Journal of Foresight and Health Governance

The present study was applied–developmental in terms of purpose and qualitative in terms of implementation. The statistical population (participants) consisted of a number of key informants from the Department of Education of Khuzestan Province. In the qualitative phase, the sample size reached theoretical saturation at eight participants through purposive sampling. The research instrument comprised semi-structured interviews. Data analysis was conducted using theoretical coding derived from the grounded theory approach with the aid of MAXQDA software. The findings indicated that the development of strategic thinking among primary school principals with a competitive advantage approach in the Department of Education of Khuzestan Province encompasses “the development of thinking based on principals’ intrinsic needs and motivation,” “analysis of the competitive advantage gap in comparison with leading schools,” and “possessing vision and future orientation.” Due to resource constraints and the necessity of reconfiguring educational policies, principals are compelled to employ strategic thinking in order to balance educational objectives with available resources and to guide schools along a transformative path. The quantitative results showed that the causal factors influencing the development of strategic thinking among primary school principals with a competitive advantage approach in the Department of Education of Khuzestan Province include the development of strategic thinking based on needs and motivation, analysis of competitive advantage in comparison with leading schools, vision and future orientation, and the reconfiguration of educational policies at the school level. Contextual factors include the climatic context affecting the strategic thinking of principals in Khuzestan Province, technology-oriented education as a facilitator of strategic thinking development, situation-based management under the crisis-prone and diverse conditions of Khuzestan, and the localization of educational directives in Khuzestan Province. Intervening factors include “institutional and organizational support” from education authorities and the degree of “structural pressures and administrative bureaucracy” as the most significant interventions. The strategies identified in the present study include “intelligent resource management,” “adaptive learning and educational innovation,” and “localization of mandated strategies.” Successful principals leverage “parents’ social capital” and act as “facilitative leaders.” The outcomes, which include “strengthening social capital and school branding,” represent the first major result, leading to increased family trust. At the internal level, this approach culminates in “teachers’ professional empowerment” and “innovation in teaching methods.” Ultimately, “enhanced organizational effectiveness” and the multidimensional growth of students in a joyful and dynamic environment constitute the most important outcomes, consolidating the school’s position within the educational system of Khuzestan Province.

The objective of this study is to analyze the factors influencing success in the sport of badminton by integrating performance, social, and survey data and to identify the key drivers of the development of this sport using artificial intelligence methods. This applied study was conducted using a qualitative approach and a descriptive phenomenological method. The study population consisted of university faculty members, coaches, professional and semi-professional badminton athletes, and sports analysts, from whom 26 participants were ultimately selected as the sample. Data were collected through semi-structured interviews and subsequently analyzed and coded. The validity and reliability of the data were ensured based on the criteria of credibility, transferability, dependability, and confirmability. The results indicated that success in badminton is influenced by a combination of factors, including individual and technical performance, athletic motivation and commitment, social and team interactions, the utilization of technology and data analytics, environmental conditions and training facilities, as well as competitive decision-making and strategic planning. The application of performance data and artificial intelligence technologies enables continuous performance monitoring, technical improvement, intelligent planning, and the identification of the principal drivers of success. This study demonstrates that the integration of performance, social, and survey data using artificial intelligence methods provides a deeper understanding of the factors influencing success in badminton and facilitates the design of optimal training programs to enhance athletes’ performance. The findings offer significant practical implications for improving training quality, identifying talent, and predicting performance, and can serve as an effective guide for coaches and sports organizations.

This study aims to explore the future configuration of the integrated ecosystem of sports brands with a particular focus on emerging technological transformations and their strategic implications. The research employed a qualitative exploratory futures-studies design drawing on expert-driven foresight methodologies. Participants were selected based on purposive and criterion sampling, including sports branding specialists, digital transformation experts, technology innovators, and academic researchers with significant experience in sports ecosystems. Data were collected through semi-structured in-depth interviews, expert panel discussions, and systematic documentary analysis of global technological and market reports. The analytic process involved iterative thematic coding, structural analysis through the MICMAC method to map influence–dependence relationships among key variables, and intuitive-logics scenario building to construct plausible future trajectories. Cross-validation among interview insights, panel deliberations, and documentary evidence ensured conceptual coherence and analytical rigor. Analyses revealed that the future of sports brand ecosystems will be predominantly shaped by technological convergence, including AI-driven personalization, IoT-enabled fan engagement, immersive AR/VR experiences, and platform-based value creation. MICMAC results showed strong influence pathways among technological, economic, and consumer-behavior variables, indicating that digital infrastructures will become the core enablers of brand competitiveness. Scenario building produced four plausible futures driven by uncertainties associated with technology adoption, data governance, and platform dominance. Across scenarios, strategic agility, consumer co-creation, sustainability pressures, and globalized digital commerce emerged as decisive factors shaping long-term ecosystem configurations. The study concludes that sports brands are transitioning from traditional linear branding models to interconnected digital ecosystems driven by technological innovation, evolving consumer expectations, and expanding global platforms.

The purpose of this study was to design a model for sports talent identification among students aged 8–12 years based on the utilization of leisure time. The present study is applied in terms of purpose. Regarding data collection and information gathering, it is classified as a field study, and the implementation method follows a mixed (qualitative–quantitative) approach. The qualitative statistical population consisted of university faculty members in the field of sports management—particularly experts in leisure studies—physical education teachers, and specialists in sports talent identification. The sampling method in this section was purposive, continuing until theoretical saturation at 16 participants. The quantitative statistical population consisted of planners and administrators of the Ardabil Department of Education, totaling 3,178 individuals. Using stratified random sampling and Morgan’s table, a sample size of 432 participants was determined, from which 425 valid and unblemished questionnaires were obtained. The data collection instrument was a researcher-developed questionnaire with 61 items measured on a five-point Likert scale. Data analysis was performed using SPSS and LISREL software through structural equation modeling tests. According to the results derived from analyzing the research questions, the contribution of factors influencing the use of leisure time among students aged 8–12 years for sports talent identification included: organizational development and collaboration (57%) as the least influential factor; expansion of social and communicative capacities (72%); establishment of supportive and motivational infrastructures (80%); educational and cultural infrastructures (70%); specific and coherent planning (89%); development and enhancement of relevant human resources (96%) as the most influential factor; and economic policymaking (65%). All research instruments demonstrated acceptable and appropriate levels of model fit.

This study was conducted with the aim of exploring the lived experiences of electronic sports (e-sports) players in Iran and providing a phenomenological analysis of their motivations and challenges. The statistical population included active e-sports players in Iran who were selected purposefully using the theoretical sampling method. The inclusion criteria were active experience in this field, willingness to participate in the study, and the ability to articulate personal experiences. In total, 17 participants (4 women and 13 men) with an average age of 25 years and between 4 to 12 years of experience in e-sports were examined. Data were collected through in-depth semi-structured interviews. To ensure credibility and dependability, the trustworthiness criteria proposed by Guba and Lincoln (1985)—including prolonged engagement in the field, persistent observation, triangulation, peer debriefing, and member checking—were applied. Findings revealed that the lived experiences of players can be analyzed across three main dimensions: (1) Lived Experiences (self-concept and identity, emotional experiences, cognitive and skill development, and escapism and role-playing); (2) Motivations for Participation (game appeal and dynamics, social and global interactions, economic and professional opportunities, accessibility and usability, and emotional and motivational effects); and (3) Challenges Encountered (personal challenges, financial and economic barriers, technical and infrastructural problems, social and familial obstacles, and competitive and professional difficulties). The results indicate that electronic sports provide a multidimensional and complex experience for players, which, while offering numerous opportunities, also presents diverse challenges.