Search Results (595)

The pervasive integration of artificial intelligence across e-commerce ecosystems has fundamentally transformed the competitive landscape, rendering systematic and reproducible platform evaluation frameworks an operational necessity rather than an academic exercise. Conventional multi-criteria decision analysis approaches for e-commerce evaluation remain structurally constrained by their dependency on human expert panels, which introduce recruitment costs, cognitive biases, limited reproducibility, and the practical infeasibility of assembling genuinely multidisciplinary panels spanning e-commerce strategy, machine learning engineering, and financial technology simultaneously. This study proposes a novel decision support framework that integrates Large Language Model (LLM) multi-agent simulation with the Best–Worst Method (BWM) to derive reproducible priority weights for AI-driven e-commerce platform evaluation within a rigorous business intelligence architecture. Twelve domain-differentiated LLM agents—organized into three expertise groups representing e-commerce management, AI and machine learning technology, and digital payment systems—were instantiated with structured system prompts encoding professional domain knowledge and deployed across three independent simulation rounds to perform BWM pairwise comparisons across a comprehensive six-dimensional, 30-sub-criterion evaluation hierarchy. Inter-agent consensus was synthesized through geometric mean aggregation, with consistency verification conducted via BWM’s xi* indicator and inter-round stability assessed through coefficient of variation analysis. Results reveal that Transaction Security and Trust achieves the highest dimension-level weight (w = 0.248), followed by AI Recommendation Effectiveness (w = 0.213), with Personal Data Protection (G = 0.0750), Recommendation Accuracy (G = 0.0607), and Transaction Transparency (G = 0.0549) emerging as the three highest globally ranked sub-criteria. The aggregated consistency indicator xi* = 0.062 confirms logical coherence of the multi-agent judgment consensus, and all dimension weights exhibit CV values below 2.8%, demonstrating exceptional inter-round stability. Spearman rank correlations among the three domain-expertise groups exceed 0.92, confirming strong inter-group convergence. Sensitivity analysis under perturbations of ±10% and ±20% demonstrates that the top-five priority indicators are structurally stable. This study establishes LLM multi-agent BWM simulation as a methodologically rigorous, institutionally accessible, and computationally reproducible alternative to traditional expert elicitation for complex platform evaluation tasks. Full article

Fintech has become an important driver of digital transformation and sustainable development in the banking industry. However, existing studies report inconsistent findings regarding the relationship between fintech and bank financial performance. This study examines the impact of fintech adoption on the financial performance of Chinese listed commercial banks and investigates the mediating roles of green finance and ESG performance, as well as the moderating role of ownership status. Using panel data from 42 Chinese A-share-listed commercial banks between 2015 and 2024, this study employs panel regression analysis to evaluate the direct, mediating, and moderating relationships among the variables. The results indicate that fintech significantly improves market valuation, operational profitability, and asset utilisation efficiency in Chinese listed commercial banks. In addition, green finance and ESG performance partially mediate the relationship between fintech and financial performance, suggesting that fintech contributes to sustainable financial value creation through sustainability-oriented mechanisms. The findings further show that ownership status significantly moderates the fintech–financial performance relationship, with fintech generating stronger positive effects among non-state-owned banks than state-owned banks. Furthermore, the instrumental variable and other robustness tests confirm the robustness of the findings after addressing potential reverse causality concerns. This paper suggests that the effectiveness of fintech depends not only on technological investment but also on sustainability capabilities and institutional conditions. This study provides empirical evidence on fintech-driven sustainable banking transformation in China and offers practical implications for regulators and commercial banks seeking to promote digital finance and sustainable development. Full article

Background/Objective: The increasing global population of older adults presents significant challenges for oral healthcare, particularly regarding the management of chronic conditions and prosthetic rehabilitation. Teledentistry, combined with intraoral scanning, offers a promising solution to enhance access, interdisciplinary collaboration, and clinical outcomes in geriatric populations. This study aimed to evaluate the utilisation of intraoral digital scanning within teledentistry for interdisciplinary oral assessment of older patients. Specifically, it investigated current clinical practices, collaboration among healthcare professionals, and perceptions regarding the effectiveness, challenges, and future potential of teledentistry in prosthodontic care. Methods: An analytical cross-sectional survey was conducted among 84 healthcare professionals, including dentists, prosthodontists, and postgraduate students, recruited via an international network. Participants completed a 40-item electronic questionnaire covering demographics, clinical practice, digital technology use, interdisciplinary collaboration, and attitudes toward research and innovation. Descriptive statistics summarised responses, and inferential analyses, including chi-square tests and Spearman correlations, examined associations between career stage, technology adoption, and interdisciplinary practices. Results: Early-career professionals demonstrated the highest adoption of intraoral scanning (76.3%), while mid-career adoption was lowest (28.6%). Sustained usage significantly increased after one year of adoption (93.8%). While 91.7% of respondents valued interdisciplinary care, active collaboration remained limited. Cost, technical barriers, and training gaps were identified as primary obstacles. Professionals perceived intraoral scanning as beneficial for prosthodontic outcomes and chronic inflammation management, though adoption was influenced by experience, systemic factors, and financial support. Conclusions: Teledentistry integrated with intraoral scanning has substantial potential to improve geriatric oral healthcare. Successful implementation depends on structured training, financial investment, and promotion of interdisciplinary collaboration. Future longitudinal and multicenter studies are warranted to evaluate clinical, economic, and patient-centred outcomes, supporting sustainable digital transformation in geriatric dental care. Full article

Based on panel data of Chinese A-share listed firms from 2011 to 2023 (29,868 firm-year observations in total), this paper explores the environmental spillover relationship between regional digital financial inclusion (a proxy for the external digital financial ecosystem) and corporate financial investment efficiency. To identify causal effects, we adopt firm fixed effects and three strategies to mitigate endogeneity, namely, interactive fixed effects, lagged terms of regional digital financial inclusion, and instrumental variable estimation. The results suggest that regional digital financial inclusion, when interpreted as an environmental spillover from the external digital financial ecosystem, is associated with curbed inefficient financial investment and thus with improved investment efficiency. This effect operates through three channels: easing financing constraints, improving managerial sentiment, and accelerating digital transformation. Moreover, the positive effect is statistically significant and concentrates among non-state-owned enterprises, firms in eastern China, and sectors with limited traditional financial access (e.g., manufacturing and low-contact industries). Different from prior studies focusing on real investment efficiency, this paper enriches the literature on regional digital financial inclusion from an environmental spillover perspective. It also offers policy implications for fostering sustainable economic growth, strengthening the resilience of the real economy, and improving capital allocation efficiency. Full article

The grocerant represents an emerging hybrid retail–foodservice format integrating grocery shopping, prepared meals, and in-store dining. Although practically significant, the academic literature remains limited and dispersed. This PRISMA-informed semi-systematic review synthesizes 16 studies—including direct grocerant research and adjacent work on retail innovation, prepared foods, and digital food retail—to clarify the current state of knowledge. The review followed structured database searches, citation tracking, title/abstract screening, and full-text eligibility assessment. Three main perspectives emerged. First, consumer-focused studies emphasize customer experience, food healthiness, multidimensional perceived value (functional, hedonic, social, and financial), brand prestige, in-store dining behavior, and loyalty. Second, strategic research positions grocerants within retail format innovation and competitive convergence between grocery and restaurant sectors. Third, operational perspectives link grocerants to prepared-food systems, retail food environments, and omnichannel transformation. Major gaps include limited operational and comparative research, geographic concentration, and weak digital integration. The review suggests that grocerants function as evolving systems where convenience, experience, branding, and digital transformation converge. Full article

This study examines experiential and financial factors associated with Metaverse readiness in Lebanon. Drawing on a socio-technical readiness perspective informed by selected concepts from technology adoption literature, the study explores how interest in immersive technologies, remote work experience, and perceived financial security in decentralized digital assets relate to individual readiness and perceived organizational expectations. Using an exploratory cross-sectional survey of 231 respondents, multiple regression analyses were conducted to examine these associations. The findings indicate that interest in VR/AR technologies and positive remote work experience are positively associated with individual willingness to use the Metaverse for work, education, or professional activities. Perceived financial security in decentralized digital assets is also positively associated with perceived organizational benefit expectations. The results suggest that Metaverse readiness is linked not only to technological interest but also to prior digital collaboration experience and financial trust. By focusing on Lebanon as a developing and crisis-affected economy, the study contributes a context-sensitive and perception-based understanding of readiness for immersive digital ecosystems. Practical implications are discussed for organizations and policymakers seeking to support responsible digital transformation. Full article

Digital technologies provide effective tools for formulating sustainable, evidence-based policies; however, this field has so far lacked a cohesive and practical framework to guide their application. Providing comprehensive answers to six primary research questions, this study aims to address this critical gap concerning the prerequisites, challenges, opportunities, key technologies, policy areas, and critical success factors (CSFs) for applying digital technologies in environmental sustainability policymaking. In this study, 39 articles were analyzed from 293 documents indexed in the Web of Science as of 19 August 2025, in accordance with the PRISMA 2020 guidelines. The prerequisites are categorized into the following themes: fiscal incentives, a culture of innovation and sustainability, effective regulations, robust digital infrastructures, participation, and reliable and accessible data. We identified significant challenges, including financial constraints, human resource deficits, infrastructural and regulatory gaps, and the adverse environmental impacts of digital technologies themselves. Opportunities emerged under two main domains: effective policymaking and enhanced environmental management. Our study indicates that pioneering technologies at the core of this transformation include artificial intelligence, big data, blockchain, the Internet of Things, machine learning, and robots. Their applications are predominant in key policy areas, including the environment, energy, climate change, urban sustainability, agriculture, industry, and food security. The analysis identifies four CSFs: the policy–digital–sustainability nexus, fundamental processes, soft capacities, and hard capacities. Full article

The circular economy (CE) is increasingly recognized as a strategic approach that enables firms to address environmental challenges while enhancing competitiveness and long-term value creation. However, evidence regarding its impact on business performance remains fragmented across sectors, performance dimensions, and organizational contexts. This study presents a systematic literature review conducted in accordance with the PRISMA 2020 guidelines to examine how CE practices influence business performance. The review synthesizes evidence from 79 peer-reviewed publications published between 2015 and 2025. The findings identify five major channels through which CE practices affect business performance: (1) economic, environmental, and social performance, (2) operational and supply chain performance, (3) competitive advantage and strategic positioning, (4) financial and environmental performance, and (5) barriers and performance in SMEs. Across these dimensions, CE practices are frequently associated with improved resource efficiency, cost reduction, innovation capacity, supply chain resilience, and enhanced environmental outcomes, including waste reduction and lower emissions. The review suggests that the performance effects of CE are contingent upon contextual factors such as firm size, ownership structure, industry characteristics, regulatory environment, and digital capabilities. While large firms often benefit from greater resources and organizational capacity, SMEs face significant barriers related to finance, technology, and governance, although these can be mitigated through collaboration networks and digitalization. The study contributes to the Strategic Environmental Management literature by indicating that CE practices may function not only as environmental initiatives but also as strategic capabilities that support competitiveness, resilience, and sustainability transitions. The findings provide implications for managers seeking to integrate circularity into business strategy and for policymakers designing institutional conditions that enable circular business transformation. Full article

Renewable energy sources, such as solar thermal and photovoltaic, geothermal, biomass, hydropower, and wind, offer significant sustainability advantages. Yet the sector still faces difficulties in several areas that tend to reduce the efficiency of these new energy forms. Some of these challenges include inconsistent electricity supply, the diffuse nature of renewable energy sources, which makes them difficult to exploit, and the inconsistent and unpredictable nature of electricity supply, which has repercussions for renewable energy markets. Although Industry 4.0 is inherently energy-intensive, its positive contribution to renewable energy systems may outweigh its costs. Consequently, this study conducts a scoping review on the role of digital technologies in renewable energy systems. It focuses on open-access conference papers, journal articles, and book chapters published between 2020 and 2026, selected from scientific platforms and databases such as IEEE Xplore, ScienceDirect, SpringerLink, and Scopus. A multi-stage screening process and a summary sheet for a set of 89 selected articles were produced to extract the necessary information. The results show that Industry 4.0 influences renewable energy systems at the design and installation stage in predictive maintenance, efficient management, and energy security. Meanwhile, Industry 4.0 in renewable energy systems still faces negative externalities that can be categorised as political, financial, infrastructural, environmental, human, security, and technological. To address these challenges, which tend to become entangled in cycles of negative reinforcement, the paper suggests defining standardised, clear, strict, and stable frameworks at the political, legal, regulatory, and environmental levels to overcome most challenges associated with the digital transformation of renewable energy. The study also recommends flexible, inclusive strategic planning that accounts for the digital maturity of the renewable energy system. From these perspectives, the study contributes to the literature by addressing the role of Industry 4.0 technologies in renewable energy systems from a strategic and coordinated perspective, from both human and technological standpoints. It also offers managerial and policy implications by supporting innovation in renewable energy systems on the one hand and contributing to policy and regulatory decision-making that favour their growth on the other. Full article

Enterprise Resource Planning (ERP) systems have long served as the primary infrastructure for internal control in financial governance, functioning as deterministic, auditable systems of record. The emergence of Zero-Trust Architecture (ZTA) and artificial intelligence (AI) progressively challenges this model, transforming enterprise systems from passive ledgers into autonomous systems of judgment capable of influencing decisions with direct financial and regulatory consequences. This study investigates how trust mediates this transformation. Drawing on a longitudinal dataset of 968 survey responses collected across five measurement waves during a ZTA deployment in a multinational telecommunications organization, we apply an extended Technology Acceptance Model (TAM) to examine changes in perceived usefulness, ease of use, and trust. The findings reveal an Audit Paradox: ZTA simultaneously strengthens formal compliance controls while eroding user trust and perceived productivity, with only partial recovery following structured governance interventions. Building on these findings, we introduce a trust-contingent framework for ERP evolution and develop the concept of the Agency Gap, a structural misalignment between algorithmic decision-making authority and institutional accountability. This study extends accounting and auditing theory into AI-driven control environments and offers practical guidance for auditors, CFOs, and technology leaders navigating the governance of increasingly autonomous digital systems. This study contributes by empirically demonstrating the trust-mediated dynamics of advanced control architectures, introducing the Agency Gap as a theoretical construct addressing algorithmic accountability in AI-driven governance, and extending Sarbanes–Oxley (SOX) oriented control theory into probabilistic, algorithmic environments. Full article

The proliferation of digital financial news offers unprecedented opportunities for automated analysis of market-moving events. This paper presents a framework for event-based sentiment analysis of financial news that leverages Large Language Models (LLMs). The approach brings together three complementary ideas: Retrieval-Augmented Generation (RAG) for contextual enhancement, Graph Neural Networks (GNNs) for modeling relationships between events, and a multi-agent ensemble for orchestrated reasoning. The methodology targets well-known difficulties in financial text processing, including domain-specific terminology, implicit event detection, and temporal reasoning, and it combines transformer-based event extraction with sentiment classification enhanced by external knowledge retrieval. We evaluate six model configurations on an aggregated corpus of 14,851 financial news samples. On the event-detection task, every configuration reaches a weighted F1-score of 100%; we show that this is a ceiling effect produced by a binary event/no-event formulation over a highly imbalanced dataset rather than evidence of a difficult problem being solved, and we discuss what it implies for how such systems should be evaluated. On three-way sentiment classification, the strongest configuration—the multi-agent ensemble—reaches 87.4% accuracy, narrowly ahead of a RoBERTa (Robustly Optimized BERT Pretraining Approach) baseline at 87.2%; however, because the gaps reported between models are small and we did not run significance testing, we report them as indicative rather than definitive. The GNN component is described as part of the proposed design, but it has not yet been validated experimentally, and we state this limitation explicitly. The framework produces interpretable, structured outputs suited to downstream use in algorithmic trading, risk assessment, and investment decision support, and the paper contributes a reusable financial NLP pipeline together with a candid account of where the current evidence is, and is not, convincing. Full article

This paper examines changes in the macroeconomic indicators of the member countries of the Comprehensive and Progressive Agreement for Trans-Pacific Partnership (CPTPP) following their accession to the agreement. This study aims to identify shifts in the structural comparability of national economies and to assess the processes of macroeconomic convergence in the context of sustainable development. To achieve this objective, reference pools of CPTPP member countries are constructed, and their digital profiles are developed based on key macroeconomic indicators and grouped into three blocks: (1) indicators of economic growth and the state of the real sector, including GDP (constant 2015 US$), GDP growth, annual %, gross capital formation, % of GDP, unemployment, total % of total labor force, and national estimate; (2) indicators of foreign economic activity and trade openness, including exports of goods and services, % of GDP, imports of goods and services, % of GDP, external balance on goods and services (% of GDP), foreign direct investment, net inflows, % of GDP, and trade, and % of GDP; (3) indicators of financial and macroeconomic stability including inflation, consumer prices, annual %, central government debt, % of GDP, and gross savings, and % of GDP. Based on the digital profiles, similarities/differences in the economies were examined by applying linear discriminant analysis (LDA). The empirical framework covers two periods: (1) 2013–2017 (pre-accession) years and (2) 2019–2023 (post-accession) years. The results indicate that the economies of member countries in 2013–2017 exhibited a high degree of heterogeneity. In contrast, the 2019–2023 period demonstrates a tendency toward partial convergence of macroeconomic parameters, as evidenced by a reduction in distances between country profiles in the discriminant space. While interpreting the results, it is acknowledged that the 2019–2023 period coincided with the effects of the global crisis caused by the COVID-19 pandemic, which significantly impacted international trade dynamics. For most countries, this period was characterized by a decline in several macroeconomic indicators and investment activity, an increase in debt burdens, and enhanced heterogeneity in economic dynamics, which was taken into account when interpreting macroeconomic convergence processes within the CPTPP. The scientific novelty of the study lies in its application of an approach based on the analysis of the structural similarity of the macroeconomic profiles of CPTPP countries, which complements traditional assessments of the effects of economic and trade integration. The practical significance of the findings is associated with their potential use in evaluating the prospects for CPTPP expansion and in modeling alternative scenarios of participation and sustainable development within international trade agreements under conditions of global economic transformation. Full article

Achieving net-zero emissions requires balancing decarbonization with sustained enterprise development. Using panel data on China’s A-share listed firms from 2011 to 2023, this study examines whether regional carbon emission trading rights (CETR) pilots promote enterprise upgrading, proxied by the New Quality Productive Forces (NQPF) index. A staggered multi-period difference-in-differences framework shows that the CETR policy significantly increases enterprise NQPF (coefficient 0.059, p < 0.05). This finding remains robust after parallel trend tests, placebo simulations, propensity score matching, controlling for overlapping environmental policies, and using alternative outcome measures. Channel analyses indicate that CETR affects NQPF through two pathways: easing financing constraints (coefficient −0.019, p < 0.01) and accelerating digital transformation (coefficient 0.102, p < 0.01). The positive policy effect is stronger among non-state-owned enterprises and among firms whose senior managers lack financial backgrounds or do not hold concurrent positions in shareholder units. These results demonstrate that carbon trading drives systemic enterprise upgrading via resource and technology channels, with important heterogeneity across ownership and governance structures. Full article

This study examines the relationship between environmental performance, digital integration, information asymmetry, and default risk among European firms. It seeks to understand how sustainability and digitalization jointly enhance corporate financial stability. The sample comprises 1303 non-financial firms from 20 European countries over the period 2016–2023. This study uses a Thomson Reuters sample composed of European publicly listed companies with ESG (environmental, social, and governance) ratings. Europe represents an ideal setting for this analysis due to its dual green and digital transition, supported by some of the most advanced regulatory policies in the world. Methodologically, the analysis employs a dynamic panel model estimated using the two-step system GMM approach, complemented by a robustness check based on 2SLS-IV estimation to address potential endogeneity concerns. The empirical findings reveal that both environmental performance and digital integration significantly reduce default risk whereas information asymmetry increases it. Moreover, sustainability and digital transformation attenuate the adverse effect of information asymmetry on financial stability, confirming their complementary role as resilience-enhancing mechanisms. These results underscore the critical importance of transparency, innovation, and organizational capabilities in mitigating financial risk. Overall, the study makes an original contribution to the literature on sustainable governance by demonstrating that environmental performance and digital integration are not merely regulatory requirements but constitute strategic intangible assets that strengthen financial soundness and reduce default risk within the European context. Full article

Background: In the era of digital transformation, public health systems increasingly rely on digital technologies to improve accessibility, efficiency, and patient outcomes. However, policymakers face significant challenges in allocating limited resources across competing digital health investments characterized by uncertainty and dynamic impacts. Methods: This study introduces the Adaptive Impact–Cost Optimization Theory (AICOT), a hybrid framework integrating fuzzy logic and genetic algorithms to optimize digital health investment portfolios. The model defines the Investment Priority Score (IPS) as a function of cost, expected impact, and implementation feasibility, enabling structured evaluation under uncertainty. A fuzzy inference system with centroid-based defuzzification is used to convert qualitative assessments into quantitative scores, while optimization techniques identify optimal portfolios across different fiscal scenarios. The empirical analysis covers 15 OECD countries (2018–2024) using publicly available datasets. Sensitivity analyses assess robustness under inflation, cost shocks, and changing system priorities. Results: The findings show that blended investment strategies combining routine digital health tools with pandemic-oriented infrastructures yield the highest resilience-adjusted efficiency. Results remain stable across sensitivity scenarios, with pandemic surveillance consistently ranking as a top priority even under increased cost conditions. The model effectively captures cross-country heterogeneity, demonstrating adaptability to different levels of digital maturity. Conclusions: AICOT provides a transparent and policy-relevant decision-support framework that improves resource allocation efficiency and reduces unnecessary expenditures. These contributions support long-term financial sustainability and align with global health objectives, including Universal Health Coverage and Sustainable Development Goal 3 (Good Health and Well-being). Full article