Search Results (478)

This paper examines the effect of digital innovation on cost stickiness in manufacturing firms, focusing on the underlying mechanisms and contextual factors. Using data from Chinese A-share listed manufacturing firms from 2012 to 2023, we find that, first, for each one-unit increase in the level of digital technology, the cost stickiness index of enterprises decreases by an average of 0.4315 units, primarily through digital process innovation and digital business model innovation, whereas digital product innovation does not exhibit a statistically significant impact. Second, manufacturing servitization and the optimization of human capital structure are identified as key mediating mechanisms. Digital innovation promotes servitization by transitioning firms from product-centric to service-oriented business models, thereby reducing fixed costs and improving resource flexibility. It also optimizes human capital by increasing the proportion of high-skilled employees and reducing labor adjustment costs. Third, the effect of digital innovation on cost stickiness is found to be heterogeneous. Firms with high financing constraints benefit more from the cost-reducing effects of digital innovation due to improved resource allocation efficiency. Additionally, mid-tenure executives are more effective in leveraging digital innovation to mitigate cost stickiness, as they balance short-term performance pressures with long-term strategic investments. These findings contribute to the understanding of how digital transformation reshapes cost behavior in manufacturing and provide insights for policymakers and firms seeking to achieve sustainable development through digital innovation. Full article

As the fundamental physical carrier for human production and socio-economic endeavors, enhancing urban land green use efficiency (ULGUE) is crucial for realizing sustainable development. To effectively enhance urban land green use efficiency, this study systematically examines the intrinsic relationship between industrial policies and ULGUE based on panel data from 286 Chinese cities (2010–2022), employing an integrated methodology that combines the Difference-in-Differences (DID) model, Super-Efficiency Slacks-Based Measure Data Envelopment Analysis model, and ArcGIS spatial analysis techniques. The findings clearly demonstrate that the establishment of the “Made in China 2025” pilot policy significantly improves urban land green use efficiency in pilot cities, a conclusion that endures following a succession of stringent evaluations. Moreover, studying its mechanisms suggests that the pilot policy primarily enhances urban land green use efficiency by promoting industrial upgrading, accelerating technological innovation, and strengthening environmental regulations. Heterogeneity analysis further indicates that the policy effects are more significant in urban areas characterized by high manufacturing agglomeration, non-provincial capital/non-municipal status, high industrial intelligence levels, and less sophisticated industrial structure. This research not only provides valuable policy insights for China to enhance urban land green use efficiency and promote high-quality regional sustainable development but also offers meaningful references for global efforts toward advancing urban sustainability. Full article

Differences exist between rural–urban migrants and urban–urban migrants in terms of human capital’s accumulation and pathways of social integration, yet few studies have systematically compared these distinctions. Based on the CMDS2017 survey data, this study constructed a comprehensive social integration index across four dimensions—economic integration, behavioral adaptation, identity recognition, and psychological assimilation—to analyze the influencing factors and decompose the disparities in social integration levels between the two groups from a human capital perspective. Using Oaxaca mean decomposition and Machado–Mata (MM) quantile decomposition, the results indicated that urban–urban migrants exhibited higher social integration levels than rural–urban migrants, with human capital significantly influencing integration outcomes. Better education, health status, longer migration duration, and more work experience positively enhanced migrants’ social integration. Human capital accounted for 38.35% of the social integration gap between the two groups, while coefficient differences were the primary driver of disparities. The returns to education diminish at higher integration levels, suggesting education played a stronger role for those with lower integration. The social integration gap between the two groups followed an inverted U-shaped trend, with smaller disparities at higher quantiles. As integration levels rose, characteristic differences declined continuously, indicating convergence toward homogeneity among high-integration migrants. These research findings indicated that the improvement in the social integration level of migrants still requires continuous investment in cultivating the human capital of migrants. Full article

In a business environment with rapidly growing digital technologies, knowledge management (KM) capability is an indispensable source for enterprise innovation activities. Nevertheless, there is limited understanding of the specific KM capability that leads to sustainable business model innovation (SBMI). This study therefore aimed to investigate the internal relationship between KM capability and SBMI by leveraging dynamic capability theory. A hierarchical regression analysis (HRA) and a fuzzy set qualitative comparative analysis (fsQCA) are used to analyze a sample of 115 Chinese innovative enterprises. The results indicate that organizational structure promotes information technology by improving human capital, and that information technology then stimulates collaboration depth by expanding collaboration breadth, thereby driving SBMI. Specifically, human capital, information technology, collaboration breadth, and collaboration depth play significant chain-mediating roles in the relationship between organizational structure and SBMI. This study contributes to the literature on KM and innovation management, extends the use of low-order and high-order dynamic capabilities in DCT, and assists managers in developing SBMI effectively. Full article

Achieving high-level green technological innovation in heavily polluting enterprises is critical for advancing sustainable development, particularly in the context of both organizational and regional digitalization. This study adopts a configurational perspective grounded in the Technology–Organization–Environment (TOE) framework and integrates theoretical insights from resource orchestration, resource dependence, and IT capability theories. It investigates how different types of skilled talent, such as production, technical, sales, and managerial employees, contribute to green innovation under varying digital conditions. By applying fuzzy-set qualitative comparative analysis (fsQCA) to a sample of 96 publicly listed firms from China’s heavily polluting industries, this study identifies four distinct talent-based configurations that can lead to high levels of green innovation: production-centric, management-led, technical talent driven, and regionally enabled models. Each configuration reflects a specific system state in which a core group of skilled employees plays a leading role, supported by complementary functions, and shaped by the interaction between internal digital transformation and the external digital environment. This study contributes to the systems literature by elucidating the combinational roles of digital resources and talent deployment within the systemic TOE framework, and offers practical guidance for enterprises aiming to strategically utilize human capital to enhance green innovation performance amid ongoing digital transformations. Full article

The paper analyses the relationship between human capital formation and income growth in Burkina Faso using data from household surveys conducted in 2009 and 2018. By combining estimates from multiple linear regressions of the impact of human capital variables on income with variance decomposition techniques, this paper quantifies the contribution of education, health, underemployment, and dietary diversity to income growth. It distinguishes between the shares related to the effects of increasing capital factor endowments and those related to the returns on these endowments. The results demonstrate that an increase in human capital endowment is a key factor in determining workers’ income growth. Furthermore, the impact of human capital on income growth is greater when the endowment and return effects of these factors are both positive and high. These results also indicate that a significant improvement in household income is more likely to be achieved by interventions focused on both increasing human capital endowments and improving human capital outcomes. Full article

Grounded in coupling theory, this study investigates the interplay among three key elements of economic growth, namely the digital economy, carbon emissions efficiency, and high-quality economic development. Drawing on data from 30 Chinese provinces from 2000 to 2023, we employ exploratory spatiotemporal data analysis and the GeoDetector model to examine the spatial–temporal evolution and underlying driving forces of coupling coordination. This research enriches the theoretical framework of multi-system synergistic development in a green transition context and offers empirical insights and policy recommendations for fostering regional coordination and sustainable development. The results reveal that (1) both the digital economy and high-quality economic development show a steady upward trend, while carbon emissions efficiency has a “U-shaped” curve pattern; (2) at the national level, the degree of coupling coordination has evolved over time from “mild disorder” to “on the verge of disorder” to “barely coordinated,” while at the regional level, this pattern of coupling coordination shifts over time from “Eastern–Northeastern–Central–Western” to “Eastern–Central–Northeastern–Western”; (3) although spatial polarization in coupling coordination has improved, disparities fluctuate in a “decline–rise” pattern, with interregional differences being the main source of that variation; (4) the degree of coupling coordination has a positive spatial correlation, but with a declining trend with fluctuations; and (5) improvements in the level of economic development, human capital, industrial structure, green technological innovation, and market development capacity all contribute positively to coupling coordination. Among them, green technological innovation and market development capacity are the most influential drivers, and the interactions among all driving factors further enhance their collective impact. Full article

This paper takes the five northwestern provinces of China as research objects to explore the intrinsic mechanisms of the digital economy, industrial structure upgrading, and regional green development through empirical analysis. This study reveals that the digital economy plays an indispensable role in the green and high-quality development of the five northwestern provinces. (1) This study investigates the influence of the digital economy on green high-quality development in China’s five northwestern provinces, focusing on the mediating effect of industrial structure upgrading. Using panel data and multiple regression analysis, it demonstrates that the digital economy significantly promotes green development, even when controlling for infrastructure, human capital, and openness. (2) Industrial structure upgrading serves as a critical mediator, transmitting part of this positive effect. Heterogeneity analysis shows that the digital economy’s impact is more pronounced in high-GDP regions, while low-GDP regions remain dependent on conventional drivers like infrastructure. Additionally, human capital and tax burdens exhibit positive effects on green development, whereas R&D intensity has a negligible short-term influence. (3) These findings highlight the importance of region-specific policies integrating digital infrastructure, industrial upgrading, and human capital investment to foster sustainable regional development. This study provides a theoretical basis for deepening digital economic development and promoting green industrial upgrading in northwest China. It suggests that policymakers should account for regional economic disparities and coordinate the deployment of digital infrastructure, industrial transformation, and human capital investment to achieve long-term, coordinated green and high-quality development in the region. Full article

This study investigates the complex dynamics of new-type urbanization in resource-based county-level cities, using Wuan City in Hebei Province, China, as a representative case. As China pursues a high-quality development agenda, cities historically dependent on resource extraction face profound challenges in achieving sustainable and inclusive urban growth. This research employs a multi-method approach—including Theil index analysis, industrial shift-share analysis, a Cobb–Douglas production function model, and a composite urbanization index—to quantitatively diagnose the constraints on Wuan’s development and assess its transformation efforts. Our empirical results reveal a multifaceted situation: while the urban–rural income gap has narrowed, rural income streams remain fragile. The shift-share analysis indicates that although Wuan’s traditional industries have regained competitiveness, the city’s economic structure is still burdened by a persistent negative structural component, hindering diversification. Furthermore, the economy exhibits characteristics of a labor-intensive growth model with inefficient capital deployment. These underlying issues are reflected in a comprehensive urbanization index that, after a period of rapid growth, has recently stagnated, signaling the exhaustion of the city’s traditional development mode. In response, Wuan attempts an “industrial transformation-driven new-type urbanization” path. This study details the three core strategies being implemented: (1) incremental population urbanization through development at the urban fringe and in industrial zones; (2) in situ urbanization of the existing rural population; and (3) the cultivation of specialized “characteristic small towns” to create new, diversified economic nodes. The findings from Wuan offer critical, actionable lessons for other resource-dependent regions. The case demonstrates that successful urban transformation requires not only industrial upgrading but also integrated, spatially aware planning and robust institutional support. We conclude that while Wuan’s model provides a valuable reference, its strategies must be adapted to local contexts, emphasizing the universal importance of institutional innovation, human capital investment, and a people-centered approach to achieving resilient and high-quality urbanization. Full article

Amid growing concern about labour market resilience in an era of digital and green transitions, this study carries out an investigation on how academic innovation and industrial transformation jointly shape sustainable employment outcomes across EU-27 member states. We frame this inquiry within the emerging concept of the “employment trilemma”, which posits inherent tension between competitiveness, innovation, and social inclusiveness in modern economies. Drawing on a dynamic panel dataset (2005–2023) and employing System SMM estimations, we test the hypothesis that the alignment of academic innovation systems and industrial transformation strategies enhances long-term employment sustainability. Our results reveal a nuanced relationship: academic innovation significantly supports employment in countries with high knowledge absorption capacity, whereas industrial transformation contributes positively only when embedded in cohesive, inclusive economic frameworks. Thus, these findings provide valuable insights for international business due to their emphasis on the importance of cross-sectoral collaboration, policy synchronisation, and investment in human capital for firms navigating increasingly volatile labour markets. Likewise, the study offers actionable insights for business leaders, policymakers, and universities striving to balance innovation with equitable labour market outcomes in an integrated European economy. Full article

Higher education institutions (HEIs) are increasingly seen as central actors in entrepreneurial ecosystems, yet their support mechanisms do not always align with the needs of student entrepreneurs. This study investigates how key stakeholders, business students, professors, and experienced start-up founders perceive the relative importance of success factors for student-led start-ups within HEIs. Using a cross-sectional descriptive design, this study used a 34-item survey instrument developed through an extensive literature review and validated for content by a panel of experts. Triangulation between stakeholder groups enabled a multidimensional comparison of perspectives. Descriptive statistics were used to analyze patterns of agreement and variability, resulting in a three-tier framework of success factors based on perceived importance and consensus. High-impact factors included faculty entrepreneurial experience, student mindset, and access to mentorship, while traditional inputs such as infrastructure, legal support, and funding were ranked lower. The findings highlight a misalignment between institutional offerings and stakeholder priorities, highlighting the critical role of social and human capital. This research provides practical guidance for HEIs seeking to improve entrepreneurial support and contributes to theoretical discussions on stakeholder-informed ecosystem models. Although limited by its single-institution context, this study offers a foundation for future cross-institutional and longitudinal research. Full article

With the widespread adoption of deep learning in critical domains, such as computer vision, model security has become a growing concern. Backdoor attacks, as a highly stealthy threat, have emerged as a significant research topic in AI security. Existing backdoor attack methods primarily introduce perturbations in the spatial domain of images, which suffer from limitations, such as visual detectability and signal fragility. Although subsequent approaches, such as those based on steganography, have proposed more covert backdoor attack schemes, they still exhibit various shortcomings. To address these challenges, this paper presents HCBA (high-frequency chroma backdoor attack), a novel backdoor attack method based on high-frequency injection in the UV chroma channels. By leveraging discrete wavelet transform (DWT), HCBA embeds a polarity-triggered perturbation in the high-frequency sub-bands of the UV channels in the YUV color space. This approach capitalizes on the human visual system’s insensitivity to high-frequency signals, thereby enhancing stealthiness. Moreover, high-frequency components exhibit strong stability during data transformations, improving robustness. The frequency-domain operation also simplifies the trigger embedding process, enabling high attack success rates with low poisoning rates. Extensive experimental results demonstrate that HCBA achieves outstanding performance in terms of both stealthiness and evasion of existing defense mechanisms while maintaining a high attack success rate (ASR > 98.5%). Specifically, it improves the PSNR by 25% compared to baseline methods, with corresponding enhancements in SSIM as well. Full article

This study proposes a predictive framework that integrates machine learning techniques with Transactional Net Promoter Score (tNPS) data to enhance sustainable Human Resource management. A synthetically generated dataset, simulating real-world employee feedback across divisions and departments, was used to classify employee performance and engagement levels. Six machine learning models such as XGBoost, TabNet, Random Forest, Support Vector Machines, K-Nearest Neighbors, and Neural Architecture Search were applied to predict high-performing and at-risk employees. XGBoost achieved the highest accuracy and robustness across key performance metrics, including precision, recall, and F1-score. The findings demonstrate the potential of combining real-time sentiment data with predictive analytics to support proactive HR strategies. By enabling early intervention, data-driven workforce planning, and continuous performance monitoring, the proposed framework contributes to long-term employee satisfaction, talent retention, and organizational resilience, aligning with sustainable development goals in human capital management. Full article

The relationship between firm size and the financial performance of advertising and marketing companies remains understudied in the academic literature, including in the regional context. Using a panel data methodology, this study analyzes the impact of three proxies for firm size (total assets, number of employees, and sales) on the financial performance (return on assets and profit margin) of the 500 most profitable advertising and marketing companies from 16 Western European countries over the period 2019–2023. Weighted least squares regression analysis revealed statistically significant negative effects of all three proxies for firm size on financial performance, with the strongest negative effects on total assets on return on assets and sales on profit margin, which is similar to return on sales. Empirical data confirm the inverse relationship between total assets and their profitability; this indicates the advantages of resource-optimized business models with high management flexibility and effective use of intellectual capital compared to material-intensive structures. The inverse relationship between the number of employees and financial performance is due to higher operating personnel costs and the difficulty of effectively managing human resources as the number of employees increases. Increased sales negatively affect profit margins, demonstrating a decrease in the efficiency of converting revenue into profits as operations expand. These findings are important for developing effective financial management strategies and making investment decisions in the industry under study. The research contributes to SDGs 8, 9, and 12 by demonstrating how resource-optimized structures with higher management flexibility and effective use of intellectual capital can outperform material-intensive structures in the advertising and marketing industry. Full article

Indonesia’s high logistics costs—approximately 14.6% of its GDP—pose a significant challenge to national economic competitiveness. Key contributing factors include complex geography, fragmented multimodal transport systems and inefficient container terminal operations, particularly concerning the handling of empty containers. This study investigates operational optimization in a container terminal using Agile and Lean principles, without additional investment or infrastructure expansion. It compares throughput before and after optimization, focusing on equipment productivity and reduction in idle time, especially related to equipment and human resources. Field implementation began in 2015, followed by simulation-based validation using system dynamics modeling. The terminal demonstrated a sustained increase in capacity beginning in 2016, eventually exceeding its original design capacity while maintaining acceptable berth and Yard Occupancy Ratios (BOR and YOR). Agile practices improved empty container handling, while Lean methods enhanced berthing process efficiency. The findings confirm that significant reductions in port operational costs, shipping operational costs, voyage turnover time, and logistics costs can be achieved through strategic operational reforms and better resource utilization, rather than through capital-intensive expansion. The study provides a replicable model for improving terminal efficiency in ports facing similar constraints. Full article