El impacto del turismo en el Casco Viejo de Bilbao mediante los modelos de economía colaborativa :una aproximación a través de una distribución binomial negativa

  1. Alvaro Fierro 1
  2. Cristina Salmón 2
  1. 1 Cultumetria S.L, España
  2. 2 Abra Invest, España
Revue:
Lurralde: Investigación y espacio

ISSN: 0211-5891

Année de publication: 2018

Número: 41

Pages: 175-201

Type: Article

DIALNET GOOGLE SCHOLAR lock_openAccès ouvert editor

D'autres publications dans: Lurralde: Investigación y espacio

Résumé

This paper aims to measure the impact of the type of tourism resulting from the new models of digital collaborative economy accommodation and its effect on the rent of commercial establishments in the old part of Bilbao, known as Casco Viejo. The article identifies a profile of the type of guest that does not collect official statistics, and which is conditioned, in turn, by the profile of the host who rents his private residence. In addition, it is demonstrated, in a preliminary way, that this phenomenon and the tourist activity if IS not cause, contributes to the increase the square meter price of the locals which are dedicated to the commerce, and therefore generate a process of gentrification of the neighborhood. We are therefore looking for the relationship between the profile of the new tourist and the economic activity that takes place in this area.

Références bibliographiques

  • El impacto del alojamiento compartido en Madrid The Airbnb Blog (2015).
  • Ayuntamiento de Bilbao (Bilbao.eus)
  • Bilbao Turismo (bilbaoturismo.net)
  • CASANOVAS, S. (2014). Del yo al nosotros: análisis y diagnóstico de la economía colaborativa. Universitat Autònoma de Barcelona. Trabajo fin de grado.
  • CASIMIRO, P. G. (1992). Error cuadrático medio de predicción para modelos estructurales de series temporales. Estadística española, nº 129, pp.117-136.
  • CRAGG, J. G. (1971). Some statistical models for limited dependent variables with application to the demand for durable goods. Econometrica: Journal of the Econometric Society, pp.829-844.
  • COXE, S., WEST, S. G., & AIKEN, L. S. (2009). The analysis of count data: A gentle introduction to Poisson regression and its alternatives. Journal of personality assessment, vol. 91, nº 2, pp. 121-136.
  • DAVIDSON, R, MACKINNON J (2004): Econometric Theory and Methods.
  • DÍEZ, TORIBIO, S (2015): La Economía Colaborativa: Un nuevo modelo de consumo que requiere la atención de la política económica. Universidad de Valladolid. Trabajo fin de grado.
  • EUSTAT (www.eustat.eus)
  • EVANS, G. (2005). Measure for measure: Evaluating the evidence of culture’s contribution to regeneration. Urban studies, vol. 42, nº 5-6, pp. 959-983.
  • GENERALITAT DE CATALUNYA (web.gencat.ca)
  • GUTTENTAG, D. (2015). Airbnb: disruptive innovation and the rise of an informal tourism accommodation sector. Current issues in Tourism, vol. 18, nº 12, pp. 1192-1217.
  • HOMELIDAYS (homelidays.es)
  • HOYOS, D. (2016): Tema 6: Datos de Conteo. Apuntes de Microeconometría. Master de Instrumentos del Análisis Económico. UPV/EHU.
  • IDEALISTA (www.idealista.com)
  • IKKALA, T., & LAMPINEN, A. (2015): Monetizing network hospitality: Hospitality and sociability in the context of airbnb. In Proceedings of the 18th ACM conference on computer supported cooperative work & social computing, pp. 1033-1044. ACM.
  • KAPLAN, R.A. and NADLER, M.L. (2015), “Airbnb: a Case Study in occupancy regulation and taxation”, No. 82, The University of Chicago Law Review Dialogue, pp. 103-15
  • LAMBERT, D. (1992). Zero-inflated Poisson regression, with an application to defects in manufacturing. Technometrics, vol. 34, nº 1, pp. 1-14.
  • MACQUEEN, J. (1967, June). Some methods for classification and analysis of multivariate observations. In Proceedings of the fifth Berkeley symposium on mathematical statistics and probability, vol. 1, Nº 14, pp. 281-297.
  • MAHALANOBIS, P.C. (1936): On the generalised distance in statistics, Proceedings of the National Institute of Science of India nº12, pp. 49-55.
  • MONTERO, A. R. (2014). Razones por las que AIRBNB va como un tiro: el auge del consumo colaborativo en el turismo. Tecnohotel: revista profesional para la hostelería y restauración, vol. 60, nº 72.
  • NIUMBA (www.niumba.com)
  • PLAZA, B., TIRONI, M and HAARICH, S.N., (2009): Bilbao´s Arts Scene and the “Guggenheim Effect” Revisited. European Planning Studies, vol. 17, nº 11, pp. 1711-1729.
  • PACHECO JIMÉNEZ, MN (2016): La Web 2.0 como instrumento esencial en la economía colaborativa. Revista CESCO de Derecho de Consumo, nº 17, pp, 76-84.
  • RIFKIN, J. (2014). La sociedad de coste marginal cero: el internet de las cosas, el procomún colaborativo y el eclipse del capitalismo. Grupo Planeta (GBS).
  • THIERER, A. D., KOOPMAN, C., HOBSON, A., & KUIPER, C. (2015). How the Internet, the Sharing Economy, and Reputational Feedback Mechanisms Solve the’Lemons Problem’. Available at SSRN 2610255.
  • ZERVAS, G., PROSPERPIO, D., & BYERS, J. (2016). The rise of the sharing economy: Estimating the impact of Airbnb on the hotel industry. Boston U. School of Management Research Paper (2013-16).
  • ZERVAS, G., PROSPERPIO, D., & BYERS, J. (2015). A first look at online reputation on Airbnb, where every stay is above average. Boston U. School of Management Research Paper, 16.
  • Wimdu: (www.wimdu.es)
La source de données: Dialnet