Using fuzzy logic and neural networks to classify socially responsible organisations
| Autor: | Raúl León-Soriano, Elena Escrig-Olmedo, Juana María Rivera-Lirio, Idoya Ferrero-Ferrero, M. Jesús Muñoz-Torres, M. Ángeles Fernández-Izquierdo |
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| Rok vydání: | 2013 |
| Předmět: |
Fluid Flow and Transfer Processes
Knowledge management Artificial neural network Computer science business.industry Geography Planning and Development Management Monitoring Policy and Law computer.software_genre Fuzzy logic Expert system Sustainability Corporate social responsibility Performance measurement Marketing business computer Social responsibility General Environmental Science Water Science and Technology |
| Zdroj: | Journal of Environmental Planning and Management. 56:238-253 |
| ISSN: | 1360-0559 0964-0568 |
| DOI: | 10.1080/09640568.2012.663324 |
| Popis: | Academics and practitioners have not yet developed an adequate method to evaluate the social performance of organisations that includes a robust and comprehensive approach of sustainability and uses the most relevant data sources. However, sustainability rating agencies are evaluating the social performance of organisations according to their own methodologies, which are not always clearly explained to stakeholders; and the evaluations they provide are being used as a reference in markets. This study contributes to research on the evaluation of social performance in organisations, by means of an innovative methodology that combines the use of neural networks and fuzzy logic for the development of expert systems suitable for classifying organisations according to their performance on Corporate Social Responsibility. The methodology has been validated in a simplified scenario and results indicate that it is suitable for replicating the classifications provided by sustainability rating agencies. |
| Databáze: | OpenAIRE |
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