Digital technology innovation has reshaped the operational logic and competitive landscape of the global banking industry. Although numerous studies discuss the link between Fintech and bank profitability, most adopt linear empirical designs and ignore stage-based threshold effects, leading to inconsistent research conclusions. Based on 2015–2024 panel data of 120 Chinese commercial banks, this paper applies a two-way fixed-effects model to explore the nonlinear impact of Fintech development on bank profitability. Using the Peking University Digital Financial Inclusion Index and ROA as core indicators, a significant U-shaped relationship is verified. In the initial stage, Fintech suppresses bank profitability via market crowding-out effects and high digital transformation costs. After crossing a critical threshold, technological empowerment optimizes operational efficiency and credit risk management, and expands innovative intermediary businesses, thereby improving profitability. Heterogeneity tests show that the U-shaped pattern is more significant for small-and-medium-sized and non-state-owned banks, while large state-owned banks exhibit stronger resistance to Fintech shocks. This study supplements the nonlinear theoretical evidence of Fintech’s financial governance effect and provides differentiated digital transformation strategies for banks and targeted regulatory references.
With the economic globalization and the continuous upgrading of healthy consumption, it has become a trend for China's traditional beverage brands to expand into overseas markets. As a representative brand of herbal tea culture, WALOVI is in the process of changing from "Chinese kitchen" to "global drink". Based on the global value model of PCBC, this paper analyzes the development process of WALOVI brand globalization, dissembles its transformation route from four dimensions: product, channel, brand and culture, and deeply analyzes the internal logic of four-dimensional synergy and the mechanism of value creation. Through research, it is found that with the help of localized product innovation, The "online+offline" channel layout, the remolding of WALOVI's international brand, and the transnational spread of auspicious culture, WALOVI has established a collaborative model of "products lay the foundation, channels pave the way, brands empower, and culture casts the soul", and achieved multiple improvements in market, brand and cultural values.
Promoting the integration of the Party's innovative theories and national major strategies into textbooks, classrooms, and minds is a key aspect of universities fulfilling the fundamental task of cultivating students' moral character. However, the current integration of "Economics" courses into national medium- and long term plans generally faces structural challenges such as the disconnection between teaching content and value guidance, the "two skins" phenomenon of professional knowledge and ideological and political elements, and vague effectiveness evaluation. This paper takes the integration of the spirit of the 14th Five-Year Plan into "Economics" teaching as the starting point, proposes a teaching reform logic of "theory integration-situational construction-value internalization", and explains the innovative scheme from three dimensions: content integration, methodological approach, and evaluation system. It constructs a modular embedded teaching content system, a core teaching aid of macroeconomic decision-making simulation sandbox, and a "four-dimensional integrated" comprehensive evaluation model. The study believes that the key to achieving the paradigm shift from external embedding to endogenous integration lies in transforming planning concepts into analytical perspectives for economic theory teaching rather than supplementary cases. Through immersive situational teaching, students' embodied cognition and value recognition are facilitated, and process data and qualitative evidence are used to solve the observability problem of "entering minds".
Against the backdrop of global economic integration, the exhibition and convention industry, as a vital platform for economic exchange and cooperation, is constantly seeking breakthroughs and innovation. Following an examination of the characteristics of blockchain technology and trends in the exhibition and convention economy, this paper primarily explores the relationship between the industry and blockchain. It analyses, from a practical perspective, how ‘Blockchain+’ technology can be utilised to address specific challenges in the digitalisation of the exhibition and convention sector, thereby promoting innovation and development within the industry.
Sustainable apparel brands increasingly employ environmental claims to differentiate themselves in markets shaped by climate concern, consumer skepticism, and heightened scrutiny of greenwashing. Nature-based claims, particularly tree planting and ecosystem restoration, are attractive because they are tangible, emotionally resonant, and easy to communicate. However, the number of trees planted does not, by itself, demonstrate durable climate, biodiversity, or community outcomes. This article examines how sustainable apparel brands can move nature-based sustainability claims from activity-based storytelling to verified impact reporting. It uses a conceptual, illustrative case-based analysis of Tentree, a Canadian sustainable apparel brand, drawing on literature on sustainable fashion, greenwashing, consumer trust, nature-based solutions, and sustainability assurance. The analysis identifies five requirements for credible nature-based claims: clear claim definition, transparent evidence, independent verification and assurance, outcome-based reporting, and accountability for limitations and risks. Tentree’s 2024 Impact Report demonstrates meaningful progress through specific tree-planting figures, restoration partnerships, sustainability certifications, carbon-footprint reporting, material traceability, and emerging nature-related disclosure commitments. The case also indicates that future credibility could be strengthened through consistent project-level disclosure of survival rates, carbon and biodiversity outcomes, evidence of additionality, leakage-risk assessment, and corrective actions for restoration projects that underperform. The article contributes to sustainable marketing and corporate sustainability literature by distinguishing activity-based claims from outcome-based impact reporting and by offering practical guidance for more transparent, verified sustainability communication.
This study examines which skill types exert the greatest influence on winning in the National Basketball Association (NBA). Four key play types are analyzed: the Spot Up Shooter, the Pick & Roll Ball Handler, the Post Up Big Man, and the Isolation player. Using 2022–23 NBA Advanced Stats data, the study includes all players who appeared in at least 65 games. A suite of statistical tests—including multiple regression, descriptive statistics, Pearson correlation, single-factor ANOVA, and Tukey post-hoc analyses—was applied to identify relationships between these skill types and team wins, and to derive salary cap allocation recommendations. Findings indicate that all four skill types support winning above the .500 threshold, with the Spot Up Shooter demonstrating the highest win output (43.49 wins out of 82), followed by the Isolation player (42.86), the Pick & Roll Ball Handler (42.43), and the Post Up Big Man (42.29). A strong positive correlation (r = 0.5811) was identified between team payroll and wins. Recommended per-team salary allocations are approximately $29 million for Spot Up Shooters, $27 million for Isolation players, $21 million for Post Up Big Men, and $18 million for Pick & Roll Ball Handlers, from a league-average payroll of $151.7 million. These findings provide a data-driven framework to help franchises optimize salary cap decisions for maximum on-court performance.
California's Central Valley produces approximately 80% of the world’s almonds but has faced significant acreage reductions due to stricter Sustainable Groundwater Management Act (SGMA) mandates, rising production costs, and declining wholesale prices. Economic evidence is essential for almond growers to make informed farm-level decisions using accounting management methods. This study uses estimated cost data from a hypothetical 100-acre research orchard in California’s Central Valley in 2025 and applies accounting management methods to estimate per-acre operational and long-term investment costs. The study conducts breakeven, capital budgeting, sensitivity, and discounted cash flow analyses. Results show that: 1) from a wholesale price perspective, almond production cannot effectively break even in the short run when prices fall below approximately $4.50 per pound; 2) annual operating costs averaged approximately $10,343 per acre, including variable and fixed costs; 3) long-term investment analysis shows that without a down payment, almond growers face substantial annual investment costs associated with irrigation infrastructure, orchard establishment, and land acquisition, totaling approximately $276,660 annually ($2,767 per acre) for a 100-acre operation; and 4) under a 20% down payment scenario, annual investment costs decline to approximately $248,132 annually ($2,481 per acre), but long-term profitability remains highly sensitive to financing structure and land costs.
E-commerce has become an unavoidable force reshaping competition and consumer behavior across industries. Businesses increasingly depend on sentiment analysis to extract consumer intelligence from vast amounts of online reviews, social media, and digital interactions. However, existing models often ignore contextual information, limiting their ability to capture nuanced meanings in consumer sentiment. To address this gap, we propose a contextual ontology-based theoretical model architecture that integrates sentiment analysis with knowledge graph construction. Contextual ontology enables the formal representation of semantic meaning as it varies by context, thus reducing ambiguity in textual data interpretation. While simple algorithms may suffice for a consumer with straightforward preferences, such as price as an overriding criterion, only a contextual ontology can capture the complex, multi-criteria behaviors of more sophisticated consumers. Our theory framework demonstrates how consumer intelligence can be enriched by combining lexicon-based sentiment classification with ontology-driven context modeling, creating more robust insights for e-commerce decision-making. The knowledge graph in our architecture captures multi-dimensional relationships and dynamically updates as interactions evolve, allowing managers to filter context-induced noise and achieve precision market segmentation. By integrating context variables with non-context variables, businesses can move from generic opinion mining to context-aware sentiment analysis that optimizes strategic resources and enhances customer lifetime value (CLV). By invoking a behavioral Sensemaking lens, our framework accounts for the complex, identity-driven nuances and multifaceted personality traits that govern sophisticated consumer behaviors. This research contributes to both theory and practice by advancing sentiment analysis methods beyond context-free approaches and by offering e-commerce managers a pragmatic tool for high-velocity consumer intelligence gathering.
Grounded in the Social Exchange Theory (SET) and Social Identity Theory (SIT), the study investigates the impact of ethical leadership style on project success, with a focus on the mediating roles of trust and knowledge sharing. The study adopted a descriptive time-lagged design, in which data was collected from 415 project workers at three separate time points. Data on ethical leadership was collected at Time 1, trust and knowledge sharing at Time 2, and Time 3 focused on project success. Data was analyzed quantitatively using Partial Least Squares - Structural Equation Modelling with SmartPLS 4. The results show that ethical leadership has a significant and positive effect on project success, trust, and knowledge sharing. Further, both trust and knowledge sharing have a significant positive effect on project success. The mediating effect of trust and knowledge sharing on the relationship between ethical leadership and project success revealed a partial mediation. This study is among the first project management literature to empirically validate a dual-mediation framework that simultaneously examines trust and knowledge sharing as parallel mediators between ethical leadership and project success within a developing economy context. By integrating social exchange theory and social identity theory through a time-lagged design, the study offers a more rigorous and theoretically grounded explanation of the mechanisms linking ethical leadership to project outcomes, contributing novel insights that extend beyond existing single-mediator and cross-sectional studies.
Based on resource conservation theory and social cognitive theory, this study investigates how digital leadership influences job burnout in the context of digital transformation in traditional enterprises. A questionnaire survey was conducted among 245 employees from five traditional enterprises in central and western China. The results show that digital leadership has a significant positive effect on job burnout. Technology anxiety fully mediates this relationship, acting as a core psychological mechanism. Moreover, digital self-efficacy negatively moderates the effect of digital leadership on technology anxiety; specifically, the positive effect of digital leadership on technology anxiety is stronger among employees with lower digital self-efficacy, which in turn intensifies job burnout through technology anxiety. This study provides empirical evidence on the pathways through which digital leadership affects employee mental health in digital work environments and offers practical insights for organizations to alleviate burnout by enhancing employees' digital competencies and optimizing leadership practices.
In the fast-paced environment of sales management, both traditional Customer Relationship Management (CRM) and customer experience (CX) systems are ineffective at reading behavioral cues that indicate the onset of critical decisions and act as the foundation of reactive strategies and decreased revenue predictability. This research proposes Customer Intelligence as the next-generation managerial framework that goes beyond CRM to focus on behavioral probability management using the new Behavioral Sales Architecture (BSA) or multi-layered structure that includes data aggregation, pattern recognition and predictive decision-making. The study is based on the executive leadership of the author and the evolution of Customer Happiness Intelligence System (CHIS), an expandable commercial intelligence process, that incorporated qualitative executive analysis and quantitative client contact of 500 client interactions in 12 months with Sunlocate Properties, a real estate company that deals with commercial relocations. Empirical results show the notable improvements: the churn dropped by 24.7%, the revenue forecast accuracy increased by 27.0%, and the client lifetime value increased by 18.1%, which are proven with the help of Bayesian probabilistic modeling and triangulation based on themes. Such results place Customer Intelligence as a strategy layers to resilient business processes, as part of the scholarly discussion of the subject of commercial analytics, and provides practical implications on scalable and customer-centered innovation across industries. Incorporating BSA into the patent pending architecture of CHIS and into its future software MVP, this paper propagates the applied practice and cutting-edge theoretical development in favor of the paradigm based on probability in the era of data-driven trade.
This study examines the state of academic research on human development and sustainable economic growth. While related bibliometric reviews exist, this intersection has received less systematic attention. The study maps the field’s evolution, intellectual structure, and emerging directions, offering a future research agenda. A dataset of 68 publications indexed in Scopus (2000-2025) was analyzed using Microsoft Excel and R for performance indicators and VOSviewer for science mapping, capturing both descriptive trends and relational structures. This bibliometric analysis shows that publications have steadily increased, with a sharp rise after the 2015 adoption of the Sustainable Development Goals. The field is interdisciplinary but geographically concentrated in Europe, North America, and Asia, with fragmented collaboration networks. Thematic patterns reveal a shift from growth-centered models toward multidimensional approaches integrating sustainability, inclusion, and innovation. Emerging but underexplored areas include digital innovation, resilience, and human capital-environment linkages. Quantitative approaches dominate, though qualitative and mixed methods are gaining ground. This study provides a systematic bibliometric synthesis of a field that has received less attention, offering insights to guide future scholarship and policy. The analysis is limited to Scopus-indexed and English-language studies, which may introduce selection bias. Findings highlight gaps in regional representation and methodology, informing a future research agenda.
Under the accelerated development of the digital economy, examining the impact of supply chain digitalization (SCD) on corporate governance quality (CGQ) is of critical importance for identifying pathways to optimize governance structures amid technological change. The existing literature primarily focuses on the effects of corporate digital investment on governance quality, while insufficient attention has been paid to the role of collaborative digitalization across upstream and downstream supply chain segments. Using panel data for Chinese A-share listed corporates from 2010 to 2024, this paper investigates the impact of SCD on CGQ and its underlying mechanisms. The results indicate that SCD significantly enhances CGQ, with more pronounced effects observed in regions with higher levels of digital infrastructure, in high-technology industries, and among state-owned corporates. Mechanism analysis further reveals that improvements in information transparency, reductions in principle-agent costs, and enhancements in internal control quality constitute the primary channels through which SCD strengthens corporate governance. From the perspective of supply chain management, this study provides novel empirical evidence and managerial implications for emerging economies seeking to leverage digital technologies to improve CGQ.
Public-private partnerships (PPPs) are emerging as the pivotal mechanisms for financing and managing large-scale infrastructural development projects in many developing nations. The collaboration between governments and the private sector entities has been enhancing efficiency, performance, and innovation in infrastructure development, thus driving growth and development. However, critics have been questioning the viability of PPPs as a financing model in emerging economies. The paper explores the viability of PPPs as a financing model in developing nations by assessing potential benefits and challenges using the case study of Guyana, which is a developing nation with significant economic transformation. It investigates the current economic and political landscape of Guyana. The paper examines successful case studies of PPPs in developing nations for assessing their potential applicability in Guyana. It develops a set of recommendations for effective implementation of PPPs as a financing model in Guyana. The research employed a mixed-methods approach for providing a comprehensive analysis of PPPs in Guyana. It utilized data from a survey of 260 participants across Guyana 10 administrative regions and insights from document analysis and case studies. The findings identified the challenges affecting successful implementation of PPPs, including corruption, political instability, inadequate infrastructure, and insufficient education and training within Guyana. The results revealed the need for governance reform and policy consistency. The paper recommendations are strengthening governance frameworks, enhancing political stability, investing in education and infrastructure, and improving public engagement in Guyana.
Artificial intelligence (AI) is increasingly transforming recruitment processes, yet existing research remains fragmented across technical, operational, and behavioral perspectives. While prior studies emphasize efficiency gains and predictive accuracy, they often overlook the socio-organizational dimensions that shape the effectiveness and acceptance of AI-driven hiring systems. This study addresses this gap by advancing a socio-technical governance framework that integrates operational efficiency, candidate perception, and organizational legitimacy into a unified analytical model. Drawing on legitimacy theory and interdisciplinary insights from human resource management, operations management, and marketing, the paper conceptualizes AI-driven recruitment as a dynamic and adaptive system. The proposed model introduces causal relationships between core dimensions, highlighting the mediating role of candidate perception and the moderating function of governance mechanisms. Furthermore, it extends existing approaches by incorporating feedback loops that capture the temporal evolution of AI systems within organizational and institutional environments. The study contributes to the literature by reframing AI recruitment from a purely technical tool to a governance-driven socio-technical system. It also contributes to interdisciplinary AI governance research by linking recruitment efficiency, candidate experience, and legitimacy within the emerging European regulatory context. While conceptual in nature, the framework provides a foundation for future empirical research and offers practical insights for organizations seeking to balance efficiency, fairness, and legitimacy in AI-enabled recruitment processes.
Knowledge leveraging (KL) is an under-researched topic of importance. This study explores knowledge leveraging (KL) as a construct to be measured and its relationship to knowledge sharing (KS). An overall sample of n = 189 non-profit employee respondents was randomly split into two separate samples, n =95 and n = 94, allowing the initial results found in Sample 1 to be checked by Sample 2. Using exploratory factor analysis (EFA), two distinct three-item KL scales, KL – individual (KLI) and KL – team (KLT) were found to be distinct from a three-item KS measure. Confirmatory factor analysis (CFA) on the second sample supported these results. These three short, reliable scales may be useful to practitioners for a quick assessment. Results showed that KLI had a stronger impact on KS than KLT across both samples, while KLT was only significant for Sample 1 but not Sample 2. Team dynamics such as cohesiveness and diversity may complicate measuring team-level efforts and need further study. Additional study limitations and future research recommendations are discussed.
This study aimed at establishing the effect of corporate governance on performance of commercial state corporations in Kenya. Corporate governance is the scheme through which firms are managed, measured, and made accountable. Corporate governance plays a key part in accomplishment of a firm because it outlines modalities of achieving social and financial objectives. The main objective of the study was to determine the influence of corporate governance on performance of commercial state corporations in Kenya. Hypothesis was formulated to address this objective. The study adopted a cross sectional descriptive survey design, using a sample of 47 commercial state corporations. Commercial state corporations are income generating entities, managed by management board and governed by best practices of governance. The study revealed that corporate governance accounted for 55.3 percent (R2 = 0.553) of variation in non-financial performance and 39 percent (R2 = 0.39) of variation in financial performance amongst commercial state corporations in Kenya. The study found that corporate governance positively influences the performance of commercial state corporations in Kenya. More specific for every one-unit increase in corporate governance non-financial performance increases by 0.717 units (β = 0.717) holding other factors constant while financial performance increases by 0.801 units’ (β = 0.801) other factors held constant. This positive relationship was significant (P-value = .000<.05). The results of this study have contributed to theory and better understanding of the antecedents of corporate governance providing reference for further research. It is recommended that organizations improve corporate governance and recognize the combination of antecedents of corporate governance.
Technology finance, including venture capital, government grants, and R&D bank credit, significantly boosts technological innovation in knowledge-intensive small and medium-sized enterprises (SMEs), as demonstrated in a study of Thai firms. This study examines three objectives: (1) testing whether technology finance positively impacts innovation output; (2) examining whether financing constraints mediate this relationship; and (3) probing heterogeneity across firm size, age, and sub-sector. Using a panel dataset of 2,847 firm-year observations across five technology sub-sectors and mediation analysis, the research finds that technology finance directly improves patent applications and new product revenue, with a one-standard-deviation increase associated with an 18-22% rise in patents and a 14-17% rise in new product revenue. This effect is partly mediated by easing financing constraints (measured via the Size-Age index), meaning technology finance works both by providing capital and by reducing financial barriers to R&D, with the indirect pathway accounting for approximately 38-44% of the total effect. The impact is strongest for younger, smaller, and high-tech firms, particularly in digital technology and advanced manufacturing. The study addresses fragmented empirical evidence in emerging ASEAN economies and contributes to the middle-income trap literature, demonstrating that alleviating financial bottlenecks is a key mechanism for enabling the innovation-led structural transformation necessary for Thailand to escape growth stagnation. These findings offer actionable guidance for SME owners, finance managers, and policymakers in designing Thailand’s technology finance ecosystem under the Thailand 4.0 agenda.
The increasing integration of Artificial Intelligence (AI) into national cyber defense systems has fundamentally transformed threat detection, predictive analytics, and automated incident response. While these AI-driven capabilities enhance operational efficiency and resilience, they also introduce novel vulnerabilities, including susceptibility to adversarial attacks, model drift, cascading failures, and automation bias. This paper examines the pivotal role of AI safety evaluations in mitigating such risks, ensuring the reliability, robustness, and trustworthiness of AI-enabled defense mechanisms. It explores contemporary evaluation frameworks, performance and safety metrics, and methodological approaches to testing AI systems under simulated and real-world cyber threats. Through case studies of AI-powered intrusion detection systems, autonomous Security Operation Centers (SOC), and hybrid human-AI architectures, the study demonstrates measurable improvements in threat response accuracy, operational safety, and analyst decision-making. Furthermore, it outlines risk mitigation strategies, including continuous model monitoring, scenario-based testing, and policy integration, emphasizing the importance of human-in-the-loop (HITL) interventions. The findings highlight that systematic AI safety evaluations are essential not only for technical reliability but also for strategic national security, providing a framework for policymakers, cybersecurity professionals, and AI developers to enhance cyber resilience against evolving threats.
The aim of this study was to examine the relationship between environmental responsibility practices and environmental sustainable performance within firms, as well as the mediating role of social media. Using survey data from a convenient sample of 82 CEOs from medium-sized enterprises, regression analysis was utilized to examine the relationships between environmental responsibility practices, social media and environmental sustainable performance. Findings indicate that environmental responsibility practices have a significant positive relationship with organizations' environmental sustainable performance, with social media use positively mediating this relationship. The study emphasizes the importance of green practices for businesses and highlights the potential benefits of effectively utilizing social media. Managers can enhance performance on environmental aspects through green initiatives and leverage social media for reputation management, while policymakers can foster collaborative relationships and incorporate green norms into sustainability plans. This study enriches sustainability and social media fields by providing new insights and further understanding of how organizations can use both green practices and social media to improve their environmental sustainable performance from the natural resource-based view (NRBV) perspective.
