Search Results (247)

The adoption of digital technologies, such as the Internet of Things (IoT), has emerged as a key strategy to improve efficiency, sustainability, and productivity in the agricultural sector, especially in contexts of modernization and digital transformation in developing regions. This study analyzes the key factors influencing the adoption of IoT technologies by farmers in the province of Guayas, Ecuador, and their impact on agricultural yields. The research is grounded in innovation diffusion theory and technology acceptance models, which emphasize the role of perception, usability, training, and economic viability in digital adoption. A total of 250 surveys were administered, with 232 valid responses (92.8% response rate), reflecting strong interest from the agricultural sector in digital transformation and precision agriculture. Using structural equation modeling (SEM), the results confirm that general perception of IoT (β = 0.514), practical functionality (β = 0.488), and technical training (β = 0.523) positively influence adoption, while high implementation costs negatively affect it (β = −0.651), all of which are statistically significant (p < 0.001). Furthermore, adoption has a strong positive effect on agricultural yield (β = 0.795). The model explained a high percentage of variance in both adoption (R² = 0.771) and performance (R² = 0.706), supporting its predictive capacity. These findings underscore the need for public and private institutions to implement targeted training and financing strategies to overcome economic barriers and foster the sustainable integration of IoT technologies in Ecuadorian agriculture. Full article

This study aimed to investigate the future trajectories of last-mile delivery (LMD), and their implications for sustainable urban logistics and smart city planning. Through a Delphi-based scenario analysis targeting the year 2030, this research draws on inputs from a two-round Delphi study with 52 experts representing logistics, academia, and government. Four key thematic areas were explored: consumer demand and behavior, emerging delivery technologies, innovative delivery services, and regulatory frameworks. The projections were structured using fuzzy c-means clustering, and analyzed through the Technology Acceptance Model (TAM) and Innovation Diffusion Theory (IDT), supporting a systemic understanding of innovation adoption in urban logistics systems. The findings offer strategic insights for municipal planners, policymakers, logistics service providers, and e-commerce stakeholders, helping align infrastructure development and regulatory planning with the evolving needs of last-mile logistics. This approach contributes to advancing resilient, low-emission, and inclusive smart city ecosystems that align with global sustainability goals, particularly those outlined in the UN 2030 Agenda for Sustainable Development. Full article

This study explores the enhancement of spatial vitality in the Historic Center of Macau from the perspective of museumification theory. This research employs GIS technology to analyze Baidu heatmap data, comparing the differences in spatial vitality between the festive and daily periods. Furthermore, experiential quality questionnaire data were collected from 224 tourists visiting the historical district, constructing a theoretical model of “objective vitality–experience quality”. Through objective analysis, the results indicate that the distribution of vitality in the Historic Center of Macau exhibits a clear core–periphery diffusion pattern. During the festive period, the intensity of spatial vitality significantly increases. Through subjective analysis, this study reveals that experiential quality has a significant impact on spatial vitality. Among the dimensions, education and inspiration, cultural exchange, and entertainment enjoyment have a notably positive effect on spatial vitality. The elements of education and inspiration play a crucial role during festive periods—particularly artistic attractions and educational entertainment—which positively influence vitality. This study innovatively applies museumification theory to the research of vitality in a historical district, providing valuable references for the sustainable cultural tourism development and cultural heritage preservation of the Historic Center of Macau. Full article

The accelerating climate crisis demands innovative approaches that address both systemic drivers of environmental degradation and the psychological barriers to sustained pro-environmental action. Traditional climate communication often relies on fear-based messaging, which risks triggering eco-anxiety, disengagement, or paralysis, ultimately underlying long-term behavioral change. This paper proposes mindfulness as an evidence-based alternative to foster sustained pro-environmental behavior (PEB) by integrating insights from neurocognitive science, self-determination theory (SDT), and social diffusion theory. We present a novel framework outlining five pathways through which mindfulness cultivates PEB: (1) enhanced emotional regulation, (2) intrinsic motivation and value-behavior alignment, (3) nature connectedness, (4) collective action, and (5) cognitive flexibility. Critically, we examine structural barriers to scaling mindfulness interventions—including inequities, commercialization risks, and the individualism paradox—and propose mitigation strategies grounded in empirical research. By bridging contemplative science with sustainability praxis, this work advances SDG-aligned strategies (SDG 12, 13) that prioritize both inner resilience and systemic change. It offers a roadmap for research and practice beyond fear-based approaches. Full article

This study investigates the attributes influencing the adoption of fintech services for sustainable investment within the blue economy. Specifically, it integrates the Diffusion of Innovations (DOI) theory and the Technology Acceptance Model (TAM) to examine how the perceived relative advantages, compatibility, complexity, trialability, and observability of fintech services influence their perceived ease of use and perceived usefulness, and it explores their impact on the intention to adopt fintech services. Finally, the study assesses how the intention to adopt fintech services affects sustainable investment decisions in the blue economy. Data were collected from 224 stakeholders in the blue economy sectors in India during the summer of 2024 and analyzed using structural equation modeling with partial least squares (SEM-PLS). The results reveal which attributes significantly influence perceived ease of use and perceived usefulness. Additionally, perceived ease of use and perceived usefulness significantly influence the intention to adopt fintech services. The intention to adopt fintech services positively impacts sustainable investment decisions in the blue economy. This study provides a comprehensive framework for advancing fintech services that support sustainable investment decisions, thereby contributing to the growth of the blue economy. Full article

This study investigates the influence of agricultural mechanization on maize productivity in Tanzania’s Ruvuma region, a major maize-producing area vital to national food security. It addresses gaps in understanding the cumulative effects of mechanization across the maize production cycle and identifies region-specific barriers to adoption among smallholder farmers. Focusing on five key stages—land preparation, planting, plant protection, harvesting, and drying—this research evaluated mechanization uptake at each stage and its relationship with yield disparities. Statistical analyses using Python libraries included regression modeling, ANOVA, and hypothesis testing to quantify mechanization–yield relationships, controlling for farm size and socioeconomic factors, revealing a strong positive correlation between mechanization and maize yields (r = 0.86; p < 0.01). Mechanized land preparation, planting, and plant protection significantly boosted productivity (β = 0.75–0.35; p < 0.001). However, harvesting and drying mechanization showed negligible impacts (p > 0.05), likely due to limited adoption by smallholders combined with statistical constraints arising from the small sample size of large-scale farms (n = 20). Large-scale farms achieved 45% higher yields than smallholders (2.9 vs. 2.0 tons/acre; p < 0.001), reflecting systemic inequities in access. These inequities are underscored by the barriers faced by smallholders, who constitute 70% of farmers yet encounter challenges, including high equipment costs, limited credit access, and insufficient technical knowledge. This study advances innovation diffusion theory by demonstrating how inequitable resource access perpetuates low mechanization uptake in smallholder systems. It underscores the need for context-specific, equity-focused interventions. These include cooperative mechanization models for high-impact stages (land preparation and planting); farmer training programs; and policy measures such as targeted subsidies for harvesting equipment and expanded rural credit systems. Public–private partnerships could democratize mechanization access, bridging yield gaps and enhancing food security. These findings advocate for strategies prioritizing smallholder inclusion to sustainably improve Tanzania’s maize productivity. Full article

The present study examines the impact of customer firms’ environmental, social, and governance (ESG) performance on suppliers’ green innovation efficiency, grounded in stakeholder theory and innovation diffusion theory. The DEA-SBM model is employed to measure green innovation efficiency and analyze transmission mechanisms through knowledge spillovers, financing constraints, and the moderating roles of executives’ green cognition and digitization. This analysis is based on panel data from 3134 customer–supplier pairs of China’s A-share listed firms from 2014 to 2023. The findings indicate that high ESG performance by customer firms has a substantial impact on suppliers’ green innovation efficiency, with a 1% increase in customer ESG score resulting in a 1.38% improvement in supplier efficiency. The phenomenon under scrutiny is hypothesized to be precipitated by knowledge spillovers and mitigated by reduced financing constraints. The hypothesis further posits that supplier firm executives’ green cognition and customer digitization will amplify the effect. A heterogeneity analysis reveals stronger effects in technology-intensive firms and regions with higher governmental environmental oversight. These findings underscore the pivotal function of ESG-driven supply chain collaboration in propelling sustainable industrialization. It is imperative that policymakers prioritize cross-regional ESG benchmarking and digital infrastructure to amplify green spillovers. Conversely, firms must integrate ESG metrics into supplier evaluation systems and foster executive training on sustainability. This research provides empirical evidence for the optimization of green innovation policies and the achievement of China’s dual carbon goals through the coordination of supply chain governance. Full article

This systematic review explores key theories and factors shaping the adoption of photovoltaic (PV) systems by households in developing countries. Following the PRISMA protocol, we reviewed 44 empirical and theoretical studies published between 2010 and 2024, selected from an initial set of 350 articles retrieved from Scopus and Web of Science. Studies were included if they addressed household PV adoption specifically within developing economies, excluding review articles and conference proceedings. Due to varied methodologies across studies that do not allow for a homogenous assessment, a formal bias risk assessment was not conducted. Our results reveal frequent use of frameworks such as the Theory of Planned Behavior, Technology Acceptance Model, and Diffusion of Innovations. Despite their popularity, these models sometimes fail to fully capture the economic, infrastructure, and cultural realities specific to nonmatured markets. Key adoption barriers identified include affordability constraints, weak infrastructure, social norms, and inconsistent policy support. Geographic imbalance, particularly concentrated in Asia and Africa, and limited consideration of behavioral economics insights represent limitations in the current evidence base. These findings suggest the need for context-sensitive theoretical models and deeper integration of behavioral factors, providing practical directions for future research and policy to facilitate renewable energy transitions. Full article

This study investigates the primary technological and socio-environmental factors influencing the adoption intentions of AI-powered technology at the corporate level within higher education institutions. A conceptual model based on the Diffusion of Innovation Theory (DOI), the Technology–Organization–Environment (TOE), and the Technology Acceptance Model (TAM) combined framework were proposed and tested using data collected from 367 higher education students, faculty members, and employees. SPSS Amos 24 was used for CB-SEM to choose the best-fitting model, which proved more efficient than traditional multiple regression analysis to examine the relationships among the proposed constructs, ensuring model fit and statistical robustness. The findings reveal that Compatibility “C”, Complexity “CX”, User Interface “UX”, Perceived Ease of Use “PEOU”, User Satisfaction “US”, Performance Expectation “PE”, Artificial intelligence “AI” introducing new tools “AINT”, AI Strategic Alignment “AIS”, Availability of Resources “AVR”, Technological Support “TS”, and Facilitating Conditions “FC” significantly impact AI adoption intentions. At the same time, Competitive Pressure “COP” and Government Regulations “GOR” do not. Demographic factors, including major and years of experience, moderated these associations, and there were large differences across educational backgrounds and experience. Full article

As urbanization accelerates globally, higher education agglomeration (HEA) emerges as a critical mechanism for integrating regional economic theories with practical strategies, driving innovation and sustainable development. This paper examines how HEA promotes innovation, human capital accumulation, industrial restructuring, and equitable income distribution across 193 cities in the “Two Transverse and Three Lengthways” urban clusters from 2006 to 2020. Using dynamic panel regression and spatial econometric models, the results show that HEA yields significant local and spatial spillover benefits, particularly in core cities that facilitate knowledge diffusion and resource sharing. Heterogeneity analysis reveals that these positive spillovers are strongest in first-tier, highly developed clusters and third-tier, early-stage clusters but weaker or even negative in second-tier, rapidly expanding regions. These spatial effects grow over time, reflecting the evolving patterns of regional integration. Theoretically, the paper advances the understanding of spatial synergy and spillover mechanisms in HEA in urban clusters. Practically, the findings highlight the need to tailor higher education strategies to the developmental stage of each urban cluster to optimize resource allocation and foster inclusive growth. This paper provides policy insights for using HEA as a catalyst for coordinated urban development. Full article

Despite the transformative potential of artificial intelligence (AI), small and medium-sized enterprises (SMEs) continue to face significant challenges in its effective adoption. While prior studies have emphasized strategic benefits and readiness models, there remains a lack of operational guidance tailored to SME realities—particularly regarding implementation barriers, resource constraints, and emerging demands for responsible AI use. This study presents an analysis of AI adoption in SMEs by integrating the technology–organization–environment (TOE) framework with selected attributes from the diffusion of innovations (DOI) theory to examine adoption dynamics through a dual structural and perceptual lens. Empirical insights from sectoral and regional contexts are also incorporated. Ten critical challenges are identified and analyzed across the TOE dimensions, ranging from data access and skill shortages to cultural resistance, infrastructure limitations, and weak governance practices. Notably, the framework is expanded to incorporate responsible AI governance and democratized access to generative AI—particularly open-weight large language models (LLMs) such as LLaMA, DeepSeek-R1, Mistral, and FALCON—as emerging technological and ethical imperatives. Each challenge is paired with actionable, context-sensitive solutions. The paper is a structured, literature-based conceptual analysis enriched by empirical case study insights. As a key contribution, it introduces a structured, six-phase roadmap methodology to guide SMEs through AI adoption—offering step-by-step recommendations aligned with technological, organizational, and strategic readiness. While this roadmap is conceptual and has yet to be validated through field data, it sets a foundation for future diagnostic tools and practical assessments. The resulting study bridges theoretical insight and implementation strategy—empowering inclusive, responsible, and scalable AI transformation in SMEs. By offering both analytical clarity and practical relevance, this study contributes to a more grounded understanding of AI integration and calls for policies, ecosystems, and leadership models that support SMEs in adopting AI not merely as a tool, but as a strategic enabler of sustainable and inclusive innovation. Full article

Faced with mounting pressure to achieve high-quality green transformation, manufacturing enterprises are increasingly scrutinized for greenwashing behaviors. This study develops a novel hybrid modeling framework that combines evolutionary game theory with the SEIR epidemic model to investigate the dynamic interactions between environmental regulation, media pressure, and green innovation behavior. The model captures how strategic decisions among boundedly rational actors evolve over time under dual external pressures. Simulation results show that stronger environmental regulatory intensity accelerates the adoption of substantive green innovation and concurrently reduces the media pressure associated with greenwashing. Moreover, while social media disclosure has a limited impact during the early stages of greenwashing information diffusion, its influence becomes significantly amplified once a critical dissemination threshold is surpassed, rapidly transforming latent information into widespread public concern. This amplification triggers significant public opinion pressure, which, in turn, incentivizes local governments to enforce stricter environmental policies. The findings reveal a synergistic governance mechanism where environmental regulation and media scrutiny jointly curb greenwashing and foster genuine corporate sustainability. Full article

Digital transformation has become a strategic imperative for micro and small enterprises (MSEs) in emerging economies, yet the mechanisms linking digitalization to performance outcomes remain underexplored. This study examines how the strategic emphasis on digital transformation and the breadth of technology adoption influence firm performance among MSEs in Bhutan. Drawing on an integrative theoretical framework combining diffusion of innovations theory, the resource-based view, and institutional theory, survey data from 217 MSEs were analyzed using regression and interaction modeling techniques. The findings indicate that firms with stronger digital strategic emphasis adopt a broader range of technologies and achieve superior performance. However, unstructured or excessive knowledge sharing negatively moderates these relationships, potentially creating cognitive overload and impeding digital strategy execution. Furthermore, tourism enterprises exhibit significantly higher levels of digital engagement compared to non-tourism counterparts, highlighting the role of sector-specific institutional pressures. By uncovering the systemic dynamics between strategic orientation, technology adoption, and knowledge flows, this study contributes to a deeper understanding of how digital transformation processes can be optimized in resource-constrained environments. These findings not only offer practical insights for enhancing digital readiness and organizational resilience among small enterprises but also contribute to the broader theoretical discourse on how strategic orientation and contextual moderators shape the effectiveness of digital transformation in emerging markets. Full article

Understanding consumer heterogeneity is crucial for analysing attitude formation and its role in innovation diffusion. Traditional top-down models struggle to reflect the nuanced characteristics and activities of the consumer population, while bottom-up approaches like agent-based modelling (ABM) offer the ability to simulate individual decision-making in social networks. However, current ABM applications often lack a strong theoretical foundation. This study introduces a novel, theory-driven ABM framework to examine the heterogeneity of consumer attitude formation, focusing on electric vehicle (EV) adoption across consumer segments. The model incorporates non-linear decision-making rules grounded in established consumer theories, incorporating Rogers’s Diffusion of Innovations, Social Influence Theory, and Theory of Planned Behaviour. The consumer agents are characterised using UK empirical data, and are segmented into early adopters, early majority, late majority, and laggards. Social interactions and attitude formation are simulated, micro-validated, and optimised using supervised machine learning (SML) approaches. The results reveal that early adopters and early majority are highly responsive to social influences, environmental beliefs, and external events such as the pandemic and the war conflict in performing pro-EV attitudes. In contrast, late majority and laggards show more stable or delayed responses. These findings provide actionable insights for targeting segments to enhance EV adoption strategies. Full article

The diffusion of green energy technological innovation based on international green energy cooperation is a critical pathway to achieving global low-carbon emission reductions. However, few studies have considered the innovation diffusion pathways of green energy technologies under bilateral policy uncertainties. This paper constructs an evolutionary game model for the diffusion of green energy technological innovation in a complex network environment, with a focus on analyzing the impacts of key parameters such as policy spillover effects, technological heterogeneity, technical leakage risks, and free-riding risks on the equilibrium outcomes of evolutionary strategies. The results of the study are as follows: (1) Technological synergy and technological heterogeneity have a significant role in promoting the diffusion of green energy technological innovation, but when technological heterogeneity is too high, it is difficult for the two parties to find more common interests and areas of technological interaction, and the cooperative innovation will be turned into an empty shell that has a name but no reality. (2) Policy uncertainty has a significant impact on the diffusion of green energy technology innovation, and the specific impact depends on the type of policy, policy intensity, policy spillover effects, and other key parameters. (3) The risk of technological obsolescence has prompted countries to deeply participate in green energy international cooperation to realize the “curved road overtaking” of green energy technology based on technological locking and latecomer advantages; due to the existence of the phenomenon of “free-riding”, the logic of value creation based on win–win cooperation is replaced by the opportunism of “enjoying the benefits”, and cooperative innovation may be turned into a one-time “handshake agreement”. The existence of the risk of technology leakage can turn collaborative innovation into a “witch hunt” by the underdog against the overdog, and the diffusion process of green energy technology innovation is led in the wrong direction. Full article