Analyzing online reviews in hospitality: data-driven opportunities for predicting the sharing of negative emotional content

Hospitality is one of the sectors that are nowadays most heavily characterized by consumers’ tendency to share online reviews on dedicated digital platforms. While most past work has focused on understanding the effect of online reviews and ratings on consumers’ evaluation and purchase decisions, this research tackles the issue of what drives the sharing of certain types of online content. Specifically, we investigate the sharing of user-generated content characterized by negative emotional valence, and study the effect of two factors on the extent to which user-generated content contains negative emotions. One such factor is reviewer's expertise, while the other is hotel quality. Our analysis of 1200 TripAdvisor reviews on Italian hotels located in three major Italian cities confirm our hypothesis that expert reviewers might share reviews containing less intense negative emotional content compared to less expert reviewers especially when the hotel is of high quality. To support our hypothesis, we build on the research on psychological antecedents of word-of-mouth behaviour suggesting that expert consumers are particularly reluctant to share negative word-of-mouth to avoid projecting a negative image of themselves in social contexts, thus possibly damaging their reputation.     

EXPERIMENTAL AND SELF‐REPORTED MEASURES OF RISK TAKING AND DIGIT RATIO (2D:4D): EVIDENCE FROM A LARGE,SYSTEMATIC STUDY

We systematically investigate the links between the digit ratio (2D:4D)—a biomarker for prenatal testosterone exposure—and two measures of individual risk taking: (i) risk preferences (RP) over lotteries with real monetary incentives and (ii) self‐reported risk attitude (RA). We find that both the right‐hand and the left‐hand digit ratio are significantly associated with RP: Subjects with lower digit ratios tend to choose riskier lotteries. Neither digit ratio, however, is associated with self‐reported RA.     

Does apprenticeship improve job opportunities? A regression discontinuity approach

In Italy the main difference between apprentices and other types of temporary workers is that apprentices must receive firm-provided training. The firm incentive in hiring apprentices consists in paying lower wages and labour taxes. Using an Italian administrative dataset containing information on the jobs started between January 2009 and June 2012, we estimate the effect of apprenticeship on the hazard function to a permanent job. Identification is based on a regression discontinuity design. We find that, for 29-year-old workers, apprenticeships are “long entrance halls” towards permanent contracts, especially within the firm where the apprenticeship is performed.

     

State-owned banks in the market for corporate control

We study the pre-deal characteristics of state-owned banks acquiring other companies, relative to their private counterparts. We build a unique international data-set of 3682 deals in the years 2003–2013. Econometric results highlight that those state-owned banks that are acting as acquirers have an ex-ante performance similar to their private benchmarks. The results are driven by the role of development banks. This new finding points to the recent evolution of some types of contemporary state-owned financial players.     

Likelihood evaluation of models with occasionally binding constraints

Applied researchers interested in estimating key parameters of dynamic stochastic general equilibrium models face an array of choices regarding numerical solution and estimation methods. We focus on the likelihood evaluation of models with occasionally binding constraints. We document how solution approximation errors and likelihood misspecification, related to the treatment of measurement errors, can interact and compound each other.