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Purpose – The aim of this paper is to assess the performance of different widely-adopted models to forecast Italian hotel occupancy. In particular, the paper tests the different models for forecasting the demand in hotels located in urban areas, which typically experience both business and leisure demand, and whose demand is often affected by the presence of special events in the hotels themselves, or in their neighborhood.\ud \ud Design/methodology/approach – Several forecasting models that the literature reports as most suitable for hotel room occupancy data were selected. Historical data on occupancy in five Italian hotels were divided into a training set and a test set. The parameters of the models were trained and fine-tuned on the training data, obtaining one specific set for each of the five Italian hotels considered. For each hotel, each method, with corresponding best parameter choice, is used to forecast room occupancy in the test set.\ud \ud Findings – In the particular Italian market, models based on booking information outperform historical ones: pick-up models achieve the best results but forecasts are in any case rather poor.\ud \ud Research limitations/implications – The main conclusions of the analysis are that the pick-up models are the most promising ones. Nonetheless, none of the traditional forecasting models tested appears satisfactory in the Italian framework, although the data collected by the front offices can be rather rich.\ud \ud Originality/value – From a managerial point-of-view, the outcome of the study shows that traditional forecasting models can be considered only as a sort of “first aid” for revenue management decisions

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We analyze the problem of agents' interactions in a given population. The purpose of this paper is twofold. Starting from a scheme proposed by Galam [Physica A 320, 571 (2003)], which is based on a majority rule to treat the individuals' interactions, we first study some of its relevant properties. Then, we introduce special individuals, called opinion leaders, who play a key role in information spreading in several practical applications. Opinion leaders have the special feature of strongly interfering with the process based on the majority rule, speeding up the diffusion. We consider a model describing agents' interactions, which encompasses Galam's proposal, where opinion leaders are included as special agents. Then we study its specific properties which significantly recast and extend some conclusions drawn for the models given by Galam and Ellero, Fasano, and Sorato [Physica A 388, 3901 (2009)]. Finally, we provide theoretical and numerical results concerning the dynamics of our model, showing that a small percentage of opinion leaders may both accelerate and/or even reverse the overall consensus among all the agents.

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