set of city investment proposals. The dynamic growth in the popularity of PB during the last 10 years has been due to a significant increase in the number of projects submitted and the demonstrable weakness of the traditional majority vote. The rationality of decision-makers is restricted by the large number of possible options from which voters can choose only a few within a limited amount of time, and thus there is no opportunity to review all of the projects. Appropriate decision support tools can assist with the selection of the best outcome and help to address the growth of PB processes. The ranking of PB projects is a specific problem because multi-criteria comparisons are based on non-quantitative criteria, i.e., nominal and fuzzy criteria. The “Technique for Order Preference by Similarity to Ideal Solution” (TOPSIS) method aims to minimize the distance to the ideal alternative while maximizing the distance to the worst. In a fuzzy extension of TOPSIS, the ratings of alternatives and the weights of the criteria are fuzzy numbers or linguistic variables. The major modification required to the TOPSIS method for PB is that the perfect objective solution does not exists among the maximum and minimum values for the criteria. Thus, the subjective choice is the ideal solution for the decision maker and the negative ideal solution is the most dissimilar solution. This study describes the application of fuzzy TOPSIS with a modification for PB based on an empirical example from a Poznan PB project (Poland).
6. Summary
The importance of PBs has increased significantly in the last 10 years. However, the sudden and dynamic growth of PBs has highlighted the need for DSSs in this area. The key problem with PBs is that the ranking methods used for projects do no employ quantitative assessment criteria. In this study, we proposed a modified fuzzy TOPSIS method for PBs, which we illustrated using real-world data from Poznan. The application of TOPSIS to PBs required some major changes to the algorithm, i.e., the transition to relative values (distance) depends on the initial choice of the voter and the criteria are modelled as fuzzy or categorical values, where the distances are calculated basis on the proposed classifications. At present, the ranking results are being tested by the test group. In further research, we plan to extend the classification to include the degree of membership for each class and we aim to apply the algorithm in a new voting process.