Neural based contingent valuation of road traffic noise |
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| Institution: | 1. Colegio de Administración y Economía, Universidad San Francisco de Quito, Ecuador;2. Banco Solidario, Risk Division, Data Analytics, Quito, Ecuador;3. Data Science Research Group - CIDED, Escuela Superior Politécnica de Chimborazo, Territorial Development, Business and Innovation Research Group - DeTEI, Universidad Técnica de Ambato, Ecuador;4. Department of Economics and Statistics, University of Siena, Piazza San Francesco, 7/8 53100 Siena, Italy;5. Università di Siena CRENoS, Italy;6. Facultad de Ingeniería y Ciencias, Universidad Adolfo Ibáñez, Viña del Mar, Chile;7. ANID-Millennium Science Initiative Program-Millennium Nucleus Center for the Discovery of Structures in Complex Data, Chile |
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| Abstract: | In this paper, we present a new approach to value the willingness to pay to reduce road noise annoyance using an artificial neural network ensemble. The model predicts, with precision and accuracy, a range for willingness to pay from subjective assessments of noise, a modelled noise exposure level, and both demographic and socio-economic conditions. The results were compared to an ordered probit econometric model in terms of the performance mean relative error and obtained 85.7% better accuracy. The results of this study show that the applied methodology allows the model to reach an adequate generalisation level, and can be applicable as a tool for determining the cost of transportation noise in order to obtain financial resources for action plans. |
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| Keywords: | Artificial neural network Contingent valuation Road traffic noise |
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