The search for happiness, understood as an inner and personal attitude that goes beyond mere satisfaction, is one of the aims of tourists’ co-creation of value. To date, few studies have analysed the importance of people’s moral principles in the co-creation of tourist value. Moral emotions play an essential role in this process. In this study, 12 tourism managers within administration, 28 hotel managers and 24 travel agencies actively participated in defining the indicators selected to measure how the co-creation of value from five Spanish towns affected customers’ happiness. Moreover, 444 tourists participated in the study. The PLS-SEM technique was used to examine the data obtained. Results show that the co-creation of value contributes to the happiness of the tourist. Of particular significance is the influence of customers’ co-creation of value on customer happiness. Additionally, the predictive capacity of the model is replicable to other tourist destinations.

The article proposes a planning model to develop tourism from a holistic perspective that includes economic, population and social aspects. Following a participatory methodology, the objective of the study is to propose a tourism planning model that contributes to the development of rural territories based on the involvement of tourism planners in the study. A total of 205 tourism planners and 443 tourism offices participated in the study. The data obtained were analysed using the PLS-SEM method. The results indicate that tourism planning has to be carried out by a professional team with diverse technical profiles that monitors the objectives set and adapts them to changes in the environment.

Purpose: This study aims to empirically examine the impact of generative artificial intelligence (GAI) on employee happiness within green hotel environments in Spain. By analyzing 221 eco-hotels, it explores how GAI influences the awareness of key sustainability indicators, environmental performance, process management, and sustainability – and how these, in turn, affect employee happiness. Employee happiness is directly related to occupational well-being and job satisfaction, fostering greater motivation, lower turnover and improved service quality. The study explores how advanced technologies foster sustainable, competitive and human-centered workplaces in hospitality, addressing gaps in happiness management research. Design/methodology/approach: This study uses a mixed-method approach combining focus group insights and PLS-SEM analysis of 221 Spanish Ecostars-certified green hotels, examining how generative AI impacts employee happiness, environmental performance, management processes and sustainability, providing a novel framework for Industry 5.0 competitiveness. Findings: The study confirms that generative AI positively influences employee happiness in green hotels by enhancing process efficiency, sustainability and environmental awareness. GAI improves management processes (61.6% variance), supports sustainable practices and enables fulfilling work. Environmentally driven performance significantly increases happiness, validating GAI and sustainability as key predictors for a competitive, responsible tourism sector. Originality/value: This first EU study links generative AI to employee happiness in Spain’s green hospitality sector, validating a PLS-SEM model that shows GAI fosters pro-environmental behavior, operational efficiency and well-being, challenging the view of AI as purely job automation.

This study investigates the implementation of dual training at the University of Extremadura (2023–2024), aiming to bridge theoretical academic knowledge with practical industry insights. This research utilizes SmartPLS 4.1.0.9 SEM-PLS software to explore the relationship between corporate engagement, academic outcomes, and sustainability challenges, validating hypotheses and refining dual training models in sustainability education. Key variables include Information Collection (IG), Sustainable Business Challenges (SCh), and Knowledge Developed by Business Strategies (KBS). The findings reveal that while the dual training model successfully integrates academic curricula with corporate engagement, it struggles to connect business strategies with actionable recommendations and has limited impact on improving teaching methods. This study identifies structural and practical barriers in the Spanish education system that hinder the full realization of dual training’s potential. To address these challenges, this research recommends incorporating continuous feedback mechanisms throughout the learning process and enhancing mentorship opportunities. Continuous feedback would allow students to refine their conclusions, leading to more practical and sustainable solutions. Additionally, the use of authentic case studies and greater industry involvement would help students bridge the gap between theoretical knowledge and real-world applications, enabling them to generate actionable recommendations and better understand sustainability challenges and business strategies. These recommendations aim to improve student learning outcomes and strengthen the integration of academic and corporate practices, fostering more effective sustainability education.

The sustainability of a territory is achieved through orderly, balanced and harmonious planning over time. Sustainable tourism planning must incorporate the emotions of interest groups. Based on a scale of negative and positive emotions that has already been validated, a participatory study of a qualitative nature has been developed with 118 hotel managers from the region of Extremadura, in the south-west of Spain. In addition, another quantitative research study has been carried out, using a longitudinal exploratory model analyzed in three phases throughout the years 2021 and 2022, using the SEM-PLS methodology. The objective is to detect if the II Tourism Plan (2021–2023) can influence the willingness of hotel managers to participate, and if this participation generates emotions that enrich the planning process of the tourist authorities. The results highlight the importance of completing decision making (cognitive part) with the measurement of emotions (sensitive part) of private agents to involve them in the planning process.

Purpose: This study aims to investigate the challenges of integrating artificial intelligence (AI) ethics to enhance employee happiness in high-interaction tourism workplaces, where emotional labor and continuous guest engagement increase stress and affect performance. Design/methodology/approach: This study used a mixed-methods approach, combining manager interviews with surveys of 558 employees and 130 managers. Using SmartPLS 4.1.1.4 for nonnormal data and complex mediation, the research is primarily confirmatory while also exploring underexamined intersections of ethical AI and employee happiness in tourism. Findings: Results show ethical AI impacts employee well-being (R² = 0.640) more than managers’ (R² = 0.414). Technostress reduction supports employees’ cultural integration, while transparency and fairness enhance managers’ empowerment. Data privacy shapes employee human capital development and hospitality perceptions, indicating role-specific priorities and ethical AI’s potential to boost happiness in service contexts. Originality/value: This study provides empirical evidence that ethical AI fosters employee well-being in tourism and hospitality. Offering a replicable framework for other sectors and regions, it links human-centered AI with human capital development, contributing to theory and practice while guiding the creation of employee-focused, ethically responsible AI strategies in service-intensive workplaces.