Search Results (131)

This study explores the role of solidarity finance in promoting local development and the empowerment of marginalized communities through financial inclusion and access to community credits. It focuses on how solidarity-based financial mechanisms provide accessible credit with fewer barriers, fostering productive activities and economic resilience. This study employed a quantitative and exploratory design, analyzing data from 51 community funds in Ecuador out of a total of 220 through a self-administered online survey, validated by auditing professionals and answered by community representatives. The 25-item questionnaire gathered data on organizational dynamics, financial practices, and perceptions of sustainability. Descriptive analysis was complemented with an analysis of variance to test hypotheses concerning associativity, self-management, and organizational performance. The results show that while associativity, self-management, and organizational management are perceived as institutional strengths, aspects such as autonomy and solidarity received lower evaluations, suggesting critical areas for strategic improvement. Notably, significant differences emerged between self-management–organization and solidarity–organization groups, emphasizing the importance of associativity (collaboration) in enhancing the sustainability of solidarity finance, which proves to be a vital mechanism for community empowerment and local development; however, its long-term sustainability depends on strengthening internal dimensions, particularly autonomy and solidarity, and reinforcing associativity as a core driver of organizational resilience. Full article

This study explores the application of spiking neural networks (SNNs) for click-through rate (CTR) prediction in personalized online advertising systems, introducing a novel hybrid model, the Temporal Rate Spike with Attention Neural Network (TRA–SNN). By leveraging the biological plausibility and energy efficiency of SNNs, combined with attention-based mechanisms, the TRA–SNN model captures temporal dynamics and rate-based patterns to achieve performance comparable to state-of-the-art Artificial Neural Network (ANN)-based models, such as Deep & Cross Network v2 (DCN-V2) and FinalMLP. The models were trained and evaluated on the Avazu and Digix datasets, using standard metrics like AUC-ROC and accuracy. Through rigorous hyperparameter tuning and standardized preprocessing, this study ensures fair comparisons across models, highlighting SNNs’ potential for scalable, sustainable deployment in resource-constrained environments like mobile devices and large-scale ad platforms. This work is the first to apply SNNs to CTR prediction, setting a new benchmark for energy-efficient predictive modeling and opening avenues for future research in hybrid SNN–ANN architectures across domains like finance, healthcare, and autonomous systems. Full article

Employees’ green voice behavior (GVB), as a specific category of extra-role green behavior, plays a vital role in promoting a firm’s sustainable development. However, its underlying mechanism has not been sufficiently explored. Drawing on social learning theory (SLT), this study proposes a research model that examines the indirect influence of environmentally-specific transformational leadership (ESTFL) on GVB via psychological empowerment (PE) and ecological reflexivity (ER) as well as the moderating role of person-supervisor value congruence (PSVC). To achieve the research goals, we conducted a two-wave online survey via the convenience sampling method to collect data from 530 employees and 106 direct supervisors working in the manufacturing, hospitality and service, energy production, construction, transportation, information and communication, and finance industries in China. Regression analyses and CFA based on SPSS and Mplus were employed to test and validate the research model. Our findings show that PE and ER both partially mediated the positive association between ESTFL and GVB. Moreover, PSVC moderated the mediating effects of ESTFL on GVB via PE and ER. This study advances empirical research regarding how leadership impacts GVB by revealing dual cognitive mechanisms and identifying its boundary condition. It also offers managerial implications for leaders and enterprises in China to promote employees’ GVB and improve sustainable management. Full article

As digital connectivity transforms financial decision-making, this study offers one of the first empirical investigations into the relationship between social media use and socially responsible investing (SRI). Using data from the 2021 National Financial Capability Study, multinomial regression analysis was used to explore whether people who rely on social media for investment decisions were more likely to invest in ways that reflect their values. The results show that investors who use social media for investment information are more likely to value being socially responsible as an important reason for investing. Younger, less experienced, and more risk-tolerant investors were especially likely to follow SRI strategies, and certain platforms like Twitter were more associated with SRI interest than others. These findings suggest that social media is not just a platform for sharing information; it may also shape how people think about investing and the role their money can play in making a societal difference. As online platforms continue to influence financial behavior, understanding their impact on values-based investing becomes increasingly important. This research contributes novel insights to the emerging intersection of social media, behavioral finance, and values-driven investing. Full article

Weeds cause significant yield and economic losses by competing with crops and increasing production costs. Compounding these challenges are labor shortages, herbicide resistance, and environmental pollution, making weed management increasingly difficult. In response, precision weed control (PWC) technologies, such as robots and unmanned aerial vehicles (UAVs), have emerged as innovative solutions. These tools offer farmers high precision (±1 cm spatial accuracy), enabling efficient and sustainable weed management. Herbicide spraying robots, mechanical weeding robots, and laser-based weeders are deployed on large-scale farms in developed countries. Similarly, UAVs are gaining popularity in many countries, particularly in Asia, for weed monitoring and herbicide application. Despite advancements in robotic and UAV weed control, their large-scale adoption remains limited. The reasons for this slow uptake and the barriers to widespread implementation are not fully understood. To address this knowledge gap, our review analyzes 155 articles and provides a comprehensive understanding of PWC challenges and needed interventions for scaling. This review revealed that AI-driven weed mapping in robots and UAVs struggles with data (quality, diversity, bias) and technical (computation, deployment, cost) barriers. Improved data (collection, processing, synthesis, bias mitigation) and efficient, affordable technology (edge/hybrid computing, lightweight algorithms, centralized computing resources, energy-efficient hardware) are required to improve AI-driven weed mapping adoption. Specifically, robotic weed control adoption is hindered by challenges in weed recognition, navigation complexity, limited battery life, data management (connectivity), fragmented farms, high costs, and limited digital literacy. Scaling requires advancements in weed detection and energy efficiency, development of affordable robots with shared service models, enhanced farmer training, improved rural connectivity, and precise engineering solutions. Similarly, UAV adoption in agriculture faces hurdles such as regulations (permits), limited payload and battery life, weather dependency, spray drift, sensor accuracy, lack of skilled operators, high initial and operational costs, and absence of standardized protocol. Scaling requires financing (subsidies, loans), favorable regulations (streamlined permits, online training), infrastructure development (service providers, hiring centers), technological innovation (interchangeable sensors, multipurpose UAVs), and capacity building (farmer training programs, awareness initiatives). Full article

Green innovation, which promotes the coordinated development of the economy and ecology, serves as a critical means to achieve enterprises’ green transformation. Against the backdrop of the Internet era, retail investors, as an important supervisory group for enterprises, can generate online public opinion through interactive exchanges on social media platforms. This raises the question: Can such public opinion rooted in social media influence enterprises’ green innovation behaviors? To address this, this study uses data from Chinese A-share listed enterprises in heavily polluting industries on the Shanghai and Shenzhen Stock Exchanges from 2008–2021, comprising a total sample size of 8755, and employs ordinary least squares (OLS) regression models to empirically examine the relationship between retail investors’ social media interactions and enterprise green innovation. The findings reveal that interactive discussions by retail investors on social media significantly enhance enterprises’ green innovation levels. Mechanism tests show that social media interactions among these investors strengthen enterprises’ environmental awareness and alleviate their financing constraints, thereby promoting green innovation. Moderation effect tests indicate that the quality of social media information interaction and public opinion sentiment positively moderate the relationship between retail’s social media interactions and enterprise green innovation. Heterogeneity tests further show that the positive effect of retail’s social media interactions on enterprise green innovation is more pronounced in regions with stronger environmental information regulation and stronger investor protection. The conclusions of this study not only enrich research on the relationship between retail investors’ social media supervision and enterprises’ behavioral decision-making but also extend the literature on the influencing factors of enterprise green innovation from the perspective of public governance. These findings hold important implications for enterprises’ green transformation practices under the “double carbon” goals and provide valuable insights for corporate governance in the era of the digital economy. Full article

Digital inclusive finance (DIF) is regarded as a key instrument in poverty alleviation efforts. However, existing research reveals significant gaps in understanding its poverty-reduction impact: the debate on its inclusivity remains unresolved, its mechanisms of action are unclear, and the psychological empowerment dimension has been largely overlooked. Using micro-level data from seven waves of the China Family Panel Studies (CFPS) from 2010 to 2022, this study employs fixed-effect models, quantile regression models, and mechanism analysis to explore the differentiated impact of digital inclusive finance on rural multidimensional relative poverty and the mechanisms at play. The empirical findings reveal that DIF significantly mitigates multidimensional relative poverty, with more pronounced marginal effects among the poorest households, confirming its pro-poor characteristics. Heterogeneity analysis reveals that, at the regional level, DIF has greater impacts in western regions and remote rural areas farther from county centers; at the individual level, it is particularly effective for women, those with lower education, and individuals with limited digital literacy. Mechanism analysis shows that DIF operates through three channels: promoting employment, encouraging entrepreneurship, and enhancing financial accessibility. Moreover, extended analysis demonstrates that DIF also fosters the endogenous motivation of rural households to escape poverty, as reflected in heightened confidence about the future, increased belief in social mobility and returns of work, and reduced perceived barriers to employment. These findings provide new micro-level evidence to unpack the poverty-alleviation potential of DIF. Full article

In the evolving landscape of fandom economics, fan-driven crowdfunding has emerged as a powerful force, transforming audiences from passive consumers into active participants in celebrity branding. This study examines the roles of trust, loyalty, and perceived value in shaping crowdfunding participation within Chinese Weibo K-pop communities, where fans collectively finance large-scale public advertisements for their idols. Using structural equation modeling (SEM) on survey data from 260 participants, our findings reveal that trust and loyalty within fan communities significantly enhance engagement in crowdfunding activities, reinforcing perceived idol value and financial commitment to promotional campaigns. These insights position fan crowdfunding as a key driver of digital-era consumer culture, illustrating its impact on idol branding, online community dynamics, and the monetization of fandom engagement. By bridging fandom studies, digital marketing, and behavioral economics, this research provides theoretical advancements and practical strategies for entertainment agencies and celebrity managers seeking to harness the economic power of fan-driven marketing. As fandoms continue to reshape traditional advertising models, understanding the mechanisms behind community-based crowdfunding offers new avenues for brand engagement, audience monetization, and sustainable fan participation in the global entertainment industry. Full article

Background: Precision medicine (PM) considers the genetic variability of individuals to identify tailored diagnosis and treatments. It relies on the possibility of gathering the widest possible health data and genetic information from individuals to obtain a broad pool of comparative data. To achieve this goal, the Region of Valle d’Aosta, since 2019, has co-financed the research center CMP³VdA, aiming to sequence 5000 genomes of patients with neurodevelopmental, neurodegenerative, oncological, and organ transplantation diseases, and to investigate the genetic variability of the resident population. Methods: This paper presents the results of an online survey of 472 (328F) respondents regarding willingness to participate in the genomic project and awareness, attitudes, and concerns about PM. Results: The main results show that the vast majority (92.6%) would be willing to participate—a higher percentage than in previous studies. Age, education, and prior experience in the healthcare sector are significant factors influencing the awareness of PM. Additionally, subgroups organized by age, gender, and religiosity show significant differences with respect to participants’ reasons for participating in research and which types of biological samples they would be willing to donate. Conclusions: Our findings can serve as a guide for stakeholders—particularly policymakers—to target institutional communication and achieve maximum participation in genomic research projects. Full article

Waste is a complex challenge that requires collaboration between multiple stakeholders to achieve a circular economy. In this context, there is a growing demand for digital solutions that integrate physical and digital infrastructure to create digital waste governance systems. Analog management, without accurate data, is becoming increasingly unfeasible in light of the UN Sustainable Development Goals. Tools such as online geographic information systems (WebGIS) allow the collection and integration of large volumes of physical and human data and the establishment of a digital governance structure that brings together different technologies, tools and methods in the same environment. This article aims to present the State of the Art on the topics of zero-waste cities, WebGIS, and disruptive innovation. The article starts from the hypothesis that only a process of disruptive and systemic innovation in the value chain and urban solid waste management (MSWMS), supported by the principle of zero-waste cities, circular economy and webGIS, can effectively help to solve this problem. The research uses an exploratory literature review on the concepts of zero-waste cities, systemic innovation and webGIS applied to waste management, linking them to the theoretical framework of sustainability as a science and to Brazilian public policies, such as the National Solid Waste Policy (Law 12.305/2010), the National Circular Economy Policy (Law 1.874/2022) and the National Digital Government Strategy of Brazil 2024–2027 (ENGD). As a result, scientific publications on zero-waste cities increased from 2018 to 2023 and several countries have adopted zero-waste guidelines in waste management policies. WebGIS, remote sensing, geoprocessing and different technologies are increasingly being incorporated into waste management, generating significant impacts on the diversion of resources from landfills, mitigating climate change, and generating and/or adding value to the useful life of waste and garbage resources, in addition to the optimization and efficiency of collection operators and citizen engagement in public policies. Disruptive innovation has proven to be a concrete process to enable the transition from obsolete sociotechnical systems (such as the linear economy), where sustainable finance and environmental entities play a fundamental role in orchestrating and coordinating the convergence of private, public and civil society actors towards this new sustainable development paradigm. The case study proved to be fruitful in proposing and encouraging the adoption of such methods and principles in municipal waste management, allowing us to outline a first conception of a digital government structure and digitalization of public services for zero-waste cities, as well as pointing out the difficulties of implementing and transforming these systems. This digital governance structure demonstrates the possibility of being replicable and scalable to other cities around the world, which can materialize an important tool for the implementation, articulation and development of a long-term sustainable development paradigm, based on the vision of the circular economy and zero-waste cities. Full article

Background/Objectives: Diagnosis-related group (DRG)-based financing, a subcategory of case-based payment models, has been established as the primary reimbursement scheme in most high-income countries. Almost 40 years thereafter, the impact of the reform on gynecologic oncology funding and recompensation has not been clearly elucidated. This systematic review aims to address the scarce bibliographic data, consolidate the information regarding DRG-based systems in gynecologic oncology, evaluate the advantages and challenges of its implementation worldwide, and examine alternative and complementary recompensation schemes in this context. Methods: A stringent and comprehensive literature review of original articles using online databases (Google Scholar and Pubmed) yielded 173 potential results. Results: These were further assessed for relevance and eligibility and, finally, an in-depth investigation of 15 articles was conducted. We concluded that, despite the fact that DRG-based financing may be beneficial in most healthcare scenarios, the reimbursement scheme is challenged in the context of gynecologic oncology. Conclusions: An innovative approach comprising a combination of the values of case-based and value-based payment models would extend healthcare services beyond acute treatments and propose new perspectives in holistic healthcare provision in a financially sustainable environment. Full article

This article examines energy audit procedures as a crucial instrument for raising building and business energy efficiency in European Union (EU) Member States. Energy audits, which include technical, economic, and environmental aspects, are essential to reaching the EU’s climate targets, which include increasing energy independence and cutting emissions by 55% by 2030. The study highlights how crucial energy efficiency initiatives are to combating climate change, cutting energy use, and advancing sustainable development. A thorough examination of methods, financing sources, and legislative frameworks reveals differences in how Member States carry out directives such as the Energy Performance of Buildings Directive and the Energy Efficiency Directive. A case study on Latvia is included in the article, highlighting the country’s energy audit regulations, implementation difficulties, and successes. This study applied a bibliographic methodology or review of the scientific and other relevant literature, analyzing sources identified through targeted keyword searches in academic databases and a variety of online sources, including official legal websites, handbooks, reports, plans, and other publicly available digital resources. The integration of energy efficiency principles and country performances are compared using data from the Odyssee and Mure databases. The results highlight how important it is to standardize energy auditing practices, promote information sharing across national borders, and move past obstacles like public resistance and budgetary limitations. Policy recommendations to improve energy efficiency and aid the EU’s transition to climate neutrality by 2050 are included in the research’s conclusion. Full article

The continued rise in SMEs’ corruption-related activities results in uncertainty around their ability to sustainably contribute to economic growth, leaving SMEs financially fragile and exposed to problems associated with trade credit management resulting in business exits. Given that little research has been conducted on how corruption affects smaller businesses while corruption’s impact on SMEs’ trade credit management effectiveness remains largely unexamined, the study aims to determine the impact of corruption on SMEs’ trade credit management effectiveness. By addressing this unanswered research gap, SMEs could be better equipped to understand how corruption affects their trade credit management in support of their overall finances. The study employed a quantitative research design with purposive sampling using a survey by administrating 10450 online questionnaires tested by a sample of 450 SMEs across South Africa. The result aligns with expectations around corruption being detrimental to SMEs’ trade credit management effectiveness while also indicating, unexpectedly, SMEs’ willingness to partake in corruption, given that SMEs benefit from increased effectiveness in managing trade credit. The study adds to the existing literature on corruption and SMEs’ trade credit management while also providing anti-corruption recommendations to SMEs that are dependent on trade credit. In so doing, SMEs could be better equipped to understand how corruption affects their trade credit management to support their overall finances contributing to improved SME creation rates and fostering entrepreneurship as a pivotal mechanism for improving South Africa’s sustainable development goals. Full article

This study examined the influence of cognitive biases on financial literacy test outcomes across four generational groups: Gen Z, Millennials, Gen X, and Baby Boomers. Using the National Financial Capability Test and an online in silico experiment, we analyzed how cognitive biases influence the likely responses of each generation. The results indicate that the current test format aligns more closely with Baby Boomers, who are less affected by certain biases but tend to exhibit resistance to new financial strategies. A key contribution of this research is the identification of generational bias profiles and actionable recommendations for tailoring financial literacy assessments to reflect these differences. Our approach not only advances behavioral finance literature but also introduces innovative methodology through AI-driven simulations, providing a replicable framework for exploring cognitive influences in decision-making. The findings underscore the need for tailored financial education programs that consider these cognitive biases, aiming to foster unbiased financial decision-making across age groups. Full article

While entrepreneurship continues to gain significance worldwide as a means for economic development and a tool for youth employment, coffee cultivation entrepreneurial intention becomes an essential goal to investigate and a necessary instrument. Accordingly, this research investigates the role of external factors, namely Access to Finance (ATF), Structural and Institutional Support (SIS), Physical Infrastructure Support (PIS), Social Influence (SIF) and Education and Training (ET), in stimulating Coffee Farming Entrepreneurial Intention (CFEI) among potential entrepreneurs (students). A sample of 318 participants from various universities in Saudi Arabia responded to an online questionnaire, forming the basis for analysis using Partial Least Squares-Structural Equation Modelling (PLS-SEM). The study reported different findings, such as a positive relationship between CFEI and other factors, namely PIS, SIF and ET. However, the study found no positive connection between ATF, SIS and CFEI. The study concluded by providing actionable recommendations for policymakers about stimulating coffee farming among students and contributing to the economic development process and youth employment. It also assists in the establishment of sustainable business environments for future generations. Full article