Search Results (8)

Agentic artificial intelligence—systems that reason, plan, and act autonomously within governed workflows—is converging with autonomous electric mobility and urban robotics to reshape how cities govern, move, and manage physical space. We argue that the simultaneous arrival of these three vectors is triggering a transformation comparable in scope to the Industrial Revolution. Cities that deploy across all three domains are becoming the new hubs of innovation: they concentrate talent, accelerate knowledge circulation, enable cross-fertilisation, and generate hybrid proposals that no single vector could produce alone. Just as Manchester, Birmingham, and the Ruhr became the defining centres of industrialisation because steam, textiles, iron, and coal recombined through the proximity of the engineers and entrepreneurs who moved between them, a small number of cities today are pulling ahead because they host the shared talent pool around which agentic governance, autonomous mobility, and urban robotics co-evolve. Conceptually, we extend the mirroring hypothesis in two directions: dynamically, arguing that organisations and urban ecosystems converge toward the configurations new technologies make possible; and ontologically, arguing that agentic AI introduces non-human agents into organisational architectures, requiring hybrid human–AI coordination. We formalise this dynamic as five propositions (P1–P5) of cumulative recursive hybridisation (CRH), operating through four reinforcing feedback loops—data, regulation, infrastructure, and talent. Together, these loops explain why the emerging urban order is path-dependent: early movers accumulate compounding advantages, while latecomers face exponentially rising costs of entry. We demarcate CRH from adjacent frameworks—general-purpose technologies, organisational complementarities, and complex adaptive systems—and test it against counterfactual evidence from failed, stalled, and Global South trajectories (Sidewalk Toronto, the Cruise rollback, Songdo, Bengaluru). We also examine its political-economy, equity, and surveillance limits. Drawing on comparative evidence from public-sector chatbot deployments, autonomous mobility ecosystems in the United States and China, and emerging urban robotics cases, we conclude that what is at stake is not incremental modernisation but the construction of a new urban order. The cities that act as innovation hubs for the agentic AI era will shape global standards, attract global talent, and define the institutional templates that others eventually adopt—much as the industrial cities of the eighteenth and nineteenth centuries did. Full article

The introduction of international faculties is a crucial strategy in enhancing the talent pool of Chinese universities, yet its impact on scientific research development remains underexplored. This study investigates how the presence of an international faculty influences the international academic impact of 128 “Double First-class” Chinese universities from 2011 to 2020. Using benchmark regression models alongside endogeneity and robustness tests, the analysis incorporates moderating effects and heterogeneity to examine underlying mechanisms. The results indicate that the introduction of foreign faculty significantly enhances the international academic impact of these institutions. Furthermore, the scientific and technological human capital of a foreign faculty plays a key role in this effect. This study also finds that the universities’ level of digitalization significantly moderates the relationship between international faculty presence and academic impact. Additionally, the impact varies across regions and development levels, highlighting heterogeneity in outcomes. These findings suggest that Chinese universities should strategically strengthen the recruitment of international faculties, carefully assess their expertise, and leverage digital capabilities to maximize academic benefits. This research provides empirical evidence on the value of international faculties in advancing the global academic standing of Chinese higher education institutions. Full article

With the rapid development of society and technology, the physical health of university students has become a critical concern, influencing both individual well-being and the national talent pool. This study employs an improved K-means algorithm integrated with machine learning models to analyze university students’ fitness data and develop personalized health intervention strategies. The enhanced K-means algorithm overcomes the limitations of traditional clustering approaches, leading to improved clustering accuracy and stability. Machine learning models—including Random Forest, decision trees, Gradient Boosting Trees, and logistic regression—were utilized to validate the clustering outcomes and to identify key health indicators associated with different student groups. Based on the clustering and model analysis, targeted intervention programs are proposed, such as strength training for groups with low muscular explosiveness, endurance training for those with stamina deficiencies, and flexibility exercises for groups exhibiting limited mobility. This integrated analytical framework provides a scientifically grounded tool for comprehensive health assessments and offers actionable, data-driven recommendations for student health management. Future research will focus on optimizing algorithmic performance, enhancing data diversity, and broadening the application scope to further improve the effectiveness and feasibility of health interventions. Full article

Prefabricated building construction is an important method of enhancing construction productivity and promoting sustainable development in the construction industry. Evaluating and predicting the development performance of prefabricated buildings will contribute to identifying and implementing the most effective responses to promote prefabricated building technologies. Based on the Drives–Pressures–States–Impacts–Responses (DPSIR) framework, 14 evaluation indexes are determined to evaluate the development level of prefabricated buildings. The entropy weight method was used to determine the weight of the evaluation index, and the Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) method with improved grey correlation was applied to comprehensively evaluate the trend of the index. The grey model (GM(1,1)) was developed to predict the development trend of prefabricated buildings. The development of prefabricated buildings in Shandong province, China, is employed as a case to apply the developed method and investigate development experiences. The results demonstrate that the case has achieved significant progress and has great potential in promoting the use of prefabricated buildings. The development recommendations include developing a policy and regulation system, strengthening a prefabricated building talent pool, and enhancing the investment in technological innovation. This study innovatively formulated the evaluation and prediction system based on the DPSIR, TOPSIS and GM(1,1) models, which could be used for evaluating development performance between social and environmental factors among various cause-effect relationships. Full article

The digital economy system is an essential driving force that promotes the development of the sports industry, aligning with Sustainable Development Goals (SDGs), including Goal 9 (Industry, Innovation, and Infrastructure), Goal 8 (Decent Work and Economic Growth), and Goal 11 (Sustainable Cities and Communities). This paper aims to provide a comprehensive understanding of the roles of the digital economy in enhancing the sustainable high-quality development of the sports industry in China. This study utilizes panel data from 17 provinces in China, spanning the period from 2014 to 2020. The level of high-quality development in both China’s digital economy and sports industry is calculated using the entropy method. To examine the empirical relationship between the digital economy and the sports industry’s high-quality development, this study employs benchmark regression, mediation models, and spatial analysis and conducts robustness tests. The findings of this study indicate that the digital economy not only directly and significantly contributes to the development of the sports industry but also drives it indirectly through the transformative effects of technological innovation. This study reveals that the impacts of the digital economy on the sports industry’s high-quality development exhibit nonlinear characteristics, with an initial period of rapid growth followed by a diminishing growth rate and spatial spillover effects. By recognizing this dynamic relationship, stakeholders could better strategize and allocate resources in their efforts to achieve SDGs. To advance the development of the sports industry and contribute to the SDGs, it is crucial to accelerate the construction of digital infrastructure in China, nurture a diverse pool of talent in sports science and technology, and develop region-specific strategies that consider sustainability and inclusivity. Full article

High-performance work systems are being increasingly used in organisational management. However, such system development over time has resulted in increasingly complex impacts on employee innovation behaviour. How to stimulate innovation in the technological talent pool of individuals at high-tech enterprises has gradually become a research hotspot. Based on an effective sample of 351 technological individuals from high-tech enterprises in Jiangsu, Zhejiang and Guangdong provinces, this paper discusses the mechanism and boundary conditions of a high-performance work system affecting the active innovation behaviour of such individuals based on self-determination theory. The empirical results show the following: (1) Informational practices and controlled practices in a high-performance work system have mutually exclusive effects on active innovation behaviour, with significant positive and negative effects. (2) The need for autonomy and competence play mediating roles between informational practices and active innovation behaviour; the need for autonomy plays a masking effect between controlled practices and active innovation behaviour. (3) The need for relatedness negatively moderates the effects of a high-performance work system which is focused on the needs for autonomy and competence. The findings reveal the internal mechanism and boundary conditions of high-performance work system influencing active innovation behaviour, which provides a reference for high-tech enterprises to encourage technical talents to innovate, and have important practical significance for improving the core competitiveness of high-tech enterprises. Full article

Regional carbon efficiency (CE) improvement is critical to China’s “taking concerted efforts to achieve ecological protection” strategy in the Yangtze River Economic Belt (YREB) and their program to build a leading demonstration belt for ecological civilization. This study applied the super efficiency slacks-based measure to calculate the regional differences and evolution characteristics of the YREB’s CE from the year of 2006 to 2017. It also constructed a coupling evaluation model to empirically analyze the interactions between CE and technology absorptive capacity (TAC). The results showed that (1) the CE for all YREB provinces followed a “U-shaped” trend. TAC generally increased and incrementally decreased in the sequence of the upper stream, middle stream, and downstream. The gap among the downstream, upper stream, and middle stream increased; (2) coupling between the CE and TAC for the YREB provinces can be characterized as a relatively stable medium to low coupling degree and medium-to-high coordination degree. To improve coupling and achieve balanced, sustainable development in the YREB, this study proposes several measures, including promoting balanced, high-quality economic development, building the YREB talent pool, appropriately guiding foreign capital flows, implementing the strategy of driving economic development through innovation, and launching the network for coordinated technological innovation in YREB. Full article

Under the backdrop of the Maritime Silk Road Initiative, the study on the international development of China’s marine biopharmaceutical industry based on factor allocation is of great practical significance for industrial sustainability and building the industry into a leading international player in the global market. In this paper, we first identify the leading factors that influence the development of the marine biopharmaceutical industry, namely, resources, technologies, talents, investments and policies. Furthermore, the hierarchical structure model of these factors was established and analyzed using the analytic hierarchy process (AHP). The importance ranking of these constraints was identified, as follows: technologies > talents > resources > policies > investments. Then, based on the theory of comparative advantage and game theory, we analyzed the necessity of China’s marine biopharmaceutical industry going global, that is, international cooperation may lay a solid foundation for the win-win outcome of this industry in countries along the Maritime Silk Road. According to the status quo of China’s marine biopharmaceutical industry, based on these findings, an international factor–allocation cooperation path was designed, and the path chart of the international development of the marine biopharmaceutical industry was drawn. Finally, methods for the development of China’s marine biopharmaceutical industry were proposed, which covers efforts to protect marine resources, promote R&D for core technologies, establish a strong talent pool, encourage more investments, provide policy support and promote worldwide cooperation. It is the first report to investigate the path of the sustainable exploitation of the marine biopharmaceutical industry from the perspective of factor allocation amidst the backdrop of the Maritime Silk Road Initiative. Full article