Search Results (79)

This exploratory case study assesses ecotourism adaptability across three zones within the proposed Southwest Karst National Park (Guangxi), where UNESCO-recognised geological heritage intertwines with diverse ethnic cultures. To fill the gap in zone-specific integrated assessment frameworks, we employed a two-stage entropy-weighted TOPSIS method—calibrated via Delphi-AHP adjustments within a Social-Ecological Systems framework—using 2023–2024 data, complemented by ethnographic observations. Preliminary results indicate divergent trajectories: the Tiankeng zone exhibits high geological uniqueness and market appeal (composite score 0.74); the Mulun zone shows relatively balanced social–ecological coupling (0.58); and the Underground River zone displays pronounced asymmetry between vulnerability and development potential (0.16). Accordingly, tentative daily visitor caps of 3000, 8000, and 14 persons, respectively, and a pilot adaptability alert threshold of 0.20 for this specific case are proposed. These findings reveal a “vulnerability–capacity inverse matching” dynamic, informing differentiated governance: high-adaptability zones may allow moderate tourism with real-time monitoring, whereas low-adaptability zones require strict conservation-first measures and phased institutional capacity-building prior to any development. This preliminary framework offers actionable insights for sustainable management, conceptually aligned with SDG 11.4 and SDG 15.9. Full article

This research establishes a framework to evaluate how effectively financial institutions convert environmental, social, and governance (ESG) pressures into readiness for open innovation (EOIR). EOIR is conceptualized as a higher-order capability that encompasses environmental opportunity, social legitimacy, and governance discipline. This study employs a triangulated multi-criteria decision-making framework consisting of CRITIC, Shannon Entropy, and Fuzzy AHP weighting with MARCOS ranking, TOPSIS validation, and pillar-focused scenario analysis to evaluate ESG–open innovation readiness. Results inindicate the importance of governance practices, such as board independence, low controversies, and alignment with the Paris Agreement and environmental innovation. Data privacy outperforms representational social attributes. The MARCOS and TOPSIS rankings demonstrate a high degree of concordance; leaders maintain their stability across weighting philosophies, while mid-tier positions exhibit policy-sensitive mobility. Scenario analysis indicates a stable frontier, high top-10 overlap, and mid-teen rank shifts, highlighting actionable levers. The framework provides a transparent, reproducible multiple-criteria decision-making pipeline for EOIR measurement and clarifies important enablers, including credible governance, environmental technology alignment, and privacy-centric data governance, from a theoretical and practical perspective. Full article

Understanding the interactions between water resource utilization, socioeconomic development, and the ecological environment is fundamental to ensuring ecological security and promoting sustainable development in the lower Yellow River region. This study developed a composite system integrating water resources, socioeconomic development, and ecological environment for 27 cities in the lower Yellow River Basin. The indicator weights were determined using the combined Analytic Hierarchy Process (AHP) and entropy weight method. Subsequently, several models, including Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), the coupling coordination degree (CCD) model, spatial autocorrelation, and obstacle degree analysis, were integrated to systematically evaluate the spatiotemporal evolution, coordination patterns, and key constraints of the composite system. The findings indicate that the development of the three subsystems surged with fluctuations, following the gradient pattern of ecological environment > socio-economic development > water resources. The water resource subsystem improved slowly and remained the main constraint. The CCD gradually shifted from barely and primarily coordinated stages to intermediate and well-coordinated stages. Spatially, Shandong outperformed Henan, eastern areas exceeded western areas, and core cities showed higher coordination levels than inland cities. Significant and increasing positive spatial autocorrelation indicated strengthened spatial agglomeration, with high–high clusters in eastern Shandong and low–low clusters in western and northwestern Henan. The per capita water resource indicator emerged as the dominant obstacle, while forest and grassland area, the Normalized Difference Vegetation Index (NDVI), agricultural water use, and the share of the tertiary industry also constituted major constraints. Full article

Prefabricated construction is increasingly adopted worldwide because of its advantages in sustainability and construction efficiency. Nevertheless, the construction phase still faces substantial and multifaceted risks. These risks are characterized by high uncertainty and strong dependence on the subjective judgments of decision-makers, which may limit the wider promotion and application of prefabricated construction. Existing risk assessment methods often struggle to represent neutral and refusal attitudes in expert evaluations with sufficient precision. They also do not fully account for the psychological and behavioral mechanisms of decision-makers under risk. To address these limitations, this study proposes an integrated evaluation framework that combines interval-valued picture fuzzy sets (IVPFSs), cumulative prospect theory (CPT), and TOPSIS. The decision objective is to rank alternative construction-stage risk-control schemes and identify the relatively important risk factors influencing the ranking results. IVPFSs are used to represent support, opposition, neutrality, and refusal degrees in expert evaluations. CPT is incorporated to capture decision-makers’ risk preferences, reference dependence, and loss-aversion behavior. A comprehensive risk indicator system is developed from five dimensions: personnel, management, technology, environment, and materials/equipment. Attribute weights are determined using a coordinated AHP–entropy weighting scheme to balance subjective expert judgment with objective information contained in the evaluation data. The proposed framework is applied to a prefabricated building project in Shanghai. The results indicate that personnel-related factors, especially the technical proficiency of construction workers, are relatively important risk sources in the examined case. The model also provides a structured ranking of alternative risk-control schemes. Overall, this study offers an exploratory case-based decision-support framework for construction-stage risk management in prefabricated building projects and demonstrates the potential value of incorporating behavioral preferences into fuzzy multi-criteria risk assessment. Full article

Under the “dual carbon” goals (carbon peak and carbon neutrality), the new energy vehicle (NEV) industry has become a strategic focus of great-power competition, and the resilience of its international supply chain is critical to industrial security and development initiatives. As a traditional automobile manufacturing hub in China, Hubei Province faces increasingly prominent global risks in its supply chain during the transition to NEVs; scientifically evaluating and enhancing its international supply chain resilience is therefore of great practical significance. Drawing on supply chain resilience theory, this paper constructs an evaluation index system comprising 18 specific indicators across four dimensions: robustness, redundancy, agility, and innovativeness. To overcome the limitations of a single weighting method, a combined subjective and objective weighting approach that integrates the Analytic Hierarchy Process (AHP) and the entropy weight method was employed to determine indicator weights. Subsequently, the TOPSIS model was applied to measure the supply chain resilience level of Hubei Province from 2018 to 2025, with horizontal comparisons conducted against Shanghai and Guangdong. Finally, an obstacle degree model was introduced to quantitatively diagnose the key factors constraining resilience improvement. The results indicate that the international supply chain resilience of Hubei’s NEV industry has shown a continuous upward trend. By 2025, it ranks in the first tier alongside Guangdong (with closeness coefficients of 0.8180 and 0.8181, respectively), approaching the level of Shanghai. Weaknesses are concentrated primarily in the agility dimension, while upstream resource dependence remains a salient issue within the robustness dimension. “External dependence on key raw materials,” “average recovery time from logistics disruptions,” and “level of supply chain information sharing” are still the top three obstacle factors. Fuzzy-set qualitative comparative analysis (fsQCA) further reveals that low resource autonomy and slow logistics recovery are core conditions leading to low resilience, and the coupling of multiple obstacle factors amplifies the risk transmission effect. Based on this, this study proposes optimization recommendations focusing on foundation strengthening and chain consolidation, digital chain connectivity, and innovation–chain integration, in order to enhance the resilience of the international supply chain for new energy vehicles in Hubei. This research provides a methodological reference for evaluating the supply chain resilience of regionally distinctive industries and offers a quantitative basis for Hubei Province and related enterprises to formulate targeted improvement strategies. Full article

Semi-arid wetlands are highly sensitive to changes in hydrological regimes, as strong evaporation often exceeds limited natural recharge. Ecological water replenishment is widely used to restore these systems, but schemes designed only to meet water-volume targets may cause excessive hydrodynamic disturbance, promote sediment resuspension, and increase the release of internal pollutants. In this study, we developed an ecological water-replenishment assessment framework for Chahannaoer Wetland that incorporates ecological water-demand thresholds, suspended-solids disturbance, and an AHP–entropy weight–TOPSIS decision model. Using hydrological and meteorological data from 2014 to 2024, six replenishment scenarios were evaluated in terms of water-balance recovery, disturbance control, and habitat suitability. The results show that Chahannaoer Wetland experienced a persistent evaporation-dominated water deficit. The mean annual natural recharge was 0.225 × 10⁸ m³, with a mean annual ecological water shortage of 1.03 × 10⁸ m³ and an evapotranspiration-to-recharge ratio of 3.42–4.56. Based on the previous comprehensive water-quality assessment using DO, COD, NH₃-N, TN, and TP, the minimum water volume required to maintain Class IV water quality was 0.86 × 10⁸ m³, whereas the suitable ecological water demand ranged from 1.27 × 10⁸ to 1.56 × 10⁸ m³. With the total replenishment volume held constant, centralized replenishment met the required water volume but substantially increased near-bed disturbance and sediment resuspension risk. By contrast, decentralized uniform replenishment performed best, with the highest relative closeness coefficient of 0.9105, a disturbance index of approximately 0.32, and water depths maintained within the suitable habitat range of 30–50 cm. These findings suggest that ecological restoration in semi-arid wetlands should move beyond volume-based water supplementation and pay greater attention to the timing, pathway, and hydrodynamic effects of replenishment. The proposed framework provides a quantitative basis for optimizing ecological water replenishment in evaporation-dominated wetlands and other inland lakes in arid and semi-arid regions. Full article

Inbound tourism has become an important indicator of destination openness, service capacity, cultural communication, and sustainable governance. However, existing evaluations often separate visitor experience, destination competitiveness, and sustainability, making it difficult to diagnose how service quality supports long-term competitiveness. This study develops a sustainability-oriented framework for evaluating inbound tourism service quality in 10 representative Chinese cities. Nineteen indicators are organized into four dimensions: basic service provision, cultural and experiential perception, safety and emergency response, and sustainable and resilient development. A TIFN-AHP-TOPSIS model is used to integrate official statistics, public tourism information, online-review evidence, and expert judgments while retaining uncertainty and hesitation in qualitative assessments. The results show that Shanghai, Beijing, and Hangzhou form the leading tier; Shenzhen, Chengdu, Guangzhou, Sanya, and Xiamen form the balanced tier; and Xi’an and Chongqing form the potential tier. Robustness checks based on risk-preference adjustment, entropy-weighted TOPSIS, grey relational TOPSIS, and perception-indicator perturbation confirm the stability of the tier classification. The findings suggest that inbound tourism competitiveness depends not only on transport access and reception capacity but also on cultural interpretation, digital convenience, safety governance, ecological quality, and resilience. The framework provides a diagnostic tool for improving sustainable destination competitiveness. Full article

Prefabricated mechanical, electrical, and plumbing (MEP) systems have been increasingly adopted in energy station projects; however, systematic evaluation frameworks capable of integrating construction performance, cost constraints, and uncertain multi-indicator assessments remain limited. To address this gap, this study constructs an Analytic Hierarchy Process (AHP)–Entropy–Fuzzy evaluation framework to assess the comprehensive benefits of BIM-enabled prefabricated MEP construction in energy stations. A hierarchical evaluation system was established based on five dimensions: schedule, quality, cost, safety, and environmental performance, and ten secondary indicators were defined. The Analytic Hierarchy Process was used to determine expert-based subjective weights, the entropy method was applied to capture objective data variability, and multiplicative normalization was employed to obtain combined weights. A fuzzy comprehensive evaluation model was then introduced to transform heterogeneous construction records into comparable benefit levels and scores. The prefabricated method scored 87.80 and was classified as “high”, whereas the conventional method scored 60.85 and was classified as “low”. A Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)-based sensitivity analysis further showed that, under 10%, 20%, and 50% criterion-weight perturbations, the prefabricated group consistently achieved higher closeness coefficients than the conventional group. The smallest margin occurred when the schedule weight was reduced by 50%, but the prefabricated group retained a positive advantage. The results demonstrate that Building Information Modeling (BIM)-enabled prefabricated MEP construction can achieve superior overall project performance through the coordinated optimization of schedule, cost, safety, quality, and environmental objectives, offering a practical evaluation framework and decision-support tool for the industrialized delivery of future energy infrastructure projects. Full article

Smart museums increasingly rely on digital media, interactive installations, artificial intelligence, augmented reality, and virtual reality to support cultural communication and visitor engagement. However, existing studies have mainly examined specific technologies, usability, or visitor satisfaction, while a systematic and quantitative framework for comparing interactive experience across different smart museums remains limited. To address this gap, this study proposes a hybrid multi-criteria decision-making framework for evaluating smart museum interactive experience. Based on the Strategic Experiential Modules, an evaluation system consisting of five dimensions—Sense, Feel, Think, Act, and Relate—and sixteen indicators was constructed. The Analytic Hierarchy Process was used to determine subjective weights from expert judgments, the entropy method was applied to capture the data-driven dispersion characteristics of expert evaluation data, and a game-theoretic combination weighting strategy was used to integrate the two weighting results. Subsequently, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) was employed to compare five representative smart museum cases. The results show that Zhejiang Provincial Museum achieved the highest relative closeness value (C_i = 0.9891), followed by Shanghai Museum (C_i = 0.8457) and Hunan Museum (C_i = 0.5326). Robustness analysis further showed that the ranking order remained consistent under entropy weights, AHP weights, average weights, and game-theoretic combined weights. The Friedman test indicated no significant difference in the relative closeness coefficients across weighting schemes (χ² = 1.200, p = 0.753). These findings indicate that the proposed framework can effectively identify relative strengths and weaknesses in smart museum interactive experience and provide a replicable decision-support tool for experience-oriented museum design and optimization. Full article

Tunnel water inrush risk assessment poses a complex multi-attribute decision-making challenge, garnering significant global attention as a critical yet unresolved issue in geotechnical engineering. While the Attribute Interval Recognition Theory (AIRT) has been widely adopted for geological hazard prediction, its application in tunnel water inrush scenarios often faces limitations in precise index attribute quantification and risk probability estimation. To address these constraints, this study proposes an improved integrated model combining AIRT, the Analytic Hierarchy Process (AHP), the Inverse Entropy Method (IEM), Game Theory (GT), the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), and Monte Carlo random simulation technology. In this framework, AHP and IEM are used to determine subjective and objective weights, GT is used to optimise the combined weights, TOPSIS is introduced to determine the index attribute measure coefficients, and Monte Carlo simulation is employed to estimate risk probabilities. The novelty of the model lies in improving both risk attribute identification and probabilistic assessment under interval-valued index conditions. The model was validated using 20 representative tunnel water inrush cases, demonstrating robust performance in capturing dynamic risk scenarios. When the confidence level was set to 0.65, all 20 cases were correctly classified, achieving an accuracy of 100%. Subsequently, the model was applied to the inlet section of the Nafeng Tunnel. The results show that the assessed section is classified as Class II, with risk probabilities of 0.515 and 1.000 for the D0 + 220.6–D0 + 285 m and D0 + 285–D0 + 340.6 m sections, respectively. These findings indicate that the proposed model can provide a quantitative basis for tunnel water inrush risk assessment and prevention. Full article

Rapid urbanization and escalating demands for pollution and carbon reduction pose significant challenges to the cement industry in China, characterized by high energy consumption and emissions. However, a multidimensional framework to assess the synergies and trade-offs between environmental, carbon, and economic effects for various decarbonization technologies in cement production is still lacking. Here, six application scenarios of new suspension preheater dry process cement production were developed and evaluated using a life cycle assessment (LCA) framework to quantify environmental impacts, synergistic reduction of pollution and carbon emissions (SRPC), and economic performance. A multi-attribute decision-making model, Analytic Hierarchy Process–entropy–TOPSIS (AHP–entropy–TOPSIS), was applied to assess environmental–economic trade-offs. The results indicate that biomass fuel substitution and high grinding efficiency achieved the best SRPC and environmental–economic trade-off scores (S_norm: 0.17–0.22). Alternative raw materials moderately reduced carbon but increased pollutant emissions and economic uncertainty (S_norm: 0.14–0.20). Mono-ethanolamine absorption and calcium looping provided substantial carbon reduction but weaker overall performance due to environmental trade-offs and higher costs (S_norm: 0.12–0.16). These findings provide quantitative guidance for prioritizing and combining decarbonization strategies to support the green transition and sustainable development of the cement industry. Full article

Locust outbreaks are major biological disturbances in grassland ecosystems of arid and semi-arid regions. Accurate identification of locust suitable habitats is important for regional monitoring and management. However, direct comparisons between multi-criteria analysis (MCA) and species distribution models (SDMs) under a unified framework remain limited. In this study, we compared these two approaches for dominant locust species in Xinjiang, China, including Calliptamus italicus, Gomphocerus sibiricus, and Locusta migratoria manilensis. We used the same environmental variables and occurrence records for all models. The MCA methods included the analytic hierarchy process (AHP), technique for order preference by similarity to ideal solution (TOPSIS), and ordered weighted averaging (OWA). The SDMs included the generalized linear model (GLM), maximum entropy model (MaxEnt), extreme gradient boosting (XGBoost), and an ensemble model. The results showed that SDMs had higher area under the receiver operating characteristic curve (AUC) and true skill statistic (TSS) values than MCA under the internal point-based evaluation framework, although both approaches effectively identified locust-suitable habitats. The two approaches also showed high spatial agreement in moderately and highly suitable habitats, with Jaccard indices of 0.88–0.92, and consistently identified the northern slopes of the Tianshan Mountains, the Ili River Valley, and the margins of the Junggar Basin as core suitable areas. These results indicate that the two approaches are complementary for locust monitoring and management. Full article

Electric vehicles (EVs) are essential for sustainable urban mobility, coordinating transportation demands with energy distribution networks. However, uncoordinated EV charging neglects trip chain continuity, inducing spatial–temporal congestion and overloading local charging capacities. Thus, effectively guiding EVs is a key problem in mitigating traffic emissions and preventing power grid-side stress. In this paper, a two-stage dynamic routing framework within a traffic–energy coordination architecture is proposed, integrating an AHP–Entropy–TOPSIS model for station selection and an Improved Ant Colony Optimization algorithm for trajectory execution. Using this framework, a series of macro–micro simulations on the Sioux Falls network was conducted alongside a congestion-driven dynamic pricing mechanism. The results indicate that the pricing strategy facilitates spatial load balancing through peak shaving at core nodes. Compared to conventional standard meta-heuristic baselines, this framework reduces average economic costs by 28.9% while ensuring battery safety and limiting indirect carbon emissions. The proposed framework provides a multi-objective navigation solution that prevents cross-layer decision fragmentation, supporting the sustainable development of smart city infrastructure. Full article

The efficient and optimized operation of copper smelting processes is comprehensively governed by process flow characteristics and energy efficiency. This study establishes a game theory–based comprehensive evaluation framework and proposes a hybrid weighting-TOPSIS method. The optimal combined weights are determined by integrating subjective and objective approaches, including the analytic hierarchy process (AHP), entropy weight method (EWM), and CRITIC method. The proposed model is used to quantitatively evaluate the effects of flue gas and steam flow rates, and temperature differences, on overall system energy efficiency. Compared with single-weighting methods, the presented strategy demonstrates greater rationality and comprehensiveness. Furthermore, exergy analysis is conducted to investigate energy and exergy efficiencies and exergy destruction of key components. Results show that the energy and exergy efficiencies of waste heat boilers are both approximately 30%, with a maximum exergy destruction of 3646 kW, indicating significant potential for improvement. This finding is consistent with the comprehensive evaluation results obtained from the game theory-based weighting method, providing a reliable basis for energy efficiency optimization of copper smelting waste heat recovery systems. Full article

Traditional villages embody regional culture and local knowledge, yet culture–tourism integration often suffers from a mismatch between resource value and effective transformation. To address this problem, this study proposes a two-dimensional “benefit–obstacle” diagnostic and strategy-matching framework and tests its case-based applicability in Dayuwan Village. First, a cultural landscape gene (CLG) atlas was constructed for the village based on a geo-information coding scheme, covering both tangible and intangible CLGs. Second, a four-dimensional evaluation system was operationalized through five expert judgments and 106 valid on-site questionnaires collected from tourists (n = 67) and residents (n = 39). Criterion weights were determined using an AHP–entropy combination approach, and the comprehensive benefit closeness coefficient was calculated via TOPSIS. Third, an obstacle degree identification model was employed to pinpoint key constraints and derive composite obstacle degrees. Results within the Dayuwan case show that the TOPSIS closeness coefficients of the 17 genes ranged from 0.653 to 0.782 (mean = 0.714), with 4, 6, and 7 genes classified as excellent, good, and medium, respectively; composite obstacle degrees ranged from 0.0228 to 0.1975. In Dayuwan Village, higher obstacle degrees clustered mainly in intangible CLGs, whereas Ming–Qing architecture and frequently practiced folk-cultural genes showed comparatively lower obstacle degrees. The transformation process is constrained by four mechanisms—landscape character protection, economic transformation, social identity, and market demand—with economic transformation constraints being the most prominent. Based on the benefit–obstacle matrix, 17 CLGs were classified into five activation scenarios and matched with corresponding revitalization strategies. This framework links benefit ranking, obstacle diagnosis, and strategy matching, and provides a case-based diagnostic reference for the conservation and culture–tourism integration of villages with comparable heritage conditions, subject to local recalibration of indicators, weights, and thresholds. Full article