Cómo citar este artículo/Citation: Núñez Tabales, J. M., Rey Carmona, F. J., Caridad y Ocerin, J. M.ª (2016). Redes neuronales (RN) aplicadas a la valoración de locales comerciales. Informes de la Construcción, 69(545) RESUMENLa estimación de precios de inmuebles mediante la utilización de métodos objetivos es de interés para compradores, vendedores y para la propia Administración. Existen diferentes metodologías que permiten la determinación del precio de un inmueble, siendo numerosas las aportaciones cuyo propósito es la estimación de precios de inmuebles residenciales. No obstante, el presente trabajo es pionero en la aplicación de técnicas de Inteligencia Artificial (IA) para la determinación de precios de locales comerciales. Se presenta un estudio de esta tipología de inmueble en la ciudad de Córdoba (España). Los resultados evidencian que las Redes Neuronales (RN) constituyen una alternativa atractiva a los tradicionales Modelos Hedónicos (MH), registrando un mejor ajuste a las no linealidades del mercado y resultando con menores errores. Asimismo, se obtienen los precios implícitos correspondientes a los atributos determinantes del precio de un local comercial a partir de la ecuación de la RN diseñada.

In recent years, the number of sharing economy accommodations has grown exponentially due to the Internet and peer-to-peer networks, which has made researchers increasingly interested in analysing this new type of lodging. This study sought to develop models that determine the significant variables for the daily price of staying in holiday rentals based on data extracted from Booking.com and other sources. The hedonic pricing method (HPM) was selected to conduct the research as this methodology has been widely used in real estate valuation and hotel daily rate determination; however, the HPM is still rarely used for holiday rentals. The study focused on the city of Seville, where a notable increase in holiday rentals has been observed in recent years. Variables related to the accommodation typology, including location, size and equipment, as well as seasonality, are the most influential factors in the proposed models. These results are of interest to both owners and users of holiday rentals and can help these individuals to determine if the price of a stay is what would commonly be offered in the market under normal circumstances.

The enormous expansion of the video game sector, driven by the emergence of live video game streaming platforms and the professionalisation of this hobby through e-sports, has spurred interest in research on the relationships with potential adverse effects derived from cumulative use. This study explores the co-occurrence of the consumption and viewing of video games, based on an analysis of the motivations for using these services, the perceived positive uses, and the gamer profile. To that end, a multilayer perceptron artificial neural network is developed and tested on a sample of 970 video game users. The results show that the variables with a significant influence on pathological gaming are the motivation of a sense of belonging to the different platforms, as well as the positive uses relating to making friends and the possibility of making this hobby a profession. Furthermore, the individual effects of each of the variables have been estimated. The results indicate that the social component linked to the positive perception of making new friends and the self-perceived level as a gamer have been identified as possible predictors, when it comes to a clinical assessment of the adverse effects. Conversely, the variables age and following specific streamers are found to play a role in reducing potential negative effects.

article may be used for non-commercial purposes in accordance with Routledge Taylor & Francis Group terms and conditions for use of self-archived versions. this article may not be enhanced, enriched or otherwise transformed into a derivative work, without express permission from Routledge Taylor & Francis Group or by statutory rights under applicable legislation. Copyright notices must not be removed, obscured or modified. the article must be linked to Routledge Taylor & Francis Group´s version of record on Routledge Taylor & Francis Group online library and any embedding, framing or otherwise making available the article or pages thereof by third parties from platforms, services and websites other than Routledge Taylor & Francis Group online library must be prohibited. Open the doors to tourism or remain cautious: Residents' dilemma amidst a pandemicDuring a pandemic, residents of tourism destinations face the dilemma of whether to welcome tourists to help the economy rebound or to oppose their arrival to minimize the risk of contagion. This paper examines the influence of residents' perception of the economic crisis triggered by the pandemic and the health risks associated with tourist arrivals on their attitudes towards tourism impacts and willingness to support tourism development. To this end, a novel model is tested using structural equation modelling (SEM). The potential moderating effect of belonging to certain population groups is also analysed, namely (i) having a household member linked to the tourism sector, (ii) residing in the city centre, and (iii) belonging to a COVID-19 risk group. Perceived risk of contagion was found to be a stronger predictor of residents' support for tourism development than perception of the economic crisis; an effect that increases notably among residents of the most popular tourist areas of the city. These empirical findings provide useful information with a view to designing destination planning strategies during and after the pandemic.

Econometric hedonic models encounter s e v e r a l t h e o re t i c a l a n d p r a c t i c a l difficulties when applied to the real estate market, such as downward biases in the estimation of hedonic prices, subjective decisions in the measurement process of categorical attributes, frontier problems related to an imperfect information framework and uniequational specification. Many of these are linked to the parametric approach. A r t i f i c i a l N e u r a l N e t w o r k s ( A N N ) provide an attractive alternative: better dwelling prices estimates, avoidance of bias at different market segments, direct use of categorical data and full use of the information available. The price to be paid is the difficulties in the economic interpretation of network parameters. Nowadays, if the final objective to produce better estimates of the transaction prices, this methodology show lower errors, provided of a broad representative database of sales are recorded. A case study is presented for a medium size city in the South of Spain. Keywords