Municipal Public Budget Planning with Sustainable and Human Development Goals Integrated in a Multi-Criteria Approach
Abstract
:1. Introduction
2. Materials and Methods
- Establishing the intention of the research: the definition of the research problem or theme.
- Preliminary exploratory research (keywords in databases): After the research theme has been defined, the next phase is to carry out preliminary research in order to choose and test the adherence of possible keywords.
- The definition and combination of keywords and databases.
- Searching in the databases.
- Filtering procedures: In this phase, the raw bibliographic portfolio is remodeled in order to exclude works that are repeated, or which do not adhere to the research theme.
- Identifying the impact factor, year of publication and number of citations: at this stage, the data regarding the impact factor of the journal in which the work was published and the number of citations are collected. The impact factor indicates the relevance of the journal in which the work was published, and the number of citations indicates the scientific recognition of its authors [23].
- Ranking of the papers based on the InOrdinatio Index: With data from the previous step, the Ordinatio Index (InOrdinatio) of each article is calculated, according to Equation (1):
- IF: Impact Factor;
- Ry: Research year;
- Py: Publication year;
- Nc: Number of citations.
- 8.
- Finding the full papers: The papers are downloaded from the databases.
- 9.
- The final reading and systematic analysis of the papers: Finally, the articles selected from the bibliographic portfolio are read in full.
- Calculate the non-normalized weights k = (k1, k2, · · ·, ); let be the number of non-criteria between the ranks r and r + 1.
- 2.
- Calculate the normalized weights k* = ; let ci be the number of criteria in each ranking i, where 1 ≤ i ≤ . The normalized weights k* are calculated as follows in Equation (8):
3. Results
3.1. Systemic Analysis
3.1.1. Approach Lens
3.1.2. Singularity Lens
3.1.3. Identification Lens
3.1.4. Measurement Lens
3.1.5. Integration Lens
3.1.6. Management Lens
4. Discussion
4.1. Municipal Budget, Costs and Sustainability
4.2. Systematic Analysis of the Lenses
4.3. Contributions from Papers with High Adherence to the Theme
4.4. Sorting Procedure—ELECTRI TRI Method
5. Final Remarks
- (a)
- The use of values reported by decision makers (municipal manager and population) in the construction of a decision matrix and the application of multi-criteria methods to find the best budget allocation according to these stakeholders’ preferences. The biggest challenge is the use of the opinion of the decision makers, who are representatives of the population, without political or personal interests. Considering methodologically efficient tools and scientifically strong factors for decision-making is fundamental for the achievement of the municipality’s growth and wellbeing goals. In this sense, the multi-criteria approach can offer great advantages by satisfactorily weighting the involved parts favoring the main objective.
- (b)
- The recognition of the decision makers’ knowledge limits and aligning the recognition of these limits for application in popular participatory budget projects. The inclusion of participatory budgeting in municipalities’ decision-making encourages the creation of laws so that the population is also included, and public budget decision-making models can be developed efficiently.
- (c)
- The development of structures that use multi-criteria methods to choose budget distribution priorities, and that use statistical elements by ordinal and cardinal measurement scales. Thus, managers could control the budget distribution and the economic crises that lead to the scarcity of resources. Multi-criteria models are recommended for their ability to integrate factors and consider several alternatives in the budget distribution problem.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A
Paper | (Titles/Journals/Authors) | Impact Factor | Quantity of Citations | InOrdinatio Index |
---|---|---|---|---|
1 |
| 10.56 | 40 | 110 |
2 |
| 2.592 | 6 | 96 |
3 |
| 1.777 | 5 | 95 |
4 |
| 2.592 | 3 | 93 |
5 |
| 2.592 | 13 | 93 |
6 |
| 2.592 | 2 | 92 |
7 |
| 1.687 | 1 | 91 |
8 |
| 1.123 | 1 | 91 |
9 |
| 2.592 | 0 | 90 |
10 |
| 0 | 0 | 90 |
11 |
| 0.455 | 1 | 81 |
12 |
| 0.112 | 0 | 80 |
13 |
| 3.898 | 26 | 76 |
14 |
| 0.217 | 0 | 60 |
15 |
| 0.162 | 2 | 52 |
Papers/Authors | SUM of Values | Lens APPROACH | Lens SINGULA- RITY | Lens IDENTIFI- CATION | Lens MEASUREMENT | Lens INTEGRA- TION | Lens MANAGE- MENT | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Criterion aspects for the Lenses | 1 | 2 | 3 | 4 | 1 | 2 | 3 | 1 | 2 | 3 | 1 | 2 | 1 | 2 | 1 | 2 | |
1. Cucchiella, et al., 2017 [31] | 8 | 2 | 0 | 0 | 2 | 2 | 2 | ||||||||||
2. Raszkowski, A. and Bartniczak, B., 2019 [5] | 6 | 2 | 0 | 0 | 2 | 0 | 2 | ||||||||||
3. Yi, P., Dong, Q. and Li, W., 2019 [32] | 8 | 2 | 0 | 0 | 2 | 2 | 2 | ||||||||||
4. Yi, P., Li, W. and Zhang, D., 2019 [9] | 8 | 2 | 0 | 0 | 2 | 2 | 2 | ||||||||||
5. Alinska, A., Filipiak, B.Z. and Kosztowniak, A., 2018 [8] | 7 | 2 | 1 | 0 | 2 | 0 | 2 | ||||||||||
6. Liu, T., Li, J., Chen, J. and Yang, S., 2019 [31] | 8 | 2 | 0 | 0 | 2 | 2 | 2 | ||||||||||
7.da Rosa, F.S., Lunkes, R.J. and Saviatto, K., 2019 [2] | 8 | 2 | 0 | 0 | 2 | 2 | 2 | ||||||||||
8. Moschen, et al., 2019 [3] | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ||||||||||
9. Zhou, Y., Li, W., Yi, P. and Gong, C., 2019 [30] | 7 | 1 | 0 | 0 | 2 | 2 | 2 | ||||||||||
10. Coronado, F., 2019 [39] | 4 | 2 | 0 | 0 | 0 | 0 | 2 | ||||||||||
11. Hendriks, C.J., 2018 [17] | 4 | 2 | 0 | 0 | 0 | 0 | 2 | ||||||||||
12. Pourshahabi, et al., 2018 [6] | 12 | 2 | 2 | 2 | 2 | 2 | 2 | ||||||||||
13. Chen, X., Liu, X. and Hu, D., 2015 [37] | 8 | 2 | 0 | 0 | 2 | 2 | 2 | ||||||||||
14. Liu, C., 2016 [40] | 7 | 1 | 0 | 0 | 2 | 2 | 2 | ||||||||||
15. Amin, S.R. and Tamima, U., 2015 [33] | 8 | 2 | 0 | 0 | 2 | 2 | 2 | ||||||||||
Number of occurrences (papers in lenses) | 12 | 2 | 0 | 1 | 1 | 1 | 13 | 1 | 0 | 14 | 12 | 3 | 10 | 5 | 14 | 1 | |
Percentage (%) = Number of occurrences/Total of papers | 80 | 13 | 0 | 7 | 7 | 7 | 86 | 7 | 0 | 93 | 80 | 20 | 67 | 33 | 93 | 7 | |
Maximum percentage for the positive aspect (%)—Criterion 1 | 80.0% | 7.0% | 7.0% | 80.0% | 67.0% | 93.0% |
Rank (r) | Criteria in the Rank (r) | Number of Criteria According to Rank (r) | Positions | Non-Normalized Weights (kr)% | Normalized Weights % | Total % | Adjustment % |
---|---|---|---|---|---|---|---|
1 | 1,4,5,6 | 4 | (1+2+3+4) ÷4 ÷→ | 2.50 | 0.20 | 0.78 | 0.77 |
2 | 1,4,6 | 3 | (5+6+7) ÷3 → | 6.00 | 0.47 | 1.41 | 1.39 |
3 | 1,4,5,6 | 4 | (8+9+10+11)÷4 → | 9.50 | 0.75 | 2.98 | 2.93 |
4 | 1,4,5,6 | 4 | (12+13+14+15)÷4 → | 13.50 | 1.06 | 4.24 | 4.17 |
5 | 1,4,6 | 3 | (16+16+18)÷3 → | 16.67 | 1.31 | 3.92 | 3.86 |
6 | 1,4,5,6 | 4 | (19+20+21+22)÷4 → | 20.50 | 1.61 | 6.43 | 6.33 |
7 | 1,4,5,6 | 4 | (23+24+25+26)÷4 → | 24.50 | 1.92 | 7.69 | 7.56 |
8 | - | 0 | 27 | 0.00 | 0.00 | 0.00 | 0.00 |
9 | 4,5,6 | 3 | (28+29+30)÷3 → | 29.00 | 2.27 | 6.82 | 6.71 |
10 | 1,6 | 2 | (31+32)÷2 → | 31.50 | 2.47 | 4.94 | 4.86 |
11 | 1,6 | 2 | (33+34)÷2 → | 33.50 | 2.63 | 5.25 | 5.17 |
12 | 1,2,3,4,5,6 | 6 | (35+36+37+38+39+40)÷6 → | 37.50 | 2.94 | 17.65 | 17.36 |
13 | 1,4,5,6 | 4 | (41+42+43+44)÷4 → | 42.50 | 3.33 | 13.33 | 13.12 |
14 | 4,5,6 | 3 | (45+46+47)÷3 → | 46.00 | 3.61 | 10.82 | 10.65 |
15 | 1,4,5,6 | 4 | (48+49+50)÷3 → | 49.00 | 3.84 | 15.37 | 15.12 |
Sum of Positions | 1275 | 101.65 | 100.00 |
Legend | % | % | |
---|---|---|---|
Approach | 1 | 22.16 | 21.88 |
Singularity | 2 | 2.89 | 2.86 |
Identification | 3 | 2.89 | 2.86 |
Measurement | 4 | 22.93 | 22.64 |
Integration | 5 | 22.47 | 22.18 |
Management | 6 | 27.94 | 27.59 |
101.29 | 100.00 |
Classes | Adherence | Border | Approach | Singularity | Identification | Measurement | Integration | Management | Sum |
---|---|---|---|---|---|---|---|---|---|
Class1 | High | b1 | 3 | 2 | 2 | 3 | 2 | 3 | |
Class2 | Medium | b2 | 1 | 1 | 1 | 1 | 1 | 1 | |
Class3 | Low | b3 | 0 | 0 | 0 | 0 | 0 | 0 | |
Number of Occurrences | 12 | 1 | 1 | 12 | 10 | 14 | 50 | ||
Weights by Simos’ procedure | 21.88% | 2.86% | 2.86% | 22.64% | 22.18% | 27.59% | 100% |
Papers | Pessimist Sorting | Optimist Sorting | Level of Adherence | SUM (Table A2) | Ordinatio Index | Contributions |
---|---|---|---|---|---|---|
1 | Class C | Class A | High | 8 | 110 | It assessed the sustainability performance and presented a comparison among European countries from the environmental and energy perspectives using Eurostat and Analytical Hierarchy Process (AHP) method. |
2 | Class C | Class B | Medium | 6 | 96 | |
3 | Class C | Class A | High | 8 | 95 | It assessed the sustainability of 17 cities in Shandong Province, China. A set of 21 indicators was selected from the economic, social and environmental dimensions. The criteria weights were calculated using the deviation maximization (DM) method to highlight the overall difference between the alternatives |
4 | Class C | Class A | High | 8 | 93 | It investigated the sustainability of 13 cities in the Capital Economic Circle using three dimensions: economy, society and environment. The Induced Ordered Weighted Average (IOWA) operator was used for aggregation of criteria |
5 | Class C | Class B | Medium | 7 | 93 | |
6 | Class C | Class A | High | 8 | 92 | It provided a method for the quantitative study of sustainable urban development, and also provided some decision-making references for improving urban ecological efficiency in Henan Province |
7 | Class C | Class A | High | 8 | 91 | It analyzed the effects of the public resources uses and training for the sustainable development in Brazilian municipalities using structural equation modeling method with PLS (Partial Least Squares) |
8 | Class C | Class C | Low | 0 | 91 | |
9 | Class C | Class A | High | 7 | 90 | It incorporated the behavior of decision makers into an model and proposed a weighting method, considering the distribution of data to guide cities to develop the goals established for sustainability. The model was applied in 14 cities in Liaoning, China from 2015 to 2017 |
10 | Class C | Class B | Medium | 4 | 90 | |
11 | Class C | Class B | Medium | 4 | 81 | |
12 | Class B | Class A | High | 12 | 80 | It identified and prioritized the components of sustainable development that influenced and improved the level of development in a case study of provinces in the Iran, using the hierarchical analysis method (AHP) |
13 | Class C | Class A | High | 8 | 76 | It assessed the performance of Sustainable Objectives from 2005 to 2012, considering a pilot Sustainable Objective construction city in China-Wuhan. |
14 | Class C | Class A | High | 7 | 60 | It analyzed the key components of sustainable development in the city of Huangshi, a resource-depleted city in Hubei province between 2000 and 2014 |
15 | Class C | Class A | High | 8 | 52 | It proposed a Sustainable Urban Development Indicator (SUDI) for each urban community of Montreal to assess sustainable development plans |
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Thesari, S.S.; Lizot, M.; Trojan, F. Municipal Public Budget Planning with Sustainable and Human Development Goals Integrated in a Multi-Criteria Approach. Sustainability 2021, 13, 10921. https://doi.org/10.3390/su131910921
Thesari SS, Lizot M, Trojan F. Municipal Public Budget Planning with Sustainable and Human Development Goals Integrated in a Multi-Criteria Approach. Sustainability. 2021; 13(19):10921. https://doi.org/10.3390/su131910921
Chicago/Turabian StyleThesari, Shirley Suellen, Mauro Lizot, and Flavio Trojan. 2021. "Municipal Public Budget Planning with Sustainable and Human Development Goals Integrated in a Multi-Criteria Approach" Sustainability 13, no. 19: 10921. https://doi.org/10.3390/su131910921