Search Results (230)

The objective of this study is to examine the impact of Chief Executive Officer (CEO) attributes on corporate performance in Jordan, a representative frontier market. The analysis focuses on four key CEO attributes, comprising two socio-demographic variables—age and educational—and two corporate governance-related ones—tenure and origin. Return on assets (ROA) and return on equity (ROE) are used as proxies for firm performance. Using a sample of 416 firm-year observations from companies listed on the Amman Stock Exchange (ASE) during 2015–2023, the study employs the system GMM methodology to estimate dynamic panel data models, addressing potential endogeneity and capturing the dynamic nature of firm performance. The results show that CEO age has a positive but insignificant effect, whereas CEO education and tenure significantly enhance firm performance. Conversely, CEO origin has a statistically negative impact on firm performance, reflecting the value of insider CEOs. The significant effects of CEO education, tenure, and origin—observed within the models that also incorporated firm- and country-level controls—reflect their incremental contribution to firm performance in frontier markets. Robustness checks, including controls for the COVID-19 pandemic and industry effects, confirm these findings. The study contributes to the literature by demonstrating the applicability of established theories—namely Upper Echelons, Stewardship, Resource Dependence, and Human Capital Theories—while identifying the CEO traits that drive success in frontier markets. It also offers practical guidance for shareholders, board directors, and policymakers in designing effective leadership and governance strategies. Full article

The digital economy is significantly transforming the global economic environment and has emerged as the primary driver behind China’s high-quality development. The comprehensive melding of the cultural and tourism sectors (CTI) serves as a strategic approach to boost regional competitiveness and enhance public welfare. This study investigates the mechanisms and boundary conditions through which the growth of the digital economy across China’s 31 provinces from 2011 to 2023 impacts CTI, aiming to address existing research gaps related to micro-level transmission mechanisms and the analysis of contextual variables. Utilizing a two-way fixed-effects moderated mediation model complemented by instrumental variable (IV-2SLS) regression for testing endogeneity, the research uncovers intricate interactions among the digital economy, CTI, and significant influencing factors. The results strongly suggest that advancements in the digital economy substantially facilitate the integration of cultural and tourism sectors. This beneficial effect is partially mediated through two primary channels: the construction of new infrastructure and enhancements in employment quality, underscoring the critical role of both material and human capital in digital empowerment. Significantly, this research uniquely identifies that new quality productive forces (NQP) have a notable negative moderating impact on the link between the digital economy and cultural–tourism integration. This indicates that in provinces exhibiting high levels of NQP, the positive influence of the digital economy on cultural–tourism integration is considerably diminished. This unexpected finding can be interpreted through mechanisms such as resource dilution, varied integration pathways or maturity effects, along with differences in developmental stages and priorities. Furthermore, it resonates well with the resource-based view, innovation ecosystem theory, and dynamic capability theory. Instrumental variable regression further substantiates the notable positive influence of the digital economy on the integration of cultural tourism. This approach effectively tackles potential endogeneity concerns and reveals the upward bias that may exist in fixed-effects models. The findings contribute significantly to theoretical frameworks by enhancing the understanding of the intricate mechanisms facilitating the digital economy and, for the first time, innovatively designating NQP as a surprising key boundary condition. This enriches theories related to industrial advancement and resource allocation in the digital age. On a practical note, the research provides nuanced and differentiated policy guidance aimed at optimizing pathways for integration across various Chinese provinces at different stages of development. Additionally, it underscores significant implications for other developing nations engaged in digital tourism growth, thereby improving its global relevance. Full article

Urban Waterlogging Susceptibility Assessment (UWSA) is vital for resilient urban planning and disaster preparedness. Conventional methods depend heavily on Historical Waterlogging Records (HWR), which are limited by their reliance on extreme rainfall events and prone to human omissions, resulting in spatial bias and incomplete coverage. While hydrodynamic models can simulate waterlogging scenarios, their large-scale application is restricted by the lack of accessible underground drainage data. Recently released flood control plans and risk maps provide valuable physics-informed priors (PI-Priors) that can supplement HWR for susceptibility modeling. This study introduces a dual-source integration framework that fuses HWR with PI-Priors to improve UWSA performance. PI-Priors rasters were vectorized to delineate two-dimensional waterlogging zones, and based on the Three-Way Decision (TWD) theory, a Multi-dimensional Connection Cloud Model (MCCM) with CRITIC-TOPSIS was employed to build an index system incorporating membership degree, credibility, and impact scores. High-quality samples were extracted and combined with HWR to create an enhanced dataset. A Maximum Entropy (MaxEnt) model was then applied with 20 variables spanning natural conditions, social capital, infrastructure, and built environment. The results demonstrate that this framework increases sample adequacy, reduces spatial bias, and substantially improves the accuracy and generalizability of UWSA under extreme rainfall. Full article

This study explores the convergence in greenhouse gas emissions (GHGs) and its determinants across 38 OECD countries during the period 1996–2022, employing the novel approach which combined club convergence method with supervised machine learning algorithm Extreme Gradient Boosting (XGBoost) and SHapley Additive exPlanations (SHAP) method. The findings reveal the presence of three distinct convergence clubs shaped by structural economic and institutional characteristics. Club 1 exhibits low energy efficiency, high fossil fuel dependence, and weak governance structures; Club 2 features strong institutional quality, advanced human capital, and effective environmental taxation; and Club 3 displays heterogeneous energy profiles but converges through socio-economic foundations. While traditional growth-related drivers such as technological innovation, foreign direct investments, and GDP growth play a limited role in explaining emission convergence, energy structures, institutional and policy-related factors emerge as key determinants. These findings highlight the limitations of one-size-fits-all climate policy frameworks and call for a more nuanced, club-specific approach to emission mitigation strategies. By combining convergence theory with interpretable machine learning, this study contributes a novel empirical framework to assess the differentiated effectiveness of environmental policies across heterogeneous country groups, offering actionable insights for international climate governance and targeted policy design. Full article

Sustainable tourism development has emerged as a strategic priority across ASEAN countries, yet the role of green innovation and environmentally responsible investment in shaping tourism outcomes remains underexplored. Existing studies often overlook the spatial interdependencies that characterize regional integration and cross-border environmental dynamics. This study investigates how green patents and green foreign direct investment (FDI) influence sustainable tourism development, both within and across ASEAN nations. Drawing on endogenous growth theory, ecological modernization, and FDI spillover frameworks, the analysis employs a Spatial Durbin Model (SDM) using panel data from 2000 to 2023. The findings reveal that green innovation and green FDI significantly enhance tourism development, with notable spatial spillover effects that benefit neighboring countries. These effects are most pronounced in leading ASEAN economies, where institutional capacity and absorptive readiness amplify the impact of green practices. The relationship is further shaped by economic growth, human capital, and political stability, while environmental degradation and inflation pose constraints. The study underscores the nonlinear and regionally heterogeneous nature of green tourism development, offering policy insights for fostering inclusive, resilient, and environmentally sustainable tourism strategies across ASEAN. Full article

Social workers are required to have the capacity to effectively support welfare recipients to restore their labor participation for social inclusion. However, a systematic method for process evaluation of this capacity has not yet been established. In this study, we developed the Index of Social Work Process in Promoting Social Participation of Welfare Recipients (SWP-PSP) to address this gap. Item domains and pools were prepared by referring to existing social work guidelines and human capital management theories, and content and face validity were confirmed by an expert panel review. The initial 75 items were revised to 44. We conducted a cross-sectional survey with 139 social workers working in public livelihood support at various municipal authorities in Japan. Item response theory analysis was performed for item selection, followed by the criterion-related validity test for convergent validation using Utrecht Work Engagement (UWE) scale scores as a reference. The selected 20 items with four domains were moderately correlated with UWE scores (Pearson’s correlation coefficient r = 0.35). Certified social workers demonstrated a stronger correlation with UWE (r = 0.44) than social workers without certification (r = 0.26). Cronbach’s alpha coefficients in each domain were over 0.77. These results indicate the reliability and validity of the SWP-PSP. This measure may be helpful for the evaluation of social workers’ capacity to promote social inclusion of welfare recipients. Full article

Career choices of master’s students, particularly regarding the pursuit of doctoral degrees, have received limited scholarly attention. This study examines the employment pathways and influencing factors of engineering master’s students. Drawing on human capital theory, career preference theory, and the two-way selection model, we analyse nationwide survey data from 21,973 engineering master’s students collected in 2021. Using a multinomial logistic regression model, we examine their post-graduation choices, including pursuing a doctorate, joining universities or scientific research institutions, working in government agencies, or entering the workforce. The findings suggest that gender, family background, and human capital have a significant impact on students’ career destinations. Male students are more likely to choose academic sectors, while those from high-income families tend to opt for non-academic sectors. Higher parental educational attainment increases the likelihood of pursuing doctoral studies, and students with more academic publications are also more likely to pursue a doctorate. These results highlight divergence in employment intentions between academic and non-academic sectors and reveal their underlying logic. The study offers insights for reforming talent cultivation models in universities, enhancing graduate employability, and informing the development of educational policy. Full article

This study examines the influence of entrepreneurship education on the career choices of female college students in China, focusing on four dimensions: courses, competitions, practices, and policy initiatives. Drawing on human capital and stereotype threat theories, the research analyzes data from 24,508 female students across 31 provinces to assess whether these educational factors would affect female entrepreneurship. The results indicate that courses and competitions play a critical role in promoting entrepreneurial career decisions, while practices and policy initiatives have a more limited effect. These findings highlight the need for targeted approaches to enhance female entrepreneurship education. The study provides actionable insights for policymakers and educators aiming to design effective programs that foster women’s entrepreneurship, especially in developing economies. Full article

This paper contributes conceptually and empirically to a more rigorous understanding of the role of intellectual capital in the sustainable development of the BRICS+ bloc. We investigate the growing command of technical competencies over social competencies across the entire knowledge process. A range of factors, including the ever-increasing tension between AI and humans, the multidimensional nature of intellectual capital, and a focus on competency-based approaches, shape the theory of a knowledge economy. This study presents a spatial modeling approach to analyze the sustainable development of economic systems, reevaluates the importance of intellectual capital in the era of Industry 4.0, introduces the concept of scientific management of intellectual capital by categorizing it into the AI, individual, and collective human mind, and enhances the methodology of managing the knowledge economy to foster intellectual capital development. The primary finding of the research is that the advancement of the knowledge economy is driving digital communication and network-based collaboration on a larger scale within the BRICS+ bloc. Policy implications are intricately linked to the necessity for the holistic development of intellectual capital, encompassing both human and artificial intelligence. This development requires enhancements in quality of life and living standards, advancements in education and healthcare, optimization of the labor market, and reinforcing its connection with the educational sector. Concurrently, it is vital to stimulate research and development (R&D), support the commercialization of high-tech innovations, and accelerate the process of robotization. These combined efforts are essential to fostering economic growth effectively. Full article

Over the past several decades, old industrialized regions worldwide have faced immense pressure to adapt to global economic shifts. Using one of China’s major industrial provinces, Hebei, as a representative case study, this study examines how the evolution of one of China’s old industrial provinces, Hebei’s industrial structure has influenced its economic growth from 1990 to 2023. Drawing on theories of structural transformation and endogenous growth, we argue that the reallocation of resources from lower-productivity sectors (e.g., agriculture) to higher-productivity sectors (manufacturing and services) can act as an engine of growth. We employ a shift-share analysis (SSA) to decompose Hebei’s economic growth into components attributable to national trends, industrial structure, and regional competitive performance. The results reveal a globally relevant pattern of stagnation: while Hebei’s growth largely benefited from nationwide economic expansion (national effect), its heavy industrial structure initially posed a drag on growth (negative structural effect) and its regional competitive advantage in steel and energy sectors has eroded over time (weakening competitive effect). Our regression analysis further shows that growth was overwhelmingly dependent on capital accumulation while the contribution of labor was statistically insignificant, pointing to a low-productivity trap common in such regions. By integrating these methods, this study provides a robust diagnostic framework for identifying the root causes of economic distress in legacy industrial regions both within and outside China. These findings underscore the importance of structural upgrading for sustainable growth and offer critical lessons for policymakers globally, highlighting the necessity of moving beyond extensive, capital-driven growth toward an intensive model focused on industrial diversification, innovation, and human capital to ensure the sustainable revitalization of post-industrial economies. Full article

In South Africa, small enterprise development is at the top of the government agenda. However, a significant issue lies in the type of skills and support necessary to develop SMMEs through the various phases of the business cycle. This study addresses a knowledge gap regarding whether SMME support interventions comprehensively address all managerial functions as per the P-O-L-C model. Guided by the Resource-Based Theory (RBT), and the Human Capital Theory (HCT), data was collected from 350 SMMEs in the Eastern Cape province using a structured self-administered questionnaire. Multiple regression analyses revealed that non-financial support from both the public (R² = 0.089, p = 0.215) and private (R² = 0.161, p = 0.207) sectors was not significantly associated with SMME success. Furthermore, while private sector support explained 14.8% (R² = 0.148, p < 0.001) and public sector support 7.6% (R² = 0.076, p < 0.001) of the variation in meeting SMME needs, support in key functional areas remains fragmented and poorly targeted. These findings highlight a systemic disconnect between the supply and demand sides of the SMME support ecosystem. To address this, this study proposes an integrative support model that aligns RBT and HCT within the P-O-L-C managerial framework, ensuring phase-appropriate, function-specific support. This framework departs from prior applications by reconceptualizing managerial support not as a generic intervention, but as a strategically sequenced process aligned with the business lifecycle. The model contributes a new lens for theorizing support efficacy and offers practical guidance for more targeted intervention design. This framework offers both theoretical and practical contributions toward improving the design and implementation of business interventions in South Africa. Full article

The implementation and impact of inclusivity and accessibility in the banking sector are crucial to the banking sector’s participation of any country in achieving the United Nations’ Sustainable Development Goals (SDGs) 1, 4, 5, 8, 10, 11, 16 and 17. This study examines the implementation and impact of inclusivity and accessibility in the South African banking sector, with a focus on the Free State province. Guided by the Sustainable Livelihoods Framework (SLF) and Institutional Theory, this research employs a quantitative, deductive approach to assess two core objectives: (1) the alignment of fintech banking practices with selected Sustainable Development Goals (SDGs), and (2) the identification of barriers to inclusivity and accessibility for women and youth. A stratified random sample of 208 banking professionals—comprising front-line employees, supervisors, and managers—was surveyed using a Likert-type questionnaire. Data were analysed using SPSS version 21. The findings reveal significant progress toward SDGs 1, 4, 5, 8, 10, 11, 16, and 17, reflected in a female-majority workforce, a youthful and educated employee base, and a nationally oriented employment strategy. These attributes signal a strong institutional commitment to inclusive growth and sustainable development. The sector also demonstrates readiness for fintech innovation, supported by high levels of training adequacy, relevance, and accessibility, indicating robust human capital and institutional adaptability to the Fourth Industrial Revolution (4IR) and AI-driven transformation. However, persistent structural barriers—particularly in leadership representation and digital access for women and youth—highlight the need for targeted policy interventions. Integrating inclusive fintech strategies, equitable training frameworks, and development programs is essential to sustaining progress and achieving the goals of the National Development Plan (NDP) and the SDGs. The Free State banking sector offers a promising model for inclusive institutional transformation aligned with global sustainability agendas. Full article

This study critically examines the integration of artificial intelligence (AI) into education through the lens of Marx’s theory of alienation, engaging with contemporary critiques of digital capitalism and academic labour. Drawing on an exploratory survey of 395 educators in Northern Cyprus, a context of early-stage AI adoption, the paper identifies four distinct forms of alienation exacerbated by AI: from the product of academic labour, from the educational process, from professional identity (species-being), and from interpersonal relations. Findings suggest that while educators who view AI more positively tend to report lower levels of alienation, particularly with respect to their pedagogical outputs, this association is tentative due to the low reliability of the AI perception scale (Cronbach’s α = 0.42). The results, therefore, serve as hypothesis-generating rather than conclusive. Situating the empirical findings within broader critiques by Noble, Hall, Preston, and Komljenovic, the study highlights how algorithmic governance, commercial platform logics, and data-driven performance regimes threaten teacher autonomy, creativity, and relationality. The paper concludes with a call for participatory governance, ethical oversight, and human-centred design to ensure that AI integration supports, not supplants, educators. In doing so, it contributes to critical debates on the ethical sustainability of digital education under conditions of intensifying automation. Full article

This study was conducted to examine the moderating effect of size on the impact of human capital on bank performance, using data from 26 commercial banks in Vietnam from 2008 to 2023 through panel data regression methods. The results indicate that bank size and human capital are important resources for commercial banks to increase their performance, which is consistent with the resource-based view and economies of scale theory. However, bank size fails to exhibit a significant moderating effect on the impact of human capital on the bank performance in Vietnam. This phenomenon can be explained by the relatively limited influence of size effects on human capital, coupled with the fact that the majority of Vietnamese commercial banks place significant strategic emphasis on human capital development within their operational frameworks. In addition, this study highlights the impact of some internal factors and the macroeconomic conditions on bank performance. From these empirical findings, this paper recommends several critical policies. 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