Innovative Applications of O.R.Project rankings for participatory budget based on the fuzzy TOPSIS method
Introduction
A participatory budget (PB) is a group decision-making process where citizens distribute public resources among a set of proposed projects. PB is highly beneficial for multiple parties because: it enables people to shape the local budget, municipalities obtain clear information about social priorities, it helps to integrate local communities and motivates them to cooperate, it educates citizens about costs, and it constrains local investments. All of these benefits have helped PB to grow in terms of the number of processes and budget limits. The present study investigated Polish PBs. Based on this study, we can describe a typical PB in Poland according to four steps: (1) a city announces the PB; (2) citizens propose projects; (3) the city verifies the proposals and formulates the final ballots; and, finally, (4) the citizens vote for projects. We found that major Polish cities included more than 100 projects in their ballots and people only had to choose 3–7, so the winners were usually selected by majority rule. However, this method causes high dispersion of the votes among multiple alternatives, where large numbers of people may vote for less popular projects and the process is completed without any project winning. Despite those issues majority rule has great advantage - it is easy to understand and scale. Complicated decision support systems could solve money distribution problem but people would lost trust to the system. We see our solution as a recommendation system that helps people with information overload during the voting. According to Malhotra (1984), negative effects start with 10 or more options while in PB we have around 100 options. Recommendation system helps people to get familiar with potentially interesting projects instead of scanning all titles. Final solution should rank projects by different criteria: category, potential beneficiaries, location and cost. Final decision belongs to the participant.
In order to build such a system for PB, an algorithm is essential for ranking projects, which was the focus of the present study. Thus, we propose automated comparisons of PB projects using the “Technique for Order Preference by Similarity to Ideal Solution” (TOPSIS) method. 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 such as topic, location, and beneficiaries. The TOPSIS method minimizes 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 of the TOPSIS method required for PB is that the objective perfect solution does not exist 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.
The remainder of this paper is organized as follows. First, we briefly describe the PBs. Next, we present an overview of DSS systems and fuzzy TOPSIS with preliminary definitions. In Section 4, we describe the application of the modified TOPSIS method to PB projects. We then present examples based on the Poznań PB project set. In the final section, we discuss the results obtained.
Section snippets
Development
PB has its origins in Latin America but it has recently become widespread. Nelson Dias (2014) identified five stages of PB growth: trial period (local experiments in Brazil, 1989–1997); Brazilian PB (140 municipalities adopted PB, 1997–2000); Latin American and European expansion (2000–2007); national and international PB networks (2007–2008); and “jumping off the scale” (after 2008). At present, we are in the last stage where PB has become part of more complex participatory systems. The
Multi-criteria decision analysis based on the TOPSIS method
One of the most widely used multi-criteria decision analysis methods is the TOPSIS method, which was proposed by Hwang and Yoon in 1981, and extended by Yoon in 1987, as well as by lai Hwang, jou Lai, and yun Liu in 1993. In the TOPSIS method, the optimal alternative is nearest to the positive ideal solution (PIS) and farthest from the negative ideal solution (NIS). A comparison of different methods for the multiple criteria decision problem can be found in Zanakis, Solomon, Wishart, and
TOPSIS for ranking PB projects
In this section, we present a modified fuzzy TOPSIS method for ranking PB projects. The main components for decision making are as follows.
The goal is to rank participatory budget projects according to participant first choice (PIS).
Decision-makers are city residents and temporarily resident citizens such as students.
Alternatives are different projects that could be implemented. The proposals are submitted by citizens and described in a rather general manner.
Criteria It is difficult to
Examples from the Poznań project set
We tested the performance of the algorithm based on examples from recent PB projects in Poznań (PO2016). In this process, people proposed 267 (120 citywide and 147 district) projects. The vote count was (total) 73 136, which comprised 52 997 (72.46%) electronic and 20 139 (27.54%) paper votes. The number of valid votes was 66 124 (90.41%). The budget was 15 million PLN6 and it was divided as follows: 5 million PLN for citywide projects and 2 million PLN ×
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 Poznań. The application of TOPSIS to PBs required some major changes to the algorithm, i.e., the
References (48)
e-negotiation systems for e-participation
Advances in group decision and negotiation
(2010)Extensions of the TOPSIS for group decision-making under fuzzy environment
Fuzzy Sets and Systems
(2000)- et al.
A statistical comparative study of different similarity measures of consensus in group decision making
Information Sciences
(2013) - et al.
A common framework for deriving preference values from pairwise comparison matrices
Computers & Operations Research
(2004) - et al.
A gis-based multicriteria spatial decision support system for planning urban infrastructures
Decision Support Systems
(2011) - et al.
Similarity and compatibility in fuzzy set theory: Assessment and applications
(2002) - et al.
Methodology for participatory policy analysis
European Journal of Operational Research
(2001) - et al.
On deciding how to decide: Designing participatory budget processes
European Journal of Operational Research
(2013) - et al.
A participatory budget model under uncertainty
European Journal of Operational Research
(2016)
Multi-criteria decision analysis in environmental sciences: Ten years of applications and trends
The Science of the Total Environment
A new approach for multiple objective decision making
Computers and Operations Research
A generic negotiation model for MAS using XML
Proceedings of the IEEE international conference on systems, man and cybernetics
Internet GIS for public participation
Environment and Planning B: Planning and Design
An analytical solution to fuzzy TOPSIS and its application in personnel selection for knowledge-intensive enterprise
Applied Soft Computing
Transnational models of citizen participation: The case of participatory budgeting
Journal of Public Deliberation
A fuzzy hybrid project portfolio selection method using data envelopment analysis, TOPSIS and integer programming
Expert Systems with Applications
Designing electronic auctions: An internet-based hybrid procedure combining aspects of negotiations and auctions
Electronic Commerce Research
The concept of a linguistic variable and its application to approximate reasoning-I
Information Science
Multi-attribute decision making: A simulation comparison of select methods
European Journal of Operational Research
Compare and contrast analysis to the development pattern of energy producing provinces with the aim of carbon emission reducing
Proceedings of the international conference on management and service science
Metrics for ranking ontologies
CEUR workshop proceedings
A new method for elicitation of criteria weights in additive models: Flexible and interactive tradeoff
European Journal of Operational Research
Using TOPSIS for assessing the sustainability of government bond funds
Omega
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2021, European Journal of Operational ResearchCitation Excerpt :In order to extend the comparative analysis and make the discussion broader to the decision-making science, the results were compared with a multicriteria method that is not based on prospect theory, namely the Technique for Order of Preference by Similarity to the Ideal Solution (TOPSIS) method (Hwang & Yoon, 1981). This method was selected since it is one of the most widely used MCDM method (Walczak & Rutkowska, 2017) and also because it is recognized in the literature as having high prediction capacity in comparative studies with others MCDM methods (Caterino, Iervolino, Manfredi & Cosenza, 2009; Kolios et al., 2016; Leoneti, 2016; Thor, Ding & Kamaruddin, 2013; Widianta, Rizaldi, Setyohadi & Riskiawan, 2018; Yeh, 2002). Following the introduction, the second section of the present paper details the original TODIM and TOPSIS methods and their variations.