Presenter: Alessandro Destefanis
Monday, November 16th, 2020 17:30
Location: Microsoft Teams – click here to join
Alessandro Destefanis: Airbnb Adoption Process From Home-Owners Perspective In Italian Market
Sharing economy platforms have seen impressive growth in the last years, both in terms of the number and value of transactions and the variety of services deployed. This fact has had a profound impact on everybody’s life and changed the structure of many value chains, with the services sector being the most affected one. Among the others impacted by sharing economy arrival, the tourism industry has been under steady pressure, and it is still reshaping itself in terms of players involved, their role and the value generation and appropriation capabilities they have. In the particular case of peer to peer sharing economy platforms, the main reasons why they have been able to change so much the structure of their sectors is the quick adoption rate from both supply and demand side. For example, the most important and successful peer to peer sharing economy platform in the accommodation sector, Airbnb, has been able to exponentially grow from zero to million rooms in just a few years of operations. The adoption process of innovative technological solutions is not a new topic, but the diffusion process of peer to peer sharing economy solutions in still mostly unexplored due to the novelty of the phenomenon. In particular, there is a gap in the literature regarding the specific characterization of markets and the adoption rate of the platform. In particular, this work aims to reason about some issues regarding Airbnb’s supply diffusion such as differences among geographical areas according to the type of diffusion, imitative or spontaneous; the impact of industry-specific variables on Airbnb’s growth velocity and the current state of the diffusion process concerning the market potential. Moreover, beyond these research questions, this work represents a base to compare the effect of the Covid-19 pandemic on the diffusion process as it is a snapshot of Airbnb right before the beginning of the virus’ emergency. This work analyzes Airbnb home-owners’ adoption rate applying the Bass diffusion model. According to the Bass model, results will provide estimates of whether adoption is more spontaneous or innovative. The study takes into consideration the entire Italian market, considering the diffusion of the platform since its entry-date. The research shows and explains the differences between touristic areas: traditional ones compared to newer ones, where Airbnb could be considered a tourism-enabler.
Biography: Management, production and design PhD student at the Interdepartmental Centre for SmartData in Politecnico di Torino under the supervision of Paolo Neirotti. Research area is data driven strategic decision making and value creation.