La relación entre la gestión de la calidad y el rendimiento empresarial en el sector hotelero

La mayor competitividad del sector hotelero a nivel mundial y la mayor exigencia de los turistas ha provocado que la gestión de la calidad se haya convertido en un factor importante para el éxito de los hoteles. Ante esta situación, este estudio empírico tiene como objetivo analizar si la gestión de la calidad mejora el rendimiento empresarial que alcanzan los hoteles. Para ello, en primer lugar, los hoteles se han clasificado en dos grupos, los que tienen un compromiso medio con la gestión de la calidad y los que tienen un compromiso alto. En segundo lugar, se comprueba que los hoteles que tienen un compromiso alto son los que alcanzan mayores rendimientos empresariales. Por lo tanto, se obtiene una relación positiva entre el compromiso con la gestión de la calidad y el rendimiento en el sector hotelero.

Multi-objective optimization of environmentally conscious chemical supply chains under demand uncertainty

In this work, we analyze the effect of demand uncertainty on the multi-objective optimization of chemical supply chains (SC) considering simultaneously their economic and environmental performance. To this end, we present a stochastic multi-scenario mixed-integer linear program (MILP) with the unique feature of incorporating explicitly the demand uncertainty using scenarios with given probability of occurrence. The environmental performance is quantified following life cycle assessment (LCA) principles, which are represented in the model formulation through standard algebraic equations. The capabilities of our approach are illustrated through a case study. We show that the stochastic solution improves the economic performance of the SC in comparison with the deterministic one at any level of the environmental impact.

A demand-driven analysis of tourist accommodation price: A quantile regression of room bookings

Tourist accommodation expenditure is a widely investigated topic as it represents a major contribution to the total tourist expenditure. The identification of the determinant factors is commonly based on supply-driven applications while little research has been made on important travel characteristics. This paper proposes a demand-driven analysis of tourist accommodation price by focusing on data generated from room bookings. The investigation focuses on modeling the relationship between key travel characteristics and the price paid to book the accommodation. To accommodate the distributional characteristics of the expenditure variable, the analysis is based on the estimation of a quantile regression model. The findings support the econometric approach used and enable the elaboration of relevant managerial implications.