Search Results (268)

This paper systematically examines the core of new quality productive forces underpinning the sustainable development of the low-altitude economy industry. Based on the Triple Bottom Line theory, it analyzes the interrelationships among various factors of new quality productive forces and reveals the underlying mechanism through which new quality productive forces drive sustainable development in this sector. By employing an integrated Fuzzy Decision-Making Trial and Evaluation Laboratory—Interpretive Structural Modeling (Fuzzy-DEMATEL-ISM) approach, this study establishes a hierarchical structure for sustainable development in the low-altitude economy industry grounded in the logical framework of new quality productive forces. The findings indicate that: (1) the strategic origin layer represents the prerequisite and most critical task for the emergence of the low-altitude economy industry; (2) the technological breakthrough layer constitutes the core competitive strength enabling its development; (3) the resource guarantee layer provides essential resource support for operational sustainability; (4) the institutional synergy layer enhances industrial efficiency through coordinated governance; and (5) the value realization layer signifies the ultimate form of industrial evolution. These research outcomes offer significant forward-looking insights for advancing sustainable development in the low-altitude economy industry. Full article

The revitalization of idle rural homesteads constitutes a key policy instrument for promoting rural revitalization and enhancing rural household income. However, existing studies predominantly adopt a single-actor or policy-instrument perspective and lack a systematic examination of the complex coupling relationships among multiple actors, resource endowments, and institutional environments. Adopting a rural operational perspective, this study explores how internal and external elements interact to reshape rural systems and identifies the configurational paths through which multiple actors’ behavioral logics drive efficient idle homestead revitalization. Drawing on symbiosis theory, we constructed a systemic analytical framework. A mixed-methods design combining fuzzy-set Qualitative Comparative Analysis and case studies of 35 typical villages in Zhejiang Province was employed. The findings reveal that (1) there exist four equifinal high-performance paths—market-driven, government-led, multi-actor co-governance, and endogenous development; (2) efficient revitalization does not rely on any single actor but depends on the dynamic alignment between actor behavioral logics, resource endowments, and the institutional environment; and (3) a robust policy environment can compensate for resource endowment deficiencies, whereas superior resource conditions allow for optimal efficiency, even with streamlined actor participation. Theoretically, this study extends symbiosis theory to the field of rural governance. Practically, it offers transferable governance solutions for Global South countries confronting rural decline and addressing rural poverty. Full article

This paper investigates engineering decision optimization in uncertain environments. Subject to constraints on cost and expected returns, engineering decisions optimize material input, equipment selection and process arrangement to minimize costs and maximize economic benefits. As an efficient formal verification technique, model checking offers a new approach to addressing this problem. Traditional model checking focuses on qualitative verification, while quantitative approaches, including probabilistic and possibilistic model checking, have been gradually developed. Among them, possibilistic model checking is more applicable to systems with fuzzy uncertainty. However, existing possibilistic model-checking techniques have notable limitations: they are only designed for closed systems and ignore interactions between the system and external environments; their simplistic information aggregation leads to information asynchrony and loss; and they cannot model and verify systems with incomplete information. Model checking based on possibilistic decision processes enables the selection of uncertain actions and initially resolves the modeling and verification of open systems. In our previous work, we introduced quality constraints into possibilistic temporal logic to mitigate information asynchrony and loss. We also established the theories of intuitionistic fuzzy Kripke structure (IFKS) and Intuitionistic Fuzzy Computation Tree Logic (IFCTL), which support the modeling and verification of systems with incomplete information. To improve the practicality and accuracy of engineering decisions, this study adopts the ideas of uncertain decision-making behavior selection, quality constraints and incomplete information modeling. It extends IFKS to the Weighted Intuitionistic Fuzzy Kripke Structure (WIFKS) and evolves IFCTL into the intuitionistic fuzzy decision tree logic (IFDTL). We further propose an IFDTL model-checking algorithm and a multi-attribute engineering decision algorithm based on the proposed method, along with corresponding correctness proofs and complexity analysis. A case study on Qinling health-preserving tourism planning verifies the rationality and effectiveness of the presented approach. This research provides a novel formal solution for engineering decision-making under uncertainty. Full article

This study presents an adaptive learning framework that integrates fuzzy logic and learning analytics to support personalized education and multi-factor student assessment. The proposed system combines cognitive and behavioral indicators to provide an interpretable representation of the learner’s state within a dynamic digital learning environment. The architecture is based on adaptive learner modeling and classroom-level monitoring mechanisms, enabling personalized guidance, adaptive content sequencing, and continuous performance monitoring at both individual and classroom levels. A core contribution of the approach is a fuzzy logic-based evaluation mechanism that aggregates multiple signals, including quiz performance, time spent on theory, help-seeking behavior, and system interaction patterns. These inputs are transformed into fuzzy sets and combined through inference rules to produce interpretable learning level estimates aligned with Bloom’s taxonomy. The approach is grounded in Vygotsky’s Zone of Proximal Development, supporting adaptive scaffolding and targeted instructional interventions. The evaluation results demonstrate a strong correlation between the model outputs and conventional exam performance (r ≈ 0.91), while exhibiting reduced variability (SD ≈ 0.15 compared to SD ≈ 0.20), indicating a more stable representation of learner performance. Furthermore, statistical analysis confirms that the differences between traditional and model-based scores are significant (p < 0.01), suggesting that the proposed approach captures additional dimensions of learner behavior beyond conventional grading metrics. Overall, the findings indicate that integrating fuzzy reasoning with behavioral analytics enables a more interpretable, stable, and pedagogically grounded approach to learner assessment, supporting adaptive and interpretable personalized learning. Full article

As an important medium for conveying rich historical and cultural information, the decorative elements of ancient Chinese timber architecture still lack a systematic understanding of their intrinsic cultural logic in current research and conservation practices. Guided by the cultural gene theory, this study systematically analyzes the wooden decorations of the Luzhai complex in Dongyang, Zhejiang, and constructs a “tangible–intangible” gene map comprising 24 relevant factors, including form, craftsmanship, and symbolic meaning. Through AHP-FCE (Analytic Hierarchy Process- Fuzzy Comprehensive Evaluation) quantitative analysis, 126 typical components from 427 decorative samples (including 165 from the Ming Dynasty and 262 from the Qing Dynasty) in the Ming and Qing Dynasty Luzhai in Dongyang were coded and quantitatively evaluated. The results indicate that the Ming-dynasty wooden architectural decorations in the Luzhai complex are characterized by botanical patterns, relief carving, and Confucian ethics, embodying restraint and ritual order; whereas Qing-dynasty decorations are characterized by animal patterns, round carving, and status symbols, reflecting sociocultural and economic transformation. This study provides a methodological framework for interpreting regional architectural decoration and offers theoretical and practical support for the conservation and digital preservation of traditional architectural heritage. Full article

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

This study analyzes tourist loyalty in the Monarch Butterfly Biosphere Reserve by integrating affinity-based segmentation and the Forgotten Effects Theory within a fuzzy logic framework. The objective was to identify how visitor affinities condition the indirect construction of loyalty in contexts of high environmental complexity. Data were collected through a structured questionnaire administered to 316 tourists using a non-probabilistic sampling approach. Using the Pichat Algorithm and the Forgotten Effects Theory, the research captured gradual membership patterns and mediated relationships that conventional models often overlook. Results indicate that, while age, particularly Generation X, acts as a connecting axis, postgraduate education levels generate a polarization of visitor perceptions across segments. Significant forgotten effects (up to 0.30) were identified, suggesting that variables such as satisfaction, entertainment, and relaxation act as mediating mechanisms between learning, perceived value, and the intention to revisit. This study suggests that loyalty is not constructed directly but is indirectly shaped by affinity-based visitor structures. It recommends that management strategies evolve toward environmental edutainment models and that marketing efforts be diversified according to differentiated visitor profiles. These findings demonstrate the utility of fuzzy logic for the strategic management of high-value ecological destinations. Full article

In future active distribution networks with high penetrations of renewable energy, flexible loads are expected to play an increasingly important role as reserve resources to support the sustainable and reliable operation of power grids. Accurate evaluation of flexible load reserve capacity is therefore essential for reliable reserve scheduling. Existing research mainly focuses on the operational characteristics and physical constraints of flexible loads, while insufficiently accounting for user response willingness and the uncertainty of user decision-making behavior, which may lead to biased reserve capacity assessments and impair the sustainability of reserve supply in actual grid operation. To address this issue, this paper proposes a results-oriented reserve capacity evaluation method for flexible loads that explicitly incorporates user response willingness. Specifically, a fuzzy logic system is developed to quantitatively characterize the response willingness of electric vehicle (EV) and air-conditioning (AC) users under multiple influencing factors. Then, a probabilistic modeling approach for user decision-making behavior is established using the theory of planned behavior, enabling explicit representation of behavioral uncertainty. Furthermore, a comprehensive reserve capacity evaluation framework for flexible loads is constructed by integrating user willingness states, sustainable response duration, and operational power constraints. Finally, the case studies demonstrate that the proposed method can effectively improve the objectivity of flexible load reserve capacity assessments while maintaining high user participation willingness, thus supporting the long-term sustainable application of flexible loads as grid reserve resources. Full article

The research landscape in tourism and hospitality often feels like a house divided. On one side, there is the quantitative camp searching for broad, linear patterns; on the other side, there are qualitative scholars who prefer deep, contextual dives. This division suggests that scholars may overlook valuable insights in the middle. Therefore, this study examines how Fuzzy-Set Qualitative Comparative Analysis (fsQCA) and Necessary Condition Analysis (NCA) are transforming the landscape and bridging the methodological and analytical divide. For this purpose, authors analyzed 91 peer-reviewed articles using PRISMA 2020 systematic review principles from six databases. The findings highlight that this multi-methodological triangulation addresses causal asymmetry, acknowledging that the drivers of success are not necessarily mirror images of those of failure. The study implies that, in theory, it bridges the gap between qualitative nuance and quantitative rigor, moving from universal linear assumptions to complexity theory. Methodologically, it allows for a prioritized roadmap in which NCA pinpoints exact operational thresholds and fsQCA provides strategic flexibility. In practice, the findings offer a two-tiered decision-making framework for industry managers: first, addressing non-negotiable bottlenecks, and second, selecting the strategic configuration that best aligns with their unique resource base. The review concludes that, while challenges such as data calibration and interpretative complexity remain, integrating these paradigms offers a more authentic and comprehensive understanding of the volatile landscape of tourism and hospitality. Full article

Corporate risk-taking, crucial for sustainable development, is shaped by the interplay of multiple institutional logics. However, existing research lacks a systematic understanding of how government, market, and technology logics collectively drive corporate risk-taking. This study addresses this gap by employing fuzzy-set Qualitative Comparative Analysis on data from Chinese intelligent manufacturing firms to explore the configurational pathways leading to high risk-taking. Our analysis reveals three distinct pathways: (1) An innovation-driven transformation pathway, characterized by a strong synergy between government and technology logics, with market logic playing a supplementary role. (2) A green transformation pathway, where government logic dominates, supported by market and technology logics in a hierarchical structure. (3) A resource synergy pathway, marked by the high-level integration of all three logics for strategic breakthroughs. Theoretically, this study advances institutional theory by developing an integrative framework that moves beyond a single-logic perspective, revealing the synergistic and substitutive relationships among multiple logics. Practically, our findings provide managers with a configurational roadmap for strategically aligning with institutional forces to enhance risk-taking capacity. Full article

The Internet of things (IoT) is rapidly pervading daily life and linking everything. Although higher connectivity offers many benefits, including higher productivity, robotic processes, and decision-making guided by data, it also poses a number of security dangers. Modern risks to data authenticity and confidence are getting harder to handle through typical central safety solutions. In this paper, we present a detailed investigation of the latest innovations and approaches for assessing reputation and confidence in the blockchain-empowered Internet of Things (BIoT) area. A comprehensive literature search was conducted across major electronic databases, including IEEE, Springer, Elsevier, Wiley, MDPI, and top indexed conference proceedings. The publication year was restricted to the period from 2018 to 2025. The methodological quality of a total of 122 studies met the inclusion criteria assessed using predefined quality measures. We figure out existing flaws at each layer of IoT architecture, illustrating how autonomous, transparent, and impenetrable blockchain ledgers address these flaws. Plus, we analytically compare public, private, consortium, and hybrid blockchain networking architectures to emphasize the underlying compromises among security, reliability, and decentralization. We also assess how reputation evaluation techniques evolved over time, moving from classical fuzzy logic and weighted average models to modern mature game theory and machine learning (ML) models, addressing their limitations in terms of computational overhead, scalability, adaptability, and deployment feasibility in IoT systems. Additionally, we outline future directions for BIoT system trust assessment and identify research limitations and potential solutions. Our research indicates that although ML-driven models offer more accurate predictions for identifying illicit node activities, they are still constrained by limited unbalanced data and high processing overhead. Full article

Comprehensively integrating eco-farms and rural tourism represents a crucial pathway for advancing rural revitalization and sustainable development; however, existing research has pre-dominantly focused on the net effects of individual factors, failing to reveal the underlying complexity of multiple co-occurring factors and their interactive logics. With the aim of addressing this theoretical gap, we employ a configurational approach that integrates Necessity Condition Analysis (NCA) with fuzzy set qualitative comparative analysis (fsQCA), and data was collected from 1041 Chinese ecological farms (ecological farm operators) using a structured questionnaire, to systematically explore the integrated complex configurational driving logic. Our findings reveal that no single necessary condition independently causes high-level integration. The fsQCA results further reveal that high-level integration is attainable via two distinct, yet equivalent pathways. First, the “Endogenous–Technological–Economic Synergistic Drive Model” emphasizes the intrinsic development needs of business entities, requiring extensive synergy with external technological empowerment and the regional economic environment; second, the “re-source–market–integration linkage-driven” pathway leverages unique resource endowments and achieves value transformation through efficient resource integration capabilities, guided by clear market demand. Both pathways exhibit functional substitutability among their conditions, demonstrating strategic systemic flexibility. Additionally, in the analysis of non-high-integration configurations, we draw upon structural hole theory to categorize systemic failures caused by missing key connections or factor misalignment. Full article

This paper introduces the concept of interval-valued intuitionistic fuzzy n-fold implicative filters in hoop algebras and explores their fundamental properties. We establish several new and equivalent characterizations, investigate their closure properties, and provide explicit algorithms for their construction and verification. Furthermore, we examine the relationships between interval-valued intuitionistic fuzzy n-fold implicative filters, interval-valued intuitionistic fuzzy filters, and classical n-fold implicative filters. The results presented here extend beyond straightforward generalizations, offering both practical tools and theoretical insights that are not previously available in the literature. The results presented here build upon earlier studies by systematically characterizing interval-valued intuitionistic fuzzy n-fold implicative filters in hoop algebras. Several new equivalent conditions and computational methods are introduced, and relationships with existing filter concepts are clarified. Full article

The development of China’s marine food production system is receiving increasing attention, as its developmental level and obstacle factors will profoundly impact the nation’s future food security and nutritional supply. This study establishes a theoretical framework for evaluating the development level of marine food production systems based on three dimensions—resources, benefits, and governance—structured around the logical framework of “exogenous safeguard, endogenous drive, goal oriented”. First, a three-tier coding method based on grounded theory was employed to construct a Chinese marine food production system evaluation framework encompassing 28 specific indicators. Subsequently, a comprehensive weighting of these indicators was achieved by integrating fuzzy comprehensive evaluation with the entropy weighting method. Finally, based on the evaluation results and obstacle degree modeling, a comprehensive assessment study was conducted on 11 coastal provinces and cities, focusing on developmental level investigation and obstacle factor analysis. The results indicate that China’s marine food production system development level exhibits a trend of slow, fluctuating growth overall, maintaining an average annual growth rate of 3.23%. However, significant differentiation characteristics are emerging, with high regional heterogeneity and substantial variation in obstacle factors. Currently, the main constraints hindering the development of the marine food production system are insufficient human resource supply, uneven production resource distribution (higher in the north, lower in the south), and intensified fluctuations in comprehensive output. Finally, this study proposes three strategic recommendations: ecological restoration coupled with strict controls, comprehensive restructuring of the human resource support system, and establishing a multi-scale comprehensive evaluation mechanism. These strategies aim to disrupt the transmission mechanisms of different obstacle factors and accelerate the rapid development of the marine food production system. Full article

This study investigates the impact of sustainability-related uncertainty (SRU)—captured via the Sustainability-related Uncertainty Index in equal-weighted (ESGUI_EQ) and GDP-weighted (ESGUI_GDP) forms—on the volatility of green financial assets, focusing on decentralized finance (DeFi) protocols and Environmental, Social, and Governance (ESG)-focused Exchange-Traded Funds (ETFs). Employing a fuzzy logic framework, complemented by 3D surface visualization, Rule Viewer analysis, diagnostic validation, and Granger causality tests, the study uncovers non-linear, asymmetric, and time-varying responses of these assets to sustainability ambiguity. Empirical results reveal a structural divergence: DeFi protocols amplify volatility due to fragmented governance, speculative investor behavior, and sensitivity to policy-driven signals, often exhibiting bidirectional predictive feedback with SRU, whereas ESG ETFs maintain stability through diversification, regulatory oversight, and rigorous ESG screening, primarily absorbing sustainability shocks. These findings extend sustainable finance theory by integrating governance, technology, and policy dimensions, and illustrate the value of fuzzy logic combined with Granger causality in modeling complex, ambiguous markets. From a practical standpoint, the study provides actionable guidance for investors, fund managers, and policymakers, emphasizing the importance of technology-informed governance, standardized ESG disclosures, regulatory sandboxes, and continuous monitoring of SRU. Full article