The Disruptive Effect of Technological Innovation in the Tourist Accommodation Industry

This work focuses on the disruptive effect generated by online tourist accommodation platforms. This technological innovation has brought about changes not only in the tourism industry, but also in the lives of the citizens of host communities. This research analyzes the perception that citizens economically dependent on tourism have the socio-economic impacts linked to the activity of these online platforms. The field work was carried out in Spain in April 2020 by means of a survey in which citizens residing in one of the main tourist cities in the country took part. This analysis has allowed for the construction of four categories of positive impacts and four categories of negative impacts, all linked to disruptive technological innovation in the tourism sector. The most salient impact is related to how citizens economically dependent on tourism assess the changes taking place in the existing business network. This group’s assessment might possibly be the consequence of a shift in the focus of local businesses, which have gone from resident-oriented businesses to tourist-oriented businesses.

The most salient impact is related to how citizens economically dependent on tourism assess the changes taking place in the existing business network.

Modeling Cross-National Differences in Automated Vehicle Acceptance

The technology that allows fully automated driving already exists and it may gradually enter the market over the forthcoming decades. Technology assimilation and automated vehicle acceptance in different countries is of high interest to many scholars, manufacturers, and policymakers worldwide. We model the mode choice between automated vehicles and conventional cars using a mixed multinomial logit heteroskedastic error component type model. Specifically, we capture preference heterogeneity assuming a continuous distribution across individuals. Different choice scenarios, based on respondents’ reported trip, were presented to respondents from six European countries: Cyprus, Hungary, Iceland, Montenegro, Slovenia, and the UK. We found that large reservations towards automated vehicles exist in all countries with 70% conventional private car choices, and 30% automated vehicles choices. We found that men, under the age of 60, with a high income who currently use private car, are more likely to be early adopters of automated vehicles. We found significant differences in automated vehicles acceptance in different countries. Individuals from Slovenia and Cyprus show higher automated vehicles acceptance while individuals from wealthier countries, UK, and Iceland, show more reservations towards them. Nontrading mode choice behaviors, value of travel time, and differences in model parameters among the different countries are discussed.