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In this paper, we analyse the long-run equilibrium demand of the peer-to-peer sharing economy. Our panel data demand model relates occupancy rates to relative prices of Airbnb and HomeAway listings, prices of competitors (hotels and apartments) and a proxy for income of tourists visiting the Canary Islands (Spain). We use a fractional heterogeneous panel data model which allows for a more general persistence and cointegration relationship and incorporates individual and interactive fixed effects. We find some evidence for (fractional) cointegration in P2P at the listing level. Regarding elasticities, classic cointegration methods give larger estimates for individual slopes and mean group coefficients than the fractional integrated heterogeneous model. Finally, own-price elasticities are inelastic, and the cross-price elasticity indicates that P2P listings and hotels are substitute goods. Income elasticity is lower than 1 and is not statistically significant, indicating that the demand for tourism in the Canary Islands is not sensitive to the economic conditions in the origin countries. [ABSTRACT FROM AUTHOR]

This paper analyses the determinants of tourist length of stay in sharing accommodation. Methodologically, the paper proposes a new approach to account for the observed bimodality of length of stay. More specifically, the determinants of length of stay are analyzed by modeling both the conditional mean and conditional modal frequencies, which represent shorter and longer tourist stays, unlike previous contributions on length of stay where modeling has been based exclusively on the conditional mean. The empirical analysis examines the length of stay in sharing accommodation lodgings (Airbnb and Homeaway) of tourists visiting the Canary Islands (Spain) before and after the outbreak of the COVID-19 pandemic. The results show a bimodal distribution of length of stay: 1 and 7 nights in the pre-pandemic period, reduced to 1 and 2 nights in the pandemic period. The results also indicate that the model approach followed in this paper is preferable to other previous bimodality models in terms of estimation simplicity and fit. In addition, the model allows an analysis of the determinants of length of stay and differentiation of the influence of each determinant on shorter and longer stays. [ABSTRACT FROM AUTHOR]

This paper analyses the effect of the different levels of hosts' professionalism (single and multi-unit host) and accommodation types on the time-varying technical efficiency of P2P accommodation. To do this, we employ a panel data stochastic frontier model which disentangles time-varying efficiency from unobserved heterogeneity. We use a database from Airbnb listings for the Canary Islands (Spain) from January 2019 to September 2020, including the lockdown period due to the Covid-19 pandemic. The results indicate that the lowest priced lodgings are the most efficient accommodation type and that properties managed by single-unit hosts are more efficient than those managed by multi-unit hosts. These results are theoretically founded on the existence of positive agglomeration effects in the hospitality industry. [ABSTRACT FROM AUTHOR]

This paper analyses whether peer-to-peer (P2P) accommodation substitutes traditional accommodation, taking into account dynamic and spatial spillover effects. We also analyse the impact of the COVID-19 pandemic crisis on the demand and substitution effect. To do this, we use a spatial dynamic panel data demand model for occupancy rates related to prices of P2P accommodation units, prices of competitors (hotels and apartments) and income. Its dynamic component allows estimation of the short- and long-term effects of prices and income on P2P accommodation demand. The model was applied to the P2P accommodation demand in the Canary Islands, Spain. The results indicate that, in the pre-pandemic period, occupancy rates were positively autocorrelated, demand was own-price elastic and substitution with hotels was significant in the short-term. This substitution effect and consumer sensitivity to prices and substitution increase in the long term. However, the irruption of COVID-19 largely distorted price and income-elasticities. [ABSTRACT FROM AUTHOR]

The aim of this study is to determine the presence or otherwise of transient and/or persistent cost inefficiency in the lodging industry. To do so, we applied the method proposed by Filippini and Greene, within a stochastic frontier panel data framework. Our empirical analysis is based on data for the hotel industry in the Canary Islands (Spain), an important destination for European tourists, for the period 2002-2015. Using a stochastic translog cost frontier model, we show that the industry's real output during the study period could have been achieved at 17% less cost if persistent (systematic) inefficiency were eliminated, and at 24% less cost in the absence of transient (nonsystematic) inefficiency. We also present evidence of factors that strongly influence hotels' transient cost efficiency, such as the positive effects of market share (in total revenue terms) and certain management characteristics, including the degree of independence with respect to shareholders, the experience in the industry (years in business) and the number of subsidiaries. [ABSTRACT FROM AUTHOR]

This study was conducted to analyse the influence of technological differences on hotel efficiency in the Canary Islands (Spain), with particular regard to the heterogeneity observed in hotel ownership and size. A metafrontier approach, based on non-parametric deterministic efficiency methods (data envelopment analysis and free-disposal hull) and robust non-parametric estimators (order-α), is used. This empirical analysis considered a panel data sample selection model of Canary Islands hotels for the period 2002–2015. The results obtained show that the frontiers against which the hotels are compared (metafrontier or group) and the consideration or otherwise of outliers are factors of crucial importance. We find that efficiency depends on hotel size (large hotels are more efficient than small ones), but not on the type of ownership. The results also show that the impact of the global financial crisis on the average technical efficiency of these hotels was slight or non-existent. Finally, the technological gap narrowed over time, especially in large hotels and those with no majority shareholder. [ABSTRACT FROM AUTHOR]

This article explores the spending patterns of tourists by market segments of expenditure distribution. We focus on the case of the Canary Islands, that is, a region that is one of the main destinations in the European tourism market, and distinguish between expenditure at origin and expenditure at destination. To do this, we use unconditional quantile regression (QR), which is more appropriate than conditional QR for the interpretation of coefficients. The results suggest that spending behaviour is heterogeneous among quantiles of expenditure in terms of income, price, level of loyalty and hotel accommodation effects. Furthermore, some differences arise between the pattern of expenditure at origin and the one at destination, and among items of expenditure at destination. [ABSTRACT FROM AUTHOR]

This article proposes a model of foreign tourist expenditure, based on expenditure in the country of origin (i.e. reservation of accommodation and transport) and on goods and services at the destination. The study focuses on two measures reflecting the two types of expenditure: the tourist budget share and the difference in growth rates between expenditure at origin and at destination. The random nature of each of these variables is taken into account. The tourist budget share is determined using a fractional response model, based on the beta distribution. This approach allows us to accommodate certain aspects of the empirical budget share distribution, such as skewness, and to represent the results as bounded between 0 and 1, but also to include covariates. The empirical analysis was conducted using data obtained by the Canary Islands Tourist Expenditure Survey, focusing on German and British tourists in particular. The results obtained show that the fractional regression model proposed represents the behaviour of the relevant variables reasonably well and surpasses the performance of the linear regression model. [ABSTRACT FROM AUTHOR]

The production of services in the accommodation sharing industry is heterogeneous in the sense that listings with different strategic management could adopt distinct technologies. This paper analyses the time-varying efficiency of the peer-to-peer accommodation sector using the input distance stochastic frontier model with random coefficients to accommodate both multi-input and multi-output technology and the technological heterogeneity among listings. An empirical analysis is conducted based on data from Airbnb and HomeAway listings in the Canary Islands (Spain), before, during and after the COVID-19 lockdown (source: AirDNA), in the period January 2019-September 2020 (monthly data). The results show technological heterogeneity between listings and time-varying inefficiency which negatively depends on productivity. Moreover, multi-unit hosts are clearly more efficient than single-unit hosts. A mean efficiency of around 78% during the study period was estimated. • The technological heterogeneity of the peer-to-peer accommodation is analysed. • The effect of the COVID-19 lockdown on the efficiency of listings is calculated. • A mean efficiency of 78% during the study period was estimated. • Multi-unit hosts are more efficient than single unit hosts. [ABSTRACT FROM AUTHOR]

Although the Poisson distribution is appropriate for modelling equi-dispersed distributions, it reflects bimodality less well. In this paper, we propose a distribution which is more suitable for the latter purpose. It can be fitted to both positively and negatively skewed data and appears to represent overdispersion phenomena correctly in count data models obtained using a Poisson distribution. Furthermore, the distribution can be normalised in terms of its mean value, and therefore covariates can be included. Our empirical results are based on tourists' length of stay in the Canary Islands (Spain), a popular holiday destination. The study analyses data supplied by the Canary Islands Tourist Expenditure Survey. Our findings show that the model presented is valid and that the fit obtained is reasonably good. [ABSTRACT FROM AUTHOR]