Search Results (508)

In this study, we collected Instagram posts that contain misinformation in order to understand the fact-checking practices followed by Meta shortly before its decision to cancel its collaboration with fact-checking organizations in 2025. This paper uses the theoretical frameworks of Digital Capitalism and Algorithmic Governance and employs a mixed-method approach. The study’s findings are only meant to offer an empirical reference point before Meta’s new fact-checking policy implementation. The study, which investigated 39 misinformation-related terms, showed that the company used two types of fact-checking ratings (automated and human) that most often labelled posts that contained false news, followed by false and misleading news. Based on the limited collected data, the results indicate some intensification of its fact-checking efforts in 2020 with the emergence of the COVID-19 pandemic, but it greatly reduced the volume of its work in 2022, a few years before its decision to stop working with fact-checkers. The manual thematic categorization of fact-checked posts shows that the most frequent type is related to false claims about harmful or useless vaccines, followed by other claims like harmful or useless facemasks and COVID-19 being fake or unharmful. The implications of the study are discussed in the conclusion. Full article

The world context has changed rapidly over the last few centuries. This is interesting because it has brought important innovations that have allowed us to improve human quality of life, but has also created new challenges for humanity due to the increased anthropological footprint. The question that the scientific community may pose sometimes is whether the old theories are still relevant in today’s frameworks. For example, is the Cobb–Douglas production function developed in the twenties of the last century still relevant for analyzing the current agricultural economic realities? This is a pertinent question, considering the changes in economic dynamics, the modernization of farms, and the innovations available for agricultural practices. From this perspective, this research aims to estimate the Cobb–Douglas model, considering panel data and cross-sectional methodologies for international countries’ agriculture, including spatial autocorrelation approaches, with statistical information from the FAOSTAT database for 162 countries for the period 2000–2023. This model was extended with variables selected through machine learning algorithms. The original linear Cobb–Douglas function model yields elasticities of 0.561 and 0.361 for the logarithm of net capital stocks and the logarithm of employment in agriculture, respectively. When the model is extended to take account of the results from machine learning approaches, the elasticities for the logarithm of agricultural land, the logarithm of net capital stocks, the logarithm of employment in agriculture, and the logarithm of export value are, respectively, 0.216, 0.43, 0.244, and 0.099. With the inclusion of dummy variables in the extended model for the years under consideration, the elasticity results obtained are not very different from those obtained using this model without these dummies. Taking country dummies into account, the elasticity results are 0.436, 0.231, 0.118, and 0.072, respectively, for the logarithms of agricultural land, net capital stocks, employment in agriculture, and export value. When spatial autocorrelation effects and panel data are taken into account, the results are not very different from those obtained for the model with country dummies (with the exception of the elasticity for the logarithm of net capital stocks, which is slightly lower). For the model incorporating spatial autocorrelation effects and cross-sectional data, the elasticities of the logarithms of agricultural land, net capital stocks, employment in agriculture, and export value are, respectively, 0.142, 0.336, 0.293, and 0.256. These findings suggest that the estimation of the Cobb–Douglas production function for the global agricultural sector, using data from different countries, should take into account heterogeneity between countries and spatial dependence in order to obtain relatively more stable elasticities. The results suggest that taking into account country-specific effects and spatial autocorrelation may be more important for the robustness of the estimates than simply extending the model with additional explanatory variables. Full article

Climate change poses growing risks to coffee farming in Uganda. However, households do not adapt to the same degree, and it remains unclear which household resources contribute to differences in adaptation. This study examines the specific household resources associated with climate adaptation among 376 smallholder coffee-farming households across four districts in Southwestern Uganda. Adaptation was measured using a count of adopted practices and a continuous index derived from Principal Component Analysis (PCA), with Multiple Correspondence Analysis (MCA) used as a robustness check. The analysis examined constituent household resources separately to assess whether broad livelihood-capital categories obscure divergent relationships among their components. Household size, knowledge exchange with other farmers, training, and ownership of basic farm tools were the most consistent positive correlates of adaptation. Years of coffee-farming experience, by contrast, showed a negative relationship with adaptation, opposite to the direction observed for household size despite both being classified within the human-capital domain. A composite human-capital specification showed weaker statistical fit than the disaggregated specification. A similar divergence occurred within financial capital: off-farm income showed a positive relationship with adaptation, whereas access to credit did not. Within physical capital, tool ownership was positively related to adaptation, whereas irrigation equipment, owned by only 1.6% of households, was not statistically significant. These findings suggest that policies to strengthen climate adaptation among smallholder coffee farmers should prioritize farmer-to-farmer knowledge exchange, training, and access to basic farm tools. Additionally, findings caution against treating broad livelihood-capital categories as internally homogeneous because constituent resources may have different or opposing relationships with adaptation. Full article

This study examines how distinct dimensions of financial literacy relate to the business performance of rural female micro-entrepreneurs in a transition economy. Drawing on the Resource-Based View, Human Capital Theory, and Entrepreneurial Capability Theory, financial literacy is conceptualized as four separable capabilities: financial education, cash forecasting, bookkeeping practice, and financial self-efficacy. Survey data were collected from 200 women micro-entrepreneurs sampled at random in Shovot District, Khorezm region, Uzbekistan, and 173 usable responses were analysed with partial least squares structural equation modelling (PLS-SEM). After validation and refinement of the measurement model, the results show that bookkeeping practice (β = 0.407) and financial education (β = 0.294) are positively and significantly associated with business performance, as is financial self-efficacy (β = 0.155), whereas cash forecasting shows no significant unique association. The findings are robust to alternative construct and outcome specifications and to endogeneity checks, and they suggest that, where formal financial infrastructure is thin, record-keeping and foundational financial knowledge appear to be the capabilities most closely associated with micro-enterprise performance; because the measurement model was refined on these data, these associations are exploratory and await confirmation on independent samples. Full article

Driven by the strategies of high-quality development and manufacturing transformation and upgrading, China’s economy is gradually shifting to an innovation-driven growth model. Empowering firms to lift innovation quality through new-generation artificial intelligence has become a core priority for industrial development and policy support. This paper adopts unbalanced panel data of A-share listed manufacturing firms from 2012 to 2023 and employs the Double Machine Learning model to systematically investigate the impact and transmission mechanisms of new-generation artificial intelligence on manufacturing firms’ innovation quality. The results reveal that new-generation artificial intelligence can significantly boost manufacturing firms’ innovation quality, and this core conclusion remains valid after a series of robustness tests. Mechanism verification confirms that new-generation artificial intelligence promotes the upgrading of firms’ human capital structure, deepens firms’ digital transformation, and raises firms’ R&D investment intensity. These three channels work synergistically to indirectly empower the upgrading of firms’ innovation quality. Heterogeneity analysis verifies that the innovation quality improvement effect of new-generation artificial intelligence exhibits prominent stratified differences across regions, industrial sectors, and environmental regulatory scenarios. Specifically, the empowerment effect of new-generation artificial intelligence (GAI) is significantly stronger for samples from environmental pilot cities, Southern Coastal, Eastern Coastal, and Northern Coastal regions, as well as high-tech manufacturing firms. In contrast, its positive driving effect is weak or insignificant for samples in the middle reaches of the Yellow River and Northwest China, along with non-high-tech industries. This paper improves the theoretical analytical framework for artificial intelligence empowering micro-firm innovation and enriches relevant research on digital technologies and corporate innovation. It provides a theoretical basis and practical implications for China’s manufacturing sector to break through innovation bottlenecks via intelligent technologies and achieve comprehensive high-quality innovative development across the manufacturing industry. Full article

Commercial operations across trading, import/export, logistics, and technology distribution are being reshaped by the convergence of artificial intelligence (AI), machine learning, multi-agent robotics, and Extended Reality (XR). Small and Medium-sized Enterprises (SMEs) feel this shift acutely: they face the same pressures as their larger competitors; labor shortages, high-SKU inventories that resist tidy categorization, narrow margins, and customer expectations set by Amazon-grade fulfilment, but rarely command the capital or the structured warehouse environments that make industrial automation straightforward. Existing frameworks for AI-driven automation and digital twins have been developed primarily for large-scale industrial settings and do not account for the capital, infrastructure, and organizational constraints specific to SMEs, leaving a gap in SME-scoped integration models. This research addresses that gap by asking how AI-driven robotics and immersive technologies can be integrated to optimize commercial workflows in SMEs operating in dynamic logistics and trading environments. The proposed framework is grounded in Sociotechnical Systems Theory, which treats technology and organizational workflows as jointly designed and mutually adapting, and follows a Design Science orientation in which the architecture itself is constructed as an evaluable artifact rather than a purely descriptive model. Methodologically, the study conducts a narrative synthesis of literature on embodied AI, computer vision, digital twins, VR training, and AR-assisted operations, combined with workflow analysis to identify where SMEs lose the most time and money. These are translated into a four-layer system architecture (perception, cognition, execution, integration) deployed through a four-phase implementation model: needs assessment, digital-twin and VR pre-training, controlled hardware pilot, and AR-supported scaling. The contribution of the study is twofold: conceptually, it brings together several technologies that are often discussed separately in the literature, while focusing specifically on the needs and constraints of SMEs while practically, it proposes a phased roadmap that can help SMEs adopt these technologies gradually, reducing both financial and operational risks. The approach also emphasizes human–robot collaboration rather than replacing human workers. The study does not include experimental validation, it presents a conceptual architecture and implementation roadmap consistent with a Design Science artifact-construction stage that can serve as a basis for empirical testing in real commercial environments. Full article

Planetary health recognizes that human health, well-being, and sustainable development depend fundamentally on the integrity of natural ecosystems that regulate climate, maintain biodiversity, secure food and water resources, and protect populations from environmental risks. As environmental degradation increasingly threatens this life-support system, there is a growing need for economic indicators that explicitly recognize the value of natural capital alongside conventional measures of development. Gross Ecosystem Product (GEP) has emerged as comprehensive metric for quantifying the monetary value of ecosystem services and informing evidence-based policy. This study estimates India’s GEP for the period 2011–2012 to 2020–2021 using an ecosystem accounting framework aligned with the System of Environmental Economic Accounting (SEEA). The analysis integrates provisioning services (timber, non-timber forest products, fuelwood, and fisheries), regulating services (carbon sequestration), and cultural services (nature-based tourism) using market price, replacement cost, and benefit transfer methods based on secondary data from national and published sources. India’s total GEP is estimated at US$207.05 billion, highlighting the substantial but under-recognized contribution of ecosystems to the national economy and societal well-being. Regulating services dominate GDP, with carbon sequestration alone accounting for US$166.73 billion, followed by provisioning services, while cultural services contribute a relatively smaller share. These findings reveal a significant gap between ecosystem contributions and their representation in conventional metrics such as Gross Domestic Product (GDP), underscoring the limitations of growth-centric development frameworks. By integrating ecosystem values into national accounting, GEP provides a practical tool for advancing planetary health, strengthening climate resilience, conserving biodiversity, supporting ecosystem-based management, and guiding policies that align economic development with ecological sustainability and long-term human well-being. Full article

Intellectual capital is the foundation of the knowledge-based economy. The main purpose of this study is to examine the impact of intellectual capital on corporate sustainable growth in the Chinese baijiu industry and to investigate whether firm profitability and capitalized research and development (R&D) investment mediate this relationship. This study takes Chinese baijiu listed companies during 2010–2024 as the sample and employs fixed-effects regression models. Intellectual capital is measured through the modified value-added intellectual coefficient (MVAIC) method, and corporate sustainable growth is measured through Higgins’ sustainable growth model. The results show that intellectual capital promotes corporate sustainable growth in China’s baijiu industry. This impact is more significant during and after COVID-19, in private-owned companies, in middle- and low-end-brand companies, and in companies receiving no government innovation subsidies. Regarding intellectual capital components, human capital along with physical capital contributes to corporate sustainable growth. In addition, firm profitability plays a mediating role in the relationship between intellectual capital and corporate sustainable growth, whereas capitalized R&D investment does not play a mediating role. This study can generate practical insights for corporate managers to achieve their future sustainable development. Full article

Despite growing regulatory and investor attention to human capital as a core pillar of corporate sustainability and ESG reporting, it remains unclear how human capital-related information is priced in financial markets. This study examines the associations between human capital disclosure, management practices, and firms’ financing costs. Using a global panel of 1180 non-financial firms across 53 countries from 2017 to 2023, we employ Bloomberg ESG data to construct measures of human capital disclosure, management practices, and materiality. Panel regression analyses indicate that while human capital management practices exhibit no significant standalone associations, human capital disclosure is positively associated with the cost of equity, cost of debt, and the weighted average cost of capital. However, we document a significant complementary effect: when coupled with strong management practices, disclosure is associated with a lower cost of equity, particularly in contexts where human capital is financially material. Furthermore, the positive association between disclosure and capital costs becomes weaker as human capital materiality increases. Overall, our findings suggest that capital markets do not uniformly price human capital information; rather, its valuation is highly conditional, depending on the substantive credibility of management practices and contextual materiality. Full article

Sustainable Digital Infrastructure plays an increasingly important role in strengthening regional economic resilience and promoting inclusive growth. However, its dynamic effects on nascent entrepreneurship remain underexplored. Treating China’s smart city pilot policy as a quasi-natural experiment, this study uses data on newly registered enterprises in 288 Chinese cities from 2005 to 2019 and a multi-period difference-in-differences (DID) model to examine this relationship. The results show that Sustainable Digital Infrastructure significantly promotes new venture creation. Owing to environmental dynamism—manifested in creative destruction, strategic wait-and-see behavior, and learning-curve effects—its entrepreneurial impact is initially volatile before becoming significantly and persistently positive. The industry-level analysis reveals heterogeneous effects across sectors: the largest estimated effect occurs in wholesale and retail trade, while the estimated effect in scientific research and technical services strengthens over time. Mechanism analyses provide suggestive evidence for three channels: technological innovation, human capital development, and digital finance. The effects are also more pronounced in eastern China and smaller cities. This study provides empirical evidence and practical guidance for emerging economies seeking to promote new venture creation through digital infrastructure. It conceptualizes “sustainability” in the SDI context as the capacity of digital infrastructure to support enduring and inclusive economic development, rather than as a property of the infrastructure’s environmental performance. Full article

Public sector organizations face mounting pressure to improve employee performance while pursuing sustainable management practices, yet evidence on how sustainability-oriented leadership relates to tangible performance outcomes remains scarce, particularly in regional government settings. Grounded in Self-Determination Theory, this study examines the association of Human Capital Sustainability Leadership (HCSL) with Employee Job Performance (EJP) and the mediating role of Innovative Work Behavior (IWB) among Indonesian civil servants managing regional government assets (Barang Milik Daerah). Survey data were collected from 541 civil servants across the DKI Jakarta Provincial Government using validated multi-item scales and analyzed with Partial Least Squares Structural Equation Modeling (PLS-SEM). HCSL was positively associated with IWB (β = 0.834, p < 0.001) and EJP (β = 0.438, p < 0.001), and IWB was positively associated with EJP (β = 0.383, p < 0.001). Bootstrap analysis indicated a complementary partial mediation of the HCSL–EJP relationship through IWB (β = 0.319, 95% CI [0.194, 0.440]). The model accounted for 61.9% of the variance in EJP and 69.5% in IWB, though the cross-sectional, single-source design and very high construct reliabilities mean these estimates should be read as upper bounds. The findings suggest that sustainable leadership development may be one credible lever for supporting innovation and performance in public asset stewardship, with implications for sustainable governance and human capital development. Full article

This article discusses Zygmunt Bauman’s and Erich Fromm’s diagnoses of love in contemporary consumer societies and reads them as a critical contribution to current debates on the civic potential of love. Focusing on two major transformations that affect everyday life and primary face-to-face relationships—the growing pervasiveness of digital media and the consolidation of a consumerist ethos—the paper shows how commodification, ontological insecurity and the “expulsion of the Other” undermine human relationships and contribute to the fragmentation of social love. Drawing on Bauman’s notion of liquid love and Fromm’s conception of love as an art oriented to the good of the other, it reconstructs how both authors interpret love’s erosion as a structural feature of modern capitalism and liquid modernity. At the same time, the article suggests that their analyses also illuminate the conditions under which love can still operate as a civic and solidaristic force, capable of resisting consumerist logics, sustaining caring practices and re-opening spaces of recognition, responsibility and social bonding. In this sense, Bauman’s and Fromm’s reflections help us understand not only the contemporary breakdown of real human relationships but also the ambivalent role of love in the making and unmaking of the social. In Bauman’s and Fromm’s work, the critique of contemporary forms of love does not simply describe an inevitable moral decay, but rather highlights the conditions under which love is deprived of its social and civic potential and contributes to the “expulsion of the Other”. Full article

Synergistic pollution reduction and carbon mitigation (SPRCM) is a critical pathway for advancing global climate governance and promoting green and low-carbon transitions. It also represents an important practice for strengthening ecological civilization and achieving regional sustainable development in China. Based on panel data from 31 Chinese provinces during 2010–2024, this study employs an improved entropy-weighted TOPSIS method to measure SPRCM levels and integrates a modified gravity model, social network analysis, and the CatBoost-SHAP explainable machine learning approach to examine its spatiotemporal evolution, spatial network structure, and nonlinear association characteristics. The main findings are as follows. First, China’s overall SPRCM level shows a gradual upward trend, while significant regional disparities remain. Second, the interprovincial spatial association network has gradually evolved toward a polycentric structure and exhibits clear hierarchical characteristics. Although network connectivity has continuously improved, linkages between core and peripheral provinces remain relatively weak. Third, individual network characteristics display distinct regional differentiation. Eastern coastal provinces consistently occupy core network positions, whereas northeastern and some western provinces remain relatively peripheral. Fourth, the block model analysis identifies four functional groups within the network: net beneficiaries, net spillovers, brokers, and two-way spillovers. These blocks play differentiated roles in spatial association and network interactions. Fifth, the CatBoost-SHAP analysis indicates that road density, freight volume, and human capital are the most important variables in explaining model predictions, with their combined mean absolute SHAP importance accounting for 54.59%. Moreover, these factors exhibit significant nonlinear association patterns with predicted SPRCM levels. Full article

Lebanon is currently going through a multi-faceted crisis with what appears to be an unrelenting cycle of economic and banking defaults, unstable infrastructure, market uncertainty, and difficult working conditions for employees who are trying to support the economy. This study examines whether opportunities for human capital development in SMEs are associated with less work–family conflict and higher employee productivity and well-being in turbulent times. Furthermore, the study investigates whether technostress and coping mechanisms moderate the association between work–family conflict and employee outcomes. Data were collected through a quantitative cross-sectional survey targeting 207 employees working for SMEs in Lebanon and analyzed using PLS-SEM. Results indicated that human capital development opportunities were negatively associated with work–family conflict and that work–family conflict was, in turn, negatively associated with employee productivity and well-being. Further, technostress and coping mechanisms moderated the negative association between work–family conflict and employee outcomes. From a theoretical perspective, this research offers an integrated framework that synthesizes organizational, technological, and psychological dimensions within the SME context during times of crisis. From a practical standpoint, these associations may help inform how Lebanese SMEs approach workforce development, digital-work management, and coping-support practices. Full article

Small and medium enterprises all over the world are facing challenges associated with sustainability. In the United Kingdom the government is highly concerned about sustainability and has made special laws which create several challenges. The purpose of this study is to identify the role of skilled human capital in achieving sustainable performance of small and medium enterprises. Moreover, considering the environmental challenges, small and medium enterprises need to change their strategies on a continuous basis. Additionally, considering the inconsistencies in the literature regarding the relationship between skilled human capital and sustainable performance of small and medium enterprises, adaptive strategy is added to the framework. The resource-based view of firms provides theoretical support for this research. To support the mediating role of adaptive strategy, we integrate the dynamic capability view with the resource-based view. Although the mediation is partial, it is significant and cannot be ignored. For evaluating the framework, the data have been collected from 384 small and medium enterprises operating in the main cities of the United Kingdom using convenience sampling. The results confirmed the direct relationship between skilled human capital and sustainable performance of small and medium enterprises. Likewise, adaptive strategy partially mediates the relationship between skilled human capital and sustainable performance of small and medium enterprises. The research adds several practical and theoretical implications for academics as well as practitioners. The study ends up with limitations and recommendations for the future studies. Full article