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Global trade is plagued by slow and inefficient manual processes associated with physical documents. Firms are constantly looking for new ways to improve transparency and increase the resilience of their supply chains. This can be solved by the digitalisation of supply chains and the automation of document- and information-sharing processes. Blockchain is touted as a solution to these issues due to its unique combination of features, such as immutability, decentralisation and transparency. A lack of business cases that quantify the costs and benefits causes uncertainty regarding the truth of these claims. This paper explores how the costs and benefits of a blockchain-based solution for digitalising and automating documentation flows in cross-border supply chains compare to a conventional centralised relational database solution. The research described in this paper uses primary data collected through semi-structured interviews with industry experts, as well as secondary data from literature. Two models based on existing services were developed and the costs and benefits compared and then analysed using the Architecture Trade-off Analysis Method (ATAM) and the Analytic Network Process (ANP). Findings from the analysis show that a consortium blockchain solution like TradeLens is the favourable solution for digitalising and automating information flows in cross-border supply chains. [ABSTRACT FROM AUTHOR]

Following the outbreak of COVID-19, the cruise industry hit its lowest point, which made operators either cancel or change cruise itineraries, causing significant devastation to cruise ports and port cities. Consequently, the concept of resilience, which focuses on an industry's ability to recover after disruption, has grown in popularity and must be studied by both scholars and practitioners. This study aims to construct a valid hierarchical resilience model based on the causal interrelationship between attributes to guide practitioners in reaching resilient outcomes. The results are expected to be useful for researchers and industry stakeholders in determining actions to utilize the remaining equipment and budget to build future strategies for a quicker recovery. This study uses the fuzzy decision-making trial and evaluation laboratory (FDEMATEL) and the analytic network process (ANP) to analyze questionnaires and accomplish the objectives of the study. The findings show that technological resilience is the most important dimension and that it has strong influences on all other dimensions. In addition, innovation adaptability, port authorities, the urban built environment and resource allocation procedures are the linkage criteria identified as the strongest causes in achieving resilience. [ABSTRACT FROM AUTHOR]

This research proposes and tests a model to select the best enterprise social network for teaching. An emic approach is employed, and a Delphi study based on an analytic hierarchy process is developed. The results show that Viva Engage® is the most appropriate enterprise social network for teaching business administration subjects, and the most important factors that affect teachers’ selection are related to teachers’ profiles, students’ profiles, and the platform’s pedagogical features. This study extends the literature on educational technologies by presenting enterprise social networks as new learning management systems. Additionally, it provides a list of potential enterprise social networks together with a customising decision-making model. Starting from these, teachers can decide the best enterprise social network for teaching, given their objectives and preferences. Therefore, it helps teachers choose the best platform for their needs and make the transition from socio-constructivism learning to social network learning. [ABSTRACT FROM AUTHOR]

Decision-making is among the main concerns in management discussions. This applied research is about a Multiple Criteria Decision Making problem since the decision-making process is drawn upon quantitative and qualitative criteria under uncertain conditions. This study was conducted for an oil reservoir consisting of nine criteria and eight alternatives. To form the network structure and recognize the relationships between the criteria, alternatives, and criteria weights, the Fuzzy Analytic Network Process (FANP) was used. Moreover, the Interval Valued Intuitionistic Fuzzy-TODIM (IVIF-TODIM) technique prioritized the alternatives. A case study was applied to demonstrate and show the suitability of the suggested method. The study's objective is to prioritize enhanced oil recovery (EOR) methods based on the feasibility criteria using the FANP and IVIF-TODIM techniques. This issue is required to implement the research because not all the EOR methods are implemented practically. They should be prioritized and chosen based on the budget, available infrastructures, and other important factors. The important issue is the manager's decision to choose the best method by considering different indicators. This method is a tool for better decision-making. Using these techniques, low salinity water injection was selected as the best and most effective and feasible method. [ABSTRACT FROM AUTHOR]

This study investigates the determinants of financial distress from the corporate social responsibility (CSR) perspective and examines how poor CSR performance leads to financial distress in enterprises. Based on theoretical analysis, we select predictive indicators and construct an early warning indicator system for predicting financial distress from a CSR standpoint. Additionally, we develop a novel dynamic financial distress prediction (FDP) model using decision‐making trial and evaluation laboratory (DEMATEL)‐based analytic network process (DANP), variable weights with penalty (VWP), and maximal entropy ordered weighted average (MEOWA) weight methods to assess corporate financial status. Furthermore, to evaluate the accuracy of our model, we apply it to Chinese listed companies for empirical analysis using a sample of 1142 listed Chinese companies spanning 2011–2023. The results demonstrate that our developed FDP model exhibits higher predictive accuracy compared to previous models, suggesting that poor CSR practices can contribute to corporate financial distress while significantly enhancing FDP performance. [ABSTRACT FROM AUTHOR]

The purpose of this study is to identify and analyze the application barriers and internal mechanisms of BIM technology in green building projects. It is found that BIM technology can effectively integrate information and optimize management, but its application still faces economic externalities and requires government intervention to promote its development. Through the analysis of five aspects of technology, economy, management, policy and environment, we identified 16 influencing factors and focused on nine key factors, such as insufficient technology maturity and high-cost issues. Research shows that policy and management factors play a fundamental role in BIM adoption and influence economic effectiveness through complex interactions. Based on the ISM-ANP coupling model, we propose that the government should encourage technological innovation and personnel training to promote the effective application of BIM technology in green buildings. This study provides a theoretical reference for the application of BIM and green building on a global scale. [ABSTRACT FROM AUTHOR]

Sustainable cashmere production in Mongolia needs to reduce the negative impact of production on the environment and society. However, the industry still bears responsibility for significant resource consumption and disposal and has not yet taken the necessary transformative measures to fully sustainable production transition. In this context, the production method enhancement is still insufficient although it is preparing for the transition to sustainable practices. This study aims to determine the valid attributes of sustainable production as a hierarchical structure and the interdependence relationships using a hybrid of the fuzzy Delphi method, fuzzy decision-making trial and evaluation laboratory, and analytic network process. As a result, 4 aspects and 15 criteria are validated as a sustainable production hierarchical structure. Cleaner production practices and supply chain greening are indicated as the major aspects. The practical criteria are carbon accounting, wastewater reduction, investment in recycling-related research and development, eco-design, and green manufacturing. [ABSTRACT FROM AUTHOR]

The aim of the supplier selection process is to reduce purchasing risks, boost customer profitability, and cultivate enduring, close relationships between suppliers and buyers. This process stands as a pivotal component of supply chain management (SCM), making supplier selection a critical concern for establishing an effective supply chain system. In this instance, a case study has been presented for supplier selection employing Analytic Hierarchy Process (AHP) in conjunction with the Multi-Criteria Decision Making (MCDM) technique. We have explained it using fuzzy data. It not only contributed on utility of fuzzy AHP methodology, but also provided comprehensive literature review of MCDM problems. Furthermore, by outlining the steps of fuzzy AHP in a straightforward numerical manner, this study can serve as a guide for implementing the methodology in other (MCDM) problems. In this study, we evaluate four suppliers using fuzzy AHP. This method can be used when one has to select one particular supplier from a number of suppliers in a short time span. It will be also helpful to the Pharmacists to select the best supplier who can fulfil all their needs. Despite the abundance of studies on supplier selection, there has been relatively less investigation into the evaluation and selection of suppliers using specific measures tailored to the healthcare sector. To bridge this gap, this research puts forth a guideline for selecting suppliers of baby hygiene products. [ABSTRACT FROM AUTHOR]

Resident engagement is highlighted as a crucial aspect that directly impacts the residents' well-being of life in the process of sponge-style old community renewal (SOCR). However, there is a lack of in-depth study on exploring the classification of resident engagement clusters in the SOCR and developing a comprehensive evaluation system to measure this engagement. Therefore, this paper categorizes resident engagement into distinct clusters and develops an evaluation method for quantifying resident engagement in the SOCR. First, this study identified seven types of engagement clusters in the SOCR drawing from educational psychology and Arnstein's citizen engagement ladder theory. Second, an evaluation indicator system with 5 primary indicators and 21 secondary indicators was developed through a literature review and expert interviews. Third, a hybrid evaluation method combining the Analytic Network Process (ANP) and Preference Ranking Organization Method for Enrichment Evaluations II (PROMETHEE II) was established to effectively quantify resident engagement in the SOCR. Finally, 16 typical communities from five Chinese cities were selected as study areas to examine resident engagement in the SOCR. The results demonstrated that the full engagement cluster achieved the highest scores at the individual level, while the non-engagement cluster recorded the lowest scores. At the city level, Shanghai attained the highest overall engagement score, whereas Chizhou recorded the lowest. Several strategies were proposed to improve resident engagement in the SOCR. This study not only contributes to the body of knowledge on resident engagement in the SOCR but also provides guidance for fostering resident engagement in sponge city construction. [ABSTRACT FROM AUTHOR]

With the vigorous development of information technology, the applications of the Internet of Things (IoT) have become increasingly common in recent years. Robot vacuum has become a popular and representative product in smart homes. This study proposed a hybrid fuzzy multi-criteria decision-making (MCDM) model that applied fuzzy analytic network process (FANP) and decision-making trial and evaluation laboratory (DEMATEL) to analyze the critical factors evaluated by users when adopting a robot vacuum. It was found that the top two dimensions in order are "epistemic value" and "functional value"; and the top five factors in order are "novelty", "exploratory", "family information infrastructure", "family consensus", and "reliability". Significant influential and affected factors were identified. Gender differences in decision-making factors are also discussed. [ABSTRACT FROM AUTHOR]

Sub-watershed prioritization is essential for developing watershed management plans that maximize impact with minimal resources. This study used a multicriteria decision-making approach to rank sub-watersheds by degradation status in the Huehuetan River Basin, Chiapas, Mexico. The eight sub-watersheds in the basin were classified using the Analytic Network Process (ANP) model, evaluating morphometry, hydrology, hillslope stability, soil water saturation, land-use change, and socioeconomic factors. The results identified hydrology and land-use change as the most influential criteria, with weights of 20.62% and 19.82%, respectively, driven mainly by surface runoff and deforestation. Swtr 08 and Swtr 07 were identified as the highest-priority sub-watersheds, covering 24.31% of the basin area, with 55.31% of Swtr 08 classified as unstable and showing a combined high-vegetation loss of 16.46 km2. The entire watershed showed an annual vegetation loss rate of 146 ha year−1. Increasing the weighting by 50% resulted in greater variability in priority rankings, with runoff and low vegetation showing maximum global ranges of −44.33% and 30.25%, respectively, instability decreasing by 33.94%, and peak flow increasing by 18.20%. These findings emphasize the need for focused interventions in the vulnerable subwatersheds of the upper basin to manage runoff, curb deforestation, and reduce soil instability. [ABSTRACT FROM AUTHOR]

In recent decades, the issues of ecology and environmental sustainability have become a global concern in contemporary urban design. Among various urban elements, water features play a significant role in improving the ecological characteristics of their surrounding environment, especially in hot and arid areas. The aim of this study is to evaluate the ecological characteristics of urban water features comprehensively and quantitatively, which has been overlooked in previous studies, taking their physical characteristics into account. To this end, a multicriteria decision-making method, an analytic network process, was proposed to quantitatively evaluate the ecological characteristics of water features. In this approach, four ecological criteria—microclimate, biodiversity, greenery, and human wellbeing—and ten physical characteristics of water features were considered. Twenty-one experts were asked to complete a questionnaire for pairwise comparisons of all ecological criteria and the influence of physical characteristics. The results showed that vegetation and scale, with the relative influencing values of 0.255 and 0.188, respectively, were identified as the most decisive features influencing ecological criteria. Conversely, texture, with a value 0.023, had the least impact. Moreover, it was shown that water features have the greatest impact on the microclimate compared with other ecological criteria. The results were used to compare water features at the Koohsangi Transregional Park, located in a hot and arid city of Iran. The results of this study lead to a framework that can help urban designers integrate ecological criteria into water feature planning to enhance urban ecology and sustainability. [ABSTRACT FROM AUTHOR]

As demonstrated by the existing literature, lean production and management can contribute to the improvement of firm performance. However, there are many companies that struggle to apply its ethos and practices. The key point is that lean production differs from traditional mass production in many ways. Other than that, numerous studies have shown that business management systems must take into account both soft power and hard power. The main purpose of this study is to use the Analytic Hierarchy Process (AHP) and Analytic Network Process (ANP) tools to find out the soft and hard power factors, rank their importance in identifying the key success factors for the introduction of a lean production system, and assist in making the company's transformation smoother and more successful. The research results verify that a lean production system needs to take into account both soft power and hard power. Lean management in this study concludes the following priorities of critical factors: In hard power (technical dimension): (1) 5S, (2) seven major wastes, (3) solutions to lean production-related issues, (4) storage location management and warehouse management, (5) single minute exchange of die, and (6) total productive maintenance; In soft power (management dimension): (1) teamwork, (2) communication, (3) leadership, (4) culture, (5) initiative, and (6) employee training. The combination of soft power and hard power can improve the success rate of lean management system introduction. [ABSTRACT FROM AUTHOR]

In the later stages of oilfield development, the decline in oil well production and the increase in development costs, attributed to issues such as insufficient liquid supply, necessitate the implementation of intermittent pumping measures. However, current methods for selecting these wells lack comprehensiveness in the decision-making process. This article proposes a novel method for selecting intermittent pumping wells utilizing the analytic network process (ANP) and fuzzy logic. Initial surveys identified the main factors influencing intermittent pumping effectiveness. The ANP was employed to screen and integrate six core factors, including submergence depth and water cut. Subsequently, a fuzzy-logic-based model was developed, incorporating trapezoidal and rectangular membership functions to establish detailed correlations among the factors. The model's efficacy was validated and tested using real-world data from the oilfield. Results indicate that the model's assessments of intermittent pumping wells align closely with professional engineering judgments. This approach not only provides clear guidance for well selection but also demonstrates high scalability and adaptability across different oilfields by adjusting membership functions, thereby showcasing significant practical value. [ABSTRACT FROM AUTHOR]

The risk of both fatal accidents and non-fatal injuries in the construction industry is significantly high in most countries. To reduce this construction safety risk, the proper use of personal protective equipment (PPE) is one of the major measures on the jobsite. In this research, in order to comprehensively assess the PPE plans, a three-phase framework was proposed to identify the optimal solution for PPE planning from a set of alternatives. As a result, four main criteria and fifteen sub-criteria were identified based on a systematic literature review, and a decision-making model integrating the analytic network process (ANP) and VIekriterijumsko KOmpromisno Rangiranje was developed. As the assessment information in the survey was incomplete and vague, the fuzzy sets theory was adopted to transform the linguistic terms into fuzzy numbers for evaluation. The model further calculated the weight of each criterion and prioritized the potential PPE plan alternatives. Finally, the presented model was implemented in a case study to verify its feasibility and applicability for practical construction management. The proposed method enables the selection of the most compromising solution as the optimal PPE plan. This research assists decision-makers and safety planners at construction workplaces to improve the overall safety performance and reduce accident risks, which significantly contributes to construction safety management and practice. [ABSTRACT FROM AUTHOR]

To better reduce the carbon emissions of a park-integrated energy system (PIES), optimize the comprehensive operating cost, and smooth the load curve, a source-load flexible response model based on the comprehensive evaluation index is proposed. Firstly, a source-load flexible response model is proposed under the stepped carbon trading mechanism; the organic Rankine cycle is introduced into the source-side to construct a flexible response model with traditional combined heat and power (CHP) unit and electric boiler to realize the flexible response of CHP to load; and the load-side categorizes loads into transferable, interruptible, and substitutable loads according to the load characteristics and establishes a comprehensive demand response model. Secondly, the analytic network process (ANP) considers the linkages between indicators and allows decision-makers to consider the interactions of elements in a complex dynamic system, resulting in more realistic indicator assignment values. Considering the economy, energy efficiency, and environment, the PIES optimization operation model based on the ANP comprehensive evaluation index is constructed to optimize the system operation comprehensively. Finally, the CPLEX solver in MATLAB was employed to solve the problem. The results of the example show that the source-load flexible response model proposed in this paper reduces the operating cost of the system by 29.90%, improves the comprehensive utilization rate by 15.00%, and reduces the carbon emission by 26.98%, which effectively enhances the system's economy and low carbon, and the comprehensive evaluation index based on the ANP reaches 0.95, which takes into account the economy, energy efficiency, and the environment, and is more superior than the single evaluation index. [ABSTRACT FROM AUTHOR]

Abstract The purpose of this study is to identify and analyze the application barriers and internal mechanisms of BIM technology in green building projects. It is found that BIM technology can effectively integrate information and optimize management, but its application still faces economic externalities and requires government intervention to promote its development. Through the analysis of five aspects of technology, economy, management, policy and environment, we identified 16 influencing factors and focused on nine key factors, such as insufficient technology maturity and high-cost issues. Research shows that policy and management factors play a fundamental role in BIM adoption and influence economic effectiveness through complex interactions. Based on the ISM-ANP coupling model, we propose that the government should encourage technological innovation and personnel training to promote the effective application of BIM technology in green buildings. This study provides a theoretical reference for the application of BIM and green building on a global scale.

This study aims to evaluate the impact of big data analytics (BDA) on the performance of healthcare supply chain management (HCSCMP) by examining both overall efficiency improvements and identifying critical success factors for effective implementation. Through a systematic literature review, the research investigates how BDA enhances real-time decision-making within healthcare supply chains (HCSCs) and identifies the key enablers required for successful BDA adoption. A comprehensive search strategy was employed to analyze 65 papers, resulting in the inclusion of 39 studies published between 2016 and 2023. The review revealed a preference for literature reviews and questionnaires as the primary research methods. The findings indicate that BDA significantly improves HCSCs’ efficiency, particularly in real-time decision-making and operational management. However, successful BDA implementation depends on addressing critical enablers and overcoming associated challenges.

This study aims to evaluate the impact of big data analytics (BDA) on the performance of healthcare supply chain management (HCSCMP) by examining both overall efficiency improvements and identifying critical success factors for effective implementation. Through a systematic literature review, the research investigates how BDA enhances real-time decision-making within healthcare supply chains (HCSCs) and identifies the key enablers required for successful BDA adoption. A comprehensive search strategy was employed to analyze 65 papers, resulting in the inclusion of 39 studies published between 2016 and 2023. The review revealed a preference for literature reviews and questionnaires as the primary research methods. The findings indicate that BDA significantly improves HCSCs’ efficiency, particularly in real-time decision-making and operational management. However, successful BDA implementation depends on addressing critical enablers and overcoming associated challenges.

Nowadays, a new emerging tourism industry, named fisherman's homestay, has become a very representative marine leisure tourism project, widely promoted in coastal areas in China. However, the development of China's fisherman's homestay industry is not yet mature and there are many problems, such as incomplete laws and regulations, lack of infrastructure, and severe homogenization. Therefore, it is very important to help the owners of fisherman's homestay improve the service quality. Based on the Service Quality Gap Model, this paper establishes an evaluation index that affects the service quality of fishermen's homestay. We apply decisionmaking trial and evaluation laboratory-based analytic network process (DANP) to identify the critical factors and the causal relationship between them. And the grey clustering model is used to evaluate the service quality of Liaoning province and other five places. Experimental results reveal those six factors, including surrounding facilities, online marketing, room infrastructure, personalized service, community co-prosperity, and attention to harmonization with the environment, contribute to improving the service quality of fisherman's homestays. The fisherman's homestays in Shandong Province, Liaoning Province, and Zhejiang Province are in "excellent" level, and the fisherman's homestays in Fujian Province and Guangxi Zhuang Autonomous Region are in "good" level. [ABSTRACT FROM AUTHOR]

The aging population in Taiwan has increased the demand for long-term care and healthcare facilities, posing challenges in addressing highly infectious diseases, particularly among vulnerable groups like the elderly and disabled. Existing literature on nursing homes primarily focuses on influenza and general public health emergencies, neglecting preventive policies for highly infectious and less curable diseases. With limited treatment options and vaccines for emerging infectious diseases like COVID-19, exploring preventive strategies becomes crucial. This study addresses the research gap by utilizing the fuzzy multi-criteria decision-making (FMCDM) method, including the fuzzy Delphi method, fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL)—based analytic network process, fuzzy technique for order preference by similarity to ideal solution (TOPSIS) and fuzzy VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR). Methodological enhancements, such as integrating fuzzy importance-performance analysis and fuzzy DANP into a 2D matrix, are proposed. The study also considers resource acquisition and technical difficulty, leading to fuzzy multidimensional importance-performance analysis. Incorporating the theory of inventive problem-solving (TRIZ) into FMCDM addresses practical solution gaps from previous evaluations. The study provides pertinent recommendations for academic and related institutions to enhance preventive strategies and contingency policies for highly infectious diseases in nursing homes and healthcare facilities. The research contributes methodological advancements and practical insights by integrating fuzzy decision-making methods and TRIZ, facilitating the development of effective preventive measures and policies. [ABSTRACT FROM AUTHOR]

Multi-criteria decision-making (MCDM) methods provide a framework for addressing sustainable forest management challenges, especially under climate change. This study offers a systematic review of MCDM applications in forest management from January 2010 to March 2024. Descriptive statistics were employed to analyze trends in MCDM use and geographic distribution. Thematic content analysis investigated the appearance of MCDM indicators supplemented by Natural Language Processing (NLP). Factorial Correspondence Analysis (FCA) explored correlations between models and publication outlets. We systematically searched Web of Science (WoS), Scopus, Google Scholar, Semantic Scholar, CrossRef, and OpenAlex using terms such as 'MCDM', 'forest management', and 'decision support'. We found that the Analytical Hierarchy Process (AHP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) were the most commonly used methods, followed by the Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE), the Analytic Network Process (ANP), GIS, and Goal Programming (GP). Adoption varied across regions, with advanced models such as AHP and GIS less frequently used in developing countries due to technological constraints. These findings highlight emerging trends and gaps in MCDM application, particularly for argan forests, emphasizing the need for context-specific frameworks to support sustainable management in the face of climate change. [ABSTRACT FROM AUTHOR]

The primary objective of this research is to design a sustainable supply chain agility model in the oil and gas industry of Bushehr Province. This study employs a mixed-method approach (qualitative-quantitative), content analysis, the fuzzy DEMATEL technique, and the Analytic Network Process (ANP). The statistical population consists of managers, officials, and mid- to senior-level experts from companies operating in the oil and gas industry of Bushehr Province. A sample size of 10 managers, experts, and industry specialists was selected for each stage. The qualitative findings revealed that sustainable supply chain agility indicators are comprised of environmental factors (green purchasing, eco-friendly and economic design and packaging, environmental preservation), economic factors (adoption of information technology, responsiveness, speed, competence, flexibility), and social factors (customer collaboration, ethical purchasing, social responsibility, compliance with laws, integration of relationships, and supplier collaboration). In the quantitative section, the first stage using the fuzzy DEMATEL approach showed that environmental factors fall under the category of effect criteria, while economic and social factors fall under the category of cause variables. ANP findings indicated that among the environmental factors, the green purchasing indicator holds the highest weight (0.33), followed by the environmental preservation indicator (0.087) and eco-friendly and economic design and packaging (0.086). Among the economic factors, the speed indicator has the highest weight (0.0524), followed by flexibility (0.0513) and competence (0.0505). Among the social factors, the customer collaboration indicator (0.0439) and compliance with laws (0.0438) have the highest weight. [ABSTRACT FROM AUTHOR]

In a competitive business environment, companies must carefully evaluate a range of complex factors to select suppliers that align with operational requirements and market demands. This study employs the Analytic Network Process (ANP) to identify and prioritize critical criteria for supplier selection, including halal certification, quality, sustainability, cost, delivery, flexibility, responsiveness, and technical capabilities. Data were collected through semi-structured interviews with supply chain managers and questionnaire-based surveys, integrating qualitative and quantitative insights. The ANP model was used to analyze the interdependence between these criteria, revealing that quality ranks highest (0.331), followed by halal certification (0.231) and cost (0.157). These findings highlight the priority given to maintaining high product quality and strict adherence to halal standards over short-term cost considerations. Supporting factors such as delivery, flexibility, responsiveness, technical capabilities, and sustainability were also evaluated for their roles in maintaining an efficient supply chain and meeting international logistics requirements. The structured ANP framework provides practical insights for halal instant food manufacturers, enabling them to optimize supply chain management and align with regulatory standards, market demands, and sustainability objectives. This approach enhances export capabilities and strengthens the competitive position of halal food producers in the global market. [ABSTRACT FROM AUTHOR]

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). [ABSTRACT FROM AUTHOR]

The survivability of out-of-hospital cardiac arrest patients in China is notably low, at less than 1%, primarily due to difficulties in accessing nearby Automated External Defibrillator (AED) devices during emergencies. Therefore, the strategic deployment of AEDs is crucial for improving patient survival. This study adopts a novel hybrid methodology that integrates the Fuzzy Analytic Network Process (FANP) and Grey Relational Analysis (GRA) to assess and prioritize the critical factors for optimizing AED deployment in China. In the FANP model, the rate of cardiopulmonary resuscitation training among individuals in the area, the rate of AED training among individuals in the area, and records of AED device usage within the area are key factors for improving the effectiveness of AED deployment. Furthermore, in the GRA model, the factors with higher gray relational degrees are Visibility, Social Environment, and Accessibility. This analysis sheds light on which secondary indicators can have the most significant impact on improving specific primary indicators. The insights from this study can guide the optimization of AED deployment strategies in China and offer practical solutions for enhancing the deployment of relevant public medical facilities. [ABSTRACT FROM AUTHOR]

Before integrating Autonomous Vehicles (AVs) into transportation systems, it's important to evaluate various aspects to facilitate their adoption. Numerous factors are likely to be crucial in this process. This research investigates the critical success factors influencing the adoption of AVs in sustainable urban transportation through a hybrid fuzzy Multiple-Attribute Decision-Making (MADM) approach. The primary aim is to identify key criteria and sub-criteria perceived by transport experts, shedding light on the complex dynamics of AV adoption. Methodologically, a fuzzy Decision Making Trial and Evaluation Laboratory (DEMATEL) is employed to unveil cause-and-effect relationships among the main criteria, determining their respective weights. Subsequently, fuzzy Analytic Network Process (ANP) is applied to calculate the weights of criteria and sub-criteria based on the fuzzy DEMATEL results. The study considers seven major factor dimensions: economic, technical, operational, environmental, safety and risk, social and regulatory, and user acceptance. Key findings underscore user acceptance, financial costs, and environmental impact as the most pivotal criteria, emphasising their significance in the eyes of transportation experts. Contrarily, technological and operational criteria hold the lowest weight in the considered criteria for AV adoption in transportation networks. This research provides valuable insights into critical barriers and opportunities in the adoption of AVs, contributing to the advancement of sustainable urban transportation. • Identification of critical success factors for AV adoption in urban transportation networks. • Fuzzy DEMATEL analysis reveals cause-and-effect relationships among criteria. • Integration of fuzzy ANP enables weighted evaluation and ranking of criteria. • User acceptance, financial costs, and environmental factors are crucial for AV adoption. [ABSTRACT FROM AUTHOR]

Understanding the flood resilience of an area is an important task for decision-makers, practitioners, and community members. However, despite the wide acceptance of the need for resilience assessment in recent years, there has been no clear agreement on what flood resilience exactly constitutes and thus no consensus on the way in which it should be quantified. As such, this study aims to identify the most pivotal indicators to establish a standardised sustainable flood resilience framework (SFRF) for an overall measure of resilience before a flood event. The framework uses the United Nations Sustainable Development Goals (UN SDG) indicators as a benchmark to establish a measurement structure that can be consistently implemented globally, using publicly sourced data. Users of the SFRF will be able to assess whether their target area has successfully achieved the conditions required for flood resilience and as a result, the associated UN SDG targets. A detailed review of 55 journal articles related to flood resilience assessment was first conducted to identify the most frequently used indicators globally across the different frameworks in the literature. A hybrid method using the decision-making trial and evaluation laboratory (DEMATEL) approach combined with the analytic network process (ANP) was then adopted to rank the top indicators in terms of their importance in evaluating the flood resilience. Finally, two examples are provided to show how the SFRF established in this study can enable users to make a universally standardised assessment of the level of flood resilience for a specific area. [ABSTRACT FROM AUTHOR]

The multi-functional integrated RF system (MIRFS) is a crucial component of aircraft onboard systems. In the testability design process, traditional methods cannot effectively deal with the inevitable differences between system designs and usage requirements. By considering the MIRFS's full lifecycle characteristics, a new testability allocation method based on multi-criteria decision-making (MCDM) is proposed in this paper. Firstly, the testability framework was constructed and more than 100 indicators were given, which included both different system-level and inter-system indicators. Secondly, to manage parameter diversity and calculate complexity, the basic 12 testability indicators were optimized through the Analytic Hierarchy Process and Technique for Order Preference by Similarity to Ideal Solution (AHP-TOPSIS) method. Thirdly, the detailed testability parameters were obtained by using the Decision-Making Trial and Evaluation Laboratory and Analytic Network Process (DEMATEL-ANP) to reduce the subjectivity and uncertainty. Finally, an example was utilized, and the results show that the MCDM method is significantly better than traditional methods in terms of accuracy and effectiveness, which will provide a more scientific basis for the MIRFS testability design process. [ABSTRACT FROM AUTHOR]

Chinese independent clothing designer brands are clothing brands founded and operated by local Chinese designers. In recent years, China's independent fashion designer brands have been in a state of continuous growth. Such types of brand are good at promoting and selling through the e-commerce model of brand integrated stores, buyer stores, fashion weeks, showrooms and online small batch pre-sales. They have formed an emerging brand force in China, being mainly small and medium-sized startups. However, the competitiveness of Chinese independent fashion designer brands is still in the market exploration stage, and the development of its evaluation system research and cultivation strategies is slow. As market competition intensifies, it has become increasingly important to discover and tap a brand's core competitiveness to obtain excess profits. In order to facilitate the strategic decision making of enterprises and ensure that the core capabilities of brands or designers match market opportunities, it is necessary for us to summarize the factors affecting brand competitiveness and explore the core influencing factors and mechanisms. To enhance the core competitiveness of China's independent fashion designer brands, the key indicators for the development of China's independent fashion designer brands competitiveness are identified. This study systematically identifies relevant indicators based on the understanding of the brand ecology and the review of previous research results. The brand competitiveness of Chinese independent fashion designers is investigated from the two dimensions of internal force and external force, and the internal force is divided into brand innovation power, brand resource financing and supply power, brand marketing power and brand quality support power. The external forces are divided into seven categories, including brand financial strength, brand market strength, and brand image strength, which are considered as first-level evaluation indicators. Sixteen second-level indicators and 33 third-level indicators are selected to construct an evaluation index system for the brand competitiveness of Chinese independent fashion designers. The ANP method is used to analyze the correlation between indicators to form an evaluation model and determine the weight and priority of each indicator. Compared with other evaluation index systems, the evaluation system of the brand competitiveness of independent fashion designers in China can focus on the development characteristics and operating rules of the market. It can help many small and micro independent fashion designer brand companies to clarify their own strategic flaws and scientifically and objectively identify important factors affecting the future development of the brand. The research results show that the newly constructed evaluation model can guide the development strategy of the core competitiveness of Chinese independent fashion. designers brands, and can accurately reflect the important factors that affect the brand competitiveness of Chinese independent fashion designers. The results show that the primary task to improve its brand competitiveness is to enhance brand resource financing, brand image, and brand innovation. Among them, the factors that have a great impact on the brand competitiveness of independent fashion designers in China include policy support, brand cluster incentive index, sales growth rate, designers professional quality index, and market share. For decision makers of new brands and small and medium-sized enterprises, a complete and scientific evaluation system can quantify the brands operating status and is a beneficial tool for brand management. The construction of the evaluation system can promote the continuous updating and iteration of the brand, and has positive guiding significance for the maintenance of industry in order and long-term high-quality development of competitiveness in China's independent fashion designer brand market. The research on the evaluation system relies on the market environment. Therefore, as China's independent fashion designer brand market matures, phased repair and update of the shortcomings of the evaluation. system are the direction of future research. Faced with the current imperfect and unsound market mechanism, the intellectual property rights, talent and supply chain issues of China's independent fashion designer brands are also the focus of attention. [ABSTRACT FROM AUTHOR]

E-government transformation requires a deeper understanding of contextual factors, including prevailing challenges. Significantly, few studies have raised that e-government challenges are not independent and that their interdependencies warrant further investigations. This study aims to analyse the interdependencies of e-government challenges using qualitative and quantitative methods – PESTELMO (Political, Economic, Socio-cultural, Technological, Environmental, Legal, Managerial and Organisational) analysis method and DEMATEL (Decision-Making Trial and Evaluation Laboratory) and ANP (Analytic Network Process) respectively. PESTELMO analysis method categorised 27 e-government challenges in Tanzania, which were then subjected to DEMATEL. DEMATEL results show that net causes are political, economic and legal challenges, while net receivers are sociocultural, technological, environmental, managerial and organisational challenges. The ANP results reveal that economic challenges are the most significant among the net causes. Hence, e-government policy and strategy makers may want to prioritise economic challenges to propagate beneficial results. This is the first study that analyses, visualises and attempts to measure the interdependencies among e-government challenges in Tanzania. The contributions of this paper lie in the empirical analysis of e-government challenges. The results provide insights to practitioners and researchers of e-government in Tanzania on the most critical challenges/hurdles to focus on for successful e-government transformation. [ABSTRACT FROM AUTHOR]

The social risk of a community renewal project is a macro concept, which is composed of many micro social risk factors. Community renewal projects involve a large number of stakeholder subjects, and the relationship between the subjects is intricate and complex, which leads to a more diversified source of social risk factors behind community renewal projects. There are interactions and interdependence among many factors, and complex interactions form a coupled relationship between the factors. In this paper, an original corpus is constructed based on online and offline data, and 19 risk factors of community renewal projects and the coupling effects of the factors are identified through the grounded theory. The factor weights are solved through the analytic network process (ANP). The dynamic evolution model of social risks is constructed through the system dynamics model based on the factors, the coupling effects of the factors, and the factor weights, so as to simulate the dynamic evolution process of the social risks. The results show that factors such as the management mechanism soundness have larger weights, and in the process of social risks evolution, core factors such as unsound management mechanism will trigger a series of other risk factors, which will increase the overall social risks. This paper identifies the key factors of social risks, clarifies the complex coupling relationship between the factors, provides a dynamic evolution model, reveals the dynamic evolution process of social risks, and provides theoretical basis and countermeasure suggestions for efficiently identifying and controlling the social risks of community renewal projects. Practical Applications: Community renewal projects involve numerous stakeholders, including the government, enterprises, and residents. These stakeholders interact frequently, creating complex relationships that significantly impact the project. The diverse factors from these stakeholders can lead to significant social risks in community renewal projects, with these factors influencing and interacting with each other. This paper constructs a dynamic evolution model of social risks, which can reveal how social risk factors from diverse entities evolve dynamically. It uncovers the micro-level components behind the macro concept of social risks, helping managers and practitioners clarify the constituent factors of social risks and their dynamic interrelationships. By predicting social risks and their evolution in community renewal projects, this model provides a theoretical basis and feasible suggestions for efficiently identifying, evaluating, analyzing, and controlling social risks. Ultimately, it contributes to enhancing the efficiency and sustainability of community renewal projects. [ABSTRACT FROM AUTHOR]

In order to identify the greater risks in the implementation of the new construction technology of 'Embedded positioning construction technology of rotary digging pile hole casing'. And further explore the construction technical risk factors and the relationship between them. On the basis of the existing research and related standards, this paper uses the work decomposition method (WBS-RBS) to construct the construction technical safety risk index system from four dimensions: natural environment, material and equipment, construction quality and working personnel. And use the decision laboratory method (DEMATEL) to establish the internal relationship between the risk evaluation indicators, and then use the network analytic hierarchy process (ANP) method to determine the weight of the risk evaluation index, establish a risk assessment model based on DEMATEL-ANP and carry on the example operation. The results show that the burying stability, fixing mode, type, upper position and installation stability of the reamer are the key work to ensure the normal implementation of the technology. [ABSTRACT FROM AUTHOR]

Energy storage systems (ESS) are essential in establishing renewable energy systems. The implementation of ESS, particularly in countries that have only recently begun their shift toward renewable energy, however, is far from fully realized. Hence, this presents an opportunity to compare different types of ESS using the SPELL framework that identifies criteria based on the social, political, economic, legal, and logistic factors that influence the successful implementation of such systems in countries with developing energy infrastructures, and this is explored in the Philippine context. This study proposes a multi-criteria decision-making method built on a hybridized Best-Worst Method, Analytic Network Process, and Decision-Making Trial and Evaluation Laboratory (BWM-ANP-DEMATEL) framework, allowing the interdependence in evaluating the importance of criteria such as price perception, public understanding of ESS, legal frameworks, and supply chain readiness to be considered in the design of the model. It was found that the levelized cost under the economic factors is considered as the most critical criterion for implementation based on both BWM-ANP-DEMATEL (w = 0.1565) and BWM (0.2027) only, representing the methods performed with and without considering influence, while perceived health under social factors is the least critical (0.0477, 0.0286). Application of the selection model on various types of ESS showed that battery-based energy storage systems, particularly lithium-ion batteries, are prioritized, followed by pumped hydro storage due to their relatively affordable cost and more widely available infrastructure compared to most other ESS considered in the study. Meanwhile, flywheel storage is the lowest ranked due to lower familiarity and legal framework for its implementation. [ABSTRACT FROM AUTHOR]

To address the existing issues in the development of the textile intangible cultural heritage industry and leverage its competitive advantages, an evaluation system for the competitiveness of the textile intangible cultural heritage industry is established by analyzing the operation process of the industry and using Porter's Diamond model. A correlation structure model of the evaluation indicators was further constructed using Analytic Hierarchy Process (ANP), and the weights of each indicator were determined by combining the Delphi method and expert scoring method. To verify the effectiveness of the model, three provinces, Zhejiang, Hunan, and Guizhou, were selected for empirical analysis. The evaluation model obtained in this study provides an important theoretical basis and practical guidance for local governments to formulate strategic policies to promote the development of the textile intangible cultural heritage industry. [ABSTRACT FROM AUTHOR]

Background: This research endeavors to enhance supplier selection processes by combining the Analytic Network Process (ANP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methodologies, with a specific focus on sustainability criteria. Method: Initially comprising 21 sub-criteria derived from prior research, the selection criteria are refined to 17, eliminating redundant elements. The core principle guiding this refinement is the comprehensive coverage of economic, social, and environmental dimensions, essential for sustainable supplier evaluation. Results: The study's outcomes underscore the paramount importance of economic criteria (0.0652) in supplier selection, followed by environmental (0.0343) and social dimensions (0.0503). Key sub-criteria contributing significantly to this evaluation encompassed consistent product quality, competitive raw material pricing, proficient labor capabilities, recycling potential, punctual delivery performance, and effective waste management practices. Conclusions: These sub-criteria are thoughtfully integrated into the sustainable assessment framework, aligning seamlessly with the economic, environmental, and social criteria. [ABSTRACT FROM AUTHOR]

The aim of this study was to study the impact of artificial intelligence (AI) on enterprises in terms of strategy, technology, business operations, and organizational management. This study used grounded theory analysis to identify the influencing factors of AI technology application maturity in Chinese enterprises. Taking Chinese film and television enterprises as an example, this study constructed an AI technology application maturity evaluation index system for enterprises based on the analytic network process (ANP) and evaluated the application maturity of AI technology in enterprises in terms of enterprise strategy, technology, business operations, and organizational management. To comprehensively evaluate and empirically analyze the application maturity of enterprise AI technology, this study calculated the index weight based on the ANP, and combined it with the fuzzy comprehensive evaluation method to construct a comprehensive evaluation model. The research results showed that intelligence strategy was the element that was believed to be most affected by the maturity of enterprise AI technology. For technology, intelligence technology and equipment were the elements that were believed to be affected the most. For business operations, smart shooting was the element that was believed to be affected the most. With respect to organizational management, corporate culture was the element that was believed to be most affected. The results showed that the proposed methods for evaluating the application maturity of enterprise AI technology are scientific and effective. The results of this study provide a reference for promoting the application of AI, implementing the intelligence transformation, and enhancing the core competitiveness of enterprises. [ABSTRACT FROM AUTHOR]

Due to many unexpected events, international enterprises are facing an increasing supply and demand uncertainty. From the perspective of logistics demands, selecting the appropriate logistics service providers is an important issue. From the perspective of logistics service providers, satisfying customers’ needs in competitive markets is vital. This study focuses on three multinational logistics companies providing services in China, Hong Kong, and Taiwan as case studies for investigating the selection criteria in the context of logistics service providers and for evaluating their performance in an uncertain market. The criteria with a higher total influence and net influence should receive a higher weight than other criteria. However, the existing modified DANP-mV model that integrates the DEMATEL (Decision-Making Trial and Evaluation Laboratory) method, the ANP (Analytic Network Process) method, and the mVIKOR (modified Vlsekriterijumska Optimizacija I Kompromisno Resenje) method often does not follow this logic. This study proposes a new model called rDANP-U (revised DANP with mean group Utility) with the purpose of generating more proper weights for the selection criteria with a higher total influence and net influence. Further on, the mean group utility component derived from the VIKOR method is employed for evaluating the performance of the three chosen logistics service providers operating in an uncertain environment and for providing improvement strategies for them. [ABSTRACT FROM AUTHOR]

This paper aims to assess the extent to which Brazilian companies adhere to the accuracy, balance, clarity, comparability, reliability, and timeliness criteria recommended by the Global Reporting Initiative (GRI) standards. A survey was conducted with experts in sustainability reporting with extensive experience in the Brazilian corporate context. The analytic hierarchy process was employed to assign weights to the criteria, and a grey fixed weight clustering model was proposed to analyze the collected data. Clarity and accuracy received the highest weights, which is concerning given the quality observed in sustainability reports. A lower emphasis on timeliness in sustainability reporting reflects many companies' publishing practices, prompting more efficient reporting. The majority of respondents perceive the quality of information in sustainability reports from Brazilian companies as falling within the medium maturity range, suggesting significant room for enhancement. The originality of this study lies both in the methodological approach, which combines multicriteria decision techniques capable of incorporating uncertainty related to data on sustainability reports, as well as in the results that provide information for improving sustainability reporting practices. The findings provide a foundation for companies and policymakers to enhance sustainability reporting, particularly in developing nations, promoting transparency, accountability, and international standard compliance. [ABSTRACT FROM AUTHOR]

Brand collaboration requirement (BCR) evaluation is a key premise for core manufacturing enterprises to lead the collaborative brand construction of a large-scale manufacturing industry value chain (LSMIVC). Because brand collaboration (BC) in LSMIVC requires interaction with other businesses, BCRs are interactional and decision-makers come from multiple groups. However, existing requirement evaluation approaches rarely consider the interactional nature of requirements and the multiple groups nature of decision makers, producing unstable, easy-to-fail, and inaccurate results. Therefore, this study presents a multi-group decision-making approach based on a decision-making trial and evaluation laboratory and analytic network process (DEMATEL-ANP). This approach integrates the assessment information of BCRs from group decision-makers and prevents unstable and easily invalid assessment results owing to an incomplete decision-maker team. Additionally, DEMATEL-ANP was used to rank the interaction BCRs, which improved the accuracy and effectiveness of the requirement evaluation. Finally, the developed approach and model were tested against the air-conditioning industry value chain. The case study shows that the proposed method can determine requirement ranking. Comparative tests show that the proposed approach is effective and superior, and is more consistent with real-world BC situations. Therefore, the proposed approach provides a direction and theoretical basis for core manufacturing enterprises to implement BC. [ABSTRACT FROM AUTHOR]

The Analytic Hierarchy Process (AHP), Fuzzy Analytic Hierarchy Process (FAHP), and Analytic Network Process (ANP) methods are widely used for decision-making across various fields, and have shown success in numerous applications within human resource management (HRM). The purpose of this study is to present a systematic literature review on the applications of AHP, FAHP, and ANP in human resource management. The search process encompassed two main online databases, Scopus and Web of Science. This research covers a total of 180 application papers. To help readers extract quick and meaningful information, references are summarized in tabular format. The results showed that these methods have been applied in various domains of HRM such as performance management and appraisal, selecting human resources, talent attraction and retention, intellectual capital, workplace safety, reward management, e-HRM, green HRM, etc. To the best of our knowledge, no comprehensive research review has yet been conducted on the applications of AHP in HRM. [ABSTRACT FROM AUTHOR]

The high index of poor air quality and the increasing demand for oil fuel pose severe problems for Indonesia. The largest sector contributing to both of these issues is the transportation sector. Electric mobility offers a notable opportunity for decreasing carbon emissions within the transportation domain. Despite the Indonesian government's notable backing of this initiative, the implementation has been slow. Therefore, this study aims to identify the critical factors necessary for a successful transition to electric mobility. This study identifies the factors influencing the transition to e-mobility in the initial stage. Subsequently, these factors are validated and assessed by a panel of nine experts. In the validation phase, data processing involves the use of the Content Validity Index (CVI) and Modified Kappa methods. To assess relationships and prioritize essential success factors, the Decision-making Trial and Evaluation Laboratory-based Analytic Network Process (DEMATEL-based ANP) is applied. This study identifies six dimensions and 24 critical success factors. The political dimension emerges as the most significant, with the top five priorities being government funding, charging infrastructure, value proposition, fuel price, and charging time. The findings can be used to provide recommendations to the government or relevant stakeholders in supporting the shift to electric mobility in Indonesia. [ABSTRACT FROM AUTHOR]

The laboratory is a high-risk place for scientific research and learning, and there are many risk factors and great potential for harm. Hazardous chemicals are important to consider and are the key objects to monitor in a laboratory. In recent years, hazardous chemical fire accidents have occurred in laboratories in various industries, bringing painful lessons and making it urgent to strengthen the safety management of hazardous laboratory chemicals. In this study, a semi-quantitative comprehensive risk assessment model for hazardous chemical laboratory fires was constructed by combining the bowtie model, three-dimensional risk matrix, and analytic network process (ANP). This study applied this method to the management of hazardous chemicals at the TRT Research Institute; evaluated the probability, severity, and preventive components of the corresponding indicators by constructing different index systems; and calculated the evaluation results using the weight of each index. The evaluation results show that the comprehensive likelihood level is 2, the comprehensive severity level is 3, the comprehensive preventive level is 3, and the final calculated comprehensive risk level is tolerable (II). Based on the results of the risk assessment, the corresponding control measures that can reduce the fire risk of hazardous chemicals in the laboratory are proposed according to the actual situation at the TRT Research Institute. [ABSTRACT FROM AUTHOR]

The consistency analysis in AHP (Analytic Hierarchy Process) and ANP (Analytic Network Process) methods is a critical element that helps evaluate how consistent the pairwise comparisons of criteria or decision alternatives made by the decision-maker are. Inconsistent evaluations can lead to erroneous or misleading results. The article presents a simple method of graphical analysis of the consistency of these evaluations (occurring in the so-called pairwise comparison matrix). The proposed concept of spatial visualization of the relative positioning of the compared pairwise criteria or decision alternatives offers analysts, on the one hand, a straightforward and visually appealing way to formulate always consistent evaluations. On the other hand, it facilitates the identification (seeing), understanding, and correction of undesirable inconsistencies in situations where the classical method of evaluation formulation, recommended by Saaty [1], has been used, where each compared pair of elements is considered separately. [ABSTRACT FROM AUTHOR]

Stakeholder engagement in collaborative research and innovation projects poses significant challenges, particularly in complex, multistake-holder settings addressing sustainability concerns. This study proposes a novel method for stakeholder prioritization in such projects, com-biningtheanalyticnetworkprocess(ANP)toolwiththesustainabilitycategoriesoftheP5standardforsustainabilityinprojectmanagement. Its applicability and usefulness are demonstrated through a case study project, using the new stakeholder theory (NST) lens. The ANP-P5 method can assist project managers in effectively aligning stakeholder management with both sustainability and NST principles. [ABSTRACT FROM AUTHOR]

In the context of transitioning energy structures, thermal power generation is adapting to peak load regulation, highlighting the need for comprehensive studies on boiler combustion characteristics under varying load conditions. This study focuses on a 660 MW tangentially fired boiler, evaluating its combustion and pollutant generation at different operational loads: boiler maximum continuous rate (BMCR), turbine heat acceptance (THA), 75% of THA, and 40% of THA. The findings reveal a general decline in temperature, and nitrogen oxide concentration as the load decreases. However, at 40% THA, increased oxygen mole fractions lead to higher carbon dioxide and sulfur dioxide levels compared to other conditions. Through the Analytic Network Process, each parameter's impact is evaluated and scored to identify the most effective burner and deflection angle combinations. Optimal configurations are identified: a 10-degree rightward adjustment for ABDE layer burners at BMCR and a 10-degree leftward adjustment for BD layer burners at 40% THA, both enhancing combustion performance and reducing pollutants at the furnace outlet. For THA and 75% THA conditions, the industrial standard combination is recommended.