Search Results (795)

Given the rising urban demand for gas, it has emerged as a primary energy source for urban activities and daily life. However, China’s urban gas pipeline network has witnessed a surge in accidents, leading to significant losses and disasters. Therefore, it is particularly necessary to study the disaster risk assessment model caused by urban gas pipeline leakage. There are some problems in the previous evaluation methods, such as less consideration of the influence relationships between disaster factors. To redress this issue, a novel fuzzy hybrid analytic hierarchy process evaluation methodology is proposed. First, a hybrid hierarchical risk assessment model is developed by combining the analytic hierarchy process and the network analytic hierarchy process. Membership matrices and impact matrices are utilized to calculate comprehensive factor weights. This approach enhances the understanding of relationships between risk factors within the hierarchical structure model. Subsequently, employing a fuzzy evaluation method, the risk level matrix is derived by using multiplication and bounded operators to ascertain the risk level state. This solves the problem of the fuzzy boundaries when measuring the index factors of the gas pipeline network. Finally, experimental analysis is carried out on the gas pipeline network in the central area of a city and validates the model’s accuracy in practical applications. Full article

Background: The supplier selection process (SSP) has grown as a crucial mechanism in organizations’ supply chain management (SCM) strategies and as a foundation for continuously gaining a competitive advantage. The concept of the circular economy has garnered significant interest due to its ability to address both environmental and social criteria. It is highly important to carefully choose suppliers across all industries that take into account circular and sustainability issues, as well as traditional criteria. There is very limited research involving the supplier selection process in the Indian HVAC manufacturing sector. Design/Methodology/Approach: Thus, this study aimed to determine the critical factors for sustainable supplier selection for HVAC manufacturing firms using a mixed research method with three stages: a secondary study, the Delphi method, and the fuzzy analytical hierarchy process (FAHP). Thirty-two critical sub-factors were identified and grouped into eight major factors: delivery, economic, environmental, social, management and organization, quality, services, and supplier relationship. Results/Conclusions: For HVAC manufacturing firms, the major factors of delivery, quality, and economics were found to be top-ranked among the factors, followed by environmental factors. Studies in developing countries using sustainable factors are still nascent, especially in India. Originality/Value: This study’s novelty lies with the proposed eight major factors, comprising all facets of organizations, including sustainability factors. Supplier selection in HVAC manufacturing firms is exhaustively dealt with in this study, filling a gap in the existing literature. This is important because HVAC products are high-energy-consuming, high-energy-releasing, and costly. Full article

This article is the first attempt to understand and develop an effective tool to support decision-makers in defining actions aimed at the development of rural areas in view of the global rationalization and optimization of resources. The objective was to create a rurality index (RI) to assist in resource allocation and policy design by considering the unique characteristics of India addressing a critical gap in regional development studies. A modified Fuzzy Analytical Hierarchy Process (F-AHP) was used to develop an RI tailored to the Gonda district in India. A comprehensive survey of 1300 experts guided the selection and prioritization of 21 factors across six domains: education, infrastructure, employment, agriculture, healthcare, and social index. These factors were then applied to assess 1214 villages in 16 development blocks. This methodology facilitated the ranking and zoning of the areas, resulting in 16 distinct zones, which enhanced the interpretability of the results. Rupaideeh and Itiyathok emerged at the top of the combined domain rankings, while Babhanjot and Chapiya occupied the bottom positions. The developed index provides a robust framework for guiding resource allocation and designing targeted interventions, thereby promoting more equitable development across communities. The results underscored the complex interplay of factors influencing village development across the assessed regions. Moreover, this model demonstrated the potential for adaptation and application in diverse localities, subject to appropriate modifications of parameters to suit local contexts. The index’s versatility and comprehensive approach offers valuable insights for policymakers and development practitioners seeking to address regional disparities effectively. Full article

This study aims to assess and analyze the urban food resilience of the Zhengzhou metropolitan area, proposing innovative assessment frameworks and methodologies. Utilizing a dual-level analysis approach that combines long-term planning impact analysis (2000–2020) with short-term resilience assessment (2018–2022), the study integrates public government data and Geographic Information System (GIS) data, employing spatial analysis, Analytic Hierarchy Process (AHP), and fuzzy comprehensive evaluation techniques. Findings from 2000 to 2020 indicate that urban planning within the metropolitan area has significantly impacted the food system. Urbanization has led to reduced agricultural land, but improvements in infrastructure have enhanced the efficiency of the food supply chain. Woodland and grassland areas have remained relatively stable, providing an ecological buffer for the food system. Building on this, the short-term assessment from 2018 to 2022 reveals significant dynamic changes and a continuous improvement trend in food resilience, though there is still room for enhancement. Food supply chain management and emergency preparedness and management contributed the most to overall resilience. Notably, extreme events such as the COVID-19 pandemic and the “7.20 Flood Disaster” prompted the adoption of innovative measures to enhance food resilience. The study develops a multidimensional theoretical framework and assessment system for urban food resilience, offering new perspectives and methods for understanding and enhancing urban food resilience. The results highlight the critical role of urban planning in enhancing food resilience, recommending the integration of the food system into comprehensive urban planning, strengthening regional collaboration, and enhancing public engagement. These findings provide an important basis for policymaking and practice aimed at improving the long-term adaptability and short-term recovery capabilities of urban food systems. Full article

This study addresses a significant problem: it is difficult to choose a suitable mobile learning platform effectively since many learning platforms are readily available for users. For this purpose, the study proposes an efficient way to rank and choose the most suitable mobile learning platform by integrating risk analysis and multi-criteria decision-making methods. The selection of a suitable mobile learning platform is challenging due to the vast collection of available platforms. Traditional decision-making approaches often struggle to manage the inherent uncertainty and subjectivity in platform evaluation. To address this, we propose an enhanced methodology that combines grey relational analysis (GRA) and fuzzy analytic hierarchy process (FAHP), leveraging their complementary strengths to provide a robust and adaptive solution. The study employs ISO/IEC 9126 software quality standards to locate the most suitable mobile learning platform. FMEA is based on three risk factors: occurrence, severity, and detection. The fuzzy analytical hierarchy process (FAHP) is used to determine the relative weight of each risk factor to identify the grey risk priority number that can be calculated for each criterion. Mobile learning platforms are then ranked based on their grey risk priority number. The method was applied to five widely used mobile learning platforms with three decision-makers. In addition, the multi-criteria decision-making software was developed to aid users, educators, and administrators in their decision-making processes. The integrated FMEA-GRA-FAHP technique, using ISO/IEC 9126 standards, provides an effective way of locating the most suitable mobile learning platform and ranking them according to their reliability. This research is believed to be the only study applying an integrated FMEA-GRA-FAHP approach to evaluate the risks and quality of mobile learning platforms. The unique approach overcomes certain limitations of the standalone methods such as FMEA and FAHP, making it a valuable tool for identifying the suitability of mobile learning platforms. In addition, the study underscores the importance of inclusivity and equity in ensuring high-quality education and creating an environment conducive to lifelong learning for all. Full article

Camellia oleifera fruit pickers are essential for improving picking efficiency and promoting the Camellia oleifera industry. However, it is challenging to develop pickers that meet user needs. Current design tools and methods have limitations, such as a single model, poor synergy between integrated models, and subjective bias when analysing user requirements and translating them into product attributes. To solve these problems, this study proposes a new design decision model based on the Fuzzy Analytic Hierarchy Process (FAHP), Function Analysis System Technique (FAST), Theory of Inventive Problem Solving (TRIZ Theory), and extension transformation theory. The model was developed and applied to design an Camellia oleifera fruit picker. In this paper, an empirical investigation of an Camellia oleifera base in Wuhan was carried out, and multi-level demand analysis was used to identify the design demands in the behavioural process; FAHP was used to calculate the demand weights to clarify the design focus; expert knowledge was used to convert the demands into specific product functional features, and FAST was used to decompose these features to find the contradictory conflicts; TRIZ theory was used to determine the principles of resolving the contradictions, and the extension transformation theory were used to generate the creative design solutions for the products. By integrating FAHP, FAST, TRIZ theory and the extension transformation theory, the subjective bias in product design is eliminated, the design decision-making process is improved, and new methods and ideas are provided for the design of oleaginous tea fruit pickers and similar products. Finally, the conceptual design of an Camellia oleifera fruit picking machine was produced. However, the conceptual design has yet to be subjected to exhaustive simulation experiments and prototype testing. Future research will focus on conducting the necessary simulations, prototypes, and field tests to fully assess the feasibility and effectiveness of the design and make the required iterative improvements accordingly to commercialize the product eventually. Full article

In the context of healthcare technology management (HTM) in Saudi Arabia and the Gulf region, this study addresses a significant gap by exploring both external and internal risk factors affecting HTM performance. Previous studies have primarily focused on modeling or predicting failures in medical devices, mostly examining internal (endogenous) factors that impact device performance and the development of optimal service strategies. However, a comprehensive investigation of external (exogenous) factors has been notably absent. This research introduced a novel hierarchical risk management framework designed to accommodate a broad array of healthcare technologies, not limited to just medical devices. It significantly advanced the field by thoroughly investigating and validating a comprehensive set of 53 risk factors and assessed their influence on HTM. Additionally, this study embraced the perspective of enterprise risk management (ERM) and expanded it to identify and incorporate a wider range of risk factors, offering a more holistic and strategic approach to risk assessment in healthcare technology management. The findings revealed that several previously underexplored external and internal factors significantly impacted HTM performance. Notably, the Fuzzy AHP survey identified “design risk” under facility and environmental risks as the highest risk for HTM in this region. Furthermore, this study revealed that three out of the top ten risks were related to “facility and internal environmental” factors, six were related to technological endogenous factors, and only one was related to managerial factors. This distribution underscores the critical areas for intervention and the need for robust facility and technology management strategies. In conclusion, this research not only fills a critical void by providing a robust framework for healthcare technology risk assessment but also broadens the scope of risk analysis to include a wider array of technologies, thereby enhancing the efficacy and safety of healthcare interventions in the region. Additionally, the proposed hierarchy provides insights into the underlying risk factors for healthcare technology management, with potential applications extending beyond the regional context to a global scale. Moreover, the equation we proposed offers a novel perspective on the key risk factors involved in healthcare technology management, presenting insights with far-reaching implications applicable not only regionally but also on a global level. This framework also supports sustainability goals by encouraging the efficient and responsible utilization and management of healthcare technologies, essential for ensuring the long-term economic and environmental sustainability of medical technology use. This research is of an exploratory nature, with the findings from the Fuzzy AHP analysis being most applicable to the specific geographic regions examined. Additional research is required to validate these results and to confirm the trends observed in various other regions and contexts. Full article

Open-pit mining seriously damages the original vegetation community and soil layer and disturbs the carbon cycle of vegetation and soil, causing instability in the mining ecosystem and decrease in the carbon sequestration capacity of the mining area. With the deepening of environmental awareness and the influence of related policies, the ecological restoration of open-pit mines has been promoted. The mining ecosystem is distinct owing to the disperse distribution of mines and small scale of single mines. However, the carbon sequestration capability of mines after ecological restoration has not been clearly evaluated. Therefore, this study evaluated the carbon sequestration capacity of restoration mines, taking the mines of the Yangtze River Basin in Jurong City, Jiangsu Province as the research objects. Firstly, the visual effects of the vegetation and soil in their current status were determined through field investigation, the methods for sampling and data collection for the vegetation and soil were selected, and the specific laboratory tests such as the vegetation carbon content and soil organic carbon were clarified. Meanwhile, the evaluation system consisting of three aspects and nine evaluation indexes was established by using the analytic hierarchy process (AHP) and fuzzy comprehensive evaluation (FCE). The process of evaluation included the following: the establishment of the judgment matrix, calculation of the index weight, determination of the membership function, and establishment of the fuzzy membership matrix. Finally, the evaluation results of the restoration mines were determined with the ‘excellent, good, normal and poor’ grade classification according to the evaluation standards for each index proposed considering the data of the field investigation and laboratory tests. The results indicated that (1) the evaluation results of the mines’ carbon sequestration capacity were of excellent and good grade at a proportion of 62.5% and 37.5%, which was in line with the field investigation results and demonstrated the carbon sequestration capacity of all the restored mines was effectively improved; and (2) the weights of the criterion layer were ranked as system stability > vegetation > soil with the largest value of 0.547, indicating the stability of the system is the main factor in the carbon sequestration capacity of the mines and the sustainability of the vegetation community and the stability of soil fixation on the slope. The proposed evaluation system effectively evaluates the short-term carbon sequestration capability of the restoration mining system according to the visual effects and the laboratory testing results, objectively reflecting the carbon sequestration capacity via qualitative assessment and quantitative analysis. The evaluation method is relatively applicable and reliable for restoration mines and can provide a reference for similar ecological restoration engineering. Full article

Interdependent criteria play a crucial role in complex decision-making across various domains. Traditional methods often struggle to evaluate and prioritize criteria with intricate dependencies. This paper introduces a generalized method integrating the analytic network process (ANP), the decision-making trial and evaluation laboratory (DEMATEL), and the consistent fuzzy analytic hierarchy process (CFAHP) in a fuzzy environment. The Drazin inverse technique is applied to derive a fuzzy total priority matrix, and we normalize the row sum to achieve the steady-state fuzzy priorities. A numerical example in the information systems (IS) industry demonstrates the approach’s real-world applications. The proposed method derives narrower fuzzy spreads compared to the past fuzzy analytic network process (FANP) approaches, minimizing objective uncertainty. Total priority interdependent maps provide insights into complex technical and usability criteria relationships. Comparative analysis highlights innovations, including non-iterative convergence of the total priority matrix and the ability to understand interdependencies between criteria. The integration of the FANP’s network structure with the fuzzy DEMATEL’s influence analysis transcends the capabilities of either method in isolation, marking a significant methodological advancement. By addressing challenges such as parameter selection and mathematical complexity, this research offers new perspectives for future research and application in multi-attribute decision-making (MADM). Full article

As a part of the service industry, product design practitioners should possess an understanding of the multifaceted factors and solutions that contribute to delivering exceptional service quality. However, related research on the service quality factors and solutions for China’s ceramic product design industry is still an important research gap. In view of this, an integrated approach based on multi-criteria decision making (MCDM), combining the fuzzy analytic hierarchy process (FAHP) and the measurement of alternatives and ranking according to compromise solution (MARCOS), was proposed in this research to analyse and evaluate the service quality factors and solutions for China’s ceramic product design industry. Initially, the FAHP method determined the significance of the service quality dimensions and indicators. Subsequently, the MARCOS method ranked the alternatives based on their performance against these criteria. This research focuses on the growing subject of service quality in China’s ceramic product design industry. The proposed model identifies essential service quality factors and solutions for China’s ceramic product design industry. The findings of this study may assist ceramic product design practitioners in China in making strategic decisions to provide excellent service quality. Full article

This research paper examines the digital infrastructure required to achieve project management success by analyzing the enabling elements of this digital infrastructure in terms of three pillars: digital readiness, digital fitness, and digital tools. A comprehensive literature review was conducted to identify these enabling elements and to develop a list of project management success indicators through which the success of project management can be measured. To evaluate and rank the digital infrastructure enabling elements, a Multi-Criteria Analysis (MCA) was implemented using a hybrid approach combining Fuzzy Analytic Hierarchy Process (FAHP) and Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS). The study used the digital infrastructure enabling elements as MCA alternatives and the project management success indicators identified in the literature review as MCA criteria. The results indicated that the enabling elements associated with digital tools are the most significant for project management success, with a FTOPSIS closeness coefficient (CC_i) of 0.8525, followed by those related to digital fitness (CC_i = 0.6481) and digital readiness (CC_i = 0.1602). These findings have proven to be robust, as they remained consistent even when weights of the MCA criteria were adjusted in three new scenarios proposed in a scenario analysis. This research highlights the critical role of digital enabling elements in enhancing project management practice and achieving project management success. It also offers a strategic framework for organizations to develop and strengthen their digital infrastructure. Full article

Municipal management involves making decisions on various technical issues, and one such crucial aspect is the multicriteria decision-making process. When choosing suitable locations for wastewater treatment plants, it becomes necessary to consider a range of factors such as technical feasibility, economic viability, environmental impact, ecological aspects, and management requirements. However, evaluating these criteria and dealing with uncertainties can be complex. To address this challenge in the Tabuk region, a combination of two powerful analytical methods, the fuzzy analytical hierarchy process (FAHP) and geographical information system (GIS), were employed. The FAHP methodology allows for considering uncertainties and subjective judgements, while GIS provides spatial analysis capabilities. By combining FAHP and GIS, a thorough evaluation of potential wastewater treatment plant locations was conducted by determining the relative weights for each geospatial parameter. These weights were then used to generate a suitability map, visually representing the most favourable areas for site selection. The FAHP analysis resulted in higher importance given to the treatment plant’s distance to urban areas, followed by the distance to roads among the seven investigated parameters. The integrated FAHP-GIS model results show that the western parts of the region are most suitable for constructing wastewater treatment plants. These findings are valuable in facilitating multicriteria decision-making for identifying the optimum site in the area. In summary, integrating FAHP and GIS in the assessment process enables decision-makers to consider various technical, economic, environmental, ecological, and management aspects, thereby providing a comprehensive framework for site selection that can be replicated in other regions with different conditions. This approach enhances the decision-making process in municipal management and promotes more informed and effective planning in the Tabuk region. Full article

In order to improve grid security while pursuing a grid operation economy and new energy consumption rates, this paper proposes a short-term optimal scheduling method based on security quantification for the grid containing a pumped-storage power plant. The method first establishes a grid security evaluation model to evaluate grid security from the perspective of grid resilience. Then, a short-term optimal dispatch model of the grid based on security quantification is constructed with the new energy consumption rate and grid loss as the objectives. In addition, an efficient intelligent optimization algorithm, Dung Beetle Optimization, is introduced to solve the scheduling model, dynamically updating the evaluation intervals during the iterative solution process and evaluating the grid security level and selecting the best result after the iterative solution. Finally, the improvement in the term IEEE 30-bus grid connected to a pumped-storage power plant is used as an example to verify the effectiveness of the proposed method and model. Full article

Smart electric vehicles (SEVs) hold significant potential in alleviating the energy crisis and environmental pollution. The augmented reality (AR) dashboard, a key feature of SEVs, is attracting considerable attention due to its ability to enhance driving safety and user experience through real-time, intuitive driving information. This study innovatively integrates Kansei engineering, factor analysis, fuzzy systems theory, analytic hierarchy process, grey relational analysis, and factorial experimentation to evaluate AR dashboards’ visual imagery and subjective preferences. The findings reveal that designs featuring blue planar and unconventional-shaped dials exhibit the best performance in terms of visual imagery. Subsequent factorial experiments confirmed these results, showing that drivers most favor blue-dominant designs. Furthermore, in unconventional-shaped dial designs, the visual effect of vertical 3D is more popular with drivers than horizontal 3D, while the opposite is true in round dials. This study provides a scientific evaluation method for assessing the emotional experience of AR dashboard interfaces. Additionally, these findings will help reduce the subjectivity in interface design and enhance the overall competitiveness of SEV vehicles. Full article

This study evaluated vegetation management (VM) strategies under electricity distribution lines (EDLs) through ecosystem service (ES) criteria. Deforestation, worsened by insufficient VM practices, poses a threat to ecosystem stability. Using a hybrid FAHP (Fuzzy Analytic Hierarchy Process) and TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) approach, ten VM strategies were assessed based on 15 ES criteria. The FAHP results identified biodiversity, timber resources, and erosion control as the most crucial criteria due to their significant weights. The TOPSIS analysis determined that VM6 (creation and restoration of scrub edges) was the most effective strategy, achieving a value of 0.744 for reducing deforestation and enhancing energy security. VM6 helps preserve forest cover and protect infrastructure by creating a “V”-shaped structures within the EDLs corridor. This study underscores the importance of ES-oriented VM strategies for sustainable vegetation management and deforestation mitigation. It also highlights the need for incorporating scientific, ES-based decision support mechanisms into VM strategy development. Future research should expand stakeholder perspectives and conduct a comprehensive assessment of ESs to ensure that VM strategies align with ecological and socio-economic sustainability. This study provides a framework for improving VM practices and offers directions for future sustainable energy management research. This study focuses exclusively on ecological criteria for evaluating VM strategies, neglecting other dimensions. Future research should use methods like ANP and fuzzy cognitive maps to explore inter-dimension relationships and their strengths. Additionally, employing SWARA, PIPRECIA, ELECTRE, and PROMETHEE for ranking VM strategies is recommended. Full article