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Purpose -Online reviews have become increasingly important for customer decisionmaking. The hotel industry represents a noticeable case. Consumer reviews posted on websites such as Bookings.com, TripAdvisor, and Venere.com play a critical role in consumers' choice of a hotel. For this reason a number of recent studies analyses different aspects of online reviews. The purpose of this paper is to investigate their effects in terms of hotel occupancy rates.Design/methodology/approach -The paper measures through regression analysis the impact of three dimensions of consumer reviews (i.e. review score, review variance and review volume) on the occupancy rates of 346 hotels located in Rome, isolating a number of other factors that might also affect demand.Findings -Review score is the dimension with the highest impact. The results suggest that, after controlling for other variables, a one-point increase in the review score is associated to an increase in the occupancy rate by 7.5 percentage points. Regardless the review score, the number of reviews has a positive effect, but with decreasing returns, implying that the higher the number of reviews, the lower the beneficial effect in terms of occupancy rates is.Practical implications -The findings quantify the strong association of online reviews to occupancy rates suggesting the use of appropriate reputational management systems to increase hotel occupancy and therefore performance.2 Originality/Value -A major contribution of this paper is its comprehensiveness in analysing the relation between online consumer reviews and occupancy across a heterogeneous sample of hotels.

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Drawing on the services marketing and sharing economy literature, the study identifies the leading reputational attributes that boost popularity in sharing economy platforms. As popularity stands as a purchase decisionmaking tool, the purpose of this paper is to jointly examine the influence of personal reputation and product description. A sample of Airbnb listings was collected in November 2016 in Italy and UK (n=502). The database consists of popularity variables along with personal reputational attributes and the description of the product being offered. The findings of the study, based on the Shapley Value Regression, suggest that personal reputation is of paramount importance, explaining alone almost 40% of popularity variation. The paper concludes with theoretical implications on self-branding and, given the importance weights of the different attributes in popularity building, practical implications for sellers operating in sharing economy platforms.

The study aims to contribute to the research on service quality, analyzing almost 30 years of research on the Gaps Model proposed by Parasuraman, Zeithaml and Berry in the 1980s. A literature review has been conducted from 1985 to 2013 with the purpose of underlining the model evolution and its criticisms. Major international academic databases have been consulted.On this basis the paper summarizes some theoretical-conceptual and methodological-operational critical aspects identified by scholars who analyzed and applied the model and the scale. Despite that, the Gaps Model and the SERVQUAL scale are still the most used instruments to study service quality in marketing literature.The analysis allows to identify interesting points for future research on the topic of service quality. The conceptual framework presented in the paper does not include any empirical research that could be eventually implemented to validate the findings.