1,721,194 research outputs found
Stars vs lemons. Survival analysis of peer-to peer marketplaces: the case of Airbnb
No full textThis paper analyses the determinants of listings' survival on peer-to-peer marketplaces. Working on a dataset of Airbnb listings in Ibiza, we implement survival analysis to estimate the relationship between listings' key attributes and the probability to leave the platform. In addition, we highlight the importance of user-generated content to reduce the asymmetry of information and prevent adverse selection. Results confirm that listings' characteristics, location, degree of local competition and hosts' managerial skills, significantly affect the survival chance. Moreover, we found that low quality listings (proxied by the customer rating) are intended to disappear: the reviewing system successfully signals the quality on this market and drive the market selection process
Customer satisfaction during COVID-19 phases: the case of the Venetian hospitality system
No full textThis work presents a longitudinal analysis of hotel customer satisfaction, making a comparison between pre- and post-pandemic situations, as well as a detailed analysis of the evolution of customer satisfaction throughout the different phases of the COVID-19 crisis. To this end, we used representative microdata from more than 405,000 online reviews of 802 Venetian accommodation facilities. Data were retrieved from the Booking.com platform and cover the 2018-2021 period. Results point to a systematic reduction of customer satisfaction, although the negative effect is non-linear over time. In fact, the magnitude of the effect varies according to the severity of the phase (acute vs. transitional periods) and on the replication number of the phase type (first versus second wave), displaying some adaptation effects. The paper contributes to the literature on sustained crises, with an empirical application to one of the most popular tourist destinations. Our results suggest that hotel managers should respond to critical situations taking care of their customers' satisfaction identifying their different needs depending on the crises' phases
Distance Traveled in Times of Pandemic: An Endogenous Switching Regression Approach
Full text linkThis paper studies the change in the distance traveled by domestic tourists considering the pre- and post-pandemic outbreak summer periods of 2019 and 2020. Using representative monthly microdata involving more than 31,000 trips conducted by Spanish residents, we examine the heterogeneity in behavioral adaptation to COVID-19 based on sociodemographic and trip-related characteristics. To account for selection effects and the potential change in the population composition of travelers between the two periods, we estimate an endogenous switching regression that conducts separate regressions for the pre- and post-pandemic periods in a unified econometric framework. Our results point to heterogeneous shifts in the distance traveled by domestic travelers after COVID-19 outbreak per sociodemographic group, with notable differences by travel purpose and lower relevance of traditional determinants like income
Exposure to COVID-19 and travel intentions: Evidence from Spain
Full text linkThe outbreak of coronavirus disease 2019 (COVID-19) has disrupted the global economy. Since containment measures directly limit mobility and social interactions, the pandemic has substantially affected the tourism sector. This work explores the effect of COVID-19 exposure on people’s travel intentions during the summer of 2020 use representative survey data for 3873 individuals collected in Spain, one of the countries with the highest infection and mortality rates. We define exposure to COVID-19 at two levels: (i) zonal, according to the degree of limitations imposed in the zone where the respondent lives, and (ii) individual, according to whether the individual has personally suffered from COVID-19 symptoms. We perform regression analysis and propensity score matching and also consider potential treatment heterogeneity. The results consistently show that those who were more severely affected by the pandemic exhibit a relatively higher willingness to travel
COVID-led consumption displacement: A longitudinal analysis of hotel booking patterns()
No full textThis research contributes to the literature on consumption displacement by exploring the pandemic-led shifts in hotel booking patterns. We perform a longitudinal analysis and a critical comparison of bookings before and after COVID-19 outbreak, focusing on the booking window, length of stay, and booking channel. Data include weekly bookings of a representative sample of Balearic Islands’ hotels between 2018 and 2021. Results indicate that the pandemic has led to a drop in the volume of bookings and a remarkable change in booking patterns. Specifically, we find a temporal shift in booking behavior, characterized by a lower anticipation and a change in the tourism supply chain, namely a decrease in the share of intermediated bookings. The expected increase in the frequency of exogenous shocks, such as weather-related and sanitary crises, could affect purchasing behaviors, thus enhancing the relevance of this study, with managerial implications for industry and destination managers
‘Apparent’ and actual hotel scores under Booking.com new reviewing system
Full text linkIn September 2019, Booking.com changed its reviewing system based on the simple average of six items on a 2.5–10 scale by an unrestricted valuation on a 1–10 scale. This change has resulted in the drop of observed average scores. However, it is unclear which part of the shrinkage is due to the scale adjustment and which to priorly neglected aspects that consumers consider when valuing their satisfaction with the hotel stay. Using a dataset of more than 429,000 individual reviews for hotels in Madrid, Barcelona, Rome, Milan and Lisbon before and after the change, this paper disentangles apparent from actual changes in scores produced by the new scoring system. Using linear regressions and Propensity Score Matching, we show that, once the scale effect is left out, the new system has led to an increase by around 0.1 points in the actual valuation. Our results are potentially explained by the existence of unpacking effects
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