Abstract
The purpose of this article is to develop a quantitative model that supports policy makers in the tourism sector in making socially responsible investment decisions. In particular, this paper proposes a methodological approach to assess the impact of strategic decisions at the policy level, in the field of tourism, from an economic, environmental and social point of view. The Calabria region, in Italy, has been chosen as a real-world case study. Based on historical data, the study identifies the main levers that influence tourism-related dynamics in Calabria. A quantitative forecasting model to support future investment decisions for sustainable tourism has then been developed. This problem is modeled through a multi-criteria optimization framework. To initialize such a framework, a non-linear autoregressive network with exogenous inputs (NARX) has been used. The proposed model is a flexible instrument to evaluate public investment policies in the field of tourism from the point of view of sustainability and social responsibility.
Highlights
Tourism is a sector with a strong economic, environmental and social impact
In the first stage of the analysis, in which a set of relationships is developed through a non-linear autoregressive network (NARX), we consider the possibility that the impact of some decision variables on an objective response could be achieved only after a certain amount of time
We describe how we have developed a predictive model from a time series of data related to Calabria and how the model can be used to make future decisions
Summary
Tourism is a sector with a strong economic, environmental and social impact. National and regional governments which invest in tourism need to consider the problem of making socially responsible decisions. This work aims at supporting socially responsible strategic investment decisions taking into account drivers related to socio-environmental aspects To achieve this goal we examine the impact of tourism on the quality of life of a community. In the first stage of the analysis, in which a set of relationships is developed through a non-linear autoregressive network (NARX), we consider the possibility that the impact of some decision variables on an objective response could be achieved only after a certain amount of time (years) This is relevant, since it might be possible that public funding used for the activation of multi-year projects generates an immediate social value due to the newly created job positions and a delayed economic return due to the project outputs
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