Abstract
Tourism has a positive effect on economic growth in large and small countries. The combination of technology and applications is referred to as Tourism 3.0. In this chapter, we propose a tourism app to produce personalized trip itineraries. The app has embedded a genetic algorithm that searches for the best choices of places to maximize the tourist’s satisfaction. However, running a genetic algorithm in a standard smartphone suppose to be a challenge since a standard smartphone is a constrained device. The above may affect the tourists’ behavior towards using our proposed tourism app. Then, to evaluate tourists’ attitudes toward using our tourism app based on a genetic algorithm, we apply the technology acceptance model. Results show that most test participants found our tourism app easy to use. They also show a strong positive correlation between attitude towards use and intention to use.
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Cosío-Léon, M.A., Martínez-Vargas, A., Lopez-Sanchez, M., Silva-Rodríguez, V. (2023). Genetic Algorithm to Maximize the Tourist’s Satisfaction: An Assessment of Technology Adoption for a Tourist App. In: Kulkarni, A.J. (eds) Optimization Methods for Product and System Design. Engineering Optimization: Methods and Applications. Springer, Singapore. https://doi.org/10.1007/978-981-99-1521-7_13
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