In the context of the increasing digitization of education, online teachers’ competence and the affective factors of digital competence, psychological resilience, and self-efficacy have become prominent areas of academic inquiry. However, there is a dearth of extant research addressing the interactions between these variables in an online teaching Chinese as a foreign language (TCFL) environment. This study investigated the relationships among the digital competence, psychological resilience, and self-efficacy of online TCFL teachers via quantitative research methods. The questionnaires were administered to 610 online TCFL teachers, and the data were analyzed via structural equation modeling. The results indicate that digital competence and psychological resilience can significantly predict online teachers’ self-efficacy, and that the relationship between psychological resilience and self-efficacy can be significantly moderated by digital competence. This finding not only provides novel perspectives and insights for enhancing online teaching effectiveness, particularly in the domain of online foreign language instruction, but also complements and extends self-efficacy theory from the perspective of social cognitive theory.

Digital technology drives global industrial transformation. The synchronized development of organizational digital transformation and innovation systems is pivotal in corporate strategy and governmental governance. The dynamic interaction mechanisms among digital economy, government innovation policy, and regional innovation capacity remain insufficiently explored. This study employs panel data from 15 prefecture-level cities within the Yangtze River Delta urban agglomeration, spanning the years 2012 to 2020, and uses the panel vector autoregression (PVAR) model to investigate the interrelationships among the digital economy, government innovation preferences (the government’s supportive attitude and policy inclination towards innovative activities in the fields of science and technology as well as economic development), and regional innovation capacity. This research emphasizes the impact of the digital economy on regional innovation capacity and the influence of government innovation preferences on regional innovation capacity. The findings indicate that both the digital economy and government innovation preferences significantly enhance technological and product innovation, with this effect being particularly pronounced in the initial stages but diminishing over time. The three dimensions of the digital economy exert varying effects on technological and product innovation. Specifically, digital application has the most substantial impact on technological innovation, whereas infrastructure has a more pronounced effect on product innovation. Overall, the influence of government innovation preferences on technological and product innovation is less significant than that of the digital economy. The intensity of government innovation preferences has a greater impact than does the structure of government innovation preferences; however, in the long term, the structure of government innovation preferences can exert a more stable and sustainable influence. This study offers policy implications for constructing an innovation ecosystem driven by the synergy between government and market forces, particularly in optimizing data governance systems and planning sustainable transformation pathways, which hold practical value.

The Han River Ecological Economic Belt (HREEB) has a substantial amount of water resources; however, its distribution is uneven, and issues such as seasonal and engineering water shortages are prevalent. This necessitates a thorough assessment of the current water resource situation and trends in water resource carrying capacity (WRCC) to provide scientific support for the rational allocation of water resources. This study employed the RAGA-PP model to establish a WRCC evaluation index system composed of four subsystems: water resources, economy, society, and the ecological environment. The WRCC of the 17 major cities in the HREEB was evaluated from 2008 to 2022. The differentiation method was introduced to compare the reliability of the RAGA-PP model with three evaluation methods: the entropy weight TOPSIS method, the rank sum ratio method, and the principal component analysis method. In addition, an obstacle degree model was introduced to analyze the factors influencing WRCC enhancement. The results indicated the following. (1) In the differentiation test of the four models, the RAGA-PP model was found to have the highest differentiation value, and the results showed that it was more reliable in the WRCC evaluation of HREEB. (2) WRCC in the HREEB underwent significant changes between 2008 and 2022. (3) The WRCC in Shiyan and Wuhan, which are located in the eastern part of the HREEB, were high in Hubei, low in four cities in Henan, and satisfactory in three cities in Shaanxi. (4) The carrying capacity of the subsystems of the cities in the HREEB exhibited fluctuating changes with obvious internal variations. (5) The problems in the WRCC guideline layer were consistent across all cities in the HREEB, with limited per capita water resources being the primary issue in the indicator layer. Assessing WRCC is essential for achieving sustainable water resource use and high-quality regional development.

The Jianghan Plain (JHP) is a key agricultural area in China where efficient agricultural water use (AWUE) is vital for sustainable water management, food security, environmental sustainability, and economic growth. This study introduces a novel AWUE prediction model for the JHP, combining a BP neural network with the Sparrow Search Algorithm (SSA) and an improved Tent Mixing Algorithm (Tent-SSA-BPNN). This hybrid model addresses the limitations of traditional methods by enhancing AWUE forecast accuracy and stability. By integrating historical AWUE data and environmental factors, the model provides a detailed understanding of AWUE’s spatial and temporal variations. Compared to traditional BP neural networks and other methods, the Tent-SSA-BPNN model significantly improves prediction accuracy and stability, achieving an accuracy (ACC) of 96.218%, a root mean square error (RMSE) of 0.952, and a coefficient of determination (R²) of 0.9939, surpassing previous models. The results show that (1) from 2010 to 2022, the average AWUE in the JHP fluctuated within a specific range, exhibiting a decrease of 0.69%, with significant differences in the spatial and temporal distributions across various cities; (2) the accuracy (ACC) of the Tent-SSA-BPNN prediction model was 96.218%, the root mean square error (RMSE) was 0.952, and the coefficient of determination (R²) value was 0.9939. (3) Compared with those of the preoptimization model, the ACC, RMSE, and R² values of the Tent-SSA-BPNN model significantly improved in terms of accuracy and stability, clearly indicating the efficacy of the optimization. (4) The prediction results reveal that the proportion of agricultural water consumption has a significant impact on AWUE. These results provide actionable insights for optimizing water resource allocation, particularly in water-scarce regions, and guide policymakers in enhancing agricultural water management strategies, supporting sustainable agricultural development.

Purpose: Complementary resources and dual learning play crucial roles in enhancing the innovation capabilities of latecomer firms. However, the precise processes through which they contribute to this enhancement remain unclear. The aim of this study was to elucidate the underlying mechanisms involved. Design/methodology/approach: A longitudinal case study spanning the period from 1986 to 2022 was conducted to examine Haier water heaters from the perspective of the catch-up process of latecomer firms in emerging economies. Findings: The development of digital infrastructure has not shown a notable ability to advance the transformation and modernization of the small home appliance industry. Additionally, digital industrialization has had a minimal constraining effect on this process. Nonetheless, digital governance has persistently exhibited substantial influence in facilitating the transformation and modernization of the small home appliance industry. Although both industrial digitization and digital innovation possess significant potential for promoting the transformation and modernization of the small home appliance industry, their sustainability remains limited. Practical implications: It is crucial for late-developed enterprises to concentrate on building complementary assets while simultaneously alternating between exploratory learning and utilization learning. Additionally, it is essential to consider the dynamic relationship between complementary assets and dual learning during the catch-up process. Originality/value: This study addresses the inadequacy in the literature concerning the operational process of complementary assets and dual learning in fostering the innovation capacity of late-developing companies, thereby augmenting the theoretical frameworks pertaining to complementary assets and technological catch-up, as well as extending the scope of dual learning to some extent.

School-enterprise cooperation is a crucial strategy in China's vocational education and a vital aspect of vocational education reform. Conducting a comprehensive empirical study and evaluation of the effectiveness of school-enterprise cooperation in China's vocational education can enhance the quality and efficiency of such cooperation. Nevertheless, current evaluations of school-enterprise cooperation are predominantly theoretical, and there is a scarcity of systematic indicators and empirical research methods. To address this gap, the author adopts scientific, systematic, goal-oriented, and operational principles and utilizes stakeholder theory and system contract theory as the theoretical basis and framework. The author constructs three primary indicators, namely,participation, return, and potential, and several secondary indicators from the viewpoints of cooperation objectives, process, and results of vocational education school-enterprise cooperation for both schools and enterprises using factor analysis and the fuzzy comprehensive evaluation method. This evaluation offers precise empirical verification and a theoretical and practical reference for the high-quality practice of school-enterprise cooperation in China's vocational education.