Investigating tourism efficiency of beach touristic centers in Mexico: application of dynamic two-stage DEA model and fuzzy time series forecasting Academic Article in Scopus uri icon

abstract

  • This study evaluates the tourism efficiency of 20 Mexican beach touristic centers using a novel dynamic two-stage Data Envelopment Analysis (DEA) model combined with fuzzy time series forecasting. The analysis spans a 10-year period from 2010 to 2019 and incorporates the dynamic DEA model based on time-window approach to capture efficiency trends across overlapping periods. Stage 1 of the DEA model assesses hospitality efficiency based on hotel capacity and its rating with the outputs represented by the rooms occupation rate and the number of tourist nights. The latter serves as the input to the Stage 2 which examines efficiency of the cultural heritage sector through museum and archeological site attraction and the number of their visits. The analysis focuses on two categories of destinations: Traditional beaches, developed between the 1950s and 1980s, and Other beaches. The findings highlight significant efficiency disparities between these two types of beach centers, with the latter demonstrating superior performance, particularly in attracting international tourists. Fuzzy time series forecasting, applied to the period 2020¿2023, helps to estimate the potential losses experienced by the tourism sector due to the COVID-19 pandemic, offering a basis for recovery planning. The findings suggest the need for revitalization strategies for Traditional beach centers, including cultural enhancement and infrastructure upgrades. The integration of dynamic DEA and fuzzy forecasting provides a robust framework for identifying trends and formulating data-driven tourism policies to enhance the competitiveness and sustainability of Mexico¿s coastal destinations. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

publication date

  • January 1, 2025