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This study aims to provide a new perspective on the factors determining a country’s tourism performance, understand the interrelationships among these factors and explore their implications for the future of tourism in high-income countries.

The study employs a fuzzy-set qualitative comparative analysis (fsQCA) using five variables from the World Economic Forum’s Travel and Tourism Development Index (TTDI). The focus is on identifying seven configurations of antecedents of Travel and Tourism Industry Gross Domestic Product (T&T Industry GDP).

The study identifies seven configurations of antecedents influencing T&T Industry GDP, revealing how these factors operate in different scenarios, specifically in countries with high and low T&T GDP. These configurations offer insights into potential future pathways for tourism development.

The study implies that tourism is a complex phenomenon influenced by multiple interacting factors. It provides a framework for understanding how different combinations of factors can lead to high or low tourism performance, offering valuable insights for anticipating and shaping the future of tourism.

This study adds value by providing a more nuanced understanding of the tourism industry, challenging the notion of singular effects of variables and highlighting the importance of analyzing multiple, interacting factors in understanding and predicting tourism performance. It contributes to the field of futures studies by offering a tool for anticipating potential future scenarios and their impact on the tourism industry.

Agribusiness shows a growing degree of competitiveness and innovation. However, the organizational mechanisms that compete for innovation and organizational performance are not sufficiently studied. Thus, this study aims to analyze the influence of market orientation and organizational structure on innovation generated and its influence on market and financial performance in agribusiness firms in Extremadura (Spain).

A conceptual model was designed and tested. Data were collected from a questionnaire sent to innovative agri-food companies. The analysis of the model methodologically combines partial least square structural equation modelling, necessary condition analysis and importance-performance map analysis.

The main results reveal that low levels of innovation ambidexterity impact significantly performance but when compared to exploitative innovation, explorative innovation shows a stronger influence on the market and financial performance.

The results are intended to be useful to managers to improve their innovative performance by incorporating new strategies in the market orientation and organizational structure.

The originality of this research lies in the novelty of the proposed mediators, as well as the sector under study. The study expands the knowledge of the influence that market orientation and organizational structure have on the types of innovation (exploitative/explorative).

This study aims to examine the impact of market-driven policies on adoption and integration of green chemistry into higher education in Saudi Arabia, uncovering challenges and opportunities faced by educators and institutions in promoting sustainable scientific education.

This study used a grounded theory methodology to explore the integration of green chemistry in Saudi Arabian higher education amid market-driven policies. In-depth interviews were conducted with 22 participants, and data were analyzed using a systematic coding process.

The study reveals that market-driven policies significantly influence the integration of green chemistry by prioritizing immediate economic returns over long-term sustainability goals. Key challenges include securing funding and aligning green chemistry with traditional curricula. Opportunities to promote sustainability through curricular reform and policy adaptation were identified.

This study is limited to Saudi Arabian higher education, which may affect the generalizability of findings to other contexts.

Insights suggest policymakers should re-evaluate prioritization of short-term economic gains and develop incentives to integrate green chemistry. Institutions are encouraged to invest in faculty development, adopt interdisciplinary approaches and collaborate with industry and government.

Integrating green chemistry into higher education promotes environmental stewardship and prepares future generations to address sustainability challenges. Institutions can shape environmentally conscious societies by fostering a culture of sustainability and ethical responsibilities.

This study contributes to discourse on sustainability in education by providing a grounded theoretical analysis of the dynamics between market-driven policies and green chemistry integration, offering insights for policymakers, educators and researchers.

This study aims to provide a comprehensive, textometric analysis of the evolving Quality 4.0 (Q4.0) research, identifying key themes, emerging trends and critical research gaps in the field.

A total of 129 peer-reviewed articles on Q4.0 were analyzed using IRAMUTEQ software. The textometric approach employed includes lexicographic analysis, descending hierarchical classification, factorial correspondence analysis and similarity analysis to uncover underlying patterns in the literature.

Three major clusters emerged from the analysis of Q4.0 research: (1) the digital transformation of quality management practices, (2) technological enablers of Q4.0 and (3) organizational implications of Q4.0 adoption. Key themes identified include the integration of Industry 4.0 technologies (e.g. IoT, AI and big data) into traditional quality management systems, the role of artificial intelligence in quality control and the challenges organizations face during Q4.0 implementation. This research also conceptualizes a comprehensive framework that outlines a strategic roadmap for Q4.0 adoption and integration, including the identification of antecedents and consequences of Q4.0 implementation. Additionally, the study proposes a measurement scale for assessing the dimensions of Q4.0.

The research proposes valuable implications for practitioners and organizations seeking to implement Q4.0 strategies as well as for researchers in the field of digital transformation and quality management. The proposed conceptual framework serves as a practical guide for effectively navigating Q4.0 implementation in diverse organizational contexts.

This study presents an innovative approach by applying textometric analysis to the field of Q4.0, offering an objective, data-driven perspective on the existing literature. It identifies significant gaps in research and proposes future avenues for investigation. As one of the first studies to develop a conceptual framework for Q4.0, including its antecedents, consequences and a measurement scale, this research provides a foundational contribution to the growing body of knowledge on Q4.0.

This study aims to investigate the relationship between patient satisfaction (PS) and the parameters in healthcare and supply chain management (HLSCM).

The structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA) method have been employed to identify correlation and possible configuration of causal factors that influence PS, including lack of resilience (LS), lack of visibility (LV), cost management (CM) and integration and interoperability (II).

The results from SEM confirmed that PS is highly correlated with lack of visibility, CM and II as critical parameters. Moreover, fsQCA findings state that the configuration of high levels of both resilience and lack of visibility, as well as high levels of II, are crucial for PS.

The researchers also identified the configuration of factors that lead to low PS. The study’s results could assist healthcare providers in improving their supply chain operations, resulting in more effective and efficient healthcare service delivery and ultimately improving PS.

The fsQCA method used in the study provides a more nuanced understanding of the complex interplay between these factors. The inclusion of supply chain management characteristics as parameters in the evaluation of PS is a novel aspect of this research. Previous studies largely focused on more traditional factors such as physical care, waiting times and hospital amenities. By considering supply chain management factors, this study provides insights into an under-explored area of PS research, which has important implications for healthcare providers looking to improve their operations and PS.