Fuzzy Multi-criteria Decision-making Approach Research Articles

A Fuzzy Multi-Criteria Method for Sustainable Ferry Operator Selection: A Case Study

This study is motivated by the Zhuhai municipal government, which needs to select a sustainable ferry operator. Previous research has ignored the evaluation and selection of ferry operators. In addition, since ferry operator evaluation involves conflicting qualitative and quantitative criteria, and there may be uncertainty and ambiguity in the evaluation of criteria by experts, a fuzzy multi-criteria decision-making (MCDM) approach is required to address this challenge. To this end, this paper proposes an integrated MCDM framework model to evaluate and select the best ferry operator. First, a ferry operator evaluation index system with 15 sub-criteria is constructed according to literature and expert opinions; then the fuzzy analytic hierarchy process (FAHP) is used to determine the subjective weight of the criteria, and the entropy weight (EW) method is used to calculate the objective weight of the criteria. We use the linear weighting method to obtain the comprehensive weights of the criteria; finally, the fuzzy technique for order preference by similarity to ideal solution (FTOPSIS) method is adapted to determine the best ranking of the alternatives. This paper takes the Wanshan Islands in Zhuhai as a real case study to verify the proposed FAHP-EW-FTOPSIS method. The results show that the proposed method can be effectively applied to the evaluation and selection of ferry operators. Sensitivity analysis of criteria weights demonstrates the effectiveness and robustness of the proposed framework model. Key findings based on the research provide management insights that can benefit relevant stakeholders. This is the first paper to study the evaluation and selection of ferry operators. Hence, the evaluation index system and integrated framework model proposed in this paper can make important contributions to the evaluation of ferry operators.

An Extended ORESTE Approach for Evaluating Rockburst Risk under Uncertain Environments

Rockburst is a severe geological disaster accompanied with the violent ejection of rock debris, which greatly threatens the safety of underground workers and equipment. This study aims to propose a novel multi-criteria decision-making (MCDM) approach for evaluating rockburst risk under uncertain environments. First, considering the heterogeneity of rock mass and complexity of geological environments, trapezoidal fuzzy numbers (TrFNs) are adopted to express initial indicator information. Thereafter, the superiority linguistic ratings of experts and a modified entropy weights model with TrFNs are used to calculate the subjective and objective weights, respectively. Then, comprehensive weights can be determined by integrating subjective and objective weights based on game theory. After that, the organísation, rangement et synthèse de données relarionnelles (ORESTE) approach is extended to obtain evaluation results in a trapezoidal fuzzy circumstance. Finally, the proposed approach is applied to assess rockburst risk in the Kaiyang phosphate mine. In addition, the evaluation results are compared with empirical methods and other trapezoidal fuzzy MCDM approaches. Results show that the proposed extended ORESTE approach is reliable for evaluating rockburst risk, and provides an effective reference for the design of prevention techniques.

Combination of Fuzzy-Weighted Zero-Inconsistency and Fuzzy Decision by Opinion Score Methods in Pythagorean m-Polar Fuzzy Environment: A Case Study of Sign Language Recognition Systems

In the fuzzy multicriteria decision-making approach, a committee of decision-makers is usually involved in the assessment of the suitability of different alternatives based on the evaluation criteria by using linguistic terms and their equivalent fuzzy numbers. In this context, researchers have developed the Pythagorean fuzzy set (PFS) to overcome the limitation of intuitionistic fuzzy set in the description of decision-maker information such as imposing restrictions on the representation of membership and nonmembership grades. On the one hand, PFS still does not have sufficient ability and flexibility to deal with such issues. On the other hand, multipolar technology is used to operate large-scale systems in real-life situations, especially in dealing with dissatisfaction and indeterminacy grades for the alternatives of the reference set. Thus, m-polar fuzzy set is utilized and applied with other fuzzy sets because of its remarkable ability as a tool for depicting fuzziness and uncertainty under multipolar information in many circumstances. With the practical features of m-polar fuzzy set in combination with PFS, this paper employs it to extend two considerable MCDM methods, namely, fuzzy decision by opinion score method and fuzzy-weighted zero inconsistency. Such extensions, called Pythagorean m-polar fuzzy-weighted zero-inconsistency (Pm-PFWZIC) method and Pythagorean m-polar fuzzy decision by opinion score method (Pm-PFDOSM), are formulated to weight the evaluation criteria followed by alternative ranking progressively. The research methodology is presented as follows. Firstly, the mechanisms of Pm-PFWZIC and Pm-PFDOSM are formulated and integrated into the development phase. Secondly, the description of the real-world case study of the evaluation and benchmarking of the sign language recognition systems is adapted and presented. The result of Pm-PFWZIC shows that the criterion of ‘finger movements’ has the highest weight amongst the rest of the criteria, whereas ‘misclassification error’ has the lowest weight. In the ranking results, a variation of ranking is scored by each expert, and group decision-making is applied to solve the individual ranking variety. The robustness of the formulated methods is evaluated using systematic ranking, sensitivity analysis and comparison analysis.

Analyzing the impact of COVID-19 vaccination requirements on travelers’ selection of hotels using a fuzzy multi-criteria decision-making approach

In the later stages of the COVID-19 pandemic, hotels are taking various measures to balance pandemic prevention and business operations. Some hotels require travelers to be fully vaccinated prior to check-in, while others do not. In the latter type of hotels, fully vaccinated travelers may encounter others who are not vaccinated. All of these have created constraints for travelers to choose suitable hotel accommodation during this time. To address this issue, a fuzzy multi-criteria decision-making approach is proposed in this study to help traveler choose suitable hotel accommodation. In the proposed methodology, firstly, hotels are divided into two types considering their requirements for COVID-19 vaccination. Travelers are then asked to list the key factors to consider when choosing between these two types of hotels. To derive the priorities of these key factors, the proportionally calibrated fuzzy geometric mean (pcFGM) method is proposed. Subsequently, the fuzzy VIšekriterijumskoKOmpromisnoRangiranje (fuzzy VIKOR) method is applied to evaluate and compare the overall performances of different types of hotels for recommendations to travelers. The applicability of the proposed methodology is illustrated by a real case study. According to the experimental results, most hotels did not request travelers to be full vaccinated. Nevertheless, the hotels recommended to travelers covered both hotel types.

Barriers to circular economy implementation in designing of sustainable medical waste management systems using a new extended decision-making and FMEA models.

The idea of the circular economy (CE) has gained prominence in the policies of the European Union (EU), commerce, and academic studies. Basically, CE is capable of achieving the best value and resolving many of the systemic challenges in the society and commerce of a country, thus leading to sustainable development and preventing irreparable damage to the environment. Medical waste management has proved a daunting challenge with the increase in the global population and the demand for medical services. Fuzzy multi-criteria decision-making approaches try to cover the different and uncertain views of decision-makers (DMs). The present study suggests a novel strategy based on multi-objective optimization using the ratio analysis (MOORA) in the area of spherical fuzzy sets (SFSs) to counterbalance the disadvantages of the failure modes and effects analysis (FMEA) method, such as the lack of weight assignment for risk factors and consideration of uncertainty. In the proposed method, first, the barriers are identified using the FMEA method, and the risk factors are given values. Then, the barriers identified using MOORA are prioritized in the spherical fuzzy (SF) area. The computational procedure of the proposed methodology is established through a case study of the barriers to circular economy implementation in designing sustainable medical waste management systems problems under an SF environment. The proposed approach was compared with IF-MOORA and was found that the results are more reliable using the proposed method, also the ranking in the MOORA method was compared with the TOPSIS method in terms of degree of correlation.

A PDCA based approach to evaluate green supply chain management performance under fuzzy environment

ABSTRACT This paper proposes a novel plan-do-check-act (PDCA) based group decision making model to evaluate the GSCM performance of manufacturing organizations. This research employs an integrated fuzzy multi-criteria decision-making (MCDM) approach in which the fuzzy-analytical hierarchy process (FAHP) method determines criteria weights and the fuzzy-technique for order preference by similarity to the ideal solution (FTOPSIS) method ranks the organizations. Five qualitative criteria are selected from the extant literature, which encompass both environmental, operational, and economic aspects of sustainability. Data is collected by developing a questionnaire, establishing a decision-makers’ committee, and carrying out a survey. To illustrate the industrial application of the proposed model, this study considers a real-world case study in the Indian manufacturing sector, in which three organizations (Organization A, Organization B, and Organization C) are selected from three distinct industrial segments, namely the leather industry, the pharmaceutical industry, and the steel industry, respectively. The result reveals that the environmental impact of harmful substances released from production is the most influential parameter. The result also reveals that Organization C is the benchmark organization and its strategies can guide other organizations for GSCM performance improvement. Moreover, the proposed model is capable of handling vagueness and ambiguity in decisions.

Pythagorean fuzzy multi-criteria decision-making approach based on Spearman rank correlation coefficient

Pythagorean fuzzy multi-criteria decision-making approach based on Spearman rank correlation coefficient

A new fuzzy multi-criteria decision-making approach for risk assessment of competitors’ cooperation in new product development projects

PurposeThis study aims to identify and accurately assess the risk factors of competitors’ cooperation in the NPD project.Design/methodology/approachNew product development (NPD) is essential to the survival of companies and surpassing other competitors. A key prerequisite for the success of an NPD project is the timing of new product delivery to the market. The main challenge faced by many project managers is the delay in execution and completion phases due to the complex nature and uncertainty of these projects. Rival companies' cooperation reduces the time spent on an NPD project which is an excellent way to reduce the risk of losing the market, but it increases other risk factors.FindingsBased on the results, the security and confidentiality of innovation, the competitors attracting human resources and the company’s brand credibility factors were ranked higher than other factors and should be predicted and managed before cooperating with competitors.Originality/valueThis paper proposed a new model to assess risk factors in cooperation with rival companies in NPD projects. This model takes into account new parameters, for example, negative and positive risks, negative and positive passable risks and risk-based multi-objective optimization by ratio analysis plus full multiplicative form methodology for the rival companies cooperation in NPD projects. To evaluate the efficiency of the proposed model, a real case of the R&D unit of Iran Khodro Company was studied.

Integrated Life Cycle Assessment and Life Cycle Cost Assessment based fuzzy multi-criteria decision-making approach for selection of appropriate wastewater treatment system

The current study proposes a comprehensive fuzzy formulated Multi-Criteria Decision Making (MCDM) framework with integrated Life Cycle Assessment (LCA) and Life Cycle Cost Assessment (LCCA) approach for selection of best suitable wastewater treatment (WWT) system, especially for multi-storeyed residential buildings. By utilising a thorough literature survey, experts' opinions and questionnaires, the study attempts to identify four dimensions of sustainability with associated key nineteen indicators. Furthermore, the study is benefited by undertaking quantitative parameters related to environmental and economic sustainability assessed by LCA and LCCA respectively. The proposed three-phase methodological framework illustrates the identification of widely used WWT systems in the first phase followed by Fuzzy Analytic Hierarchy Process (FAHP) assessment for criteria and indicators' screening and finalisation in the second phase and ranking of alternative by Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS) in the third phase. Moreover, the current paper suggests a novel approach of incorporating “environmental floor” in multi-storeyed building, where gravity governed nature-based wastewater treatment tanks of Decentralized On-Site Integrated WAste Management (DOSIWAM) system can be positioned. To test the proposed framework, the sustainability of DOSIWAM system is compared with five widely used wastewater treatment systems viz. membrane bioreactor (MBR), moving bed biofilm reactor (MBBR), sequencing batch reactors (SBR), activated sludge process (ASP), soil biotechnology (SBT). Results of alternative ranking indicate DOSIWAM (allocated at environmental floors) as the best suitable option followed by the second, third and fourth rank of MBR, SBT and SBR respectively whereas, MBBR and ASP are the least preferred. It has been observed that the experts prefer mostly natural treatment systems since they are more sustainable in environmental and economic considerations. In addition, by changing the weights of the main criteria, sensitivity analysis is carried out considering five scenarios, which signifies in three out of five scenarios; relative percentage change in criteria weight does not affect the first rank of the DOSIWAM system. The developed framework successfully facilitates a reliable base for the selection of the best suitable WWT system for multi-storeyed residential building and could be made available to the relevant local planning authority to incentivize the effort undertaken for the welfare of citizens as well as the government.

A Hybrid Spherical Fuzzy MCDM Approach to Prioritize Governmental Intervention Strategies against the COVID-19 Pandemic: A Case Study from Vietnam

The unprecedented coronavirus pandemic (COVID-19) is fluctuating worldwide. Since the COVID-19 epidemic has a negative impact on all countries and has become a significant threat, it is necessary to determine the most effective strategy for governments by considering a variety of criteria; however, few studies in the literature can assist governments in this topic. Selective governmental intervention during the COVID-19 outbreak is considered a Multi-Criteria Decision-Making (MCDM) problem under a vague and uncertain environment when governments and medical communities adjust their priorities in response to rising issues and the efficacy of interventions applied in various nations. In this study, a novel hybrid Spherical Fuzzy Analytic Hierarchy Process (SF-AHP) and Fuzzy Weighted Aggregated Sum Product Assessment (WASPAS-F) model is proposed to help stakeholders such as governors and policymakers to prioritize governmental interventions for dealing with the COVID-19 outbreak. The SF-AHP is implemented to measure the significance of the criteria, while the WASPAS-F approach is deployed to rank intervention alternatives. An empirical case study is conducted in Vietnam. From the SF-AHP findings, the criteria of “effectiveness in preventing the spread of COVID-19”, “ease of implementation”, and “high acceptability to citizens” were recognized as the most important criteria. As for the ranking of strategies, “vaccinations”, “enhanced control of the country’s health resources”, “common health testing”, “formation of an emergency response team”, and “quarantining patients and those suspected of infection” are the top five strategies. Aside from that, the robustness of the approach was tested by performing a comparative analysis. The results illustrate that the applied methods reach the general best strategy rankings. The applied methodology and its analysis will provide insight to authorities for fighting against the severe pandemic in the long run. It may aid in solving many complicated challenges in government strategy selection and assessment. It is also a flexible design model for considering the evaluation criteria. Finally, this research provides valuable guidance for policymakers in other nations.

Optimal selection of safety recommendations: A hybrid fuzzy multi-criteria decision-making approach to HAZOP

One of the most important outputs of Hazard and Operability (HAZOP) study is a list of recommendations (safety measures) for improving the safety of the system under study. Although, it is generally assumed that all the recommendations should be implemented, due to the limited resources (budget, time, etc.) simultaneous implementation of all the recommendations is not feasible in reality. The large number of recommendations, a wide range of factors which should be evaluated by experts, and the uncertainty in the expert opinions make the conventional methods ineffective. Despite the widespread use of HAZOP, the decision as to which recommendations to implement is still a challenge for process safety managers.The present study aims to develop (i) a comprehensive hierarchy of factors for the evaluation of the recommendations, (ii) a novel methodology by integrating the Best Worst Method (BWM) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) for ranking the recommendations and (iii) fuzzy logic and group decision-making are used to consider the imprecision of expert opinions so as to improve the accuracy of the results. The proposed model is capable of considering most factors of recommendations for any number of HAZOP recommendations.The methodology can be applied to a broad range of hazardous facilities and industries. In the present study, however, its application has been demonstrated for a sulfuric acid storage system.

Geospatial modelling of COVID-19 vulnerability using an integrated fuzzy MCDM approach: a case study of West Bengal, India.

COVID-19 is a worldwide transmitted pandemic that has brought a threatening challenge to Indian society and the economy. The disease has become a public health disaster, which has no effective medication. However, proper management and planning, which includes understanding the transmitting pattern, number of containment zones, vulnerable factors, and level of risk, may break the chain of transmission and reduce the number of cases. Hence, this study has attempted to model the COVID-19 vulnerability using an integrated fuzzy multi-criteria decision-making (MCDM) approach, namely fuzzy-analytical hierarchy process (AHP) and fuzzy-technique for order preference by similarity to ideal solution (TOPSIS) for West Bengal, India, through geographic information system (GIS). A total of 15 parameters were utilised to model the COVID-19 vulnerability, which was further categorised into three criteria: social vulnerability, epidemiological vulnerability, and physical vulnerability. The final vulnerability mapping has been done using these three criteria through the GIS platform. This study reveals that COVID-19 infection highly threatens about 20% of the total area of West Bengal, 23.42% moderately vulnerable, and 57.03% of the area comes under low vulnerability. The highly vulnerable region includes the Kolkata, South 24 Paraganas, and North 24 Paraganas, which are considered highly populated districts of West Bengal. Therefore government agencies should be more focused and plan accordingly to safeguard the community, especially the region with very high COVID-19 vulnerability, from further spreading the infection.

Accurate location planning for a wind-powered hydrogen refueling station: Fuzzy VIKOR method

This study seeks to enhance the site selection procedure for decision-makers to select the most effective wind-powered hydrogen refueling station via the aid of Fuzzy Multi-criteria Decision-making (FMCDM) approaches. To accomplish the purpose of the study, technical, economic, environmental, geographical, and social aspects constitute the influential criteria for prioritizing the eight aptest cities of Iran. Then, the Fuzzy Multi-criteria Optimization and Compromise Solution (FVIKOR) is employed to ascertain which alternative should be chosen as the most efficient one with respect to the criteria. In addition to several non-fuzzy MCDM techniques, the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS) and a novel integrated method are applied for validation. Moreover, an FMCDM approach coupling FTOPSIS and FVIKOR has been introduced for the prioritization of different alternatives while many conflicting criteria exist. The simulation results of fuzzy and non-fuzzy approaches suggest that Manjil is the best option for the purpose of study. The numerical findings also imply utilizing a 100-kW turbine in Manjil generates 548,376 kWh of electricity, resulting in the prevention of 109,675 kg of CO2 emissions and in the production of 8876 kg of hydrogen annually.

A combined hesitant fuzzy MCDM approach for supply chain analytics tool evaluation

Data quantity generated in supply chains expands as supply chain processes get more complex. Companies can leverage such data and gain valuable insight into their processes with Supply Chain Analytics (SCA) tools. The selection of the most appropriate SCA tool directly affects companies’ productivity since they allow enhancing visibility, obtaining informed decision-making and developing well-planned strategies for companies. A simple, practical, efficient and robust decision-making method can help select the most suitable SCA tool. Such a selection problem can be solved with multi-criteria decision-making (MCDM) methods that consider different criteria. This paper proposes an SCA tool evaluation model which combines hesitant fuzzy linguistic term set (HFLTS), analytic hierarchy process (AHP), multi-objective optimization by ratio analysis, and the full multiplicative (MULTIMOORA). The HFLTS technique is applied for handling the uncertainty and hesitancy of experts’ views in the evaluation process. The weights of the six main selection criteria and their thirty sub-criteria are computed via the hesitant fuzzy linguistic (HFL) AHP method. Then, the HFL MULTIMOORA method is combined with the fuzzy envelope technique for the first time in the literature to rank the eight SCA tool alternatives from different companies. A case study for a logistics firm illustrates the potential of the proposed evaluation model, which underlines the most important criteria to be the statistical power, product quality improvement, organizational performance enhancement, and service cooperation. It also ranks PeopleSoft as the most appropriate SCA tool for the case company. A comparative analysis with the HFL VIKOR method demonstrated that the proposed method is robust and consistent.

Fuzzy Multi-Criteria Decision-Making Approach for Online Food Delivery (OFD) Companies Evaluation and Selection: A Case Study in Vietnam

The COVID-19 pandemic has boosted the growth of the online food delivery (OFD) market in every corner of the world. In Vietnam, the food delivery service is rising rapidly and opening a large gateway of opportunities for numerous OFD platforms, also making it a competing business market in this country. Thus, to keep up with the ever-changing market dynamics, there are numerous measures and dimensions for the OFD entrepreneurs to take into consideration towards sustainable development. This paper’s objective is to evaluate major OFD companies in Vietnam based on a comprehensive set of criteria, which are social and environmental criteria (healthy and safety, information security, and environmental impact), economic criteria (delivery cost, operational capability, and risk management), service quality (order fulfillment, delivery speed, convenience of payment, online/offline service level, and customer feedback), and technology (web design, real-time tracking systems, and marketing techniques). To achieve this objective, this work proposes a multi-criteria decision-making (MCDM)-based framework combining the fuzzy analytic hierarchy process (FAHP) and the weighted aggregated sum product assessment (WASPAS). The FAHP is used to generate criteria weights in which fuzzy set theory is applied to translate the linguistic evaluation statements of experts. Then, WASPAS is used to rank the OFD companies against the selected criteria. The evaluation criteria that have obtained maximum weight priority in the FAHP analysis are “convenience of payment”, “delivery speed”, “online service level”, “order fulfillment”, and “delivery cost”. From the final ranking of WASPAS, Foody is today the best performing OFD player in Vietnam regarding the selected criteria, followed by GrabFood and Now. The proposed methodology can be an accurate and robust evaluation model for the industry, while the managerial implications of this study provide significant materials for decision-makers in the OFD market in improving their businesses towards sustainable development.

Coupling Fuzzy Multi-Criteria Decision-Making and Clustering Algorithm for MSW Landfill Site Selection (Case Study: Lanzhou, China)

The siting of Municipal Solid Waste (MSW) landfills is a complex decision process. Existing siting methods utilize expert scores to determine criteria weights, however, they ignore the uncertainty of data and criterion weights and the efficacy of results. In this study, a coupled fuzzy Multi-Criteria Decision-Making (MCDM) approach was employed to site landfills in Lanzhou, a semi-arid valley basin city in China, to enhance the spatial decision-making process. Primarily, 21 criteria were identified in five groups through the Delphi method at 30 m resolution, then criteria weights were obtained by DEMATEL and ANP, and the optimal fuzzy membership function was determined for each evaluation criterion. Combined with GIS spatial analysis and the clustering algorithm, candidate sites that satisfied the landfill conditions were identified, and the spatial distribution characteristics were analyzed. These sites were subsequently ranked utilizing the MOORA, WASPAS, COPRAS, and TOPSIS methods to verify the reliability of the results by conducting sensitivity analysis. This study is different from the previous research that applied the MCDM approach in that fuzzy MCDM for weighting criteria is more reliable compared to the other common methods.

A hybrid fuzzy MCDM approach for sustainable project portfolio selection problem and an application for a construction company

Although the construction sector is an indispensable sector in meeting human needs, it also has negative environmental and social effects. The construction industry has environmental impacts due to its significant share in consuming scarce resources and big amount of greenhouse gas emissions to the atmosphere. It is also a labor force-intensive industry. Due to the intensity of the labor force, ignoring social concerns cause a negative social image. Consequently, taking sustainability into consideration for construction projects is of great importance in terms of solutions to social and environmental problems. Due to limited resources, it is not possible to implement every project for companies. The most suitable projects are preferred among alternative projects. The problem of project portfolio selection (PPS) is an important decision problem that companies frequently encounter. Many factors should be taken into consideration for selecting projects. In many studies in the literature, the problem of PPS is addressed only by considering economic criteria. In this study, the problem of PPS is addressed with sustainability consideration. Considering sustainability, environmental and social factors have also been taken into account besides economic factors. A hybrid fuzzy multi-criteria decision-making (FMCDM) approach has been used due to uncertainties in the decision process. In the hybrid approach, the methods of Fuzzy complex proportional assessment (F-COPRAS) and Fuzzy step-wise weight assessment ratio analysis (F-SWARA) are used together. An application is conducted for a construction company.

Analysis and Comparison of State-of-the-Art Fuzzy Multi-criteria Decision-making Methods Under Different Levels of Uncertainty

Often, data in multi-criteria decision-making (MCDM) problems are imprecise and changeable due to the mandatory participation of human judgement, which is often unclear and vague. Besides, different MCDM methods may produce different results under different levels of uncertainty and require divergent levels of computational resources. Therefore, the quality of the decision and the amount of effort are heavily affected by selection of the MCDM method. With the regular proliferation of such methods and their modifications, it is important to carry out a comparative study that provides comprehensive insight into their performances under uncertain conditions. In this study, we use the randomized quasi-Monte Carlo simulation approach to compare empirically the results produced by 12 classic and contemporary fuzzy MCDM (FMCDM) approaches with rank-reversal perspective over increasing uncertainty in various decision scenarios. Furthermore, this study also investigates the similarity between ranks produced by each pair of methods for the same decision problems. The study further compares the results obtained by quasi-Monte Carlo simulation with the results obtained by Monte Carlo simulation. The findings of this study will assist decision-makers in the selection of most appropriate fuzzy MCDM approach for different decision scenarios. The results of this research are significant additions to the current repository of knowledge in the multi-criteria decision analysis as well as the literature pertaining to the Information Systems. It also provides insights for many managerial applications of these MCDM methods.

Outsourcing Reverse Logistics for E-Commerce Retailers: A Two-Stage Fuzzy Optimization Approach

On the heels of the online shopping boom during the Covid-19 pandemic, the electronic commerce (e-commerce) surge has many businesses facing an influx in product returns. Thus, relevant companies must implement robust reverse logistics strategies to reflect the increased importance of the capability. Reverse logistics also plays a radical role in any business’s sustainable development as a process of reusing, remanufacturing, and redistributing products. Within this context, outsourcing to a third-party reverse logistics provider (3PRLP) has been identified as one of the most important management strategies for today’s organizations, especially e-commerce players. The objective of this study is to develop a decision support system to assist businesses in the selection and evaluation of different 3PRLPs by a hybrid fuzzy multicriteria decision-making (MCDM) approach. Relevant criteria concerning the economic, environmental, social, and risk factors are incorporated and taken into the models. For obtaining more scientific and accurate ranking results, linguistic terms are adopted to reduce fuzziness and uncertainties of criteria weights in the natural decision-making process. The fuzzy analytic hierarchy process (FAHP) is applied to measure the criteria’s relative significance over the evaluation process. The fuzzy technique for order preference by similarity to an ideal solution (FTOPSIS) is then used to rank the alternatives. The prescribed method was adopted for solving a case study on the 3PRLP selection for an online merchant in Vietnam. As a result, the most compatible 3PRLP was determined. The study also indicated that “lead time,” “customer’s voice,” “cost,” “delivery and service,” and “quality” are the most dominant drivers when selecting 3PLRLs. This study aims to provide a more complete and robust evaluation process to e-commerce businesses and any organization that deals with supply chain management in determining the optimized reverse logistics partners.

A Novel Methodology for Prioritizing Zero-Carbon Measures for Sustainable Transport

Achieving a zero-carbon city requires a long-term strategic perspective. Transport emissions are a major source of carbon emissions, and cities grapple with reducing carbon emissions, and improving the air quality for their citizens. London's new transport strategy document, called Mayor's Transport Strategy 2018, aims to achieve a zero-carbon city by 2050 and set out many actions to facilitate this transition. However, London needs a prioritisation framework which would take into account the financial, environmental and social impacts of these actions. Considering the uncertainties around these actions, which has been now significantly more crucial during the COVID-19 pandemic, this study proposes a novel extension of Best-Worst Method (BWM) and extension of the TODIM (an acronym in Portuguese for Iterative Multi-Criteria Decision Making (MCDM)) method using D numbers. This TODIM-D based fuzzy MCDM approach provides a prioritisation framework for the actions associated with zero-carbon city policies set out in London's strategy document. According to the results of the proposed method, “introducing zero-emission zones” should be selected as the first initiative to implement. The prioritization of this initiative allows London to achieve a zero-carbon transport by having the greatest impact on the modal shift from cars to sustainable mobility modes with a lower operational and implementation cost as well as having greater public support. The proposed method used in this study can be transferred to other cities which aim to achieve a zero-carbon transport.