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Due to the rapid development of information technology, supply chain network is evolving, which involves a higher level of interdependence between organisations. Conventional production capability evaluation relies on centralised approaches with limited sharing of performance and evaluation data. Besides, traditional evaluation methods are mainly based on subjective manual operation using limited data. In this paper, we propose a production capability evaluation system by incorporating Internet of Things (IoT), machine learning and blockchain technology for supply chain network. It contributes to achieving real-time data collection and automated enterprise production capability evaluation mechanism. Besides, blockchain technology is adopted to enable open and decentralised data storage and sharing, provide fair and automatic trading of data. The proposed system is evaluated through a simulation experiment. It demonstrated how to utilise the proposed system to choose suitable upstream enterprises. The successful development of the system could help to enhance production efficiency, reduce risk and provide a reasonable and more sustainable production management in supply chain network. [ABSTRACT FROM AUTHOR]

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

Precast Concrete Construction (PCC) is a famous method in construction industry due to its different advantages. Nevertheless, this method has several discontinuous processes and they can enhance various uncertainty safety-quality issues. In this system, Building Information Modeling (BIM) technique plays a key role in managing of discontinuous processes to improve multidimensional safety and quality. Dimensionless parameters were used to evaluate the modified type of multidimensional BIM index (IMBIM) as the target index using the Modified Fuzzy Analytic Network Process (MFANP) method. In fact, the importance weight of input indices on the target was determined by the MFANP approach. The results of statistical analysis in verification step indicate that MFANP is well compatible with other approaches, so this developed method was considered as a reference point. The modified uncertainty Markov Chain Monte Carlo (MCMC) analysis was used for the validated method to determine the optimal high occurrence rate of IMBIM. The results demonstrate that a high percentage of occurrence frequency for IMBIM is in the range between 0.9 and 0.925. In this range, the mean optimal value of IMBIM as a management measure for multidimensional problems is 0.912. Stakeholders in PCC projects can use the proposed high occurrence range to assess the quality-safety of construction and make appropriate decisions. [ABSTRACT FROM AUTHOR]

Drawing on the resource-based view, we propose a model to understand the roles of human capital, market and entrepreneurial orientation, absorptive capacity and ways to improve performance with an effective innovation strategy for hospitality development. We combine the Fuzzy Delphi Method, Decision-Making Trial and Evaluation Laboratory and analytic network process to demonstrate the interactions and relations among critical criteria by using data from 20 Taiwanese restaurant entrepreneurs obtained in 2015–2017. The positive effects of human capital, market orientation, entrepreneurial orientation and absorptive capacity on innovation performance are confirmed. These findings advance resource-based scholarship and highlight the value of understanding the relationship between a restaurant's tangible and intangible resources for hospitality development. [ABSTRACT FROM AUTHOR]

In order to deeply explore the evolutionary process and characteristics of social stability risk of reservoir resettlement, and improve the scientific nature of government management decisions, Firstly, the risk transmission chain of reservoir resettlement social stability and the risk indicator system including 4 primary indicators and 15 secondary indicators of economy, government management, living environment and social interaction are established from the perspective of risk perception. Then, based on the established risk transmission chain, the causal relationship between risk factors is qualitatively analyzed. Finally, the system dynamics (SD) evolution model of reservoir resettlement social stability risk is constructed, and the ANP is used to determine the basic weight of each index, and the risk evolution simulation is carried out with an example. The results show that with the investment of funds and the implementation of the government' s pacification measures, the risk value of social stability shows a general trend of rapid increase first, then a rapid decrease, and finally tends to be flat. Its specific characteristics are as follows: the risk amount in the first to third years accumulates rapidly, and rises to the peak in a short time. The risk value in the third to sixth years decreases rapidly due to the intervention of various policies, and the risk value gradually tends to be flat in the sixth year, and keep it descending slowly. [ABSTRACT FROM AUTHOR]

The aim of this article is to present a novel framework that integrates the strategic dimensions of sustainability and the ISO 21500 standard to evaluate and select subcontractors for megaprojects. ISO 21500 processes were utilized to develop benefits, opportunities, costs, and risks subnets, whereas triple-bottom line sustainability dimensions were used as strategic criteria. Subsequently, the Analytic Network Process was used to examine the proposed framework for the Qatar Rail megaproject. The proposed framework supports organizations dealing with megaprojects to align their subcontractor selection with ISO 21500 and achieve ecological and social objectives alongside the project's stipulated economic benefits. [ABSTRACT FROM AUTHOR]

Several workplace injuries and fatalities are annually reported in the construction industry, and various efforts have been made to ensure safety. However, the construction industry still has higher casualty rates than other industries, and a preemptive safety management system that considers the safety risk factors at the construction site is deemed a necessity. Therefore, this study proposed a model that can quantitatively evaluate the safety of construction workers. A total of 18 safety risk factors consisting of three groups was derived from disaster-case data through a literature review, and was consulted to experts based on a survey to verify the suitability. Based on the results from the survey, 13 safety risk factors were selected, and the weights for each factor were derived. Moreover, an Analytic Network Process was used to derive the weights. Afterwards, a safety risk scale for each factor was derived based on the utility function from the accident case data provided by Korea Occupational Safety and Health Agency and opinions provided by expert. Finally, a safety assessment index for construction workers was proposed by combining the derived weights and safety risk scales. Accordingly, this study facilitates identifying construction workers with a high probability of suffering accidents in advance. Therefore, this study can contribute to preventing accidents at the construction site by supporting customized safety management for workers in hazardous environments. [ABSTRACT FROM AUTHOR]

Manufacturing resources allocation (MRA) is important area, and a significant challenge is encountered when considering high value, customized, complex structure and long lifespan of complex product system (CoPS). The relationship between uncertainty factors (i.e., inputs and outputs) of processes in CoPS's manufacturing, operation and maintenance needs comprehensive trade-offs in the preliminary MRA stage. Meanwhile, the CoPS's MRA schemes are contradictory from a customer's perspective with different emphasis on operating cost related to operation and maintenance stage. These problems are unavailable in traditional expressions for model and objective function. In this paper, a new variant of MRA multi-criteria decision-making (MCDM) model of CoPS (MRA&CoPS) is developed to evaluate MRA schemes with considering CoPS's lifecycle. Meanwhile, considering characteristics of CoPS and customer-involved MRA process, the three-layer criteria cumulative model is established. In the proposed method, intuitionistic fuzzy sets (IFSs) based subjective–objective hybrid fuzzy method is presented to deal with uncertainty of evaluation criteria. The weights of criteria are determined by the proposed intuitionistic fuzzy information entropy (IFIE). The hybrid IFIE-TOPSIS method is proposed to obtain the optimum MRA scheme by ranking results. An example of CoPS's MRA in a case enterprise is addressed to verify the rationality and validity of the proposed method. The results show that the proposed method is more preferable and robust in MCDM problem of MRA&CoPS. [ABSTRACT FROM AUTHOR]

With the aim of addressing the complexity of decision environments, uncertainty of decision information and weight determination of mutual influence between decision makers, a (p,q)-rung interval-valued orthopair fuzzy multi-attribute group decision making algorithm based on weight optimization is proposed. First, in order to improve the ability of decision makers to capture their judgment in a wider space, the concept of a (p,q)-rung interval-valued orthopair fuzzy set is proposed, and its related definition and properties are studied. Second, considering the mutual influence between decision makers and the relationship between attributes, the analytic network process (ANP) and entropy method are employed to determine the subjective and objective weights, respectively. Considering the influence of subjective and objective weights on the combination weights, the deviation degree and dispersion degree of the subjective and objective weights are taken as objective functions, and the optimal solution of the combination weights is iteratively solved by genetic algorithm. Then, based on the (p,q)-rung interval-valued orthopair fuzzy set and weight optimization model, an improved (p,q)-rung interval-valued orthopair fuzzy ELECTRE method is proposed. Finally, in order to verify the accuracy and robustness of the algorithm, the algorithm is applied to the example analysis of investment enterprise evaluation, and the results demonstrate that the algorithm has definite theoretical and application value. [ABSTRACT FROM AUTHOR]

In a recent competitive and challenging market, supply chain management has faced many challenges due to rapid technological changes, new products and variable customer tastes. Therefore, supply chain management seems to require more vigilance and speed leading to the formation of the concept of the agile supply chain. Since supply chain management plays a significant role in food industries and due to the specific nature of the food companies as well as the importance of their supply chain agility, the main purpose of the current study is to evaluate and prioritize the success key factors for agile supply chains in food companies. In this regard, a DANP method is employed as a hybrid decision-making method considering the Fuzzy Decision Making Trial and Evaluation Laboratory (DEMATEL) and Analytic Network Process (ANP). The results reveal that among 17 factors of success for agile supply chains in these companies, employee skill development, utilizing robust scheduling systems in distribution and process integration are the highest priority. [ABSTRACT FROM AUTHOR]

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

Assessing areas prone to flash floods is crucial for effective disaster management and mitigation. This study proposes a framework for mapping flood-prone areas by integrating geographic information system (GIS), remote sensing data, and multi-criteria decision-making (MCDM) techniques. The hybrid MCDM model combines the decision-making trial and evaluation laboratory (DEMATEL) with GIS-based analytic network process (ANP) to evaluate flood vulnerability in Golestan province, Iran. Fourteen criteria related to flood potential, including elevation, slope, aspect, vegetation density, soil moisture, flow direction, river distance, rainfall and runoff, flow time, geomorphology, drainage density, soil type, lithology, and land use, were considered. In areas where official data was lacking, a questionnaire was administered to gather information from 15 specialists, experts, and 20 local managers. The relationships between criteria were analyzed using the DEMATEL method, and their weights were determined using the ANP method. Topography was found to have the greatest impact on flood risk, followed by the type of surface and vegetation cover. Hydrographic, soil and geology, climatic also influence flooding in the region. The study identified the northern and central parts of the study area being at higher risk of flooding compared to the southern part. Based on the flood intensity map, 68 villages (50% of all villages in the Qarasu watershed) with a population of approximately 83,595 were identified as at risk of flooding. The proposed GIS-DANP model provides a valuable tool for flood management and decision-making, aiding in risk reduction and minimizing casualties. [ABSTRACT FROM AUTHOR]

Colombia exhibits a considerable incidence rate of natural disasters because of its location within the intertropical zone, which exposes it to various meteorological and geological phenomena, including the Nevado del Huila volcano. The identification of suitable areas for the installation of temporary shelters is critical for managing these disasters. However, the task of identifying such locations is a complex problem that involves multiple criteria. This study uses a fuzzy systems approach to identify suitable sites for establishing temporary shelters in the Paez municipality during natural disasters, considering the essential criteria determined by experts through pairwise comparisons. The study results indicate that responsiveness is the most significant criterion, followed by area profile. Using these criteria, it identified a specific locality in the Paez municipality as suitable for establishing temporary shelters during natural disasters caused by volcanic phenomena. The findings were compared with those obtained from existing scientific literature and validated by experts in natural disasters. The methodological process described in this study provides a valuable tool for public entities to make informed decisions concerning natural disasters in indigenous territories caused by volcanic phenomena. [ABSTRACT FROM AUTHOR]

Fast tool servo (FTS) is a promising technique for the high-speed diamond turning of micro-structured functional surfaces due to its fast response capacity. However, the inherent actuator non-linearity, the lightly damped vibration mode and the external disturbance of the FTS would degrade its tracking performance severely and thus restrict its machining ability. To overcome this limitation, a band-stop-filter-based repetitive control (BSF-RC) scheme is proposed in this article to improve the operating performance of the FTS. Firstly, the spectra of the FTS tool paths (FTS-TPs) for machining typical micro-structured functional surfaces with the cylindrical coordinate machining method are analyzed in detail. The results reveal that the frequency components concentrate on the tiny neighborhoods of the rotational frequency of the spindle and its harmonic frequencies. Afterwards, the comb-like band-stop filter used by the BSF-RC is elaborately designed via the cascade of three comb-like notch filters to generate a comb-like band-stop loop shape for covering main spectral components of the FTS-TPs. The analytical expression of the comb-like band-stop filter amplitude as well as the stability condition of the closed-loop control system are derived to provide effective criteria for the parameter selection of the BSF-RC. The experimental validation of the developed BSF-RC scheme is conducted on a five-axis ultra-precision lathe equipped with a self-developed FTS via the diamond turning of three typical micro-structured functional surfaces. The experimental results show that good surface qualities with the maximal form error of a few hundred nanometers and the surface roughness of a several nanometers are achieved for all the obtained micro-structured surfaces by using the BSF-RC scheme under a high spindle speed. • A novel repetitive controller is proposed for fast tool servos to fabricate the micro-structured surfaces. • The frequency components of fast tool servo tool paths for the micro-structured surfaces are analyzed. • The design methods and the stability analysis of the proposed repetitive controller are presented. • Three typical micro-structured surfaces are fabricated by fast tool servo diamond turning. • A submicron form error and a nanometric surface roughness are obtained for all the generated surfaces. [ABSTRACT FROM AUTHOR]

The Internet of Medical Things (IoMT) is an emerging technology in the healthcare revolution which provides real-time healthcare information communication and reasonable medical resource allocation. The COVID-19 pandemic has had a significant effect on people's lives and has affected healthcare capacities. It is important for integrated IoMT platform development to overcome the global pandemic challenges. This study proposed the national IoMT platform strategy portfolio decision-making model from the non-financial (technology, organization, environment) and financial perspectives. As a solution to the decision problem, initially, the decision-making trial and evaluation laboratory (DEMATEL) technology were employed to capture the cause-effect relationship based on the perspectives and criteria obtained from the insight of an expert team. The analytic network process (ANP) and pairwise comparisons were then used to determine the weights for the strategy. Simultaneously, this study incorporated IoMT platform resource limitations into the zero–one goal programming (ZOGP) method to obtain an optimal portfolio selection for IoMT platform strategy planning. The results showed that the integrated MCDM method produced reasonable results for selecting the most appropriate IoMT platform strategy portfolio when considering resource constraints such as system installation costs, consultant fees, infrastructure costs, reduction of medical staff demand, and improvement rates for diagnosis efficiency. The decision-making model of the IoMT platform in this study was conclusive and significantly compelling to aid government decision makers in concentrating their efforts on planning IoMT strategies in response to various pandemic and medical resource allocations. [ABSTRACT FROM AUTHOR]

Multiple criteria decision-making methods have been extremely useful for identifying the optimal alternative in complicated decision problems. However, in dynamic decision situations, they often suffer from rank reversal problem (RRP). For minimising the RRP, various improvements in existing methods have emerged in recent times. The proximity-indexed value (PIV) method is one method that promises to minimize the rank reversal problem. However, a detailed investigation of the RRP issue for the PIV method does not exist. In this paper, the PIV method has been taken up for a detailed examination of RRP using a MATLAB simulation-based framework by generating a sample of 10,000 random decision matrices. Seven approaches have been used to detect the existence of rank reversal. It is found that a sizeable prevalence of rank reversal remains in the PIV method. A new, improved PIV (IPIV) method is also proposed in this paper, which has been demonstrated to be effective in reducing the prevalence of rank reversal to almost zero. The effect of varying the number of criteria and the number of alternatives is also evaluated while considering the variation in criteria weights, i.e. equal and unequal criteria weights. Analysis of variance using the concept of blocking has been carried out on the results obtained at a 5% level of significance. The study also identifies more effective approaches from the seven approaches used to detect rank reversal. In addition, the application of the IPIV method is demonstrated in a real-world problem. [ABSTRACT FROM AUTHOR]

The construction industry is increasingly recognized as critical in achieving Sustainable Development Goals. Construction activities and infrastructure have both beneficial and non-beneficial impacts, making infrastructure design a focal point of current research investigating how best to contribute to sustainability as society demands. Although methods exist to assess infrastructures' economic, environmental, and social life cycle, the challenge remains in combining these dimensions into a single holistic indicator to facilitate decision-making. This study applies four decision-making techniques (ANP, TOPSIS, COPRAS, and VIKOR) to evaluate five different design alternatives for a concrete bridge exposed to a coastal environment. The results indicate that concretes containing even small amounts of silica fume perform better over their life cycle than other solutions usually considered to increase durability, such as water/cement ratio reduction or concrete cover increase. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to investigate relationships of urban seismic resilience assessment indicators. Design/methodology/approach: To achieve this aim, construction of the urban seismic resilience assessment indicators system was conducted and 20 indicators covering five dimensions, namely building and lifeline infrastructure, environment, society, economy and institution were identified. Following this, this study used evidence fusion theory and intuitionistic fuzzy sets to process the information from experts then developed the fuzzy total interpretive structure model. Findings: A total of 20 urban seismic resilience assessment indicators are reconstructed into a hierarchical and visual system structure including five levels. Indicators in the bottom level including debris flow risk, landslide risk, earthquake experience and demographic characteristics are fundamental indicators that significantly impact other indicators. Indicators in the top level including open space, gas system and public security are direct indicators influenced more by other indicators. Other indicators are in middle levels. Results of MICMAC analysis visually categorize these indicators into independent indicators, linkage indicators, autonomous indicators and dependent indicators according to driving power and dependence. Originality/value: This paper attempts to explore relationships of urban seismic resilience assessment indicators with the interpretive structural model method. Additionally, Fuzzy total interpretive structure model is developed combined with evidence fusion theory and intuitionistic fuzzy sets, which is the extension of total interpretive structure model. Research results can assist the analytic network process method in assessing urban seismic resilience in future research. [ABSTRACT FROM AUTHOR]

One of the most dangerous natural disasters, which causes massive damage all over the world, is flash floods. Therefore, the assessment of flash floods disasters is considered increasingly urgent and important. The widely used techniques for studying and analyzing the causes and impact of natural hazards are multi-criteria techniques. Several researchers used traditional multi-criteria decision-making techniques in the estimation process of flash floods problems as the analytical hierarchy process, decision making trial and evaluation laboratory and analytic network process. The main disadvantage of these traditional models is the incapability of simulating and reflecting uncertain human thoughts. Since neutrosophic logic has a great ability for simulating human's thoughts and increase the flexibility of expert's preferences in real world problems, we applied it in this study. There are different locations in Egypt that are at a serious risk of flooding, especially in Upper Egypt. Asyut has suffered from frequent flash floods, with some flood events that lead to mortality, damages, and economic losses in the last decades. The intensity of floods in Egypt varies from year to year, according to several climatic and hydrological variables. This study focuses on using a Neutrosophic Decision making trial and evaluation laboratory (N-DEMATEL) technique with remotely sensed data and geographical information system (GIS) for producing a flash floods hazard map. The N-DEMATEL technique is applied to determine the weights of various factors that related to flash flooding, including elevation, slope, topographic wetness index, distance from the stream, flow accumulation, aspect, flow direction, soil, land cover, watershed, curvature, drainage density, total population, population density and precipitation. The obtained weight of selected criteria used then to produce the flood hazard map (FHM) using a raster calculator tool in geographic information system. [ABSTRACT FROM AUTHOR]

This study comprehensively analyzes the optimal hurdle rate, or the Minimum Attractive Rate of Return (MARR), for oil and gas investments in Indonesia's National Oil Company. By incorporating country-specific, industry, and project risk into the calculation of the Weighted Average Cost of Capital (WACC), the study outlines a risk-adjusted methodology to guide investment decisions. The Analytic Network Process (ANP) method and Monte Carlo Simulation employ the lognormal distribution to quantify and analyze risk variables, establishing a project-specific risk premium. The significance of the country risk premium is emphasized, highlighting its role in investment diversification, accurate valuations, strategic decision-making, and effective risk management. The calculated hurdle rate ranges from 10,91% to 15,42%. The study underscores the importance of thorough risk analysis in ensuring sound investment decisions in the global oil and gas industry. It concludes by emphasizing the risks of setting too low a hurdle rate, leading to excessive risk-taking, or too high a hurdle rate, which might preclude potentially profitable investments. [ABSTRACT FROM AUTHOR]

Supply chain mapping is gaining heightened attention due to its vital role in improving supply chain visibility and resilience. Despite its crucial role in uplifting supply chain resilience, the critical elements of supply chain mapping are yet to be determined. The study adopts a twofold approach to identify and prioritize the dimensions and sub‐dimensions of supply chain (SC) mapping. At the first stage, through an extensive review of literature, 43 sub‐dimensions of SC mapping were identified. In the second stage, Gray ‐ DEMATEL‐based Analytic Network Process (GDANP) was employed by taking the input from 25 experts selected from Oil and Gas industry of an emerging market. The findings reveal three major dimensions of SC mapping followed by 15 sub‐dimensions. Among the dimensions, upstream mapping contains the highest priority weights, followed by midstream and downstream mapping. The findings suggest a step‐wise strategy to adopt SC mapping where upstream mapping should be given the first priority. The major contribution of this study is to develop a framework for measuring the extent of SC mapping of a firm using GDANP. [ABSTRACT FROM AUTHOR]

Ratings are the basis for the survival of programmes and the key to commercial television (TV) stations’ operations in Taiwan. Therefore, in the decisionmaking process of drama purchasing, TV stations need an objective and comprehensive selection model owing to the complex criteria and because the drama purchasing decision is crucial to their ratings and operations. From the viewpoint of commercial TV station managers, we proposed a decisionmaking model to select overseas dramas. We first established the criteria for purchasing overseas dramas based on past literature and fuzzy Delphi method (FDM), including American, Korean, Japanese, and Chinese dramas. The case commercial TV station then selected the most suitable Chinese dramas for purchase by conducting empirical research with decision making trial and evaluation laboratory (DEMATEL), analytic network process (ANP), and technique for order preference by similarity to ideal solution (TOPSIS). This model provides an objective, quantitative, and effective way for commercial TV stations to purchase the optimal overseas dramas with academic and practical value and contribution. [ABSTRACT FROM AUTHOR]

Purpose: The Indian micro small and medium scale enterprises (MSMEs) are potential suppliers to the original equipment manufacturers (OEM). The implementation of sustainable supply chain practices (SSCPs) enhances the chances of developing a long-term partnership with these OEMs. Design/methodology/approach: A hybrid framework of analytical network process (ANP) and fuzzy logic (FL) is developed for implementing SSCPs in Indian MSMEs. This model has been validated through a case study. Findings: The study has identified several critical success factors (CSFs) for the implementation of SSCPs in MSMEs. This study has observed that Government regulation is the most important CSF for the implementation of SSCP in Indian MSMEs followed by management support and policy framework. Originality/value: The article presents a mechanism, i.e. an adaptability test that enables the OEM decision-makers to assess the suitability of an MSME for a long-term partnership. [ABSTRACT FROM AUTHOR]

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

Introduction: Executive functions (EFs) are linked to positive outcomes across the lifespan. Yet, methodological challenges have prevented precise understanding of the developmental trajectory of their organization. Methods: We introduce novel methods to address challenges for both measuring and modeling EFs using an accelerated longitudinal design with a large, diverse sample of students in middle childhood (N = 1,286; ages 8 to 14). We used eight adaptive assessments hypothesized to measure three EFs, working memory, context monitoring, and interference resolution. We deployed adaptive assessments to equate EF challenge across ages and a data-driven, network analytic approach to reveal the evolving diversity of EFs while simultaneously accounting for their unity. Results and discussion: Using this methodological paradigm shift brought new precision and clarity to the development of these EFs, showing these eight tasks are organized into three stable components by age 10, but refinement of composition of these components continues through at least age 14. [ABSTRACT FROM AUTHOR]

Chinese firms are actively investing in movie ticketing Apps, but there is no unified model for how to evaluate such investments, which can hinder investment decision-making into such ticketing Apps. Currently, there is limited research on the criteria for investors to select the best Chinese movie ticketing Apps. To fill this gap, the present study proposes a three-stage evaluation model for investments in these specific Apps. First, it constructs a new hierarchy for movie ticketing App networks via the Modified Delphi Method (MDM), which consists of 5 criteria and 20 sub-criteria. Second, we apply the Analytic Network Process (ANP) to calculate the weight of the criteria and sub-criteria, finding that information is the most important, followed by system, trust, service, and word-of-mouth (WOM) in that order. Finally, three movie ticketing Apps are utilized as alternatives, and the best alternative is selected by Techniques for Order Preference Similarity Ideal Solution (TOPSIS) to verify the model's feasibility. The results herein offer theoretical and practical insights for the development and promotion of movie ticketing Apps and provide a reference for investors to formulate relevant financing strategies. [ABSTRACT FROM AUTHOR]

Purpose: The aims of this paper is to establish an appropriate physical-change-based renewal (PCBR) projects selection mechanism capable of selecting the combination of the PCBR projects that can make up an integrated urban renewal program in high-density cities. Design/methodology/approach: The research design follows a sequential integrated methodology that combines the calculation algorithms of Fuzzy Analytic Network Process (Fuzzy-ANP) with Zero-One Goal Programming (ZOGP) to support decisions for the selection of PCBR projects. In the first phase, general criteria for assessing the sustainability performance of PCBR projects were collected from relevant literature. In the second phase, the Fuzzy-ANP was used to identify the priority weights of the candidate projects through clarifying the interdependent degree between the criteria and candidate projects. Finally, ZOGP method was selected as a predetermined number of PCBR projects among candidate projects. Findings: The feasibility and effectiveness of this hybrid approach is then verified in a case study of Yuzhong District, Chongqing in China. The results of this study indicate that the integrated method is capable of directing the decision maker toward the best compromising solution of PCBR program that can achieve the maximization of sustainable benefits and allocate limited resources most efficiently. Originality/value: The novelty of this paper consists in combining the algorithms of the Fuzzy-ANP method with those of the ZOGP model that serves as an effective analysis tool to address practical decision problems. This is the first hybrid algorithms to make PCBR projects selection decision that reach the maximization of the sustainable benefits, both in economic and socio-environmental terms. [ABSTRACT FROM AUTHOR]

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

The underutilization of e-learning among university lecturers is an important issue that needs to be resolved. This study aimed to formulate an e-learning postadoption model for Malaysian universities. Data were collected using self-administered questionnaires involving 36 e-learning experts who from lecturers in public and private universities in Malaysia. The data collected was then analyzed using the extent analysis method proposed by Chang (European Journal of Operational Research,95(3), 649–655, 1996) to examine the weights and rankings of the factors and subfactors. This study showed that for e-learning postadoption, the most important factor is institution service quality, followed by system quality, content quality, instructors' characteristics, and learners' characteristics. This study extends the information systems success model into the e-learning postadoption context. In particular, this study offered insights concerning the dependencies among the factors in the model within the Malaysian university context. The findings are useful for the long-range strategic management of university administrators, and the model can be adopted as a reference to form a rating system to analyze e-learning postadoption. University administrators can analyze critical factors that increase e-learning's post adoption and lead to more efficient resource allocation and management of e-learning. [ABSTRACT FROM AUTHOR]

The protection of the ecological landscape and the development of ecological resources are vital in the development of the global green economy, Their win‐win coordinated development is influenced by factors such as nature, culture, and economy, and more attention should be placed on tourist perception and sustainable resource development. Previous studies have mainly focused on a single perspective and failed to comprehensively consider the coordinated relationship between ecological landscape and ecological resources. This research combined push‐and‐pull theory and applied empirical analysis to verify the structure of tourists' perceptions and the law of sustainable development of resources related to the development of ecological landscape in the new era. It extracted and analyzed 34 influencing factors and applied the analytic network process (ANP) to analyze each factor's weights, to propose an evaluation system for eco‐tourism sustainability development that can help the construction of ecological landscape in the future. The reconstruction and further development of eco‐tourism in the new era is reflected in the ideological and practical dimensions; from single‐perspective linear thinking to multi‐dimensional integrated governance; from conflict between resources conservation and development to collaboration; from isolated management to building a community with a shared future; and showing the transformation and innovation at multiple levels of individual, community, government and national governance. [ABSTRACT FROM AUTHOR]

Recently, developing strategies for sustainable development (SD) in the hotel industry has been seen globally as a crucial issue. Numerous management systems can assist the hotel industry in creating sustainable performance, such as Total Quality Management (TQM) which is well-reputed in the industry. As such, selecting TQM under an evolving hotel industry environment is seen as an important decision from a strategic perspective given it constitutes contradictory practices, thereby making it a multi-criteria decision-making (MCDM) issue. In achieving this aim, a Decision-Making Trial and Evaluation Laboratory (DEMATEL) approach was adopted in determining the inter-relationships between the primary practices and sub-practices in addition to applying the Analytic Network Process (ANP) for examining the weights of primary practices and sub-practices. In other words, this study aims to provide innovative insight to researchers and practitioners to examine the TQM optimal practices to be implemented incrementally in phases within the hotel industry environment. [ABSTRACT FROM AUTHOR]

In the modern world in various spheres of activity, the number of problems that need multi-criteria decision-making (MCDM) is constantly increasing. Researchers and experts offer a number of approaches to MCDM process in such tasks; in particular, most of them are based on expert methods. However, in practice, these methods require significant intellectual effort of experts and organizational and technical workload during the expert survey, and also usually take a long time. At the same time, it is not always possible for experts to use certain characteristics of alternatives, which also carries the risk of making decisions based on unfounded expert opinions. Therefore, such methods and tools should be clear and informative and at the same time easy to use to ensure the efficiency and effectiveness of their use. We offer a graph-based approach to expert decision-making and information visualization processes that meets these requirements and can significantly improve the efficiency of decision-making in multi-criteria selection tasks.

The eucalyptus oil factory (PMKP) Sukun Ponorogo is an industry with complex supply chain activities, starting from the raw material’s procurement, production processes, distribution, and reverse logistics. Some of these activities may result in environmental problems. Therefore, measurement of its supply chain management (SCM) performance related to environmental conditions is critical. The green supply chain management (GSCM) concept can help the company to assess the supply chain's performance conditions that could harm the environment. This study aimed to assess the current SCM and measure its performance, as well as to evaluate the potential implementation on GSCM in the PMKP Sukun Ponorogo. The analytical network process (ANP) was used in this study, consisting of 36 key performance indicators (KPI) from five categories of plan, source, deliver, make, and return. The study results show that all KPIs from the responsiveness dimension in the deliver category have the lowest weight, thus require priority for improvement. The results of the scoring system using the objective matrix (OMAX) method indicated two KPIs were in the red category (or need improvement), including on-time delivery of raw materials to production site and the rejection rate of raw materials. This study suggested to improve the estimated delivery time for avoiding any delays during the production process. This improvement may support the company to continuously offer on-time production process and product’s distribution.

AbstractEarthquake risk in urban areas has recently taken quite a lot of attention. Risk is a cross-cutting combination of vulnerability and hazard. Abbottabad district, a rapidly growing district, is an earthquake-prone area in the north of Pakistan. In 2005, the region suffered enormous casualties due to a significant earthquake (Mw = 7.6). The various regional behaviours, including social, physical, and economic behaviours, are causing a vulnerable situation. At the same time, the high seismicity has the potential to invite earthquake hazard, thus ensuing a possible risk situation in the region. Consequently, this study proposes an integrated approach involving an artificial neural network (ANN), convolutional neural network (CNN), and analytic network process (ANP) to carry out the seismic risk analysis of the Abbottabad district. The proposed two integrated frameworks are ANP-ANN and ANP-CNN. This kind of methodology has not been applied before in this area. The geographic information system is used to formulate a broad range of contributing factors depicting the hazard and vulnerability of the area and potentially contributing to the seismic risk. A total of 16 contributing factors are chosen for this study. The selected factors are weighed using the ANP, and training and testing databases are generated to train and test the models, thus producing the area’s earthquake risk maps (ERMs). As per the ERMs, the northwestern regions and the borderline regions from the southeast, covering an area of 30%, possess a greater earthquake risk. The rest of the 70% of the area has less risk exposure. The AUC values of ANN and CNN are found to be 0.843 and 0.878, respectively, exhibiting a good performance by the models. The study paves the way for the concerned authorities to match and redefine their policies for developing, expanding, and managing the region’s structural, health care, and disaster management facilities.

Prediction of scour depth around bridge piers during flood events has been and continues to be regarded as a paramount concern for researchers of local scour, and many empirical formulas have been proposed. Because of the multiplicity and variability of these formulas, it remains extremely delicate to choose the correct formula among the many available. This study aims to develop a new framework to compare the different formulas currently used for the evaluation of local scour. For this purpose, 18 distinctly different formulas are selected and then evaluated using a large set of field-measured scour data. The rating is pronounced along three main streambed granulometric distributions. The validation process is performed using the Analytical Network Process approach (ANP), in which the already available conventional weights are re-evaluated and updated using various analyses, notably in terms of statistics, sensitivity, and correlation. The validation and comparison results of these 18 scour formulas reveal that the efficiency of a given particular formula depends on the type of stream soil studied. Furthermore, the scour formulas that include parameters having a geometrical dimension provide better performances. HIGHLIGHTS Comparison of a wide selection of scour calculation formulas.; Assessment of scour variation as a function of streambed soil class.; Application of Multi-Criteria Decision Support for local scour.; Investigating the variation of parameters influencing scour.; Proposal of a new hybrid method of Analytic Network Process coupled with sensitivity and correlation analysis.;

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

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

Over the years, the AHP has been used either as part of a multi-method approach (i.e., the AHP is preceded by another MCDM method) or as an integrated method (i.e., the AHP is combined with another method to constitute a new hybrid methodology). ANP development Still, while the AHP has been improved and its use has become more sophisticated over the years, a major development has been the creation of the Analytic Network Process (ANP) which is a generalization of the AHP (Saaty, [30], [31]). Three Developments of the Analytic Hierarchy Process: Calibrated Fuzzy AHP, AHP, AHPSort and GAHPO. We are proud to publish this ANOR special issue on the topic of the Analytic Hierarchy Process (AHP) and Analytic Network Process (ANP). [Extracted from the article]

A globally aging population results in the long-term care of people with chronic illnesses, affecting the living quality of the elderly. Integrating smart technology and long-term care services will enhance and maximize healthcare quality, while planning a smart long-term care information strategy could satisfy the variety of care demands regarding hospitals, home-care institutions, and communities. The evaluation of a smart long-term care information strategy is necessary to develop smart long-term care technology. This study applies a hybrid Multi-Criteria Decision-Making (MCDM) method, which uses the Decision-Making Trial and Evaluation Laboratory (DEMATEL) integrated with the Analytic Network Process (ANP) for ranking and priority of a smart long-term care information strategy. In addition, this study considers the various resource constraints (budget, network platform cost, training time, labor cost-saving ratio, and information transmission efficiency) into the Zero–one Goal Programming (ZOGP) model to capture the optimal smart long-term care information strategy portfolios. The results of this study indicate that a hybrid MCDM decision model can provide decision-makers with the optimal service platform selection for a smart long-term care information strategy that can maximize information service benefits and allocate constrained resources most efficiently. [ABSTRACT FROM AUTHOR]

This study aimed to identify the factors expected to drive value-for-money (VfM) when using public-private partnerships (PPPs) for affordable housing in Indonesia. Utilising economy, efficiency and effectiveness as the VfM criteria, the study employed the analytic network process to determine the relative importance of 13 factors compiled from the literature review. The factors were then grouped into five clusters: private sector capacity, transparent and competitive procurement, risk and reward allocation, public sector capacity and the nature of the long-term contract. The data were gathered through a survey of 20 experts with hands-on experience in Indonesia's PPPs. Effectiveness was identified as the most critical VfM criterion, implying that bringing other VfM aspects into public decisions is indefensible if the outcome, providing low-income customers with suitable housing at rents they can afford, is not achieved. The justified scope and size of the project, clear output-based specifications, quality project planning and preparation and long-term service delivery emerged as the most critical factors enhancing VfM, each with a different focus on a specific VfM criterion based on local weights. At the cluster level, risk and reward allocation ranked the highest. This study also acknowledges several limitations and provides directions for future research. [ABSTRACT FROM AUTHOR]

Ecotourism plays a critical strategic role in regional development. In many remote communities, ecotourism is the main contributing factor in their economic growth. The role of ecotourism development in the sustainability of the local economy is widely known. However, the local communities' role in the development of the industry has been neglected. The presented study, therefore, examines the importance of community engagement as the missing link in the successful development of the ecotourism industry. This research uses strengths, weaknesses, opportunities, and threats methodology and analytic network process technique to determine the importance of the strategies directly related to the local community in comparison to other ecotourism development strategies. Arasbaran Biosphere Reserve, in northwest Iran, was used as a case study. A decision-making model containing 20 clusters, 69 sub-factors, and seven alternatives were developed in SuperDecisions software. The results showed in overall, the strategies directly related to the local community are more effective than all the other strategies. There were significant differences between the local community's point of view and local authorities on the importance of community engagement. The results also indicated lack of trust and willingness of local authorities had been the main contributions in unsuccessful community engagement programs in the region. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to develop the maqasid index (MI) for Islamic corporate social responsibility (CSR), namely, Dana Abadi Umat (DAU) (Ummah's Endowment Fund) or MI-DAU in Indonesia. Design/methodology/approach: Modeling and weighting are based on Delphi and analytic network process (ANP) methods, called Delphi–ANP additive weighting. The Delphi method was applied to design and validate the factors of the MI-DAU model, and the ANP method was applied to generate and validate weights for these factors. Finally, the MI-DAU is calculated, based on the planned budget and actual allocation of DAU returns, called the maslahah fund, using additive weighting. Findings: Delphi and ANP show significant and robust results. The priority order and weights of maqasid Shariah are safeguard the faith (0.32), safeguard the intellect (0.219), safeguard the life (0.204), safeguard the wealth (0.171) and safeguard the lineage (0.104). Meanwhile, the priority order and weights of the main activities are education (0.190), Ummah's economy (0.167), Hajj service (0.155), Da'wah (0.124), health care (0.118), social-religious (0.097), worship facilities (0.085) and disaster emergency response (0.065). Finally, the results of MI-DAU show a high index in 2019 and 2020 of 71.89 and 69.51, respectively, generated from allocation ratio of 90.63% and 85.98%, respectively. Research limitations/implications: Maqasid Shariah used in this study follows Al-Ghazali, where it could also follow maqasid Shariah of Abu Zahrah or Al-Najjar. Moreover, the MI-DAU score uses additive calculations, where it can also use Pentagon calculation. Practical implications: The improved framework and method used to design MI-DAU in this study could be applied to design more scientific MI for other Islamic financial institutions. Originality/value: The novelty of this study is in the improved method used to design the MI model, including its factors, using Delphi, and to assign weights of all factors using ANP, where both provide validation for more robust MI model. [ABSTRACT FROM AUTHOR]

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