Purpose: This study aims to measure the effect on prices through the differing characteristics and attributes of hotels. Design/methodology/approach: A hedonic price model (HPM) was adopted to estimate the impact of various site and situational factors on hotel prices in Warsaw, Poland. To better understand room rates not explained by HPM, spatial analysis of residuals was used. Datasets regarding prices from three different online travel agents (OTAs) and star ratings, either official or provided by OTAs, were investigated. Findings: A significant impact on hotel prices by star rating has been confirmed. Every additional star allows the hotel to set approximately 25 to 36 per cent higher prices, which is in line with previous studies. Moreover, two factors indicated a high but still underestimated theoretical hotel prices: location within the city centre and proximity to the international airport. Practical implications: The results of this study suggest that hoteliers should use a spatial analysis of room rates offered by the competing enterprises. Moreover, managers are expected to verify their price tactics and policies according to the geographical determinants of hotel prices investigated. Originality/value: The uniqueness of the study is highlighted by comparison of HPMs based on data from different OTAs, analysing differences in HPMs based on star ratings provided by OTAs and official systems and spatial analysis of residuals of estimated HPMs. Moreover, this study is among the first to examine the usage of HPM in the hospitality industry in East-Central Europe.

As the P2P (peer-to-peer) accommodation market is expanding, there is a growing interest in the factors affecting customer satisfaction. The previous literature largely concentrates on Airbnb users and tends to use online questionnaires as research data. To address this gap, we analyze the key attributes affecting customer satisfaction in the P2P accommodation market in 2020, the first year of the pandemic, based on onsite research. This will allow the authors to examine the key determinants of customer satisfaction across many platforms. Based on previous research, a conceptual model was developed, and two dimensions of service quality were created: host service quality and facility service quality. An offline primary survey was conducted, and the model was tested using exploratory factor analysis, correlation analysis, and regression analysis. The empirical results show a strong relationship between host service quality and facility service quality and customer satisfaction. This study provides clear theoretical insights to advance our knowledge about the determinants of customer satisfaction. Our results are in line with previous research, despite the survey being conducted during the first year of the pandemic and with the use of offline questionnaires. Furthermore, this study offers practical implications for both peer-to-peer and institutional market actors.

Purpose – This paper aims to identify major supply data sources for short-term rental market research and to provide their advantages and limitations. Methodology – In the paper a grounded approach was used based on a literature review. This review comprised two steps with the first being the query in major databases that was supplemented by academic search engine that resulted in 170 articles. The second step was to investigate the papers’ methodological sections to identify characteristics and limitations of all data sources. Findings – This study identifies three major data sources for the short-term rental market: web scraping with the use of self-made bots, Inside Airbnb and Airdna. A majority (e.g. 74% of papers using Airdna as a source) did not mention any limitations and provide no discussion about the data source, while the remainder gave only superfluous information about possible limitations of its use. Their characteristics and limitations are extensively discussed using a proposed framework that consists of three levels: intermediary, web scraping, and source-specific. Contribution – Very limited number of studies have focused on the short-term rental data sources and this is the first one that discusses advantages and limitation of their use. This paper may be of help to academics or professionals in identifying the right source of data to suit their technical knowledge, financial and technical resources and research areas.

Fair pricing used to refer to the problem of the buyer’s judgement of a seller’s price decision. Nowadays, when sustainability becomes a vital and fundamental consideration of tourism development, fair pricing should be discussed in a much wider context. The ethical context of fair pricing in tourism should be emphasised, as it is recognised as one of the transparent and ethical practices of tourism enterprises. In consequence, fair pricing is a significant element of corporate social responsibility and supports other goals like the beneficial partnerships of tourism enterprises with local communities and suppliers, providing equal opportunities and remuneration for the employees of tourism enterprises, as well as increasing the sustainable treatment of scarce natural resources. Fair pricing relates not only to the judgement of tourists (price versus value), but also to the opinion of the employees of tourism enterprises (price related to salaries), suppliers (price of finished product related to prices of raw materials and services), local communities (price versus income), and other stakeholders dependant on tourism industry in different ways. Finally, fair pricing must solve the issue of so-called “cheap nature”. This means that fair pricing relates to a valuation of ecosystem services, as tourism “consumes” environmental assets and significantly influences the cultural landscape. In consequence, fair pricing might contribute to the protection of bio- and geodiversity, climate, and cultural landscape. The aim of the chapter is to: (1) define fair pricing and discuss the evolutionary changes of the definition; (2) highlight the emerging importance of fair pricing in tourism; (3) review the theoretical concepts, empirical results, and practical applications of fair pricing; and (4) discuss the contribution of fair pricing to achieving sustainable development goals for tourism.