Step-wise Weight Assessment Ratio Analysis Research Articles

PESTEL ANALYSIS OF THE HEALTHCARE SYSTEM WITH REFERENCE TO THE RIGHT TO HEALTH DURING A PANDEMIC

A pandemic caused by the coronavirus affects all aspects of life of an individual and a society as a whole. It is not only a question of the medical profession, but also of other areas, and especially the need for fundamental human rights. The measures adopted by state bodies are primarily aimed at protecting human health, but the effects and implications they cause limit other rights, so it raises the question of their adequacy. The basic and most important question is how to access health care in such conditions. Therefore, the main aim of the paper is to try to answer the question through PESTEL (P-Political, E-Economic, S-Social, T-Technological, E-Environmental, L-Legal) analysis of the healthcare system of the local community of Pale. Thirty factors of PESTEL analysis were quantified by using the Improved Fuzzy Stepwise Weight Assessment Ratio Analysis (IMF SWARA) method. The results obtained through the total of 70 formed models show that the current state of the observed local community is marked by social and legal factors. This analysis should present a diagnostic test of the current situation and provide a good basis for future actions.

An integrated decision support framework using single-valued neutrosophic-MASWIP-COPRAS for sustainability assessment of bioenergy production technologies

As a clean and renewable energy, bioenergy is one of the most prospective alternatives to fossil fuels. Therefore, it has been received much attention and occupied a considerable status in the world’s energy consumption. Moreover, the sustainable bioenergy production can effectively decrease the risk of energy poverty and contribute to the economic and ecological benefits, particularly in developing countries. However, the selection of bioenergy production technologies (BPTs) has significant challenges and uncertainties due to various factors. Thus, the aim of this study is to evaluate the BPTs and choose the most suitable and sustainable alternative among them. For this purpose, an integrated decision-making framework is proposed under single-valued neutrosophic environment. In the present approach, the method based on the removal effects of criteria (MEREC) and stepwise weight assessment ratio analysis (SWARA) weighting integrated procedure (MASWIP) is introduced to compute the relative significances of the considered sustainability indicators. Then, the MASWIP-based complex proportional assessment (COPRAS) is introduced to prioritize the BPTs from single-valued neutrosophic perspective. Further, the present framework is implemented on a case study of BPTs evaluation problem with uncertain, inconsistent and indeterminate information, which approves the effectiveness and practicality of introduced method. To assess its robustness and stability, sensitivity and comparative studies are performed. The advantages of the developed method are emphasized in terms of stability and reliability by comparisons with five existing approaches, and the effectiveness of the present approach is verified. The findings of the study prove that the application of single-valued neutrosophic MASWIP-based COPRAS method in BPT selection is robust.

Risks of data-driven technologies in sustainable supply chain management

PurposeWith the rapid change that has taken place with digitalization and data-driven approaches in supply chains, business environment become more competitive and reaching sustainability in supply chains become even more challenging. In order to manage supply chains properly, in terms of considering environmental, social and economic impacts, organizations need to deal with huge amount of data and improve organizations' data management skills. From this view, increased number of stakeholders and dynamic environment reveal the importance of data-driven technologies in sustainable supply chains. This complex structure results in new kind of risks caused by data-driven technologies. Therefore, the aim of the study to analyze potential risks related to data privacy, trust, data availability, information sharing and traceability, i.e. in sustainable supply chains.Design/methodology/approachA hybrid multi-criteria decision-making (MCDM) model, which is the integration of step-wise weight assessment ratio analysis (SWARA) and TOmada de Decisao Interativa Multicriterio (TODIM) methods, is going to be used to prioritize potential risks and reveal the most critical sustainability dimension that is affected from these risks.FindingsResults showed that economic dimension of the sustainable supply chain management (SSCM) is the most critical concept while evaluating risks caused by data-driven technologies. On the other hand, risk of data security, risk of data privacy and weakness of information technology systems and infrastructure are revealed as the most important risks that organizations should consider.Originality/valueThe contribution of the study is expected to guide policymakers and practitioners in terms of defining potential risks causes by data-driven technologies in sustainable supply chains. In future studies, solutions can be suggested based on these risks for achieving sustainability in all stages of the supply chain causes by data-driven technologies.

Evaluation of Gender Equality Criteria Related to Social Sustainability in Ports

Ports are developing sustainability frameworks in order to cope with latest requirements from the stakeholders. Economic, environmental and social dimensions of sustainability are the three pillars of the topic. Although economic and environmental aspects of sustainability in ports are widely researched in the literature, the social dimension of gender equality research is scarce. To fill the gap, it is important to identify the most important efforts for improving gender equality in ports. The aim of this study is to evaluate the gender equality criterias by port executives in terms of social sustainability. For this purpose, one of the Multi-Criteria Decision Making (MCDM) methods, Step-wise Weight Assessment Ratio Analysis (SWARA) was used to evaluate the priority weights of five criterias in Turkey. The results show that recruitment policy is the most important criteria in the field. Therefore, some suggestions are made to port industry to become more socially sustainable by minimizing the gender gap.

Identifying and Evaluating the Essential Factors Affecting the Incidence of Site Accidents Caused by Human Errors in Industrial Parks Construction Projects.

In terms of safety management, the implementation of industrial parks construction projects (IPCPs) is incredibly challenging due to the special working conditions and the specific type of use of the buildings. On the other hand, the possibility of causing accidents in these areas based on human errors is high and important for project execution due to the risks of human errors and financial losses. Therefore, this study tries to fill this existing research gap by identifying and evaluating the effective key factors leading to the occurrence of construction accidents caused by human errors in the development of IPCPs. After a holistic review of the reported literature, four rounds of fuzzy Delphi survey were launched to capture the individual opinions and feedback from various project experts. Accordingly, 41 key factors affecting human errors in the implementation of industrial parks construction projects in Iran were identified and classified into nine main groups of wrong actions, observations/interpretations, planning/processes, equipment, organization, individual activities, environmental conditions, rescue, and technology. Then, the step-wise weight assessment ratio analysis (SWARA) method was adopted to rate and rank the identified factors of human errors in the implementation of IPCPs in Iran. The research findings indicated that among the elicited factors, time factor (0.1226), delayed interpretation (0.1080), and incorrect diagnosis/prediction (0.0990) are the three most crucial factors leading to human errors in the implementation of IPCPs in Iran. The results of this research study have provided various major project stakeholders with an effective decision-aid tool to make better-informed decisions in managing and reducing the occurrence of construction site accidents particularly caused by human errors associated with IPCPs.

Key performance factors for integration of Industry 4.0 and sustainable supply chains: a perspective of Indian manufacturing industry

PurposeThe purpose of this paper is to identify the key performance factors that can lead toward sustainability in the Industry 4.0 supply chains of manufacturing industries.Design/methodology/approachQuestionnaire is used to collect the data from manufacturing sector to prioritize the factors, which integrates both Industry 4.0 and sustainability. For this, stepwise weight assessment ratio analysis (SWARA) method is used to obtain the weights for criteria and sub-criteria to prioritize the factors.FindingsThe present study brings the findings about five key performance factors. Social factor needs much attention among all the criteria, followed by ecological, economic, information technology and dynamic capability theory. Further, change management, third-party audits and novel business models are key sub-factors to improve performance of sustainability in Industry 4.0 supply chains.Practical implicationsThis study prioritized the performance factors of Industry 4.0 and sustainable supply chain in Indian manufacturing sector. These prioritized factors help to improve performance of organizations, which are practicing the Industry 4.0 and sustainability practices. Managers in manufacturing industries can use the SWARA for assessment of weights for the criteria and sub-criteria factors to take appropriate decisions to improve the organizations’ performance.Originality/valueManagers in manufacturing industry can use these prioritized factors to improve the performance of their supply chains.

Balanced scorecard-based cost analysis of service industry using a novel hybrid decision making approach based on golden cut-oriented bipolar and q-ROF sets

This study aims to create a strategy for reducing energy costs in hospitals to ensure the sustainability of health services. In this framework, a novel hybrid decision making approach is generated based on golden cut-oriented bipolar and q-rung orthopair fuzzy sets (q-ROFs). Firstly, balanced scorecard (BSC)-based criteria are evaluated by using multi stepwise weight assessment ratio analysis (M-SWARA) approach. Secondly, alternatives are examined with the help of technique for order preference by similarity to ideal solution (TOPSIS) technique. The novelty of this study is to find critical factors that affect the energy costs of health institutions with an original fuzzy decision-making model. This proposed model has also some superiorities by comparing with previous models in the literature. First, SWARA method is improved, and this technique is generated with the name of M-SWARA. Hence, the relationship between the criteria can be examined owing to this issue. Additionally, golden cut is taken into consideration to compute the degrees in bipolar q-ROFSs to achieve more accurate results. These two issues have an important impact on the originality of the proposed model. The findings demonstrate that consciousness level of employees has the highest weight with respect to the energy costs in hospitals. Additionally, the type of energy used also plays a significant role for this issue. Thus, renewable energy sources should be considered in meeting the energy needs of hospitals. Although the installation costs of these energy types are higher, it will be possible to significantly reduce energy costs in the long run.

Evaluation of Landfill Site Selection by Combining Fuzzy Tools in GIS-Based Multi-Criteria Decision Analysis: A Case Study in Diyarbakır, Turkey

Solid waste disposal is one of the important environmental and socioeconomic problems faced by city managers with the increase in urban population. To overcome this problem, landfilling is a common and effective solution used by municipalities frequently. This study aims to assess and identify suitable potential areas for municipal solid waste disposal. For this purpose, a criteria determination and evaluation commission consisting of experts from various institutions and disciplines was established. Fourteen criteria, including environmental, economic and sociocultural sensitivities, were selected via the experience of an expert team and a wide literature search. The criteria used in this study were standardized by using fuzzy membership functions and feature values turned into continuous values. The Stepwise Weight Assessment Ratio Analysis (SWARA) method, in which expert opinions are effective, was used to determine the criterion weights. A site suitability map was obtained by using the Weighted Linear Combination (WLC) method with standardized thematic maps and the criterion weight variables. As a result of this study, 3.44% of the total study area was determined suitable for a solid waste storage area. These determined areas were found in different locations of study and numbered on the map and each of them was selected as an alternative storage area candidate. Developed methodology was validated via exploration and observation of candidate areas by the expert team. The proposed methodology can be used for similar scale cities with its ease of use, flexibility and expert opinion.

Evaluate sustainable human resource management in the manufacturing companies using an extended Pythagorean fuzzy SWARA-TOPSIS method

Today, organizations realized the importance of sustainability in concern with their business activities. They found out that they should focus on other aspects such as environmental and social and economic sustainability. Lately, Sustainable Human Resource Management (SHRM) is introduced as an instrument to indicate that HRM can affect the sustainable development and resource preservation of organizations. Despite that, SHRM and its related subjects are still in an emerging phase. The present study aims to propose a comprehensive approach to examine the main important factors of SHRM. To do so, a survey approach with the literature review interviewsview with experts is carried out to classify, rank, and evaluate the key SHRM factors in the manufacturing companies in Ecuador. In order to assess and prioritize the factors and the alternatives, this paper introduces a new approach using an integrated Stepwise Weight Assessment Ratio Analysis (SWARA)- Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method on the Pythagorean fuzzy sets (PFSs) setting called the PF-SWARA-TOPSIS method. To do this, we extend the SWARA method to identify and rank the SHRM factors by using PFSs. Afterward, to assess and prioritize the alternatives, this study utilizes the TOPSIS approach under PFSs. Next, to show the efficacy and applicability of the developed framework, a real case study of the SHRM problem is discussed on PFSs. Furthermore, this study performs a sensitivity investigation over diverse sets of criteria weights to illustrate the advantages of the proposed methodology. The investigation results demonstrate that the green work-life balance was ranked as the first factor by following corporate social responsibility, green employee relations, and business process redesign factors. Finally, the results of this study found that the developed approach has high efficacy and capability to handle the SHRM problem in manufacturing companies.

Improvement projects with an environmental focus: A novel approach for prioritization

Employment of a systematic approach for prioritization of improvement projects and addressing the voice of the stakeholders are imperative for organizations in the current business circumstances. This study suggests a novel approach that employs multi-criteria decision-making (MCDM) methods for project prioritization. A combination of step-wise weight assessment ratio analysis (SWARA) method and house of quality (HOQ) is used in the calculation of the importance of criteria, followed by utilization of criteria importance in COmplex PRoportional ASsessment of alternatives with grey relations (COPRAS-G) for selection of the final project. It considers environmental effects alongside traditional criteria. Innovation in this study is in the combination of the MCDMs with HOQ and prioritizing projects considering the impact on the environment. The advantages are efficiency and simplicity. The practical focus of the approach is illustrated using a case example. The approach is used for the prioritization of projects that apply the Define–Measure–Analyze–Improve–Control (DMAIC) framework in a Six Sigma organization. The evaluation of three DMAIC projects suggested taking up Project C. The illustration has shown applicability in real-life situations. Thus, the novel approach identifies an environment-friendly project that satisfies the stakeholders the most. The utilization of Grey MCDM method makes the approach suitable for use in an uncertain environment.

Intelligent Novel IMF D-SWARA—Rough MARCOS Algorithm for Selection Construction Machinery for Sustainable Construction of Road Infrastructure

The quality of road infrastructure largely depends on the quality of road construction and adequate construction machinery. In order to reduce uncertainties and improve the performance of road infrastructure, it is necessary to apply modern and appropriate construction machinery. The aim of this study was to create a novel integrated multi-criteria decision-making (MCDM) model for the selection of pavers for the middle category of roads. A total of 16 criteria were defined and then divided into four main groups, on the basis of which the performance of 12 pavers was evaluated. Improved Fuzzy Stepwise Weight Assessment Ratio Analysis (IMF SWARA) with D numbers (IMF D-SWARA) was extended to determine the significance of the criteria for the selection of construction machinery based on two groups of experts. Rough measurement of choices and their ranking as a compromise solution (R-MARCOS) was used to evaluate and rank the performance of construction machinery. The results show that three alternatives out of the set considered can satisfy defined requirements. After that, we performed a multi-phase validity test in which different values of criterion weights were simulated. A comparative analysis with seven other Rough MCDM methods was also created, and the Spearman’s correlation coefficient (SCC) and WS coefficient were calculated to determine the correlation of ranks for sensitivity analysis and comparative analysis. Thus, the obtained results were verified.

Evaluation of wind power generation projects to reduce air pollution using multi-criteria decision-making methods in Saudi Arabia.

Currently, Saudi Arabia has very limited renewable energy generation capacity, as most of the country's electricity sector is dependent on cheap fossil fuels. However, in recent years, the Saudi government has announced a national development program called "the Saudi Vision 2030," whereby the country intends to increase the share of renewable energies in its total power generation to 20% by 2030. This research is aimed on the possibility of developing wind farms in Saudi Arabia's Al-Jawf area, which is known to be rich in wind sources. The potential of wind energy in the region was examined in the first phase of the research, which focused at the environmental, economic, and technical aspects. For this goal, the two-parameter Weibull function was used to model wind energy in the area. The economic assessment was performed in terms of the Levelized Cost of Energy and payback period. Multi-criteria decision-making approaches were employed in the second phase of the study to determine the most proper sites for harvesting wind energy in the study region based on eight factors including technical, economic, environmental, and social aspects. The most proper site for wind farms was identified by the combined use of Stepwise Weight Assessment Ratio Analysis and Weighted Aggregated Sum Product Assessment. The results showed that the most proper site for locating wind farms in the study area is the city of Al-Qurrayyat, where, using 1 MW turbines, it will be possible to produce 2357 MWh/year of electricity at a cost of 0.092 $/kWh, resulting in a payback period of 8.1 years. From the environmental perspective, wind power generation in Al-Qurrayyat will result in 1124.15 ton/year of CO2 emissions reduction.

Golden Cut-Oriented Q-Rung Orthopair Fuzzy Decision-Making Approach to Evaluation of Renewable Energy Alternatives for Microgeneration System Investments

This study aims to find an appropriate system for microgeneration energy investments and identify optimal renewable energy alternatives for the effectiveness of these projects. In this context, a model is constructed by multi stepwise weight assessment ratio analysis (M-SWARA) and technique for order preference by similarity to ideal solution (TOPSIS) with q-rung orthopair fuzzy sets (q-ROFSs) and golden cut. At the first stage, five different systems are weighted for the effectiveness of the microgeneration energy investments. Secondly, four different renewable energy alternatives are ranked regarding the performance of these projects. In addition, a comparative analysis is also implemented with intuitionistic fuzzy sets (IFSs) and Pythagorean fuzzy sets (PFSs). The findings are the same in all different fuzzy sets that demonstrates the reliability of the findings. It is determined that grid-connected with battery backup is the most important system choice. On the other hand, solar energy is the most appropriate alternative for microgeneration system investments. Grid-connected system should be implemented for the performance of the microgeneration projects. Hence, providing a sustainable access to the electricity can be possible. Sufficient amount of electricity may not be obtained from wind and solar energy because of the climate changes. In this process, grid-connected system can handle this problem effectively.

Selection of Plant Location for Hemp Fibre Production in TR72 Region

This study has emerged within the scope of the sectoral studies requested by the Ministry of Industry and Technology of Turkish Republic from the Development Agencies, and aims to select the optimal plant location among the organized industrial zones in the TR72 Region consisting of Kayseri, Sivas and Yozgat provinces in order to produce processed fibre from the raw fibre obtained as a by-product of hemp cultivation. The criteria such as parcel unit price, electricity unit price, service water unit price, waste water unit price, natural gas unit price, insurance premium employer's share support period, investment contribution rate for insurance premium employer’s share support, tax reduction rate, investment contribution rate for tax reduction, interest or profit share support, access to raw material sources, access to market and access to qualified labour supply that form the basis for the selection of plant location were determined and weighted according to the Stepwise Weight Assessment Ratio Analysis (SWARA) method The most available plant location among the emerging alternatives was determined by using Multi-Criteria Decision Making Methods consisting of Combined Comprimise Solution (COCOSO), Complex Proportional Assessment (COPRAS) and Multi-Attributive Ideal-Real Comparative Analysis (MAIRCA). Consequently, it was concluded that Kaleseramik Private Organized Industrial Zone (OIZ) located in Yozgat province is the most available plant location among the other seven alternatives.

Coalition-oriented strategic selection of renewable energy system alternatives using q-ROF DEMATEL with golden cut

Hybrid energy investment projects help to increase the efficiency in renewable energy production. This situation can be a solution to the high installation cost problem of the clean energy investments. While examining similar studies in the literature, it is determined that there is a need for a new study to identify the optimal combinations of the renewable energy alternatives to increase the effectiveness of the hybrid energy investments. This study aims to identify coalition-oriented strategic selection of renewable energy system alternatives. Several combinations are weighted by q-rung orthopair fuzzy (q-ROF) decision making trial and evaluation laboratory (DEMATEL) with golden cut and coalition game theory. Intuitionistic fuzzy sets (IFSs) and Pythagorean fuzzy sets (PFSs) are also used to check the validity of the findings. Moreover, multi stepwise weight assessment ratio analysis (M-SWARA) methodology is also considered to measure the consistency of the analysis results. It is defined that solar is the most efficient energy alternative for the hybrid energy investments. Solar energy should be prioritized in hybrid investment projects where at least two of the renewable energy alternatives are evaluated together. The usage area of solar energy is wide because it is not necessary to be close to the water source or the city network to install solar panels. Additionally, solar energy systems generally do not require much maintenance that provides a cost advantage compared to others. Owing to these issues, solar energy projects provide the highest contribution in all investment combinations. The novelty of this paper is to provide a unique model by combining the methodology of q-ROF and golden cut properly with the aim of proposing a set of renewable energy system combinations in terms of coalition game theory.

An economic investigation of the wind-hydrogen projects: A case study

Hydrogen as an energy carrier can play a significant role in reducing environmental emissions if it is produced from renewable energy resources. This research aims to assess hydrogen production from wind energy considering environmental, economic, and technical aspect for the East Azerbaijan province of Iran. The economic assessment is performed by calculation of payback period, levelized cost of hydrogen, and levelized cost of electricity. Since uncertainty in the power output of wind turbines may affect the payback period, all calculations are performed for four different turbine degradation rates. While it is common in the literature to choose the wind turbine based on a single criterion, this study implements Multi-Criteria Decision-Making (MCDM) techniques for this purpose. The results of Step-wise Weight Assessment Ratio Analysis illustrates that economic issue is the most important criterion for this research. The results of Weighted Aggregated Sum Product Assessment shows that Vestas V52 is the most suitable wind turbine for Ahar and Sarab cities, while Eovent EVA120 H-Darrieus is a better choice for other stations. The most suitable location for wind power generation is found to be Ahar, where it is estimated to annually generate 2914.8 kWh of electricity at the price of 0.045 $/kWh, and 47.2 tons of hydrogen at the price of 1.38 $/kg, which result in 583 tons of CO2 emission reduction.

Sustainable assessment for selecting the improved air quality technology under hesitant bipolar fuzzy

Due to increasing population and urbanization, it is a complex task to find a better solution to control air pollution without impact on humans. But in this vast world there are numerous technologies and possibilities remain to control air pollution. The possibilities to improve air quality is attained by using a Multi Criteria Decision Making (MCDM) method. The selection of cost effective and efficient improved air quality technologies ensures sustainable development. Thus, in the present study we provide a new version of the Complex Proportional Assessment (COPRAS) method and Stepwise Weight Assessment Ratio Analysis (SWARA) to Hesitant Bipolar Fuzzy (HBF) for the selection of Air Quality Technology (AQT) alternatives. The Hesitant Bipolar Fuzzy Numbers (HBFNs) are used by analysts to assign the preferences of alternatives on the basis of criteria. The study proposes an integrated approach based on SWARA and COPRAS method within the HBFs context named as, HBF-SWARA-COPRAS method. In the integrated framework, the criteria weights are determined by the SWARA process and the ranking of the alternatives is determined by the COPRAS method using HBFs. In addition, sensitivity analysis is also performed to check the stability of the presented methodology.

Application of M-SWARA and TOPSIS Methods in the Evaluation of Investment Alternatives of Microgeneration Energy Technologies

Investments in microgeneration technologies help to boost the usage of clean energy while reducing pollution. However, selecting the appropriate investment remains the most critical phase in developing these technologies. This study aims to design a multi-criteria decision-making method (MCDM) to evaluate investment alternatives for microgeneration energy technologies. The proposed MCDM is based on a Multi Stepwise Weight Assessment Ratio Analysis (M-SWARA), to define the relative importance of the factors. The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and q-Rung Orthopair Fuzzy Soft Sets (q-ROFSs) are used to rank investment alternatives. Calculations were also made with Intuitionistic Fuzzy Sets (IFSs) and Pythagorean Fuzzy Sets (PFSs). For analysis, five evaluation criteria were selected based on the literature: frequency of maintenance, ease of installation, environmental adaptation, transmission technologies, and efficiency of cost. Similarly, six alternatives for microgeneration technology investments were selected: ground source heat pumps, micro hydroelectric power, micro combined heat and power, micro bioelectrochemical fuel cell systems, small-scale wind turbines, and photovoltaic systems. The results showed that cost efficiency was the most significant factor in the effectiveness of microgeneration energy investments, and the photovoltaic system was the best alternative to increase microgeneration energy technology investment performance. Furthermore, the results were the same for the analyses made with IFSs and PFSs, demonstrating the reliability of the proposed method. Therefore, investors in microgeneration technologies should prioritize photovoltaic systems. This conclusion is supported by the fact that photovoltaic is a renewable energy source that has witnessed the most technological improvements and cost reductions over the last decade.

Comparative analysis of multicriteria decision‐making approaches for evaluation hydrogen projects development from wind energy

Nowadays energy demand has increased due to industrial development and population growth. On the other hand, attention to environmental issues has made it necessary to use renewable energy. The utilization of wind energy is emphasized due to low construction costs and rapid installation. Wind energy, on the other hand, can be stored via creating hydrogen because its power fluctuates at different times and is not uniform. The production of hydrogen and energy is essential to meet the needs of industries in different countries. Therefore, in this study, a comprehensive approach is presented to locating hydrogen production from wind energy using multicriteria decision-making (MCDM). To implement the proposed approach, a case study in Iran and Hormozgan province is used. Hormozgan province is in good condition in terms of wind potential and many industries in this province need energy and hydrogen. The most appropriate factors were judged to be average wind speed, each region's number of refineries, and each region's rate of industrial development, with weights of 0.192, 0.167, and 0.141, respectively, using the stepwise weight assessment ratio analysis (SWARA) approach. The cities in Hormozgan province were then prioritized using the weighted aggregated sum product assessment (WASPAS) technique. Then, the sensitivity analysis of the ranking results was performed and The COmplex PRoportional ASsessment (COPRAS), additive ratio assessment (ARAS), and weighted sum methods (WSM) methodologies were then used to validate the results. For the development of hydrogen projects, Bandar Abbas was determined as the most suitable place. A 900-kW turbine at Bandar Abbas will generate 532 730 kWh of power and 8620 kg of hydrogen annually.

RETRACTED ARTICLE: Evaluate the challenges of sustainable supply chain 4.0 implementation under the circular economy concept using new decision making approach

Industry 4.0 has the potential of growing industrialization and, on the other hand, disrupting the sustainability of prevailing manufacturing supply chains through inducing great challenges such as higher resource consumption that, in turn, results in global warming and climate change. As a result, researchers working in the area of sustainable supply chain 4.0 need to make deep evaluations on the challenges arising for manufacturing supply chains contemplating the improvement of their sustainability levels and having a digital transformation toward Industry 4.0. To fill this gap, the current paper designs an innovative framework on the basis of the Stepwise Weight Assessment Ratio Analysis (SWARA) technique and the Complex Proportional Assessment (COPRAS) approach to evaluate the challenges that may arise for supply chain 4.0 in the q-Rung Orthopair Fuzzy Sets (q-ROFSs) setting. The proposed method uses an extended SWARA process to determine the criteria importance degrees considering the experts’ preferences. The performance of the proposed method was assessed by conducting an empirical case study under the q-ROFSs condition. Further, a sensitivity analysis was executed to check whether the proposed method is stable enough to be relied on parameter values. Finally, the results obtained were compared to those of currently used methods to verify the obtained results’ reliability. As revealed by the comparative results, the framework proposed in this article was of higher consistency and strength compared to other prevailing approaches.