Open innovation through customer satisfaction : a logit model to explain customer recommendations in the hotel sector

Open innovation allows the hotel industry to create platforms and channels for collaboration with its customers, which results in a better understanding of their tastes and demands. In the current environment, which is full of uncertainty, many companies have seen their profits decrease, and even the permanence of their businesses endangered due to the COVID-19 pandemic. In such an environment, it is even more necessary to take into account the customer's opinion about the service received, since once the customer makes use of the hotel's services, he/she will recommend the hotel to third parties if he/she is satisfied with it. Through customer satisfaction and subsequent recommendations, the hotel thus obtains new clients and retains old ones. This feedback from the client allows for understanding their priorities in order to jointly design a tailor-made service. It is for this reason that this research has been carried out to analyze the service attributes evaluated by customers. In order to achieve the proposed objectives, a survey instrument was used, as well as a longitudinal study procedure applying logistic regression over a period of one year. The descriptive results and the logistic regression show the level of customer satisfaction with the service and the importance given to each of the selected attributes. In this way, the research shows in which areas innovation strategies should be sought. Although the research offers a model composed of five attributes to measure satisfaction through recommendation with a probability of more than fifty percent, it is necessary to take into account the limitations of the current environment due to COVID-19 or the possibility of extending the multidimensionality of the model. It is necessary to continue to work through open innovation platforms to keep contact with the customer and to update the examined attributes in order to obtain customer satisfaction and feedback.