Abstract: This article examines the growing inadequacy of Gross Domestic Product (GDP) as a measure of human progress in a world shaped by ecological fragility, socio-technical transformations, and civilizational transitions. While GDP served as a convenient post-war metric for national accounting, it now obscures critical dimensions of wellbeing, including ecological sustainability, relational capabilities, and systemic resilience. Drawing from complexity economics, relational sociology, and post-growth political economy, the article proposes a renewed understanding of value as emergent, interconnected, and ecologically embedded.Complexity economics demonstrates that economies are not linear production machines but adaptive systems shaped by feedback loops, cooperation, and innovation. Relational perspectives from Sen, Nussbaum, and Appadurai highlight capabilities, agency, and aspiration as fundamental components of wellbeing beyond monetary aggregates. Post-growth scholarship—including recent contributions from Hickel, Raworth, and Stiglitz—calls for civilizational metrics aligned with planetary boundaries and distributive justice.The article synthesizes these paradigms to propose a multidimensional framework integrating ecological boundaries, relational wellbeing, and systemic capabilities. Special attention is given to Africa and the Global South, where informal economies, urban complexity, and community resilience constitute fertile ground for post-GDP experimentation.Overall, the analysis argues that moving beyond GDP is not merely a technical adjustment but a civilizational shift toward a regenerative, capability-enhancing, and complexity-aware understanding of prosperity fit for the twenty-first century.

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The research focused on Sustainable Development Goal 8, which promotes decent work and economic growth, by studying theories related to determining the profile of online shoppers. The overall objective was to determine the characteristics of the digital consumer profile and the segments to which digital customers of optical stores in Chimbote belong in 2025. The research was applied, with a quantitative approach, a non-experimental design, and a descriptive-correlational level. The population consisted of 1,800 customers from 2024, with a sample of 317 customers. Simple random sampling was used to obtain data through a survey. The results showed the existence of five segments based on the profiles found: exclusive aesthetics, natural aesthetics, whimsical aesthetics, practical naturals, and traditional naturals. This was corroborated by the hypothesis test, where the resulting p-value of 0.018 was less than 0.05, confirming the existence of digital consumer profile characteristics according to the segments to which the digital customer belongs. In conclusion, the data obtained made it possible to determine the main characteristics that define the profiles of digital consumers in the optical sector of Chimbote.

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This research conducts a systematic review of Tunisian stakeholders' perceptions of green finance, microfinance, and gender through the lens of the Business Model Canvas (BMC). Within this framework, a systematic search was conducted until October 2024 in electronic databases and grey literature. The findings indicate a dual perception of women as both vulnerable victims and active agents in the ecological transition. The BMC analysis reveals major weaknesses in the value proposition, distribution channels, and cost structures of gendered green microfinance offerings. The study highlights the crucial role of the regulatory and institutional context in these perceptions. It proposes an updated conceptual framework for thinking about more inclusive and sustainable green microfinance models.

Abstract: The rapid advancement in Artificial Intelligence (AI) has dramatically impacted the field of marketing, by allowing companies to interact with their customers through automation, to optimize marketing campaigns, and to make better decisions in marketing; yet, there are still many challenges that small businesses face when considering AI-based marketing solutions due to limited resources, capability gaps, and uncertainty about the benefit of using AI in marketing. This review is a synthesis of recent academic research on the adoption of AI-based marketing tools among small businesses in order to identify the key barriers and enablers of adoption. Using existing models of technology acceptance and use, such as the Technology Acceptance Model (TAM), Unified Theory of Acceptance and Use of Technology (UTAUT), and Resource-Based View (RBV), this review found that the adoption of AI-based marketing tools is influenced primarily by how useful a company perceives the tool, whether or not the costs of the tool outweigh the benefits, whether or not a company has the necessary knowledge to implement and use the tool, and whether or not a company trusts the tool to perform as promised. Additionally, incorporating industry-specific information highlighted the importance of third party service providers and developing capabilities to help support the adoption of AI-based marketing tools. This review also presents an integrative conceptual model of the relationships between the technological aspects of AI-based marketing tools, the organizational aspects of a company, the environmental aspects of a company, and the human aspects of a company, and provides a comprehensive way of viewing the adoption of AI-based marketing tools that can be used by both researchers and practitioners.

Abstract: The Role of Artificial Intelligence (AI), Internet of Things (IoT), and Blockchain in Augmented Finance Augmented finance is emerging as an important approach to tackle the complex financial challenges that accompany climate change. This systematic review aims to provide existing research, identifying how these technologies may help in sustainable finance. Thus, following the PRISMA guidelines, we reviewed and analysed 42 peer-reviewed studies released between 2018 and 2025. Our results are applicable in three general areas: (1) increased MRV of the environmental impacts by employing IoT and blockchain, to ensure transparency and traceability, (2) better physical and transition risk control using predictive AI modelling and (3) better ESG analysis and the detection of greenwashing and risk reduction via alternative data. We highlight the power of these technologies to address stubborn problems such as information asymmetry and transparency holes in impact chains. However, significant challenges persist, such as algorithmic bias, difficult data governance, and regulatory lag. The present study contributes to this landscape by offering a scientific framework of augmented finance in a climate context. It also suggests a proposed future research agenda with emphasis on impact assessment, algorithmic transparency, and impact on financial stability.

Abstract: Although AI is widely believed to have transformative potential in organizations, recent reports reveal that many organizations are grappling with value derivation therefrom and the ability to take ownership of due ethical and regulatory demands, among other responsible uses of technology. Our goal is to examine these challenges with a view to proposing an approach to effective AI adoption by organizations and pave the way for further impact studies. As a first step, we reviewed and clarified these challenges, categorizing them into Weak or Non-Existent Strategy, Poor Data Readiness and Privacy Concerns, Inadequate Integration with Existing Technology Stack, Inadequate Human Knowledge Skills and Attitudes/Abilities, Scalable and Secure Infrastructure Challenges, Ethical Governance Concerns, Regulatory Framework Lag, Responsibility and Accountability Concerns as well as Reliability Concerns. Next, we carried out a thematic review of constituent AI technology innovation concepts and tools that have adoption potential in organizations vis-à-vis Enterprise Resource Planning (ERP). In the light of these reviews, we used inductive reasoning to propose an approach to AI adoption and create a tool (OAAD) that exemplifies our recommendations, and which could facilitate well-informed adoption and real-life impact research. To set a compass for our effective adoption approach proposal, we expanded on Yang et al. (2024) and defined organizational AI readiness as the organization’s capacity and disposition to deploy and use AI technology tools in ethical, responsible and accountable ways that add value to the organization. Finally, we make some recommendations for progressive impact studies in line with our proposed adoption experimentation.

Abstract: This study examines the working capital management efficiency of Türkiye’s forestry and logging sector over the 2009–2024 period using the index method developed by Bhattacharya (1997). The analysis utilizes sector balance sheet and income statement data published by the Central Bank of the Republic of Türkiye. Performance, utilization, and efficiency indexes were calculated to assess both the effectiveness of investments in current asset subcomponents and the degree to which these assets support sales growth. Results indicate that, despite fluctuations observed during certain years, the average values of all three indices for micro-scale, small-scale, and overall sectoral groups exceeded 1 over the study period, suggesting that enterprises in this sector generally managed their working capital efficiently. The highest index levels were reached in 2022, largely driven by a sharp increase in net sales relative to current assets. A comparison with existing research on wood products, paper, and furniture manufacturing sectors demonstrates that the forestry and logging sector exhibits relatively higher working capital efficiency, suggesting a stronger capability to maintain liquidity and support operational performance under changing economic conditions. Given the scarcity of prior research applying the index method to this sector, the study contributes new empirical evidence and demonstrates the suitability of index-based efficiency measurement for sector-level financial data. The results also suggest several implications: enterprises should reinforce cash-flow forecasting, improve monitoring of current asset subcomponents, and adopt scale-appropriate working capital policies. Policymakers may consider supporting micro- and small-scale companies through financial training initiatives and improved access to short-term credit instruments. Future research could incorporate firm-level datasets, expand coverage to medium and large enterprises, and apply alternative efficiency techniques to further validate and extend the findings.

Abstract: This article examines how fintechs and payment institutions in emerging markets have been used as parallel banking infrastructures that facilitate tax evasion, large-scale money laundering and regulatory arbitrage. Focusing on Brazil, it analyzes recent high-profile investigations—such as the Carbono Oculto, Tank and Quasar operations—to show how criminal organizations exploited payment institutions, digital accounts and card schemes to move value outside the visibility of traditional banks and supervisory authorities. The study employs a qualitative, document-based approach, drawing on official reports, judicial decisions, supervisory guidance and financial intelligence materials to map the architecture of fintech-enabled illicit finance. The findings show that fintechs and payment institutions provided anonymity, opacity and transactional mobility through fragmented regulatory perimeters, lighter reporting requirements and gaps between financial, tax and AML/CFT oversight. These blind spots allowed parallel banking structures to operate at national scale while remaining formally within the legal financial system. The article contributes by proposing an integrated conceptual framework for understanding fintech-enabled parallel banking in emerging markets and by outlining policy recommendations to close supervisory gaps, align reporting obligations across institutions and strengthen cooperation between financial regulators, tax authorities and law-enforcement agencies.

Abstract: This study empirically investigated the relationship between digital advertising strategies and the marketing performance of deposit money banks in Rivers State. The study adopted the quantitative research methodology and quasi-experimental research design method through cross-sectional survey design. The population comprised nineteen (19) listed deposit money banks operating in Rivers State. One hundred and twenty-seven (127) questionnaires were distributed; one hundred and nineteen (119) were fit for analysis. Face and content validity and Cronbach's Alpha were used to measure the validity and reliability. All were fit for the analysis. The Pearson Product-Moment Correlation and Partial Correlation tools were adopted with the aid of Statistical Package for Social Sciences (SPSS version 23.0). The findings of the study showed that social media advertising was significantly related with the marketing performance of deposit money banks in Rivers State; e-mail advertising significantly related with marketing performance of deposit money banks in Rivers State; pop-up advertising significantly related with marketing performance of deposit money banks in Rivers State and mobile-based advertising significantly related with marketing performance of deposit money banks in Rivers State. Based on the findings, the study concluded that digital advertising strategies (social media advertising, e-mail advertising, pop-up advertising, and mobile-based advertising) have a positive and significant impact on marketing performance (brand awareness and customer engagement) of deposit money banks in Rivers State. The study thus recommended that deposit money banks should ensure that their E-trade channels command trust in such a way that customers can effectively transact business through such channels without being defrauded. It must be proven at all instances by these deposit money banks that their social media channels are reliable; this must be guaranteed by providing customers with 24-hour information about their offerings.

Abstract: Capital mobilization is often portrayed as the main bottleneck to decarbonization in emerging economies, yet BRICS countries struggle to scale clean energy even when funding is formally available. This paper argues that capital is a necessary but insufficient condition for the energy transition in the BRICS because institutional fragility creates binding financial barriers. Drawing on a comparative, document based analysis of Brazil, Russia, India, China and South Africa, the study synthesizes academic literature, international reports and policy documents on clean energy investment, governance and financial systems. It develops a conceptual framework linking political and regulatory risk, fiscal constraints and the role of public development banks to the cost and allocation of capital for low carbon projects. The analysis highlights common patterns—such as high perceived country risk, policy instability and weak project pipelines—that raise the cost of capital and deter private investment, as well as country specific institutional configurations that condition outcomes. The paper concludes that improving governance, policy credibility and the design of public financial institutions is as important as mobilizing new capital, and discusses implications for climate finance strategies and future research on the political economy of the energy transition in emerging markets.

Abstract: Losses resulting from the opportunistic use of insider information are detrimental, and therefore it is essential to mitigate this behavior through robust corporate governance practices. This research analyzes the determinants of corporate governance that reduce the signs of opportunistic insider trading, considering the assumptions of information asymmetry and opportunistic behavior. The hypotheses formulated consider that compa-nies listed on the Novo Mercado or Level 2 of Corporate Governance, with independent Boards of Directors and greater female representation, active Fiscal Councils, consolidated ESG practices, non-family firms, robust Audit Committees, and audits not linked to the Big Four, tend to show a lower propensity for opportunistic conduct. 237 firms were analyzed, representing 51% of the firms listed on the [B]3 between 2010 and 2021, with 2,175 obser-vations. The panel data analysis confirmed the proposed hypotheses. Therefore, the theo-retical conclusion is that the greater the level of corporate governance practices, the lower the incidence of opportunistic insider trading in the Brazilian capital market. This work contributes to the literature by highlighting the unique characteristics of the largest stock market in Latin America and emphasizing the importance of transparency, formal moni-toring, and informal mechanisms, such as social and reputational pressure on insiders, in-fluencing ethical behavior, and restricting the misuse of privileged information.

Abstract: Purpose This study develops a conceptual model explaining how home-service businesses (e.g., plumbing, HVAC) adopt AI-driven lead-generation automation. While new tools abound, adoption among small firms remains low. This study uses behavioral, technological, and organizational perspectives to describe both adoption and performance outcomes.Design/Methodology/Approach This conceptual paper combines technology adoption theories (TAM, UTAUT, TOE, DOI) with industry findings. It proposes a framework linking owner attitudes, risk, system quality, vendor support, and resource constraints to performance outcomes like improved lead quality and operational efficiency.Findings The model suggests adoption depends on owner digital self-efficacy, trust, utility, complexity, workflow integration, and vendor support. Successful implementation enables benefits including faster response times, higher booking rates, and improved marketing ROI.Originality/Value This study addresses a significant gap by developing a model specifically for AI lead generation in micro-home-service businesses—an ignored segment. It incorporates behavioral, technological, and performance factors to explain how small service businesses successfully adopt AI.Practical Implications Practitioners and vendors can use this model to identify adoption barriers and design user-friendly AI systems that meet the specific needs of small service businesses.Social Implications Increased AI adoption by small businesses contributes to stronger local economies, job security for the self-employed, and better access to digital markets.

Abstract: This research studied the role of the fisheries sector, in particular pond-based grouper aquaculture in the coastal area of Lamongan, Indonesia, which is crucial for coastal food security and economy. Despite relatively high productivity, technical efficiency was not optimal because of its limited livelihood assets, which include human, natural, social, financial, and physical capital. The gap in ownership of these assets has resulted in technical efficiency variations across farmers and has affected both their livelihoods and environmental sustainability. Previous research has mostly focused on capture fisheries or non-grouper species, leaving a critical gap regarding the linkage between livelihood assets and technical efficiency in pond-based grouper aquaculture. This research measured livelihood asset levels, technical efficiency, and the effect of assets on efficiency, using quantitative data from 83 respondents. Livelihood assets were assessed through scoring and index analysis, technical efficiency was estimated using Stochastic Frontier Analysis (SFA), and the determinants of inefficiency were examined through Tobit regression with robust standard errors. The results found that the average livelihood asset index was 0.47 (moderate), with financial capital being the weakest component. Technical efficiency averaged 0.83, indicating efficient use of inputs while still allowing room for improvement. Natural capital (land area and water resources) and financial capital (income and savings) significantly affected technical inefficiency, whereas human, social, and physical capital did not. These findings emphasize the important to strengthen the financial capital and the management of natural resources optimally to promote the efficiency and sustainability of grouper aquaculture in the coastal area of Lamongan, Indonesia.

Abstract: Background: Soaring drug prices threaten affordability and equity in high-income health systems. This study examines how two families of reform tools, international reference pricing (including the U.S. Most Favored Nation–type proposals and Canada’s PMPRB comparators) and value-based payment approaches, perform across four core policy goals: cost containment, innovation, equity, and implementation feasibility.Methods: Guided by institutional and governance theories, we conducted a structured comparative policy analysis of the United States, Canada, and the United Kingdom using a four-dimensional trade-off matrix. We coded 37 documents (2007–2025), including policy guidance, legislation, and empirical evaluations, to rate each country–instrument pair (1–5) on cost, innovation incentives, equity of access, and feasibility, based on design features rather than realized outcomes.Results: The U.K.’s integrated model, combining NICE’s cost-effectiveness appraisals with the voluntary scheme for branded medicines (VPAG), shows the most consistent alignment across all four dimensions. Canada’s PMPRB-based system achieves strong cost control and broad baseline access but provides weaker, indirect innovation incentives and limited outcome-linked pricing. In the U.S., MFN-type proposals and pharmaceutical value-based contracts face legal challenges, fragmented payers, and limited infrastructure, resulting in low scores on equity and feasibility despite some innovation-supportive features.Conclusions: Neither international reference pricing nor value-based payment alone is sufficient to advance Universal Health Coverage goals. A hybrid approach, anchoring negotiations in international benchmarks while linking reimbursement to therapeutic value, appears more realistic for fragmented systems such as the U.S., but only if accompanied by investments in data, governance, and federal negotiating capacity. The trade-off matrix offers a repeatable framework for assessing pricing reforms and illustrates how institutional “fit,” rather than technical design alone, shapes policy success.

Abstract: Understanding how moral and emotional language operates in paid social advertising is essential for evaluating persuasion and its ethical contours. We provide a descriptive map of Moral Foundations Theory (MFT) language in Meta ad copy (Facebook/Instagram) drawn from seven global beverage brands across eight English-speaking markets. Using the moralstrength toolkit, we implement a two-channel pipeline that combines an unsupervised semantic estimator (SIMON) with supervised classifiers, enforce a strict cross-channel consensus rule, and add a non-overriding purity diagnostic to reduce attribute-based false positives. The corpus comprises 758 text units, of which only 25 ads (3.3%) exhibit strong consensus, indicating that much of the copy is either non-moral or linguistically ambiguous. Within this high-consensus subset, the distribution of moral cues varies systematically by brand and category, with loyalty, fairness, and purity emerging as the most prominent frames. A valence pass (VADER) shows that moralized copy tends toward a negative valence that may still yield a constructive overall tone when advertisers follow a crisis–resolution structure in which high-intensity moral cues set the stakes while surrounding copy positions the brand as the solution. We caution that text-only models undercapture multimodal signaling and that platform policies and algorithmic recombination shape which moral cues appear in copy. Overall, the study demonstrates both the promise and the limits of current text-based MFT estimators for advertising: they support transparent, reproducible mapping of moral rhetoric, but future progress requires multimodal, domain-sensitive pipelines, policy-aware sampling, and (where available) impression/spend weighting to contextualize descriptive labels.

Abstract: : Marine ecotourism and SME digitalization are increasingly seen as key drivers for coastal community welfare, yet their combined impact, particularly through local economic empowerment, remains underexplored. This study addresses this gap by proposing an integrative model to examine how marine ecotourism and SME digitalization influence local community welfare, mediated by SME empowerment, and moderated by government support. A quantitative, cross-sectional survey was conducted with 312 marine tourism entrepreneurs in North Minahasa, Indonesia, and data were analyzed using Partial Least Squares Structural Equation Modeling. The results show that ME and SD have a significant positive effect on SE and LCW. However, ME and SD were found to be insignificant on LCW. Crucially, SE fully mediates the relationship between both ME and SD on LCW, indicating that empowerment is the primary mechanism for welfare improvement. Furthermore, GS was found to significantly strengthen the positive relationship between SE and LCW. This study concludes that empowering local SMEs is the critical bridge for transforming ecotourism and digitalization into tangible community welfare, and this process is significantly amplified by a supportive institutional environment provided by the government.

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This study utilized Scopus to examine patterns in scientific publications, co-authorship, institutional contributions, and shifts in the discipline's primary themes. Analytical techniques such as VOSviewer and Bibliometric have been employed to identify indicators of success and examine the structure of collaborative networks and word matching. They demonstrate that scientific research continues to improve. Contemporary research topics focus on utilizing renewable energy and ensuring environmental protection. Significant efforts are directed towards environmental policies, hybrid designs incorporating green energy, solar energy systems, and eco-friendly business practices. The collaboration network of co-authors highlights the partnership between leading Algerian institutions and experts. Additionally, international researchers are being brought together to collaborate in innovative ways. Although there has been considerable progress, much of the research in this area remains technology-centric. Taxation policies, green finance, closed-loop economies, and governmental procedures have yet to be fully integrated. The study tells us more about what scientists in Algeria know about sustainability and diversity. It also finds areas where scientists from different fields can work together better and suggests future research and policy initiatives that will help the country move towards a more sustainable and diverse economy.

Abstract: The Fourth Industrial Revolution represents a fundamental challenge for organisational leaders attempting to navigate digital transformation successfully. Despite widespread technological advancement, many organisations struggle to convert their digital investments into meaningful business results global failure rates hover between 70-80%. This research explores the leadership approaches that drive successful Industry 4.0 adoption across various sectors and geographies, closing the gap between what organisations can do technologically and what they're actually ready to accomplish. We employed a mixed-methods approach combining quantitative analysis of secondary data from 847organisations across 15 countries with qualitative document analysis of 85 corporate reports and industry publications. Our findings reveal that transformational leadership particularly when leaders articulate clear digital visions and empower their employees correlates strongly with successful adoption (r=0.74, ρ <0.01).Organisations that invest in comprehensive leadership development see 43% higher digital transformation success rates. Three leadership dimensions stand out: digital literacy paired with strategic vision, hands-on change management capability, and the ability to build collaborative cultures. Perhaps most importantly, we discovered that the most successful leaders reverse conventional thinking they devote 70% of transformation resources to developing people and organisational culture, 20% to processes and systems, and only 10% to pure technology.

Abstract: This study examines the major challenges affecting the implementation of the National Poverty Eradication Programme (NAPEP) in Bauchi State, Nigeria. A quantitative descriptive survey design was adopted, and a total of 264 questionnaires were distributed across four selected Local Government Areas. Out of these, 252 were correctly completed and returned, representing a response rate of 95.5 percent. Findings revealed that although 154 respondents (61.1%) participated in NAPEP skill acquisition programmes, several structural barriers continue to hinder successful implementation. The leading challenge identified was inadequate funding, reported by 207 respondents (82%), followed by political interference (194; 77%), poor monitoring and evaluation (174; 69%), insufficient training facilities (161; 64%), and delays in fund disbursement (154; 61%). These constraints significantly weaken programme delivery and limit its capacity to support sustainable youth empowerment. The findings align with Institutional Theory, which highlights how administrative inefficiencies and political interests undermine public-sector interventions. The study concludes that NAPEP’s impact in Bauchi State remains limited primarily due to weak institutional frameworks and inconsistent resource allocation. It recommends strengthening monitoring systems, depoliticizing programme processes, improving training facilities, and ensuring timely funding if NAPEP is to achieve meaningful poverty reduction and long-term youth development.

Abstract: Background— Youth unemployment persists across East Africa despite rapid tertiary-enrolment growth. Many graduates aspire to create ventures, yet student-loan obligations and absent safety nets truncate the time they can afford to experiment. This study tests whether post-graduation income-security instruments furnish an “entrepreneurial runway” that converts intention into business formation. Methods — We assemble a harmonised panel of 25,000 graduates from Kenya, Uganda, and Tanzania (2016-2022), linking higher-education loan-board ledgers, national labour-force surveys, enterprise registries, and UN-Habitat urban indicators. Logistic regressions with cubic-spline and interaction terms estimate the effect of income support—loan-repayment moratoria, stipends, or wage subsidies—on entrepreneurial entry within 24 months, with clustered errors at university level. Results — Receiving any income support raises the odds of launching a venture by 82 % (marginal effect +5.5 percentage points, p < 0.001). The relationship is non-linear: predicted entry peaks at 20 % when support lasts 9-12 months and tapers thereafter, indicating an optimal runway length. Direct stipends outperform loan holidays, while high student-debt burdens and multiple dependents attenuate, and urban opportunity density amplifies the treatment effect. Conclusions — Modest, time-bound income security demonstrably mitigates risk aversion and institutional voids, doubling graduate entrepreneurship across three national contexts. Policies pairing a one-year stipend or grace period with targeted debt relief and rural ecosystem investment could unlock inclusive, innovation-driven growth. Originality/Value — This is the first large-sample, cross-country evidence from Sub-Saharan Africa that quantifies a causal link between graduate income security and venture formation, integrating behavioural, institutional, and human-capital lenses to refine entrepreneurship theory and inform design of cost-effective support programmes.