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Smart tourism is a destination management approach that requires the buy-in of a myriad of stakeholders. Its many audiences and complexity demand the creation of meaningful brands to effectively position and communicate smart tourism initiatives. The purpose of this paper is to explore how smart tourism branding strategies have been implemented to communicate relevant values, benefits and attributes to industry stakeholders through institutional websites.

Based on a semiotic analysis of two smart tourism-related sites (destinosinteligentes.es and smarttourismcapital.eu), the research interprets the brand-related visual and verbal signs.

The findings highlight how brand elements embedded in websites communicate a brand identity and facilitate particular interpretations of smart tourism. Both brands use similar signs to promote a techtopian vision of smart destinations but employ different strategies to motivate stakeholder buy-in.

Smart tourism is currently largely embedded in overall smart city initiatives and finding tourism-specific examples online is difficult. However, the two selected websites reflect the brands of multiple destinations and permit a detailed analysis of meaning making. Future research can focus on how brand-related signs are perceived by different stakeholders.

Identifying the strategies and shortcomings of current smart tourism brands informs future smart tourism branding efforts and effective communication with smart tourism stakeholders.

Semiotics is a relevant but underutilized method to understand how smart tourism initiatives conceptualize “smartness.”

The purpose of this paper is to propose physically based varying fidelity surrogates to be used in structural design optimization of space trusses. The main aim is to demonstrate its efficiency in reducing the number of high fidelity (HF) runs in the optimization process.

In this work, surrogate models are built for space truss structures. This study uses functional as well as physical surrogates. In the latter, a grid analogy of the space truss is used thereby reducing drastically the analysis cost. Global and local approaches are considered. The latter will require a globalization scheme (sequential approximate optimization (SAO)) to ensure convergence.

Physically based surrogates were proposed. Classical techniques, namely Taylor series and kriging, are also implemented for comparison purposes. A parameter study in kriging is necessary to select the best kriging model to be used as surrogate. A test case was considered for optimization and several surrogates were built. The CPU time is reduced when compared with the HF solution, for all surrogate‐based optimization performed. The best result was achieved combining the proposed physical model with additive corrections in a SAO strategy in which C1 continuity was imposed at each trust region center. Some guidance for other engineering applications was given.

This is the first time that physical‐based surrogates for optimum design of space truss systems are used in the SAO framework. Physical surrogates typically exhibit better generalization properties than other surrogates forms, produce faster solutions, and do not suffer from dimensionality curse when used in approximate optimization strategies.