We explore the key determinants of job satisfaction and employee turnover in high contact services studying employees' electronic word of mouth expressed through online reviews. We analyze a novel dataset of 297,933 employee online reviews for 11,975 US tourism and hospitality firms, taking advantage of both review valence and text. Our results exhibit that firms with high scores in leadership and cultural values yield higher employee satisfaction.Moreover, we show that career progression is a critical factor of employee turnover, with a unit increase in the career progression rating being accompanied with 14.87% reduction in the likelihood of an employee to leave the company. Most importantly, we quantify the effect of job satisfaction on firm profitability. In particular, an increase in job satisfaction by one unit is associated with an increase in Return on Assets between 1.2% and 1.4%. This finding is extremely important since we do not find evidence supporting the reverse relationship, that profitable firms increase employee's satisfaction. Overall, our empirical analysis indicates that the feedback to management provided through online employee reviews holds information value which can be enacted with specific managerial implications.

Service quality is a multi-dimensional construct which is not accurately measured by aspects deriving from numerical ratings and their associated weights. Extant literature in the expert and intelligent systems examines this issue by relying mainly on such constrained information sets. In this study, we utilize online reviews to show the information gains from the consideration of factors identified from topic modeling of unstructured data which provide a flexible extension to numerical scores to understand customer satisfaction and subsequently service quality. When numerical and textual features are combined, the explained variation in overall satisfaction improves significantly. We further present how such information can be of value for firms for corporate strategy decision-making when incorporated in an expert system that acts as a tool to perform market analysis and assess their competitive performance. We apply our methodology on airline passengers' online reviews using Structural Topic Models (STM), a recent probabilistic extension to Latent Dirichlet Allocation (LDA) that allows the incorporation of document level covariates. This innovation allows us to capture dominant drivers of satisfaction along with their dynamics and interdependencies. Results unveil the orthogonality of the low-cost aspect of airline competition when all other service quality dimensions are considered, thus explaining the success of low-cost carriers in the airline market.

Customers increasingly consult opinions expressed online before making their final decisions. However, inherent factors such as culture may moderate the criteria and the weights individuals use to form their expectations and evaluations. Therefore, not all opinions expressed online match customers' personal preferences, neither can firms use this information to deduce general conclusions. Our study explores this issue in the context of airline services using Hofstede's framework as a theoretical anchor. We gauge the effect of each dimension as well as that of cultural distance between the passenger and the airline on the overall satisfaction with the flight as well as specific service factors. Using topic modeling, we also capture the effect of culture on review text and identify factors that are not captured by conventional rating scales. Our results provide significant insights for airline managers about service factors that affect more passengers from specific cultures leading to higher satisfaction/dissatisfaction.

We examine the effect of employee satisfaction on corporate performance using employees’ online reviews. Our results indicate that although employee satisfaction positively impacts corporate performance, this is not fully reflected in equity prices

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