Search Results (307)

Enterprise systems are widely adopted in organizations, yet user acceptance remains a major challenge due to the complex interplay of cognitive, social, motivational, and innovation-related factors. Existing technology acceptance models often provide fragmented explanations by focusing on limited determinants. This study proposes TAM 4, an exploratory framework integrating constructs from the Technology Acceptance Model (TAM), Unified Theory of Acceptance and Use of Technology (UTAUT), Hedonic-Motivation System Adoption Model (HMSAM), and Diffusion of Innovation (DOI). The study was conducted in the context of enterprise application usage and professional enterprise system training environments involving organizational users, trainees, and practitioners. Data were collected from 115 enterprise system users (trainees and practitioners). To consolidate overlapping indicators and strengthen construct definition, principal component analysis (PCA) was applied, yielding seven higher-order constructs that explain 81.642% of cumulative variance. The framework was validated using PLS-SEM with three scenario-based structural models (full mediation, partial mediation, and direct effects). The results show that Model 3 provides the best fit and predictive performance (SRMR = 0.048; NFI = 0.786), indicating that enterprise system adoption is better explained through a direct effect structure rather than a purely mediated TAM pathway. The novelty of this study lies in introducing TAM 4 as a PCA-driven multi-theory acceptance model and evaluating its explanatory robustness through multi-scenario model comparison, offering practical insights for improving enterprise system implementation strategies. Full article

This study investigates the predictive contribution of digital infrastructure to GDP per capita growth across 27 European Union Member States over the period 1995–2024, using a balanced panel of 810 country–year observations and an explainable machine learning framework. An XGBoost model trained on six World Bank indicators—fixed broadband subscriptions, internet users, mobile subscriptions, patent applications, R&D expenditure, and secure internet servers—achieves a training R² of 0.804 and a test R² of 0.430 under temporal out-of-sample validation spanning the COVID-19 structural break. TreeSHAP decomposition identifies fixed broadband as the strongest predictor of model-estimated GDP per capita growth (mean |SHAP| = 0.948; bootstrap rank 1 in 78% of 50 resamples; Friedman Chi-square (5) = 168.16, p < 0.001), providing predictive support for Hypothesis H1. Innovation indicators, represented by patent applications and R&D expenditure, exceed the pre-specified materiality threshold, providing predictive support for H2, while SHAP dependence plots reveal pronounced non-linear threshold patterns consistent with S-curve diffusion theory, supporting H3. Temporal SHAP decomposition identifies three structural phases: broadband dominance (1995–2007), crisis-induced reconfiguration (2008–2013), and quality convergence (2014–2024). The framework reconciles contradictory findings from prior literature by visualizing the complete functional form of the broadband–growth relationship without imposing a parametric specification. Full article

Universities are increasingly expected to contribute to societal and environmental challenges, yet the concept of the fourth mission remains fragmented and weakly operationalized in the literature. This study aims to develop a measurement framework for the fourth mission of universities. The research adopts a theory-driven qualitative design based on a systematic literature review, synthesizing contributions on community engagement, social innovation, sustainability and institutional embeddedness. Building on this synthesis, the study develops a three-level conceptual model that integrates an institutional framework, core fourth mission processes and transformative impact domains. The core processes are structured around community engagement, co-creation and social innovation, and knowledge diffusion and local application, while the model explicitly links these processes to societal challenges and environmental sustainability outcomes. Furthermore, the model is operationalized through a structured indicator system applicable in document-based analysis, supported by a four-point scoring scale capturing the depth of institutionalization. An illustrative pilot test was also conducted using the example of one university faculty. The study contributes by clarifying the boundaries of the fourth mission and offering an operational framework that shifts attention from output-based measurement to universities’ transformative societal roles. Full article

This study examines the hypothetical issue of the impact of ancient Egyptian beliefs on Africa as a whole. Several focal points are explored. These include (1). The situation of the discipline of folklore within allied academic specializations. (2). Culture diffusion within Africa, and (3). Spoken folk stories as the only field that integrates, in the space and time continuum, culture on the one hand, with its bearers/(society), on the other. (4). [Beside the] colonial past, the problem, is a result of a number of academic factors that include: (a). The establishment at universities of African studies departments that confine the continent to the sub-Saharan tier excluding Africa of the North; thus, folklore is isolated without a proper stage for studying it academically (see Dorson 1972); (b). The stereotyping concerning the capacity of scholars with unfamiliar names or recognized departmental membership as capable of dealing with theory or innovation, though some of their ideas are adopted by the famous without accrediting the source; (c). Ignoring the unfamiliarity for the family (especially under conditions of secrecy; cf. bias, ethnocentrism); and (d). Inadequacy of academic classroom pedagogy on the basics of verbal lore. Folklore in its original, mainly verbal branches, as represented by Stith Thompson’s monumental works on motif (1955–1958), and its predecessor by Antti Aarne on Type, (1910, 1928, 1961/1964), whose coverage, especially on Africa of the North, is seriously lacking in both the Type and Motif Indexes. The tracking of this line begins with recent calls for need for morphological studies of a South African tale (Dseagu [²⁰⁰¹] 2021). An association among various regions of Africa with ancient Egypt concerning mythological contacts merits this investigation. Full article

This paper presents a probabilistic–statistical approach to the analysis of diffusion processes in randomly nonhomogeneous multilayered bodies under conditions of incomplete experimental information on the boundary. The boundary condition is reconstructed from experimental data using linear regression, while the solution of the corresponding contact initial-boundary value problem is obtained in the form of a Neumann series and averaged over an ensemble of phase configurations. A system of statistical estimates for the solution is developed, including confidence intervals and two-sided critical regions, which provide complementary characteristics of uncertainty. Numerical experiments are performed for six representative samples differing in sample size, variance, and observation interval. It is shown that, despite significant differences in the statistical properties of the input data, the averaged concentration field preserves a qualitatively stable spatio-temporal structure. The results of the article address gaps in existing research by applying a probabilistic-statistical approach that consistently integrates two key elements for the analysis of diffusion processes in multilayer media. The first of these is the reconstruction of boundary conditions using linear regression to recover the conditions at the body boundary based on incomplete experimental data. The second key point is the analysis of uncertainty propagation by combining the regression model with a probabilistic analysis of the corresponding contact initial-boundary value problem, which allows us to quantitatively assess how the errors in the experimental data affect the final solution. From the point of view of mathematical modeling methods, the novelty of the approach lies in the creation of a structural-hierarchical scheme that synthesizes the approaches of mathematical statistics and the theory of random fields. The developed method is a theoretical and computational innovative basis for the analysis of specific physical and technological processes. Full article

The adoption of disruptive technologies has become increasingly critical for organizations, particularly following the global shifts prompted by the COVID-19 pandemic. Despite the potential benefits, many organizations, including those in the Fast-Moving Consumer Goods (FMCG) industry, face significant hurdles in this transition. Consequently, this study aims to understand the primary challenges and enabling factors influencing the adoption of disruptive technologies for sustainable digital transformation within the South African FMCG sector. A quantitative methodology was employed, utilizing a questionnaire for data collection. Data from 102 respondents were analyzed using SPSS version 28, involving descriptive statistics (mean item score) to rank factors and exploratory factor analysis (EFA) to identify underlying constructs, and a reliability test was carried out with a score of 0.7. Key challenges identified include high initial costs and poor collaboration. Prominent enabling factors include top management commitment and operational cost reduction. The EFA revealed significant underlying challenge dimensions such as “Infrastructural and Resources Constraints” and “Human Factors Constraints,” and enabling dimensions including “Organizational Commitment and Strategy” and “Leadership.” The study concludes with key implications for promoting successful adoption. The adoption of disruptive technologies has become a strategic imperative for sustainable digital transformation (SDT), particularly in emerging markets such as South Africa’s FMCG sector. This study investigates the key challenges and enabling factors shaping technology adoption within this context. A quantitative methodology was employed, using a structured questionnaire distributed to 102 professionals across FMCG organizations in Gauteng. Exploratory factor analysis (EFA) revealed latent dimensions within both challenges and enablers, which were then interpreted through the lens of Rogers’ Diffusion of Innovation (DOI) theory. To enhance analytical clarity, a matrix model was developed linking factor dimensions to DOI attributes such as relative advantage, complexity, compatibility, trialability, and observability. The study found that high initial costs, poor collaboration, and human capability gaps significantly impede adoption, while strong leadership, strategic alignment, and operational cost savings facilitate it. The findings underscore the need for systemic interventions that address not only technical readiness but also leadership, organizational culture, and structural alignment. Practical implications are outlined for both policy and management, particularly in leveraging DOI attributes to accelerate digital transformation, as well optimize innovation diffusion within resource-constrained environments. For the future, the study proposed a hybrid methodology incorporating qualitative interviews to enhance depth and suggests longitudinal tracking to capture temporal shifts in transformation maturity. Full article

Background: Small- and medium-sized enterprises (SMEs) constitute a large portion of the industrial energy demand in the emerging economies, but their shift to renewable energy is not well comprehended at the firm level. Bangladesh is a special case, since the country has adopted national commitments to Sustainable Development Goal 7 on clean energy, but the uptake of renewable energy by SMEs remains minimal due to complex socio-economic factors. Most of the literature has concentrated on household access to energy or national policy models, leaving a gap in empirically validated models of firm-level adoption in the manufacturing sector. Method: Based on the diffusion of innovation theory, institutional theory, and the resource-based view, this research paper formulates and empirically verifies a combined socio-economic model of renewable energy adoption. Partial least squares structural equation modeling (PLS-SEM) was used to analyze a cross-sectional survey of 426 owners and managers of manufacturing SMEs in Bangladesh’s textile and food processing sub-sectors. Findings: Four out of five hypothesized direct relationships were supported. The most important drivers were environmental orientation (β = 0.467, p < 0.001, f² = 0.413), market competitiveness (β = 0.287, p < 0.001, f² = 0.413), policy and institutional factors (β = 0.211, p < 0.001, f² = 0.413), and access to finance (β = 0.096, p = 0.004). Perceptions of cost did not become significant (β= −0.036, p = 0.279). Top management support significantly and negatively moderated the relationship between environmental orientation and adoption (β = −0.093, p = 0.003), possibly because it moderates the substitution mechanism in SME decision-making, which is highly centralized. The model accounted for 64.5% of the variation in renewable energy adoption (R² = 0.645). Conclusion: The results show that attitudinal and institutional factors tend to be more important than financial barriers in determining SMEs’ energy transitions. Environmental consciousness, market incentives, and streamlined institutional access should be the focus of policy interventions to hasten inclusive low-carbon transitions in emerging manufacturing economies. Full article

This empirical study examines how FinTech innovation is adopted, scaled, and sustained in a small and highly regulated market, such as Latvia. The triangulated analytical framework is applied in this study, integrating Rogers’ Innovation Diffusion Theory (IDT), De Meyer’s Innovation Ecosystem framework, and Value Chain Theory. This framework analyses the relationship between innovation characteristics, ecosystem relationships, and restructuring in the value chain. The data was collected from FinTech leaders, conventional financial institutions (banks), regulators, and associations, and was analysed thematically. Based on interviews with stakeholders, the relative advantage of Latvian FinTech lies in its flexibility, speed, and trialability; however, barriers to adoption result in complex regulation, an uneven distribution of technology in infrastructure, and differences in institutional readiness. The authors found strong collaboration among the ecosystem’s players but limited proactive regulatory engagement. This research provides a replicable model for cross-border or cross-sector analysis to assess the progress of innovation in regulatory and Environmental, Social and Governance (ESG) integration. Full article

Grounded in the knowledge-based view and the emerging logic of digital knowledge governance, this study investigates how blockchain adoption strategies reshape inter-firm knowledge-sharing and sustainable innovation. A game theory and decision-optimization model is developed to capture the interplay among blockchain cost, knowledge trust, and collaboration incentives under four adoption scenarios between knowledge creators and users. The results uncover a double-threshold mechanism: when blockchain costs are high, the technology suppresses collaboration by increasing coordination frictions; yet as costs fall below a critical level, blockchain shifts from a trust-reinforcing tool to a catalyst for co-creation efficiency and joint environmental performance. Interestingly, partial adoption can yield a trust paradox-enhancing local reliability but diminish system-wide innovation synergy. As adoption diffuses, the equilibrium dynamically evolves from non-adoption to asymmetry and eventually bilateral digital trust, producing higher social welfare and resilience. Among asymmetric modes, creator-led adoption consistently outperforms user-led adoption, underscoring the strategic value of upstream knowledge transparency. The findings extend the knowledge-based view to the context of digital trust architecture and provide actionable insights for policymakers and firms seeking to build trust-based, knowledge-driven, and digitally sustainable innovation ecosystems. Full article

Traditional approaches to university-level history education often fail to provide immersive and interactive environments that foster deep cognitive engagement. To address these limitations, we developed an AI-enabled virtual museum system that integrates AI-generated content with knowledge graphs through a multi-layered architecture. The system architecture follows a three-tier framework: a front-end interaction layer (Unity/Unreal Engine) for real-time user engagement, a core service layer for intelligent event scheduling and response control (Chat General Language Model/Stable Diffusion), and a data and model layer (My Structured Query Language/MongoDB) to provide structured knowledge. To evaluate the system’s effectiveness, a four-week controlled experiment was conducted with 83 university students. The experimental group using the AI virtual museum showed a significantly higher mean post-test score (84.5 ± 6.8) than that of the control group (71.6 ± 7.9), with statistical significance at p < 0.001, starting from nearly identical baseline scores (61.2 and 60.4 for the experimental and control groups). Correlation analysis was conducted to identify scenario simulations (r = 0.59) and deep inquiry tasks (r = 0.54) as key drivers of learning mastery. By aligning advanced system engineering with educational theory, the results of this study offer a solution for high-fidelity, intelligent digital educational platforms, proposing a validated model for integrated system innovation in education. Full article

This study explores how innovation, economic diversification, and digitalization are boosting Oman’s efforts toward building a smart economy within the context of Oman’s banking and financial regulatory sector, while considering the role of artificial intelligence and governmental support. Supported by the and the Resource-Based View and Innovation Diffusion Theory, this study views innovative and digital competences as key national resources that help governments and organizations to adapt to technological variation and reinforce economic pliability. By using a quantitative approach and convenient sampling, the data were collected through a closed-ended structured questionnaire from 296 individuals representing businesses across Oman and analyzed using SmartPLS 4.0. The results demonstrate that innovation, diversification, and digitalization have a positive and significant impact on governmental support, which eventually plays a mediating role in leading the implementation of a smart economy. Although artificial intelligence was expected to strengthen the effects of digitalization and innovation, the findings reveal that its moderating role is not yet significant, suggesting an early stage of AI diffusion within the banking sector. These results not only confirm Resource-Based View and Innovation Diffusion Theory in an emerging economy but also present practical understandings for business leaders and policymakers. Furthermore, these findings underscore the importance of institutional readiness and diffusion maturity in shaping the role of advanced technologies in smart economy development. This study also suggests that incorporating AI-driven innovation, digital capability development, and strong governance can support Oman to attain the Vision 2040 goals of endorsing diversification, inclusive economic growth, and sustainability in the digital era. Full article

Watershed stewardship programs succeed when intended users progress from awareness to participation. This study applies diffusion of innovations theory to five forestry, agricultural, and economic viability programs administered by the Watershed Agricultural Council in the New York City watershed. These five programs are voluntary and intended to support water quality and community vitality on working lands. A survey of nonindustrial private farm and forest landowners measured awareness, participation, and satisfaction across the watershed programs. Awareness was limited and participation was rare, yet nearly all participants reported high satisfaction, indicating an entry bottleneck at the awareness-to-participation stage. Logistic regression and generalized estimating equations models showed higher participation among landowners with larger acreage. The study recommends strengthening existing extension and outreach to better communicate programs’ relative advantages and increase observability through peer examples and targeted messaging to improve enrollment among eligible landowners. Full article

COVID-19 vaccine hesitancy is well documented, but less is known about booster hesitancy among fully vaccinated adults. A qualitative approach was employed to identify factors affecting COVID-19 booster hesitancy using diffusion of innovation (DoI) theory. The study was conducted in Philadelphia, Pennsylvania. In-depth interviews (n = 30) were done with adults, including those who had (n = 9) and had not (n = 21) been boosted. Participants were categorized into DoI adopter groups or a “refuser” group for those with no intention of getting boosted. Transcripts were analyzed using an iterative coding process with consensus and triangulation to develop thematic categories. Participants had a mean age of 41 and were 63.3% Black; 20% were classified as innovators, 6.7% early adopters, 3.3% early majority, 6.7% late majority, 43.3% laggards and 20% refusers. Three themes varied across groups: level of perceived risk susceptibility of getting COVID-19 in the future, information needs and levels of vaccine literacy, and effects of ongoing institutional mistrust. Those in the laggard and refuser groups generally had lower vaccine literacy, higher levels of institutional mistrust, and were more likely to listen to friends and family for booster advice, all consistent with DoI adopter characteristics. These differences indicate important intervention targets to promote booster uptake, especially in those who have been previously vaccinated. Full article

Sustainable territorial development seeks to balance economic growth, social well-being, and environmental preservation across spatial contexts. In fragile and resource-constrained regions, achieving this balance remains particularly challenging. With the growing diffusion of artificial intelligence (AI), digital tools are increasingly presented as potential enablers of sustainability-driven territorial strategies. This study explores the role of AI in supporting sustainable territorial development across rural and urban areas of North Lebanon, a region characterized by infrastructural deficits, governance constraints, and socio-economic vulnerability. Adopting a qualitative research design, the study draws on semi-structured interviews with five key stakeholders from the public sector, civil society, business, and sustainability expertise, complemented by an illustrative case study of the proposed AI-enabled redevelopment of Klayaat (René Mouawad) Airport. The findings reveal that while stakeholders recognize AI’s potential to enhance resource optimization, smart agriculture, urban mobility, and disaster preparedness, its effective adoption remains constrained by limited digital infrastructure, insufficient policy frameworks, funding shortages, and gaps in digital literacy. Interpreted through the lenses of the Triple Bottom Line and Diffusion of Innovation theories, the results show that AI-driven sustainability outcomes in fragile territorial contexts are highly conditional on institutional readiness, governance capacity, and contextual alignment. The study contributes to the literature by providing context-specific insights into AI-enabled sustainable development in a developing and crisis-affected region, highlighting the need to complement technological innovation with policy reform, capacity building, and inclusive territorial governance. Full article

This study rethinks innovation diffusion in craft-based small and medium-sized enterprises (SMEs) by examining how cultural logics and collective governance shape selective digitalization. Drawing on a qualitative case of Ata handicraft SMEs in Bali, Indonesia, the study analyzes in-depth interviews with artisans through the lens of Innovation Diffusion Theory. The findings reveal that digital technologies are not rejected but adopted selectively, mediated by Balinese Hindu philosophies such as Tri Hita Karana, Tat Twam Asi, and Segilik Seguluk Selunglung Sebayantaka, which emphasize balance, relational ethics, and communal solidarity. Rather than pursuing efficiency-driven digital adoption, artisans prioritize collective control, cultural continuity, and equitable value distribution. Digital tools function primarily as complementary mechanisms—supporting coordination, documentation, and market interaction—rather than as transformative drivers of organizational change. This study contributes theoretically by extending Innovation Diffusion Theory beyond linear adoption models, demonstrating how culturally grounded governance structures recalibrate the meaning and trajectory of digital innovation. More broadly, it offers insights for inclusive innovation discourse by showing how collective institutions enable SMEs to engage with digitalization while safeguarding cultural integrity and social sustainability. Full article