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The use of big data analytics (BDAs) allows for the collection, management, and analysis of large volumes of data, which helps in making real-time decisions. This study aims to assess how the application of BDA impacts the performance of healthcare supply chain management (HCSCMP). Through a systematic literature review, the research explores how BDA enhances efficiency within healthcare supply chains (HCSCs) and identifies the critical factors enabling successful BDA implementation. A comprehensive search strategy was employed to analyze 65 papers, resulting in the inclusion of 39 studies published between 2016 and 2023. The review revealed a preference for literature reviews and questionnaires as the primary research methods. The findings indicate that BDA significantly improves HCSCs' efficiency, particularly in real-time decision-making and operational management. However, successful BDA implementation depends on addressing critical enablers and overcoming associated challenges.

The health sector is one of the components of development, social welfare and economic growth. The purpose of this study was to develop an economic evaluation model of the environmental and health costs of occupational diseases by hybrid approach. To achieve the study goal, a taxonomy of economic evaluation model of the environmental and health costs of occupational diseases has been developed. The Delphi method was used to identify health and environmental criteria and the analytic network process (ANP) method was used to weigh the sub-criteria. Finally, health and environmental cost were estimated based on the available information. Naft Subspecialty Hospital in Tehran, Iran (NSHT), was selected as the place of case study. In this study, eight and eleven sub-criteria were identified in the health and environmental sector, respectively. The ANP results indicated that the medicine and medical equipment cost criteria with a weight of 0.312 in the Medical sector, and the special and infectious waste cost criteria with a weight of 0.085 in the environmental sector were the most significant cost criteria in NSHT. Furthermore, the parametric model findings indicated that 99.84 and 0.16% of the total costs are associated with health and environmental costs, respectively. The findings indicated that 61.3% of the costs of the health sector were associated with the two sectors of medicine and medical equipment and the cost-of-service personnel, and 91.7% of the costs of the environmental sector are associated with wastewater treatment and the cost of electricity consumption. This study tried to present a quantitative model of the health and environmental costs of NSHT. Implemention of this integrated model can be a practical and effective step in allocating resources and prioritize interventions. [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]

Corporate social responsibility (CSR) is a popular research topic, but there have not been comprehensive discussions on CSR evaluation in the banking sector. The purpose of this study is to propose a two-stage analysis combining the modified Delphi method (MDM) and Analytic Network Process (ANP) in order to construct a model for evaluating banks' CSR. First, we use MDM to select and determine the interdependence of the criteria and then employ ANP to obtain their weights and to rank the alternatives. The results show that 5 criteria and 18 sub-criteria need to be considered in CSR evaluation. The most important criterion and sub-criterion are bank governance and regulatory compliance, respectively. The evaluation model constructed herein can be taken as a decision-making guide for evaluating banking organizations' CSR and to help promote CSR development in China's financial industry. [ABSTRACT FROM AUTHOR]

Given the advances in technology and the development of urban development and progress in people's lifestyles, the use of bridges is considered as an important and necessary way of esophageal communication. Bridges are one of the most important tools for connecting roads and different cities, which connect different areas and create connections between people. One of the most important and necessary measures in the bridge industry is related to the repair and maintenance of bridges, which cost less than building a bridge and help to create connections between people. To this end, the present study examines the effects affecting the maintenance and repair of bridges in urban contexts and for this issue an approach under conditions of intuitive fuzzy uncertainty based on analytic network process and comprise solution methods to calculate weights and option ranking offers. However, an integrated group decision making-based soft computing approach is tailored by computing the criteria importance and experts' weights to solve the urban concrete bridge maintenance model selection problem. Finally, to validate the proposed method, a case study is used along with a comparison of the proposed method and existing methods in the literature. The final results indicate the strength and efficiency of the proposed method in calculating weights and ranking options for the project of maintenance and repair of urban bridges in Rasht. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to identify potential major risks of railway metro project implementation and to assess the priority of project risks concerning cost, time, and quality in terms of five project aspects as follows: stakeholder consensus; technological and technical; economic and commercialized; natural environmental; political and legal. In this study, the analytical network process was carried out to assess the influence of risk variables on project objectives. The involvement of experts, together with the analytical network process, provided a list of 27 risk variables affecting the outcome of a railway metro project implementation in Ho Chi Minh City, Vietnam. The results show that the economic and commercialized risk group has the largest standardized composite risk preference index (NRPI = 0.334), the technological and technical risk group is ranked second with an NRPI = 0.276 value, followed by stakeholder consensus, political-legal and environmental risks with standardized composite risk priority indices of 0.182, 0.140 and 0.067 respectively. The prioritization of risk components regarding given groups can provide a holistic picture of potential project risks; and this can support policy-makers to re-evaluate a project plan and associated backup solutions to mitigate the risk consequences on project objectives. [ABSTRACT FROM AUTHOR]

The concurrent engineering approach necessitates integrating material selection into the product design to effectively align with client specifications. Premature product failure, leading to substantial losses, frequently arises as a consequence of inadequate material selection due to conflicting demands. The Multi-Criteria Decision Making (MCDM) procedures are essential for making wise decisions since choosing materials is complicated. This study employs fuzzy analytic network process (FANP) techniques to determine which bio-composite filaments will be the most effective for Fused Deposition Modeling (FDM). The requirements and available factors of egg carton packaging material determine the selection criteria for bio-composite filaments. These factors serve as the foundation for identifying ten essential features. The acquired data showed that the sugar palm fiber/polylactic acid composite (SPF/PLA) 7.5 wt.% fiber loading exhibited the highest priority score, 19.80%. The kenaf/acrylonitrile butadiene styrene (Kenaf/ABS) composite, with a fiber loading of 7.5%, exhibited the lowest ranking, scoring 4.4%. Subsequently, a sensitivity analysis was conducted to further corroborate the findings. It was observed that the SPF/PLA 7.5 wt.% fiber loading consistently ranked highest throughout all four examined scenarios. The study determined that a bio-composite filament material with a weight ratio of 7.5% SPF/PLA fiber loading is the optimal choice for utilizing FDM technology in the design of egg carton packaging. [ABSTRACT FROM AUTHOR]

As the world is more focused on developing products and services, which are sustainable, special attention is needed in the design and manufacture of machine tools. There is a multitude of elements that contribute to the sustainability of machine tools. Moreover, the elements are interdependent with each other. The presence and absence of each element can be measured by different indicators. This paper analyzes the influence of elements and their indicators on the sustainability of machine tools. Sustainability elements and their indicators have been identified first. Further, a new hybrid model was developed to find the interdependencies between the sustainability elements for machine tools and determine the priorities of the indicators. Two structural models, i.e., Decision-Making Trial and Evaluation Laboratory and Analytic Network Process, have been combined to establish levels and intensities of interdependence as well as the relative weight of selected indicators. The results classify the indicators into the receiver, dispatcher, and neutral groups and also point out the indicators with feedback dependencies, i.e., indicators that depend on themselves. The methodology can be applied for evaluating as well as comparing the sustainability of different machines. The observations would be helpful to the designers of machine tools to make strategies for improving the sustainability of their machines. [ABSTRACT FROM AUTHOR]

Flash flood is the most recurrent natural threat in northeastern India, especially during the peak of the monsoon season. In recent decades, the frequency of flash floods has considerably increased in the Himalayan watersheds, causing enormous human suffering, infrastructure damage, ecosystem disruption, and economic losses. Considering the exponential rise in the frequency of flash flood events, identifying the Flash Flood Vulnerable Zones (FFVZs) is one of the most crucial findings to limit their negative consequences. In this study, grey fuzzy analytic hierarchy process-based model integrated with the geographic information system is implemented to assess the flash flood vulnerability in the Ranikhola watershed, East Sikkim, India. Additionally, a novel Flash Flood Vulnerability Index (FFVI) is proposed to determine the flash flood vulnerability that takes into account twelve natural and anthropogenic parameters. Further, the FFVI map is classified into three FFVZs: low, moderate, and high. The effectiveness of the methodology implemented is judged by the high EV value (6.4286) and the comparison parameter. The harshest conclusion of this analysis, the major cities, such as Gangtok, Ranipool, and Singtam, are designated high FFVZ. The sensitivity analysis results show the LULC has the maximum positive influence on high FFVZ. [ABSTRACT FROM AUTHOR]

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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]

This article discusses the importance of climate risk and environmental accounting in corporate reporting. It highlights the increasing concern over climate risk and its impact on companies' operations and performance. Stakeholders from various spheres are advocating for a transition to a low-emissions economy, pressuring organizations to disclose their climate-related risks and governance systems. Legislative developments, such as the Paris Agreement and the Task Force on Climate-Related Financial Disclosures (TCFD) recommendations, have further intensified the pressure on firms to integrate climate risk management into their accounting processes. The article features a collection of papers that explore different aspects of corporate reporting and how firms have responded to recent legislative and policy developments regarding climate risk disclosures. [Extracted from the article]

Purpose: The growing business complexity has caused many risks (e.g. operational, financial, reputational, cybersecurity, regulatory and compliance) that threaten companies' sustainability and have received attention from regulators, investors, and businesses. The authors present a model for assessing and reporting corporate risk by examining the indicators underlying corporate risk reporting. Design/methodology/approach: A thorough review of the literature and semi-structured interviews with experts were conducted and the fuzzy Delphi technique was used to obtain consensus and screening of risks. The relationships between these risk indicators were recognized, weighted and prioritized by employing a hybrid Decision Making Trial and Evaluation Laboratory Model (DEMATEL) method integrated with Analytic Network Process (ANP) (DEMATEL-ANP [DANP]) approach. Finally, using the Iranian setting of corporate risk reporting, a model was developed to calculate the risk-reporting scores. Findings: The results indicate that risk disclosure quality is more important than risk disclosures' textual properties and quantity. According to the experts, reporting the key risks that the company faces, management's approach to dealing with these risks and quantifying their impact are more important than the other indicators. The results also show that risk reporting in Iran lacks quantitative and specific information, and most risk disclosures are sticky. Research limitations/implications: The data have been prepared and analyzed according to the unique Iranian reporting environment, which should be considered when interpreting the results. Practical implications: The results of this research can be used by the regulators of the Stock Exchange Organizations (SEO) to evaluate corporate risk reports and rank companies. Results are also relevant to investors and policymakers to identify companies with poor risk disclosure and to take necessary measures to improve their reporting practices. Social implications: This paper contributes to the social and governance literature by presenting the importance of risk reporting in corporate disclosures. Originality/value: The unique Iranian setting of corporate risk reporting furthers the understanding of risk reporting and thus provides education, policy, practice and research implications for other emerging economies like Iran. Many prior studies focus mainly on the quality of risk disclosure, and other aspects of corporate risk disclosure presented in the study have remained largely overlooked. The corporate risk reporting attributes identified in the study are relevant to the rise of non-financial risks, the textual and qualitative nature of risk reporting and textual risk disclosures. [ABSTRACT FROM AUTHOR]

While the world is grappling with economic uncertainty, corporate social responsibility (CSR) has been extensively studied with a focus on favorable economic conditions. This study aims to investigate and prioritize the drivers for CSR in large‐sized construction organizations during economic uncertainty. Based on the literature review and discussions with experienced professionals, 13 critical drivers for CSR were identified and categorized into four clusters. Using the combination of fuzzy Decision Making Trial and Evaluation Laboratory and fuzzy Analytic Network Process (DANP), drivers for CSR performance during economic uncertainty were ranked regarding their interrelationships. Among 13 drivers, the results illustrated that enhancing company reputation was the most critical driver for CSR, followed by long‐term economic benefit, employee commitment and loyalty, and credibility gain. This study expands the current understanding of CSR practices in the construction industry, shedding light on its unique characteristics during economic uncertainty. [ABSTRACT FROM AUTHOR]

Application of the Water-Energy-Food Nexus system is essential for addressing Water-Energy-Food Security and Environmental Protection in urban agricultural areas. However, there is currently no standardized framework for measuring and comparing sustainability indicators in these areas using the WEF Nexus practices. This study proposes sustainability measurement indicators to evaluate the WEF Nexus sustainability. The Analytical Hierarchy Process (AHP) was employed to identify the most crucial indicators for policymakers. The WEF nexus sustainability indicators were selected based on three dimensions of sustainability: social, environmental, and economic. The study focused on Varamin, a semi-arid city in Tehran that serves as a center for urban agriculture. Research results indicate that water-related components are crucial in arid and semi-arid regions. Based on the environmental sustainability indicators, pollution prevention, with a priority of 52.8%, is a critical component of sustainability. Finally, several key indicators are recommended for decision-makers to address sustainability. Allocating national budgets to create environmental policies and increasing public education on environmental issues are two priorities for achieving sustainability goals. However, future studies should utilize the Analytic Network Process (ANP), which enables interdependencies among decision components, as the AHP approach has some limitations. [ABSTRACT FROM AUTHOR]

The power industry is currently undergoing a rapid transformation toward the maximum utilization of renewable energy resources. In grid-connected renewable energy systems, enhancing the voltage stability during the fluctuations in renewable energy outputs can be achieved using a transformer with built-in on-load tap changing. It is one of the main traditional voltage regulation techniques utilized to improve the voltage profile in the power grid. Due to the unpredictable nature of renewable energy penetration, the frequent operation of an on-load tap changer (OLTC) may increase significantly. Despite the proposed methods used to optimize the location and size of renewable generation, there is a lack of empirical or detailed studies that have been looking at the issue of tap changers, mainly the impact of renewable energy storage allocation. The main aim of this paper is to find a compromise approach to mitigate unnecessary tap-changing operation time by wisely siting and sizing the renewable energy storage system (RESS). Initially, a generalized method is proposed to formulate an analytical optimization framework coupled with a renewable storage index. This approach is employed to evaluate the behavior of OLTC in a grid-connected renewable energy system. The formulation is then used to model a decision-making approach to confirm the location and size of RESS, using the analytic network process (ANP) with entropy and technique for order of preference by similarity to an ideal solution (TOPSIS). The performance of the proposed approach is evaluated and compared using the IEEE benchmark networks. Aspects in relation to the predictions of future operations about the management of renewable energy storage in coordination with voltage regulators in the smart grid context, that will be the subject matter of additional studies are also discussed. [ABSTRACT FROM AUTHOR]

With the objectives including the reduction of whole life costs, increasing construction and operation efficiencies and enhancing service quality, Public-Private Partnership (PPP) schemes have been increasingly used in healthcare projects throughout the world. Besides its advantages, several issues were reported in the literature regarding the success of healthcare PPPs. Poor project performance is a key concern, while performance is determined by the occurrence of multiple interrelated factors. In this study, it was aimed to develop a network-based success model for PPP healthcare projects, which encompasses the whole project life cycle and various project dimensions, by considering the interdependence among the Critical Success Factors (CSFs). A framework comprised of 33 CSFs organized in six groups was proposed based on the findings of an extensive literature review and semi-structured expert interviews. Project success was modeled with the Analytic Network Process (ANP) through three group discussion sessions held with experts from the private sector. The model was tested via the assessment of two real projects' performance by the experts. The proposed model, which is a unique attempt in this area, can be used by decision-makers during the pre-tender, planning and execution phases of a PPP healthcare project to develop strategies for performance improvement. [ABSTRACT FROM AUTHOR]

In this study, we address a critical aspect of the routing protocol for low-power and lossy Networks (RPL), namely the selection of the parent node, which plays a pivotal role. As IoT networks expand rapidly, tackling data congestion becomes increasingly crucial. The conventional RPL algorithm, initially designed for smaller networks, lacks mechanisms for balancing loads during parent–child node assignment and does not consider congestion scenarios. To overcome these limitations, we propose a novel objective function (OF) tailored specifically for the RPL algorithm. This OF integrates network load and congestion conditions using an Adaptive fuzzy multi-criteria decision-making approach, combining fuzzy analytic hierarchy process and technique for order of preference by similarity to ideal solution (TOPSIS) techniques. By redefining the process of selecting parent nodes, our approach enhances the efficiency of data transmission, alleviates congestion, and optimizes the performance of IoT networks. Our method introduces a multi-criteria decision-making framework for parent node selection, ensuring that the chosen parent node is both free of congestion and balanced in load, resulting in efficient forwarding of data packets. We prioritize parent node selection based on five crucial criteria, directly addressing load and congestion challenges in IoT networks. Through fuzzy AHP, we determine the relative importance of each criterion, while the TOPSIS method aids in ranking alternatives. This comprehensive approach provides a robust solution to mitigate network congestion, optimize load distribution, and enhance IoT network performance amidst dynamic growth. Implementing the algorithm using Contiki OS and the Cooja simulator, our results demonstrate 0–15% reduction in delay, 20–30% lesser energy consumption, and 10–25% reduction in packet overflow rate while maintaining network throughput by 15% as compare to CQARPL, CAFOR and QHCA and enhancing overall performance. [ABSTRACT FROM AUTHOR]

Pairwise comparisons have been a long-standing technique for comparing alternatives/criteria and their role has been pivotal in the development of modern decision-making methods such as the Analytic Hierarchy/Network Process (AHP/ANP), the Best-Worst method (BWM), PROMETHEE and many others. Pairwise comparisons can be performed within several frameworks such as multiplicative, additive and fuzzy representations of preferences, which are particular instances of a more general framework based on Abelian linearly ordered groups. Though multiplicative, additive and fuzzy representations of preferences are widely used in practice, it is unknown whether decision makers are equally precise in the three aforementioned representations when they measure objective data. Therefore, the aim of this paper is to design, carry out and analyse an experiment with over 200 respondents (undergraduate university students) from two countries, Czechia and Italy, to compare precision of the respondents in all three representations. In the experiment, respondents pairwise compared (by approximation) the areas of four geometric figures and then, the imprecision of their assessments was measured by computing the distance with the exact pairwise comparisons. We grouped the respondents in such a way that each participant was allowed to deal with a unique type of representation. The outcomes of the experiment indicate that the multiplicative approach is the most precise. [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]

Agricultural investment project selection is a complex multi-criteria decision-making problem, as agricultural projects are easily influenced by various risk factors, and the evaluation information provided by decisionmakers usually involves uncertainty and inconsistency. Existing literature primarily employed direct preference elicitation methods to address such issues, necessitating a great cognitive effort on the part of decision-makers during evaluation, specifically, determining the weights of criteria. In this study, we propose an indirect preference elicitation method, known as a preference disaggregation method, to learn decision-maker preference models from decision examples. To enhance evaluation ease, decision-makersmerely need to compare pairs of alternatives with which they are familiar, also known as reference alternatives. Probabilistic linguistic preference relations are employed to account for the presence of incomplete and uncertain information in such pairwise comparisons. To address the inconsistency among a group of decision-makers, we develop a pair of 0-1mixed integer programming models that consider both the semantics of linguistic terms and the belief degrees of decision-makers. Finally, we conduct a case study and comparative analysis. Results reveal the effectiveness of the proposed model in solving agricultural investment project selection problems with uncertain and inconsistent decision information. [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]

Various multi-criteria decision-making methods have been utilized in literature to address vendor selection challenges in various contexts. This study reflects on these decision-making techniques for vendor selection in the software ecosystem during software outsourcing. For the same, firstly, a requirement framework for the decision-making process for software vendor selection is proposed. Afterwards, five selected different multi-criteria decision-making techniques are compared and critically analysed against this requirement framework. This study supports software practitioners and decisionmakers by providing information about which decisionmaking method to choose, considering the trade-off between the benefits and drawbacks of adopting each method or using hybrid approaches by combining two or more techniques with fuzzy logic. It is found that decision-making techniques generally lack in modelling the problem itself and handling the conflicts and uncertainties that may prevail during the decisionmaking process. Furthermore, it has been identified that artificial neural networks (ANN) and analytic network process (ANP) can support the dependencies between alternatives and criteria while handling complex interactions in the software ecosystem. On the other hand, due to its comparative ease of use, analytic hierarchy process (AHP) can serve better in scenarios where decision-makers are not experienced, or past data to train the ANN or ANP models is unavailable. [ABSTRACT FROM AUTHOR]

This research aims to see the extent of the problem of zakat in alleviating poverty in North Sumatra. This research method uses a descriptive qualitative method with a quantitative approach. For analysis, use the ANP (Analytic Network Process) method with the help of "Super Decision" software. This research uses secondary data originating from the zakat outlook of the BAZNAS Center for Studies and Strategy, accompanied by the opinions of zakat practitioners in North Sumatra. This research was carried out in the North Sumatra Province area and the research was carried out in stages starting from August 2023 to September 2023. The results of the research show that (1) The most priority problem in managing zakat funds in North Sumatra is external problems at 65%, (2) The most priority internal problem is the Amil problem at 70%, (3) The most priority external problem is the Muzakki problem at 49%, (4) The most priority internal solution is the Amil solution at 71%, (5) External solutions the most priority is the Mustahik Solution at 72%, (6) The most priority strategy to be implemented for effective management of zakat funds is Developing the correct mindset for muzakki and mustahik at 61%. [ABSTRACT FROM AUTHOR]

This study delves into the flow and structure of knowledge prevalent in Analytic Network Process (ANP) literature. It traces the evolutionary pathway of ANP research, spotlighting seminal works and unfolding the development of topics over time. Analysing 4583 ANP literature records from 1986 to 2022, this research utilizes two pivotal data sources: Web of Science (WoS) and Dimensions. This main path analysis (MPA) approach is coupled with techniques such as citation analysis, social network analysis, and centrality measures to identify most influential papers, as well as using a search path algorithm (SPC) to provide higher weights to papers that serve as bridges connecting different research paths rather than simply counting all citations equally. Key works emerged as focal points in both datasets, including notable contributions from Lee, Kheybari and Büyüközkan, with the Dimensions dataset uniquely highlighting Saaty as the initial conceptual knowledge source of the ANP. The centrality measures unearthed persistent bridge roles undertaken by key contributors such as Saaty and Sarkis over different time periods. Furthermore, a detailed topic analysis discerned eight distinctive thematic clusters among the two data sources: analytical network process, network process, fuzzy analytic, evaluation laboratory, supply chain, quality function, hierarchy process, and information systems. These clusters emerged, providing a comprehensive map of ANP topics and their evolution. The study offers a comprehensive framework for scholars to navigate the expansive domain of ANP research. Identifying pivotal works and emergent themes provides direction for future research endeavours. It allows practitioners to gain invaluable insights into the foundational and transformative works in the ANP realm, enhancing their understanding and application of the methodology. This paper proposes of a dual methodological strategy: First, by using traditional academic data sources (WoS) along with a more encompassing Dimensions database; and second, by using a SPC algorithm to weight MPA papers based on their connecting role among different research paths. At the discipline level, this study carves out a novel vantage point in understanding the ANP research landscape. It offers an integrated portrayal of the field's conceptual evolution, identifying specific cluster topics as an indispensable resource for scholars, practitioners, and students. [ABSTRACT FROM AUTHOR]

A new approach to the solution of an important problem of a better use of personnel, sales representatives, for cable television service system providers in Taiwan is discussed. A new multi-criteria decision-making (MCDM) model is proposed for personnel selection meant as a process of selecting candidates who are qualified to perform specific jobs in the best possible way. The new approach involves first the selection of criteria for the sales representatives. Fuzzy importanceperformance analysis (FIPA) is used to design a questionnaire, and interviews with executives are performed. A new method for the determination of importance and degree of satisfaction of the criteria proposes is developed. Decision making trial and evaluation laboratory (DEMATEL) method is used to establish interactions between the dimensions and criteria. Analytic network process (ANP) is then used to find the weights of each dimension and selection criterion based on their interaction via pairwise comparison. The integrated weights obtained for each selection criterion are then employed in technique for order preference by similarity to ideal solution (TOPSIS) to select the best sales representative. A realistic example is provided. [ABSTRACT FROM AUTHOR]

Modeling and linguistic representation in the form Interval Type-2 Fuzzy have better accuracy than Type-1 Fuzzy. The type-2 fuzzy set involves more uncertainty than the type-1 fuzzy set. The degree of fuzzy membership is used to explain uncertainty and ambiguity in the real world. This study presents the type-2 Fuzzy Analytic Network Process (ANP) method to determine the weight of each attribute based on the level of interest and the extension method of type-2 Fuzzy TOPSIS to handle problems based on the value of the fuzzy type-2 attribute. Decision-making is based on the assessment of several experts called Multi-Criteria Group Decision Making (MCGDM), using type-2 Fuzzy geometric mean aggregation function. The membership function in this research is type-2 fuzzy based on the trapezoid. The contribution is a hybrid method Type-2 Fuzzy TOPSIS with Fuzzy Type-2 ANP group-based with new metric intervals on fuzzy type-2 for decision making. The results are a hybrid type-2 FANP and FTOPSIS decision-making model to support the best decision-making. Based on a comparison of the accuracy of trapezoid model 1, model 2, and model 3, the best accuracy result is model 3, which is 84%. The research benefits by presenting a hybrid Type-2 Fuzzy TOPSIS and ANP method that improves decision-making accuracy and better handling uncertainty and ambiguity than Type-1 Fuzzy systems. [ABSTRACT FROM AUTHOR]

This paper presents a method for identifying causal relationships between strategic objectives within a strategy map of a Balanced Scorecard. Strategy maps are modeled as a network of strategic objectives (nodes) and causal relationships (directed arcs). The nodes are also grouped into clusters that represent the perspectives of a Balanced Scorecard: (a) Finances, Clients, Internal Processes and Growth and Learning. The method uses the Analytic Network Process (ANP) to establish the importance of every relationship and uses a multi-objective integer linear programming model to select the relationships to be included within a strategy map of a company. The method provides a method that optimizes the selection of the relationships to be included in a strategy map. An illustration of the application of the method in a manufacturing company is presented. [ABSTRACT FROM AUTHOR]

Introduction: Performance evaluation is essential in defining supply chain strategies because the firm can find out how the business processes in the supply chain are running and formulate strategic policies. Kayumas coffee is one of Indonesia’s specialty coffee with a unique aroma and flavor originating from Kayumas Village, Situbondo District, East Java. Kayumas coffee supply chain needs to be evaluated because of the lack of competitiveness with other specialty coffees. Strategies are needed to improve supply chain performance, improve product quality, and reduce costs. This study aims to configure the supply chain of Kayumas specialty coffee structure, evaluate its performance, and determine performance improvement strategies. Methods: This study uses descriptive analysis to configure the supply chain structure and flow. Analysis of supply chain performance based on Supply Chain Operation Reference (SCOR) model then weighted with Analytic Network Process (ANP). Performance improvement strategies were formulated by a discussion with experts and then weighted with ANP. Results: The research results show that the Kayumas specialty coffee supply chain comprises farmers, farmer groups, distributors or resellers, and consumers. There are 6 performance indicators (metrics) to measure performance: perfect order fulfillment, order fulfillment cycle time, flexibility, total supply chain management cost, cost of goods sold, and cash-to-cash cycle time. Performance measurement shows that Kayumas specialty coffee supply chain performance is in the inferior category. Conclusion: The strategy needed to improve supply chain performance by reducing cost is a partnership between supply chain members to reach a price agreement.

This study assessed the service efficacy of Nanjing’s urban open space (UOS) system, emphasizing the complex structural characteristics of UOS services, specifically, the impact of interactions between different subsystems on the overall service efficacy of the UOS system. The objective was to understand whether and how a UOS system can effectively and efficiently meet urban needs under constrained conditions. The dimensions of UOS services and the interrelationships between services offered by different subsystems were examined, and a structural model for assessing the service efficacy of the UOS system was developed. A multidimensional analytical approach was applied to quantify and characterize the relationships between subsystems and identify and determine the weighting of subsystem analysis indicators. The findings indicate that subsystems and their respective indicators differ in importance across dimensions, influence each other, and collectively form the overall service efficacy of a UOS system. Furthermore, while service efficacy across different administrative districts in Nanjing’s main urban areas generally remains moderate, significant differences in evaluation values exist among districts and subsystems, offering direction for future urban planning and resource allocation. This study offers detailed insights into the efficiency and optimization of UOS services, helping urban planners improve UOSs globally.

In order to scientifically evaluate the command capability of a joint combat command organization, the paper establishes a command capability indicator system for the joint combat command organization, analyzes the interrelationships between indicators at various levels and the interrelationships between elements within the indicator group, and uses Super Decisions software to establish a relationship diagram of command capability evaluation indicators for the joint combat command organization, obtaining the weight of the final indicator system, collects two groups of command organization exercise evaluation data and calculates the evaluation results of capability. By analyzing the weight of indicators, it is pointed out that to improve the command capability of joint operations organizations, it is particularly important to focus on three key points: planning and decision-making capabilities, intelligence reconnaissance capabilities, and operational control capabilities.

In dealing with the occurrence of earthquakes, urban communities and people within the system should primarily consider the geological background, secondary hazards caused by earthquakes, countermeasures to mitigate earthquake disasters, community connectivity, and the impact of various indicators and criteria on the earthquake-proof capacity of the community. It is important to comprehensively assess these factors to ensure that a community is well-prepared to withstand an earthquake. This study takes Shenzhen (China) as an example to conduct a preliminarily evaluation of a method of earthquake-proof capacity during an earthquake, with the results reflecting the comprehensive capacity of communities. The evaluation framework focuses more on effectively improving the disaster response capacity and resilience of urban communities. [ABSTRACT FROM AUTHOR]

The coordinated development of land urbanization and population urbanization is crucial for the advancement of new urbanization. The study applied the entropy weight method and coupling coordination degree model, taking Shaanxi—a province in China characterized by a moderate pace of economic development and volume, along with distinct geographic and demographic features within its region—as the subject. It assessed the coordination conditions of these two types of urbanization from both macro and micro scales during the years 2010–2022. Utilizing the Analytic Network Process (ANP), the study ranked and analyzed the causes of issues stemming from uneven development, thus connecting a crucial link from theoretical analysis to decision-making implementation. The results showed that: (1) The province's land urbanization index was between 0.075 and 0.203, whereas the population urbanization index ranged from 0.221 to 0.408, with the development of the former significantly lagging behind the latter. (2) The coupling degree between land and population urbanization ranged from 0.835 to 0.854, with a coordination degree between 0.148 and 0.306. This indicated that a close connection had been formed between the two, yet a benign coupling relationship had not been established, displaying a spatial distribution characterized by "high in the middle, low in the north and south". (3) The limitation on further urban expansion was identified as the primary issue to be addressed (with a weight of 0.324), followed by insufficient infrastructure (with a weight of 0.261). The extent of ecological environmental damage was comparatively lower (with a weight of 0.225), and the degree of social injustice was the lowest (with a weight of 0.191). Therefore, to alleviate the problems associated with the imbalanced development between land urbanization and population urbanization, measures such as optimizing land spatial layout, enhancing urban ecological service functions, and strengthening the central cities' radiating effect should be implemented. [ABSTRACT FROM AUTHOR]

This study aims to analyze problems and formulate and strategize in the development of halal tourism destinations rooted in local wisdom in Jambi Seberang City. The research method used is a combination of qualitative and quantitative approaches. The specific methodology applied is the Analytic Network Process (ANP), which is implemented through Super Decision software. ANP was chosen for its ability to set priorities in the context of decision making. The results obtained from this study show that the main issue faced is related to government participation. The priority strategies identified include the formation of synergies between various interested parties, increasing government commitment in supporting the development of halal tourism, developing a structured halal tourism development concept, and improving the quality of human resources. Through this research, it is expected to be a source and basis for planning the development of halal tourism in Jamb, especially in Jambi Kota Seberang. [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 present study aims to identify and prioritize the factors affecting the marketing of knowledge-based products of basic chemicals. This research is applied in terms of objectives and a data-based cross-sectional survey concerning its method. Initially, the factors affecting the marketing of products in this sector were identified based on library and field studies and by purposive sampling of 15 senior managers of knowledgebased chemical companies (research experts) utilizing a semi-structured interview in the form of a questionnaire. Cochran's formula was then employed, and 400 experts and staff working in this department were selected as the study's statistical population through simple random sampling. Subsequently, confirmatory factor analysis was used to analyze the data and check the final model's fitting. In the end, each factor's relative importance was determined by the fuzzy Dematel analytic network process (DNAP) method. The results led to the identification of 16 sub-criteria under 7 main criteria, including technical and managerial, information and knowledge, economic, infrastructural, legal, and support issues, besides supply capabilities. The results revealed that the information and knowledge criterion and the innovation sub-criterion had the highest score, while the supply capability criterion and the knowledge management sub-criterion were ranked last. [ABSTRACT FROM AUTHOR]

Maritime freight companies are beneficial in carrying the majority of commodities globally. The large number of parties involved makes data exchange hard. Blockchain technology's potential benefits are becoming more apparent to maritime freight firms. This report examines the important factors influencing blockchain technology adoption in the maritime freight sector. To calculate their weights, the study applies the Grey-DEMATEL based Analytic Network Process. According to the analysis, the most important determinants are government policies, firm size, and perceived cost of investment. These insights can assist government agencies, freight companies, and blockchain service providers in planning successful implementations and increasing competitiveness. [ABSTRACT FROM AUTHOR]

The present research focuses on ranking cloud services by using the k-means algorithm with multi-criteria decision-making (MCDM) approaches that are the prime factor in the decision-making process and have been used to choose cloud services. The tools offered by MCDM can solve almost any decision-making problem. When faced with a selection challenge in the cloud environment, the trusted party would need to weigh the client's choice against a predetermined list of criteria. There is a wide range of approaches to evaluating the quality of cloud services. The deep learning model has been considered a branch of artificial intelligence that assesses datasets to perform training and testing and makes decisions accordingly. This paper presents a concise overview of MCDM approaches and discusses some of the most commonly used MCDM methods. Also, a model based on deep learning with the k-means algorithm based decision-making trial and evaluation laboratory (kDE-MATEL) and analytic network process (ANP) is proposed as k-means algorithm based decision-making trial and evaluation laboratory with analytic network process (kD-ANP) for selecting cloud services. The proposed model uses the k-means algorithm and gives different levels of priority and weight to a set of criteria. A traditional model is also compared with a proposed model to reflect the efficiency of the proposed approach. [ABSTRACT FROM AUTHOR]

Copyright of Experimental Technology & Management is the property of Experimental Technology & Management Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this study, it was aimed to select the most suitable dowelled-leg-and-rail joint (DLRJ) type with multi-criteria decision-making (MCDM) techniques. For this purpose, five types of DLRJ with staggered-rail, flush-rail, lapped-rail, elevated-rail, and mitered-and-lapped-rail were selected as the decision-alternatives and 4-variables consisting of strength, cost, capacity and aesthetics were determined as the decision-criteria. To obtain data, sample tests for the strength values, a work-study analysis for the capacity and cost values, and a questionnaire were performed for the aesthetic superiority values of the joints. In prioritization of the decision criteria and selection and ranking of the alternatives, Criteria Importance through Intercriteria Correlation (CRITIC) + Additive Ratio Assessment (ARAS) hybrid method was used. According to the questionnaire, the most aesthetically pleasing joint was the DLRJ with flush-rail while the DLRJ with lapped-rail was the lowest priority joint type. According to the results of the CRITIC application, strength was the top priority criterion in the selection. The cost, the capacity and the aesthetics followed this respectively. According to the results of the ARAS application, the DLRJ with mitered-and-lapped-rail was optimal while the DLRJ with lapped rail was the last choice option. An increase in the number of criteria, the variables of criteria and the analysis values of these variables are effective factors in the results. [ABSTRACT FROM AUTHOR]

Copyright of Command Control & Simulation / Zhihui Kongzhi yu Fangzhen is the property of Command Control & Simulation Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Objective: The aim of the current research is to identify the effective factors on the cultural model of good governance in government performance monitoring agencies using the Fuzzy ANP method. Methodology: This research is considered applied in terms of its goal and is of a mixed nature. The research population, in a qualitative framework, consists of academic experts and specialists in government performance monitoring agencies, of which 10 individuals were selected through purposive judgment sampling. The data collection tool in this research is the Delphi questionnaire. Findings: The main factors affecting good cultural governance were identified based on the research background and expert opinions, based on structure, law, and value, and a total of 11 sub-criteria were also determined for the main factors. Conclusion: The results of the research indicate that the legal dimension was the most significant factor affecting the cultural model of good governance in government performance monitoring agencies, followed by value and structural factors in subsequent ranks. The main reasons affecting good governance based on culture relate to professional ethics, the suitability of culture with requirements, and the presence of a value system. In this regard, the enumeration of ethical principles in the organization and their institutionalization can be effective. [ABSTRACT FROM AUTHOR]

Introduction: Global climate changes, primarily manifested as global warming and rapid urbanization, exacerbate extreme weather events. Statistics indicate that floods are among the most prevalent and catastrophic natural disasters (Safiah Yusmah et al., 2020: 552). Urban floods caused by heavy rainfall have evolved from gradual accumulation to sudden surges (Masozera et al., 2007: 299; Hallegatte et al., 2013: 802). Therefore, urban flood resilience, crucial for flood control and disaster reduction, has garnered increasing research focus (Obrist et al., 2010: 284; Xu et al., 2018: 5298). The Sendai Framework for Disaster Risk Reduction (2015-2030), endorsed by the World Conference on Disaster Risk Reduction in 2015, and the 2018 Beijing Resilient City Development Plan, underscore the importance of enhancing urban resilience to disasters (Sun et al., 2022: 1). To address the growing risk of natural events, it is essential to strengthen capacities that enable vulnerable communities to better prepare for, cope with, and recover from adverse effects. In disaster management literature, this strategy is commonly referred to as resilience. Resilience, when applied to communities, is defined as “the ability of a community to prepare for, plan, absorb, recover, and adapt to actual or potential adverse events in a timely and efficient manner, including rebuilding and improving essential functions and structures.” A resilient community incurs fewer losses and recovers more swiftly from hazardous events (Cutter et al., 2014: 65; Abdali et al., 2022: 6). Theoretical Framework: The concept of resilience originated from Holling’s seminal work in ecology, aimed at understanding the instability and dynamics of nature. According to Holling, resilience is “the measure of a system’s ability to absorb change and disturbance while maintaining the same relationships between populations or state variables.” However, resilience is not simply “the ability of a system to return to equilibrium after a temporary disturbance” (Holling, 1973: 14-17). In ecological literature, two definitions of resilience emerged: one that encompasses continuity, change, and unpredictability in a nonlinear and non-equilibrium system (ecological resilience), and another that focuses on efficiency, stability, and predictability in a single equilibrium system (engineering resilience) (Holling, 1996: 25; Folke, 2006: 256). Engineering resilience emphasizes rapid and efficient recovery post-disturbance, while ecological resilience is about absorbing changes and ensuring continuity (Pickett et al., 2004: 373). Methodology: This study employs a combined multi-criteria decision-making approach using the Analytic Network Process (ANP), DEMATEL technique, and the Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE). The DEMATEL-ANP model identifies internal relationships between indicators, allowing for pairwise comparisons and weight evaluation, while PROMETHEE ranks solutions based on their proximity to the ideal solution, with the best solution being closest to the ideal point (Chen et al., 2011: 909; Chiu et al., 2013: 49; Thor et al., 2013: 27; Ju et al., 2015: 348-349). Results and Discussion: Resilience in Khorramabad exhibits a clear spatial pattern, with higher resilience in affluent upper city areas and lower resilience in less affluent lower city areas. This disparity highlights the inequitable distribution of urban facilities and services, emphasizing the need for equitable development and access to vital resources. Economic resilience is surprisingly lower in the city’s economic center due to deteriorated infrastructure and the residence of lower socioeconomic strata. Institutional resilience is higher in central areas, benefiting from the concentration of governmental, private, and grassroots organizations. Peripheral areas suffer from inadequate infrastructure, resulting in lower overall resilience. Social capital resilience lacks a specific spatial pattern, with most areas rated as medium to low, indicating weak community connections. Environmental resilience shows that city center areas are more prone to flooding, while higher resilience is observed in different parts of the city, possibly due to land permeability and river positions. Comparative analysis reveals that regions 1, 4, 7, 13, and 17 have the lowest resilience, while regions 23 and 14 rank high. This analysis provides a comprehensive understanding of resilience levels at the city scale, identifying areas requiring further intervention. Conclusion: Mapping the results reveals distinct spatial patterns of resilience and identifies hotspots needing more intervention. Central and western regions, with lower resilience, require more attention. Environmental and infrastructural factors are key, directly relating to land use and planning. The findings can assist Khorramabad’s urban planning organizations in integrating disaster resilience into urban planning, transforming reactive plans into proactive adaptation strategies. Additionally, identifying potential hotspots can aid emergency management institutions in effective disaster risk management. Enhancing social resilience is crucial for community capacity building to prepare for, respond to, and adapt to climate change impacts, guiding local stakeholders in fostering fair development and equitable resource access. [ABSTRACT FROM AUTHOR]

Floating cities have emerged as an efficient long-term solution over unsustainable practiced solutions to combat the rising seas problem; nevertheless, the world lacks an international, official, and comprehensive framework regarding floating cities. Although previous research approached modular floating city design; however, resulted in configurations with various critical design restrictions mainly regarding interlocking capabilities and space utilization. The purpose of this paper is to offer a new systematic strategy for configuring modular and expandable floating cities without such restrictions. This paper explores Euclidean tilings as a strategy to offer numerous configurations based on regular, semi-regular, and demi-regular tilings. Selecting the ideal configuration is complicated; therefore, both quantitative and qualitative data methods were implemented to attain the objectives. Via an extensive literature review, this research derives key factors for configuring floating cities, then sets a brainstorming session with experts for group decision making before providing findings upon calculations via analytic hierarchy process, one of the most used quantitative data methods of multiple-criteria decision analysis. Through comprehensive literature review: seakeeping, modularity, zoning and circulation, and feasibility have been identified as the most significant criteria in floating city research. It explores the qualities and limitations of triangular, squared, hexagonal, octagonal, and dodecagonal platforms. Regarding criteria, seakeeping was the most significant criterion for platform selection by 53.6%. Regarding platforms, the hexagonal platform scored the highest with 25.31%. Relying on this method and the design considerations presented, numerous dynamic configurations can be offered and assessed through specific contexts without any of the past restrictions. [ABSTRACT FROM AUTHOR]