@misc{10481/66462,
year = {2020},
url = {http://hdl.handle.net/10481/66462},
abstract = {Our research aims to address the following research questions: (a)
to identify guests’ hidden experiences in a distribution of terms
over a fixed vocabulary by analysing a bulk set of online reviews
through the process of text mining, and in particular, (b) to assess
if the Airbnb guest experience represented in them can be used
to enhance Airbnb services. On the other hand, our study analyses the relationship between the topics identified and Airbnb
pricing, and mainly measures the influence of gender as a moderating cue. In this regard, a growing body of research has emerged
to examine gender differences in leisure participation. In particular, our study concludes how the guests’ gender affects the contributions of listings’ features in price prediction. Females are
more intrinsically motivated and preferentially mention, for
instance, the Airbnb accommodation’s location and the gratifying
(local) experiences in their narratives. On the contrary, male
guests highlight hygiene and apartment facilities. To sum up, our
research provides design guidelines to reflect the willingness to
hire an apartment, offering insights for research and practice, and
allowing the layout of pricing-recommendation systems.},
organization = {Research Group, Government of Andalusia, Spain 	
SEJ494},
publisher = {ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD},
keywords = {Airbnb},
keywords = {Prices},
keywords = {Gender},
keywords = {Structural topic models},
keywords = {XGBoost},
keywords = {SHAP values},
title = {Exploring gender-based influences on key features of Airbnb accommodations},
doi = {10.1080/1331677X.2020.1831943},
author = {Sánchez Franco, Manuel Jesús and Alonso Dos Santos, Manuel},
}