Advertisement

Soft Computing

, Volume 23, Issue 10, pp 3327–3345 | Cite as

A group decision process based on expert analysis and criteria coalition to measure municipalities’ financial distress

  • Manuel A. Fernández
  • Elías Bendodo
  • José R. SánchezEmail author
  • Francisco E. Cabrera
Methodologies and Application
  • 142 Downloads

Abstract

The aim of this work is to propose a new operating model to evaluate municipalities’ financial distress, based on the analysis of experts and the synergies between the variables that are evaluated in the process. For such purpose, the methodology of decision-making in multi-criteria group will be used, which is implemented by combining the hierarchical analytic process, the Choquet integral, the majority operator, and linguistic information. This new model has been applied to a sample of 120 Spanish municipalities and has allowed the assessment of their financial situation in a powerful manner using a set of variables corresponding to the year 2015. Given the flexibility of the proposed model, the above-mentioned application could be useful for assessing the financial capacity of municipalities in any international context.

Keywords

Local governments Financial distress AHP Criteria coalitions Expert analysis Fuzzy logic 

Notes

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

References

  1. Aczél J, Saaty TL (1983) Procedures for synthesizing ratio judgements. J Math Psychol 27(1):93–102MathSciNetCrossRefzbMATHGoogle Scholar
  2. Ahmad N, Laplante PA (2007) Reasoning about software using metrics and expert opinión. Innov Syst Softw Eng 3:229–235CrossRefGoogle Scholar
  3. Akkoç S, Vatansever K (2013) Fuzzy performance evaluation with AHP and topsis methods: evidence from Turkish banking sector after the global financial crisis. Eur J Bus Econ 6(11):53–74Google Scholar
  4. Alter TR, McLaughlin DK, Melniker NE (1984) Analysing local government fiscal capacity. Pennsylvania State University Cooperative Extension Service, University ParkGoogle Scholar
  5. Bernal R, Karanik M, Peláez JI (2015) Fuzzy measure identification for criteria coalitions using linguistic information. Soft Comput 20(4):1315–1327CrossRefGoogle Scholar
  6. Blair AR, Mandelker GN, Saaty TL, Whitaker R (2010) Forecasting the resurgence of the U.S. economy in 2010: an expert judgment approach. Socio Econ Plan Sci 44:114–121CrossRefGoogle Scholar
  7. Cabaleiro R, Buch E, Vaamonde A (2012) Developing a method to assessing the municipal financial health. Am Rev Publ Adm 43(6):729–751CrossRefGoogle Scholar
  8. Cabrerizo FJ, Herrera-Viedma E, Pedrycz W (2013) A method based on PSO and granular computing of linguistic information to solve group decision making problems defined in heterogeneous contexts. Eur J Oper Res 230(3):624–633MathSciNetCrossRefzbMATHGoogle Scholar
  9. Cabrerizo FJ, Chiclana F, Al-Hmouz R, Morfeq A, Balamash AS, Herrera-Viedma E (2015) Fuzzy decision making and consensus: challenges. J Intell Fuzzy Syst 29(3):1109–1118MathSciNetCrossRefzbMATHGoogle Scholar
  10. Cabrerizo FJ, Al-Hmouz R, Morfeq A, Balamash AS, Martínez MA, Herrera-Viedma E (2017) Soft consensus measures in group decision making using unbalanced fuzzy linguistic information. Soft Comput 21(11):3037–3050CrossRefzbMATHGoogle Scholar
  11. Carmeli A, Cohen A (2001) The financial crisis of the local authorities in Israel: a resource-based analysis. Publ Adm 79(4):893–913CrossRefGoogle Scholar
  12. Choquet G (1954) Theory of capacities. Ann Inst Fourier 5:131–295MathSciNetCrossRefzbMATHGoogle Scholar
  13. Cohen S, Doumpos M, Neofytou E, Zopounidis C (2012) Assessing financial distress where bankruptcy is not an option: an alternative approach for local municipalities. Eur J Oper Res 218:270–279CrossRefGoogle Scholar
  14. Cohen S, Costanzo A, Manes-Rossi F (2017) Auditors and early signals of financial distress in local governments. Manag Audit J 32(3):234–250CrossRefGoogle Scholar
  15. Dollery B, Crase L, Byrnes J (2006) Local government failure: Why does Australian local government experience permanent financialausterity? Aust J Polit Sci 41(3):339–353CrossRefGoogle Scholar
  16. Doumpos M, Cohen S (2014) Applying data envelopment analysis on accounting data to assess and optimize the efficiency of Greek local governments. Omega 46:74–85CrossRefGoogle Scholar
  17. Durán O, Aguilo J (2008) Computer-aided machine-tool selection based on a fuzzy-AHP approach. Exp Syst Appl 34:1787–1794CrossRefGoogle Scholar
  18. Fawcett T (2006) An introduction to ROC analysis. Pattern Recognit Lett 27:861–874CrossRefGoogle Scholar
  19. Galariotis E, Guyot A, Doumpos M, Zopounidis C (2016) A novel multi-attribute benchmarking approach for assessing the financial performance of local governments: empirical evidence from France. Eur J Oper Res 248:301–317CrossRefzbMATHGoogle Scholar
  20. García-Díaz V, Pascual J, González R, Pelayo BC, Bustelo G, Cueva JM (2017) An approach to improve the accuracy of probabilistic classifiers for decision support systems in sentiment analysis. Appl Soft Comput.  https://doi.org/10.1016/j.asoc.2017.05.038 Google Scholar
  21. García-Sánchez IM, Cuadrado-Ballesteros B, Frías-Aceituno JV, Mordan N (2012) A new predictor of local financial distress. Int J Publ Adm 35(11):739–748CrossRefGoogle Scholar
  22. Gómez-Ruiz JA, Karanik M, Peláez JI (2010) Estimation of missing judgments in AHP pairwise matrices using a neural network-based model. Appl Math Comput 216(10):2959–2975MathSciNetzbMATHGoogle Scholar
  23. Gorina E, Maher C, Joffe M (2017) Local fiscal distress: measurement and prediction. Publ Budg FinanceGoogle Scholar
  24. Harker PT (1987) Incomplete pairwise comparisons in the analytic hierarchy process. Math Model 9(11):837–48MathSciNetCrossRefGoogle Scholar
  25. Hendrick R (2004) Assessing and measuring the fiscal heath of local governments. Urban Aff Rev 40(1):78–114CrossRefGoogle Scholar
  26. Honalde BW (2003) The states’ role in US local government fiscal crises: a theoretical model and results of a national survey. Int J Publ Adm 26(13):1431–1472CrossRefGoogle Scholar
  27. Honadle BW, Costa JM, Cliger BA (2004) Fiscal health for local governments: an introduction to concepts, practical analysis, and strategies. Elsevier Academic Press, San DiegoGoogle Scholar
  28. Hu YC, Tsai JF (2006) Backpropagation multi-layer perceptron for incomplete pairwise comparison matrices in analytic hierarchy process. Appl Math Comput 180(1):53–62MathSciNetzbMATHGoogle Scholar
  29. Jones S, Walker R (2007) Explanators of local government distress. Abacus 43(3):396–418CrossRefGoogle Scholar
  30. Karanik M, Peláez JI, Bernal R (2016) Selective majority additive ordered weighting averaging operator. Eur J Oper Res 250(3):16–26MathSciNetCrossRefzbMATHGoogle Scholar
  31. Kloha P, Weissert CS, Kleine R (2005) Developing and testing a composite model to predict local fiscal distress. Publ Adm Rev 65(3):313–323CrossRefGoogle Scholar
  32. Lamata MT, Peláez JI (2002) A method for improving the consistency of judgements. Int J Uncertain Fuzziness Knowl Based Syst 10(6):677–686MathSciNetCrossRefzbMATHGoogle Scholar
  33. La Red DL, Peláez JI, Doña JM, Fernández EB (2011) WKC-OWA: a new neat-OWA operator to aggregate information in democratic decision problems. Int J Uncertain Fuzziness Knowl Based Syst 19(5):759–779MathSciNetCrossRefGoogle Scholar
  34. Lara-Rubio J, Rayo-Cantón S, Navarro-Galera A, Buendía-Carrillo D (2017) Analysing credit risk in large local governments: an empirical study in Spain. Local Gov Stud 43(2):194–217CrossRefGoogle Scholar
  35. Liao X, Liu Y (2014) Local fiscal distress and investment efficiency of local SOEs. China J Acc Res 7(4):119–147Google Scholar
  36. Lo SC, Sudjatmika FV (2016) Solving multi-criteria supplier segmentation based on the modified FAHP for supply chain management: a case study. Soft Comput 20(12):4981–4990CrossRefGoogle Scholar
  37. Morente-Molinera JA, Mezei J, Carlsson C, Herrera-Viedma E (2017a) Improving supervised learning classification methods using multi-granular linguistic modelling and fuzzy entropy. IEEE Trans Fuzzy Syst 25(5):1078–1089CrossRefGoogle Scholar
  38. Morente-Molinera JA, Kou G, González-Crespo R, Corchado JM (2017b) Solving multi-criteria group decision making problems under environments with a high number of alternatives using fuzzy ontologies and multi-granular linguistic modelling methods. Knowl Based Syst 137:54–64CrossRefGoogle Scholar
  39. Navarro-Galera A, Rayo-Cantón S, Lara-Rubio J, Buendía-Carrillo D (2015) Loan price modelling for local governments using risk premium analysis. Appl Econ 47(58):6257–6276CrossRefGoogle Scholar
  40. Navarro-Galera A, Rodríguez-Bolívar MP, Alcaide-Muñoz L (2016) Measuring the financial sustainability and its influential factors in local governments. Appl Econ 10(1080/00036846):1148260Google Scholar
  41. Peláez JI, Lamata MT (2003) A new measure of consistency for positive reciprocal matrices. Comput Math Appl 46(12):1839–1845MathSciNetCrossRefzbMATHGoogle Scholar
  42. Peláez JI, Bernal R, Karanik M (2016) Majority OWA Operator for opinion rating in social media. Soft Comput 20(3):1047–1055CrossRefGoogle Scholar
  43. Pérez LG, Mata F, Chiclana F, Kou G, Herrera-Viedma E (2016) Modelling influence in group decision making. Soft Comput 20(4):1653–1665CrossRefGoogle Scholar
  44. Pina V, Torres L, Yetano A (2009) Accrual accounting in EU local governments: one method, several approaches. Eur Acc Rev 18(4):765–807CrossRefGoogle Scholar
  45. Rowe G, Wright G (2001) Principles of forecasting. A handbook for researchers and practitioners. Expert opinions in forecasting: the role of the delphi technique. Springer, New York, pp 125–144Google Scholar
  46. Saaty TL (1980) The analytic hierarchy process. McGraw-Hill, New YorkzbMATHGoogle Scholar
  47. Tribunal de Cuentas (2016) www.rendiciondecuentas.es
  48. Turley G, Robbins G, McNena S (2015) A framework to measure the financial performance of local governments. Local Gov Stud 41(3):401–420CrossRefGoogle Scholar
  49. Wang JQ, Wu JT, Wang J, Zhang HY, Chen XH (2016) Multi-criteria decision-making methods based on the Hausdorff distance of hesitant fuzzy linguistic numbers. Soft Comput 20(4):1621–1633CrossRefGoogle Scholar
  50. Zhang H, Dong Y, Herrera-Viedma E (2017) Consensus building for the heterogeneous large-scale GDM with the individual concerns and satisfactions. IEEE Trans Fuzzy Syst. https://doi.org/10.1109/TFUZZ.2017.2697403 (in press)
  51. Zafra-Gómez JL, López-Hernández AM, Hernández-Bastida A (2009) Developing a model to measure financial condition in local government. Am Rev Publ Adm 39(4):425–449CrossRefGoogle Scholar
  52. 2/2012 Act, April 27th, on budgetary stability and financial sustainability. Official State Gazette no. 103, April 30th, 2012, pp 32653–32675Google Scholar
  53. 8/2013 Act, 28th June, on urgent measures to aid the default of public administration and to support local entities with financial problems. Official State Gazette no. 155, June 29th, 2013, pp 48782–48811Google Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2017

Authors and Affiliations

  • Manuel A. Fernández
    • 1
  • Elías Bendodo
    • 2
  • José R. Sánchez
    • 1
    Email author
  • Francisco E. Cabrera
    • 3
  1. 1.Department of Finance and AccountingUniversity of MalagaMalagaSpain
  2. 2.Interuniversity PhD programUniversity of MalagaMalagaSpain
  3. 3.Department of Languages and Computer SciencesUniversity of MalagaMalagaSpain

Personalised recommendations