Ir al menú de navegación principal Ir al contenido principal Ir al pie de página del sitio

Enfoque multicriterio jerárquico para el análisis de la competitividad de las regiones en México

Resumen

El objetivo principal de este trabajo es el de evaluar el nivel de competitividad de las regiones de México basado en el desempeño de 10 principales factores provenientes de 100 indicadores. La metodología está basada en el Proceso Jerárquico Multicriterio con la capacidad de analizar el desempeño de un subconjunto de indicadores y el conjunto completo de indicadores, y como impactan en la competitividad de la región. Un aspecto importante de Proceso Jerárquico Multicriterio implementado es que considera la interacción entre criterios (indicadores) y mide el desempeño de un gran número de criterios. La principal contribución de la investigación es la identificación del nivel peor de competitividad de la región, y los factores que requieren más atención por el tomador de decisiones.

Palabras clave: Análisis multicriterio, enfoque jerárquico, competitividad.

Códigos JEL: C69, C81, D81

Recibido: 10/07/2020. Aceptado: 05/11/2020.  Publicado: 01/12/2020

Palabras clave

Análisis multicriterio, enfoque jerárquico, competitividad

PDF (English)

Citas

  1. Angilella, S., Catalfo, P., Corrente, S., Giarlotta, A., Greco, S., & Rizzo, M. (2018). Robust sustainable development assessment with composite indices aggregating interacting dimensions: The hierarchical-SMAA-Choquet integral approach. Knowledge-Based Systems, 158, 136-153. doi:10.1016/j.knosys.2018.05.041 DOI: https://doi.org/10.1016/j.knosys.2018.05.041
  2. Botti, L., & Peypoch, N. (2013). Multi-criteria ELECTRE method and destination competitiveness. Tourism Management Perspectives, 6, 108-113. doi:10.1016/j.tmp.2013.01.001 DOI: https://doi.org/10.1016/j.tmp.2013.01.001
  3. Blanco-Mesa F., Gil-Lafuente, A.M. (2014). Characterization and Grouping of the Colombia Regions to Develop of Clusters: An Application of Pichat Algorithm. Journal of Computational Optimization in Economics and Finances 5 (3), 187-196.
  4. Blanco-Mesa F., Gil-Lafuente A.M. (2017). Towards competitiveness in the economic activity in Colombia: Using Moore's families and Galois Lattices in clustering. Economic Computation and Economic Cybernetics Studies and Research 51 (3), 231-250.
  5. Blanco-Mesa F., Merigó, J.M, Gil-Lafuente, A.M. (2017). Fuzzy decision making: A bibliometric-based review. Journal of Intelligent & Fuzzy Systems 32 (3), 2033-2050 DOI: https://doi.org/10.3233/JIFS-161640
  6. Carayannis, E. G., Ferreira, F. A. F., Bento, P., Ferreira, J. J. M., Jalali, M. S., & Fernandes, B. M. Q. (2018). Developing a socio-technical evaluation index for tourist destination competitiveness using cognitive mapping and MCDA. Technological Forecasting and Social Change, 131, 147-158. doi:10.1016/j.techfore.2018.01.015 DOI: https://doi.org/10.1016/j.techfore.2018.01.015
  7. Charles, V., & Zegarra, L. F. (2014). Measuring regional competitiveness through Data Envelopment Analysis: A Peruvian case. Expert Systems with Applications, 41(11), 5371-5381. doi:10.1016/j.eswa.2014.03.003 DOI: https://doi.org/10.1016/j.eswa.2014.03.003
  8. Corrente, S., Doumpos, M., Greco, S., Slowinski, R., & Zopounidis, C. (2017). Multiple criteria hierarchy process for sorting problems based on ordinal regression with additive value functions. Annals of Operations Research, 251(1-2), 117-139. doi:10.1007/s10479-015-1898-1 DOI: https://doi.org/10.1007/s10479-015-1898-1
  9. Corrente, S., Figueira, J. R., Greco, S., & Słowiński, R. (2017). A robust ranking method extending ELECTRE III to hierarchy of interacting criteria, imprecise weights and stochastic analysis. Omega, 73, 1-17. doi:10.1016/j.omega.2016.11.008 DOI: https://doi.org/10.1016/j.omega.2016.11.008
  10. Corrente, S., Greco, S., & Słowiński, R. (2012). Multiple Criteria Hierarchy Process in Robust Ordinal Regression. Decision Support Systems, 53(3), 660-674. doi:10.1016/j.dss.2012.03.004 DOI: https://doi.org/10.1016/j.dss.2012.03.004
  11. Delgado, M., Porter, M., and Stern, S. (2010). Clusters and entrepreneurship. Journal of Economic Geography, 10(4), 495-518. DOI: https://doi.org/10.1093/jeg/lbq010
  12. Delgado, M., Porter, M., and Stern, S. (2014). Clusters, Convergence, and Economic Performance, Research Policy, 43(10), 1785-1799. DOI: https://doi.org/10.1016/j.respol.2014.05.007
  13. Del Vasto-Terrientes, L., Valls, A., Slowinski, R., & Zielniewicz, P. (2015). ELECTRE-III-H: An outranking-based decision aiding method for hierarchically structured criteria. Expert Systems with Applications, 42(11), 4910-4926. doi:10.1016/j.eswa.2015.02.016 DOI: https://doi.org/10.1016/j.eswa.2015.02.016
  14. Ginevičius, R., & Podvezko, V. (2009). Evaluating the Changes in Economic and Social Development of Lithuanian Counties by Multiple Criteria Methods. Technological and Economic Development of Economy, 15(3), 418-436. doi:10.3846/1392-8619.2009.15.418-436 DOI: https://doi.org/10.3846/1392-8619.2009.15.418-436
  15. Goncalves, J. M., Ferreira, F. A. F., Ferreira, J. J. M., & Farinha, L. M. C. (2019). A multiple criteria group decision-making approach for the assessment of small and medium-sized enterprise competitiveness. Management Decision, 57(2), 480-500. doi:10.1108/md-02-2018-0203 DOI: https://doi.org/10.1108/MD-02-2018-0203
  16. Hernández Rodriguez, C., & Montalvo Corzo, R. F. (2012). Entrepreneurial clusters in China and Mexico –implications for Competitiveness. Revista de globalización, competitividad y gobernabilidad, 6(1), 55-90. doi:10.3232/GCG.2012.V6.N1.04 DOI: https://doi.org/10.3232/GCG.2012.V6.N1.04
  17. Huang, J. H., & Peng, K. H. (2012). Fuzzy Rasch model in TOPSIS: A new approach for generating fuzzy numbers to assess the competitiveness of the tourism industries in Asian countries. Tourism Management, 33(2), 456-465. doi:10.1016/j.tourman.2011.05.006 DOI: https://doi.org/10.1016/j.tourman.2011.05.006
  18. Huang, K. W., Huang, J. H., & Tzeng, G. H. (2016). New Hybrid Multiple Attribute Decision-Making Model for Improving Competence Sets: Enhancing a Company's Core Competitiveness. Sustainability, 8(2). doi:10.3390/su8020175 DOI: https://doi.org/10.3390/su8020175
  19. IMCO. (2016a). Índice de Competitividad Estatal 2014. México: Impresos Villaflorito S.A. de C.V.
  20. IMCO. (2016b). Instituto Mexicano para la Competitividad. Retrieved from https://imco.org.mx/
  21. Kabir, G., Sadiq, R., & Tesfamariam, S. (2013). A review of multi-criteria decision-making methods for infrastructure management. Structure and Infrastructure Engineering, 10(9), 1176-1210. doi:10.1080/15732479.2013.795978 DOI: https://doi.org/10.1080/15732479.2013.795978
  22. Kao, C., Wu, W.-Y., Hsieh, W.-J., Wang, T.-Y., Lin, C., & Chen, L.-H. (2008). Measuring the national competitiveness of Southeast Asian countries. European Journal of Operational Research, 187(2), 613-628. doi:10.1016/j.ejor.2007.03.029 DOI: https://doi.org/10.1016/j.ejor.2007.03.029
  23. Ketels, C. (2003). The Development of the cluster concept - present experiences and further developments. In NRW Conference on Clusters (pp. 1-25). Duisburg
  24. Ketels, C. (2013). Recent research on competitiveness and clusters: what are the implications for regional policy? Cambridge Journal of Regions, Economy and Society, 6(2), 269-284 DOI: https://doi.org/10.1093/cjres/rst008
  25. Khayyat, N., & Lee, J. (2014). A measure of technological capabilities for developing countries. Technological Forecasting and Social Change, 9, 210-223. DOI: https://doi.org/10.1016/j.techfore.2014.09.003
  26. Ko, Y. C., Fujita, H., & Tzeng, G. H. (2013). A fuzzy integral fusion approach in analyzing competitiveness patterns from WCY2010. Knowledge-Based Systems, 49, 1-9. doi:10.1016/j.knosys.2013.04.001 DOI: https://doi.org/10.1016/j.knosys.2013.04.001
  27. Krugman, P. (1994). Competitiveness: A Dangerous Obsession. Foreign Affairs, 73(2), 28. doi:10.2307/20045917 DOI: https://doi.org/10.2307/20045917
  28. Krugman, P., Obstfeld, M., & Melitz, M. (2012). International Economics, Theory and Policy. Boston: Pearson.
  29. Lee, S. K., Mogi, G., Kim, J. W., & Gim, B. J. (2008). A fuzzy analytic hierarchy process approach for assessing national competitiveness in the hydrogen technology sector. International Journal of Hydrogen Energy, 33(23), 6840-6848. doi:10.1016/j.ijhydene.2008.09.028 DOI: https://doi.org/10.1016/j.ijhydene.2008.09.028
  30. Marzouk, M. M. (2011). ELECTRE III model for value engineering applications. Automation in Construction, 20(5), 596-600. doi:10.1016/j.autcon.2010.11.026 DOI: https://doi.org/10.1016/j.autcon.2010.11.026
  31. Oyarce, J. (2013). Excelencia empresarial y competitividad: ¿una relación fructífera? Panorama Socioeconómico, 31(46), 58-63.
  32. Porter, M. (1990). The competitive advantage of nations. Harvard Business Review, 70-91. DOI: https://doi.org/10.1007/978-1-349-11336-1
  33. Porter, M. (1998). Clusters and the New Economics of Competition. Harvard Business Review, 76(6), 77-90.
  34. Porter, M. (2000). Location, Competition, and Economic Development: Local Clusters in a Global Economy. Economic Development Quarterly, 14(1), 15-34. DOI: https://doi.org/10.1177/089124240001400105
  35. Porter, M. (2003). The Economic Performance of Regions. Regional Studies, 37(6-7), 545-546. DOI: https://doi.org/10.1080/0034340032000108688
  36. Roy, B. (1985). Méthodologie multicritère d'aide à la décision. Paris, France: Economica.
  37. Roy, B. (1990). The Outranking Approach and the Foundations of ELECTRE Methods. In C. A. Bana e Costa (Ed.), Reading in Multiple Criteria Decision Aid (pp. 155-183). Berlin: Springer-Verlag. DOI: https://doi.org/10.1007/978-3-642-75935-2_8
  38. Santiesteban, M. L., & Lopez, J. C. L. (2017). A multicriteria decision aid for evaluating the competitiveness of tourist destinations in the northwest of Mexico. Anuario Turismo Y Sociedad, 21, 51-67. doi:10.18601/01207555.n21.03 DOI: https://doi.org/10.18601/01207555.n21.03
  39. Smith, A. (1776). An Inquiry into the Nature and Causes of the Wealth of Nations (Vol. 1). Oxford: Oxford University Press. DOI: https://doi.org/10.1093/oseo/instance.00043218
  40. Suñol, S. (2006). Aspectos teóricos de la competitividad. Ciencia y Sociedad, 31(2), 178-198. DOI: https://doi.org/10.22206/cys.2006.v31i2.pp179-198
  41. WEF. (2016). World Economic Forum. Retrieved from https://es.weforum.org/agenda/2016/10/
  42. Yeo, G. T., Song, D. W., Dinwoodie, J., & Roe, M. (2010). Weighting the competitiveness factors for container ports under conflicting interests. Journal of the Operational Research Society, 61(8), 1249-1257. doi:10.1057/jors.2009.88 DOI: https://doi.org/10.1057/jors.2009.88
  43. Yeo, G. T., Wang, Y., & Chou, C. C. (2013). Evaluating the competitiveness of the aerotropolises in East Asia. Journal of Air Transport Management, 32, 24-31. doi:10.1016/j.jairtraman.2013.06.004 DOI: https://doi.org/10.1016/j.jairtraman.2013.06.004
  44. Zangoueinezhad, A., Azar, A., & Kazazi, A. (2011). Using SCOR model with fuzzy MCDM approach to assess competitiveness positioning of supply chains: focus on shipbuilding supply chains. Maritime Policy & Management, 38(1), 93-109. doi:10.1080/03088839.2010.533715 DOI: https://doi.org/10.1080/03088839.2010.533715
  45. Zhang, H., Gu, C. L., Gu, L. W., & Zhang, Y. (2011). The evaluation of tourism destination competitiveness by TOPSIS & information entropy - A case in the Yangtze River Delta of China. Tourism Management, 32(2), 443-451. doi:10.1016/j.tourman.2010.02.007 DOI: https://doi.org/10.1016/j.tourman.2010.02.007

Descargas

Los datos de descargas todavía no están disponibles.

Artículos similares

1 2 3 > >> 

También puede {advancedSearchLink} para este artículo.