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A Multicriteria Model for the Assessment of Countries' Environmental Performance

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A Multicriteria Model for the Assessment of Countries' Environmental Performance

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dc.contributor.author Guijarro, Francisco es_ES
dc.date.accessioned 2020-12-23T04:31:55Z
dc.date.available 2020-12-23T04:31:55Z
dc.date.issued 2019-08-14 es_ES
dc.identifier.issn 1660-4601 es_ES
dc.identifier.uri http://hdl.handle.net/10251/157770
dc.description.abstract [EN] Countries are encouraged to integrate environmental performance metrics by covering the key value-drivers of sustainable development, such as environmental health and ecosystem vitality. The proper measurement of environmental trends provides a foundation for policymaking, which should be addressed by considering the multicriteria nature of the problem. This paper proposes a goal programming model for ranking countries according to the multidimensional nature of their environmental performance metrics by considering 10 issue categories and 24 performance indicators. The results will provide guidance to those countries that aspire to become leaders in environmental performance. es_ES
dc.language Inglés es_ES
dc.publisher MDPI AG es_ES
dc.relation.ispartof International Journal of Environmental research and Public Health es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Multicriteria environmental performance es_ES
dc.subject Goal programming es_ES
dc.subject Ranking es_ES
dc.subject Weighting es_ES
dc.subject.classification ECONOMIA FINANCIERA Y CONTABILIDAD es_ES
dc.title A Multicriteria Model for the Assessment of Countries' Environmental Performance es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.3390/ijerph16162868 es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Economía y Ciencias Sociales - Departament d'Economia i Ciències Socials es_ES
dc.description.bibliographicCitation Guijarro, F. (2019). A Multicriteria Model for the Assessment of Countries' Environmental Performance. International Journal of Environmental research and Public Health. 16(16):1-15. https://doi.org/10.3390/ijerph16162868 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.3390/ijerph16162868 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 15 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 16 es_ES
dc.description.issue 16 es_ES
dc.identifier.pmid 31405177 es_ES
dc.identifier.pmcid PMC6720289 es_ES
dc.relation.pasarela S\392222 es_ES
dc.description.references Short, F. T., Kosten, S., Morgan, P. A., Malone, S., & Moore, G. E. (2016). Impacts of climate change on submerged and emergent wetland plants. Aquatic Botany, 135, 3-17. doi:10.1016/j.aquabot.2016.06.006 es_ES
dc.description.references Lynch, A. J., Myers, B. J. E., Chu, C., Eby, L. A., Falke, J. A., Kovach, R. P., … Whitney, J. E. (2016). Climate Change Effects on North American Inland Fish Populations and Assemblages. Fisheries, 41(7), 346-361. doi:10.1080/03632415.2016.1186016 es_ES
dc.description.references Wang, Z.-X., Hao, P., & Yao, P.-Y. (2017). Non-Linear Relationship between Economic Growth and CO2 Emissions in China: An Empirical Study Based on Panel Smooth Transition Regression Models. International Journal of Environmental Research and Public Health, 14(12), 1568. doi:10.3390/ijerph14121568 es_ES
dc.description.references Greco, S., Ishizaka, A., Tasiou, M., & Torrisi, G. (2018). On the Methodological Framework of Composite Indices: A Review of the Issues of Weighting, Aggregation, and Robustness. Social Indicators Research, 141(1), 61-94. doi:10.1007/s11205-017-1832-9 es_ES
dc.description.references Biggeri, M., Clark, D. A., Ferrannini, A., & Mauro, V. (2019). Tracking the SDGs in an ‘integrated’ manner: A proposal for a new index to capture synergies and trade-offs between and within goals. World Development, 122, 628-647. doi:10.1016/j.worlddev.2019.05.022 es_ES
dc.description.references Munda, G., & Nardo, M. (2009). Noncompensatory/nonlinear composite indicators for ranking countries: a defensible setting. Applied Economics, 41(12), 1513-1523. doi:10.1080/00036840601019364 es_ES
dc.description.references Munda, G. (2011). Choosing Aggregation Rules for Composite Indicators. Social Indicators Research, 109(3), 337-354. doi:10.1007/s11205-011-9911-9 es_ES
dc.description.references Ding, Y., Fu, Y., Lai, K. K., & John Leung, W. K. (2017). Using Ranked Weights and Acceptability Analysis to Construct Composite Indicators: A Case Study of Regional Sustainable Society Index. Social Indicators Research, 139(3), 871-885. doi:10.1007/s11205-017-1765-3 es_ES
dc.description.references Zhou, P., Ang, B. W., & Poh, K. L. (2007). A mathematical programming approach to constructing composite indicators. Ecological Economics, 62(2), 291-297. doi:10.1016/j.ecolecon.2006.12.020 es_ES
dc.description.references Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429-444. doi:10.1016/0377-2217(78)90138-8 es_ES
dc.description.references Zhou, L., Tokos, H., Krajnc, D., & Yang, Y. (2012). Sustainability performance evaluation in industry by composite sustainability index. Clean Technologies and Environmental Policy, 14(5), 789-803. doi:10.1007/s10098-012-0454-9 es_ES
dc.description.references García, F., Guijarro, F., & Moya, I. (2010). A goal programming approach to estimating performance weights for ranking firms. Computers & Operations Research, 37(9), 1597-1609. doi:10.1016/j.cor.2009.11.018 es_ES
dc.description.references García, F., Guijarro, F., & Moya, I. (2010). Ranking Spanish savings banks: A multicriteria approach. Mathematical and Computer Modelling, 52(7-8), 1058-1065. doi:10.1016/j.mcm.2010.02.015 es_ES
dc.description.references Juwana, I., Muttil, N., & Perera, B. J. C. (2012). Indicator-based water sustainability assessment — A review. Science of The Total Environment, 438, 357-371. doi:10.1016/j.scitotenv.2012.08.093 es_ES
dc.description.references Wiréhn, L., Danielsson, Å., & Neset, T.-S. S. (2015). Assessment of composite index methods for agricultural vulnerability to climate change. Journal of Environmental Management, 156, 70-80. doi:10.1016/j.jenvman.2015.03.020 es_ES
dc.description.references Charnes, A., Cooper, W. W., & Ferguson, R. O. (1955). Optimal Estimation of Executive Compensation by Linear Programming. Management Science, 1(2), 138-151. doi:10.1287/mnsc.1.2.138 es_ES
dc.description.references Tamiz, M., Jones, D., & Romero, C. (1998). Goal programming for decision making: An overview of the current state-of-the-art. European Journal of Operational Research, 111(3), 569-581. doi:10.1016/s0377-2217(97)00317-2 es_ES
dc.description.references Linares, P. (2002). Aggregation of preferences in an environmental economics context: a goal-programming approach. Omega, 30(2), 89-95. doi:10.1016/s0305-0483(01)00059-7 es_ES
dc.description.references Romero, C. (2001). Extended lexicographic goal programming: a unifying approach. Omega, 29(1), 63-71. doi:10.1016/s0305-0483(00)00026-8 es_ES
dc.description.references Dunlap, R. E., & Mertig, A. G. (1995). Global Concern for the Environment: Is Affluence a Prerequisite? Journal of Social Issues, 51(4), 121-137. doi:10.1111/j.1540-4560.1995.tb01351.x es_ES


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