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Artificial intelligence (AI) is considered a mechanism that can improve supply chain resilience. Organisations around the world are investing in implementing AI systems to improve their supply chain and become more resilient to pandemics and disruption. At the same time, practitioners are not fully aware of the factors that impact the implementation of these systems. Alongside this, the extant literature lacks a comprehensive study that evaluates the enablers impacting the implementation of AI in production systems. This research fills this gap by identifying, defining, and evaluating the critical enablers influencing the adoption and implementation of AI in production systems. We extracted twelve enablers, created a conceptual model, and categorised the enablers based on the Technology, Organization, and Environment (TOE) framework. After categorisation, we used the analytical hierarchy process to assess the importance of the enablers presented in the model using data collected from eight experts. The results revealed that technology, as a category, is more crucial than organisation or environment. The findings also indicated that project management is the most critical of all twelve enablers. We discuss the implications of the analysis for practitioners and researchers. We also offer twelve propositions that researchers can empirically assess in future studies. [ABSTRACT FROM AUTHOR]

The ever-happening disruptive events interrupt the operationalisation of manufacturing organisations resulting in stalling the production flow and depleting societies with products. Advancements in cutting-edge technologies, viz. blockchain, artificial intelligence, virtual reality, digital twin, etc. have attracted the practitioners' attention to overcome such saddled conditions. This study attempts to explore the role of artificial intelligence (AI) in building the resilience of production function at manufacturing organisations during a COVID-19 pandemic. In this regard, a decision support system comprising an integrated voting analytical hierarchy process (VAHP) and Bayesian network (BN) method is developed. Initially, through a comprehensive literature review, the critical success factors (CSFs) for implementing AI are determined. Further, using a multi-criteria decision-making (MCDM) based VAHP, CSFs are prioritised to determine the prominent ones. Finally, the machine learning based BN method is adopted to predict and understand the influential CSFs that help achieve the highest production resilience. The present research is one of the early attempts to know the essence of AI and bridge the interplay between AI and production resilience during COVID-19. This study can support academicians, practitioners, and decision-makers in assessing the AI adoption in manufacturing organisations and evaluate the impact of different CSFs of AI on production resilience. [ABSTRACT FROM AUTHOR]

Unlike mass production manufacturing systems, where configurations are rarely changed after the initial design, reconfigurable cyber-physical systems (RCPMS) self-change their structures throughout missions and thus self-adjust production in response to demand requirements. Accordingly, such a paradigm requires enhancing selective maintenance strategy to optimise scheduling maintenance actions, selecting configuration layouts for capacity and product family changes, and achieving maintenance cost reduction and reliability maximisation. This paper is the first to propose a robust model for a selective maintenance problem with imperfect repairs in the RCPMS context. The model also integrates uncertainties originating from the imperfect observations of components' health status. The model's objectives are to maximise the expected reliability and minimise the variance and maintenance cost under maintenance resource constraints. Moreover, we propose a new deep reinforcement learning framework for solving the resulting multi-objective and combinatorial optimisation problem. In addition, we use decision values to enhance the scalarisation process by permitting the priorities of specific objectives to be adjusted after the learning process. Furthermore, we employ Analytical Hierarchy Process to adjust the static priorities with respect to the objective functions and the actual learning context. Finally, broad experiments are conducted to highlight the performance of the proposed model and resolution framework. [ABSTRACT FROM AUTHOR]

In order to promote the evaluation performance of deep learning infrared automatic target recognition (ATR) algorithms in the complex environment of air-to-air missile research, we proposed an analytic hierarchy process (AHP) evaluation system consisting of the target recognition ability, the generalization recognition ability, the anti-interference ability, the background suppression ability, and the cost metrics ability. According to detailed quantitative analysis and experimental results, we establish probability evaluation models and get their probability values. Compared with traditional evaluation systems, our proposed method implementation is showing high reliability. Similar superior performances are also achieved, such as quick, comprehensive, and scientific. Through the above research, the key technology of deep learning performance evaluation in automatic target recognition has been broken through, which provides some basis and guidance for the analysis of infrared imaging-guided weapon systems. [ABSTRACT FROM AUTHOR]

The objective of this paper is to propose a novel dual-level multisource information fusion approach for handling open multicriteria decision-making (MCDM) issues related to accurately determining the weights of criteria while considering the relative importance of expert opinions, handling heterogeneous information, and selecting an appropriate MCDM ranking method. The proposed approach includes two levels. The first integrates the "analytic hierarchy process (AHP)—full consistency method (FUCOM)", which comprises two phases. In the first phase, criteria weights are assigned using AHP, and FUCOM is employed to correct inconsistencies. In the second phase, the weights are computed for decision-makers. Triangular fuzzy numbers are employed due to their ability to encapsulate all the utilized heterogeneous data types. At the second level of the approach, three well-known distance-based methods, including "technique for order preference by similarity to ideal solution", "visekriterijumska optimizacija i kompromisno resenje", and "multiattributive border approximation area comparison", are fused to process a homogeneous decision matrix and provide comprehensive and robust rankings for alternatives. To develop our novel approach, a renewable energy source for Pakistan's electricity generation is adopted as a case study. The decision matrix contains four alternatives (i.e., hydropower, biomass energy, solar energy, and wind energy) and six main evaluation criteria (i.e., economic, quality of energy, social, political, environmental, and technical), with several subevaluation criteria under each criterion. The findings of the proposed approach were as follows: A2 was in the first rank with a score of 1.7889, and A4 was in the last rank with a score of 0.1199. The rest of the alternatives were distributed between them. The paper's implications include the advancement of decision-making methods, enhancement of decision-making outcomes, and addressing heterogeneous information to highlight the relative importance of experts. [ABSTRACT FROM AUTHOR]

Flooding is one of the most common natural dangers occurring almost everywhere. Remote sensing and geographic information systems (GIS) are common and effective tools for hydrological analysis assessment and hazard management. Using GIS and remote sensing techniques, this study aimed to identify flood hazard maps in the Diyala governorate with a higher vulnerability to floods. Nine influencing parameters were collected, including elevation, slope, distance from the road, distance from the river, rainfall, drainage density, land use and land cover, normalized vegetation index, and topographic wetness index. The collected data were processed using GIS software and then relative weights were estimated using the analytical hierarchy process (AHP) approach to produce a flood map. According to the findings of this study, the largest zone, about 64% of the study area, faces moderate potential flood hazard, a very small area of less than 1% faces very high and very low potential flood dangers, and approximately 35% of the study area is subjected to high and low flood hazard. [ABSTRACT FROM AUTHOR]

The increasing pressure on resources and the persistent failure to address global malnutrition are evident challenges. A significant contributing factor is the decline in the quality of production resources, particularly water. As a result, many countries and their experts have prioritized the need to balance resource consumption. To address the research gap regarding balanced and optimal resource use, various methodologies have been developed over time, culminating in nexus studies. This study aimed to investigate the what, why, and how of conducting water-energy-food nexus (WEFN) studies. The research employed a sequential mixed-methods approach, integrating content analysis with the Analytical Network Process (ANP). The findings reveal that the objectives of WEFN studies encompass a wide range of interests, which can be systematically categorized into seven principal domains: system sustainability assessment, integration of planning and decision-making processes related to resource consumption, optimization of resource use, management of resource consumption systems, development of theoretical frameworks for the nexus, evaluation of the impacts of resource consumption, and assessment of associated risks. Notably, the results indicate that system sustainability assessment is the most critical reason for conducting WEFN studies. Furthermore, the analysis of WEFN methodologies identified simulation as the most effective technique within the Analytical Hierarchy Process (AHP) framework. In the context of the ANP technique, statistical analysis and simulation emerged as the most important methods. This research advocates for using a diagram to facilitate the selection of the optimal method for conducting a WEFN study. [ABSTRACT FROM AUTHOR]

As an important military defense project in Chinese history, the Ming Dynasty Great Wall and its associated military settlements played a crucial role in maintaining border security. A systematic analysis of how military settlements allocated resources based on external threats and geo-strategic needs is essential to understanding their settlements defense systems. However, this aspect has been relatively under-explored in existing research. Therefore, a resource allocation assessment model for Great Wall military settlements during the Cold Weapon era is established to facilitate a more scientific analysis and quantitative assessment of Military Defense Capabilities(MDC) and Military Requirements(MR). This study employs a combined Analytical Hierarchy Process (AHP) and Principal Component Analysis (PCA) approach to determine the weight of each indicator for both military defense capability and military requirement. Spatial clustering using K-means is conducted to visualize the distribution of these strengths and weaknesses. An Ordinary Least Squares (OLS) regression model links military requirements with defense capabilities, assessing the relationship between settlement locations and historical battle sites. Residual analysis is utilized to identify areas of resource over-allocation or under-allocation. The study reveals that the regional differences in military defense capabilities and requirements within the Zhenbao Town area during the Ming Dynasty correspond closely with the locations of frequent conflicts. This finding suggests that the distribution of defensive capabilities were strengthened in areas with challenging terrain, while the effectiveness and allocation of defense capabilities were determined by logistical support and transportation conditions. This study enhances our understanding of historical military strategies from a historical geography perspective and offers innovative insights for analyzing Great Wall settlement, moving beyond mere sensory intuition and historical experience. [ABSTRACT FROM AUTHOR]

Introduction: Environmental therapy theory has been applied in the research of disease prevention, and the effectiveness of using color and graphic designs to assist patients with spatial orientation has been confirmed. Visual-spatial impairments are common symptoms associated with cognitive decline. However, the interaction and driving factors between these impairments and spatial color and graphic designs remain unclear. Methods: This paper first discusses the correlation between the characteristics of visual-spatial impairments and environmental factors and then investigates the color preferences of such patients based on the CIE 1976 color system and the Analytic Hierarchy Process (AHP). Subsequently, the paper explores spatial design strategies conducive to spatial orientation from the perspective of adaptability to pathological characteristics, utilizing case study analysis. Results: (1) Pathological characteristics of visual-spatial impairments (such as difficulties in spatial orientation and spatial neglect) are related to environmental factors; (2) Emotional attachment factors play a key role in patients' perception of satisfaction with environmental colors; (3) Color associations have the potential to strengthen spatial memory. Additionally, interface designs with high luminance, low saturation, and clear color differentiation facilitate patients' recognition of space. Discussion: This paper posits that spatial interface design is a feasible approach to assist with spatial orientation, and it achieves this through a mediating process that progresses from influencing visual stimuli to cognitive memory and then to behavioral orientation. The article provides insights into the operational feasibility of this method. [ABSTRACT FROM AUTHOR]

The increasing emphasis on fostering agri-entrepreneurship in emerging economies is based on the understanding that it holds the potential to drive economic growth and sustainable development. Its impact transcends mere financial indicators, influencing facets such as innovation, job creation, and societal empowerment. This perspective is also relevant in the Indian context, where organizations promoting agri-entrepreneurship often encounter challenges. This study was carried out to identify the constraints faced by various stakeholders involved in providing and accessing entrepreneurial support, also strategizing solutions for the identified bottlenecks. Data was gathered through structured interviews involving about 200 agri-entrepreneurs and 43 extension professionals in selected states. Constraints as well as strategies in the promotion of agri-entrepreneurship were systematically categorized into four dimensions viz. administrative, financial, technical, and socio-cultural which were further ranked through Garett's ranking method and Analytical Hierarchy Process. Financial and administrative constraints, including lack of priority lending, favoritism, and delays in fund release, emerged as significant hurdles for sustainable entrepreneurship development, other constraints among technical and socio-cultural domains include lack of prototype testing facility and orientation toward conventional ventures, respectively. Experts suggested strategies like post program funding support, timely disbursement of seed funding and transparency in pitch evaluation for mitigating the challenges. The overall consistency ratio of AHP matrix indicates a high level of agreement in suggestions among experts. Incorporating the suggestions through policy changes is expected to promote a sustainable food value chain thereby promoting sustainable agri-entrepreneurship. [ABSTRACT FROM AUTHOR]

Ground handling companies (GHCs) have the highest potential for occupational accidents in the air transportation sector. Understanding the success factors of occupational health and safety management systems (OHSMSs) implemented by GHCs ensures effective and efficient use of resources. Knowing the relative importance of success factors will enable companies to focus their energies on the most important factors. The analytic hierarchy process was used to determine the relative importance of success factors. The data of the study were obtained through a questionnaire survey of participants working as occupational safety and health (OSH) managers in GHCs operating in Turkey. According to the results of the study, the most critical success factor is ‘top management support’, followed by ‘positive safety culture’. The differentiating result of the research from the literature is that ‘OSH professionals’ ranks third as an important success factor. Other success factors include ‘OHSMS practices’, ‘stakeholder attitudes and characteristics’ and ‘regulations’. [ABSTRACT FROM AUTHOR]

Innovation is key to gaining a sustainable edge in an increasingly competitive global manufacturing landscape. For Bangladesh's manufacturing sector to survive and thrive in today's cutthroat business environment, adopting transformative technologies such as the Internet of Things (IoT) is not a luxury but a necessity. This article tackles the formidable task of identifying and comprehensively evaluating the impediments to IoT adoption in the Bangladeshi manufacturing industry. We delve deeply into the complex terrain of IoT adoption challenges by synthesizing expert insights and a meticulously selected body of contemporary literature. We employ a robust methodology combining the Delphi method with the fuzzy Analytical Hierarchy Process to systematically analyze and prioritize these challenges. Using this methodology, we leveraged the combined expertise of domain specialists and subsequently employed fuzzy logic techniques to address the inherent ambiguities and uncertainties within the data. Our findings highlight this clear path. They reveal that among the myriad barriers, "Lack of top management commitment to implementing new technology" (B10), "High initial implementation investment costs" (B9), and "Risks associated with switching to a new business model" (B7) loom most extensive, demanding immediate attention. These insights are not confined to academia but serve as a pragmatic guide for industrial managers. Armed with the knowledge gleaned from this study, managers can craft tailored strategies, set well-informed priorities, and embark on a transformational journey toward harnessing the vast potential of IoT in the Bangladeshi industrial sector. This article provides a comprehensive understanding of IoT adoption challenges and industry leaders with the tools necessary to navigate these challenges effectively. This strategic navigation, in turn, contributes significantly to enhancing the competitiveness and sustainability of Bangladeshi manufacturing in the IoT era. [ABSTRACT FROM AUTHOR]

Introduction: As a means of environmental regulation, the low-carbon city pilot policy aims to address climate change and alleviate environmental resource pressures in economic development. The development of low-carbon cities often requires changes to the existing industrial and energy structures, which will have a significant impact on the regional economy. Methods: The study is based on panel data from 273 prefecture level cities in China from 2012 to 2022, and uses the Analytic Hierarchy Process and Entropy Comprehensive Evaluation Method to construct an evaluation index system for urban circular benefits. Finally, the multiple time point differences model and mediation effect model were used to evaluate the impact and influencing factors of policies on urban economy. Results: The results indicate that at the 1% level, the explanatory variable coefficient significantly improves the level of urban circular economy development after adding control variables. The construction of low-carbon pilot cities has improved the performance of circular economy development by about 6.42%. The mediating effect of industrial structure rationalization is significantly positive at the 1% significance level, indicating that the construction of low-carbon pilot cities has greatly promoted the coordinated development of industrial relations within China's low-carbon development regions. Discussion: It can be seen that the low-carbon city pilot policy has a significant promoting effect on China's economic development and the development of urban circular economy. Therefore, it is recommended to further expand the pilot scope of low-carbon cities and fully leverage their promoting role. This article is based on panel data from 273 prefecture level cities from 2012 to 2012, and uses a multi time difference model to analyze the impact of low-carbon city pilot policies on the development of urban circular economy. The research results indicate that the construction of low-carbon pilot cities has significantly promoted the coordinated development of intra regional industrial relationships. [ABSTRACT FROM AUTHOR]

Jordan is currently facing an energy crisis characterized by a heavy dependence on imported fossil fuels, prompting the nation to target a 50% share of renewable energy by 2030. This study introduces a novel approach by simulating hybrid solar-geothermal heat pump systems tailored to various Jordanian locations, assessing both their energy efficiency and economic feasibility. Unlike previous studies that focused solely on geothermal or solar technologies, this research uniquely combines these two renewable sources, offering a comprehensive evaluation across multiple climates. Key findings include the superior performance factors of vertical (4.0) and horizontal geothermal heat pumps (4.2) in Amman, compared to the air-to-water heat pump (3.5). Additionally, Aqaba station demonstrated an exceptional solar contribution, meeting 99.34% of heating demand, while Amman achieved 77.93%. Notably, Maan station provided the highest solar contribution for space heating at 6,902 kWh/year, and Amman airport station led in CO2 emission avoidance at 2,120.29 kg/year. The economic analysis revealed that while vertical heat pump systems were economically unviable with a negative NPV of -4,987.51 JD, horizontal and air-to-water systems showed promising NPVs of 5,734.27 JD and 8,428.46 JD, respectively, with payback periods of 9.44 and 6.5 years. Additionally, this study is the first to employ both the fuzzy Best–Worst Method (BWM) and Analytic Hierarchy Process (AHP) techniques to rank station suitability, identifying Maan station as the most optimal and Ghor El-Safi as the least. The results underscore the potential of hybrid solar-geothermal systems to significantly reduce energy consumption and CO2 emissions, despite initial financial barriers, and highlight the importance of further investment in geothermal technologies to enhance Jordan's energy security and reduce fossil fuel dependency. [ABSTRACT FROM AUTHOR]

In the food manufacturing industry, which is critical to national economies, there is a growing imperative to meet heightened safety, quality, and environmental standards, particularly in the face of supply chain disruptions. This study addresses the gap in literature by integrating sustainable and resilient supply chain theories with risk management and low-carbon principles into a supplier selection framework. Utilizing the Delphi method, fuzzy analytic hierarchy process (FAHP), and fuzzy multi-objective programming (FMOP), we develop a decision-making model specifically calibrated for the food sector. Initially, the study establishes a comprehensive criteria system encompassing quality, cost, delivery, low-carbon, and risk management through a literature review and expert consultation. Subsequently, FAHP is employed to determine the relative importance of each criterion in supplier selection. Furthermore, FMOP is utilized to develop a decision-making model for optimizing supplier selection and order allocation. Validated through a numerical study based on a Chinese food manufacturer, the framework presents a practical tool for food manufacturers, ensuring supply chain stability while aligning with sustainability objectives. This research refines decision making and strengthens the competitive stance of food manufacturers, significantly propelling the industry's green transformation. [ABSTRACT FROM AUTHOR]

Currently, the need for a clean transition has made the upscaling of sustainable energy investment projects imperative. This paper addresses the increasing importance of sustainable energy investment projects in the context of climate change and the urgent need for a global energy transition. Given the complexity of decision-making in this field, a multi-criteria decision-making (MCDM) approach is employed to assess the main criteria considered by project developers and financial institutions. Using the Analytic Hierarchy Process (AHP) method, eight criteria are identified and evaluated. Results highlight differing priorities between project developers and investors, emphasizing the need for adaptable approaches to accelerate sustainable energy investments. The study underscores the importance of understanding diverse stakeholder preferences and priorities in formulating effective strategies and managing associated risks to effectively promote sustainable energy projects. Future research should focus on real-life case studies and policy assessments to further enhance the understanding of sustainable energy investment dynamics. [ABSTRACT FROM AUTHOR]

With the development of modernization, traditional fossil energy reserves are decreasing, and the power industry, as one of the main energy consumption forces, has begun to pay attention to increasing the proportion of clean energy generation. With the deepening of electrification, the peak-valley difference of residential electricity consumption increases, but photovoltaic and wind power generation have fluctuations and are manifested as reverse peak regulation. Thermal power plants as the main force of peak regulation gradually reduce the market share, making nuclear power plants bear the heavy responsibility of participating in peak regulation. The traditional method of adjusting operating power by inserting and removing control rods has great safety risks and wastes resources. Therefore, this paper proposes a new energy storage system that can keep the nuclear power plant running at full power and produce hydrogen to synthesize ammonia from excess power. A comprehensive evaluation model of energy storage based on z-score data standardization and objective parameter assignment AHP (analytic hierarchy process) analysis method was established to evaluate energy storage systems according to a multi-index system. With an AP1000 daily load tracking curve as the input model, the simulation model built by Aspen Plus V14 was used to calculate the operating conditions of the system. In order to provide a construction basis for practical engineering use, Haiyang Nuclear Power Plant in Shandong Province is taken as an example. The system layout scheme is proposed according to the local environmental conditions. The accident tree analysis method is combined with ALOHA 5.4.1.2 (Areal Locations of Hazardous Atmospheres) hazardous chemical analysis software and MARPLOT 5.1.1 geographic information technology. A qualitative and quantitative assessment of risk factors and the consequences of leakage, fire, and explosion accidents caused by hydrogen and ammonia storage processes is carried out to provide guidance for accident prevention and emergency rescue. The design of an "Electric-Hydrogen-Ammonia" energy storage system proposed in this paper provides a new idea for zero-carbon energy storage for the peak shaving of nuclear power plants and has a certain role in promoting the development of clean energy. [ABSTRACT FROM AUTHOR]

The large-scale storage and stable supply of oil products are essential for national energy security and economic development. As the economy expands and energy demands rise, centralized storage and supply systems become increasingly vital for ensuring the efficiency and reliability of oil product distribution. However, large oil storage depots present substantial safety risks. In the event of fires, explosions, or other accidents, emergency response efforts face stringent demands and challenges. To enhance the emergency response capabilities of oil storage and transportation bases (OSTBs), this paper proposes an innovative approach that integrates the improved analytic hierarchy process (IAHP) with the Entropy Weight Method (EMW) to determine the combined weights of various indices. This approach reduces the subjective bias associated with the traditional analytic hierarchy process (AHP). The emergency response capabilities of OSTBs are subsequently evaluated through fuzzy comprehensive analysis. An empirical study conducted on an OSTB in the Zhoushan archipelago quantitatively assesses its emergency preparedness. The results show that the base excels in pre-incident prevention, demonstrates robust preparedness and response capabilities, and exhibits moderate recovery abilities after incidents. These findings provide a theoretical foundation for reducing the likelihood of accidents, enhancing emergency response efficiency, and mitigating the severity of consequences. Practical recommendations are also offered based on the results. [ABSTRACT FROM AUTHOR]

In the process of CO2 geological storage in the salt water layer, CO2 leakage along the wellbore will seriously affect the effective storage of CO2 in the target geological area. To solve this problem, based on the investigation of a large number of failure cases of CO2 storage along the wellbore and failure cases of gas storage wells in the injection stage of the wellbore, the influencing factors of CO2 leakage risk along the wellbore were investigated in detail. Based on the analytic hierarchy process (AHP) and extension theory, 17 basic evaluation indexes were selected from 6 perspectives to establish the evaluation index system of CO2 leakage risk along the wellbore. The established evaluation system was used to evaluate the leakage risk of a CO2 storage well in the X gas field of BZ Block. The results showed that the influencing factors of tubing had the smallest weight, followed by cement sheath, and the influencing factors of casing–cement sheath interface and cement sheath–formation interface had the largest weight, accounting for 23.73% and 34.32%, respectively. The CO2 storage well leakage risk evaluation grade was Ι, with minimal leakage risk. The CO2 storage effect was excellent. The evaluation system comprehensively considers the tubing string, cement sheath, and micro-annulus interface, which can provide a scientific basis for the risk assessment of CO2 leakage along the wellbore under the CO2 geological storage of the salt water layer. [ABSTRACT FROM AUTHOR]

In the circular economy era, this study addresses sustainable business management for high-investment and long-life cycle projects, where accurate and reliable assessments are crucial to ensuring successful outcomes. The objective is to elevate the reliability of assessments by introducing a novel decision-making method that, for the first time, integrates time-based satisfaction and risk factors simultaneously. We propose a 3-phase multi-criteria decision-making (MCDM) method, which combines fuzzy MCDM comprising fuzzy analytic hierarchy process and fuzzy technique for order preference by similarity to ideal situation (TOPSIS), Kano model, and failure mode and effects analysis (FMEA) techniques, to handle reliable assessments effectively. Our method is distinct in its incorporation of time-based satisfaction weights derived from Kano model, emphasising decision-makers' criteria preferences in short, medium, and long terms. Furthermore, we introduce risk-discounted weights by using FMEA to tune criteria scores. The method is validated via a numerical example case, assessing and selecting the most appropriate hydrogen storage method for lightweight vehicles. The results suggest that cryo-compressed hydrogen tank with 250–350 bar and at cryogenic temperature is the most suitable storage method. Health & safety with a weight of 0.5318 emerges as the most important main criterion, and permeation & leakage with a weight of 0.4008 is the most important sub-criterion. To bridge the gap between theoretical research and practical application, we transform the new method into a user-friendly web application with graphical user interface (GUI). End-users can conduct reliable assessments and foster sustainable business management through informed decision-making. [ABSTRACT FROM AUTHOR]

As a responsible business philosophy, sustainable management is becoming a widely accepted management mode among managers, practitioners, stakeholders, and customers. The sustainable development of business management calls for the practice of the environmental, social, and governance (ESG) principle. Companies that neglect ESG criteria in their business operations may face unexpected consequences. Therefore, the ESG sustainable performance of the company is becoming a benchmark to evaluate environmental and social responsibility of companies worldwide. This paper proposes an integrated MCDM framework combining the interval type-2 fuzzy analytic hierarchy process (IT2FAHP) and the interval type-2 fuzzy combined compromise solution (IT2F-CoCoSo) method for evaluating the ESG sustainable performance of listed companies. In the integrated MCDM framework, the interval type-2 fuzzy sets serve as an effective tool to transform qualitative linguistic evaluation into quantitative expression, the criteria weights are obtained using the IT2FAHP, and the rankings of alternatives are determined by the IT2F-CoCoSo method. The proposed method is applied in a case study on the ESG sustainable performance evaluation of five medical listed companies, which are evaluated based on three aspects: E, S, and G and further divided into 14 criteria. Results reveal that the most important criterion in the E, S, and G aspects are pollution treatment, health and safety, and risk management. It suggests that the Pfizer biopharmaceutical company has the best ESG sustainable performance among the five alternative medical listed companies. We perform a sensitivity analysis with random criteria weights and different parameter values to show the stability of the proposed approach. A comparison is also performed between our approach and some existing methods for validating the proposed approach. This analysis shows that the proposed approach is efficient and well-consistent with the other methods. [ABSTRACT FROM AUTHOR]

This study introduces an innovative algorithm that leverages terrestrial laser scanning (TLS) and the fuzzy analytic hierarchy process (FAHP) for the optimization of building repair methodologies. Focusing on multi-criteria decision-making (MCDM), itshowcases a methodology for evaluating and selecting the most effective repair strategy for building elements, balancing various conflicting criteria. The research applies TLS for rapid and accurate geometric data acquisition of engineering structures, demonstrating its utility in structural diagnostics and technical condition assessment. A case study on a single-family residential building, experiencing floor deformation in a principal ground-floor room, illustrates the practical application. Maximum deflection and floor deflection distribution were measured using TLS. Utilizing FAHP for analysis, the decision model identifies the most advantageous repair method from a building user’s perspective. This approach not only provides a systematic framework for selecting optimal repair solutions but also highlights the potential of integrating advanced scanning technologies and decision-support methods in the field of building materials and structural engineering. [ABSTRACT FROM AUTHOR]

The complex geological conditions and operational performance of reconditioning modified earth pressure balance shield (M-EPBS) machines can critically influence tunnel excavation and construction safety. To address this, the study proposes a comprehensive framework for assessing the overall construction performance of reconditioned shield machines in compound strata. This framework employs fuzzy mathematics theory and analytic hierarchy process (F-AHP) to construct a three-level multi-factor evaluation matrix and establish comprehensive membership function relationships. We then quantify the weight of each factor and the interval membership function, followed by a relative superiority analysis of the interval matrix. A shield tunneling case study is utilized to evaluate the model, focusing on layer conditions, shield design parameters, and shield construction parameters. The study also addresses the challenges encountered during the tunneling process and the corresponding countermeasures. The results reveal that the proposed framework is effective, user-friendly, and adaptable for selecting and evaluating M-EPBS machines in compound strata. This framework provides a novel approach for feasibility assessments, safe operation management, pre-shield design evaluations, and post-shield construction verifications. [ABSTRACT FROM AUTHOR]

Climate change is creating massive worldwide risks to people's lives and livelihoods. Developing comprehensive and reliable techniques to estimate climate risk is crucial for climate mitigation and adaptation process. By employing multi-criteria decision-making (MCDM) techniques using principal component analysis (PCA) and the analytical hierarchy process (AHP), this study assessed climate change risks in Raichur Taluk, Karnataka, India. The study developed a novel PCA drought index (PCADI) using ArcGIS incorporating eight drought risk indicators. Ten flood risk parameters were employed using the AHP technique and the flood risk map was created for the Taluk by overlaying the selected weighted thematic layers. As a result, several villages within the Taluk are prone to flooding. Extreme climatic events evaluated by the reconnaissance drought index, standardised precipitation index, and streamflow drought index indicated 20 years of unique drought episodes with differing severity and flood risk over seven different periods. Our study further demonstrated that the annual average count of rainy days when RR ≥ 10 mm and RR ≥ 20 mm was recorded to be 18.33 and 6.49, respectively, showing a declining trend that may worsen the water situation. Results also show shifts in temperature extremes, with decreasing cold days (TX10p) and nights (TN10p) and increasing hot days (TX90p) and nights (TN90p). The validation results indicate strong and significant correlations between meteorological and remote sensing drought indicators; SPI_12 with NDVI and VCI (r = 0.908, p < 0.05; r = 0.983, p < 0.01), VCI with SP1_6 (r = 0.988, p < 0.01), and VCI with RDI (r = 0.988, p < 0.01). The result from the present study along with socioeconomic information of the Raichur Taluk can be used to develop better policies underlying better climate resilient strategies for the Taluk in the future. [ABSTRACT FROM AUTHOR]

The Bagmati River Basin is experiencing significant water stress due to a reduction of surface and groundwater resources, especially during the dry season. The basin's heavy reliance on monsoon-dominated precipitation, without the buffer of snow or glacier melt, exacerbates these issues. Dam construction is seen as a viable solution for maintaining river flow and regulating river ecosystems. Thus, this study leveraged multi-criteria decision-making tools, particularly the analytical hierarchy process (AHP) and fuzzy AHP (FAHP) in conjunction with the Geographic Information System(GIS), to identify suitable dam construction sites in the Bagmati River Basin. Through an extensive literature review, nine criteria were identified: stream density, rainfall, slope, land use, elevation, soil type, distance from faults, distance from settlements, and distance from roads. Pairwise comparison matrices, based on expert surveys, were used to assign weights to each criterion, with validation against existing and proposed dams. Results show that approximately 31% of the basin area is suitable for dam construction, with about 4.45% area being highly suitable. FAHP only slightly outperforms AHP in assessing existing dam locations, demonstrating the robustness of both methodologies. For the validation of suitability analysis, location of existing dams are compared. While Nepal is not generally water-stressed, inter-seasonal water availability is high. Dam construction for multiple uses is nascent in Nepal, and location analysis studies are rare. The methodology used here can be replicated in other regions, offering valuable insights for decision-makers. [ABSTRACT FROM AUTHOR]

Aims: The aim of the study was to develop a set of nursing‐sensitive quality indicators for acute poisoning in emergency departments. Design: A two‐round e‐Delphi study was conducted from July to November 2023. Methods: Subject‐matter experts from 19 tertiary hospitals across four provinces of China participated in the survey. Potential indicators identified through a literature review were rated on a 5‐point Likert scale and comments solicited. Descriptive statistics were used to demonstrate convergence of expert opinion, and consensus was reached in two rounds. Weights of each indicator were determined by analytic hierarchy process. There were 20 expert responses in Round 1 and 18 in Round 2. Results: After two rounds, experts reached a consensus on definitions, calculation formulas, and data collection methods for these indicators. Three primary and 11 secondary indicators were included in the final nursing‐sensitive quality indicators for acute poisoning in the emergency department. Conclusion: A set of indicators about acute poisoning care, applicable to the Chinese context, was developed in collaboration with emergency nurse specialists. Implications for the Profession and Patient Care: The lack of supervision of the nursing quality for acute poisoning leads to great variability in clinical practice in different medical institutions. The results can help in their standardization in China and in other countries lacking regulation. Our study also offers nursing managers a concrete and operable evaluation tool for quality supervision. Normative nursing behaviours are conducive to increase safety and enhance patients' experience of medical treatment. Impact: The indicators identified in this study closely approach clinical practice and exhibit the characteristics of sensitivity and practicality. Although developed in the Chinese healthcare system, there is potential for adoption or adaption in other healthcare settings. Reporting Method: This study was reported in line with the Conducting and REporting of DElphi studies (CREDE) guidance on Delphi studies. Patient or Public Contribution: No patient or public contribution in this study. Contribution to the Wider Global Clinical Community: The nursing quality of acute poisoning in emergency departments remains a growing attention, but the relevant assessment tools are lack. This study provides a set of nursing‐sensitive quality indicators for acute poisoning to guide the quality monitoring of nursing managers. Study recommendations have broad applicability to all healthcare professionals who are engaged in emergency nursing. [ABSTRACT FROM AUTHOR]

Intermodal transport not only changes the traditional mode of cargo transport, hut also builds an efficient and intelligent logistics system. At present, there is a problem of low efficiency of intermodal transport in China, and the development of intermodal transport lacks a clear direction. In order to further strengthen the objective understanding and quantitative evaluation of the development level of intermodal transport in China, and to comprehensively consider factors such as data availability and data quality, in order to improve the efficiency of intermodal transport, the connotation requirements of intermodal transport were analyzed in depth firstly. Then, an intermodal transport development index system composed of 11 specific indicators in four aspects was established in this paper, including service capacity, service quality, organizational efficiency and comprehensive benefits. After data normalization, the intermodal transport development index was constructed by combining Analytic Hierarchy Process and Entropy Weight Method. Then, the first batch of national intermodal transport demonstration projects were taken as an example, and the intermodal transport key enterprise filling system was used to collect and process data. At last, the intermodal transport development index of each project was calculated and suggestions were made accordingly. The intermodal transport development index shows that the national intermodal transport demonstration projects in the southeast coastal areas of China have good results, and the construction of the national intermodal transport demonstration projects in inland areas still needs to be further strengthened. In summary, the development level of the national intermodal transport demonstration projects could be truly and effectively reflected by the intermodal transport development index, which has a good guiding effect on promoting the development of intermodal transport in China. [ABSTRACT FROM AUTHOR]

Wetlands are important ecosystems, and few of them, owing to unique characteristics, have been designated the status of Ramsar sites under the convention of wetlands. Despite the status, few of these wetlands are under threat owing to their social importance. Renuka wetland is one such important Ramsar site in India, which is culturally an embodiment of the Goddess Renuka ji. An international fair is held every year at the lake which attracts thousands of pilgrims and tourists. This event is one of the major contributors to anthropogenic risk; other pressures are siltation, pollution, land use activities, and invasive species. Under such a scenario, it becomes important to assess the health of wetlands to take timely decisions about their management. This study evaluates the health of Renuka wetland, using the Pressure State and Response (PSR) model. Relevant data related to the wetland and its catchment from a wide spectrum of sources, namely, field, laboratory, and remote sensing were combined to assess the health of the wetland. Ten indicators were identified, and Analytic Hierarchy Process (AHP) was used to assign weights to the indicators. The wetland health index of Renuka wetland is 0.35, indicating that the lake is in poor condition exhibiting degraded functioning, high external pressure, low vigor, poor resilience, and stability. The study also revealed that the water quality deteriorates post-fair. Thus, the wetland needs attention in terms of management so that the health of the lake improves and is sustained in the future. The study contributes to Sustainable Development Goal 6.6 which focuses on protecting and restoring water-related ecosystems and aims at healthier ecosystems. [ABSTRACT FROM AUTHOR]

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Prioritising sustainable development goals (SDGs) is one of the fundamental approaches to achieving global sustainability objectives, as it helps efficient resource allocation, addresses urgent needs, enhances policy coherence, and measures impact. Despite existing efforts, there remains an unclear understanding of the key factors needed for effective SDG prioritisation, presenting challenges for strategic planning and decision-making. This study provides an evidence-based analysis of these critical factors by examining relevant literature, conducting surveys, and employing Analytical Hierarchy Process (AHP)-based Multi-Criteria Decision Analysis (MCDA). The study identifies four primary factors for SDG prioritisation: SDG interrelations, performance, scope, and alignment. The findings confirm that national prioritisation have more priority compared to global, regional, and sub-national systems, and that prioritisation is more valuable at the indicator level rather than at the goal or target levels. Additionally, prioritisation should initially focus on off-track SDGs. Notably, academia ranks SDG prioritisation based on relationships and performance highly, while government officials emphasise alignment and relevance. Moreover, the results indicate that academia prefers target-level prioritisation, while government officials lean towards indicator level. However, both groups favour national scale over global and regional scales. [ABSTRACT FROM AUTHOR]

To apply the analytic hierarchy process (AHP) to solve forest management problems, it is necessary to determine when the use of this method is appropriate and when another method would be more appropriate due to the limitations of the method itself. In this study, strengths, weaknesses, opportunities, and threats (SWOT) and meta-SWOT analyses were conducted to assess the applicability of the AHP method to sustainable forest management problems. Sixteen experts from 11 different European countries participated in the research. First, they evaluated the AHP method from the SWOT perspective and weighted the SWOT factors and groups using the AHP method. The results showed that the AHP method is more suitable for application in sustainable forest management than other multicriteria decision-making (MCDM) methods with respect to two competitive dimensions: design and calculation. However, the application of the AHP in sustainable forest management also has some weaknesses and threats that should be considered. Involving stakeholders with expertise and skills in model development and pairwise comparisons is the most important issue in this area; otherwise, incorrect results could be obtained for forest management decisions. Problem-solving conditions such as uncertainty, the interactions among criteria and the economic constraints of the problem may also lead to the use of other methods instead of the AHP in sustainable forest management. The results of this study contribute to global studies on decision-making in natural resource and environmental management, especially decisions related to forest management. [ABSTRACT FROM AUTHOR]

In order to minimize human impact on the environment, it is crucial to determine the best way to utilize land through assessments of its suitability. This research focuses on the Anantnag district in the Kashmir valley, exploring its potential as a suitable area for mulberry agroforestry. Consequently, the selection of suitable sites for mulberry-based agroforestry has become an essential element of sustainable land use planning and agriculture, with the aim of maintaining ecological equilibrium. In the context of a Geographic Information System (GIS), we employ a method called multi-criteria assessment to evaluate the suitability of a specific site for mulberry agroforestry in the study area. This assessment involves considering various factors such as slope, temperature, rainfall, land use and land cover (LULC), as well as the physical and chemical properties of the soil. To assign scores to these criteria, we utilized the analytic hierarchy process (AHP) technique, conducted interviews with local experts, and referred to existing literature. By applying a weighted overlay analysis, which takes into account the importance of each parameter, we generated a map depicting the suitability of the research area for mulberry agroforestry. The map for mulberry agroforestry suitability in the study area indicates that 16.59% of the land is highly suitable, 28.16% is moderately suitable, 40.29% is marginally suitable, and 14.96% is unsuitable. To ensure the accuracy of the findings, satellite images, Sentinel-2b LULC mapping, and GPS-enabled field surveys were extensively employed to verify the results. These findings can be utilized by farmers, regional developers, and the government to inform their decisions regarding potential mulberry agroforestry areas and develop sustainable agroforestry management strategies for the region. [ABSTRACT FROM AUTHOR]

This work aims to explore the potential of available renewable energy resources such as solar, wind, biomass and ocean energy and select the best suitable renewable energy resource considering technical, economic, environmental, and social constraints as the main criteria. Five sub-criteria are considered for each main criterion, and these twenty sub-criteria are considered for ranking renewable energy resources using Analytical Hierarchy Process (AHP). The investment cost of the system having the relative weight of 57.94%. Hence it is recommended to choose the renewable energy source having higher value over the economic aspect. The results also showed that the efficiency of the system is the first prioritized criteria among the technical sub criteria with a relative weight of 38.86%. Similarly, land requirement for the implementation of renewable energy system is the first prioritized criteria (43.38%) among the five environmental sub criteria.The overall results from the AHP showed that economic criteria are the more important aspect with a relative weight of 45.04% followed by Technical, environmental and social criteria with relative weights of 22.5%, 14.16% and 12.62% respectively.For Prioritization of renewable energy resources, the study region divided into nine smaller blocks for investigation using AHP and the hierarchical results showed that solar energy is of highest priority in block 2 whereas wind energy potential is higher in blocks 5 and 9. Due to the dense population and widespread agricultural plantations, Bioenergy has average priority over the entire study region. [ABSTRACT FROM AUTHOR]

Improving the accessibility to archaeological sites in a desert is a crucial issue; it enhances the landscape value and helps in achieving sustainable tourism development. El-Fayoum Oasis and Governorate in Egypt, has a unique heterogenic environment that encompasses desert, lakes, agriculture lands, and urban areas. It is quite rich in historical heritage reflected by abundant archaeological and cultural sites, many of which fall in desert zones. A main constraint is the poor or lack of accessibility to such sites. In this study, we designed a geospatial model for planning a sustainable least cost tourist route (path) to link and develop three archaeological sites namely; Madinet Madi, Watfa city and Ummal-Barijat ruins. Spatial multicriteria decision analysis was integrated with the analytical hierarchy process (AHP) and the least cost path modules. Three cost criteria themes were created associated with economic, social and environmental costs. A cost surface and a least-cost path were created for each criterion and for each theme. The themes were combined using weighted linear combination to create four least cost scenarios for the path. Five preference criteria were used to compare the four route scenarios. Results show that the environmental scenario scored first scoring 0.69 while the economy path scores second 0.42, the equal weights path scores third 0.40 and finally the social path comes to be the last having a preference score 0.36. The method is flexible because priority can be changed and adapted according to specifications and site variances. It can be helpful for decision makers and planners in planning routes based on visual maps and priority visions. [ABSTRACT FROM AUTHOR]

Dairy farm wastewater contains high BOD, COD, and TSS, thus harming the environment if discharged without proper treatment. However, it is rich in nutrients, primarily nitrogen and phosphorus, which are needed by microalgae to grow and synthesis useful and high-value organic compounds. Microalgae biomass can be generated from a cultivation system that is integrated with wastewater sources efficiently. Selecting a suitable location is thereby crucial for the sustainable development of microalgae cultivation. This study aimed to select suitable locations in Cangkringan District, Indonesia for microalgae cultivation sites using the analytical hierarchy process (AHP) method integrated with geographic information system (GIS) and weighted overlay analysis (WOA). AHP helped determine the relative weights of the relevant factors, including dairy farm wastewater, temperature, land use, land elevation, and land slope in the study area. These weights were subsequently applied in WOA to determine locations that were most suitable for microalgae cultivation sites. The results of WOA, presented in the form of a land suitability map, showed that 0.1% (0.04 km²) of the studied areas is highly suitable for the development of microalgae cultivation and that a significant portion, approximately 67.2% (29.75 km²), is not suitable. [ABSTRACT FROM AUTHOR]

It is important to understand the relationship between urbanization and geological disaster systems to develop sustainable management strategies for many cities in the world that are located in geologically active zones. This study explored the coupling coordination degree of urbanization and geological disasters in 11 cities in Zhejiang province, China, during 2010–2020. Based on the annual demographics and socioeconomic and geological disasters data from 2010 to 2020, we analyzed the spatiotemporal changes of the coupling coordination degree between urbanization and geological disaster systems for the 11 cities in Zhejiang province during the period 2010–2020 using the analytic hierarchy process (AHP) combined entropy-weight method to determine the weights of indexes, which were used as input into the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method and coupling coordination degree model. The results indicated that the coupling coordination degree of most cities in Zhejiang province was positively correlated with time, reaching a peak in 2017, and the gap in coupling coordination was narrowing. From 2010 to 2020, the development stage of coupling coordination in Zhejiang province was mainly barely coordinated development. Moreover, the coupling coordination degree of North Zhejiang was the best, that of Central Zhejiang was second, and that of Southwest Zhejiang was the worst in terms of spatial pattern. [ABSTRACT FROM AUTHOR]

In the current study, the high-volume replacement of river sand (20%, 30%, 40%, 50%, 60%, 80%, and 100%) by pond ash in cement mortar was considered using a 1∶3 volumetric mix proportion to evaluate the engineering properties, sustainability aspects, and cost of mortar mixes. The compressive strength, tensile bond strength, and adhesive strength increased by 30%, 21%, and 24%, respectively, at 30% replacement and were in line up to 60% replacement as compared with the reference mix. However, the drying shrinkage was observed to increase with volume replacement of river sand. The life-cycle assessment of mixes containing pond ash showed reductions in the environmental impacts. Four different scenarios were considered on the basis of the preference advantage of the indicators. Considering the engineering properties, sustainability aspects, and cost as the primary indicators, the gray clustering analysis showed that the mix with 60% volume replacement exhibited the best performance among the mixes under Scenario S-1, while TOPSIS and VIKOR showed that the mix with 50% volume replacement exhibited best performance under Scenario S-1. Overall, the comparison of all scenarios showed that the mix of 60% pond ash had the best performance followed by the mix with 50% pond ash, irrespective of the multicriteria decision-making techniques and preference advantages. [ABSTRACT FROM AUTHOR]

Purpose: Cybersecurity has received growing attention from academic researchers and industry practitioners as a strategy to accelerate performance gains and social sustainability. Meanwhile, firms are usually prone to cyber-risks that emanate from their supply chain partners especially third-party logistics providers (3PLs). Thus, it is crucial to implement cyber-risks management in 3PLs to achieve social sustainability in supply chains. However, these 3PLs are faced with critical difficulties which tend to hamper the consistent growth of cybersecurity. This paper aims to analyze these critical difficulties. Design/methodology/approach: Data were sourced from 40 managers in Nigerian 3PLs with the aid of questionnaires. A novel quantitative methodology based on the synergetic combination of interval-valued neutrosophic analytic hierarchy process (IVN-AHP) and multi-objective optimization on the basis of a ratio analysis plus the full multiplicative form (MULTIMOORA) is applied. Sensitivity analysis and comparative analysis with other decision models were conducted. Findings: Barriers were identified from published literature, finalized using experts' inputs and classified under organizational, institutional and human (cultural values) dimensions. The results highlight the most critical dimension as human followed by organizational and institutional. Also, the results pinpointed indigenous beliefs (e.g. cyber-crime spiritualism), poor humane orientation, unavailable specific tools for managing cyber-risks and skilled workforce shortage as the most critical barriers that show the highest potential to elicit other barriers. Research limitations/implications: By illustrating the most significant barriers, this study will assist policy makers and industry practitioners in developing strategies in a coordinated and sequential manner to overcome these barriers and thus, achieve socially sustainable supply chains. Originality/value: This research pioneers the use of IVN-AHP-MULTIMOORA to analyze cyber-risks management barriers in 3PLs for supply chain social sustainability in a developing nation. [ABSTRACT FROM AUTHOR]

Water resource carrying capacity is a critical measure of the ability of water resources within a region to support social, ecological, and economic scales. This study establishes an evaluation index system for the water resource carrying capacity of Golmud City and calculates the weights of the indices using the Analytic Hierarchy Process (AHP). Based on an analysis of the current status of Golmud's socio-economic development, agriculture, and water resource utilization, a simulation model based on system dynamics is constructed. By setting 162 different scenario plans and normalizing the simulation results, the development trend of Golmud City's water resource carrying capacity is studied, and an evaluation is made for the sustainable development of water resources in Golmud City. Using data from 2001 to 2018 as the basic data, a carrying capacity analysis of water resources for the future from 2019 to 2030 is conducted. The study reveals that continuing the current development pattern will lead to unsustainable water resource carrying capacity. Among the scenarios aimed at coordinated development in all aspects, the best water resource carrying index is achieved, reaching 0.698 by 2030. By analyzing the development trend of the water resource carrying capacity index, existing problems in the utilization of water resources in Golmud City are identified, and feasible strategies for the sustainable use of water resources in Golmud City are proposed. [ABSTRACT FROM AUTHOR]

Extensive research has been conducted on the transition to environmentally friendly fuels in developed countries worldwide. However, there has been a significant lack of attention given to this crucial topic in developing countries. The study aims to bridge this gap by conducting a comprehensive analysis of the existing obstacles and prospects associated with transitioning to hydrogen fuel, with a specific focus on Vietnam. To achieve this objective, a rigorous SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis approach is employed, drawing upon an extensive literature review and the insights of selective experts in the field. Additionally, the Analytic Hierarchy Process (AHP) is utilized to effectively prioritize the identified factors from the SWOT analysis through eigenvalue calculation. As a result, the weaknesses are the highest first-class priority factors, with "Dedicated infrastructure for the transition to hydrogen fuel" and "Technological capacity for converting to hydrogen fuel" taking the next priorities in the second class. The outcomes of this research serve as a valuable resource for Vietnam and other developing countries, guiding policy-making and practical applications in the pursuit of transitioning to hydrogen fuel. Furthermore, this paper establishes a robust framework that can guide future studies in this specific area of research. [ABSTRACT FROM AUTHOR]

In this study, three options for coppice management in Iran were developed. These management options include Traditional Coppicing (TC), modification of TC, and extreme conservation to convert them into high forest. Analytic Hierarchy Process (AHP) was used for modeling to select the optimal solution for managing these forests. Six different scenarios were simulated in which the importance of the criteria in decision-making process changed. The results show that each of the three management options has its own importance, which depends on the conditions of the region and the different importance of the decision criteria. Therefore, the selection of the management scenario for future forest planning depends on prioritizing the criteria from the perspective of the managers and stakeholders and is dependent on social, economic and ecological conditions in each management unit. The results of this study show that it is not possible to rely solely on the results of the AHP method for forest management decisions, as AHP model does not include constraints. In this context, reverse engineering can be very helpful in the final conclusion of the decision. The results of this study can make a valuable contribution to the global literature and support decision-making, especially in scenarios where stakeholder participation may be limited and modeling stakeholder behavior is essential to the decision-making process. [ABSTRACT FROM AUTHOR]

Identifying near‐fault pulse‐like ground motions from extensive ground motion databases holds paramount importance, as it provides a pivotal foundation for further inquiries into this specific type of ground motions, including the modeling of such stochastic processes as well as thorough analysis of their potential impact on structures and infrastructure systems. Currently, a diverse array of quantitative methods for identifying pulse‐like ground motions have emerged, all of which demonstrate good accuracy within their respective research scopes. However, due to the limitations of each individual method in identifying specific cases, these diverse approaches often yield inconsistent results for certain ground motion records, posing a significant challenge in establishing a reliable classification criterion that relies solely on a single identification method. To address this issue, the present study adopts a multifaceted approach. Instead of improving a single time‐frequency analysis‐based identification method, it carefully conducts a selection of seven baseline methods through a systematic overview of the field. By leveraging the analytic hierarchy process (AHP), a comprehensive categorization method is developed that integrates the strengths of each approach, resulting in a more robust and credible classification criterion. According to the devised category indicator, ground motions can be classified into four categories: Category A comprises definitively pulse‐like ground motions; Category B comprises apparently pulse‐like ground motions; Category C consists of probably pulse‐like ground motions; and Category D encompasses ground motions unlikely to exhibit pulse‐like characteristics. It provides a more elaborate classification beyond the binary distinction of pulse‐like and non‐pulse‐like ground motions associated with traditional onefold classification methods. For validation purposes, a basic dataset comprising near‐fault ground motion records from the NGA‐West 2 database has been utilized. To verify the comprehensive categorization method, two datasets of pulse‐like ground motion records suggested by FEMA and PEER and one dataset of ground motion records collected during the 1999 Chi‐Chi earthquake are addressed. Numerical examples illustrate the remarkable effectiveness of the proposed method in identifying near‐fault pulse‐like ground motions based on their varying degrees of pulse‐like characteristics. [ABSTRACT FROM AUTHOR]

Purpose: Sustainable building design relies heavily on building parts, with crucial consideration for climate and environmental impact. Due to numerous criteria and diverse alternatives, employing multi-criteria decision-making (MCDM) to choose the best alternative is essential. Yet, relevant criteria and suitable MCDM methods for life cycle-based building planning still need to be determined. This study highlights prevalent environmental criteria and offers guidance on MCDM approaches for sustainable building parts. Methods: This study introduces an innovative approach by integrating life cycle assessment and MCDM. This provides comprehensive decision support for planners. A systematic literature review identifies environmental criteria for building parts and is validated in expert workshops. Thus, the relevance of criteria across the building life cycle is established. Furthermore, the study analyzes MCDM approaches in the built environment. From this, the study employs and evaluates the Analytical Network Process (ANP) and Analytical Hierarchy Process (AHP) in a case study. Thereby, it offers insights into effective decision-making methodologies for sustainable building practices. Results: This research categorizes environmental criteria for building parts and buildings into emissions, energy, resources, and circularity. Among 26 building part-related criteria, the global warming potential is highlighted. While the AHP is widely used in MCDM, a standardized method in planning processes is yet to emerge. Applying the ANP and AHP reveals similar rankings for the best and worst alternatives in a case study focused on selecting the optimal ceiling structure. Ribbed or box slab ceiling constructions are favored over reinforced concrete and composite timber-concrete constructions. Conclusions: This study presents a novel method for life cycle-based MCDM challenges, identifying key environmental criteria. While material correlations exist, evaluating building parts demands simultaneous consideration of multiple criteria. Future research aims to compare further MCDM methods regarding their applicability, transparency, and ranking to enhance decision-making in sustainable construction. These investigations are essential for refining decision-making processes in the built environment, ensuring effective and transparent sustainability planning approaches. [ABSTRACT FROM AUTHOR]

This paper takes the example of industrial architectural heritage in Dalian to explore design scheme generation methods based on generative artificial intelligence (AIGC). The study compares the design effects of three different tools using the Analytic Hierarchy Process (AHP). It first establishes the key indicator weights for the renovation of industrial architectural heritage, with the criterion layer weights as follows: building renovation 0.230, environmental landscape 0.223, economic benefits 0.190, and socio-cultural value 0.356. Among the goal layer weights, the highest weight is for the improvement of living quality at 0.129, followed by resident satisfaction at 0.096, and educational and display functions at 0.088, while the lowest is for renovation costs at only 0.035. The design schemes are generated using Stable Diffusion, Mid Journey, and Adobe Firefly tools, and evaluated using a weighted scoring method. The results show that Stable Diffusion excels in overall image control, Mid Journey demonstrates strong artistic effects, while Adobe Firefly stands out in generation efficiency and ease of use. In the overall score, Stable Diffusion leads the other two tools with scores of 6.1 and 6.3, respectively. Compared to traditional design processes, these tools significantly shorten the design workflow and cycle, improving design quality and efficiency while also providing rich creative inspiration. Overall, although current generative artificial intelligence tools still have limitations in understanding human emotions and cultural differences, with continuous technological iteration, this method is expected to play a larger role in the design field, offering more innovative solutions for the renovation of industrial architectural heritage. [ABSTRACT FROM AUTHOR]

The aggregate gradation of asphalt mixture is one of the most important factors affecting the service life of asphalt pavement. In order to study the gradation of asphalt mixture with the best comprehensive performance, this study puts forward a new method of mineral aggregate gradation optimization based on the fuzzy analytic hierarchy process and comprehensive evaluation method, aiming at the multi-level and multi-index evaluation of the road performance of asphalt mixture. First, the orthogonal test design method is applied to design nine target gradations with coarse aggregate (>4.75 mm) and fine aggregate (<4.75 mm) of AC-20 (asphalt concrete) mixture serving as two factors and the upper, middle, and lower positions of the gradation curve as three levels, and then the road performance test research is carried out. Second, a comprehensive model for evaluation of road performance of mineral aggregate gradation is established. A fuzzy complementary judgment matrix is constructed, and the index weights of each level and the hierarchical total ranking weight are calculated. Then, the membership function is introduced into the comprehensive evaluation model for the road performance of mineral aggregate gradation, and the membership values of each index of asphalt mixture road performance are obtained. Finally, the fuzzy comprehensive evaluation method is used to find out the comprehensive evaluation value of the road performance of the nine graded asphalt mixtures, and the mineral aggregate gradation is optimized. The research results show that the 1# gradation of the asphalt mixture has the highest comprehensive road performance evaluation value, and the combination of the fuzzy hierarchical analysis process and comprehensive evaluation method can more objectively and comprehensively evaluate the comprehensive road performance of the asphalt mixture and provide a useful reference for the optimal selection of asphalt mixture mineral gradation. [ABSTRACT FROM AUTHOR]

Greenhouse cultivation promotes an efficient and environmentally friendly agricultural production model, significantly enhancing resource sustainability and advancing sustainable agriculture. Traditional greenhouse pollination methods are inefficient and labor-intensive, limiting the economic benefits of greenhouse pear cultivation. To improve pollination efficiency and achieve fully automated mechanized operations, an innovative design method for greenhouse pear pollination drones has been developed. First, design criteria were extracted using Grounded Theory (GT), and the Analytic Hierarchy Process (AHP) was employed to determine the weight of user demand evaluation indicators. Next, the Quality Function Deployment (QFD) method translated user needs into technical requirements, resulting in the final ranking of design element weights. The drone was then designed based on these weighted rankings, yielding an optimal solution. This method quantifies the functional requirements of the product, effectively identifying key needs for the greenhouse pear pollination drones and proposing targeted solutions. Additionally, it provides a design reference for other highly functional agricultural machinery products. [ABSTRACT FROM AUTHOR]

Background: Palliative care is becoming an essential component of healthcare, but there is insufficient research on how integration across different levels of care (micro, meso, and macro) is realized in practice. Without such integration, care may become fragmented, leading to suboptimal patient outcomes. While many studies have explored palliative care models, there is a gap in understanding how priorities for integrated care align across these levels within healthcare ecosystems. Specifically, it is unclear whether key actions at each level are shared, coordinated, and supported effectively, making it difficult to implement sustainable, cohesive care strategies. Our study aims to explore the extent to which important goals (i.e., priorities) are shared across the micro, meso, and macro levels of the palliative care ecosystem in Flanders, Belgium. Methods: We applied a multimethod study using the analytic hierarchy process method (AHP). This consists of three sequential steps: a broad literature search and interviews with Belgian stakeholders (n = 12) to determine the criteria for the organization of integrated care; focus groups (n = 8) with patients, their relatives and caregivers to establish the completeness and relevance of the criteria; and prioritization of the criteria using a questionnaire among 305 Flemish participants (patients, relatives, caregivers and policy makers). Results: Our findings revealed that integration is imbalanced, with priorities being most emphasized at the micro level (57%), followed by the meso (29%) and macro (14%) level. Functional enablers dominate at the macro (80%) and meso organizational level (67%), while normative enablers are emphasized at the meso professional (67%) and micro level (75%). Effective palliative care requires vertical coordination of these enablers: for instance, transparent communication with patients at the micro level depends on cross-organizational information exchange at the meso level, supported by a unified data system at the macro level. Conclusion: Achieving integrated palliative care requires deliberate alignment of priorities across all levels of the ecosystem. While each level plays a unique role, palliative care is comprehensive and effective only by sharing both functional and normative enablers across micro, meso, and macro level. [ABSTRACT FROM AUTHOR]

In the wake of the increasing environmental challenges and the urgent need for sustainable development, this study focuses on the complex issue of mineral resource management. Given the growing global demand for minerals and the environmental impact of extraction, the research seeks to uncover the solutions that promote green growth while effectively addressing the ecological consequences of resource utilization in China. In the study, six factors, twenty‐four sub‐factors, and five potential solutions have been identified influencing sustainable mineral resource management and green growth. The study utilizes fuzzy Analytical Hierarchy Process (AHP) to assess these factors and sub‐factors. Following, the study utilizes fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method to evaluate and rank five potential solutions for sustainable development. The fuzzy AHP results indicate that environmental impact mitigation, robust policy frameworks, and innovation in extraction techniques are the most crucial factors. The fuzzy TOPSIS findings indicate that technological innovation for sustainability ranks highest, followed by policy‐driven green growth, socio‐economic empowerment, enhanced environmental stewardship, and integrated circular economy approaches. These findings emphasize the critical role of advanced technologies and robust policies in promoting sustainability while addressing the socio‐economic and environmental dimensions of mineral resource management. [ABSTRACT FROM AUTHOR]