Search Results (397)

Juniperus przewalskii Komarov, an endemic conifer in the high-altitude mountains of the Qinghai–Tibet Plateau, develops its cones in a synergistic manner with the oligophagous pest Megastigmus sabinae Xu et He (Hymenoptera: Torymidae), forming a highly specialized interaction system. However, the physiological adaptation mechanisms underlying this interaction remain unclear. Feeding by M. sabinae larvae significantly induced defense responses in J. przewalskii cones. During the early instars (2nd~3rd) of M. sabinae larvae, infested J. przewalskii endosperms upregulated protein content (48.91%; 3rd instar), significantly enhanced peroxidase (POD) activity (71.10%; 2nd instar), and specifically enriched coumarins and cinnamaldehyde derivatives (2nd instar) to increase M. sabinae larvae metabolic costs. In later instars (4th~5th) of M. sabinae larvae, the infested endosperms downregulated starch content (29.69%; 4th instar), increased phenylalanine ammonia-lyase (PAL) activity (57.34%; 4th instar), and accumulated steroid derivatives to suppress larvae development. Conversely, M. sabinae larvae demonstrated unique adaptive strategies: maintaining high levels of glutathione S-transferase (GST) as an antioxidant defense system during early instars and upregulating the level of digestive enzymes in later stages to overcome host multi-layered defenses. Juniperus przewalskii counters pest infestation through dynamic nutrient modulation, temporal activation of protective enzymes, and a multi-layered chemical defense network. The adaptation of M. sabinae larvae appears to involve the developmental regulation of detoxification and digestive enzyme levels. This study provides novel insights that enrich coevolution theory in alpine ecosystems. Full article

The entrepreneurial ecosystem theory posits that regional development emerges from synergistic interactions among entrepreneurs, institutions, and markets. This study positions entrepreneurial vitality as the core catalyst synchronizing digital inclusive finance (DIF) with rural revitalization—two systems often advancing in isolation, leading to unbalanced rural development. Using a coupling coordination degree model and provincial panel data from China (2011–2020), we demonstrate that entrepreneurial vitality significantly strengthens DIF–rural revitalization coupling coordination, following a nonlinear threshold pattern. Coordination gains accelerate only after vitality passes empirically identified critical levels, explaining persistent regional disparities in coupling coordination. Furthermore, the vitality–coordination link is moderated by technological infrastructure, organizational electronic commerce (e-commerce) engagement, and regional economic development, as outlined by the Technology–Organization–Environment framework. Framing DIF as an e-commerce-related ICT input, this paper advances the entrepreneurial ecosystem, e-commerce, and ICT-for-development (ICT4D) literature by revealing the threshold-driven nature of resource coordination in rural contexts. The findings offer a contextualized framework for catalyzing balanced and inclusive rural development in emerging economies. Full article

The global shift toward decarbonization and the rise of the digital economy are compelling manufacturing firms to undergo a complex twin transformation across their structures, operations, and value chains. Business model innovation (BMI), especially in digital servitization (DSBMI), emerges as a crucial catalyst in facilitating this change. However, there is a lack of systematic exploration of how DSBMI influences corporate decarbonization (CD). To fill this knowledge gap, a comprehensive qualitative meta-analysis of 27 case studies was conducted, identifying multiple DSBMI practices for CD employed by industrial firms. These practices can be summarized into three main types: efficiency DSBMI, novelty DSBMI, and convergent DSBMI. A system has at least two of these, while all three may coexist. Based on dynamic capabilities theory, this study also introduces six roles for the three types of DSBMI practices, which interact to help firms sense opportunities, seize them through BMI, and transform their operations and ecosystems—collectively enabling decarbonization through internal optimization (efficiency DSBMI), downstream innovation (novelty DSBMI), and value chain-wide cooperation (convergent DSBMI). The findings offer a comprehensive theoretical framework that guides companies to achieve economic benefits while advancing their CD goals through multi-level BMI strategies. Finally, the study discusses its limitations and proposes directions for future research. Full article

The purpose of this study was to develop and validate an integrated model explaining how AI-enabled knowledge integration and digital ecosystem connectivity influence knowledge innovation capability through the mediating role of knowledge agility and the moderating roles of digital trust and organizational learning culture. Grounded in the Knowledge-Based View (KBV) and Dynamic Capability Theory (DCT), this research seeks to understand how technological and cultural enablers jointly drive exploratory, exploitative, and adaptive innovation. A quantitative cross-sectional research design was employed, and data were collected from 243 professionals working in knowledge-intensive organizations. Measurement scales were adapted from previous studies, and data analysis was conducted through structural equation modeling, using SmartPLS 4. Reliability, validity, and path analyses were performed to test the hypothesized relationships among constructs. The results indicated that AI-enabled knowledge integration and digital ecosystem connectivity significantly enhance knowledge agility, which in turn positively affects knowledge innovation capability. The mediation tests confirmed the role of knowledge agility, while digital trust and organizational learning culture were confirmed to strengthen the relationship between knowledge agility and innovation capability. This study contributes to theory by integrating technological, organizational, and cultural perspectives into a unified model of digital innovation. Practically, it guides organizations in leveraging AI systems, digital connectivity, and learning culture to foster sustainable innovation. Full article

Research on users’ switching intentions in peer-to-peer (P2P) mobile payment systems, particularly in developing markets, remains limited. This study examines how two satisfaction dimensions, transaction-based satisfaction and experience-based satisfaction, influence switching intentions through two layers of trust: institution-based trust and disposition to trust. Grounded in Expectancy-Disconfirmation Theory, data from 529 users of Haiti’s leading P2P mobile payment platform were analyzed using structural equation modeling. Results show that while transaction-based satisfaction has minimal impact on switching intentions, experience-based satisfaction strengthens institution-based trust, which in turn significantly reduces switching intentions. These findings highlight the central role of institutional reliability in shaping post-adoption behavior in duopolistic and resource-constrained markets. The study extends satisfaction-trust theory to digital financial ecosystems and offers practical insights for improving user retention through sustained institutional credibility and long-term service reliability. Full article

The global demand for argan oil has grown considerably in recent years, creating economic opportunities while raising concerns about ecosystem degradation and the sustainability of production systems. To support long-term viability, several initiatives have promoted environmentally friendly practices and fair value-chain models. However, the effective market integration of these initiatives depends on understanding consumer behavior and preferences toward sustainable products. This study aims to identify the determinants influencing consumers’ purchase intention for sustainable argan oil using an extended framework of the Theory of Planned Behavior (TPB). A structural equation modeling approach was applied to analyze responses from adult consumers with a minimum education level of secondary education. The results show that consumer attitude, perceived behavioral control, and willingness to pay have significant positive effects on purchase intention, while ecological literacy exerts an indirect influence through attitude, social norms, perceived behavioral control, and willingness to pay. In contrast, ecological literacy has no significant direct impact. These findings improve the understanding of behavioral mechanisms underlying green product consumption and offer insights into designing marketing strategies that align with sustainability values and promote responsible consumer choices. Full article

Zero-Touch Network (ZTN) represents a cornerstone approach of Next Generation Networks (NGNs), enabling fully automated and AI-driven network and service management. However, their distributed and multi-domain nature introduces critical security challenges, particularly regarding service identity and data integrity. This paper proposes a novel blockchain-based framework to enhance the security of ZTN through two complementary mechanisms: decentralized digital identity management and oracle-assisted network monitoring. First, a Decentralized Identity Management framework aligned with Zero-Trust Architecture principles is introduced to ensure tamper-proof authentication and authorization in a trustless environment among network components. By leveraging decentralized identifiers, verifiable credentials, and zero-knowledge proofs, the proposed Decentralized Authentication and Authorization component eliminates reliance on centralized authorities, while preserving privacy and interoperability across domains. Second, the paper investigates blockchain oracle mechanisms as a means to extend data integrity guarantees beyond the blockchain, enabling secure monitoring of Network Services and validation of Service-Level Agreements. We propose a four-dimensional framework for oracle design, based on qualitative comparison of oracle types—decentralized, compute-enabled, and consensus-based—to identify their suitability for NGN scenarios. This work proposes an architectural and design framework for Zero-Touch Networks, focusing on system integration and security-aware orchestration rather than large-scale experimental evaluation. The outcome of our study highlights the potential of integrating blockchain-based identity and oracle solutions to achieve resilient, transparent, and self-managed network ecosystems. This research bridges the gap between theory and implementation by offering a holistic approach that unifies identity security and data integrity in ZTNs, paving the way towards trustworthy and autonomous 6G infrastructures. Full article

Conventional research on digital business development offers a limited view, overwhelmingly concerned with the isolated effects of individual variables while overlooking their synergistic relationships. This study challenges this reductive perspective by applying fuzzy set Qualitative Comparative Analysis (fsQCA) to Chinese city-level data. We specifically investigate how elements from the socio-technical framework interact synergistically to shape the urban digital business ecosystem. The results demonstrate that no single factor is sufficient as a determinant. Instead, we observe equifinality, meaning multiple distinct configurations can lead to equally high performance. Furthermore, the causal configurations for failure are not mirror images of those for success but instead exhibit a distinctive pattern. The influence of government size exemplifies this asymmetry. For policymakers, the implication is that effective strategies for urban digital business must be holistic and context sensitive, moving beyond universal prescriptions. Full article

Based on a sample of Chinese listed firms from 2010 to 2024, this study employs a complex adaptive systems (CAS) lens to investigate the spillover effects of core-firm digital transformation (CDT) on innovation within supply chain networks. It reveals that CDT fosters supplier innovation while impeding customer innovation. Heterogeneity analysis shows that the spillover effect is more pronounced when suppliers (customers) are non-state-owned, larger, more competitive, and have more able managers. Mechanism analysis suggests that the spillover effect is realized through resource and competition mechanisms. This study contributes to the literature by integrating CAS theory with established supply chain management perspectives to provide a systemic understanding of digital transformation’s ripple effects, offering valuable insights for both managers navigating digital ecosystem evolution and policymakers designing industrial innovation strategies. Full article

In developing countries, technology-based startups (TBSs) play a vital role in driving innovation, and they significantly contribute to the generation of jobs and economic development. However, despite their importance, startups have a high failure rate worldwide, and a major contributing factor is a lack of funding. The objective of this study is to compare the existing financing mechanisms in Ethiopia, Uganda, and Kenya and determine the relative position of Ethiopia in the financing landscape. This study was based on resource-based theory and signaling theory. A desk research methodology was employed, and a total of 70 sources were reviewed. The data sources include academic literature, publications from the World Bank, local reports, government policies of the three nations, articles published in reputable journals, and global database indexes. Articles were also selected based on their relevance to the research question and the credibility of the publication. The comparison was carried out based on identifying similarities and differences in economic indicators, the innovation performance of the countries, the innovation eco-system, the types of existing financing mechanisms in each country, and various government policies and initiatives. We also validated our findings by cross-checking information from multiple sources to avoid bias. The results reveal that Ethiopia is lagging behind in most of the parameters set for comparison, while its neighbors, Uganda and Kenya, have a relatively better status in general. Finally, this study has theoretical and practical implications. Full article

In the era of sustainable digital transformation, organizations increasingly rely on artificial intelligence (AI) to enhance efficiency, innovation, and long-term competitiveness. However, employees’ psychological barriers, including technostress and innovation resistance, continue to constrain successful and sustainable AI adoption. Grounded in Social Exchange Theory (SET), Conservation of Resources Theory (COR), Diffusion of Innovation Theory (DOI), and the Technology Acceptance Model (TAM), this study develops an integrated model linking perceived organizational support (POS)—comprising emotional, informational, and instrumental dimensions—to employees’ sustainable AI adoption through the dual mediating roles of technostress and innovation resistance. Based on 426 valid responses collected from multiple industries, a triadic hybrid approach combining Structural Equation Modeling (SEM), Artificial Neural Networks (ANNs), and Necessary Condition Analysis (NCA) was applied to capture both linear and nonlinear mechanisms. The results reveal that Informational Support (IFS) is the most influential factor and constitutes the sole necessary condition for high-level AI adoption, while emotional and instrumental support indirectly promote sustainable adoption by mitigating employees’ stress and resistance. This study contributes to sustainable management and AI adoption research by providing insights into the potential hierarchical and threshold patterns of organizational support systems in digital transformation. It also provides managerial implications for designing transparent, empathetic, and resource-efficient support ecosystems that foster employee-driven intelligent transformation. Full article

This study presents a systematic literature review of 58 peer-reviewed publications on blockchain-based project management to examine the dominant research methods and theoretical approaches in the field. Using an established Information Systems theory classification framework, the review classifies existing studies into four categories: Explicit Theory-Driven, Conceptual/Framework-Oriented, Design Science/Artifact-Oriented, and Descriptive/Empirical without Theory. Findings reveal that current research is largely technology-centric, with nearly 70% of studies adopting design-science or artifact-oriented methods and fewer than 10% engaging explicit theoretical foundations. This indicates that blockchain-project management scholarship remains in a pre-theoretical stage, focusing primarily on prototype development rather than explanatory or predictive theorizing. A clear method–theory coupling also emerges, where design-science methods align with artifact creation, quantitative surveys with theory-driven studies, and qualitative cases with descriptive work. Temporal patterns show gradual movement toward theory-informed and mixed-method research, signaling early maturation of the field. The review concludes by outlining three priorities for future research: translating design insights into theoretical constructs, developing hybrid frameworks that integrate behavioral and institutional perspectives, and adopting multi-level approaches to examine blockchain’s impact across project ecosystems. These insights provide a structured foundation for advancing both scholarly theory and practical applications in blockchain-enabled project management. Full article

This study investigates the dynamic behavior of a Lotka–Volterra amensalism system subject to non-selective harvesting, regulated by wind speed. We develop a coupled windharvesting population model that captures the dual regulatory mechanism of wind as an environmental factor on the marine ecosystem: it weakens the amensalistic interaction between species by enhancing the dilution of inhibitory substances while simultaneously suppressing human harvesting intensity by impeding fishing operations. Using stability theory and the Lyapunov function method, we systematically analyze the existence and stability of equilibrium points and explore the ecological state transitions driven by varying wind speed. The results show that the system admits four possible equilibrium states. Among them, the positive equilibrium, whenever it exists, is globally asymptotically stable. As wind speed increases, the system undergoes sequential ecological regime shifts: from extinction of both species to dominance by a single species and finally to stable coexistence of both species. Numerical simulations confirm the theoretical findings and reveal the intrinsic mechanism by which wind promotes biodiversity: by reducing harvesting pressure and mitigating the amensalistic effect. The concept of critical wind speed proposed in this work offers a quantitative basis for managing wind conditions in marine protected areas and designing adaptive harvesting strategies, holding significant implications for marine conservation and sustainable fishery development. Full article

Based on existing models, this paper incorporates some key ecological factors, thereby obtaining a class of eco-epidemiological models that can more objectively reflect natural phenomena. This model simultaneously integrates disease dynamics within the prey population and the Beddington–DeAngelis functional response, thus achieving an organic combination of ecological dynamics, epidemic transmission, and spatial movement under time-varying environmental conditions. The proposed framework significantly enhances ecological realism by simultaneously accounting for spatial dispersal, predator–prey interactions, disease transmission within prey species, and seasonal or temporal variations, providing a comprehensive mathematical tool for analyzing complex eco-epidemiological systems. The theoretical results obtained from this study can be summarized as follows: Firstly, the existence and uniqueness of globally positive solutions for any positive initial data are rigorously established, ensuring the well-posedness and biological feasibility of the model over extended temporal scales. Secondly, analytically tractable sufficient conditions for uniform population persistence are derived, which elucidate the mechanisms of species coexistence and biodiversity preservation even under sustained epidemiological pressure. Thirdly, by employing innovative applications of differential inequalities and fixed point theory, the existence and uniqueness of a positive spatially homogeneous periodic solution in the presence of time-periodic coefficients are conclusively demonstrated, capturing essential rhythmicities inherent in natural systems. Fourthly, through a sophisticated combination of the upper and lower solution method for parabolic partial differential equations and Lyapunov stability theory, the global asymptotic stability of this periodic solution is rigorously established, offering a powerful analytical guarantee for long-term predictive modeling. Beyond theoretical contributions, these research findings provide actionable insights and quantitative analytical tools to tackle pressing ecological and public health challenges. They facilitate the prediction of thresholds for maintaining ecosystem stability using real-world data, enable the analysis and assessment of disease persistence in spatially structured environments, and offer robust theoretical support for the planning and design of wildlife management and conservation strategies. The derived criteria support evidence-based decision-making in areas such as controlling zoonotic disease outbreaks, maintaining ecosystem stability, and mitigating anthropogenic impacts on ecological communities. A representative numerical case study has been integrated into the analysis to verify all of the theoretical findings. In doing so, it effectively highlights the model’s substantial theoretical value in informing policy-making and advancing sustainable ecosystem management practices. Full article

This study integrates complex systems theory and innovation ecosystem theory to develop a unified framework encompassing the innovation environment, innovation actors, and innovation networks. Using fsQCA and NCA, it examines the impact of cross-layer interactions and the coupling of multiple factors on collaborative performance. Empirical analysis in the field of natural language processing (NLP) demonstrates that no single factor is sufficient to serve as a necessary condition for achieving high-innovation collaboration performance. Innovation actors, as endogenous evolutionary drivers, play a central and catalytic role in the collaboration process. Moreover, under specific conditions, the relationship between the innovation environment and innovation networks exhibits a substitutive effect, with certain capabilities enabling this dynamic. This study extends the theoretical understanding of collaboration pathways within innovation ecosystems and offers practical recommendations for fostering innovation cooperation across different industries and organizations. It achieves this by constructing a “situational type–configuration path” matrix, decision tree, and innovation collaboration performance realization model. Full article