Applying Smarta to the analysis of tourist networks
March 06, 2025 Β· Declared Dead Β· π Mathematical methods in the applied sciences
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Miguel Lloret-Climent, JosuΓ©-Antonio Nescolarde-Selva, Kristian Alonso-Stenberg, AndrΓ©s Montoyo, Yoan GutiΓ©rrez-VΓ‘zquez
arXiv ID
2503.04307
Category
physics.soc-ph
Cross-listed
cs.SI
Citations
3
Venue
Mathematical methods in the applied sciences
Last Checked
4 months ago
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.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β physics.soc-ph
π
π
The Cartographer
R.I.P.
π»
Ghosted
Networks beyond pairwise interactions: structure and dynamics
R.I.P.
π»
Ghosted
Statistical physics of human cooperation
R.I.P.
π»
Ghosted
Vital nodes identification in complex networks
R.I.P.
π»
Ghosted
Influence maximization in complex networks through optimal percolation
R.I.P.
π»
Ghosted
Scale-free networks are rare
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted