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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]

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]

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]

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]

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]

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]

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]

Automatic distribution master stations (ADMSs) are software platforms that can be used to monitor energy supply and consumption of power demand-side resources as well as to guarantee grid security. They play a vital role in maintaining the optimal performance and stability of electrical power systems. However, the stability of ADMSs is usually determined by the performance of the information interaction, which includes various challenges and complexities. Therefore, an efficient multiple-indicator filtering-based information interaction evaluation method for the ADMS is proposed in this paper. The proposed method first utilizes the principal component analysis (PCA) to filter the indicators of the ADMS. Then, the data envelopment method and the analytic network process (ANP) are employed to remove the invalid indicators and to determine the indicator weights. In this regard, the secondary screening of the indicators is completed, the effective indicators are obtained, and the accuracy of the evaluation system is improved. Results of the simulation show that the proposed method works well when evaluating information interaction performance, and it offers satisfactory performance evaluation of ADMSs. [ABSTRACT FROM AUTHOR]

Urbanization without planning causes concerns about biodiversity loss, congestion, housing, and ecosystem sustainability in developing countries. Therefore, resilience and regeneration following urbanization are critical to city planning and sustainable development. Integrating multi-criteria decision-making methods (MCDM) with geographic information systems (GIS) can be a promising method for analyzing city resilience and regeneration. This study aims to use two MCDMs, the Analytic Network Process (ANP) and the Best–Worst Method (BWM), to evaluate the resilience of metropolitan neighborhoods in Tehran. Fourteen criteria were selected to represent the city's resilience, and the weights of two models were evaluated for their spatial patterns using GIS. The results showed that the building age was the most important criterion in both methods, while the per capita green space was the least important criterion. The weights of the most important criterion, the building age, for the ANP and BWM, were 19.56 and 18.98, respectively, while the weights of the least important criterion, the per capita green space, were 2.197 and 1.655, respectively. Therefore, the MCDM with GIS provides an approach for assessing city resilience and regeneration priority. [ABSTRACT FROM AUTHOR]

With the advancement of information technology, the Internet is pivotal in today's society, serving as a global connectivity platform. Leveraging Internet technology within an enterprise can improve operational efficiency and curtail costs. However, traditional Internet platform selection methods cannot simultaneously handle quantitative and qualitative information, fuzzy semantics, and incomplete expert-provided information. To address these limitations, this study integrated the fuzzy analytic hierarchy process (FAHP) and the weighted aggregated sum product assessment (WASPAS) approaches to tackle Internet platform selection problems within an incomplete information environment. To demonstrate the validity of this research approach, this study utilized a construction industry Internet platform selection case to confirm the efficacy of the proposed novel fuzzy analytic hierarchy process-based method. Comparative analysis against the weighted sum model (WSM), weighted product model (WPM), FAHP, and typical WASPAS approaches was conducted with numerical verification, revealing that the proposed method in this study effectively manages comprehensive information and yields more rational outcomes for construction industry Internet platforms. [ABSTRACT FROM AUTHOR]

In the context of a burgeoning knowledge economy, enterprise intellectual capital has emerged as a pivotal asset for organizational growth. Evaluating it requires a comprehensive and robust index, yet there is no standard methodology for such assessments. Here, we propose an index for evaluating enterprise intellectual capital. We use the Delphi method to delineate a scientific decision structure. A grey-based decision-making trial and evaluation laboratory (DEMATEL) is coupled with an analytic network process (ANP)—i.e., grey DEMATEL-based ANP (GDANP)—to determine the relative weight of indicators. Then, we use the technique for order preference by similarity to an ideal solution to validate the effectiveness and applicability of the proposed evaluation index based on data on thirty new-technology companies in China. This study bridges a critical gap in academic discourse, and we discuss the practical implications for the strategic management of intellectual capital in corporate settings. [ABSTRACT FROM AUTHOR]

Cooperative alternatives need complex multi-criteria decision-making (MCDM) consideration, especially in resource allocation, where the alternatives exhibit interdependent relationships. Traditional MCDM methods like the Analytic Hierarchy Process (AHP) and Analytic Network Process (ANP) often overlook the synergistic potential of cooperative alternatives. This study introduces a novel method integrating AHP/ANP with Shapley values, specifically designed to address this gap by evaluating alternatives on individual merits and their contributions within coalitions. Our methodology begins with defining problem structures and applying AHP/ANP to determine the criteria weights and alternatives' scores. Subsequently, we compute Shapley values based on coalition values, synthesizing these findings to inform resource allocation decisions more equitably. A numerical example of budget allocation illustrates the method's efficacy, revealing significant insights into resource distribution when cooperative dynamics are considered. Our results demonstrate the proposed method's superiority in capturing the nuanced interplay between criteria and alternatives, leading to more informed urban planning decisions. This approach marks a significant advancement in MCDM, offering a comprehensive framework that incorporates both the analytical rigor of AHP/ANP and the equitable considerations of cooperative game theory through Shapley values. [ABSTRACT FROM AUTHOR]

This study proposes an approach for simultaneously treating fuzziness and randomness when conducting safety risk assessments of nuclear power plant building projects (NPPBPs). First, the interval type-2 fuzzy set (IT2FS) and analytic network process (ANP) were employed to establish an IT2FS-ANP method for modifying the solution for the weight vector and determining the mutual relationships between the assessment indexes and their weights. Second, the IT2FS and cloud model (CM) were used to establish the IT2FS-CM method to modify the solution for the expectation value. Third, the IT2FS-ANP and IT2FS-CM methods were combined to establish a model for ranking the safety risks and determining the overall safety risk level. Finally, the approach was applied to an NPPBP in northeast China to validate its applicability. [ABSTRACT FROM AUTHOR]

The optimization of the production scheme for enhanced geothermal systems (EGS) in geothermal fields is crucial for enhancing heat production efficiency and prolonging the lifespan of thermal reservoirs. In this study, the 4100–4300 m granite diorite stratum in the Zhacang geothermal field was taken as the target stratum to establish a numerical model of water-heat coupling of three vertical wells. However, relying solely on numerical simulation for optimization is time-consuming and challenging for the determination of the globally optimal production plan. The present study proposes a comprehensive evaluation method for optimizing the performance of EGS power generation based on the integration of particle swarm optimization with backpropagation neural network (PSO-BPNN) and analytic hierarchy process (AHP). Five different PSO-BPNN models were constructed based on the numerical simulation data to predict different EGS power generation performance indexes, including the production temperature, the injection pressure, the total electricity generation, the electric energy efficiency and the levelized cost of electricity. Based on these PSO-BPNN models, the weights of various thermal development evaluation indexes were calculated by AHP to conduct a comprehensive evaluation of the power generation performance of the three vertical wells EGS. The results show that the PSO-BPNN model has good prediction accuracy for EGS prediction of various performance indicators, with a coefficient of determination (R2) exceeding 0.999. The AHP evaluation of all production schemes reveals that the optimal power generation scheme entails a well spacing of 580 m, water injection rate of 56 kg/s, injection temperature of 38 °C and fracture permeability of 2.0 × 10−10 m2. Over a span of 30 years, this scheme can provide a total power generation capacity amounting to 1775 GWh, with an associated LCOE value of 0.03837 USD/kWh. This not only provides a reference for the development and optimization of geothermal systems in the Zhacang geothermal field but also provides a new idea for the optimization design of other geothermal projects. [ABSTRACT FROM AUTHOR]

The Analytic Hierarchy Process (AHP) has been a widely used multi-criteria decision-making (MCDM) method since the 1980s because of its simplicity and rationality. However, the conventional AHP assumes criteria independence, which is not always accurate in realistic scenarios where interdependencies between criteria exist. Several methods have been proposed to relax the postulation of the independent criteria in the AHP, e.g., the Analytic Network Process (ANP). However, these methods usually need a number of pairwise comparison matrices (PCMs) and make it hard to apply to a complicated and large-scale problem. This paper presents a groundbreaking approach to address this issue by incorporating discrete Markov Random Fields (MRFs) into the AHP framework. Our method enhances decision making by effectively and sensibly capturing interdependencies among criteria, reflecting actual weights. Moreover, we showcase a numerical example to illustrate the proposed method and compare the results with the conventional AHP and Fuzzy Cognitive Map (FCM). The findings highlight our method's ability to influence global priority values and the ranking of alternatives when considering interdependencies between criteria. These results suggest that the introduced method provides a flexible and adaptable framework for modeling interdependencies between criteria, ultimately leading to more accurate and reliable decision-making outcomes. [ABSTRACT FROM AUTHOR]

This research paper presents an all-encompassing methodology for multi-criteria decision-making in the apparel sector, with the particular objective of aiding in the determination of the most appropriate location within the CLMV subregion. The research is conducted in three crucial stages. The process began with the administration of a survey to proprietors of garment businesses in both Thailand and the CLMV countries. This survey resulted in the compilation of an exhaustive list of site-selection criteria and sub-criteria. Based on the findings of subject matter-expert interviews, Cambodia (C), Vietnam (V), and Myanmar (M) were identified as feasible alternatives. Subsequently, the questionnaire criteria and sub-criteria were evaluated utilizing the Fuzzy Analytic Network Process (Fuzzy ANP), which involved the utilization of meticulously designed pair-wise comparison matrices and local priorities. Five specialists from the Thai entrepreneurial community affirmed the effectiveness of Fuzzy ANP and expressed interest in expanding manufacturing operations in the CLMV subregion. The optimal location for Thai apparel manufacturers was subsequently determined using the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (Fuzzy TOPSIS). The results indicated that Vietnam is the most favorable option. In order to improve the dependability of results, an amended mixture-design scenario analysis was implemented. This analysis assessed the sensitivity and dependability of the proposed model in different scenarios, ensuring its applicability in real-world situations. In contrast to traditional models, this study integrates managerial judgments and preferences into the decision-making procedure, thereby accounting for the complex interdependencies among numerous criteria. The suggested methodology functions as a beneficial instrument for decision-makers, both domestic and international, as it integrates effortlessly into the organizational structure of the CLMV region. By harmonizing objectives pertaining to data acquisition, manipulation, retention, and dissemination, this framework not only enables enhanced decision-making processes, but also optimizes system efficiency. [ABSTRACT FROM AUTHOR]

The reduction of environmental impact in buildings and the enhancement of environmental performance in the built environment are the key objectives of sustainable development. To achieve this, the adoption of green buildings requires a comprehensive construction approach that focuses on delivering environmentally friendly solutions throughout the entire construction process. This research aims to bridge the gap between theoretical concepts and the practical realities of construction in Iran. It proposes essential criteria and assigns weights to them for creating green buildings based on the opinions of experts from different backgrounds. To understand how buildings are influenced by the environment, society and economics, relevant factors were identified using library research. Web-based surveys involving experts, including architects, engineers, and environmental specialists, were conducted to gather insights into these criteria. A total of 14 criteria were accepted and categorized into economic, environmental, and social dimensions. The Analytic Network Process (ANP) methodology was employed to assess the opinions of 45 expert participants, as provided in the questionnaire. The findings indicate that, among sustainability features, the environmental factor holds the highest significance in Iran, while the social factor is considered the least important. Looking at the sub-criteria, reducing water consumption, financial incentives, and achieving energy efficiency at a reasonable cost are given the highest priority within the environmental, economic, and social aspects of green buildings. [ABSTRACT FROM AUTHOR]

The building construction industry in mainland China is distinguished by one of the highest accident rates and numbers of fatalities. Therefore, risk assessment plays a significant role in preventing safety incidents and economic losses. However, traditional risk assessment methods are mainly experience-based which could introduce significant uncertainties in accident chain estimation, quantitative analysis, and handling with uncertainty. Safety accidents are difficult to estimate, which might lead to inappropriate safety-related decision making. To solve this problem, an innovative quantitative analysis strategy has been developed, generating a loss index for various accidents in the construction site, based on the Bayesian Network and Analytic Hierarchy Process solution. In this solution, the contribution rate of every risk factor to a certain accident can be calculated. Based on those, the loss index of each construction site can be calculated by inputting current risk factors in the construction site. Moreover, the real-time loss index can be estimated which can help the management team with more accurate decision making compared with the traditional approaches. With this model, the safety situation on the construction site can be clarified and the risk priority can be analyzed according to the dynamic condition. [ABSTRACT FROM AUTHOR]

Aiming at the fuzzification of a decision environment and the challenge of determining the weights associated with the interaction among decision-makers, this study offers an original method for (p,q)-rung probabilistic hesitant orthopair fuzzy multi-objective group decision-making, which is founded on the weight optimization principle. Firstly, the notion of a probabilistic hesitant fuzzy set is expanded to a (p,q)-rung. Secondly, the determination of subjective and objective weights is accomplished through the utilization of the Analytic Network Process (ANP) and the Entropy Method. According to the degree of deviation and dispersion of each weight, an optimal objective function is constructed, and the neural network is used to iteratively solve for the best scheme of the comprehensive weight. Subsequently, the Elimination Et Choice Translating Reality (ELECTRE) approach was refined and applied to decision-making in the (p,q)-rung probabilistic hesitant orthopair fuzzy environment. Finally, comparative analysis was used to demonstrate the new method's effectiveness and superiority. [ABSTRACT FROM AUTHOR]

The multi-criteria group decision-making approach, rooted in fuzzy mathematics theory, is employed to address the globally significant issue of green construction in this paper. The construction industry is one of the most prominent contributors to carbon emissions, which is evident throughout the entire supply chain. Meanwhile, the renovation of old residential communities is a large-scale urban construction project in China. In striving to advance the sustainable development of the construction industry and meet decarbonization goals, the attention has shifted towards green construction in the renovation of old residential communities. However, substantial gaps persist in both technical innovation and practical application of green construction. This study aims to identify the factors that influence the popularization and implementation of green construction practices in the renovation of old residential communities. To achieve this, a comprehensive decision-making approach is sought, and these factors are thoroughly investigated. In this paper, we propose a hybrid decision-making framework that incorporates grounded theory, the fuzzy decision-making and trial evaluation laboratory (DEMATEL) method, and the analytic network process (ANP) method. Leveraging triangular fuzzy numbers and other fuzzy mathematical theories, this approach is designed to assess the factors that influence the popularization and implementation of green construction practices, uncovering their interrelationships and mechanisms. The results indicate the comprehensive nature of advancing green construction practices, encompassing the entire supply chain involved in the renovation of old residential communities. Among these factors, social participation and market environment emerge as the most influential. Building upon these conclusions, this paper offers specific recommendations. Ultimately, this study equips the construction industry with both a theoretical foundation and a methodological framework to popularize and implement green construction practices effectively. [ABSTRACT FROM AUTHOR]

Following the financial crisis of the last decade and the increasing complexity of financial products, the European Union has introduced investor protection tools that require professionals to carry out a client profiling process. The aim is to offer products that are in line with the characteristics of the individual. The classes of variables for comprehensive profiling are obtained by matching the elements proposed by the Markets in Financial Instruments Directive and studies of classical finance. However, behavioural finance studies, which emphasise the importance of behavioural attitudes, are not clearly considered in this structured profiling. The present paper discusses the implementation of an analytic network process to support financial decision-making in a behavioural context, combining regulatory guidance and qualitative and quantitative evidence from the literature. The Kersey Temperament Model is used as the behavioural model to construct the network cluster that incorporates personality into the valuation. Uncertainty management is incorporated through recent studies in the context of intertemporal choice theory. The functionality of the network is verified through a case study, where two alternatives with different characteristics are considered to meet the same investment objective. The present approach proves how the generated structure can provide strong support for financial decision-making. [ABSTRACT FROM AUTHOR]

In the context of green, low-carbon, and sustainable construction, the safety management of smart construction sites has been a key issue. Current related research mainly focuses on the application of technology, but lacks methods to evaluate the safety management level. Therefore, this research aims to construct a smart construction site safety management evaluation model from a resilience perspective. First, this research identified and screened the indicators initially based on the 4R resilience characteristics and 4M theory by analyzing the policy texts of smart construction site safety management. Then, through expert consultation, the ISM model of resilience indicators was established to determine the evaluation indicator system of smart construction site safety management. Next, the weight of each indicator was determined with the help of the analytic network process, and the evaluation criteria of the indicators were formulated according to the existing specifications and expert interviews; then, the evaluation model of smart construction site safety management was established. Finally, the feasibility of the model was proved through a case study. The findings of the research show that in terms of weights, management has the highest score, followed by media, man, and machine. However, more resilience measures are used for the safety management of machine than the other three in policy texts. Obviously, there is a deviation between weights and resilience characteristics. These findings help reveal the current situation of safety management at smart construction sites, which is of great significance for improving resilience. The findings also help smart construction sites to realize the upgrading of safety, efficiency, and greenness, and promote the sustainable development of smart construction sites as well as the construction industry. [ABSTRACT FROM AUTHOR]

Planning alternatives evaluation is often influenced by the evaluator's background knowledge and preferences, and its objectivity is hard to guarantee. A comprehensive evaluation method combining Geographic Information System (GIS) with system analysis technology is proposed in this paper. Using a land use issue in America as an example, GIS was combined with Fuzzy Logic, and the Analytic Network Process (ANP) method was used to evaluate three planning alternatives. The evaluation value of each qualitative index was obtained by Fuzzy Comprehensive Evaluation, and the quantitative index value was calculated by GIS algorithms. A weighted hypermatrix of ANP network was constructed to reveal the overall relative importance weight of alternatives. The results indicate that, in this case study, the factor weight rankings that influenced the selection of the land use alternative are Ecological factors (above 40%), socioeconomic factors (30%), Physical and Chemical factors (10–17%), and cumulative related factors (10%). In the long run, choices of planning alternatives will greatly affect the natural environment, the physical and chemical environment, and the social economy. The results indicate planners have to pay attention to a wide range of both qualitative and quantitative factors as much as possible in land use decisions. This study illustrates how the GIS-ANP method combine qualitative and quantitative factors in planning for a comprehensive analysis, thus improving the objectivity of evaluating land use planning alternatives and determining the importance of influencing factors. Future work aims to optimize the evaluation index system of planning, and measure index values in a more precise way. [ABSTRACT FROM AUTHOR]

Industrial crises exert considerable influence on a wide range of industries, national economies, and global economic landscapes. The primary objective of this study is to devise a crisis index specifically tailored for the petroleum sector—a vital component of South Korea's energy industry. An exhaustive analysis of the existing literature was conducted to extract pertinent elements and indicators, and indicator weights were determined using the analytic network process (ANP). Moreover, a combination of qualitative and quantitative methods was employed to rigorously evaluate the validity of the proposed crisis index. The implications derived from this study offer critical insights for stakeholders into the petroleum industry and demonstrate the potential applicability of a crisis index framework for other industries. [ABSTRACT FROM AUTHOR]

In recent years, bank-related decision analysis has reflected a relevant research area due to key factors that affect the operating environment of banks. This study's aim is to develop a model based on the linkages between the performance of banks and their operating context, determined by country risk. For this aim, we propose a multi-analytic methodology using fuzzy analytic network process (fuzzy-ANP) with principal component analysis (PCA) that extends existing mathematical methodologies and decision-making approaches. This method was examined in two studies. The first study focused on determining a model for country risk assessment based on the data extracted from 172 countries. Considering the first study's scores, the second study established a bank performance model under the assumption of country risk, based on data from 496 banks. Our findings show the importance of country risk as a relevant bank performance dimension for decision makers in establishing efficient strategies with a positive impact on long-term performance. The study offers various contributions. From a mathematic methodology perspective, this research advances an original approach that integrates fuzzy-ANP with PCA, providing a consistent and unbiased framework that overcomes human judgement. From a business and economic analysis perspective, this research establishes novelty based on the performance evaluation of banks considering the operating country's risk. [ABSTRACT FROM AUTHOR]

The assessment of multiple incoming autonomous underwater vehicles (multi-AUVs) and threat prioritization are critical to underwater defense. To solve problems troubling multi-AUV threat assessment solutions, such as difficult data analysis, high subjectivity, and rigid prioritization logic, we propose the PROMETHEE algorithm based on fusion weights calculated twice by entropy and an analytic network process (ANP), respectively. First, according to AUV detection performance and underwater confrontation situation analysis, the main criteria and indicators of threat assessment are determined. The threat assessment system is provided by unified measurement of these indicators. Then, through analysis and assessment, the weighting algorithm is designed using entropy and ANP. The subjective weight calculated based on ANP and the objective weight obtained based on the entropy method are fused twice to obtain the combined weights, and the influence of subjective and objective factors on problem analysis is considered. Finally, by analyzing the simulation results of a multi-AUV, it is proven that the proposed algorithm is scientific and effective for AUV threat assessment. According to the experimental results, accurate evaluation of the target improved by at least 10%, enabling delivery of results close to the real confrontation situation with high reliability. [ABSTRACT FROM AUTHOR]

Different sports have different fan bases. In addition to this, there is a lot of craze, enthusiasm, and zeal among people, mainly youngsters. Cricket is one among them that has tremendous popularity not only among youngsters, but among all age groups. This creates a kind of pressure among team members to perform well in every game, as well as on the selectors to select the best players for the opening, middle orders, wicketkeeping, and bowling from the pool of players. A game cannot be won by a single player or by openers, among others; rather, it is a collective effort of all the members of the team. As such, it is necessary and one of the most important tasks to choose the players wisely so that they play well in their respective position. In this study, we try to formulate a model using MCDM (multicriteria decision-making techniques), which evaluates not only the performance of the players, but also the performance of different sets (i.e., openers, middle orders, wicket-keepers, and bowlers). For this, we propose a novel ANP-DEA (analytic network process-data envelopment analysis) technique and evaluate the best and worst performing set and their performance evaluation. A case study is conducted to properly visualize the proposed model. [ABSTRACT FROM AUTHOR]

Within the competitive global market and fast-advancing technology environment, in order to survive and to succeed, firms need to spontaneously respond to market changes and the uncertainty of customer needs. Therefore, New Product Development (NPD) is extremely important for the success of firms. Artificial Intelligence (AI) has gradually entered people's lives, and consumer demand for AI products is increasing. Firms need to understand the AI development trend and consider the preferences of consumers for AI-related products under social changes so that suitable consumer AI products can be properly developed. In this study, the evaluation and selection of operation systems for a commercially available AI product (smart TV) is studied, and a Multi-Criteria Decision-Making (MCDM) model for facilitating the selection of the most suitable operation system for product development is constructed. The proposed model consists of three phases: Interpretative Structural Modelling (ISM) to construct a decision-making network, Fuzzy Analytic Network Process (FANP) to obtain the weights of factors, and Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (fuzzy TOPSIS) to rank the operation systems. The proposed model is applied to select an operation system that companies can use to develop a smart TV. The results show that the proposed model can provide a systematic method that helps companies make appropriate operation system selection decisions. [ABSTRACT FROM AUTHOR]

Production costs and global competition have increased sharply in recent years, forcing manufacturers to upgrade to the original brand manufacturer (OBM) to survive and thrive and capture more profit margins. However, studies that explore key factors that affect the success of such an important transition are lacking. Therefore, this study aims to investigate the key factors that will influence the success of contract manufacturers to upgrade to the OBM on the basis of a decision-making trial and evaluation laboratory with an analytic network process. Our results identify six key factors that exhibit a cause-and-effect relationship among the key criteria. Moreover, organizational innovation will determine the difference between the success and the failure of an OBM transition apart from material and component stability. Our findings can help researchers, policy makers, and practitioners increase their understanding of how to upgrade manufacturers successfully in global value chains. [ABSTRACT FROM AUTHOR]

Landslides along the main roads in the mountains cause fatalities, ecosystem damage, and land degradation. This study mapped the susceptibility to landslides along the Saqqez-Marivan main road located in Kurdistan province, Iran, comparing an ensemble fuzzy logic with analytic network process (fuzzy logic-ANP; FLANP) and TOPSIS (fuzzy logic-TOPSIS; FLTOPSIS) in terms of their prediction capacity. First, 100 landslides identified through field surveys were randomly allocated to a 70% dataset and a 30% dataset, respectively, for training and validating the methods. Eleven landslide conditioning factors, including slope, aspect, elevation, lithology, land use, distance to fault, distance to a river, distance to road, soil type, curvature, and precipitation were considered. The performance of the methods was evaluated by inspecting the areas under the receiver operating curve (AUCROC). The prediction accuracies were 0.983 and 0.938, respectively, for the FLTOPSIS and FLANP methods. Our findings demonstrate that although both models are known to be promising, the FLTOPSIS method had a better capacity for predicting the susceptibility of landslides in the study area. Therefore, the susceptibility map developed through the FLTOPSIS method is suitable to inform management and planning of areas prone to landslides for land allocation and development purposes, especially in mountainous areas. [ABSTRACT FROM AUTHOR]

The current global resource shortage and environmental pollution are becoming increasingly serious, and the development of the new energy vehicle industry has become one of the important issues of the times. In this paper, a nickel–cobalt lithium manganate (NCM) battery for a pure electric vehicle is taken as the research object, a heat dissipation design simulation is carried out using COMSOL software, and a charging heat generation model of the battery pack is established. Combined with the related research on the thermal management technology of the lithium-ion battery, five liquid-cooled temperature control models are designed for thermal management, and their temperature control simulation and effect analysis are carried out. Finally, the performance evaluation system of the thermal management scheme of the lithium-ion battery pack is established based on the analytic network process (ANP) and system dynamics (SD), and the performance of the above five thermal management design models is comprehensively scored and analyzed. The results show that liquid-cooled Models 1 (86.7075) and 5 (89.1055) have the highest overall scores, meeting both the temperature control requirements and the overall thermal management performance, and it is recommended to apply the working condition settings for which they are evaluated as Level I. [ABSTRACT FROM AUTHOR]

Agricultural sustainability is crucial for ensuring food security, promoting economic development, maintaining ecological balance, and achieving sustainable development goals. In this study, based on relevant theories of agricultural sustainability, an analytical framework is constructed for agricultural sustainability encompassing economic, resource, environmental, and social dimensions. The Analytic Network Process (ANP) method is employed to determine indicator weights and assess the spatiotemporal changes in agricultural sustainability levels across Chinese provinces. The findings reveal that environmental quality is the primary dimension for assessing agricultural sustainability, and the significance of the rural social development dimension is continuously increasing. Although the sustainability levels have significantly improved in various regions of China, there remain issues of development imbalance and instability. In conclusion, this paper offers a comprehensive understanding of the spatiotemporal changes in agricultural sustainability across Chinese provinces, providing valuable insights for policymakers and researchers. [ABSTRACT FROM AUTHOR]

The analytic hierarchy process (AHP) has been a widely used method for handling multi-criteria decision-making (MCDM) problems since the 1980s. However, it postulates that criteria are independent and static, which may not always hold true in realistic situations. Although several methods have been proposed to relax the assumption of independence between criteria in the AHP, such as the analytic network process (ANP), these methods do not account for time-dependent criteria in the AHP. Consequently, this paper presents an innovative method that integrates dynamic Bayesian networks (DBNs) with the AHP to model dynamic interdependencies between criteria in MCDM problems. We illustrate the proposed method through a comprehensive numerical example and compare the result with the conventional AHP. The findings suggest that the proposed method extends the AHP to accommodate time-dependent issues and, when ignoring specific information, reduces to the conventional AHP, thereby demonstrating that our approach serves as a more general AHP model. [ABSTRACT FROM AUTHOR]

As one of the most frequently occurring natural hazards, flooding can seriously threaten global security and the sustainable development of our communities. Therefore, enhancing the resilience of cities and improving their ability to adapt to flooding have become issues of great significance. This study developed a new comprehensive evaluation model of flood resilience that includes an evaluation index system from the basis of four key dimensions of social resilience, economic resilience, ecological environment resilience and infrastructure resilience. Firstly, interpretative structural modelling (ISM) was applied to analyze the structural issues affecting urban flood resilience. Secondly, the analytic network process (ANP) was then used to calculate the importance of these indicators. Finally, taking three cities (Zhengzhou, Xi'an, and Jinan) in the Yellow River Basin of China as examples, the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) was used to evaluate their current levels of flood resilience using the findings from the earlier stages. The results show that the levels of rainfall and vulnerability of groups were the fundamental factors affecting urban flood resilience. Indicators such as average annual rainfall, fixed-asset investments, and emergency rescue capabilities were also found to have a greater impact on urban flood resilience. In the study area, Xi'an was found to have a higher level of resilience due to having strong ecological environmental resilience. These findings are expected to provide a useful reference for policymakers and stakeholders involved in the management of flooding events. [ABSTRACT FROM AUTHOR]

Vulnerability assessment is a vital component of wildfire management. This research focuses on the evaluation of wildfire vulnerability in the Central Region of Portugal, an area historically affected by catastrophic fire events. The overall methodology entailed applying an analytical hierarchy process (AHP) to the relevant spatial variables for evaluating vulnerability associated with exposure, sensitivity, and response capacity at landscape and the wildland–urban interface (WUI) scale. Of the selected criteria, the existence of fuel in direct contact with built-up areas, population density, and firefighters' travel time were considered the most important criteria for inclusion in the vulnerability map. At landscape scale, 31% of the Central Region presents high and very high classes of vulnerability, while 22% of WUIs are classified as highly vulnerable to fire. Although the inland areas emerge as the most vulnerable, this approach enables scattered vulnerable hotspots to be identified in almost all of the Central Region. The results could be very helpful in terms of developing and enhancing local policies to mitigate human and material damage. [ABSTRACT FROM AUTHOR]

(1) Objective: to accelerate the digitalization of the elderly care service industry and the construction of the smart elderly care industry, this paper designs an intelligent e-procurement system for elderly suppliers selecting from the perspective of smart elderly care, which can enhance the efficiency of elderly care supply chains and assist manufacturers of elderly products in choosing a reliable, high-quality supplier during trades. (2) Methods: the e-procurement system, including six modules, is built with an improved dynamic Markov Decision Process selection model combined with an Analytic Network Process, bringing dynamic evolution of both inventory cost and purchasing cost into long-term reward calculation, and taking into account 15 common indexes and 7 specific indexes when evaluating suppliers' competitiveness. (3) Results: a real sample shows that when facing 50 suppliers with 50 different quotations, the e-procurement system selects a stable and reliable supplier that brings the best long-term profits for demand enterprises in ten purchase periods, and it makes the selecting process more efficient and more prompt. (4) Conclusions: the model can be used in the circumstance where an elderly product producer is forced to decide on a long-term strategy or reselect a new stable supplier since it is focused on choosing long-term and high-quality suppliers over numerous periods. [ABSTRACT FROM AUTHOR]

Sugar is a significant commodity for Indonesia because the need for sugar reaches 7 million tons. Meanwhile, imports from Thailand, Australia, and Brazil were approximately 5.54 million tons in 2020. Sugarcane and sugar production in East Java province is also supported by Lamongan Regency. Therefore, this study aims to evaluate the possible sugarcane plantation expansion areas in Lamongan. The evaluation process carried out in this study was an analysis of land suitability using the analytic network process (ANP) and land availability using an overlay analysis of several policy maps. Three parameters with the highest weight of the ANP were soil drainage (0.181), cation exchange capacity and base saturation (0.134), and rainfall (0.133). The total possible area for sugarcane plantations expansion in Lamongan was 32,552.37 ha and the largest class was Possible Area 2 (65.67%). The three sub-districts with the highest possible areas include Solokuro, Ngimbang, and Mantup. We recommend that the government and stakeholders extend the area allocated to sugarcane plantations in Lamongan because the possible expansion areas are still more than 30 ha, while in the 2011–2031 spatial plan they were only 8927 ha. Expansion plans must take into consideration other uses such as residence, industry, food crops, and protected areas. [ABSTRACT FROM AUTHOR]

The stability and efficiency of the waste supply chain (WSC) is related to the urban environment. This study constructed a framework of barriers to coordinating the WSC based on four perspectives: the costs and benefits, mechanisms involved, behaviors of the subjects, and technologies and standards used. We used an analytic network process based on the fuzzy decision-making trial and evaluation laboratory to calculate the centrality and weight of each barrier factor, and we determined the critical barriers to coordination by combining their results. A causality diagram of the barriers was drawn, and a scheme of coordination of the WSC was designed based on a closed-loop supply chain around the critical barriers. The results show that contradictions in benefits between subjects, contradictions between economic and social benefits, excessive subsidies, the failure of the market mechanism, the lack of a mechanism for supervision, and blocked information and distrust among the subjects are the five most critical barriers to the coordination of the WSC, with excessive subsidies the root cause of the lack of coordination. The subsidy for direct waste disposal should be used to reduce the cost of the operation of the WSC, waste recycling should be improved, an information-sharing platform should be built, and the cost of recyclable waste for manufacturers should be reduced to improve the efficiency of the WSC. [ABSTRACT FROM AUTHOR]

The blended educational method has become a common way of teaching and learning in the post-COVID-19 era. However, the related research on the selection model for the blended design teaching service quality solution is still an important research gap during this period. Therefore, this study proposed a hybrid method of fuzzy analytic network process (FANP) and technique for order preference by similarity to ideal solution (TOPSIS) to analyse the dimensions, indicators and alternatives of blended design teaching service quality. As for the findings of this research, the dimension of assurance is the most vital factor, followed by responsiveness, reliability and empathy. Meanwhile, this research discovered that the top three significant alternatives are "Employees are trustworthy", "Safe transaction mechanism and environment" and "Personalised needs of customers". Also, we found that dimensions utilised to evaluate the quality of education service are similar whether in the post COVID-19 era, in the COVID-19 epidemic or prior to the COVID-19 pandemic. The main contribution of this study is to establish a multi-criteria decision-making (MCDM) model for the ranking of the blended design teaching service quality index and solution under a fuzzy environment. Finally, the research findings of this study have a guiding role, thereby becoming a guide for the industries related to hybrid design education to maintain good service quality in similar scenarios in the future. [ABSTRACT FROM AUTHOR]

Public bike-sharing service systems (PBSSSs) offer an alternative to satisfy users' needs for short-trip connections. The PBSSSs provide options for short-trip connections and diversify the service experience for different users. PBSSSs also play a critical role in enabling urban citizens to reduce the needs to drive their cars and using public transport instead. This study explores the service performance of the public bike-sharing service systems for three styles of users. It proposes the integrated evaluation model of the public bike-sharing service system (PBSSS). The DEMATEL (Decision Making Trial and Evaluation Laboratory) was used to solve the network relation structure between aspects. The ANP (analytic network process) was applied to evaluate the relationship between aspects and component weights. VIKOR (Vlsekriterijumska Optimizacija I Kompromisno Resenje) was used to analyze the public bike-sharing system's service performance for different users regarding its strengths and weaknesses. After comparing the strengths and weaknesses of the various users' preferences for the urban public bike service systems, the study proposes a service development strategy for different styles of users based on the NRM (network relation map). The results can aid PBSSS providers and urban managers, strengthen the PBSSSs' competitiveness, and make the PBSSSs become the best urban short-trip connection transportation tool. [ABSTRACT FROM AUTHOR]

The article considers the actual problem of the ecology of urban areas associated with air pollution by industrial and energy enterprises. The study is aimed at substantiating the method of forming a plan for atmospheric air pollution observation using mobile laboratories. The quantitative characteristic of sites for different urban development zones is determined as a set of estimates. The air pollution index was chosen as a total sanitary and hygienic criterion for assessing pollution. The implementation of the decision-making problem using the analytic network process method is considered. Parameters of the city and environment that affect the assessment of atmospheric air quality were selected in the course of the study. A network structure of mutual influence of the studied parameters is formed. The architecture of the decision support system based on the proposed method is given. The created software makes it possible to automate the modeling of the distribution of pollutants in the atmosphere. The computational experiment is presented on the example of the Volgograd agglomeration, Russia. The proposed approach can significantly improve the organization of monitoring by mobile laboratories and reduce the cost of obtaining data on urban air pollution without increasing the number of existing observation laboratories, both stationary and mobile. [ABSTRACT FROM AUTHOR]

Off-site construction (OSC) is an innovative construction method that transfers most of the site-based work to a more controlled environment. Construction waste minimization, speedy schedules, higher sustainability, and better quality are some of the perceived benefits of OSC. Therefore, significant research attention has been given to OSC. However, minimal research attention has been given to procurement management in OSC, which could impact its pace of adoption. Existing studies on the procurement methods of OSC projects have overlooked several criteria related to OSC that impact the selection of the appropriate procurement methods (i.e., design-build, construction management, etc.). In addition, the literature lacks decision-making tools to assist OSC practitioners in selecting the appropriate procurement method. In this regard, this study contributes to the body of knowledge by (1) identifying the criteria that impact the selection of OSC procurement methods; (2) developing a multi-criteria decision-making (MCDM) model to select the appropriate OSC procurement methods. The developed MCDM model uses a hybrid approach of analytic network process (ANP) and evidential reasoning (ER). The ANP, which considers the interdependencies among the collected OSC procurement criteria, is used to calculate the relative importance weights through questionnaire surveys. The ER method evaluates various OSC procurement methods in accordance with the criteria importance weights. The results indicate that project quality, cost control, and funding arrangement are the prominent selection factors. On the other hand, the model reveals that the integrated project delivery (IPD) and construction management (CM) methods have the highest utility scores. The MCDM model has been validated by comparing the results with similar studies. The present study could assist OSC practitioners in selecting the appropriate procurement method for OSC projects. [ABSTRACT FROM AUTHOR]

To achieve the goals of carbon peaking, a national policy instrument for carbon peaking in the building and construction sector has been launched by the Chinese MOHURD (30 June 2022). We have developed an actionable framework for implementing these policy objectives. The framework was designed by classifying and prioritizing selected strategic government recommendations in the form of an interactive indicator system and tool for evaluating the quality of low-carbon urban and neighborhood planning actions based on the decarbonation principles of carbon emission reduction and carbon capture. The analytic network process (ANP) was applied for processing the interactions and prioritizing the indicators (23 in total for the two principles applied). A scorecard was designed for assessing low-carbon urban and neighborhood planning strategies and technologies. The practical implementation of the tool was then tested with two real planning cases, one from a fourth-tier Chinese city and another from a high-density city. The applicability of the tool is further discussed by comparing it with well-developed international assessment tools in other contexts. This article contributes to the literature by first initiating research on the use of this evaluative tool for low-carbon planning and secondly by demonstrating how researchers can convert policies into practical implementations. [ABSTRACT FROM AUTHOR]

With the growing global awareness of sustainable development, the impact of "fast fashion" on the environment has drawn much attention. This study investigated 365 fast fashion consumers with higher-than-average spending on fast fashion garments in Taiwan and analyzed the data with the analytic network process. From the perspective of social responsibility theory, the triple bottom line framework, and the concept of cradle-to-cradle, this study conducted in-depth interviews with 10 experts in the field of clothing. Based on the results, this study constructed a model with 4 core dimensions and 12 key criteria of sustainable clothing design, with the enterprise, design, and consumer sides as the decision-making options. Moreover, it was found that consumers believe that the first decision-making key that affects sustainable design is the enterprise side, and the most important green item that affects sustainable design is "cherishing". The findings of this study can provide an important reference standard for sustainable design in the apparel industry. [ABSTRACT FROM AUTHOR]