The Toyota Production System (TPS) was a revolutionary approach to automobile production that influenced companies all over the world. The fight against redundancy is at the core of this approach. The textile industry remains one of the most polluting sectors worldwide, which makes environmental sustainability a key concern. In line with national priorities, companies are striving to balance profitability with sustainability, minimizing defects and reducing waste. This study explores the evolution of textile production systems from TPS principles to the integration of Artificial Intelligence (AI) and how they can be used from a sustainability perspective. Smartex, a textile start-up recognized as the winner of the Web Summit 2021 competition, was chosen as the focus of this case study. Employing qualitative research methods, including content analysis of interviews, management reports and website data, the study examines the parallels and distinctions between TPS and Smartex’s AI-driven system. The findings highlight how Smartex is revolutionizing the textile industry by leveraging AI to avoid defects and reduce waste, advancing both environmental and commercial objectives. Finally, the implications and limitations of the research are explained.

This study examines the role of agritourism in developing strategies to promote a circular economy by applying the 3Rs (reduce, reuse, and recycle) and improving guests’ satisfaction. It contributes to filling the gap in the literature regarding the challenges posed, impact evidence, potential trade-offs, and socioeconomic considerations for the application of the 3Rs strategy in small tourism businesses. Interviews with hotel owners/hosts and guests were conducted through mainly qualitative methods, and the content was analyzed. This study reports on a case study conducted with a convenience sample of customers from a rural tourism company in Portugal to assess their position concerning the company’s 3Rs strategy. The case study reveals that common categories—hosts, breakfast, decoration, environment, and comfort—appreciated by guests align with the 3Rs practices. It was found that being environmentally responsible, taking part in the circular economy, and interacting with it can improve not only the satisfaction of guests but also hosts, thus creating memorable experiences for both. This study also shows that the position of customers regarding the 3Rs is not monolithic, with reusing and recycling emerging most prominently. This study shows that, in this context, a circular economy is feasible, provides tangible benefits, and successfully combines operational efficiency and guest convenience. This study also shows that it is possible to establish a successful tourism supply strategy based on a circular economy, particularly the 3Rs. Still, this strategy should not look at the 3Rs as if they were a uniform reality.

This study explores the motivations of students pursuing a university degree in hospitality and tourism and their intention to build a career in the sector. The research focused on students and recent graduates (up to two years post-graduation) from two universities in Portugal’s largest cities, Lisbon and Oporto, offering Hotel/Tourism Management programs. A quantitative study was carried out, and out of 610 questionnaires distributed, 346 valid responses were analysed using the structural equation modelling technique. Findings indicate that personal motivations, as well as macro and micro perspectives, influence the decision to pursue a degree in hospitality and tourism. Younger individuals with no prior industry experience tend to have a more optimistic outlook compared to older students or those with work experience. A key challenge is sustaining this optimism throughout their careers, which can enhance job satisfaction and improve retention in a sector known for high turnover rates. Unlike previous studies, this research links students’ motivations to their “Ikigai”—the pursuit of purpose and fulfilment. The desire to create meaningful experiences for others adds another dimension to understanding students’ motivations, particularly when considering differences in age and work experience.

The hospitality industry is a cornerstone of Portugal's economy, yet it continues to struggle with attracting and retaining qualified personnel. This qualitative study explores the core dynamics shaping talent recruitment and workforce sustainability in Portugal's hospitality sector, based on 25 semi-structured interviews. The findings reveal that while many professionals enter the sector driven by passion, family influence, or the pursuit of career advancement, long-term retention is hindered by low wages, limited recognition, and challenging work conditions. Employers face a pronounced shortage of skilled labor—particularly for operational roles—and increasingly rely on foreign workers, driven in part by the declining interest of Portuguese nationals. By capturing both employer strategies and workforce sentiment, this study offers a comprehensive view of the recruitment landscape and calls for collaborative interventions from industry, educational institutions, and government bodies to secure the future of Portugal's hospitality workforce.

Background: Population ageing, increasing care demands, and rapid advances in artificial intelligence and robotics have intensified interest in care robots as potential tools to support independent living and complement human caregiving. However, the successful implementation of robotic technologies depends largely on public acceptance, which is influenced by functional, psychological, ethical, cultural, and generational factors. Objective: This study examined generational differences in the acceptance of care robots among Portuguese adults by integrating the Almere Model of technology acceptance with the Katz Index of Activities of Daily Living (ADL) and the Lawton–Brody Instrumental Activities of Daily Living (IADL) Scale. The research sought to determine whether acceptance varies according to generation and the type of caregiving activity performed by the robot. Methods: A cross-sectional quantitative study was conducted using an online questionnaire administered to a purposive sample of 235 adults residing primarily in the Lisbon Metropolitan Area, Portugal. The questionnaire combined constructs from the Almere Model with perceptions of robotic assistance for ADLs and IADLs. Principal Component Analysis, reliability analysis, descriptive statistics, and inferential analyses were performed to examine differences across generational groups. Results: Acceptance of care robots was strongly task-dependent. Participants expressed significantly greater acceptance of robots assisting with instrumental activities, including housekeeping, shopping, transportation, meal preparation, and medication management, than with intimate personal care activities such as bathing, dressing, toileting, feeding, and continence care. Contrary to common assumptions regarding digital natives, Generation Z reported higher levels of fear, discomfort, and perceived intimidation than Generation X and Baby Boomers. Older generations generally demonstrated more pragmatic acceptance of robotic assistance, particularly regarding future support needs associated with ageing. Across generations, respondents preferred robots with more human-like appearances; however, emotional trust remained substantially lower than perceived functional usefulness. Conclusions: The findings suggest that acceptance of care robots is conditional rather than universal and is shaped by the nature of the caregiving task, generational differences, and broader emotional and cultural perceptions of care. Integrating the Almere Model with established ADL and IADL frameworks provides a novel perspective by linking technology acceptance to specific functional domains of caregiving. The results support the view that care robots are more likely to be accepted as complementary tools that enhance human-centred care rather than as substitutes for professional or family caregivers. Given the purposive and geographically limited sample, the findings should be interpreted cautiously and not generalised to the wider Portuguese population. They nevertheless provide valuable implications for the design of socially assistive robots, healthcare practice, and public policy in ageing societies.