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This paper presents an innovative approach for supplier selection (SS) within the Tunisian dairy industry, with a specific focus on sustainability and resilience. The proposed method is a hybrid model that integrates multi-criteria decision-making (MCDM) with fuzzy logic. Initially, twelve distinct criteria are identified, categorized into social, environmental, economic, and resilience indexes through a combination of literature review and expert input. To establish the importance of these criteria, a fuzzy analytic hierarchy process (FAHP) is employed to calculate their weights. These weights are then integrated into a new method called fuzzy multi-attribute border approximation area comparison (FMABAC) to rank the suppliers. The methodology aims to provide decision-makers with a more intuitive means of expressing their preferences and evaluating supplier criteria, ultimately identifying the most effective dairy farmers. The research concludes by evaluating the results through two sensitivity analyses: one involving varying criteria weights and the other involving a comparative assessment with alternative fuzzy MCDM techniques. [ABSTRACT FROM AUTHOR]

The disassembly of end-of-life (EoL) products is of high concern in sustainability research. It is important to obtain reasonable disassembly depth during the disassembly process. However, the overall safety of the disassembly process is not considered during the disassembly depth optimization process, which leads to an inability to accurately obtain a reasonable disassembly depth. Considering this, a multi-objective disassembly depth optimization method for EoL smartphones considering the overall safety of the disassembly process is proposed to accurately determine a reasonable disassembly depth in this study. The feasible disassembly depth for EoL smartphones is first determined. The reasonable disassembly process for EoL smartphones is then established. A multi-objective function for disassembly depth optimization for EoL smartphones is established based on the disassembly profit per unit time, the disassembly energy consumption per unit time and the overall safety rate of the disassembly process. In order to increase solution accuracy and avoid local optimization, an improved teaching–learning-based optimization algorithm (ITLBO) is proposed. The overall safety of the disassembly process, disassembly time, disassembly energy consumption and disassembly profit are used as the criteria for the fuzzy analytic hierarchy process (AHP) to evaluate the disassembly depth solution. A case of the 'Xiaomi 4' smartphone is used to verify the applicability of the proposed method. The results show that the searchability of the non-inferior solution and the optimal solution of the proposed method are improved. The convergence speeds of the ITLBO algorithm are 50.00%, 33.33% and 30.43% higher than those of the TLBO algorithm, and the optimal solution values of the ITLBO algorithm are 3.91%, 5.10% and 3.45% higher than those of the TLBO algorithm in three experiments of single objective optimization. [ABSTRACT FROM AUTHOR]

China has become more aware of the negative environmental impact caused by its economic expansion and fast-paced development. Therefore, the country mainly focuses on sustainable development and green finance. To evaluate the environmental, social, and governance (ESG) factors and policy options for green finance investment decisions in China, the fuzzy analytical hierarchy process (AHP) and fuzzy decision-making trial and evaluation laboratory (DEMATEL) techniques are employed. The fuzzy AHP method identifies and analyzes the most significant ESG factors and sub-sub-factors to comprehensively understand sustainable investment in China. Furthermore, this study uses the fuzzy DEMATEL method to prioritize the main policy options for advancing sustainable development and green finance investment decisions in China. The fuzzy AHP method shows that the environmental factor (ESG1) is the most significant factor for green finance investment decisions in China, followed by the governance (ESG3) and social factors (ESG2). The fuzzy DEMATEL method results revealed that supporting green finance innovation and development (P1) is the highest priority, followed by encouraging social responsibility and community engagement (P4) and developing and enforcing environmental regulations (P2). The study's findings will significantly benefit investors and decision-makers who wish to promote sustainable development and make decisions regarding green financing. The study recommends that investors and policy makers concentrate their resources and efforts on the most crucial ESG factors and policies to build sustainability and resilience in the country. [ABSTRACT FROM AUTHOR]

Storage technology selection is a very important design decision that greatly affects the future performance of a warehouse; for example, it greatly affects its costs. In making this decision, the designer is faced with a complex issue. It is necessary to select the appropriate option from a wider set of available technologies, taking into account numerous influencing factors. In design practice, solving this problem is primarily based on the experience of designers and the recommendations of manufacturers of these technologies. In the academic literature, this problem has not been properly posed and solved, so there are no papers that comprehensively address this complex design problem. The main goal of this paper is to fill that gap. The presented approach consists of two basic stages. In the first stage, starting from the definition of the project task, potential technologies are generated and critical factors are considered, in order to arrive at a set of acceptable technologies. In the second stage, these technologies are ranked, and a basis for decision making is created. This stage is based on multi-criteria decision making: the Fuzzy Analytic Hierarchy Process (FAHP) method is used to determine the weights of the criteria, and the Weighted Aggregated Sum Product Assessment (WASPAS) method is used to obtain the rankings. The application of the defined approach is tested on real assignments (distribution warehouse, production warehouse, and holding warehouse) and is proven to be applicable to solving these types of problems. The results obtained for the three tested examples prove the suitability of the application of the proposed approach in terms of the aspects of both the quality of the solution and the speed of obtaining it. Considering the practical application of the suggested and filling the recognized literature gap, evident contributions are achieved. [ABSTRACT FROM AUTHOR]

The current global economic status quo is widely seen as unsustainable in the food sector. The field of sustainability science is still rather fragmented, covering a wide range of techniques and issues, despite the large number of publications in this area. Due to population growth, the food supply chain (FSC) and farmers have to produce more food. The UN estimates that one-third of edible food is wasted, producing greenhouse gases. A balance must be struck between company operations and social, environmental, and economic activities for sustainable development of the FSC. To assist FSC organizations in managing sustainable advancement, this study created a methodology for the assessment of sustainable performance. We provide a sustainable assessment system using a fuzzy analytic hierarchy process, fuzzy VIKOR, and fuzzy TOPSIS. Our research framework evaluated the sustainability of three cooperative-society-run Indian dairy firms. Our study gives environmental criteria the highest weight (0.33) and social criteria the lowest (0.16), with economic reasons (0.306) and business operations (0.204) falling in the middle. Supply chain costs, on average, are given the highest weight, and capacity utilization, the lowest weight. Three dairy industries are ranked (DPI3, DPI1, and DPI2) based on sustainable performance. By modifying the maximum set utility value and validating VIKOR results with TOPSIS, we have checked the robustness of this performance assessment tool. This research aids dairy businesses in achieving several Sustainable Development Goals, including sustainable production and consumption, through the regular assessment of their sustainable performance. [ABSTRACT FROM AUTHOR]

The optimal management of personal resources impacts everyone's quality of life. An investment in graduate education is a sustainable opportunity for improved outcomes in human life, including cognition, behavior, life opportunities, salary, and career. Advanced technology dramatically reduces the risk of personal resources in graduate program admission recommendations that depend on multiple individual needs and preferences. In the digital age, a dynamic recommender system enhances the suitably effective solution for students' university selections. This study focused on designing, developing, and testing a recommender system for graduate admission using a dynamic multi-criteria AHP and fuzzy AHP approach. The explicit multi-criteria recommender system was a platform as a service (PaaS) web application created to aid in graduate admissions management and decision-making. The design proposed that the bit representation store a dynamic explicit multi-criteria data structure. The recommendations adopting dynamic multi-criteria were validated by comparing them to the programs to which the students were actually admitted and enrolled. They individually ranked the evaluation outcomes of dynamic explicit multi-criteria and alternative preferences to provide graduate admission recommendations. Eighty graduate students in information technology evaluated the recommender system. Using top-1, top-2, and F1-score accuracy, the effective system accuracy performance on the dynamic multi-criteria recommender system was evaluated using AHP and fuzzy AHP approaches. The fuzzy AHP demonstrated marginally greater practical accuracy than the AHP method. [ABSTRACT FROM AUTHOR]

The acceleration of coastal processes is manifested in the form of coastal erosion, average sea level rise, drastic changes in coastlines, and more turbulent ocean waters. In this study, the coasts of Kerala and Tamil Nadu, India, were selected to identify the effects of increasing coastal processes. Therefore, it is necessary to identify and map vulnerable areas by taking into account the key parameters, such as topographical and socio-economic factors, to relate to coastal processes. The fuzzy Analytical Hierarchy Process (AHP) method was employed to identify the most vulnerable zones. The key findings revealed that about 14% and 2% of the coast of Tamil Nadu and Kerala, respectively, are classified under the physically highly vulnerable category. Similarly, ~17% and ~30% of coastal Tamil Nadu and Kerala, respectively, are highly socially vulnerable. The overall vulnerability assessment showed that 7–8% of both coastal areas were highly vulnerable. We concluded that the Thiruvallur, Chennai, Kanchipuram, Cuddalore, and Nagapattinam coasts on the east coast and the Malappuram, Thrissur, Ernakulam, Alappuzha, and Kollam coasts on the west coast were very highly vulnerable to coastal processes. Identifying vulnerable zones helps to better understand the impacts of rapid coastal processes and, with this prior estimation, the policymakers can take necessary actions to mitigate the irreversible impacts of coastal processes. [ABSTRACT FROM AUTHOR]

Digital technologies like blockchain, the Internet of Things, and smart warehouses have been developed due to the fourth industrial revolution, or "Industry 4.0." Any business' supply chain includes several stakeholders, including manufacturers, distributors, suppliers, and final consumers. The demand for firms to utilize these technologies to gain competitive advantages has intensified in the modern world due to rising worldwide rivalry. Additionally, the adoption of blockchain technology, in particular, can have a huge impact on a company's reverse logistics, accelerating processes by decentralizing, tracking, and overseeing the delivery of items to final consumers. The goal of this study is to pinpoint those significant obstacles because several must be overcome for blockchain technology to be successfully implemented in reverse logistics. This study identified 16 impediments to the adoption of blockchain technology after a thorough analysis of the literature and expert opinion. The fuzzy AHP approach was used in this study to rank those barriers as this approach helps to address the complexity and uncertainty associated with decision-making in supply chain management and provides a more robust and reliable ranking of the barriers to blockchain adoption. A case study of Pakistan's e-commerce industry was carried out. The results show that the high installation cost, stakeholders' resistance to the blockchain, and the lack of top-management support are the critical success factors in blockchain adoption. From an industrial perspective, the study highlights the need for businesses to carefully evaluate the potential benefits and costs of adopting blockchain technology. It also underscores the importance of addressing the barriers to adoption to ensure successful implementation. By doing so, businesses can enhance their supply chain management and improve their overall competitiveness. [ABSTRACT FROM AUTHOR]

China has become a global leader in green infrastructure finance, investing heavily in renewable energy, sustainable transportation, and green buildings. However, there are multiple risks and challenges that impede the development of green infrastructure finance. Thus, this study analyzes and prioritizes the risks associated with green infrastructure finance in China and proposes policy plans to mitigate these risks. A Fuzzy analytical hierarchy process (AHP) is used to identify the main risks associated with green infrastructure finance. The main risks are further decomposed into sub-risks. After, the Fuzzy VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method is used to prioritize the key policy plans to mitigate risks and sub-risks. The results of Fuzzy AHP show that policy and regulations are the most significant risk associated with green infrastructure finance in China, followed by financial risks, and technical risks. The results of Fuzzy VIKOR reveal that increasing the availability of financing options is the most crucial policy plan to mitigate the risks and sub-risks for green infrastructure finance. The developed standardized technical guidelines and procedures and a legal and regulatory framework are ranked second and third are the most effective and feasible policy plans. [ABSTRACT FROM AUTHOR]

The evaluation and prioritization of environmental, social, and governance (ESG) factors are critical for green finance investment strategies. However, ESG criteria are complex and varied concepts that call for a systematic and reliable ranking system to handle ambiguity and uncertainty in decision-makers' preferences and assessments. The objective of this study was to examine and prioritize environmental, social, and governance (ESG) factors and investment strategies for the development of green finance. Although ESG criteria have gained importance recently, some research gaps still need to be filled. For this purpose, evaluating ESG criteria and integrating them with green finance investment strategies is imperative. This study employed the fuzzy analytical hierarchy process (AHP) method to assess and rank ESG criteria and sub-criteria and the fuzzy weighted aggregated sum product assessment (WASPAS) method to assess and prioritize the key investment strategies for the development of green finance. According to the fuzzy AHP findings, governance and social factors are secondary to environmental considerations in the creation of green finance. Green bonds, ESG integration, and renewable energy funds are essential to green finance methods, according to the fuzzy WASPAS data. This research provides information on creating sustainable and ethical investment strategies for green finance and successfully including ESG factors in investment decision-making processes. [ABSTRACT FROM AUTHOR]

Globalization, the growth of the world population, urbanization and the growth of the volume of the flow of goods have generated numerous problems in city logistics (CL). The opportunity to solve them is found in various fields by defining and implementing initiatives, concepts, measures, modern technologies and scenarios. The efficiency of the solution largely depends on the efficiency of logistics centers, which is one of the key subsystems of CL. The requirements for the reliable delivery of goods to customers in urban areas are conditioned by the efficiency their order fulfillment in logistics centers. Therefore, optimizing material handling (MH) time and costs aimed at reducing delivery errors, minimizing damage to goods and increasing customer service efficiency is directly conditioned by the automation of MH in logistics centers. Accordingly, this paper aims to rank and select smart MH solutions in logistics centers where deliveries are prepared for the supply of the city area. This paper proposes four smart solutions for a real company, and fourteen criteria are selected for the evaluation. A new hybrid Multi-Criteria Decision-Making model that combines the Fuzzy Analytic Hierarchy Process method, used to determine the criteria weights, and the Fuzzy COmprehensive distance-Based RAnking (FCOBRA) method, used to rank the alternatives, is proposed. The application of the model shows that the best alternative is the implementation of an autonomous forklift, which can greatly automate logistics activities and reduce the rate of delivery errors. The main contributions of this research are the definition of smart solutions, a framework for their evaluation and a new model for their ranking. [ABSTRACT FROM AUTHOR]

The integration of smart city technologies into waste management is a challenging field for decision makers due to its multivariate, multi-limiting, and multi-stakeholder structure, despite its contribution to the ecological and economic sustainability understanding of cities. The success of smart sustainable waste management strategies depends on many environmental, technical, economic, and social variables, and many stakeholders are involved in these processes. Using fuzzy multi-criteria decision-making (MCDM) methods helps decision makers determine effective, affordable, and acceptable smart waste management strategies. Although MCDM methods are widely used in various environmental engineering applications, the determination of smart sustainable waste management strategies using these methods has not yet received enough attention in the literature. This study aims to contribute to this gap in the literature by evaluating four different smart waste management strategies using a hybrid fuzzy MCDM method. The performance of the proposed strategy alternatives according to fifteen sub-criteria (under four main criteria selected from the literature) was evaluated using a combined application of fuzzy analytic hierarchy process (fuzzy AHP) and fuzzy technique for order preference by similarity to obtain the ideal solution (fuzzy TOPSIS). For this evaluation, the subjective opinions of ten different experts working in academia, in the private sector, or in the public sector were obtained using prepared questionnaires. As a result, the sub-criteria of fewer atmospheric emissions (0.42), operational feasibility (0.64), initial investment costs (0.56), and increased awareness of sustainable cities (0.53) had the highest weight values in their main criteria groups. The performance ranking of the alternatives according to the closeness coefficient (CCi) values was obtained as A2 (0.458) > A3 (0.453) > A4 (0.452) > A1 (0.440), with A3 being slightly ahead of A4 due only to a 0.001 higher CCi value. To test the reliability and stability of the obtained performance ranking results, a sensitivity analysis was also performed using eighteen different scenarios, in which the weights of the different sub-criteria were increased by 25% or decreased by 50%, or they were assumed to be 1 and 0, or all sub-criteria in the same group had equal weight values. Since the performance ranking of the alternatives did not change, the ranking obtained at the beginning was found to be robust against the sub-criterion weight changes. [ABSTRACT FROM AUTHOR]

Technology is advancing at a very rapid pace, and it helps the user in predicting things, taking the right decisions, making life less difficult and eventually increasing the profitability of their business. Due to the increasing global population, changing climatic conditions, and other natural factors predominating in nature, agriculture practice is becoming less predictable and as a result, farmers' confidence is being lost, poverty and food insecurity are rising, and other issues are becoming more prevalent. In addition, it affects the sustainability of the food supply chain. So, there is a critical need for agriculture to adopt Industry 4.0 technologies. Here, we want to select a suitable technology acceptance model which comprehensively and robustly defines all the aspects of technology adoption factors in agriculture. From the different adoption theories, we choose one theory that fits our criteria very accurately; for this, we use a hybrid MCDM approach. We utilised fuzzy AHP and fuzzy VIKOR to make the selection logically and systematically correct. Three experts are employed in the study. Fuzzy AHP helps to find the weightage of criteria used by the fuzzy VIKOR technique in ranking the theories. The results showed that the UTAUT ranking comes number one after applying all the suitable criteria and alternatives, and it is the most accurate theory for analysing the adoption of Industry 4.0 technologies in agriculture. This article offers readers a methodical approach for choosing a technology adoption paradigm. The hypothesis that best fits a person's criteria can be determined by comparing them to potential alternatives. [ABSTRACT FROM AUTHOR]

As the volume and scale of urban expressways continue to increase, renewal remains a concern for urban development. The renewal and decision-making of an urban expressway need to be endowed with new concepts to adapt to the rapid development of cities. Nevertheless, in addition to considering road factors such as facility conditions, driving conditions, and environmental protection, the existing evaluation system lacks comprehensive consideration of factors that improve resilience and adapt to future urban development, and it lacks a quantifiable general update evaluation system. Thus, the establishment of a comprehensive renewal indicator system and a mixed evaluation framework is a challenge. This study proposes an evaluation framework of expressway renewal indicators that integrates the three dimensions of macro, meso, and micro based on the fuzzy Delphi method, the fuzzy AHP method, and the TOPSIS method. A q-rung orthopair fuzzy linguistic set was used to handle expert uncertainty information in the process of conducting fuzzy evaluations. The indicators were refined into general and quantifiable evaluation indicators to improve their versatility. Moreover, the renewal value of expressways was measured and calculated using the TOPSIS method, and four renewal intervals were divided according to the calculation results. As a result, 28 renewal indicators were screened out, and the five factors with the greatest impact on renewal were the demand for transport development, the renewal of facility and service functions, the upgrading of institutional resilience, structural renewal, and economic development. The model was applied to eight expressways in Shanghai to calculate the renewal degree value and divide the renewal status. The model could identify the renewal needs of each road to guide the renewal decision. This study proposes an evaluation model to measure urban expressway renewal studies and provides a reference for urban renewal in the area of sustainable development [ABSTRACT FROM AUTHOR]

Green finance (GF) is a vital strategy implemented by China to minimize carbon emissions to achieve targets of carbon peak and carbon neutrality. Thus, the objective of this study is to reduce carbon emissions by developing green finance practices in China. This study identifies, evaluates, and ranks the factors and sub-factors of green finance because it is the core issue for sustainable development. In this regard, this study utilizes the Delphi and fuzzy Analytical Hierarchy Process (FAHP) method to analyze the main factors and sub-factors of green finance. The Delphi method finalizes the 6 factors and 26 sub-factors after a thorough investigation. The FAHP method was used to assess and rank the identified factors and sub-factors of green finance. The findings show that the political (POF) is the most crucial factor of green finance in the Chinese economy. The economic (ECF) and environmental (ENF) factors are ranked second and third important factors. The further results of the FAHP reveal that ecological and political identification (POF1), political stability (POF3), and climate commitments (POF2) are the top-ranked sub-factors of green finance. The results specify that green finance development is a very crucial strategy to minimize carbon emissions. [ABSTRACT FROM AUTHOR]

In the present era, against the background of normalized measures of epidemic prevention and control, a multi-function intelligent robot that can completely replace human beings in disinfection and epidemic prevention work needs to be designed in order to contain the spread of viruses at the source, to efficiently and conveniently serve the controlled regions, and to meet the needs of the current context. Existing disinfection robot designs only address the problem of disinfection; there is no disinfection robot that can achieve full-domain and full-space disinfection (including stairs), as well as having multiple epidemic prevention functions. The fuzzy QFD tool and the ARIZ algorithm were used here to solve the problems related to disinfection robots. By using fuzzy QFD as the research framework and combining it with fuzzy AHP to calculate the weight of demand for the disinfection and epidemic prevention robot, the authors further translated the demand into the technical and part characterization of the robot. The conflicts in the fuzzy QFD model were solved using the ARIZ algorithm. Finally, based on the solving principle of the ARIZ algorithm and the qualitative and quantitative conclusions of fuzzy QFD, a robot for disinfection and epidemic prevention was designed in a comprehensive manner. A robot that can completely replace human beings in the tasks of disinfection and epidemic prevention was designed in this work, solving the problems associated with the robot's ability to climb stairs and realizing the innovation of the robot's comprehensive disinfection, distribution of materials, real-time monitoring, temperature measurement, and other functions. This study provides a theoretical reference for the design of related products. [ABSTRACT FROM AUTHOR]

The adoption of blockchain technology (BCT) in a supply chain holds great potential for textile industries by executing transactions among stakeholders in a most reliable and verifiable way. Textile industries in emerging economies, like Pakistan, confront severe economic pressures and uncertain environment and strive to achieve sustainable supply chain excellence through blockchain implementation. This study is an initiative to analyze the key barriers in adopting BCT-related practices within the textile industry. This study conducts an extensive review of the literature using fuzzy Delphi approach for finalizing the barriers and applied fuzzy analytical hierarchy process (AHP) for prioritizing the barriers under uncertain environment. Based on the extensive review of the literature and panel discussions with experts, a total of five main barriers and 21 sub-barriers were categorized and ranked. The results and findings prioritize technological and system-related barriers (TSB) first, and human resources and R&D (HRB) barriers second among the other barrier dimensions. This paper highlights the need for an inclusive understanding of the various technological, environmental, and socio-economic perspectives to create blockchain applications that work for the textile sector. This study's key findings and policy guidelines can assist concerned stakeholders in making strategic decisions for adopting BCT within the textile supply chain. The managerial implications are provided for the industrial decision-makers and policymakers aiming to integrate BCT into the supply chain processes. Presently, there exists no research in the context of Pakistan that highlights the challenges faced during the adoption of BCT in the supply chain. For this purpose, an approach in the form of an integrated model based on fuzzy set theory is developed. Finally, the robustness of the proposed model is checked through sensitivity analysis. [ABSTRACT FROM AUTHOR]

The current study aims to develop a strategic policy for the micro, small, and medium enterprises (MSMEs) resilience system to deal with disruption during uncertainty and maintain sustainability. Previous studies stated that the MSMEs mortality rate was high, specifically in the first five years. This was caused by various internal weaknesses and the inability to deal with disruption amid uncertainty. The enterprises need government intervention to strengthen their resilience. Therefore, this study aimed to design a government policy model for a resilience system that connects actors, factors, goals, and alternative strategies during uncertainty. Since disruptions are complex, a holistic approach comprising resource theory, entrepreneurial orientation, corporate entrepreneurship, and entrepreneurship ecosystem was used. The method used is the Fuzzy Analytical Hierarchy Process, involving 20 experts as respondents. The results showed that certain factors, actors, goals, and strategies must be prioritized in formulating a policy strategy for the sustainability system in Takalar Regency, Indonesia. The main factor is entrepreneurial orientation, while the actor is highly resilient MSMEs. Additionally, the goal is for the market to accept products, while innovative transformation is the alternative priority strategy to be implemented. [ABSTRACT FROM AUTHOR]

Traffic delays are not wholly new and are a well-known problem that impacts many of the world's populations through disruptions and pollution. The rising urbanization and quantity of powered road vehicles necessitate a greater traffic control demand to maintain flow and avoid jams. In order to understand the notion of sustainable transportation, this study first examined sustainable transportation systems. This research then assessed Pakistan's present transportation infrastructure and urban transportation to find the most reasonable and sustainable alternative to reduce congestion. The Taxila intersection was utilized as a pilot study area because of its vicinity to Pakistan's leading economic hubs (i.e., industrial estates and the twin cities of Islamabad and Rawalpindi). The study used multi-criteria decision making (MCDM) techniques, including the fuzzy AHP, TOPSIS, VIKOR, and traffic simulation software, to determine the optimal solution for a more sustainable transportation system, and reducing traffic congestion. A pairwise comparison of the criteria and alternatives was made using a survey. This survey was used to look into the perspectives of various stakeholders and experts. The outcomes of the fuzzy AHP-TOPSIS and fuzzy AHP-VIKOR revealed that a flyover is the best alternative. In contrast, the best alternative, according to the software was a parking area. Ultimately, we assessed our results using the literature, and site observation, and concluded that a parking area would be the most sustainable alternative in the Taxila intersection. [ABSTRACT FROM AUTHOR]

Landslides are geological hazards that claim lives and affect socio-economic growth. Despite increased slope failure, some constructions, such as road constructions, are still being performed without proper investigation of the susceptibility of slope mass movement. This study researches the susceptibility of landslides in a study area encompassing a major highway that extends from Taiping to Ipoh, Malaysia. After a comprehensive literature review, 10 landslide conditioning factors were considered for this study. As novel research in this study area, multi-criteria decision-making (MCDM) models such as AHP and fuzzy AHP were used to rank the conditioning factors before generating the final landslide susceptibility mapping using Geographical Information System (GIS) software. The landslide susceptibility map has five classes ranging from very low (9.20%) and (32.97%), low (18.09%) and (25.60%), moderate (24.46%) and (21.36%), high (27.57%) and (13.26%), to very high (20.68%) and (6.81%) susceptibility for the FAHP and AHP models, respectively. It was recorded that the area is mainly covered with moderate to very high landslide risk, which requires proper intervention, especially for subsequent construction or renovation processes. The highway was overlayed on the susceptibility map, which concludes that the highway was constructed on a terrain susceptible to slope instability. Therefore, decision-makers should consider further investigation and landslide susceptibility mapping before construction. [ABSTRACT FROM AUTHOR]

Collaboration in green product design and development is becoming more significant to ensure a brighter future for eco industries, and research into such innovation has increased in recent years. So, it has been emphasized by practitioners that green thinking should be adopted from the design stage through the development stage and into the disposal stage of a product. However, it is challenging to identify the severity of strategies that mainly hampers the growth of green product design and development (GPDD). The current research aimed to identify and rank various strategies based on their significant impact on the development of green product design. The study contains three segments: (1) Multiple strategies were identified based on the published literature, project reports, and interactions with academics and industry experts. Then, 22 strategies were selected for GPDD that could be divided into five clusters: cooperation and commitment from top management commitment (TMC), design for environment (DFE), utilization of green technologies (UGT), green external supply chain management (GESCM), and green internal supply chain management (GISCM). (2) The Kano model was used to identify user requirements and satisfaction levels. (3) The priority weight and rank among selected strategies were determined using the fuzzy AHP approach. The results show that the "DFE" ranks highest among the main categories, and "design for disassembly" has been highlighted as a necessary sub-criteria in the emerging eco industries. Various recommendations are suggested to adopt these techniques, which augment the growth of green product design and development for eco industries. [ABSTRACT FROM AUTHOR]

Despite that products of precision manufacturing are widely used in many fields involving the national economy, precision manufacturing processes are more unfriendly to the environment, resources and social development than general manufacturing. Hence, the implementation of sustainable precision manufacturing (SPM) is of great strategic significance. There is no literature identifying and ranking the drivers of implementation of SPM and the impact on sustainability owing to the application of advanced manufacturing technologies in SPM has not been explored. To resolve these problems, drivers of SPM are identified based on combined support of prior studies and six groups of experts consisting of 71 individuals from six precision manufacturing enterprises. The drivers are calculated and ranked by a two-step fuzzy MCDM method which integrated the fuzzy AHP (fuzzy analytic hierarchy process) and fuzzy TOPSIS (fuzzy technique for order of preference by similarity to ideal solution) algorithms. The evaluation of drivers is based on the basic principles of sustainable development (environmental criterion, social criterion and economic criterion). The paper concludes that technological innovation, government support and current legislation are the most critical drivers during SPM implementation. Additionally, the result of sensitivity verification of the proposed method conducted proves the robustness and correctness of the algorithm and results. [ABSTRACT FROM AUTHOR]

Mining of the extensive, steeply dipping ore deposit takes several decades. An open-pit mining method is more often used in the early years of such a mining enterprise (ME). The management of the enterprise is faced with the problem of changing the mining method as the depth of the quarry increases. Untimely solution of this issue or the choice of the wrong strategy for the development of ME leads to a decrease in profitability, and the emergence of environmental and social difficulties. We studied the functioning of one hundred and seven MEs from different countries and substantiated four main sustainable development strategies for ME and its main system—the open-pit mining and technical system (MTS): adjustment of the current stage of mining indicators, transition to a new stage of mining, transition to a combined open–underground mining, and mine closure. The result of our research is an original methodology for selecting a strategy for MTS sustainable development. Our methodology is based on a new system of parameters and indicators for evaluating the sustainability of the opening-up of an opencast system (OOS). This assessment system includes twenty-three indicators that characterize the technical, technological, economic, social, and environmental factors of sustainable development. We propose to select a strategy for MTS sustainable development using combined fuzzy AHP-MARCOS multicriteria decision method (MCDM). The result of our case study for the Malyi Kuibas ore deposit was the choice of a mine closure strategy. The reliability of the obtained result is confirmed by a multilateral sensitivity assessment using nine other known MCDMs, while changing the criteria weights and composition of strategies. The results of the study prove the need for a timely decision to change the MTS development strategy as the depth of production increases. In addition, we have shown the effectiveness of the selection methodology based on the multicriteria assessment of the OOS sustainability. [ABSTRACT FROM AUTHOR]

Deciding on an appropriate development strategy is one of the most crucial aspects of the mining industry's green transition. This research introduces a novel integrated decision support model that can be applied to analyze various environmental factors and determine development strategies. In this study, a strengths, weaknesses, opportunities, and threats (SWOT) analysis is employed from multiple perspectives, including political, economic, social, and technological (PEST), to assess the internal and external factors that influence green mining. The fuzzy analytic hierarchy process (AHP) is used to analyze the factor weights quantitatively, and the fuzzy Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS) method is used to rank and select development strategies. According to the results, "grasp the trend of green development and improve the protection and exploitation level of mineral resources" is found to be the final optimal strategy. Comparative analysis and sensitivity analysis confirmed the accuracy of the model and the case study results. [ABSTRACT FROM AUTHOR]

India has ambitious goals to increase renewable energy penetration, and significant progress has been made since 2017. However, the Indian energy mix is highly dominated by fossil fuels. To set India on the pathway of the energy transition, a comprehensive analysis of the complex factors influencing the Indian energy sector is required. This study is put forward to delineate the current energy transition scenario in India and to direct the energy sector towards a prospective scenario for accomplishing a smooth energy transition. A hybrid quantitative-qualitative SWOT-integrated MCDA methodology is employed to accomplish the objective of this study. An extensive literature review is performed to understand and sort the various factors under each SWOT category. Fuzzy AHP methodology is utilized to convert the qualitative significance of each SWOT factor into quantitative scores, through which the crucial influencing factor in the current energy transition scenario is obtained. The top three highest-influence factors include utilizing the cost-competitiveness of solar and wind energy technologies over fossil fuels, the inadequacy of manpower having specialized skillsets, and connecting households to electricity and electrifying the transportation sector. The recommendation strategies are framed and presented for prospective energy transition scenarios. These strategies are assessed against the SWOT factors by using the PROMETHEE II methodology. The assessment results highlight that developing robust regulatory and policy frameworks, increasing the contribution of local energy resources, and promoting the distributed generation and grid infrastructure development are the highest-scoring strategies that have a synergic effect on multiple dimensions of energy transition, including political, financial, and techno-economic aspects. The proposed study will be conducive to framing effective policy in the upcoming years to assist the energy transition in India. [ABSTRACT FROM AUTHOR]

The balance between resource consumption and the ability of natural systems to meet the needs of future generations emerges as a prerequisite of sustainability. Sustainability means aligning economic growth and development with the interest of the environment and social development. Decision-making is a significant responsibility in an environment and the business world because decisions affect the ecology and business performance. It is necessary to adopt new approaches in decision-making to find an appropriate method for assessing and setting priority goals. Various methods for multi-criteria decision-making have been developed, including the Analytic Hierarchy Process (AHP). The paper deals with the management of natural and human resources for the sustainable economic development of Serbia by selecting influential factors, relying on a multi-criteria decision-making framework. Appropriate methods have been applied: AHP and several fuzzy AHP (FAHP) approaches. These methods' application enables the analysis of results from different aspects of expert opinion. Through a case study, this paper investigates the AHP method from several facets in which the identification of decision criteria is based on the perception of experts of different profiles. The findings of this research can be a guideline for decision-makers in resource management to enhance sustainable economic development. The case study confirms that the stability of the business environment and business sectors is the most influential indicator in all scenarios. [ABSTRACT FROM AUTHOR]

This paper explores and ranks the key performance indicators of multi-criteria decision-making in the process of selecting renewable energy sources (RES). Different categories of factors (e.g., political, legal, technological, economic and financial, sociocultural, and physical) are crucial for the analysis of such projects. In this paper, we apply the fuzzy analytic hierarchy process (fuzzy AHP) method--a mathematical method--in order to analyze the main criteria for such projects, which include the environment, the organizational management structure, project participants, and participants' relationship with the performance indicators. In order of ranking, the indicators are the following: time, costs, quality, monitoring the project's sustainability, user feedback, and users' health and safety. The aim of this paper is to point out the necessity of creating an adjustable model for renewable energy projects in order to proceed with the sustainable development of the southeast part of Serbia. This model should lead the creation process for such a project, with the aim of increasing its energy efficiency. [ABSTRACT FROM AUTHOR]

The ventilating crisis of Corporate Social Responsibility (CSR) issues in the textiles industry resulted in the engagement of many researchers in the analysis of CSR and its related factors throughout the globe. Some researchers in developed nations extend their policies beyond the boundary of CSR in the textiles industry, but some developing contexts are still limited to this boundary, including India, due to facts that have not yet been revealed. Hence, to fill this gap, this study reveals the factors that are resisting the implementation of CSR in the textiles industry with the assistance of a proposed model, and this model is validated with a case industry situated in southern India. Common barriers are collected through various reliable means, and among those common barriers, the essential barrier was identified with the assistance of the case industrial manager through an Analytical Hierarchy Process (AHP) under a fuzzy environment. The results show that financial constraints comprise the main barrier to the implementation of CSR in the Indian textiles industry, which is then further validated with feedback from case industry managers. This study offers both societal and scientific insights, identifies limitations, and provides an approach that may be extended in the future once additional factors are implemented. [ABSTRACT FROM AUTHOR]

India has an ambitious target to promote clean energy penetration, but as of 2021, the electricity mix of India is dominated by coal to about 71%. Therefore, analyzing the clean energy potential and the ability of the individual states to entrench energy transition in the upcoming years will be supportive for policymakers. This study is propounded to assess the clean energy transition potential with a focused analysis on seven major power-producing states of India. These states include Maharashtra, Gujarat, Tamil Nadu, Uttar Pradesh, Karnataka, Madhya Pradesh, and Andhra Pradesh. The clean energy transition potential assessment is performed by utilizing multi-criteria decision analysis methodologies such as the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Multi-Objective Optimization Method by Ratio Analysis (MOORA). Further, the analysis is performed against four major criteria that include high carbon energy resource dependency, low carbon energy resource dependency, clean energy potential, and policy support. Altogether, the assessment criteria include four primary level criteria and fourteen secondary level parameters. In order to reflect the significance of each parameter and criterion to the characteristics of clean energy transition potential, appropriate weightage is provided using the Fuzzy Analytic Hierarchy Process (AHP). The results indicate that Gujarat has the highest clean energy transition potential in both the multi-criteria decision analysis methods. On the other hand, Uttar Pradesh exhibited the least performance, and a complete energy transition to clean energy resources is less likely in this state. The rest of the states obtained intermediate ranking, and a comparative analysis between the two methods was also accomplished. This study suggests that India should focus on the clean energy policy with vigorous efforts on top-performing states which will effectively accelerate the power sector decarbonization. [ABSTRACT FROM AUTHOR]

The purpose of this research was to plan an approach to a project framework that integrated a model for sustainability and CSR, with the process groups of the Project Management Body of Knowledge (PMBOK®) standard, in its application to the training of a group of students in Project Design, Management, and Evaluation. The integration was justified by the scarce explicit references to sustainability and CSR found in traditional project management guidelines, norms, and standards. The new framework was used to structure a Sustainability Management Plan, which made it possible to incorporate sustainability criteria throughout the life cycle of the training project. The training proposal in Project Design, Management, and Evaluation was chosen, among several alternatives, by a multi-criteria selection process (fuzzy AHP) in the context of project scope management. The results reveal a great heterogeneity among the models and the lack of a base of key indicators in sustainability and CSR measurement tools as well as of explicit references to sustainability in project management standards. It is therefore necessary to develop a Sustainability Management Plan that can be introduced in the Project Management Plan and thus influence the strategic and operational guidelines of the Institution. [ABSTRACT FROM AUTHOR]

Traceability technologies have great potential to improve sustainable performance in cold food supply chains by reducing food loss. In existing approaches, traceability technologies are selected either intuitively or through a random approach, that neither considers the trade-off between multiple cost–benefit technology criteria nor systematically translates user requirements for traceability systems into the selection process. This paper presents a hybrid approach combining the fuzzy Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) with integer linear programming to select the optimum traceability technologies for improving sustainable performance in cold food supply chains. The proposed methodology is applied in four case studies utilising data collected from literature and expert interviews. The proposed approach can assist decision-makers, e.g., food business operators and technology companies, to identify what combination of technologies best suits a given food supply chain scenario and reduces food loss at minimum cost. [ABSTRACT FROM AUTHOR]

A robust project selection process is critical for the selection of sustainable projects that meet the needs of an organization or community. There are multiple factors or criteria that can be considered in the selection of the appropriate sustainable project, but it can be challenging to find sufficient depth of expert opinion to perform a strong evaluation of these criteria. Several researchers have turned to the sustainable project literature as a source of expert opinion to evaluate the criteria used in sustainable project selection and rank them based on importance using different multi-criteria decision-making (MCDM) methodologies. However, using the literature as a source of expert opinion poses a different set of challenges and may not accurately represent the actual opinions of sustainable project subject matter experts (SMEs) and practitioners. In this study, the fuzzy analytic hierarchy process (FAHP) methodology is used to determine the importance of project cost, project maturity, skill and experience, uncertainty, and technology information transfer as selection criteria using collected opinions from academic sustainable project experts and practitioners. The results are then compared with previous research that used the literature to rank these five criteria based on importance when selecting between multiple sustainable project alternatives. The results show that project cost is still considered the major driver of decision making in sustainable project selection by both the literature and practice. However, unlike the literature-as-experts approach, SMEs prioritize skill and experience and technology information transfer over project maturity and uncertainty. Project managers and decision makers can use these findings to best prioritize the types of challenges that may occur depending on inputs for the FAHP analysis. [ABSTRACT FROM AUTHOR]

The construction of hydropower plants often requires the flooding of large land areas, causing considerable alterations in the natural environment. In the region surrounding the reservoir of the Corumbá IV hydroelectric plant, located in the Cerrado region of Central Brazil, two types of soil predominate, classified as Dystroferric Red Latosol and Dystroferric Haplic Cambisol. The plant owners have to restore the degraded biome after the flooding of the margins caused by the filling of the reservoir. An experiment was carried out with fifteen native species, selected for having ideal phytosociological properties. Nine of them showed a survivability considered satisfactory in a planting situation, with a view to large-scale planting. Assuming that the planting of native fruit trees can be a quick solution to the attraction and preservation of wildlife, it would therefore provide sustainable riparian revegetation around the reservoir. We adopted the SIMOS technique to rank the criteria based on four morphological features and a Fuzzy AHP model to rank the contributions of the nine fruit tree species to the sustainable restoration of part of the riparian vegetation cover around the reservoir. In practical terms, we concluded that the soil types did not have any influence on tree survival after two years of growth, but the native trees' morphological features varied among the species. These findings simplify the large-scale planting of seedlings that must be carried out by the operator in the riparian forest around the reservoir. [ABSTRACT FROM AUTHOR]

Sustainability of the open pit mining and technical system (MTS) is one of its key goals in the changing conditions of the external and internal environment. All MTS's subsystems must function in concert to achieve this goal. The structure of the MTS is formed by many subsystems and elements, which are evaluated by a significant number of indicators. A comprehensive assessment of the MTS for all possible indicators is a complex and time-consuming task. However, each subsystem and element of the MTS has a different effect on the sustainability of this system. The MTS's parameters change significantly during transition periods, for example, at a new stage of open-pit mining or when switching to an open-underground method of developing mineral deposits. The MTS's sustainability declines during the transition periods. Changes in the parameters of technological processes during these periods can have a negative impact on the state of the economic and social subsystems of mining enterprises, as well as on the environment. Ensuring the sustainability of an MTS during transition periods requires the development of new approaches and principles for managing the work of mining enterprises, based on the alignment of economic goals, with goals in the field of ecology and social development. The study substantiates the key role of one of the MTS subsystems—the opening-up of an opencast system (OOS). It is shown that this system has a decisive influence on sustainable functioning and development. The systematization of the principles of sustainable functioning and development of mining enterprises and its systems has been carried out. Four groups of principles are distinguished: system-wide principles of management, principles of development of mining enterprises, principles of MTS development, and principles of the MTS's subsystem development. The proposed system of principles is based on the idea of a sequential transformation of the subsystems at all stages of design and operation. A feature of the proposal system of principles is the consideration of economic, social, and environmental aspects to ensure the specified parameters for the sustainable functioning and development of mining enterprises. The results of the analysis of the factors of the external and internal environment of the MTS are presented. The parameters and indicators for assessing the sustainability of OOS and MTSs were selected and substantiated. The justified parameters and indicators were ranked using the fuzzy Analytic Hierarchy Process (AHP). The results of the assessment showed a high convergence of expert opinions on a group of economic parameters, which were rather high in technical and technological parameters. However, there is a divergence of expert opinions on social and environmental parameters. As a result of the study, it was concluded that the current management decisions are aimed at ensuring the economic and technological sustainability of MTS functioning, while achieving the goals of sustainable development of this system is not ensured. The methodology developed and presented in the study can be used to assess the sustainability of the functioning and development of MTSs. [ABSTRACT FROM AUTHOR]

Corporate sustainability is considered a fundamental paradigm and solution in creating a prosperous future for organizations. However, social sustainability issues and pandemic problems from COVID-19 have affected corporations and interrupted plans for sustainable development. To date, corporate sustainability frameworks have taken a relatively narrow view of this paradigm. This study highlights serious challenges to corporate sustainability while providing a framework in an attempt to enable more sustainable business practices. To fill the gap in the literature, we have developed a framework to organize and prioritize important sustainability indicators. The first phase of the study involves the classification of 45 sub-criteria of corporate sustainability under nine main categories by using a literature review and novel Fuzzy Delphi method. The resulting categories are Corporate Governance, Product Responsibility, Transparency and Communication, Economic, Environmental, Social, Natural Environment and Climate Vulnerability, Energy Consumption along with Energy Saving, and includes Pandemic COVID-19 as a new aspect of social sustainability. Next, we applied the Fuzzy Analytical Hierarchical Process (FAHP) to help determine the weights and prioritizing the criteria and sub-criteria. The results revealed that the Pandemic, along with the Natural Environment and Climate Vulnerability, ranked higher among the main criteria category. Whereas, emergency response planning, social distances, modification of working hours, and just-in-time delivery are the most influencing sub-attributes among the 45 sub-barriers of different categories. Contributions of this study include new insights regarding corporate sustainability criteria and subcriteria, application of novel methods, and integrated framework for dimensions of corporate sustainability. This study is among the first of its kind to consider the COVID-19 pandemic as an essential category and social sustainability attribute of corporate sustainable business practices. Outcomes of this study can help assist scholars, corporations, and decision-makers in understanding sustainable development initiatives while simultaneously improving social sustainability practices. [ABSTRACT FROM AUTHOR]

This paper presents an analysis of the effectiveness of variants of the reconstruction of a polder, which is part of the flood protection system of a large urban agglomeration. The Golina polder, located in the floodplain of the Warta River, was selected as the case study. The multi-criteria decision support methods AHP and Fuzzy AHP were used to assess the effectiveness of individual variants. Information on the floods from 1997 and 2010, data on land cover, land development, nature and historical objects were used to estimate the value of the coefficients for the multi-criteria decision methods. It was shown that the planned deep modernization of the hydrotechnical infrastructure and the purchase of land in the polder area is less effective than maintaining the current state of development of the polder. [ABSTRACT FROM AUTHOR]

This study, on the one hand, develops a newfangled risk assessment and analysis (RAA) methodological approach (the MCDM-STO/DET one) for sustainable engineering projects by the amalgamation of a multicriteria decision-making (MCDM) process with the joint-collaboration of a deterministic (DET) and a stochastic (STO) process. On the other hand, proceeds to the application of MCDM-STO/DET at the workplaces of the Greek construction sector and also of the fixed-telecommunications technical projects of OTE SA (that is, the Greek Telecommunications Organization S.A.) by means of real accident data coming from two official State databases, namely of "SEPE" (Labor Inspectorate, Hellenic Ministry of Employment) and of "IKA" (Social Insurance Institution, Hellenic Ministry of Health), all the way through the period of the years2009–2016.Consequently, the article's objectives are the following: (i) The implementation and execution of the joint MCDM-STO/DET framework, and (ii) to make known that the proposed MCDM-STO/DET algorithm can be a precious method for safety managers (and/or decision-makers) to ameliorate occupational safety and health (OSH) and to endorse the sustainable operation of technical or engineering projects as well. Mainly, we mingle two different configurations of the MCDM method, initially the Analytical Hierarchy-Process (the typical-AHP), and afterwards the Fuzzy-Extended AHP (the FEAHP) one, along with the Proportional Risk Assessment Technique (PRAT) and the analysis of Time-Series Processes (TSP), and finally with the Fault-Tree Analysis (FTA). [ABSTRACT FROM AUTHOR]

Energy systems planning commonly involves the study of supply and demand of power, forecasting the trends of parameters established on economics and technical criteria of models. Numerous measures are needed for the fulfillment of energy system assessment and the investment plans. The higher energy prices which call for diversification of energy systems and managing the resolution of conflicts are the results of high energy demand for growing economies. Due to some challenging problems of fossil fuels, energy production and distribution from alternative sources are getting more attention. This study aimed to reveal the most proper energy systems in Saudi Arabia for investment. Hence, integrated fuzzy AHP (Analytic Hierarchy Process), fuzzy VIKOR (Vlse Kriterijumska Optimizacija Kompromisno Resenje) and TOPSIS (Technique for Order Preferences by Similarity to Idle Solution) methodologies were employed to determine the most eligible energy systems for investment. Eight alternative energy systems were assessed against nine criteria—power generation capacity, efficiency, storability, safety, air pollution, being depletable, net present value, enhanced local economic development, and government support. Data were collected using the Delphi method, a team of three decision-makers (DMs) was established in a heterogeneous manner with the addition of nine domain experts to carry out the analysis. The fuzzy AHP approach was used for clarifying the weight of criteria and fuzzy VIKOR and TOPSIS were utilized for ordering the alternative energy systems according to their investment priority. On the other hand, sensitivity analysis was carried out to determine the priority of investment for energy systems and comparison of them using the weight of group utility and fuzzy DEA (Data Envelopment Analysis) approaches. The results and findings suggested that solar photovoltaic (PV) is the paramount renewable energy system for investment, according to both fuzzy VIKOR and fuzzy TOPSIS approaches. In this context our findings were compared with other works comprehensively. [ABSTRACT FROM AUTHOR]

International capacity cooperation is easily affected by the interweaving of its internal and external environment. As the risk accumulation exceeds the threshold, a supply chain crisis and even emergency will occur and serious losses will be caused. Regarding multinational operation and international capacity cooperation, 208 cases were summarized to identify risk types and high-incidence areas, and a risk measurement index system was established. A Fuzzy AHP (Analytic Hierarchy Process) method was used to evaluate the importance of each risk index. It was found that country risk was the main cause of supply chain emergencies in international capacity cooperation. Construction, water and electricity supply, mining and manufacturing were major areas of emergencies. In international capacity cooperation, country risk and cross-cultural risk were more important in external risks, while in internal risk, financial risk and decision risk were more important. [ABSTRACT FROM AUTHOR]

The selection of a third-party logistics (3PL) provider is an important and demanding task for many companies and organizations dealing with distribution activities. To assist in decision making, this paper proposes the implementation of fuzzy logic. To design a fuzzy inference system (FIS), the first prerequisite is to determine a set of evaluation criteria and sub-criteria and to find the relationship between them. This task was solved by an extensive review of the literature and expert opinions on implementing the Fuzzy Analytic Hierarchy Process (AHP) approach. The results obtained in the first part of the research, together with data collected from 20 3PL providers, were further used in the second part, which was related to the implementation of the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method. Finally, a decision-making tool for 3PL provider selection was designed as an FIS structure, where the inputs were the previously defined criteria and the output was a preference for 3PL selection. The fuzzy rules were generated on the basis of the collected empirical data, the preferences obtained by the TOPSIS method, and expert opinion using the Wang–Mendel method. The proposed fuzzy model is particularly suitable when input data are not crisp values but are provided descriptively through linguistic statements. [ABSTRACT FROM AUTHOR]

Owing to rapid growth in the Asian solar photovoltaic (PV) power market, decision-making models are required to develop efficient investment strategies. Previous studies have largely focused on technological conditions and macroeconomic indicators, but not on the increasing needs of the financial sector. In this study, we developed an evaluation model of solar PV investment and financial factors at the project level. The model applies the fuzzy analytic hierarchy process and selects appropriate evaluation indicators for investment by emphasizing financial factors such as access to finance and exit strategies after the initial investment. Furthermore, we derived the relative importance of the indicators for each stakeholder. Stakeholder analysis enables comparison by quantifying the risks of each market participant. Economic factors (71.57%) were selected as the most important evaluation factors, followed by policy factors (16.26%), and technical factors (12.17%). Higher weights were assigned to indicators that directly affect profitability. Stakeholders showed significant differences in policy factors. Power generation companies showed higher weight values in policy factors than other groups. Quantification of differences in perceptions provides basic data for establishing effective investment strategies and developing policies. Therefore, the proposed model will contribute to more efficient solar PV project development. [ABSTRACT FROM AUTHOR]

Planning of sustainable urban renewal is one of the key issues for city development. Particular emphasis is placed on the problem of the sustainable urban renewal of areas that are made up of a large number of private cadastral parcels that cause ownership fragmentation. Urban renewal is most often carried out to realize a large project where it is necessary to determine the optimal way of its realization. This paper proposes a methodology for assessing the index of fragmentation for the purpose of sustainable urban renewal planning. The methods used to solve the task are Simple Additive Weighting method (SAW) for ranking alternative solutions (i.e., cadastral parcels, spatial elements and areas of future construction), and the Fuzzy Analytic Hierarchy Process method (FAHP) for defining the criteria weights. In the process of defining the index of fragmentation model as well as the weighting determination, a group of experts was involved. The proposed model was tested on the field of the construction of the University of Split campus, for which implementation was planned in several periods. The obtained results show that the proposed methodology can provide support in analyzing the spatial–functional capacities of the existing land, and for decision making in optimizing the realization of urban projects. [ABSTRACT FROM AUTHOR]

The Chinese dual land use system (DLUS) has played a crucial role in the industrialization of China since 1950s. However, this dual system caused/causes obstacles in urban development under the new market economic conditions. This paper presents an approach to assess the social-economic risks during urban development in China by integrating the strategic environment assessment (SEA) principle into the fuzzy analytic hierarchy process (AHP) method. In the proposed approach, SEA principles are set as the influencing factors in AHP. Fuzzy AHP is used to assess the relative importance degree of the six principles in SEA. To illustrate the application procedure of the proposed approach, a building collapse incident in Wenzhou is used as a case for the risk analysis. The assessment results show that the index of the manage system has the greatest importance to social-economic risk. The principle of sustainable development (A) and monitoring measures (E) have more importance than the other principles in SEA. It can be concluded that the DLUS in the market management of China may be responsible for building collapse incidents in rural areas. It is suggested that the principles of sustainable development and monitoring measures in SEA should be strictly implemented during urbanization, and it is recommended that the government establish a unified management system and ensure the effective implementation of sustainable urbanization. [ABSTRACT FROM AUTHOR]

Strengthening sale and purchase (S&P) capacity has become a fundamental requirement for sustainable growth and corporate competitiveness in the modern shipping market. However, there is a lack of research related to S&P and its priority when shipping companies attempt to implement ship acquisition through S&P activities. To fill this gap, this paper conducts an empirical analysis to analyze priority factors during the acquisition of second-hand ships from the perspective of shipping companies. Business criteria are considered to be the most important factors in the analysis of the priority of ship acquisition and investment in shipping companies. To the best of our knowledge, this research is the first exploration covering Korean shipping companies’ ship acquisition through S&P activities. This study is expected to contribute to the better understanding of the role of S&P in ensuring the sustainability of shipping companies and to provide stakeholders with valuable insights. [ABSTRACT FROM AUTHOR]