The main purpose of this degree project is to reveal the Airbnb customer’s preferences and quantify the impact of non-market factors on the market price of tourist accommodation in Berlin, Germany. The data retrieved from Airbnb listings, publicly available on Inside Airbnb (2017), was supplemented on indicator of sharing economy accommodation using machine learning method in order to distinguish between amateur and business-running professional hosts. The main aim is to examine the consumers’ preferences and quantify the marginal effect of "real sharing economy" accommodation and other key variables on market price. This is accomplished by model approach using hedonic pricing method, which is used to estimate the economic value of particular attribute. Surprisingly, our data indicates the negative impact of sharing economy indicator on price. The set of motivations of consumers, which determine their valuation of Airbnb listings, was identified. The trade-off between encompass and parsimony of the set was desired in order to build an effective model. Calculation of proportion of explained variance showed that the price is affected mainly by number of accommodated persons, degree of privacy, number of bedrooms, cancellation policy, distance from the city centre and sharing economy indicator in decreasing order.

In an age where the sharing economy has proliferated as a preferred means of travel in the tourism industry, and the accommodation sharing platform Airbnb has risen to the forefront, there is much criticism and discussion about the need for such nascent platforms to operate in alignment with sustainable development. Currently, economic benefits for the host and guest lie at the core of Airbnb’s sustainability appeal, while few concrete steps have been taken to advance environmental and social values. Many have proposed a green rating system and sustainability-oriented search filters as a means to propagate these values and catalyze a necessary paradigm shift within the sharing economy. Through the lens of green architecture and construction, this study analyzes the extent and manner in which sustainability features and amenities are promoted by hosts on Airbnb in the high-desert mountain town of Taos, New Mexico. This case study approach selects and intriguing destination that is not only characterized by a long history of earthen building traditions by the Tiwa people, but was also the birthplace of the world-renowned, off-the-grid Earthship concept. An analysis of all active Airbnb listings was compared with a more targeted analysis of off-the-grid listings to reveal that hosts more often than not frame their sustainability features and amenities in terms of visitor comfort, convenience, and enjoyment. For instance, the valorization of earthen adobe building for its authenticity and cultural appeal in lieu of its energy efficient and natural qualities. This indicated a high level of unexploited potential, wherein hosts could enhance their listing’s sustainability appeal and educational value through reframing these features to potential guests, and off-the-grid listings could benefit from implementing and promoting sustainable practices and emphasizing the local culture. Most importantly, after quantitively analyzing the features that arose, this study assembled the content basis for a theoretical green rating system and sustainability search filters that could be applied to Taos as a localized system, or merely provide insight to other destinations and the Airbnb platform as a whole.