Third-party Reverse Logistics Providers Research Articles

An integrated group decision-making framework for assessing S3PRLPs based on MULTIMOORA-WASPAS with q-rung orthopair fuzzy information

Sustainable third-party reverse logistics has gradually risen to prominence as a component of contemporary commercial development as a result of the acceleration of global economic integration and the prominent growth of information technology in the logistics industry. In the procedure of sustainable third-party reverse logistics providers (S3PRLPs) selection, indeterminacy and conflict information bring great challenges to decision experts. In view of the significant superiority of q-rung orthopair fuzzy (q-ROF) set in expressing uncertain and vague assessment information, this essay designs a comprehensive assessment framework through merging the best and worst method (BWM), Multiplicative Multi-objective Optimization by Ratio Analysis with Full Multiplicative Form (MULTIMOORA) and weighted aggregated sum product assessment (WASPAS) method to address the S3PRLPs selection issue with entirely unknown weight information under q-ROF setting. Firstly, we present a novel score function for comparing q-ROF numbers after analyzing the inadequacies of previous works. Secondly, the q-ROF Frank interactive weighted average (q-ROFFIWA) and q-ROF Frank interactive weighted geometric (q-ROFFIWG) operators are advanced based on the constructed operations to take into consideration the interactive impact of information fusion procedure. Thirdly, the q-ROF-MULTIMOORA-WASPAS decision framework is built based on novel score function and the developed operators, in which the synthetic weights of the criterion are determined by the modified BWM and entropy weight method to reflect both the subjectivity of the decision expert and the objectivity of the decision information. Ultimately, an empirical example was used to evaluate S3PRLPs to demonstrate the applicability and feasibility of the developed methodology, and a comparative analysis was conducted with other existing methods to highlight its advantages in dealing with complex decision problems. The discussion from the research indicates that the developed methodology can be used to evaluate S3PRLPs and further improve the quality of logistics services for organizations.

Group decision making with incomplete triangular fuzzy multiplicative preference relations for evaluating third-party reverse logistics providers

The strategic management of reverse logistics (RL) is essential for enterprises to enhance their operational efficiency, customer satisfaction, and sustainability performance in today's competitive marketplace. Many manufacturing firms have to cooperate with professional RL providers to overcome resource constraints and technological limitations, ultimately driving business success. Thus, it is critical for every enterprise to select the most suitable third-party RL provider (3PRLP). This paper provides a novel group decision making (GDM) method with incomplete triangular fuzzy multiplicative preference relations (TFMPRs) to cope with the selection of the most optimal 3PRLP. Firstly, a definition of acceptable incomplete TFMPRs is given. Then, the sufficient and necessary condition of an acceptable incomplete TFMPR is proposed. By analyzing the properties of consistent TFMPRs, a graph-based algorithm is designed to estimate the unknown elements in incomplete TFMPRs. Based on the proposed acceptable consistency definition of TFMPRs, an optimization model is set up to improve the consistency degree of inconsistent TFMPRs. The optimal normalized triangular fuzzy multiplicative weight vector (Tri-MWV) is obtained by computing two analytic expressions and solving a linear programming model. To measure the closeness degree of two TFMPRs, the concept of logarithmic correlation coefficient (LCC) between two TFMPRs is proposed. Combining the incomplete preference information in incomplete TFMPRs with the LCCs of any two TFMPRs, an algorithm of computing experts’ weights is displayed. Subsequently, a novel method of GDM with incomplete TFMPRs is presented. Lastly, a practical example of evaluating 3PRLPs is conducted to illustrate the effectiveness of the proposed GDM method with incomplete TFMPRs.

Assessment of Third-Party Reverse Logistics Provider Through the SWARA-WASPAS Integrated Framework

The selection of the most suitable third-party provider for reverse logistics (RL) activities is a key factor in initiating effective RL processes. However, the process of identifying the optimal third-party provider involves navigating through various conflicting objectives and criteria. This task is intricate and time-consuming, necessitating the application of multi-criteria decision-making (MCDM) approaches. This study addresses the evaluation and selection of the best 3PRLP by introducing a comprehensive MCDM framework. Therefore, this study aims to assist a manufacturer specializing in milk and dairy products who has opted to transfer its reverse logistics operations to a logistics service provider. The objective is to aid them in selecting the most suitable 3PRLP. The proposed framework incorporates the SWARA (Step-wise Weight Assessment Ratio Analysis) technique for determining weights and the WASPAS (Weighted Aggregated Sum Product Assessment) method for thoroughly evaluating alternatives. In this study, a panel of four experts made a joint decision after identifying six criteria and five alternatives. The research concluded that the reverse logistics cost (C1) emerges as the most pivotal factor, with the service quality of reverse logistics (C3) being recognized as the least significant criterion. As a result, A1 stands out as the top choice among the 3PRLP.

A hybrid generalized TODIM approach for sustainable 3PRLP selection in electronic manufacturing industry

Under the pressure of globalization, environmental protection/resource consumption, and the intensification of market competition, various industries have recognized the significant importance of sustainable supply chain management (SCM), in which reverse logistics (RL) has attracted many concentrations from governments to enterprises and the public. However, it is relatively difficult to operate RL autonomously for most electronic manufacturing companies whose core businesses and competition advantages are not in logistics operations because of limited resources and professional skills. Therefore, it is a good choice to escape from the predicament by selecting an appropriate third-party reverse logistics provider (3PRLP) with professional skills for outsourcing and accomplishing the RL business. Generally, evaluation and selection of a 3PRLP is regarded as a multi-attribute group decision-making (MAGDM) process, in which four aspects, namely, the evaluation attributes system, weight of experts and attributes, preference information representation and alternative ranking method have impacts on the decision-making results. Therefore, this paper constructs an MAGDM framework named generalized TODIM (TOmada de DecisãoInterativa e Multicritério, Portuguese acronym for Interactive multicriteria decision-making) under a hybrid information environment, which includes crisp numbers, interval numbers and fuzzy linguistic terms, for solving the problem. It provides a useful reference for manufacturing enterprises to find out the optimal 3PRLP from many alternatives. In particular, the use of different information forms for different evaluation attributes can not only facilitate decision makers to provide their judgments, but also effectively retain the original decision information as much as possible. Utilization of the generalized TODIM method is helpful for considering the risk attitudes and psychological preference behaviors of decision-makers. Finally, to demonstrate the feasibility and effectiveness of the proposed method, a case study relates to select a sustainable 3PRLP in an electronic manufacturing company was conducted. The findings show that the company should pay more attention to the attributes related to social responsibility, service quality and cost when selecting alternative 3PRLP under the sustainable SCM environment. It also provides useful suggestions for 3PRLP themselves to improve their competitiveness from these aspects. Moreover, the sensitivity and comparative analysis demonstrated the necessity and superiorities of comprehensively considering weights of experts and attributes, adopting hybrid information formats, and taking into account the risk attitudes and psychological preference behaviors of decision-makers during the evaluation and selection process.

Identifying Critical Indicators in the Evaluation of Third-Party Reverse Logistics Provider Using Best–Worst Method

Evaluation and selection of a third-party reverse logistics provider (3PRLP) is an important tool for enterprises to improve the level of reverse logistics management. The identification of critical indicators plays a crucial role in the evaluation process. Firstly, on the basis of fully considering the characteristics of 3PRLP evaluation and selection, we summarized 27 evaluation indicators from 5 dimensions—overall operation level, management service level, information technology level, social and ecological benefits, and strategic alliance. Secondly, we adopted the Delphi method to determine the formal evaluation index system, and the best–worst method (BWM) to calculate the weight of each indicator. We determined the critical evaluation indicators on the basis of the weights. Finally, based on our results, corresponding countermeasures and implications regarding the process of 3PRLP evaluation were put forward. The research results show that the critical indicators include transportation allocation capacity, network coverage, service price level, service response speed, recovery efficiency, and service flexibility level.

On spherical fuzzy distance measure and TAOV method for decision-making problems with incomplete weight information

A spherical fuzzy set is one of the reliable tools to handle the uncertainties in the data with the help of the three membership degrees: Positive, neutral, and negative. Under this environment, the paper aims to present a novel decision-making algorithm named as MCDM-TAOV with some novel distance measures using matrix norms. In the literature, several kinds of distance measures occur, but they fail to meet certain axioms of the measure. To overwhelm this, the proposed measure satisfies all axiomatic requirements and overcomes the hindrances in the existing distance measures. Several counter-intuitive examples are provided to justify the superiority of the proposed measures. Furthermore, we addressed the total area based on orthogonal vector (TAOV) methodology to solve the MCDM (“multi-criteria decision-making”) problems. A distance-based criteria weight determination method is presented to compute the unknown criteria weight. The approach has been demonstrated by assessing the third-party reverse logistics provider (3PRLP) problem. The practical applicability, comparative analysis and advantages of the study with other decision-making methods are furnished to depict the efficiency of the moulded process.

A q-rung orthopair fuzzy combined compromise solution approach for selecting sustainable third-party reverse logistics provider

PurposeReverse logistics (RL) is a type of supply chain management that moves goods from the end customer to the original manufacturer for reuse, remanufacturing and disposal purposes. Owing to growing environmental legislations and the development of new technologies in marketing, RL has attracted more significance among experts and academicians. Outsourcing RL practices to third-party reverse logistics provider (3PRLP) has been identified as one of the most important management strategies due to complexity of RL operations and the lack of available resource. Current sustainability trends have made 3PRLP assessment and selection process more complex. In order to select the 3PRLP, the existence of several aspects of sustainability motivates the experts to establish a new multi-criteria decision analysis (MCDA) approach.Design/methodology/approachWith the growing complexity and high uncertainty of decision environments, the preference values of 3PRLPs are not always expressed with real numbers. As the generalized version of fuzzy set, intuitionistic fuzzy set and Fermatean fuzzy set, the theory of q-rung orthopair fuzzy set (q-ROFS) is used to permit decision experts (DEs) to their assessments in a larger space and to better cope with uncertain information. Given that the combined compromise solution (CoCoSo) is an innovative MCDA approach with higher degree of stability and reliability than several existing methods.FindingsTo exhibit the potentiality and applicability of the presented framework, a case study of S3PRLPs assessment is taken from q-rung orthopair fuzzy perspective. The assessment process consists of three sustainability aspects namely economic, environment and social dimensions related with a total of 14 criteria. Further, sensitivity and comparative analyses are made to display the solidity and strength of the presented approach. The results of this study approve that the presented methodology is more stable and efficient in comparison with other methods.Originality/valueThus, the objective of the study is to develop a hybrid decision-making methodology by combining CoCoSo method and discrimination measure with q-ROFS for selecting an appropriate sustainable 3PRLP (S3PRLP) candidate under uncertain environment. In the proposed method, a novel procedure is proposed to obtain the weights of DEs within q-ROFS context. To calculate the criteria weights, a new formula is presented based on discrimination measure, which provides more realistic weights. In this respect, a new discrimination measure is proposed for q-ROFSs.

A new last aggregation fuzzy compromise solution approach for evaluating sustainable third-party reverse logistics providers with an application to food industry

In today’s world, reverse logistics (RLs) activities have become increasingly crucial for companies looking for improved customer service, cost reduction, and sustainability perspectives. Limited resources, and insufficient technology and knowledge, have led manufacturing firms to cooperate with professional RL providers. However, evaluating the right third-party reverse logistics providers (3PRLPs) is a complex, uncertain multi-criteria decision-making (MCDM) problem, which is affected by many conflicting qualifications, the complexity of the human mind, and imprecise and uncertain information. This paper aims to introduce a novel framework that integrates fuzzy best worst method (BWM) and a new last aggregation fuzzy compromise solution for providing systematic decision support for organizations to select the most preferred partner. The reasons behind choosing both methods in an integrated way are that; the fuzzy BWM requires a smaller number of comparisons but can provide more reliable weights due to consistent criteria comparisons. Furthermore, the approaches based on compromise solutions are powerful decision-making tools because a compromise solution is a more feasible solution closest to the ideal that can be efficient in selecting the best alternative in the presence of conflicting decision criteria. Therefore, the fuzzy BWM approach is utilized to investigate the performance criteria of the 3PRLPs from economic, environmental, and social aspects of sustainability as well as risk factor. Expert weights and the preferences of sustainable 3PRLPs are then calculated simultaneously using a new last aggregation fuzzy compromise solution. Compared with the available literature, the proposed framework considers all possible sustainable criteria along with risk factor, which offers greater flexibility for experts to articulate their evaluations. In addition, the last aggregation fuzzy method eliminates distortion and loss of information and allows decision-makers to control the outcome’s precision. Moreover, the applicability of the proposed method is numerically demonstrated by developing a decision-support tool for the food industry. Sensitivity analysis and comparative analysis further illustrate the flexibility and practicability of proposed framework through which the decision-makers can make more accurate judgments regarding the evaluation of 3PRLPs.

An attitudinal consensus method under uncertainty in 3PRLP selection

To underpin a reverse logistics (RL) outsourcing decision, this study aims to investigate a third-party reverse logistics provider (3PRLP) selection problem under the framework of group decision making (GDM). Group attitude towards distinctive opinions may affect the time and cost on consensus reaching process (CRP). Therefore, an attitudinal consensus method under uncertainty is established and composed of three parts: initialization process, consensus process and selection process. In initialization process, considering each expert’s risk preference, a transformation rule is deployed to compute semantics possibility distribution of general comparative linguistic expressions (GCLEs) based on the numerical counterpart of linguistic assessment. In consensus process, three group attitudes-oriented consensus policies are qualitatively presented, including maximum, indifference and minimum disagreement consensus policies. Considering the feasible interval of attitudinal parameter, a new consensus measure under uncertainty, i.e., attitudinal consensus acceptability index (ACAI), is quantitively defined by stochastic acceptability analysis. To resolve the issue that the consensus degree fails to reach a predefined level, an automatic feedback mechanism is designed, and is supported by a consensus improvement algorithm evolving GCLEs’ possibility distribution. In selection process, to identify the criteria weight, incomplete information such as pairwise comparisons of criteria are characterized by ordinal regression-like linear programming. TODIM (an acronym in Portuguese of interactive and multiple attribute decision making) is extended on fuzzy measure and then acted as rank function in stochastic acceptability analysis to explore the uncertainty of criteria preference. Lastly, 3PRLP selection for an automobile manufacturing firm is conducted to demonstrate the flexibility and practicability of our method along with sensitivity analysis and comparative analysis.

Assessment of third-party logistics providers by introducing a new stochastic two-phase compromise solution model with last aggregation

In the conditions of increasing governments' and consumers' awareness of environmental protection and sustainability, the enterprises have been encouraged to devote more attention to reverse logistics (RL) activities. Assessment of third-party reverse logistics providers (3PRLPs) is a crucial decision strategy for companies who choose to outsource their RL activities to third-party partners. To ensure accurate information is reflected in the decision process, it is imperative to consider uncertain information. To this aim, this paper draws attention to the selection of the most preferred RL providers using a novel comprehensive stochastic compromise solution by considering the uncertainty associated with decision variables. This paper presents a novel multi-attribute group decision-making (MAGDM) framework by integrating a new stochastic criteria importance through inter-criteria correlation (CRITIC) method and an innovative last aggregation stochastic two-phase compromise solution based on the visekriterijumsko kompromisno rangiranje (in Serbian) (VIKOR) approach to provide systematic decision support for companies to select the most preferred RL providers. In the proposed framework, the CRITIC method is utilized to calculate the priority weights of the attributes. The innovative last aggregation stochastic two-phase compromise solution is employed to evaluate decision-makers (DMs) and alternatives simultaneously. Moreover, the proposed compromise method exploits the pessimistic, most likely, and optimistic solutions to deal with stochastic uncertainty and provide DMs with more flexibility in the final evaluation. The approach is also validated by applying a sample case for selecting 3PRLPs along with sensitivity analysis on the weights of the different attributes in order to investigate the robustness of the results. Consequently, to demonstrate the reliability of the suggested approach, comparative analyses of the final ranking are conducted. The outcome of the study reveals the proposed model provides a viable, high-performance, and flexible decision-making process, by which the DMs can provide more prompt and correct judgments on the selection of the best 3PRLPs.

A linguistic Pythagorean hesitant fuzzy MULTIMOORA method for third-party reverse logistics provider selection of electric vehicle power battery recycling

Electric vehicle power battery recycling (EVPBR) is an effective way to utilize resources and reduce environmental damage. In order to ensure the safety and efficiency of electric vehicle batteries (EVBs) reuse and remanufacture, many EVB manufacturers are seeking cooperation with third-party reverse logistics (3PRL) providers to conduct the pre-treatment and transportation of post-used batteries. However, the selection of 3PRL provider is a matter of complex multi-criteria decision-making (MCDM) affected by numerous associated factors. The goal of this paper is to present a linguistic Pythagorean hesitant fuzzy MULTIMOORA method to investigate the selection of 3PRL providers for EVPBR. Firstly, given that the complexity of evaluation information, the linguistic Pythagorean hesitant fuzzy set (LPHFS) is defined in detail. On the basis of new evaluation representation tool, the weight determining models for expert panel and criteria set based on correlation consensus degrees and maximum deviation are derived, respectively. Then a MULTIMOORA method under the linguistic Pythagorean hesitant fuzzy environment is constructed. Later, the evaluation criteria system for the provider capability analysis is set up, and the proposed MCDM approach is applied to select the most suitable 3PRL provider for EVPBR in China. Finally, the sensitivity and comparative analysis results justify the robustness and feasibility of the proposed method.

A DEA model with dual-role factors and fuzzy data for selecting third-party reverse logistics provider, case study: Hospital waste collection

Today, most institutions and companies delegate reverse logistics services, organizational communication, and outsourcing company to a third-party logistics reverse provider. To select an appropriate third-party logistics provider, this study proposes a decision-making procedure considering dual role data and fuzzy states based on data envelopment analysis models. After determining evaluation indices, this study uses the α -cut approach to transform the proposed model under uncertainty to a deterministic model. Finally, a case study (collection and burial of hospital waste) is presented to show the application of this research. Results of selecting the best third-party logistics provider and more analyses are provided after coding in GAMS software.

Selection of third party reverses logistic providers: an approach of BCF-CRITIC-MULTIMOORA using Archimedean power aggregation operators

One of the most powerful tools to operate imprecision is bipolar complex fuzzy sets (BCFSs), which is an enlargement of bipolar fuzzy sets (BFSs) as well as complex fuzzy sets (CFSs). This paper deals with an integrated MULTIMOORA (multi-objective optimization on the basis of ratio analysis plus full multiplicative form) framework as a generalization of fuzzy MULTIMOORA procedure to assess the multi-criteria decision-making (MCDM) problems with BCFSs. We develop BCF-Archimedean power weighted (ordered weighted) arithmetic and geometric aggregation operators (AOs) and discuss their properties from this point of view. The proposed Archimedean power-weighted AOs can eliminate the influence of extreme evaluating criteria values from some biased experts with different preference attitudes under the BCF setting. Afterward, we put forward an integrated MULTIMOORA algorithm based on the proposed AOs, where criteria weights are estimated using the CRITIC (criteria importance through inter-criteria correlation) method, which is a well-known objective weighting method based on aggregated score values of options, intensity contrast of every criteria and conflict among attributes. In the proposed methodology, criteria values are aggregated based on the MULTIMOORA method that involves three sub-methods: the ‘ratio system’, the ‘reference point’ and the ‘full multiplicative form’ and thus takes less computational time, minimum mathematical evaluations and bears good stability. In the following, third-party reverse logistics providers' (3PRLP) selection problem is brought into consideration to manifest the sufficiency of the developed methodology. At the end of this study, we draw attention to a comparison between the proposed decision-making approach with the corresponding BCF-CRITIC-TOPSIS and BCF-CRITIC-WASPAS methods.

Assessment of sustainable third party reverse logistic provider using the single-valued neutrosophic Combined Compromise Solution framework

Customers’ pressure, social responsibility and government regulations have motivated the enterprises to consider the Reverse Logistics (RL) in their operations. Recently, companies frequently outsource RL to Third-Party Reverse Logistics Providers (3PRLPs) to concentrate on their prime concern and diminish costs. In the present study, relevant sustainability criteria are employed for a decision-making example of Sustainable 3PRLP (S3PRLP) selection problem of an Indian Electronics Company. To choose the most suitable S3PRLP, a novel integrated approach by combining Combined Compromise Solution (CoCoSo) and CRiteria Importance Through Intercriteria Correlation (CRITIC) approaches under the context of Single-Valued Neutrosophic Sets (SVNSs). This approach offers a new procedure for determining the criteria weights with the use of CRITIC technique. The efficiency and practicability of the present approach is numerically demonstrated by solving an illustrative case study of S3PRLPs selection within SVNSs context. Moreover, sensitivity analysis and comparison with previously developed techniques are presented to highlight the robustness and strength of the introduced method. The result of this work concludes that the introduced methodology can recommend more feasible performance when facing with indeterminate and inconsistent knowledge, and qualitative data. • Novel integrated SVN-CRITIC-CoCoSo method is developed for solving MCDM problems. • A sustainable third party reverse logistic provider (S3PRLP) selection and evaluation process is proposed. • CRITIC approach is used to evaluate the criteria weights. • To show applicability of proposed method, an empirical case study of S3PRLP selection is discussed. • Comparative and Sensitivity analyses are also studied to validate the results.

Sustainable third-party reverse logistics provider selection to promote circular economy using new uncertain interval-valued intuitionistic fuzzy-projection model

PurposeThis study caries a survey approach using the expert's interview and literature to select the important criteria to select and evaluate the third-party reverse logistics providers (3PRLPs) in manufacturing companies. In total, 16 criteria are selected to evaluate 3PRLPs, and these criteria are classified on the basis of three main elements of sustainable growth, including economic, social and environmental development. Therefore, a hybrid decision-making approach is utilized to evaluate and rank the 3PRLPs in manufacturing companies.Design/methodology/approachThis paper proposes a new decision-making approach using the projection model and entropy method under the interval-valued intuitionistic fuzzy set to assess 3PRLPs based on sustainability perspectives. A survey approach using the literature review and experts' interview is conducted to select the important criteria to select and evaluate 3PRLPs in manufacturing companies. To assess the criteria weight, the entropy method is used. Further, the projection model is applied to prioritize the 3PRLPs option. Sensitivity analysis and comparison process are performed in order to test and validate the developed method.FindingsThe presented methodology uses the benefits to determine the former for measuring the parameters considered and the latter for rating the 3PRLPs alternatives. A case study is taken to 3PRLPs in the manufacturing industry to illustrate the efficiency of the introduced hybrid method. The findings of this study indicate that when facing uncertainties of input and qualitative data, the proposed solution delivers more viable performance and therefore is suitable for wider uses.Originality/valueThe conception of the circular economy (CE) comes from the last 4 decades, and in recent years, tremendous attention has been carried out on this concept, partially because of the availability of natural resources in the world and changes in consumption behaviour of developed and developing nations. Remarkably, the sustainable supply chain management concepts are established parallel to the CE foundations, grown in industrial practice and ecology literature for a long time. In fact, to reduce the environmental concerns, sustainable supply chain management seeks to diminish the materials' flow and minimize the unintentional harmful consequences of consumption and production processes. Customers and governments are becoming increasingly aware of the environmental sustainability in the CE era, which allows businesses to concentrate more resources on reverse logistics (RLs). However, most manufacturing enterprises have been inspired to outsource their RL operations to competent 3PRLPs due to limited resources and technological limitations. In RL outsourcing practices, the selection of the best 3PRLP is helpfully valuable due to its potential to increase the economic viability of enterprises and boost their long-term growth.

A Conceptual Hybrid Approach from a Multicriteria Perspective for Sustainable Third-Party Reverse Logistics Provider Identification

Reverse logistics (RL) is considered the reverse manner of gathering and redeploying goods at the end of their lifetime span from consumers to manufacturers in order to reutilize, dispose, or remanufacture. Whereas RL has many economic benefits, it presents compromises to businesses that wish to remain competitive but be responsible global citizens in terms of social, environmental, risk, and safety aspects of sustainable development. Managing RL systems therefore is considered a multifaceted mission that necessities a significant level of technology, infrastructure, experience, and competence. Consequently, various commerce institutions are looking to outsourcing their RL actions to third-party reverse logistics providers (3PRLPs). In this work, a novel hybrid multiple-criteria decision-making (MCDM) framework is proposed to classify and choose 3PRLPs, which comprises the analytic hierarchy process (AHP) technique, and technique for order of preference by similarity to ideal solution (TOPSIS) technique under neutrosophic environment. Accordingly, AHP is availed for defining weights of key dimensions and their subindices. In addition, TOPSIS was adopted for ranking the specified 3PRLPs. The efficiency of the proposed approach is clarified through application on a considered car parts manufacturing industry case in Egypt, which shows the features of the combined MCDM methods. A comparative and sensitivity analyses were performed to highlight the benefits of the incorporated MCDM methods and for clarifying the effect of changing weights in selecting the sustainable 3PRLP alternative, respectively. The suggested framework is also shown to present more functional execution when dealing with uncertainties and qualitative inputs, demonstrating applicability to a broad range of applications. Ultimately, the best sustainable 3PRLPs were selected and results show that social, environmental, and risk and safety sustainability factors have the greatest influence when determining 3PRLPs alternatives.

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 Hesitant Fuzzy Combined Compromise Solution Framework-Based on Discrimination Measure for Ranking Sustainable Third-Party Reverse Logistic Providers

Customers’ pressure, social responsibility, and government regulations have motivated the enterprises to consider the reverse logistics (RL) in their operations. Recently, companies frequently outsource their RL practices to third-party reverse logistics providers (3PRLPs) to concentrate on their primary concern and diminish costs. However, to select the suitable 3PRLP candidate requires a multi-criteria decision making (MCDM) process involving uncertainty owing to the presence of many associated aspects. In order to choose the most appropriate sustainable 3PRLP (S3PRLP), we introduce a hybrid approach based on the classical Combined Compromise Solution (CoCoSo) method and propose a discrimination measure within the context of hesitant fuzzy sets (HFSs). This approach offers a new process based on the discrimination measure for evaluating the criteria weights. The efficiency and practicability of the present approach are numerically demonstrated by solving an illustrative case study of S3PRLPs selection under a hesitant fuzzy environment. Moreover, sensitivity and comparative studies are presented to highlight the robustness and strength of the introduced methodology. The result of this work concludes that the introduced methodology can recommend a more feasible performance when facing with determinate and inconsistent knowledge and qualitative data.

Fermatean fuzzy CRITIC-EDAS approach for the selection of sustainable third-party reverse logistics providers using improved generalized score function.

In today’s world, the demand for sustainable third-party reverse logistics providers (S3PRLPs) becomes an increasingly considerable issue for industries seeking improved customer service, cost reduction and sustainability perspectives. However, the assessment and selection of right S3PRLP is a complex uncertain decision-making problem due to involvement of numerous conflicting attributes, imprecise human mind and lack of information. Recently, Fermatean fuzzy set (FFS) has been recognized as one of the suitable tools to tackle the uncertain and inaccurate information. In this paper, we introduce a hybrid methodology based on CRITIC and EDAS methods with Fermatean fuzzy sets (FFSs) to solve the S3PRLP selection problem in which the attributes and decision makers’ weights are completely unknown. In this framework, CRITIC approach is applied to calculate the attribute weight and EDAS method is used to evaluate the priority order of S3PRLP options. To do this, a new improved generalized score function (IGSF) is developed with its elegant properties. Also, a formula is discussed to calculate the decision makers’ weights based on the developed IGSF. Next, developed framework is applied to assess a case study of S3PRLP selection problem with Fermatean fuzzy information, which elucidates the usefulness and practicality of the proposed method. Finally, comparative study is implemented to show the strength of introduced framework with extant approaches. The outcomes of the work confirm that the introduced approach is more feasible and well-consistent with the other extant approaches.

Wholesale price and manufacturer profit with downstream bargaining for consumer returns

This paper examines a closed-loop supply chain with a manufacturer, a retailer and a third-party reverse logistics provider (3PRLP). We focus on the management of consumer product returns assuming ...