Search Results (1,395)

In the 21st century, the concept of the Innovation Hubinnovation hub (IH) has become increasingly significant with the emergence of collaborative spaces, entrepreneurial ecosystems, and the pursuit of creative, sustainable solutions to contemporary challenges. While the literature presents various typologies of IHs, a critical knowledge gap remains due to the limited availability of empirical data on their core drivers, functions, and sustainability practices. Addressing this gap through a comprehensive primary and secondary data collection will enhance the global understanding of IH dynamics, supporting evidence-based decision-making; strategic development; and long-term accountability for hub managers, entrepreneurs, and policymakers. This study aims to identify and classify the predominant characteristics of IHs, examining their key drivers, core activities, and sustainability dimensions through an in-depth analysis of three leading innovation hub networks: the European Creative Hubs Network (ECHN), Impact Hub, and Talent Garden (TAG). By exploring how these hubs foster innovation and integrate sustainability into their operational models, this research offers actionable insights for stakeholders seeking to align innovation with inclusive, resilient, and environmentally conscious economic development. Full article

Against the background of China’s ecological civilization construction and sustainable development strategies, how remote sensing courses adapt to the demands of the artificial intelligence era has become an urgent issue for undergraduate education in relevant disciplines at universities. This study proposed a trinity teaching reform path of “deep learning and remote sensing, and ecological sustainability”, aiming to cultivate interdisciplinary talents with capabilities in intelligent interpretation and practical application. The study established a three-stage curriculum objective system, integrating knowledge, ability, and literacy, designed a five-dimensional linkage teaching method combining case-driven teaching, modular training, and blended learning, and conducted teaching practices using mainstream deep learning frameworks and cloud platforms. Through hierarchical teaching practice cases and multi-dimensional evaluation data, it was shown that the reform effectively enhanced the experiment group students’ abilities in deep learning applications, complex remote sensing data processing, and ecological problem-solving. The achievement values for all five evaluation indicators exceeded 80%, with the highest improvement reaching 28% compared to the control group. The results indicate that this teaching reform not only enhances learning outcomes but also provides a valuable framework and practical pathway for remote sensing education empowered by artificial intelligence and the cultivation of professional talent in future sustainable development fields. Full article

Background/Objectives: Quantitative approaches to talent identification in youth soccer often rely on either closed-skill assessments or small-sided games, but each carries inherent uncertainties that can reduce selection accuracy. Effective talent selection requires integrating both sources of data while accounting for their limitations. This study aimed to develop and validate a framework that combines closed-skill tests with competitive 1v1 game outcomes to optimize early-stage player selection. Methods: We assessed the dribbling and sprinting performances of 30 Brazilian youth players and used 1308 individual 1v1 bouts (70–90 bouts/individual) to estimate competitive abilities using a Bayesian ordinal regression model. Based on our empirical results, we then ran simulations to determine how many players should be selected when the aim is to reduce a player pool of 100 individuals so that the ‘true’ top 10 performers are reliably included and to determine how the weighting between data from closed-skill tests and games should change with increasing match observations. Results: Dribbling speed was a strong predictor of 1v1 success (β = –0.76, 95% CI: [–1.16, –0.40]), while sprint speed (β = 0.01, 95% CI: [–0.36, 0.40]) showed no significant association with 1v1 success. Simulations revealed that 26.0 ± 2.5 players were needed after five 1v1 contests per player to capture the true top 10% and then decreased to 18.0 ± 1.5 players after 20 contests. Optimal weighting shifted from a greater reliance on dribbling-based data (α > 0.80 at Game 0) to more match-based data after 10–20 contests per player (α = 0.16 at Game 20), but utilizing both sources of data improved selection accuracies and efficiencies. Conclusions: This study provides an uncertainty-aware protocol for talent identification that optimizes the integration of data from closed-skill tests and in-game performances within a dynamic selection framework that enhances precision and forms the basis for efficient early-stage scouting of large cohorts of players. Full article

This study examines whether China’s high-tech enterprise identification policy promotes corporate sustainable innovation. Using panel data from Chinese listed firms on the Shanghai and Shenzhen stock exchanges between 2008 and 2022, we adopt a time-varying difference-in-differences (DID) model to evaluate the policy’s effectiveness and explore its underlying mechanisms. The results reveal that this certification policy significantly facilitates green innovation, and the findings remain robust across various checks, including alternative measurements, placebo tests, propensity score matching DID (PSM-DID), and the exclusion of digital transformation trend and confounding macro-level policies. Mechanism analysis shows that the policy influences green innovation by alleviating financing constraints, increasing access to government subsidies, facilitating the agglomeration of scientific and technological talent, and encouraging greater R&D investment. Heterogeneity analysis further indicates that the policy effect is more pronounced among non-state-owned enterprises, small-scale firms, capital-intensive businesses, those located in high-institutional-quality regions, and firms in China’s eastern provinces. Moreover, the positive impact is strongest for growth-stage firms. The policy has also been found to improve green innovation efficiency. These findings offer empirical insights for optimizing selective industrial policies to enhance sustainable innovation and support China’s dual-carbon goals. Full article

In recent decades, Chinese literary studies has shifted away from center–periphery models, favoring frameworks that emphasize multiplicity and decentralization. While this turn has opened space for new perspectives, it risks overlooking persistent hierarchies that continue to shape literary careers, where certain publishers remain more central to an author’s advancement than others. This essay reconsiders the center–periphery framework through an analysis of Huizu wenxue, a literary journal published in Changji, Xinjiang Uygur Autonomous Region. Despite its geographic distance from China’s dominant literary hubs, Huizu wenxue has long served as a key platform for Hui literature. Drawing on interviews, as well as textual and paratextual analysis, I demonstrate how the journal functions both as a launchpad for emerging Hui authors and as an institutional anchor for a nationwide Hui literary community. Through dedicated columns that showcase new Hui talent and events that foster professional networks, Huizu wenxue has, since its inception, continually played a central role in shaping Hui literary production and supporting authors’ careers. Because it operates from the margins of the People’s Republic of China’s yet wields significant influence within Hui literary circles, I argue that Huizu wenxue is best understood as a “peripheral center.” Full article

Since the 21st century, Russia has pursued the construction of world-class universities as a core reform goal in higher education, aiming to address the inadequacies of its post-Soviet higher education system in adapting to international competition. This study systematically examines the historical evolution, strategic framework, key characteristics, and practical challenges of Russia’s efforts over more than two decades. Russia’s practice has gone through three distinct stages: foundational construction (2003–2012), marked by joining the Bologna Process and establishing federal and national research universities; in-depth advancement (2012–2020), driven by initiatives such as the “5–100 Plan,” Global Education Program, and regional flagship universities; and adjustment and optimization (2020–present), represented by the “Priority-2030” plan. These efforts have formed a strategic framework centered on system construction, internationalization, balanced development, and operational support. Key characteristics of Russia’s practice include the integration of strategic stability and tactical flexibility, the complementarity of tiered and classified development, and the coordination of government leadership and university autonomy. However, challenges persist, such as underperformance in global rankings, insufficient funding, uneven resource distribution, and severe talent drain. Full article

Problem-based learning (PBL) is a student-centered instruction approach focused on skills development in problem-solving, interaction, autonomy, and critical thinking to learn and act to co-create new knowledge and solutions. Rarely, but authors sometimes identify the benefits of PBL for educators, for example, by allocating instructional time more flexibly for monitoring student performance and discussing issues. However, in the era where collaboration among universities and industries is emphasized, the authors pay little attention to contextualizing PBL in a broader context, such as bringing benefits for relationship management with the industry and alumni, promoting regional development, corporate and social responsibility, marketing of educational organizations, and talent development to create a mutual benefit-based ecosystem. Academic discussions about PBL planning and implementation also neglect the needs and motivation of industry stakeholders to get involved, thus narrowing not only the possibilities for cooperation between both parties but also negatively affecting student learning outcomes, which also directly depend on industry partners. Full article

General models of talent development have highlighted the importance of a community of practice to nurture talent potential, with recent studies refining factors that contribute to the developmental journey. In music, an early model described three phases of talent development, while current research has focused on transitions between these. Choral music research has investigated conductors’ expertise and choristers’ experiences, highlighting positive social impacts for children in addition to the development of choral skills. The purpose of this qualitative case study was to investigate talent development of 11 elite middle school choristers utilising interviews. Thematic analyses identified four themes and 10 sub-themes, demonstrating that choristers followed a developmental pathway similar to choral conductors, acquiring vocal competence and mastery, nurturing a sense of belonging to a choral community, participating in meaningful experiences, and becoming advanced choristers through intensive training. Chorister talent development was also linked to personality development, with transformation in choral identity leading to growth in personal confidence. This study extends research into choral talent development by documenting the voices of middle school children participating in an advanced choir, showing that high levels of performance can be achieved through expert choral coaching and without sacrificing the enjoyment of singing. Full article

Complex task crowdsourcing (CTC) integrates distributed talent, knowledge, and ideas into innovation via the web; however, task decomposition remains a critical challenge. While existing studies focus primarily on workflow management for specific tasks, they leave a gap in decomposing more complex, creative tasks, which are characterized by the absence of objective ground truths, nonlinear dependencies, and non-sequential processes. To address this gap, we propose a novel integrated task decomposition framework for CTC that comprises three interconnected components. First, primary decomposition considers knowledge reuse by identifying similar past task decomposition schemes to inform the initial breakdown. Second, modifications to the scheme are guided by work breakdown structure (WBS)-based principles, which also serve as a foundation when no prior knowledge is available. Third, to enhance executability, a task package model is proposed to combine subtasks that share common resources, thereby reducing coordination costs and avoiding waste of workers’ capabilities. To solve this model, we develop an improved non-dominated sorting genetic algorithm (NSGA-II) to generate the final decomposition scheme. A case study from ZBJ.COM validates the feasibility and effectiveness of the proposed framework. Experimental results demonstrate that, compared to baseline algorithms, the improved NSGA-II better balances conflicting objectives and generates non-dominated solution sets with higher diversity and more uniform distribution. Full article

Grounded in the person–environment fit theory and an identity-based perspective, this study investigated the relationship between perceived overqualification and knowledge hiding, focusing on the mediating role of future work self-salience and the moderating role of the growth mindset. We suggest that perceived overqualification as a person–job misfit would negatively impact employees’ salient hoped-for work identities, representing a low level of future work self-salience. The diminished salience of a future work self leads employees to hide their knowledge. Furthermore, the growth mindset exacerbates the negative impact of perceived overqualification. We conducted a three-wave survey with 482 employees from knowledge-intensive industries. The results revealed that perceived overqualification boosted knowledge hiding by decreasing employees’ future work self-salience. The growth mindset enhanced the negative relationship between perceived overqualification and future work self-salience. Thus, the indirect effect of perceived overqualification on knowledge hiding via future work self-salience was more significant for those with a stronger growth mindset. Our findings contribute to the literature on person–job fit and knowledge behavior while providing practical insights for managing and guiding talented employees in knowledge management. Full article

Artificial Intelligence (AI) is reshaping global healthcare systems by offering innovative solutions to improve diagnostic accuracy, optimize treatment planning, and enhance public health management. This article provides a structured perspective on the role of international partnerships in accelerating the adoption of AI-driven healthcare, with a focus on advancing the United Nations Sustainable Development Goals (SDGs), particularly SDG 3 (Good Health and Well-being). Drawing on representative global initiatives, the paper explores best practices in technology transfer, ethical data sharing, and capacity building—key enablers for inclusive and equitable AI healthcare adoption. It further analyzes common challenges such as digital infrastructure gaps, regulatory fragmentation, and global inequities in data and talent. Through a synthesis of recent collaborations and policy frameworks, this article offers actionable insights for fostering global alliances that bridge innovation with healthcare accessibility. Full article

This article explores the literary significance of the bell as an important image in the poetry of Taixu 太虛 (1890–1947), a renowned modern Chinese Buddhist reformer and poet–monk. While the bell has long-held symbolic meaning in Buddhist ritual and Chinese literary traditions, its role in poetry has often been overlooked in favor of material culture studies. This article addresses that discrepancy by examining how Taixu inherited and reinterpreted classical bell imagery to articulate his personal emotions and religious philosophy. Following close analysis of more than sixty of his poems, it argues that Taixu used the bell not merely as a traditional image but also as a vehicle for expressing two core Buddhist concepts: mental purification and transcendence of the mundane. The article also highlights his creative pairing of the bell with other classical Chinese images—such as sunsets, moonlight, mountains, and forests—to form complex imagery groups. Taixu’s skillful execution of this technique exemplifies the considerable literary talent and spiritual insight that enabled him to blend Buddhist doctrine with poetic expression to remarkable effect. Overall, his poetic corpus may be considered as both a continuation and a transformation of classical Chinese poetry traditions, affirming his identity as a modern poet–monk who possessed profound esthetic and philosophical vision. Full article

The development of E-commerce and digitalization drives the rapid change in logistics management practices and poses challenges to traditional talent training modes in logistics field. Nowadays, companies expect university graduates equipped with more practical logistics skills to connect tighter with the industry. This motivates universities to establish more practically relevant curriculums to enhance students’ career competitiveness. Under such background, industry–university collaboration courses are increasingly adopted in higher education institutes in logistics discipline. Due to the difference between this type of course and the traditionally taught courses, the learning outcome of it can be difficult to guarantee. Therefore, it is necessary to identify the influential factors of the learning outcomes of industry–university collaboration courses and establish the actionable strategies to enhance course quality. However, the current literature in logistics management education has little focus on this topic, resulting in gaps on clarifying the influential factors of learning outcomes of industry–university collaboration courses in this discipline. Applying a mixed method, this study conducted a case study for an industry–university collaboration course of a logistics discipline in a Chinese university. The interval-valued Pythagorean fuzzy (IVPF) numbers and the Weighted Aggregated Sum Product Assessment (WASPAS) methods were used. The results showed that there are 15 factors which can influence the outcomes of industry–university collaboration courses in logistics discipline. Among them, the most important factor is the working environment, followed by the students’ own ability. Also, the results indicated that students’ optimistic attitudes towards the course, whether students take the course seriously, and course evaluations can be influential factors for good learning outcomes. The sensitivity analysis was then conducted, showing that the results were robust. This study can contribute to the existing literature by providing a theoretical framework to understand and assess the quality of industry–university collaboration courses in logistics and relevant subjects, as well as offering new analytical tools for management educational studies. Moreover, this study can provide practical implications for educators to develop and maintain good industry–university collaboration courses and trainings. Specifically, a practical life-cycle view was suggested to put pertinent efforts in all periods before/during/after the course to achieve high course outcomes. Full article

Artificial intelligence (AI) is transforming organizational functions across sectors; however, its application to human resource management (HRM) within healthcare remains underexplored. This study aims to unpack the black-box nature of AI capability’s impact on HR functions within China’s healthcare sector, a domain undergoing rapid digital transformation, driven by national innovation policies. Grounded in resource-based theory, the study conceptualizes AI capability as a multidimensional construct encompassing tangible resources, human resources, and organizational intangibles. Using a structural equation modeling approach (PLS-SEM), the analysis draws on survey data from 331 professionals across five hospitals in three Chinese cities. The results demonstrate a strong, positive, and statistically significant relationship between AI capability and HR functions, accounting for 75.2% of the explained variance. These findings indicate that AI capability enhances HR performance through smarter recruitment, personalized training, and data-driven talent management. By empirically illuminating the mechanisms linking AI capability to HR outcomes, the study contributes to theoretical development and offers actionable insights for healthcare administrators and policymakers. It positions AI not merely as a technological tool but as a strategic resource to address talent shortages and improve equity in workforce distribution. This work helps to clarify a previously opaque area of AI application in healthcare HRM. Full article

As hybrid organizations that combine market-related logic with social logic, social enterprises (SEs) play a crucial role in addressing the challenges faced by people in employment while creating economic benefits through innovative solutions to drive economic and social rural revitalization. Focusing on social enterprises, this study employs environmental analysis and theoretical reasoning to examine the logic and approaches through which social enterprises participate in rural revitalization in China’s northwest regions from the perspective of “new-quality productive forces.” Research findings indicate that in the face of an external environment characterized by weakened investment and consumption and the decline of the demographic dividend, and an internal environment marked by lagging socio-economic development and ecological fragility, SEs should integrate devotion and profit logic based on a mixed action logic of multi-value co-creation. Through approaches such as cultivating new quality talent, constructing a new quality industrial system, shaping a new quality rural environment, promoting synergistic innovation between science and technology and culture, and actively participating in the revitalization of rural areas in China’s northwest region, SEs can play an active role in China’s rural revitalization efforts. Full article