Applying Smarta to the analysis of tourist networks

TL;DR

The paper addresses how to assess the life-cycle stage and sustainability of a mature tourist destination by modeling Benidorm as a dynamic network. It uses Smarta, a causal-simulator based on conditional probabilities, to analyze INE occupancy data for hotels, campsites, and dwellings from January 2016 to October 2018, applying a strict correlation threshold of $|r| \geq 0.935$ to extract 51 cause–effect pairs across 26 variables. This yields six attractors, $A_1$–$A_6$, that map to distinct supply-demand interactions and occupancy dynamics, revealing a rejuvenation phase in Benidorm’s tourism life cycle. The approach demonstrates Smarta’s utility as a diagnostic tool for destination dynamics, complementing traditional causal maps and enabling dynamic, period-specific insight into complex tourism systems. The work also sets the stage for future comparisons with pre/post-COVID and Brexit-era data to evaluate robustness and adaptability of the attraction cycles.

Abstract

The framework of the present study was the destination life cycle model, a classical model that describes the development of tourist destinations. We examined mass tourism in Benidorm based on tourist accommodation supply and demand statistics over the January 2016 - October 2018 period, provided by Spain's National Institute for Statistics. The objective was to analyze the life cycle and competitiveness of Benidorm's tourism system, interpret whether the tourism product was sustainable, and at what stage in the cycle Benidorm is currently in. To do this, we used Smarta software, which, based on network analysis, enables to interpret the system's virtuous cycles and analyze causality by observing relationship patterns in the system's attractors, thus complementing typical processing based on causal maps and the study of social networks. The results obtained by this application (which has been developed by our research team), show 6 sets of attractors that mark the trends of the tourist system. Finally, the analysis of the significant variables of these attractors have helped to justify that the tourist system of Benidorm is in the rejuvenation phase.

Figures (6)

• Figure 1: Work process in the Smarta software.
• Figure 2: Directed graph of the databases of the Benidorm occupancy survey (period Jan. 2016 - Oct. 2018).
• Figure 3: Representation of the significant variables of the $A_1$ attractor.
• Figure 4: Representation of the significant variables of the $A_2$ attractor.
• Figure 5: Representation of the significant variables of the $A_3$, $A_5$ and $A_6$ attractors.