Social Indicators Research

, Volume 117, Issue 1, pp 257–274 | Cite as

Building Weighted-Domain Composite Indices of Life Satisfaction with Data Envelopment Analysis

  • Jorge GuardiolaEmail author
  • Andrés J. Picazo-Tadeo


The specialised literature has frequently addressed the relationship between life domains and people’s satisfaction with life. Some researchers have posed questions regarding the importance of domains, therefore interpreting them as weightings and creating domain satisfaction indices. This paper illustrates how Data Envelopment Analysis (DEA) and Multi-Criteria-Decision-Making (MCDM) techniques can be employed to compute domain-based composite indices of life satisfaction and weightings for life domains. Furthermore, an empirical application is performed on a sample of 178 people living in a rural community in Yucatan (Mexico). One of the main features of the aforementioned techniques is that weightings might differ from one individual to another. Accordingly, several weighting schemes are used to compute different life satisfaction indices, in addition to a constant equally-weighted index. Based on the goodness-of-fit criteria commonly used in this literature, our main result is that DEA-MCDM indicators of life satisfaction do not improve the relationship with self-reported life satisfaction in comparison to the equally-weighted index.


Data Envelopment Analysis Domains of life Life satisfaction indices Multi-Criteria-Decision-Making Weightings 



The authors gratefully acknowledge the comments and suggestions made by an anonymous referee and also the financial support from the Spanish Ministry of Economy and Competitiveness (projects ECO2011-30260-C03-01 and ECO2012-32189) and the Generalitat Valenciana (program PROMETEO 2009/098).


  1. Adler, N., & Golany, B. (2002). Including principal components weights to improve discrimination in data envelopment analysis. Journal of the Operational Research Society, 53, 985–991.CrossRefGoogle Scholar
  2. Allen, R., & Thanassoulis, E. (2004). Improving envelopment in data envelopment analysis. European Journal of Operational Research, 154, 363–379.CrossRefGoogle Scholar
  3. Andersen, P., & Petersen, N. C. (1993). A procedure for ranking efficient units in data envelopment analysis. Management Science, 39, 1261–1264.CrossRefGoogle Scholar
  4. André, F. J., Herrero, I., & Riesgo, L. (2010). A modified DEA model to estimate the importance of objectives with an application to agricultural economics. Omega, 38, 371–382.CrossRefGoogle Scholar
  5. Bernini, C., Guizzardi, A., & Angelini, G. (2012). DEA-like model and common weights approach for the construction of a subjective community well-being indicator. Social Indicators Research (in press). doi: 10.1007/s11205-012-0152-3.
  6. Campbell, A., Converse, P. E., & Rogers, W. L. (1976). The quality of American life: Perceptions, evaluations, and satisfactions. New York: Russel Sage.Google Scholar
  7. Charnes, A., Cooper, W. W., Huang, Z., & Sun, D. (1990). Polyhedral cone-ratio DEA models with an illustrative application to large commercial banks. Journal of Econometrics, 46, 73–91.CrossRefGoogle Scholar
  8. Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operations Research, 2(6), 429–449.CrossRefGoogle Scholar
  9. Cherchye, L., Moesen, W., Rogge, N., & van Puyenbroek, T. (2007). An introduction to ‘benefit of the doubt’ composite indicators. Social Indicators Research, 82, 111–145.CrossRefGoogle Scholar
  10. Clark, A. E., & Oswald, A. J. (1994). Subjective well-being and unemployment. Economic Journal, 104, 648–659.CrossRefGoogle Scholar
  11. Cooper, W. W., Seiford, L. M., & Tone, K. (2007). Data Envelopment Analysis. A comprehensive text with models, applications, references and DEA-Solver software. New York: Springer-Business Media-LCC.Google Scholar
  12. Cummins, R. A. (1996). The domains of life satisfaction: An attempt to order chaos. Social Indicators Research, 38, 303–332.CrossRefGoogle Scholar
  13. Despotis, D. K. (2002). Improving the discriminating power of DEA: Focus on globally efficient units. Journal of Operations Research Society, 53, 314–323.CrossRefGoogle Scholar
  14. Despotis, D. K. (2005). A reassessment of the human development index via data envelopment analysis. Journal of the Operations Research Society, 56, 969–980.CrossRefGoogle Scholar
  15. Diener, E. (1984). Subjective well-being. Psychological Bulletin, 95, 542–575.CrossRefGoogle Scholar
  16. Domíguez-Serrano, M., & Blancas, F. J. (2011). A gender wellbeing composite indicator: The best–worst global evaluation approach. Social Indicators Research, 102, 477–496.CrossRefGoogle Scholar
  17. Färe, R., & Lovell, C. A. K. (1978). Measuring the technical efficiency of production. Journal of Economic Theory, 19, 150–162.CrossRefGoogle Scholar
  18. Farrell, M. (1957). The measurement of productive efficiency. The Journal of Royal Statistical Society Series A, 120, 253–281.CrossRefGoogle Scholar
  19. Golany, B. (1988). An interactive MOLP procedure for the extension of DEA to effectiveness analysis. Journal of the Operations Research Society, 39, 725–734.CrossRefGoogle Scholar
  20. González, M., Coenders, G., Saez, M., & Casas, F. (2010). Non-linearity, complexity and limited measurement in the relationship between satisfaction with specific life domains and satisfaction with life as a whole. Journal of Happiness Studies, 11, 335–352.CrossRefGoogle Scholar
  21. Guardiola, J., González-Gómez, F., & Lendechy-Grajales, A. (2013a). The influence of water access in subjective well-being: Some evidence in Yucatan, Mexico. Social Indicators Research, 110, 207–218.CrossRefGoogle Scholar
  22. Guardiola, J., García-Rubio, M. A., & Guidi-Gutiérrez, E. (2013b). Water access and subjective well-being: The case of Sucre, Bolivia. Applied Research in Quality of Life (in press). doi:  10.1007/s11482-013-9218.
  23. Guardiola, J., González-Gómez, F., García-Rubio, M. A., & Lendechy-Grajales, A. (2013c). Does higher income equal higher happiness in every society? The case of the Mayan people. International Journal of Social Welfare, 22, 35–44.CrossRefGoogle Scholar
  24. Gujarati, D. (1995). Basic econometrics. New York: McGraw-Hill.Google Scholar
  25. Hashimoto, A., & Kodama, M. (1997). Has livability of Japan gotten better for 1956–1990? A DEA approach. Social Indicators Research, 40, 359–373.CrossRefGoogle Scholar
  26. Headey, B., Veenhoven, R., & Wearing, A. J. (1991). Top-down versus bottom-up theories of subjective well-being. Social Indicators Research, 24, 81–100.CrossRefGoogle Scholar
  27. Hsieh, C. M. (2003). Counting importance: The case of life satisfaction and relative domain importance. Social Indicators Research, 61, 227–240.CrossRefGoogle Scholar
  28. Hsieh, C. M. (2004). To weight or not to weight: The role of domain importance in quality of life measurement. Social Indicators Research, 68, 163–174.CrossRefGoogle Scholar
  29. Hsieh, C. M. (2012). Importance is not unimportant: The role of importance weighting in QOL Measures. Social Indicators Research, 109, 267–278.Google Scholar
  30. Hsieh, C. M. (2013). Issues in evaluating importance weighting in quality of life measures. Social Indicators Research, 110, 681–693.Google Scholar
  31. Jahansahahloo, G. R., Memariani, A., Hosseinzadeh, F., & Rezai, H. Z. (2005). A note on some of DEA models and finding efficiency and complete ranking using common set of weights. Applied Mathematics and Computation, 166, 265–281.CrossRefGoogle Scholar
  32. Jurado, A., & Perez-Mayo, J. (2012). Construction and evolution of a multidimensional well-being index for the Spanish regions. Social Indicators Research, 107, 259–279.Google Scholar
  33. Kao, C., & Hung, H. T. (2005). Data envelopment analysis with common weights: The compromise solution approach. Journal of the Operational Research Society, 56, 1196–1203.CrossRefGoogle Scholar
  34. Lance, C. E., Lautenschlager, G. J., Sloan, C. E., & Varca, P. E. (1989). A comparison between bottom–up, top–down, and bidirectional models of relationships between global and life facet satisfaction. Journal of Personality, 57, 601–624.CrossRefGoogle Scholar
  35. Li, X., & Reeves, G. R. (1999). A multiple criteria approach to data envelopment analysis. European Journal of the Operations Research, 115, 507–517.CrossRefGoogle Scholar
  36. Lovell, C. A. K., Pastor, J. T., & Turner, J. A. (1995). Measuring macroeconomic performance in the OECD: A comparison of European and non-European countries. European Journal of Operations Research, 87, 507–518.CrossRefGoogle Scholar
  37. Michalos, A. C., Zumbo, B. B., & Hubley, A. (1999). Health and the quality of life. Social Indicators Research, 51, 245–286.CrossRefGoogle Scholar
  38. Møller, V., & Saris, W. E. (2001). The relationship between subjective well-being and domain satisfactions in South Africa. Social Indicators Research, 55, 97–114.CrossRefGoogle Scholar
  39. Murias, P., Martínez, F., & de Miguel, C. (2006). An economic wellbeing index for the Spanish Provinces: A data envelopment analysis approach. Social Indicators Research, 77, 395–417.CrossRefGoogle Scholar
  40. Reig-Martínez, E. (2013). Social and economic wellbeing in Europe and the Mediterranean Basin: Building an enlarged Human Development Indicator. Social Indicators Research, 111, 527–547.Google Scholar
  41. Reig-Martínez, E., Gómez-Limón, J. A., & Picazo-Tadeo, A. J. (2011). Ranking farms with a composite indicator of sustainability. Agricultural Economics, 42, 561–575.CrossRefGoogle Scholar
  42. Rogge, N. (2011). Granting teachers the ‘benefit of the doubt’ in performance evaluations. International Journal of Educational Management, 25, 590–614.CrossRefGoogle Scholar
  43. Rojas, M. (2006). Life satisfaction and satisfaction in domains of life: Is it a simple relationship? Journal of Happiness Studies, 7, 467–497.CrossRefGoogle Scholar
  44. Rojas, M. (2007). The complexity of well-being: A life-satisfaction conception and a domains-of-life approach. In I. Gough & A. McGregor (Eds.), Researching well-being in developing countries. Cambridge: Cambridge University Press.Google Scholar
  45. Rojas, M. (2008). Experienced poverty and income poverty in Mexico: A subjective well-being approach. World Development, 36(6), 1078–1093.CrossRefGoogle Scholar
  46. Sexton, T. R. (1986). The methodology of data envelopment analysis. In R. H. Silkman (Ed.), Measuring efficiency: An assessment of Data Envelopment Analysis, new directions for program evaluation. San Francisco, CA: Jossey Bass.Google Scholar
  47. Shephard, R. W. (1970). Theory of cost and production functions. Princeton: Princeton University Press.Google Scholar
  48. Tone, K. (2001). A slacks-based measure of efficiency in data envelopment analysis. European Journal of Operational Research, 130, 498–509.CrossRefGoogle Scholar
  49. Torgersen, A. M., Førsund, F. R., & Kittelsen, S. A. (1996). Slack adjusted efficiency measures and ranking of efficient units. Journal of Productivity Analysis, 7, 379–398.CrossRefGoogle Scholar
  50. Van Praag, B. M., Frijters, P., & Ferrer-i-Carbonell, A. (2003). The anatomy of subjective well-being. Journal of Economic Behavior & Organization, 51, 29–49.CrossRefGoogle Scholar
  51. Wills, E. (2009). Spirituality and subjective well-being: Evidences for a new domain in the personal well-being index. Journal of Happiness Studies, 10, 49–69.CrossRefGoogle Scholar
  52. Wu, C. H. (2008). Can we weight satisfaction score with importance ranks across life domains? Social Indicators Research, 86, 468–480.CrossRefGoogle Scholar
  53. Wu, C. H. (2009). Enhancing quality of life by shifting importance perception among life domains. Journal of Happiness Studies, 10, 37–47.Google Scholar
  54. Wu, C. H., & Yao, G. (2006). Do we need to weight item satisfaction by item importance? A perspective from Locke’s range-of-affect hypothesis. Social Indicators Research, 79, 485–502.CrossRefGoogle Scholar
  55. Wu, C. H., & Yao, G. (2007). Importance has been considered in satisfaction evaluation: An experimental examination of Locke’s range-of-affect hypothesis. Social Indicators Research, 81, 521–541.CrossRefGoogle Scholar
  56. Zaim, O., Färe, R., & Grosskopf, S. (2001). An economic approach to achievement and improvement indexes. Social Indicators Research, 56, 91–118.CrossRefGoogle Scholar
  57. Zhou, P., Ang, B. W., & Poh, K. L. (2007). A mathematical programming approach to constructing composite indicators. Ecological Economics, 62, 291–297.CrossRefGoogle Scholar
  58. Zhu, J. (2001). Multidimensional quality-of-life measure with an application to Fortune’s best cities. Socio-Economic Planning Sciences, 35, 263–284.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.Departamento de Economía Aplicada and Instituto Universitario del AguaUniversidad de GranadaGranadaSpain
  2. 2.Departamento de Economía Aplicada II (Estructura Económica)Universidad de ValenciaValenciaSpain

Personalised recommendations