Search Results (306)

Background: Rapid urbanization has intensified the challenges of freight transport, particularly in last-mile (LM) delivery, leading to rising costs and environmental externalities. Autonomous vehicles (AVs) have emerged as a promising innovation to address these issues. While much of the existing literature emphasizes business and operational perspectives, this study focuses on the acceptance of AVs from the standpoint of e-consumers—individuals who make purchases via digital platforms—in an emerging market context. Methods: Grounded in an extended Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), which is specifically suited to consumer-focused technology adoption research, this study incorporates five constructs tailored to AV adoption. Structural Equation Modeling (SEM) was applied to survey data collected from 304 e-consumers in Northeast Brazil. Results: The findings reveal that performance expectancy, hedonic motivation, and environmental awareness exert significant positive effects on acceptance and intention to use AVs for LM delivery. Social influence shows a weaker, yet still positive, impact. Importantly, price sensitivity exhibits a minimal effect, suggesting that while consumers are generally cost-conscious, perceived value may outweigh price concerns in early adoption stages. Conclusions: These results offer valuable insights for policymakers and logistics providers aiming to implement consumer-oriented, cost-effective AV solutions in LM delivery, particularly in emerging economies. The findings emphasize the need for strategies that highlight the practical, emotional, and environmental benefits of AVs to foster market acceptance. Full article

Governments worldwide are mandating e-invoicing and real-time VAT reporting, yet many cash-intensive service SMEs continue to under-report VAT, eroding fiscal revenues. This study investigates whether financial technology (FinTech) adoption can reduce this under-reporting among tourism SMEs in Greece—an economy with high seasonal spending and a persistent shadow economy. This is the first micro-level empirical study to examine how FinTech tools affect VAT compliance in this sector, offering novel insights into how technology interacts with behavioral factors to influence fiscal behavior. Drawing on the Technology Acceptance Model, deterrence theory, and behavioral tax compliance frameworks, we surveyed 214 hotels, guesthouses, and tour operators across Greece’s main tourism regions. A structured questionnaire measured five constructs: FinTech adoption, VAT compliance behavior, tax morale, perceived audit probability, and financial performance. Using Partial Least Squares Structural Equation Modeling and bootstrapped moderation–mediation analysis, we find that FinTech adoption significantly improves declared VAT, with compliance fully mediating its impact on financial outcomes. The effect is especially strong among businesses led by owners with high tax morale or strong perceptions of audit risk. These findings suggest that FinTech tools function both as efficiency enablers and behavioral nudges. The results support targeted policy actions such as subsidies for e-invoicing, tax compliance training, and transparent audit communication. By integrating technological and psychological dimensions, the study contributes new evidence to the digital fiscal governance literature and offers a practical framework for narrowing the VAT gap in tourism-driven economies. Full article

This study synthesizes the rapidly expanding evidence on how digital technologies reshape international trade, with a particular focus on small and medium-sized enterprises (SMEs). Guided by two research questions—(RQ1) How do digital tools influence the volume and composition of cross-border trade? and (RQ2) How do these effects vary by countries’ development level and firm size?—we conducted a PRISMA-compliant systematic literature review covering 2010–2024. Searches across eight major databases yielded 1857 records; after duplicate removal, title/abstract screening, full-text assessment, and Mixed Methods Appraisal Tool (MMAT 2018) quality checks, 86 peer-reviewed English-language studies were retained. Findings reveal three dominant technology clusters: (1) e-commerce platforms and cloud services, (2) IoT-enabled supply chain solutions, and (3) emerging AI analytics. E-commerce and cloud adoption consistently raise export intensity—doubling it for digitally mature SMEs—while AI applications are the fastest-growing research strand, particularly in East Asia and Northern Europe. However, benefits are uneven: firms in low-infrastructure settings face higher fixed digital costs, and cybersecurity and regulatory fragmentation remain pervasive obstacles. By integrating trade economics with development and SME internationalization studies, this review offers the first holistic framework that links national digital infrastructure and policy support to firm-level export performance. It shows that the trade-enhancing effects of digitalization are contingent on robust broadband penetration, affordable cloud access, and harmonized data-governance regimes. Policymakers should, therefore, prioritize inclusive digital-readiness programs, while business leaders should invest in complementary capabilities—data analytics, cyber-risk management, and cross-border e-logistics—to fully capture digital trade gains. This balanced perspective advances theory and practice on building resilient, equitable digital trade ecosystems. Full article

With rising environmental awareness, numerous firms are transitioning to green investment, such as low-carbon production. However, the consumer adoption of low-carbon products remains low due to transparency concerns. Many firms are leveraging blockchain to address information asymmetry in the supply chain, thereby building consumer confidence in low-carbon products. The purpose of this work is to provide decision support for business firms by analyzing the strategic choices regarding the manufacturer’s green investment and the e-retailer’s adoption of blockchain technology. Three strategy combinations are considered, including the baseline strategy combination without green investment and blockchain technology (NN), the strategy combination with only green investment (LN), and the strategy combination with both green investment and blockchain technology (LB). The optimal pricing and green level decisions are derived, and the conditions under which green investment and blockchain technology are beneficial to the supply chain members are examined. The findings suggest that the e-retailer can obtain the highest profit without adopting blockchain technology if it holds a substantial or extremely low market share, if the consumers’ low-carbon preference is at a low to medium level, or if the consumer green trust coefficient is high when the manufacturer implements the green investment strategy. When consumers exhibit a weak preference for low-carbon products, the strategy combination NN is optimal for the supply chain members. The strategy combination LB becomes optimal if the consumer green trust coefficient is near or below the moderate threshold, if the market share of a channel is neither extremely high nor low, or if consumers exhibit a strong preference for low-carbon products. Full article

The electric vehicle (EV) business model integrates advanced battery technology, dynamic power train architectures, and intelligent energy management systems with ecosystem strategies and digital services. It incorporates environmental sustainability through lifecycle analysis and renewable energy integration. China, with 9.49 million EV sales in 2023 (33% market share), faces infrastructure gaps constraining further growth. China is strategically mitigating CO₂ emissions while fostering economic expansion, notwithstanding constraints such as suboptimal battery technology advancements, elevated production expenditure, and enduring ecological impacts. This Political, Economic, Social, Technological, Legal, Environmental (PESTLE) assessment, operationalized through a survey of 800 stakeholders and Statistical Package for the Social Sciences IBM SPSS SPSS (Version 28) quantitative analysis (factor loading = 0.73 for Technology; eigenvalue = 4.12), identifies infrastructure gaps as the dominant barrier (72% of stakeholders). Political factors (β = 0.82) emerged as the strongest adoption predictor, outweighing economic subsidies in significance. The adoption of EVs in China presents a significant prospect for reducing CO₂ emissions and advancing technology. However, economic barriers, market dynamics, inadequate infrastructure, regulatory uncertainty, and social acceptance issues are addressed in the assessment. The study recommends prioritizing infrastructure investment (e.g., 500 K fast-charging stations by 2027) and policy stability to overcome adoption barriers. This study provides three key advances: (1) quantification of PESTLE factor weights via factor analysis, revealing technological (infrastructure) and political factors as dominant; (2) identification of infrastructure gaps, not subsidies, as the primary adoption barrier; and (3) demonstration of infrastructure’s persistence post-subsidy cuts. These insights redefine EV adoption priorities in China. Full article

Prior research has focused on the technical and institutional challenges of blockchain adoption. However, little is known about how blockchain ventures claim categorical space in the market and how such domain positioning influences their visibility and evaluation. This study investigates the relationship between strategic domain positioning and market recognition among blockchain-based ventures, with a particular focus on applications relevant to e-commerce, such as non-fungible tokens (NFTs) and decentralized finance (DeFi). Drawing on research on categorization, legitimacy, and the technology lifecycle, we propose a domain lifecycle perspective that accounts for the evolving expectations and legitimacy criteria across blockchain domains. Using BERTopic, a transformer-based topic modeling method, we classify 9665 blockchain ventures based on their textual business descriptions. We then test the impact of domain positioning on market recognition—proxied by Crunchbase rank—while examining the moderating effects of external validation signals such as funding events, media attention, and organizational age. Our findings reveal that clear domain positioning significantly enhances market recognition, but the strength and direction of this effect vary by domain. Specifically, NFT ventures experience stronger recognition when young and less institutionally validated, suggesting a novelty premium, while DeFi ventures benefit more from conventional legitimacy signals. These results advance our understanding of how categorical dynamics operate in emerging digital ecosystems and offer practical insights for e-commerce platforms, investors, and entrepreneurs navigating blockchain-enabled innovation. Full article

In an increasingly digitalized marketplace, understanding Generation Z’s (Gen Z) online consumer behavior has become a critical priority, particularly in relation to newly launched technological products. Although online consumer behavior has been widely studied, a gap remains in understanding how the location of the e-shop (domestic vs. international) moderates this behavior. Addressing this gap, the present study adopts a quantitative, cross-sectional design with data from 302 Gen Z participants, using a hybrid sampling method that combines convenience and systematic techniques. A structured questionnaire, grounded in 19 well-established behavioral theories, was employed to examine the influence of six key factors, behavioral and attitudinal traits, social and peer influences, marketing impact, online experience, brand perceptions, and Gen Z characteristics, across various stages of the consumer journey. Moderation analysis revealed that e-shop location significantly affects the strength of relationships between these factors and both purchase intention and post-purchase behavior. Notably, Gen Z’s values and marketing responsiveness were found to be more predictive in the context of international e-shops. These findings highlight the importance of marketing strategies that are both locally relevant and globally informed. For businesses, this research offers actionable insights into how digital engagement and brand messaging can be tailored to meet the unique expectations of Gen Z consumers across diverse e-commerce contexts, thereby enhancing consumer satisfaction, loyalty, and brand advocacy. Full article

Using time-varying Granger causality, Neural Networks Nonlinear VAR, and Wavelet Coherence analysis, we evidence the unstable effect of the money market rate on industrial production and consumer price index in Tunisia. The effect is asymmetric and depends on geopolitical risk (low versus high). We show that global geopolitical risk has both detriments and benefits sides—it is a threat and an opportunity for monetary policy transmission mechanisms. Interacted local projections (LPs) reveal short–medium-term volatility or dampening effects, suggesting that geopolitical uncertainty might weaken the immediate impact of monetary policy on output and prices. In uncertain environments (e.g., high geopolitical risk), economic agents—households and businesses—may adopt a wait-and-see approach. They delay consumption and investment decisions, which could initially mute the impact of monetary policy. Agents may delay their responses until they gain more information about geopolitical developments. Once clarity emerges, they may adjust their behavior, aligning with the long-run effects observed in the Vector Error Correction Model (VECM). Furthermore, we identify an exacerbating investor sentiment following tightening monetary policy, during global and local geopolitical episodes. The impact is even more pronounced under conditions of high domestic weakness. Evidence is extracted through a novel composite index that we construct using Principal Component Analysis (PCA). Our results have implications for the Central Bank’s monetary policy conduct and communication practices. Full article

Decarbonizing industrial manufacturing is a significant challenge in the effort to limit the impacts of global climate change. Additive manufacturing (AM) is one pathway for reducing the impacts of manufacturing as it creates parts layer-by-layer rather than by removing (i.e., subtracting) material from solid stock as with conventional techniques. This reduces material inputs and generates less waste, which can substantially lower life cycle energy consumption and greenhouse gas emissions. However, AM adoption in the manufacturing sector has been slow, partly due to challenges in making a strong business case compared with more traditional and widely available techniques. This paper highlights the need for the development of simple screening analysis tools to speed the adoption of AM in the manufacturing sector by providing decision-makers easy access to important production life cycle emissions, and cost information. Details on the development of two Microsoft Excel software tools are provided: upgrades to an existing tool on the energy and carbon impacts of AM and a new tool for analyzing the major cost components of AM. A case study applies these two tools to the production of a lightweight aerospace bracket, showing how the tools can be used to estimate the environmental benefits and production costs of AM. Full article

As the population increases, the growing demand for residential housing escalates construction activities, significantly impacting global warming by contributing 42% of primary energy use and 39% of global greenhouse gas (GHG) emissions. This study addresses a gap in research on lifecycle assessment (LCA) for Indian residential buildings by evaluating the full cradle-to-grave carbon footprint of a typical single-family house in Northern India. A BIM-based LCA framework was applied to a 110 m² single-family dwelling over a 60-year life span. Operational use performance and climate analysis was evaluated via cove tool. The total carbon footprint over a 60-year lifespan was approximately 5884 kg CO₂e, with operational energy use accounting for about 87% and embodied carbon approximately 11%. Additional impacts came from maintenance and replacements. Energy usage was calculated as 71.76 kWh/m²/year and water usage as 232.2 m³/year. Energy consumption was the biggest driver of emissions, but substantial impacts also stemmed from material production. Cement-based components and steel were the largest embodied carbon contributors. Under the business-as-usual (BAU) scenario, the operational emissions reach approximately 668,000 kg CO₂e with HVAC and 482,000 kg CO₂e without HVAC. The findings highlight the necessity of integrating embodied carbon considerations alongside operational energy efficiency in India’s building codes, emphasizing reductions in energy consumption and the adoption of low-carbon materials to mitigate the environmental impact of residential buildings. Future work should focus on the dynamic modeling of electricity decarbonization, improved regional datasets, and scenario-based LCA to better support India’s transition to net-zero emissions by 2070. Full article

The integration of Artificial Intelligence (AI) and the Internet of Things (IoT) in Building Energy Management Systems (BEMSs) offers transformative potential for improving energy efficiency, enhancing occupant comfort, and supporting grid stability. However, the adoption of these technologies in the European Union (EU) is significantly influenced by a complex regulatory landscape, including the EU AI Act, the General Data Protection Regulation (GDPR), the EU Cybersecurity Act, and the Energy Performance of Buildings Directive (EPBD). This review systematically examines the legal, technological, and economic implications of these regulations on AI- and IoT-driven BEMS. Following the PRISMA-ScR guidelines, 64 relevant sources were reviewed, comprising 34 peer-reviewed articles and 30 regulatory or policy documents. First, legal and regulatory barriers that may hinder innovation are identified, including data protection constraints, cybersecurity compliance, liability concerns, and interoperability requirements. Second, technological challenges in designing regulatory-compliant AI and IoT solutions are examined, with a focus on data privacy-preserving architectures (e.g., edge computing versus cloud processing), explainability requirements for AI decision-making, and cybersecurity resilience. Finally, the economic opportunities arising from regulatory alignment are highlighted, demonstrating how compliant AI and IoT-based BEMS can enable energy savings, operational efficiencies, and new business models in smart buildings. By synthesizing current research and policy developments, this review offers a comprehensive framework for understanding the intersection of regulatory requirements and technological innovation in AI-driven building management. Strategies are discussed for navigating regulatory constraints while leveraging AI and IoT for energy-efficient, intelligent building operations. The insights presented aim to support researchers, policymakers, and industry stakeholders in advancing regulatory-compliant BEMS that balance innovation, security, and sustainability. Full article

The agricultural sector stands at the intersection of economic, ethical, and environmental concerns, presenting complex challenges for sustainable development. This study investigates how ethical attitudes, conceptualized at political (e.g., perceptions of transparency, anti-corruption, and policy fairness) and social levels (e.g., community engagement, labor standards, and social equity), influence ethical behavior within Romanian agricultural organizations. Additionally, it explores the impact of sector-specific and organizational ethics on the adoption of social responsibility (SR) practices. Using a quantitative research approach, the study employed a structured questionnaire covering four key dimensions: political and social ethics, corporate responsibility, environmental sustainability, and ethical management in agriculture. The findings suggested that Romanian agricultural companies could improve their long-term competitiveness by incorporating ethical governance, sustainable business practices, and stakeholder engagement into their strategic frameworks. These findings suggest that Romanian agricultural companies can enhance their long-term competitiveness by embedding ethical governance, sustainable business models, and active stakeholder engagement into their strategic frameworks. This research contributes to the theoretical discourse by demonstrating how contextual ethical attitudes influence SR, providing a nuanced understanding of the interplay between economic performance, social equity, and environmental responsibility in an emerging economy. Full article

While digital transformation in e-commerce receives the most publicity, applications in energy and water utilities have been ongoing for decades. Using a methodology based on a systematic review, the paper offers a model of how it occurs in water utilities, reviews experiences from the field, and derives lessons learned to create a road map for future research and implementation. Innovation in water utilities occurs more in the field than through organized research, and utilities share their experiences globally through networks such as water associations, focus groups, and media outlets. Their digital transformation journeys are evident in business practices, operations, and asset management, including methods like decision support systems, SCADA systems, digital twins, and process optimization. Meanwhile, they operate traditional regulated services while being challenged by issues like aging infrastructure and workforce capacity. They operate complex and expensive distribution systems that require grafting of new controls onto older systems with vulnerable components. Digital transformation in utilities is driven by return on investment and regulatory and workforce constraints and leads to cautious adoption of innovative methods unless required by external pressures. Utility adoption occurs gradually as digital tools help utilities to leverage system data for maintenance management, system renewal, and water loss control. Digital twins offer the advantages of enterprise data, decision support, and simulation models and can support distribution system optimization by integrating advanced metering infrastructure devices and water loss control through more granular pressure control. Models to anticipate water main breaks can also be included. With such advances, concerns about cyber security will grow. The lessons learned from the review indicate that research and development for new digital tools will continue, but utility adoption will continue to evolve slowly, even as many utilities globally are too stressed with difficult issues to adopt them. Rather than rely on government and academics for research support, utilities will need help from their support community of regulators, consultants, vendors, and all researchers to navigate the pathways that lie ahead. Full article

Background and Objectives: Mitral valve transcatheter edge-to-edge repair (TEER) is a widely adopted therapeutic approach for managing significant mitral regurgitation (MR) in high-risk surgical candidates. While procedural safety and efficacy have been demonstrated, the impact of institutional expertise on outcomes remains unclear. We aimed at evaluating whether the institutional monthly volume of TEER influences short- and long-term clinical results. Materials and Methods: This analysis from the multicenter, prospective GIOTTO trial study evaluated the impact of institutional monthly volume on outcomes of TEER to remedy significant mitral regurgitation. Centers were stratified into tertiles based on monthly volumes (≤2.0 cases/month, 2.1–3.5 cases/month, >3.5 cases/month), and key clinical, echocardiographic, and procedural outcomes were analyzed. Statistical analysis was based on standard bivariate tests as well as unadjusted and multivariable adjusted Cox models. Results: A total of 2213 patients were included, stratified into tertiles based on institutional procedural volume: 645 (29.1%) patients in the first tertile, 947 (42.8%) patients in the second tertile, and 621 (28.1%) patients in the third tertile. Several baseline differences were found, with some features disfavoring less busy centers (e.g., functional class and surgical risk, both p < 0.05), and others suggesting a worse risk profile in those treated in busier institutions (e.g., frailty and history of prior mitral valve intervention, both p < 0.05). Procedural success rates were higher in busier centers (p < 0.001), and hospital stay was also shorter there (p < 0.001). Long-term follow-up (median 14 months) suggested worse outcomes in patients treated in less busy centers at unadjusted analysis (e.g., p = 0.018 for death, p = 0.015 for cardiac death, p = 0.014 for death or hospitalization for heart failure, p < 0.001 for cardiac death or hospitalization for heart failure), even if these associations proved no longer significant after multivariable adjustment, except for cardiac death or hospitalization for heart failure, which appeared significantly less common in the busiest centers (p < 0.05). Similar trends were observed when focusing on tertiles of overall center volume and when comparing for each center the first 50 cases with the following ones. Conclusions: High institutional monthly volume of TEER mitral valve repair appears to correlate with an improved procedural success rate and shorter hospitalizations. Similarly favorable results were found for long-term rates of cardiac death or hospitalization for heart failure. These findings inform on the importance of operator experience and center expertise in achieving state-of-the-art results with TEER, while confirming the usefulness of the proctoring approach when naïve centers begin a TEER program. Full article

Sustainable innovation management (SIM) is increasingly recognized as a pivotal framework for addressing the dual challenges of economic growth and environmental responsibility. In response to escalating global pressures, this review explores how SIM can drive sustainable development by balancing profitability with ecological stewardship. Drawing on recent academic and industry sources, the paper examines the intersection of circular economy principles, emerging technologies, and policy frameworks in shaping sustainable innovation strategies. The review is structured around three key pillars: the integration of technologies, such as artificial intelligence, blockchain, and the Internet of things in sustainable operations; the influence of regulatory drivers, including carbon pricing and environmental, social, and governance standards; and empirical case studies that highlight both challenges and success factors in SIM adoption. By synthesizing real-world applications across sectors and geographies, this study provides qualitative insights and quantitative indicators (e.g., CO₂ reduction, return on investment, material reuse rates) to inform practical strategies for business leaders and policymakers. Addressing gaps such as the lack of global harmonization in sustainability metrics and the under-representation of developing economies, this review contributes to a more inclusive and actionable understanding of SIM. This paper concludes by offering future research directions and policy recommendations aimed at accelerating the transition toward sustainable and circular business models. Full article