浙江越秀外国语学院

Interventions aimed at fostering students' intercultural competence (IC) have received increasing scholarly attention in recent years. Yet, systematic evidence on classroom-based pedagogical interventions remains insufficiently examined. To address this gap, the present review synthesizes 54 studies published between 2015 and 2024, analysing four key aspects: (1) theoretical foundations, (2) types of pedagogical interventions, (3) research methodologies and data collection methods, and (4) reported outcomes. Analysis reveals that Byram's and Deardorff's IC models, together with Kolb's Experiential Learning Theory, are the most frequently applied theoretical frameworks. Comprehensive strategies and models constitute the predominant type of intervention. Mixed-methods approaches are most widely used, followed by qualitative approaches. Among the studies surveyed, a total of 20 distinct data collection methods were documented, with written and verbal modes being most frequently adopted. The reported outcomes suggest that classroom-based pedagogical interventions exert a positive influence on students' intercultural learning and IC development. This study contributes to the field by highlighting current trends, identifying methodological and theoretical limitations, and recommending future research to strengthen theoretical grounding, clarify implementation procedures, and diversify data collection and assessment methods to improve the rigour and applicability of classroom-based interventions.

This study examines Industry 4.0 readiness (I4R) and its role in the structural transformation of developing countries. While I4R drives growth, its sectoral impacts vary significantly. Using a novel I4R index and data from 87 countries (2007-2020), we find I4R significantly enhances manufacturing growth. Specifically, for Industrial Leaders, the total marginal effect reaches 0.635, indicating that technological depth acts as a critical multiplier for growth. However, we find a robust negative effect on the service sector, particularly in countries with weaker adaptive capacity, which risks premature deindustrialization or stagnation in the service sector. These dual findings highlight a critical policy trade-off. Leveraging I4R requires promoting manufacturing alongside targeted investments in technological infrastructure and human capital to mitigate service-sector disruption. Our study provides evidence for inclusive innovation policies to navigate this complex digital transformation.

Technological advancement promotes social changes and brings both opportunities and challenges to organizations. For high-tech enterprises in great demand of innovation and knowledge management, exploring what factors affect employees' innovative work behavior becomes emergent. This study investigates the impact of organizational innovation climate on employees' innovative work behavior, with knowledge sharing and creative self-efficacy as mediators. The structural model was tested using sample data from 307 employees of high-tech enterprises across different industries. The results demonstrated that the organizational innovation climate positively and significantly affected employees' innovative work behavior. Moreover, knowledge sharing and creative self-efficacy played chain mediation roles between organizational innovation climate and employees ' innovative work behavior. At the end of the study, we propose practical implications for enterprises regarding organizational support, knowledge management, and incentive mechanism on individual innovation from internal and external sources.

In the field of e-commerce, traditional customer segmentation models often rely on static transaction data and fail to capture the underlying temporal mechanisms of user behavior in massive and sparse datasets. To address this gap, this study proposes a unified framework that integrates value segmentation with human behavioral dynamics. First, we construct the RAIF model as an enhancement of the traditional RFM index to effectively mine user value from sparse shopping data by incorporating specific behavioral weights. Second, we utilize statistical physics to validate the behavioral distinctiveness of these RAIF segments. The results demonstrate that the proposed model improves segmentation accuracy in sparse scenarios and reveals that different value groups adhere to distinct physical laws. Specifically, we observe a unique power law characteristic comprising three stages in the distributions of intervals between events. This confirms that users of high value possess fundamentally different behavioral patterns compared to casual users. By integrating human dynamics into value mining, this study provides a novel theoretical perspective and actionable insights for dynamic personalized services.

This study draws on neoclassical economic models, resource reallocation mechanisms, comparative advantage theory, and related frameworks to examine the effects of foreign direct investment (FDI) and exports on employment during China’s economic transformation. Using provincial panel data from 2008 to 2022 and a dynamic panel data model, the results reveal that employment exhibits strong path dependence, with lagged employment, FDI, GDP, and fixed asset investment exerting positive effects at the nationwide level. Consistent with neoclassical and resource reallocation perspectives, FDI exerts a positive effect on employment by channeling capital into productive sectors and enhancing overall efficiency. By contrast, aligned with comparative advantage and new economic geography theories, export growth reduces employment in certain regions by concentrating production and shifting output toward capital- and technology-intensive sectors, thereby lowering labor demand, particularly among lower-skilled workers. The regional analysis indicates that FDI fosters employment across eastern, central, and western China, while GDP contributes to job growth in eastern and western China. By contrast, exports are associated with employment declines in the eastern and western regions, highlighting the uneven distribution of gains from trade integration. These findings underscore the importance of targeted policies that enhance the employment effects of FDI, while mitigating export-related vulnerabilities by promoting labor market resilience, industrial diversification, and workforce adaptability.