3PL Providers Research Articles

Optimizing last-mile delivery of essential medicines in Nigeria: Insights from Niger State’s health-care supply chain

Last-mile delivery of health commodities is a critical component of efficient supply chains, and third-party logistics (3PL) providers are pivotal in ensuring cost-effective and reliable product distribution. This study explores the implementation of last-mile delivery outsourcing by government-operated warehouses and drug management agencies (DMAs). This research focuses on the relationship between 3PL utilization and key performance metrics, such as cost reduction, timely delivery, and end-user satisfaction. This study combines a literature review, surveys, and interviews conducted with employees of the DMAs in Minna, Niger State, to establish significant correlations. The findings show that using 3PLs significantly reduced operational costs, improved the frequency of timely deliveries, and enhanced end-user satisfaction. These findings underscore the need for continued engagement with 3PL providers to optimize supply chain performance and improve service delivery outcomes. Managers are recommended to maintain and expand such collaborations to sustain these benefits.

Using 3rd -Party Logistics Services OR Developing Own Capability to Cater to ECommerce Demands - A comparative Analysis

Ecommerce is an inseparable part of modern global lifestyle, connecting people across international borders and enabling sellers to access global. Despite growing massively over the last couple of decades, its growth is far from over. In fact, the pandemic has acted as an accelerator and the growth momentum is continuing despite people returning to the conventional brick and mortar shops. Ecommerce innovations are constantly being rehashed and improved – especially after the global pandemic this transition is now innovating at a much faster pace. For responding to the ever-increasing demand for swifter yet efficient fulfillment of customer order along with timely shipment, a larger number of e- commerce businesses are turning towards third-party logistics or 3PL providers. While it offers them the freedom from the hassles of storing and delivering finished products to the end-users, the human resource that is therefore freed, can then focus on core competencies of the business thus allowing them to give attention to product development, innovation along with marketing and sales. There is always the risk of poor fulfillment and delayed shipments or goods getting damaged in transit which deteriorates customer satisfaction and company profitability. This article compares the use of third-party logistics (3PL) against building in-house capabilities and highlights the virtue of careful selection and employment of experienced 3PL in helping an enterprise ride the anticipated growth wave by offering cost advantages and flexibility.

A Comprehensive Approach for Selecting Third-Party Logistics Providers

The finest third-party logistics (3PL) supplier is a vital decision for businesses trying to streamline their supply chain operations. In order to free up time for businesses to concentrate on their core skills, third-party logistics providers offer a variety of services, such as distribution management, warehousing, and transportation. However, selecting the best 3PL supplier necessitates a rigorous assessment of variables including sector expertise, technical prowess, service quality, scalability, and cost-effectiveness. This introduction discusses the significance of choosing the best 3PL supplier and emphasizes important factors to take into account when making a choice. It is essential since there is a chance that third-party logistics (3PL) provider selection study may boost the supply chain's effectiveness and competitiveness. Firms may make selections that are tailored to their unique requirements by recognizing and assessing the elements that affect the choosing process. Proper 3PL selection may boost market response, save costs, expand the capacity of operations, and improve customer happiness. As a result, research in this field helps to create best practices and strategies that enhance supply chain management and promote entrepreneurship. A multi-criteria decision-making approach called The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is used to rank and choose the best option from a list of options. To determine how closely each alternative resembles the ideal answer, TOPSIS takes into account both positive and negative features. Based on the greatest distance from the inverse idealistic and the lowest distance to the positive ideal, the outcome score is calculated. This approach facilitates decision-making processes in a variety of contexts, such as project prioritization, supplier selection, and investment appraisal. Alternative parameters taken as 3PL-1, 3PL-2, 3PL-3, 3PL-4, 3PL-5. Evaluation parameters taken as Delivery Service (%), Quality of the Customer Experience (Quos), Coverage of the EU Territories (%), Flexibility, and Cost (EUR/km). From the result it is seen that 3PL-2 secures the first rank which is acquired by the TOPSIS method. To secure the first place on the table consistency will be the key factor which was maintained by 3PL-2

‘Logistics 4.0’ technologies in the 3PL industry: a maturity model

Logistics 4.0 is a recent paradigm derived from the Industry 4.0 paradigm applied to the logistics sector. Several new technologies have been developed to improve logistics performance. The present research aims to build a maturity model to support 3PL providers in assessing their level of maturity and identifying the areas in which to invest to improve the logistics service offered through the implementation of Logistics 4.0 technologies. The maturity model was developed using a structured framework of four main steps: the definition of the model scope; the model design (literature review on Logistics 4.0 and the existing maturity models); the model composition and validation; and pilot tests in three relevant 3PL providers. The proposed maturity model has four constructs (i.e. strategic outcomes, requirements, Logistics 4.0 technologies, managerial and capability supporters) and four maturity levels (i.e. initial, intermediate, advanced, cutting-edge).

Criteria for selecting third-party logistics service providers: Systematic Literature Review

Third-party logistics (3PL) is a strategic business partner for companies in carrying out company business activities that are outsourced or cannot be handled themselves. Mistakes in choosing a 3PL can have negative impacts on the company such as financial losses, reducing service quality, reducing customer trust, reducing the company's image, and so on. This article aims to classify third-party logistics based on current issue trends, the methods used in selecting criteria, and what criteria they produce. Using Systematic Literature Review, researchers reviewed, classified, and analyzed 56 relevant articles published in the 2020-2023 period from the Scopus database. The results of this review reveal that 3PL providers can be classified based on issue trends and company goals in selecting them, namely Traditional 3PL, Sustainable 3PL, Sustainable-resilient 3PL, Green 3PL, Gresilient 3PL, Traditional Third-Party Reverse Logistics, and Sustainable Third-Party Reverse Logistics. The priority criteria in selecting a 3PL provider are closely related to the 3PL classification, the industrial sector and business activity being outsourced, the country where the company operates, and the dimensions or attributes used in developing the criteria.

A branch-and-cut algorithm for the time-dependent vehicle routing problem with time windows and combinatorial auctions

The urban logistics industry typically faces traffic congestion problems that result in variation of travel times across the day and impose a great challenge in routing design. While companies may either use a private fleet of delivery vehicles or outsource the tasks to the third-party logistics (3PL) providers to fulfill their logistics demand, some companies might employ a combination of both when their resource is unable to cope with demand or if demand fluctuates significantly over time. To tackle both challenges, we focus on a new variant of the vehicle routing problem known as the time-dependent vehicle routing problem with time windows and combinatorial auctions (TD-VRPTWCA), which considers time-dependent travel times in the routing design of the private fleet while selecting competitive bids from the 3PLs to serve a subset of the customers economically. The goal is to minimize the sum of the travel cost incurred by the private fleet and the outsourcing cost charged by the 3PLs for the chosen bids. To solve this problem, we present an arc-flow model with nine families of valid inequalities to strengthen the linear relaxation of the model. Based on this, a branch-and-cut approach is developed and evaluated on instances adapted from the well-known Solomon’s benchmark data. Extensive computational results demonstrate the effectiveness of the proposed method.

Active learning based hyper-heuristic for the integration of production and Transportation: A third-party logistics perspective

The integration problem of production and transportation (IPPT) is one of the most important decision issues in real-life manufacturing and flow industries. To illustrate its potential for improving difficult production and transportation processes, we focus on a challenging case of IPPT, namely the distributed no-wait flow-shop and transportation integrated scheduling problem (DNWFSTISP) considering third party logistics (3PL), which occurs in many practical industries. DNWFSTISP consists of integrating the well-known distributed no-wait flow-shop scheduling and dedicated vehicle routing in the sense of 3PL while minimizing the total cost. First, we investigate the integration approach of the production and transportation of DNWFSTISP and present three problem-specific loading heuristics, which account for both a make-to-order strategy and 3PL providers to improve customer satisfaction. Second, we propose an active learning based hyper-heuristic algorithm (ALHHA) to solve the problem. ALHHA is unique in that it relies on an active learning based high-level exploration to discover promising search regions and a neighborhood search based low-level exploitation to intensively examine given search regions. Third, we assess the composing ingredients of the proposed ALHHA on 40 instances with up to 200 jobs and 7 factories to shed light on their impacts on the performance of the algorithm. Moreover, we make the 40 instances and solved upper bounds publicly available, which would be valuable for future research on DNWFSTISP.

Managing Warehouse Risks for 3PL Providers: A Novel Approach Based on FMECA-DEA

Managing Warehouse Risks for 3PL Providers: A Novel Approach Based on FMECA-DEA

Managing logistics risks in pharmaceutical supply chain: a 4PL perspective

Supply chain risks and vulnerabilities have been growing recently due to the global, interconnected, and complex networks. The Pharmaceutical Supply Chain (PSC), as a critical national asset, requires increased attention to mitigate the severe consequences of global events. With various risks impacting both the firm’s performance and the lives of patients, effective risk management is paramount for the PSC. This empirical study focuses on the UK-based Fourth-Party Logistics (4PL) provider, which manages pharmaceutical manufacturers’ logistics operations. The 4PL provider’s past experiences with unexpected risky events have influenced its performance. This study aims to explore inherent logistics risks, evaluate them, and recommend mitigation strategies. An integrated approach considering probability, impact and manageability parameters is proposed for risk assessment. In identifying 11 risks from the 4PL perspective, structured interviews are used to gather risk information. The probability of risk occurrence, severity of impact, and manageability are quantified. The delivery delay should be given priority in the follow-up risk management process, while counterfeiting has the least priority. Finally, three resilience strategies named improving flexibility, redundancy, and creating a risk culture are proposed for the 4PL case company. The study offers multiple theoretical and managerial implications based on its findings.

The role of relationship commitment in managing logistics outsourcing in the digital economy

PurposeDigitalization brings complexity and challenges to the relationship governance between logistics outsourcers and their providers. Drawn on resource dependence theory (RDT) and resource-based view (RBV), this study aims to examine the role of relationship commitment in simultaneously managing dependence and improving operational performance in logistics outsourcing in the digital economy, as well as the contingent factors (i.e. communication, relationship length, and company size) that affect the effectiveness of relationship commitment.Design/methodology/approachBased on data collected from 130 third-party logistics (3PL) users in China, our model was tested with the partial least squares (PLS) approach.FindingsFirst, relationship commitment is necessary for 3PL users to manage dependence on 3PL providers and improve operational performance in the digital economy. Second, communication helps 3PL users to develop higher relationship commitment but weakens the motivating effect of dependence on relationship commitment. Third, a long relationship history develops inertia to diminish the effectiveness of dependence on driving relationship commitment while it boosts the impact of relationship commitment on operational performance. Last, company size is an important signal to amplify the effectiveness of relationship commitment for operational performance enhancement.Originality/valueThis study contributes to the logistics outsourcing literature by integrating RDT and RBV to explain the twofold roles of relationship commitment, simultaneously tackling dependence and enhancing operational performance in the digital economy. Additionally, it expands the understanding of the boundary conditions (e.g. communication, relationship length, and company size) on these twofold roles.

Логістика електронної комерції: стійкість ланцюгів постачання

The global dynamics of e-commerce development are analyzed. The main drivers of е-сommerce development, in particular: ease of access to the Internet, development of social networks, increased competition, increased consumer expectations are identified. The current state and features of the development of е-сommerce in Ukraine have been studied and summarized. Consumer priorities when buying online were identified: saving money, proof of availability of the necessary product, saving time, ease of choice, security, etc. It has been determined which social networks are channels for online transactions in Ukraine. It has been established that logistics is a key factor in the success of е- сommerce. OTIF is an indicator of the quality of е-сommerce logistics. A few delivery delays may not be disastrous, but they can cause disruptions and send ripple effects in supply chains. Businesses increasingly outsource their logistics operations to 3PL providers to benefit from their expertise, infrastructure, and economies of scale. Sources of failures in е-сommerce supply chains have been investigated. Actual problems faced by logistics operators have been identified, among them: rising costs of transportation, shortage of vehicles, limited infrastructure, cyber security, labor shortage, last mile logistics, reverse logistics. Strategies for increasing the resilience of supply chains are proposed: increasing visibility, multisourcing, lean best practices, bulding security, 4PL partnership, сoopetition, сooperation, reshoring/nearshoring/friendshoring. The e-commerce logistics market is expected to experience significant growth in the coming years. Technological advancements like artificial intelligence, blockchain, and big data analytics will play a key role in improving efficiency and resilience in logistics operations. Businesses should partner with reliable logistics providers, invest in innovative technologies, and optimize their logistics processes. Consumers should be aware of potential delays and delivery issues and choose companies that offer quality logistics services.

Attitudes of 3PL Providers of the Companies towards the Activities of Organizational Performance

Businesses today specialize in their core competencies and outsource their other operations due to the emerging perception of competition brought on by the large-scale similarity of production, the quick spread of technology and information systems, and the disappearance of international borders. One of the most common fields of outsourcing activity is Third Party Logistics (3PL) service, and the Organizational Performance elements of 3PL service providers are listed as Service Quality, Relationship Management and Organizational Effectiveness. This research aims to examine the Organizational Performance criteria of the 3PL providers serving the production enterprises and to evaluate the relationship structure between the mean and standard deviation values of the statements in the survey. The empirical results obtained from frequency, regression and standard deviation analyses show that Guanxi, Reliability, Assurance, and Trust positively affect Organizational Effectiveness. However, only Trust has a positive and statistically significant impact on Service Quality

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.

A model to describe logistics service architecture based on product architecture

AbstractThe growth in e-commerce has led to increased demand for logistics services. This puts a pressure on third-party logistics (3PL) providers who struggle with increasing operating costs and heightened competition. These providers could potentially exploit the advantages of modularisation, but few studies address the design of modular logistics services. This study explores modular design of logistics services and proposes a model to describe logistics service architecture based on product architecture. A case study shows that warehousing services can be described in three domains.

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.

Sustainable supply chain design: A case of collaborative wholesale distribution

We assess the cooperative network design's efficiency outcomes in Morocco's food wholesale distribution. Before joining the collaborative coalition, we provide decision-makers with an initial preference instrument to assess the environmental and financial effects of cooperative freight distribution. We assess the practicality of incorporating decisions from the Facility Location Problem (FLP) and Vehicle Routing Problem (VRP) into partnerships for sustainable freight transportation. The coalition utilizes a 3PL provider's fleet of cars, therefore the Vehicles are exempt from having to go back to the consolidation depot; as a result, the fundamental issue becomes an open location routing problem (OLRP). Although there have been several studies on open location-routing problems, their application to horizontal shipper collaboration is new. For diverse collaboration scenarios, our computational approach is founded on two-echelon OLRP under a multiple objective and periods’ framework. Every shipper involved in the partnership needs to receive gains. Therefore, evaluating the benefits to each individual shipper is essential for an effective and durable collaboration. This study addresses the issue of profit allocation to determine the collective and individual shipper's savings. By considering not just economic variables but also environmental factors, the Open LRP may help firms plan and optimize their collaborative supply chains in a more sustainable manner.

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.

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.

Using Simulation to Determine Resource Requirements for Outsourcing Outbound Logistics Process

Outsourcing has become an important approach for organizations to improve their focus on core business and thus increase their performance since 1980s (Madsen, 2017). Many organizations outsource non-core activities with the intention to reduce costs, concentrate on core activities, gain access to skilled workforce, and etc. Logistics activities are one of the popular functions for organizations to outsource due to lack of skill and resources. Nowadays, outsourcing logistics activities is becoming a practice worldwide (Yang, 2014). Logistics outsourcing has proven to be an effective way for organization to improve customer services, reduce logistics costs, and gain competitive advantage (Aguezzoul, 2014; Jonsson, 2008; Kamble and Gawankar, 2016). This results in an emerging of 3PL or Third-party logistics provider, an external logistics service provider offering single or multiple logistics activities to its customers, which typically is on contract basis (Yang, 2014). The global 3PL market reached $750 billion in 2014. 80% of all Fortune 500 companies and 96% of the Fortune 100 used some form of 3PL services (Menner, 2015). Despites the benefits, there are some risks associated with loss of control, long-term commitment, and the failure of 3PL to perform their works. Therefore, it is crucial for a company to invest time during initial stages of the outsourcing relationship to ensure value is achieved throughout the process. Keywords: Outsourcing, Simulation Modelling, Contract Management, Resource Requirements, Resource Allocation