https://eprints.leedsbeckett.ac.uk/id/eprint/6353/6/AComparativeAnalysisOfAirbnbInLondonAndBarcelonaAM-MIGUEL.pdf
22 мар. 2019 г. We developed the models using R software with spdep [91] and regclass [92] packages. For tourist areas/sites we developed simple linear models ...
Equation 2 presents the analyti- cal model. r. SE r. Z i i j k. j j i. = +. ( )+ An. Empirical Analysis of Airbnb Supply in US Cities.” Journal of. Travel ...
An initial analysis of the data reveals interesting aspects of the Airbnb market in Thessaloniki. Botsman R.
to evaluate their performance metrics in R^2 and root mean square error (RMSE). Through topic modeling polarity
1 мая 2020 г. Inside. Airbnb compiles Airbnb data into ... Afterwards Extensive statistical analysis was conducted in R statistical software which included.
26 авг. 2020 г. function in the base R as an alternative. ... In this study we address the explanatory analysis of the airbnb data with several key features such ...
22 mar. 2019 It notices a high concentration of Airbnb listings in urban centres which contrasts with the concentration of traditional tourist rental houses ...
meta-analysis meta-regression
Using. Ordinal Least Square and Geography Weighed Regression analysis the spatial distribution features of Airbnb and its relationship with neighbourhood
To gain a better understanding of Airbnb adopters this paper systematically compares actual travel behaviour of Airbnb users in a specific destination with
average compared to 12% for a general visitor. In this analysis. HR&A applied the Airbnb guest spending distribution to all STR visitors
However a two-sided reputation system is offered in the Airbnb platform; the host and the tourist have the opportunity to leave a review simultaneously after
gative impact the usage of Airbnb has on hotel occupancy is in 4-star hotels KEYWORDS: Sharing Economies
occupancy in Mexico: a Big Data Analysis. (2007-2018). La influencia de Airbnb en la ocupación hotelera de. México: un análisis del Big Data (2007-2018).