Step-wise Weight Assessment Ratio Analysis Research Articles

“A multi-tier sustainable food supplier selection model under uncertainty”

Supplier selection in food supply chains (FSCs) is not much explored due to the inherent difficulties, complexities and nature of food industry. Food security and quality are top row topics in today’s world health scenario. During sudden food crisis, it needs extra attention where producers, suppliers, and stakeholders play the most vital roles. This paper puts forward a two-phase sustainable multi-tier supplier selection model for FSC based on an integrated decision analysis under multi-criteria perspectives considering sustainability criteria, suppliers and sub-suppliers. In the first phase, the model estimates supplier selection criteria weights using a combined version of step-wise weight assessment ratio analysis (SWARA) and level based weight assessment (LBWA) in conjunction with D-numbers. In the second phase, Measurement of Alternatives and Ranking according to the COmpromise Solution (MARCOS)-D method is applied to obtain a ranking pre-order of different tier suppliers. Moreover, several sensitivity analyses are carried out in order to examine model reliability. To check application practicability, the proposed model is implemented in a case study of WineSol Corporation in Spain. The proposed model is expected to serve as a kickoff point for developing advanced decision-making models for effectually address multi-tier supplier selection problems under uncertain environment.

Developing a new framework for conceptualizing the emerging sustainable community-based tourism using an extended interval-valued Pythagorean fuzzy SWARA-MULTIMOORA

During these years, the sustainable Community-Based Tourism (CBT) notion has received more attention in the context of the tourism industry. Sustainable CBT mainly emphasizes social, environmental, and cultural sustainability and gives power to local communities in any aspect of tourism management. This manuscript aims to propose a novel approach to examine the current status of sustainable CBT in the Indian Himalayan region context. In this regard, a comprehensive framework was developed using experts’ opinions, and the relevant literature in tourism studies was reviewed based on sustainable CBT. To this end, this study proposed an integrated decision-making method using Step-wise Weight Assessment Ratio Analysis (SWARA) and MULTIMOORA (Multiple Objective Optimization based on the Ratio Analysis plus Full Multiplicative Form) under Interval-Valued Pythagorean Fuzzy Sets (IVPFSs). Additionally, some comparisons were discussed with the outcomes obtained from the developed approach and those of extant ones to evaluate the efficiency of the proposed model. To confirm the applicability of the proposed IVPF-SWARA-MULTIMOORA approach to real-world decision-making problems, a sustainable CBT problem was considered as a case study. The final results confirmed the efficiency of the proposed approach as well as its consistency with the existing ones.

Internet of Things (IoT) adoption barriers for the circular economy using Pythagorean fuzzy SWARA-CoCoSo decision-making approach in the manufacturing sector

The growth of new cutting-edge technologies such as the Internet of Things (IoT) is proposed by the industry 4.0 concept. Despite the vast potential of IoT to be used in the circular economy, the adoption of IoT is still in its primary step. This study aims to identify the important barriers to the adoption of IoT in the circular economy in the manufacturing sector. To this end, a survey study was conducted to construct a framework for the evaluation of the IoT adoption barriers in the circular economy. Therefore, a novel method integrating the Stepwise Weight Assessment Ratio Analysis (SWARA) and Combined Compromise Solution (CoCoSo) methods based on Pythagorean Fuzzy Sets (PFSs) was proposed. In this method, the SWARA model is used to estimate the significance degree or weighting degrees of the barriers, while the CoCoSo method is applied to ranking various organizations in the manufacturing sector under the identified barriers. To show the performance of the developed approach, a comparison analysis is performed of the selection of qualified organizations. The outcome of this study indicated that the developed approach was able to suggest more realistic performance under PFSs, hence providing a wide range of applications.

A new Pythagorean fuzzy-based decision-making method through entropy measure for fuel cell and hydrogen components supplier selection

While fuel cell combined with hydrogen (FCH) technology is still largely in its infancy striving to find its footing, the present market stage towards commercialisation is bridged by the pervasive research and development (R&D) and innovation. Providing spare parts and auxiliary components of the FCH systems plays a significant role in advancing the process. For the successful transition, an optimal supplier selection function can flourish the long-term research, and further, address the lack of technological knowledge to manufacture high performance and affordable components. This paper presents an integrated approach based on entropy, Step-wise Weight Assessment Ratio Analysis (SWARA) and Complex Proportional assessment (COPRAS) methods under the Pythagorean fuzzy environment for the FCH supplier selection. In this method, the criteria weights were first calculated by combining the objective weights determined by the entropy-based approach and the subjective weights by the SWARA method. For this purpose, a new entropy measure was proposed through the Pythagorean fuzzy set as one of the new flexible tools to handle the uncertain and inaccurate information arisen in complex MCDM problems. An integrated approach developed in this study can overcome the insufficiencies which arise either in an objective-weighting model or a subjective-weighting model. COPRAS was then utilised to evaluate the ranking order of the alternatives. A real-world case study of the FCH components supplier selection problem was considered to implement the proposed integrated approach. Finally, a comparison and sensitivity analysis were discussed to illustrate the usefulness of the proposed method.

An extended hesitant fuzzy set using SWARA-MULTIMOORA approach to adapt online education for the control of the pandemic spread of COVID-19 in higher education institutions.

The world has been challenged since late 2019 by COVID-19. Higher education institutions have faced various challenges in adapting online education to control the pandemic spread of COVID-19. The present study aims to conduct a survey study through the interview and scrutinizing the literature to find the key challenges. Subsequently, an integrated MCDM framework, including Stepwise Weight Assessment Ratio Analysis (SWARA) and Multiple Objective Optimization based on Ratio Analysis plus Full Multiplicative Form (MULTIMOORA), is developed. The SWARA procedure is applied to the analysis and assesses the challenges to adapt the online education during the COVID-19 outbreak, and the MULTIMOORA approach is utilized to rank the higher education institutions on hesitant fuzzy sets. Further, an illustrative case study is considered to express the proposed idea's feasibility and efficacy in real-world decision-making. Finally, the obtained result is compared with other existing approaches, confirming the proposed framework's strength and steadiness. The identified challenges were systemic, pedagogical, and psychological challenges, while the analysis results found that the pedagogical challenges, including the lack of experience and student engagement, were the main essential challenges to adapting online education in higher education institutions during the COVID-19 outbreak.

Supply chain contract selection in the healthcare industry: a hybrid mcdm method in uncertainty environment

The aim of this research study is to address a critique of how and when a supply chain contract is selected based on critical success factors (CSFs) utilizing stepwise weight assessment ratio analysis (SWARA) and Evaluation by an Area-based Method of ranking (EAMR). This research study ranked supply chain contracts by the EAMR in uncertainty environments, such as when breaking down the health care industry. This is done by providing a theoretical framework for sustainable entrepreneurship in telecommunications industry, focusing on managerial and operational practices that should be modified, in accordance to a set of CSFs identified from experts in fertility hospital. As a novel strategy, in this research, the initial factors of selecting customized Supply Chain Management (SCM) were extracted via a Delphi method along with the EAMR to symbolize a decision matrix that needs primary weights acquired through the SWARA method by hesitant fuzzy number. CSFs for achieving SCM contract selection in fertility hospitals were found to rely on a tripod based on effectiveness, transparency, and accountability that are embedded within the ambit of managerial and operational practices, such as focusing and reducing cost and based on these factors the best SCM contract must be selected. Besides, the EAMR method has more reliability than other similar MCDM methods such as TOPSIS, MOORA, VIKOR, and so on main contribution of this paper is the combination of SWARA, EAMR, and using hesitant fuzzy set in the EAMR method. Finally, the result indicates that hospitals based on these CSFs must be selected contracts.

Modelling flexible decisions about sustainable supplier selection in multitier sustainable supply chain management

Supplier selection is crucial decision for buying companies to develop sustainable supply chain strategy. Not only first-tier suppliers but also lower-tier suppliers would influence the buyer’s sustainability performance. Thus, buying companies need to consider extending their sustainable supply chain plan to multitier suppliers, and develop multitier sustainable supply chain management (MT-SSCM). Sustainable supplier selection (SSS), as an important SSCM practice, can effectively enhance the sustainable competitiveness of supply chains. However, there are few theoretical studies on SSS under MT-SSCM, which affects the decision-making efficiency of organisations. In general, there are three multitier supply chain (MTSC) structures: open MTSC, closed MTSC and transitional MTSC structures. Because some traditional decision models cannot deal with a variety of structures at the same time, this study proposes a hybrid model that integrates fuzzy set theory, stepwise weight assessment ratio analysis and a Bayesian network to evaluate the critical SSS criteria in three MTSC structures. Finally, a case of a Chinese buying company is used to verify the flexibility and applicability of the proposed model, and some suggestions are provided for the practitioners to select sustainable suppliers in different MTSC structures.

New hybrid evolutionary algorithm for optimizing index-based groundwater vulnerability assessment method

Limited hydrogeological data accessibility leads scholars to improve the robustness of present qualitative groundwater vulnerability assessment methods using mathematical techniques. In the present study, we implemented three GIS-based groundwater vulnerability assessment indices, namely DRASTIC (Depth to water table, net Recharge, Aquifer media, Soil media, Topography, Impact of vadose zone, and hydraulic Conductivity), SINTACS (Soggicenza, Infiltrazione, Non saturo, Tipologia della copertura, Acquifero, Conducibilità, and Superficie topografica), and GODS (Groundwater confinement, Overlying strata, Depth to groundwater, and Soil media) to assess the groundwater vulnerability levels. Although DRASTIC results showed better performance with respect to the nitrate concentration data from 50 observation wells in the study site, the index is still unreliable due to its inherent drawbacks, including subjectivity. Hybrid PSO-GA method is a successful optimization algorithm gathering the advantages of Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) while avoiding their shortcomings. The DRASTIC weighting system is optimized using PSO-GA optimization algorithm. Also, Step-wise Weight Assessment Ratio Analysis (SWARA) as a Multi-Attribute Decision Making (MADM) method is applied for changing ranges of DRASTIC rates and weights. The vulnerability indices obtained from SWARA-SWARA, DRASTIC-PSO-GA, and SWARA-PSO-GA frameworks are evaluated and compared with generic DRASTIC regarding the nitrate concentration dataset by employing Area Under the ROC Curve (AUC) and Grey relational analysis methods. Results show a noticeable improvement of correlation between indices and observed nitrate concentration after modifications and optimizations. The new hybrid SWARA-PSO-GA framework is the most effective framework in assessing the vulnerability of the present study area.

An extended framework to evaluate sustainable suppliers in manufacturing companies using a new Pythagorean fuzzy entropy-SWARA-WASPAS decision-making approach

PurposeThe purpose of this study to introduce a new extended framework to evaluate and rank the sustainable suppliers based on the different sustainable criteria in the manufacturing companies using a new fuzzy decision-making approach.Design/methodology/approachThis paper introduces a new approach using decision-making and Pythagorean fuzzy sets (PFSs) to assess the best sustainable supplier. To doing so, this study integrated the entropy, stepwise weight assessment ratio analysis (SWARA) and weighted aggregates sum product assessment (WASPAS) methods under PFSs. To calculate the criteria weights, the combined entropy-SWARA method is used to compute the objective weight and subjective weight, respectively. Furthermore, the WASPAS model is utilized to rank sustainable supplier alternatives.FindingsThe results of the analysis found that occupational health and safety systems had the highest rank among other criteria, followed by green product and eco-design, green R&D and innovation and green technology. In addition, the findings of the paper demonstrated that the extended approach was efficient and useful for selecting and evaluating the best sustainable supplier in the manufacturing companies.Originality/valueRecent years have witnessed a number of studies aimed at incorporating the sustainability standards into the supplier selection problem; however, only a little research has been conducted on developing a fuzzy method for decision-making in a manner to assess and choose suppliers with high sustainability in the insurance market, encompassing the three above-mentioned sustainability criteria.

A GREY HYBRID MODEL TO SELECT THE OPTIMAL THIRD-PARTY LOGISTICS PROVIDER

Enterprises need to work with a proper third-party logistics provider to reduce costs and increase their logistics performance; so the third-party logistics (3PL) provider selection problem is a significant one for them. In this study, grey step-wise weight assessment ratio analysis (SWARA) and grey combinative distance-based assessment (CODAS) are proposed to address this problem. To the best of the authors’ knowledge, no other study uses grey SWARA and grey CODAS together to solve any problem. Therefore a new grey hybrid model incorporating grey SWARA and grey CODAS is proposed to identify the best 3PL provider.

Issues and solutions of electronic waste urban mining for circular economy transition: An Indian context

The rapid consumption of advanced e-products has intensified problems for the linear economy; constantly diminishing natural resources employed in production processes have created a need of recycle and reuse. Although the transition to a circular economy proposes to end the loop of e-products, it needs the application of processes such as urban mining to recover resources as secondary raw material. The present study intends to examine the issues and challenges of electronic waste urban mining (EWUM) in India that need to be assessed for the development of a sustainable economy. To accomplish this, the current study employs integrated Multi-Criteria-Decision making methods (MCDM). Step-Wise Weight Assessment Ratio Analysis (SWARA) is used to prioritize issues and their possible solutions with Weighted Assessment Sum Product Assessment (WASPAS) methods introduced to explore these challenges and provide solutions for managing EWUM. There is an immediate need to acknowledge the issues confronted by stakeholders in urban mining processes for successful transition to a circular economy. A better understanding of the issues will help policy makers and decision makers to implement best practices to enhance the urban mining process in India. This study has shown that socio-economic (SE) issues are the most critical issues in EWUM in India. The possible solutions that would have most impact are to enhance awareness campaigns for people to educate themselves regarding e-waste, train staff to handle safe disposal of e-waste and produce eco-friendly electronic products.

A thorough investigation for development of hydrogen projects from wind energy: A case study

Increasing energy demand has led to a substantial growth in the use of wind energy across the world, which can be attributed to the low initial and running costs and rapid and easy deployment of this technology. The development of hydrogen from wind energy is an excellent way to store the excess wind power produced, as the produced hydrogen can be used not only as clean fuel but also as input for various industries. Considering the good wind potentials of Yazd province, the variety of industries that are active in this area, and the central location of this province in Iran, which gives it ample access to major transport routes and other industrial hubs, hydrogen production from wind power in this province could benefit not only this region but the entire country. Given these considerations, we conducted a technical, economic, and environmental assessment of the potential for wind power generation and hydrogen production in Yazd province. Overall, the assessments showed that the best locations for harvesting wind energy in this province are Bahabad and Halvan stations. For these two stations, it is recommended to use EWT DW 52-900 turbine to take advantage of its higher nominal capacity to achieve higher electricity and hydrogen output and emission reduction. For Abarkoh and Kerit stations, which have a low wind energy potential, it is recommended to use small turbines such as Eovent EVA120 H-Darrieus. Also, economic and technical assessments showed that it is not economically justified to harvest wind energy in Ardakan station. The results of ranking the stations with the Step-wise Weight Assessment Ratio Analysis (SWARA) and Evaluation based on Distance from Average Solution (EDAS) techniques showed that Bahabad station was introduced as the best place to produce hydrogen from wind energy.

A framework for interactive risk assessment in projects: case study of oil and gas megaprojects in presence of sanctions

PurposeThis study aims to investigate the interactive network of risk factors in the construction and preparation project of gas condensate storage tanks in the presence of sanctions.Design/methodology/approachFirst, this paper determines and weighs the project goals using the stepwise weight assessment ratio analysis method. Then, this study identifies and categorizes the project risks and form the network of the project risk factors based on the weight of the project goals by using interpretive structural modeling and decision-making trial and evaluation laboratory techniques.FindingsThe results of the current work divide the risks of such projects into five financial, technical, managerial and contractual, social and environmental and political categories. The analyzes indicate the complicated risk network and the cause-and-effect interactions between the risks. The findings identify the financial and political risk clusters as the most effective category and select the technical, managerial and contractual and social and environmental risk clusters as the most affected categories. The technical risk has the least important among the others under the sanction conditions.Originality/valueThis paper model the domino effect of the risk factors considering the complicated interactions and the cause-and-effect relations in a network. Moreover, this study discusses the importance of the risk factors in oil and gas megaprojects in the presence of sanctions. Finally, this paper applies the proposed approach to a real case study in the field of gas projects.

Risk Assessment of Logistics Enterprises Using FMEA Under Free Double Hierarchy Hesitant Fuzzy Linguistic Environments

Failure Mode and Effects Analysis (FMEA) is an effective tool for prioritization of the failures by identifying and eliminating potential risks, free double hierarchy hesitant fuzzy linguistic term set (FDHHFLTS) can describe the hesitation more accurately and reasonably by adding the free second hierarchy hesitant fuzzy linguistic terms, and multiattribute decision-making (MADM) methods have advantages in ranking and selecting different alternatives. By considering the advantages of MADM methods and FMEA model, in this paper, we propose a novel model to evaluate the risk failure modes (FMs) under FDHHFLTS context. First, an extended Complex Proportional Assessment (COPRAS) method is proposed to address the risk assessment problems. The proposed risk assessment model is utilized to assess and rank the FMs to address the limitations of the traditional FMEA. Second, a weight determination model is constructed based on the Kemeny Median (KEM) method and Stepwise Weight Assessment Ratio Analysis (SWARA) method, which can make the weight more practical and effective under the situation of completely unknown weights. Finally, the proposed model is used to the case of logistics enterprises’ risk assessment. The application of the case shows the feasibility of the proposed model, and the comparisons with some existing methods illustrate the advantages of the proposed risk assessment model.

Theory-Based Failure Modes and Effect Analysis for Medication Errors.

Medication Errors (MEs) are still significant challenges, especially in nonautomated health systems. Qualitative studies are mostly used to identify the parameters involved in MEs. Failing to provide accurate information in expert-based decisions can provoke unrealistic results and inappropriate corrective actions eventually. However, mostly, some levels of uncertainty accompany the decisions in real practice. This study tries to present a hybrid decision-making approach to assigning different weights to risk factors and considering the uncertainty in the ranking process in the Failure Modes and Effect Analysis (FMEA) technique. Initially, significant MEs are identified by three groups of qualified experts (doctors, nurses, and pharmacists). Afterward, for assigning weights to the risk factors, Z-number couples with the Stepwise Weight Assessment Ratio Analysis (SWARA) method, named Z-SWARA, to add reliability concept in the decision-making process. Finally, the identified MEs are ranked through the developed Weighted Aggregated Sum Product Assessment (WASPAS) method, namely, Z-WASPAS. To demonstrate the applicability of the proposed approach, the ranking results compare with typical methods, such as fuzzy-WASPAS and FMEA. The findings of the present study highlight improper medication administration as the main failure mode, which can result in a fatality or patient injury. Moreover, the utilization of multiple-criteria decision-making methods in combination with Z-number can be a useful tool in the healthcare management field since it can address the problems by considering reliability and uncertainty simultaneously.

A Congruent Approach to Normal Wiggly Interval-Valued Hesitant Pythagorean Fuzzy Set for Thermal Energy Storage Technique Selection Applications

Thermal energy is the energy from a substance in which molecules and atoms vibrate faster because of an increase in temperature. Thermal energy storage (TES) is an available energy resource for renewable energy platforms that enables them to meet sustainable technical requirements. The TES technique is divided into three categories; sensible TES, latent-heat TES, and thermo-chemical TES. The best of these techniques is selected in this research paper. Here the Interval-Valued Hesitant Pythagorean Fuzzy Set (IVPHFS) under the Normal Wiggly Mathematical Methodology is proposed and described for application to multi-criteria decision making (MCDM) technology. The MCDM methods, the Step-wise Weight Assessment Ratio Analysis (SWARA) method for determining weight values, and the Weighted Aggregated Sum Product Assessment (WASPAS) method for ranking alternative values are used employed here. The alternative values are selected based on the following criteria: capacity, efficiency, storage period, charging and discharging times, and cost

A hybrid model for ranking critical successful factors of Lean Six Sigma in the oil and gas industry

PurposeThe aim of this paper is to find and prioritise multiple critical success factors (CSFs) for the implementation of LSS in the oil and gas industry.Design/methodology/approachBased on a preselected list of possible CFSs, experts are involved in screening them with the Delphi method. As a result, 22 customised CSFs are selected. To prioritise these CSFs, the step-wise weight assessment ratio analysis (SWARA) method is applied to find weights corresponding to the decision-making preferences. Since the regular permutation-based weight assessment can be classified as NP-hard, the problem is solved by a metaheuristic method. For this purpose, a genetic algorithm (GA) is used.FindingsThe resulting prioritisation of CSFs helps companies find out which factors have a high priority in order to focus on them. The less important factors can be neglected and thus do not require limited resources.Research limitations/implicationsOnly a specific set of methods have been considered.Practical implicationsThe resulting prioritisation of CSFs helps companies find out which factors have a high priority in order to focus on them.Social implicationsThe methodology supports respective evaluations in general.Originality/valueThe paper contributes to the very limited research on the implementation of LSS in the oil and gas industry, and, in addition, it suggests the usage of SWARA, a permutation method and a GA, which have not yet been researched, for the prioritisation of CSFs of LSS.

Application of SWARA Technique to Find Criteria Weights for Selecting Landfill Site in Baghdad Governorate

In this study, Stepwise Weight Assessment Ratio Analysis (SWARA) is one of multi-criteria decision-making methods (MCDM). SWARA used to define the weights of main criteria and sub-criteria for selecting landfill sites in Baghdad governorate for municipality solid waste. To control of the environmental pollution and the spread of municipality solid waste in irregular sites, SWARA was used for this matter. The alternative Landfill site selection must be properly selected in terms of environmental, social and geological criteria. The obtained results of this study, the most important criteria for selecting municipality solid waste landfill sites were determined. Based on that, the ranking weights of main criteria and sub-criteria for selecting the landfill site for solid waste in Baghdad governorate were founds.

Integration of Rough SWARA and COPRAS in the Performance Evaluation of Third-Party Logistics Providers

Currently, the use of logistics service providers in companies has become a decision chosen by several companies. Companies use Third Party Logistics (3PL) to focus more on other essential activities in the company. Evaluating the performance of a 3PL provider is an essential process in determining performance of a 3PL provider. A wrong evaluation process could lead to company’s loss. The main objective of this study was to propose a 3PL performance appraisal procedure. This study integrated the Rough method Step-wise Weight Assessment Ratio Analysis (SWARA) and the Complex Proportional Assessment Method (COPRAS) to assess the performance of 3PL providers. The SWARA Rough method was used to assess the ranking of the criteria. The results of the Rough SWARA ranking were utilized by the COPRAS method to assess supplier performance. A case study was conducted in an animal feed production company in Indonesia. The results showed that there were criteria for product safety; on-time delivery, responsiveness, and flexibility with the greatest weight among the 16 criteria used.

A New Hybrid Fuzzy Model: Satisfaction of Residents in Touristic Areas toward Tourism Development

This research brings a practical approach to the issue of the level of satisfaction from residents in tourist destinations by using three attractive methods together. After reviewing the theoretical foundations and the meta-synthesis method in identifying indicators, fuzzy Delphi was used for screening, fuzzy SWARA (stepwise weight assessment ratio analysis) for weighting, and fuzzy EDAS (evaluation based on distance from average solution) for 16 very important tourism areas in Iran. Six important factors (economic, cultural, environmental, perceptual, social, and health) along with 42 important criteria were identified in the meta-combination method, while also obtaining the total weight of the indicators. Finally, the sensitivity analysis of the model is performed and practical suggestions presented.