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Studies on the impact of tourism in art cities underlined that many cities begun to suffer too many costs because of mass tourism. The problem of costs/benefits balance was in some case further complicated by the quick increase in a peculiar kind of excursionists — the so called false excursionists. Their increase is in fact joined with the spreading around the city of “alternative” accommodations. But false excursionists bring to the destination more costs and less benefits than traditional tourism, as a relevant part of their budget is spent where they are lodging. Thus, this sort of tourism “development” calls for visitors management policies able to reduce costs and maximize the tourism benefits for the city. But these policies require a deep understanding of the relationship between demand and accommodation supply, and between accommodations within and outside the city. And, more important, a continuous monitoring on how these relationships change in time, and why. Pricing and product strategies put into effect by accommodations, joined with changes in the demand behaviour, are in fact the basic variables of a mechanisms that might eventually lead to a substantial increase in false excursionists number and a stagnation in overnight tourists demand, with major consequences on the cost/benefits ratio for the art city as a whole. Aim of this paper is to introduce a set of 10 indicators and, through their application on the Venice situation, show how they can be used to analyze on diachronic terms the impact of accommodation evolution on demand choice.

The purpose of this paper is to analyze the dynamic competitive profile of Istanbul and to compare it to ten other European cities by using a multidimensional approach.

Starting from a review of existing competitiveness models, the paper develops a methodology that takes into account the complex shifting nature of the network of “mobilities” interacting within and around the destination.

The proposed approach proves to be effective in designing a dynamic competitive profile of every city and in identifying the factors that drive competitiveness within and between different competitive clusters of cities.

The new approach presents several original elements, since it embeds the evolution of the system of diverse intersecting tourism and non tourism “mobilities” that characterize an urban destination, and integrates different dimensions and disciplinary points of view.

The purpose of this study is to reveal the research trends in guest experiences of service robots in the hospitality industry.

In this study, a review was carried out on the Web of Science (WoS) database with the assistance of bibliometric analysis techniques. Cluster analysis was also employed for this to group important data to determine the relationships and to visualize the areas in which the studies are concentrated. The thematic content analysis method was used to reveal on which customer experiences and on which methods the focuses were.

On the subject of experiences of service robots, the greatest number of publications was in 2021. In terms of country, China has come to the fore in the distribution of publications. As a result of thematic content analysis, it was determined that the leading factor was the main dimension of emotional experience. In terms of sub-dimensions, social interactions attracted more attention. Most of the studies discussed were not based on any theory. Apart from these, the Technology Acceptance Model (TAM), the Service Quality Model (SERVQUAL) and Perceived Value Theory (PVT) were featured more prominently among other studies.

In this study, only the WoS database was reviewed. In future studies, it would be possible to make contextual comparisons by scanning other databases. In addition to quantitative research designs, social dimensions may be examined in depth following qualitative research methods. Thus, various comparisons can be made on the subject with mixed-method research designs. Experimental research designs can also be applied to where customers have experienced human-robot interactions (HRIs).

In the hospitality industry, it is critical to uncover every dimension of guests' robot acceptance. This study, which presents the current situation on this basis, guides future projections for the development of guest experiences regarding service robots in the hospitality industry.