Third-party Logistics Providers Research Articles

An integrated model for road freight transport firm selection in third-party logistics using T-spherical Fuzzy sets

The efficient selection of road freight transport (RFT) firms plays a critical role in constructing well-operating logistics systems for large-scale third-party logistics (3PL) providers. However, the decision-making process for such selection is often complex and uncertain due to various influential criteria and dynamic industry nature. To address this challenge, a novel decision-making model that integrates Delphi, CRiteria Importance Through Intercriteria Correlation (CRITIC) and Combined compromise ranking solution (CoCoSo) methods based on T-Spherical Fuzzy sets has been proposed in this paper. The model integrates expert opinions with an extensive literature review to identify the influential criteria and their corresponding weights. Subsequently, it employs a comprehensive evaluation approach to rank the RFT firms based on their performance. The model accommodates uncertainties and subjectivity by utilizing T-Spherical Fuzzy Numbers, offering robustness and transparency in decision-making. A case study involving 15 evaluation criteria and 12 RFT firms were selected to demonstrate the applicability and aptness of the proposed model. Flexibility and Integrability to different transport modes emerged as the two most essential criteria, whereas RFT firm A2 emerged as the best alternative with the highest performance score of 3.0861, followed by RFT firm A7 with a score value of 3.0499.

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.

Multi-period fourth-party logistics network design from the viability perspective: a collaborative hyper-heuristic embedded with double-layer Q-learning algorithm

In the ‘new normal’ setting of a mega-crisis, the viability becomes the driving force for the fourth party logistics (4PL) network design. In this paper, the viability is characterised in terms of agility, resilience and survival sustainability as the response to changes in demand, disruption and survivability. The fortification and recovery strategies are considered in possible disruptions at transfer centres and third-party logistics providers. A novel mixed integer non-linear programming model is proposed to obtain the multi-period 4PL network solution with minimum total cost under viability constraints. Considering the NP-hard characteristic of problem and the non-convex of proposed model, the hyper-heuristic algorithm is designed. To take advantage of both global optimality seeking and local search ability, a collaborative hyper-heuristic embedded with double-layer Q-learning (CHHDLQL) algorithm is proposed. The effectiveness and efficiency of the proposed algorithm is demonstrated by the promising numerical results. By stress-testing the existing network, appropriate adjustments to fortification and recovery strategies can effectively cope with changes in demand and disruption. Furthermore, the impact of 4PL strategy, fortification and recovery strategies, and viability constraints are investigated. The demand satisfaction, network resilience and capacity can be improved by adjusting agility, resilience and survival sustainability to influence different component network costs. Highlights A novel multi-period 4PL network model under viability constraints is presented. The CHHDLQL algorithm for construction and perturbation coevolution is proposed. The stress tests apply to the 4PL network, including demand, disruption and 3PL. 4PL improves demand satisfaction, resilience and capacity by adjusting viability.

Fermatean fuzzy Z-analytic hierarchy process: An application to third party logistics providers

To decrease the impact of ambiguity, fuzzy sets are frequently used to decide if an element belongs to a set. Various fuzzy set extensions differ from others in how uncertainty is expressed in the definition of membership functions. This paper presents a novel extension named Fermatean fuzzy Z-numbers, introducing fuzzy restriction and fuzzy reliability functions with Fermatean fuzzy membership functions. By utilizing fuzzy Z-numbers to delineate membership degrees, considering both restriction and its reliability, in tandem with Fermatean membership functions offering an expanded value spectrum, the assessment of linguistic evaluations using Fermatean fuzzy Z-numbers can yield more pragmatic outcomes in decision evaluations amidst high uncertainty. Moreover, the interval-valued Fermatean fuzzy-Z-analytic hierarchy process is developed to explore the impact of proposed interval-valued Fermatean fuzzy-Z numbers on the multi-criteria decision-making process, demonstrated in the context of third-party logistics provider selection. Adding fuzzy reliability functions to the decision-making process improves how uncertainty is represented by considering variations in confidence levels associated with each decision, thus aiding in the clearer expression of decisions. Additionally, the proposed method's outcomes are compared with the outcomes of the current approaches.

A Study on Supply Chain Risks Impacting the Use of Third-Party Logistics Providers: Applying 4IR Technologies Utilization Perspective

A Study on Supply Chain Risks Impacting the Use of Third-Party Logistics Providers: Applying 4IR Technologies Utilization Perspective

APPLICATION OF PFAHP-GTOPSIS METHODS FOR THIRD-PARTY LOGISTICS PROVIDER SELECTION

Companies are now considering the option of outsourcing as hedges cost and increase productivity by concentrating on their core skills to update their supply chains due to the competition in global markets, the use of higher-quality products, and rising customer demands. They must carefully select and identify which company to collaborate with before outsourcing their numerous logistics-related tasks to Third-Party Logistics Providers (3PLP). However, the existence of uncertainties and human influence in 3PLP selection problems leads to the usage of fuzzy or related set theories. By incorporating Multi-Criteria Decision Making (MCDM) methods with fuzzy numbers and grey numbers, practical tools can be composed to address the imprecision of subjective judgments. From this perspective, an integrated MCDM model is proposed to provide insight into the 3PLP evaluation and selection. The model comprises an integrated framework with Pythagorean fuzzy numbers and grey numbers. The proposed model has applied a 3PLP a company in the food industry to fulfill customer orders. The evaluation criteria weights are calculated using the Pythagorean Fuzzy Analytic Hierarchy Process (PFAHP) method, and the 3PLPs are ranked using the grey Technique for Order Preference by Similarity to Ideal Solution (GTOPSIS) methods to find the best 3PLP. The analyses and findings concluded that cost, service quality, and on-time delivery were the three criteria that had the greatest influence

New exact and heuristic algorithms for general production and delivery integration

This study considers a general production and delivery integration problem, commonly faced by a manufacturer that adopts make-to-order and commit-to-delivery business strategies. In the problem, the manufacturer determines acceptance or rejection of customers, produces products for accepted customers, and cooperates with third-party logistics providers who offer multiple shipping modes chosen by the manufacturer to deliver the finished products to customers. To better reflect the practical needs, this problem takes into account nonlinear production cost functions, nonlinear earliness and tardiness penalty functions, and nonlinear shipping cost functions of both shipping time and shipping quantity. The problem is to determine an integrated customer acceptance, production, and delivery plan by minimizing the total cost of production, shipping and inventory holding, and the total penalty of rejection, earliness, and tardiness. We investigate two variants of the problem where splittable delivery for the orders from customers is allowed and where splittable delivery is not allowed. For both the variants, we develop exact algorithms which achieve pseudo-polynomial running time in some practical situations, and design column generation-based heuristic algorithms to find near-optimal solutions efficiently. The computational results demonstrate that the heuristic algorithms are capable of generating near-optimal solutions for the instances generated randomly, with average optimality gap less than 4% in a reasonable running time.

Cooperative strategies of emission reduction in the 3PL-led supply chain

Abstract Accepted by: M. Zied Babai The third-party logistics (3PL) industry has grown rapidly over the past few years, and its emission reduction behaviour is gaining attention. This paper considers a supply chain system composed of a manufacturer, a retailer and a 3PL provider, in which both the manufacturer and the 3PL make the low-carbon investment. 3PL is a leader in the low-carbon supply chain. To promote emission reduction in logistics, the manufacturer and the retailer separately share the logistics emission reduction costs of the 3PL. Through comparing the no-sharing, manufacturer-sharing and retailer-sharing models, we discuss the cost-sharing strategy preference of each participant and analyze the impact on environmental benefit and social welfare. The results show that cost-sharing can effectively improve product demand, which also supports society in obtaining higher benefits. Moreover, the 3PL tends to be shared by the retailer when the low-carbon investment cost of logistics is high and the investment cost of production is low. Both the manufacturer and the retailer prefer the other party to share the cost, but sharing it together can effectively alleviate free-rider behaviour.

Development of the conceptual business model of a third-party logistics provider for Indonesian small contractors

Third-party logistics (TPL) providers have shown positive impacts on supporting large construction projects. Nevertheless, their role in smaller construction still requires further clarification. Small contractors, facing logistics challenges in material supply, are frequently underrepresented in research. We propose a TPL model designed as an intermediary between suppliers and small contractors for consolidating materials. In the initial phase, TPL's business model should be developed for its business foundation. Therefore, this study aims to develop TPLS's conceptual business model that addresses Indonesian small contractors. Three interview themes were employed in this research, involving three distinct groups of small contractors to explore their capacities within construction work, their assessments of specific materials, and their logistical practices. Based on the nine blocks of the Business Model Canvas (BMC), this study found that TPL can ensure material supplies for small construction projects by coordinating sourcing, providing temporary storage, and delivering materials through building strategic partnerships with material suppliers, transportation service providers, and warehousing facility providers. Furthermore, TPL's conceptual business model allows small contractors to gain better access to material supply while providing suppliers with certainty of material purchasing demand. Nonetheless, achieving successful TPL implementation requires dedication from every stakeholder in their assigned roles.

P, q-Spherical fuzzy sets and their aggregation operators with application to third-party logistic provider selection

The selection of an appropriate third-party logistics (3PL) provider has become an inescapable option for shippers in today’s business landscape, as the outsourcing of logistics activities continues to increase. Choosing the 3PL supplier that best meets their requirements is one of the most difficult difficulties that logistics consumers face. Effective decision-making (DM) is critical in dealing with such scenarios, allowing shippers to make well-informed decisions within a restricted timeframe. The importance of DM arises from the possible financial repercussions of poor decisions, which can result in significant financial losses. In this regard, we introduce p, q-spherical fuzzy set (p, q-SFS), a novel concept that extends the concept of T-spherical fuzzy sets (T-SFSs). p, q-SFS is a comprehensive representation tool for capturing imprecise information. The main contribution of this article is to define the basic operations and a series of averaging and geometric AOs under p, q-spherical fuzzy (p, q-SF) environment. In addition, we establish several fundamental properties of the proposed aggregation operators (AOs). Based on these AOs, we propose a stepwise algorithm for multi-criteria DM (MCDM) problems. Finally, a real-life case study involving the selection of a 3PL provider is shown to validate the applicability of the proposed approach.

Enhancing third-party logistics providers partnerships: An approach through the D.L.A.R.C.S supply chain paradigm

The effective selection of third-party logistics providers (3PLs) is crucial for achieving optimal supply chain performance. This study addresses the challenge of 3PL selection by adopting the comprehensive Digital, Lean, Agile, Resilient, Circular, and Sustainable (D.L.A.R.C.S) supply chain paradigm, which encompasses dimensions vital for managing modern supply chains, including digital, lean, agile, resilient, circular, and sustainable aspects. Recognising the interconnectedness of these dimensions, this paradigm emphasises their collective importance in enhancing supply chain operations. Utilising fuzzy SWARA (Step-wise Weight Assessment Ratio Analysis) and BWM (Best Worst Method) techniques, the study evaluates and ranks 3PLs based on their performance within these dimensions. The analysis reveals pivotal criteria such as purchasing price, transportation cost, removal of wastes, service costs, reduction in costs, and crisis and risk management as paramount considerations in the 3PL selection process. These criteria not only provide specific insights but also serve as a foundation for a data-driven approach to decision-making. This research, beyond offering strategic alignment insights for outsourcing, contributes substantively to the broader discourse on supply chain management. The methodology employed in this study integrates diverse dimensions, offering a robust framework for 3PL selection, thereby enhancing operational efficiency and sustainability across industries. The findings offer valuable insights for tyre manufacturers seeking to optimise their logistics operations within the D.L.A.R.C.S. framework, contributing to the advancement of supply chain management in the tyre industry and beyond.

Assessing the Strategic Contributions and Complexity Mitigation by Third-Party Logistics Providers within the Electronic Industry.

Assessing the Strategic Contributions and Complexity Mitigation by Third-Party Logistics Providers within the Electronic Industry.

Decision-making for substitutable products in a retailer dominant channel involving a third-party logistics provider

Decision-making for substitutable products in a retailer dominant channel involving a third-party logistics provider

Third-party Logistics Provider Selection in the Industry 4.0 Era by using a Fuzzy AHP and Fuzzy MARCOS Methodology

Third-party Logistics Provider Selection in the Industry 4.0 Era by using a Fuzzy AHP and Fuzzy MARCOS Methodology

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.

Evaluation of third-party logistics service providers for car manufacturing firms using a novel integrated grey LOPCOW-PSI-MACONT model

Automotive businesses often delegate logistical tasks to third-party logistics (3PLs) service providers to acquire a competitive edge in the dynamic market. Nevertheless, selecting the most suitable third-party logistics (3PL) partner is a multifaceted undertaking that needs careful evaluation of several criteria and alternatives. This research aims to introduce an integrated grey Multiple Criteria Decision Making (MCDM) framework for automotive businesses to deal with the multidimensional 3PL selection decision problem. This framework incorporates an enhanced Preference Selection Index (PSI), Logarithmic Percentage Change-driven Objective Weighting (LOPCOW), and Mixed Aggregation by Comprehensive Normalization Technique (MACONT). The LOPCOW-G and grey PSI (PSI-G) methods extract the criterion weights, whereas the MACONT-G method ranks the alternatives. The suggested framework's practicality is shown by conducting a case study about evaluating and selecting a third-party logistics (3PLs) provider. The findings indicate that the parameters of significant importance are “skilled workforce (0.0977),” “financial strength (0.0901),” and “IT-IS competence (0.0839).” Furthermore, TPL4 has been recognized as the most optimum option with a value of 0.4797. The MACONT-G model is as well compared against other grey MCDM techniques to assess the validity of the proposed model. The Pearson correlation coefficient between MACONT-G and the other models based on grey sets is 0.958, suggesting a significant and positive link. Furthermore, it is worth noting that a sensitivity analysis has been conducted to validate the accuracy and reliability of the created framework. In conclusion, this study has identified managerial and policy implications that might assist policymakers and executives in effectively evaluating 3PL providers.

The importance of warehouses in logistics outsourcing: benchmarking the perspectives of 3PL providers and shippers

PurposeAn ever-increasing number of companies outsource logistics activities to third-party logistics (3PL) providers to beat the competition. From the buyer's (shippers') perspective, selecting the right 3PL provider is crucial, and from the 3PL provider's perspective, it is imperative to be attractive and to retain clients. To this aim, a potential lever can be physical assets, such as warehouses, which the literature has traditionally neglected. The objective is to benchmark the importance of warehouses for 3PL providers to attract/retain clients and for shippers to select the right 3PL provider.Design/methodology/approachThe authors performed an empirical investigation through interviews on dyads (3PL providers/shippers) and utilized the Best-Worst Method (BWM) to rank the criteria used in the 3PL buying process and allow the warehouse's role to emerge.FindingsResults show that the 3PL buying process consists of four phases and three evaluation steps. The selection criteria are classified into three groups: order qualifiers, order winners and retention factors. The warehouse has different levels of importance throughout the process. It appears that it can indirectly enhance the attractiveness and retention capability of 3PL providers through other selection criteria.Originality/valueBy combining the resource-based view and the customer value theory, this research extends the theory on logistics outsourcing by studying the phases of the 3PL buying process and scrutinizing the criteria used in different evaluation steps. The research adds a double perspective of analysis (3PL providers and shippers), which is missing in the literature, and focuses on the importance of warehouses.

Evaluating the Feasibility of a Shared-Fleet Operation in Healthcare Logistics between Public Organisations

Shared-fleet logistics involves collaboration between two or more companies to combine workloads and vehicle capacity to improve vehicle utilisation and transport efficiency and to reduce costs. This study considers the potential environmental and economic benefits of implementing a shared-fleet collaboration between two public organisations: a local government authority and a National Health Service (NHS) Trust. The research focuses on a specific case study using a historical dataset of vehicle movements, wherein the local authority’s fleet of electric courier vehicles is shared with the NHS Trust for transporting pathology samples from 78 doctors’ surgeries to a laboratory for analysis, thereby replacing the reliance on a third-party logistics provider. The benefits suggested by the results included a 17% reduction in costs, a 3% decrease in overall vehicle kilometres travelled, a 69% decrease in carbon dioxide (CO2) emissions, a 40% reduction in vehicle numbers, and a 27% reduction in total duty time. These results emphasise the considerable potential of shared-fleet operations to alleviate both environmental and economic problems in urban logistics, encouraging public sector organisations to actively pursue the implementation of collaborative solutions to enhance the efficiency of their own-account vehicles while making positive contributions to environmental sustainability.

Sustainable Evaluation of Major Third-Party Logistics Providers: A Framework of an MCDM-Based Entropy Objective Weighting Method

This study aims to efficiently assist decision makers in evaluating global third-party logistics (3PL) providers from the perspectives of economic, social, and environmental sustainability and explore the determinants of the 3PL providers’ performance. In doing so, an integrated framework for an MCDM-based entropy objective weighting method is proposed for the first time in a logistics industry assessment. In the first stage, the entropy method defines the weight of the decision criteria based on real data collected from the top 15 global 3PL providers. This study lists the prominent quantitative evaluation criteria, taking into consideration the sustainability perspective. The advantage of the entropy method is that it reduces the subjective impact of decision makers and increases objectivity. In the second stage, the measurement of alternatives and ranking according to compromise solution (MARCOS) method is used to rank the 3PL providers according to their performance on the basis of these criteria. Sensitivity analysis and comparative analysis are implemented to validate the results. The current research work is devoted to the emerging research topic of sustainable development in the logistics industry and supply chain management. The proposed model identifies key performance indicators in the logistics industry and determines the most efficient 3PL providers. Consequently, the results show that the carbon dioxide emissions (20.50%) factor is the most important criterion for the competitiveness of global logistics companies. The results of this study can help inefficient 3PL providers make strategic decisions to improve their performance. However, this study only focuses on 15 companies due to a lack of data. The integration of these two techniques provides a novel way to evaluate global 3PL providers which has not been addressed in the logistics industry to date and as such remains a gap that needs to be investigated.