3PL Provider Selection Research Articles

Multistakeholder Strategic Third‐Party Logistics Provider Selection: A Real Case in China

AbstractOutsourcing logistics to third‐party logistics (3PL) providers is becoming an increasing trend for companies seeking improved customer service and competitiveness. Choosing a suitable and competitive logistics provider has become more important than ever. In this study, we developed an evaluation and selection framework on strategic 3PL provider selection on the basis of a real case application in China. Multiple criteria and multiple stakeholders were considered to balance the various measurements in this framework. In the actual application, we chose the PROMETHEE technique as our specific evaluation method and we also assessed its effectiveness with further analysis. The results show that our proposed holistic framework is well suited for the strategic 3PL provider selection problem.

Fuzzy based appraisement module for 3PL evaluation and selection

Purpose – In today’s’ highly competitive market, outsourcing logistic activities have become a global trend as it offers wide range of services including transportation, distribution, packaging, labeling, warehousing, freight forwarding and order fulfillment. The demand of third-party logistics (3PL) provider becomes an increasingly important issue for corporate seeking improved customer service, operational efficiency, logistics costs as well as capital expenditure reduction. However, choosing a proper 3PL provider is a kind of multi-criteria decision making problem under consideration of complicated criteria hierarchy. Therefore, it seems necessary to develop an efficient appraisement module towards performance evaluation as well as selecting the best 3PL provider. The paper aims to discuss these issues. Design/methodology/approach – The present paper proposes a fuzzy based appraisement platform for evaluation and selection of 3PL providers. The theory behind interval-valued fuzzy numbers (IVFNs) has been utilized to aid the said decision-modeling. Based on two appraisement modules for 3PL evaluation; empirical data have been analyzed to validate case application. Findings – The proposed method has been found efficient for solving the group decision-making problem under uncertain environment due to vagueness, ambiguity associated with decision-makers’ subjective judgment. The proposed appraisement platform has been explored by an Indian automobile part manufacturing company at eastern part of India. 3PL providers have been evaluated individually to check their performance level with respect to various evaluation attributes. Apart from estimating overall performance metric, the model presented here can identify ill-performing areas which necessitate future attention. Originality/value – The major contributions of this work have been summarized as follows: First, development and implementation of an efficient decision-making procedural hierarchy to support 3PL evaluation and selection. Second, an overall performance metric has been introduced. Third, concept of IVFNs has been efficiently explored to facilitate such a appraisement cum selection decision making. Final, the appraisement index system has been extended with the capability to search ill-performing areas which require future progress.

Assessment of 3PL Providers for Hazardous Materials

Hazardous materials (hazmat) production and transportation have been increasing continuously. Especially, as they could harm people and environment during hazmat transportation, the firms tend to give hazmat transportation and other logistic activities to third party logistics (3PL) providers. Although there are many studies on hazmat, to the best of our knowledge we have not met the studies on 3PL provider selection for hazmat. Therefore, the aim of this study is to propose an assessment multi criteria decision making (MCDM) model for the selection of 3PL provider for hazmat. In this model, fuzzy decision making trial and evaluation laboratory (DEMATEL) is used to weight of criteria. Fuzzy DEMATEL is a comprehensive technique to build and analyze a structural model involving causal relationships among complex criteria. Fuzzy TOPSIS is utilized to assess the alternatives. To show applicability and effectiveness of the proposed model, an illustrative example is presented in our study.

Developing a Chance-Constrained Free Disposable Hull Model for Selecting Third-Party Reverse Logistics Providers

Demand of third-party reverse logistics (3PL) provider becomes an increasingly significant topic for corporations looking for enhanced customer service and cost reduction. To select the best 3PL providers in the presence of stochastic data, this paper proposes an innovative approach which is based on free disposable hull (FDH). FDH model is one of the classical models in data envelopment analysis (DEA). In many real world applications, data are often stochastic. A successful approach to address uncertainty in data is to replace deterministic data via random variables, leading to chance-constrained DEA. In this paper, a chance-constrained FDH (CCFDH) model is developed and also its deterministic equivalent which is a nonlinear program is derived. Furthermore, it is shown that the deterministic equivalent of the CCFDH model can be converted into a quadratic program. In addition, sensitivity analysis of the CCFDH model is discussed with respect to changes on parameters. Finally, a numerical example demonstrates the application of the proposed model in the field of 3PL provider selection.

Drivers for logistics outsourcing and factor analysis for selection of 3PL provider

Outsourcing of logistics activities has become a common practise by many companies, which implies an efficient choice of the third party logistics (3PLs) providers. This research aims to determine the current situation of outsourcing logistics activities in India. Selection of an efficient and potential set of 3PLs providers is a crucial decision. This decision is influenced by several factors or criteria. In this paper, we identify the factors that are important to the choice of a 3PLs service provider and prioritise them by employing factor analysis.

Use of analytic hierarchy process (AHP) for selection of 3PL providers

Purpose – The purpose of this paper is to present a decision model for selecting a third party logistics (3PL) provider, because international business can be a complex undertaking. It is a multi‐criteria problem, with alternative ways to weigh the importance of the chosen criteria.Design/methodology/approach – The paper used analytic hierarchy process and hierarchical decision model approaches.Findings – Given the criteria, weights and attribute scores, it was found that two 3PLs ranked very closely in the top position. It was also found that a simple ranking of the criteria can produce very similar aggregate weights, provided the number of experts is high enough. The paper contains an extensive literature review on the usage of AHP and related methods in a logistics context.Originality/value – This study applies AHP in a 3PL provider for international business, for the first time in the literature.

Developing a new chance-constrained data envelopment analysis in the presence of stochastic data

Outsourcing in logistics is a very significant theme and third-party reverse logistics (3PL) provider evaluation and selection has to be realised in a careful manner in order to provide the expected benefits. Data envelopment analysis (DEA) has been successfully used to select the most efficient supplier(s) in a supply chain. In this study, a new Russell chance-constrained data envelopment analysis (RCCDEA) approach is proposed to assist the decision-makers to determine the most appropriate 3PL providers in the presence of multiple performance measures that are uncertain. Because of the complexity of the proposed model, a genetic algorithm is presented as a solution procedure to obtain near to optimum solutions. The usefulness of the proposed model and algorithm was validated by its application to an illustrative example.

A combination of Russell model and neutral DEA for 3PL provider selection

The main advantages of logistics partners are to allow the outsourcing company to focus on the principal competency, augment the efficiency, improve the service, reduce the transportation cost, restructure the supply chains and establish the marketplace legitimacy. Determining the appropriate third-party reverse logistics (3PL) provider is a crucial strategic consideration in supply chain management. One of the techniques that can be used for selecting 3PL provider is data envelopment analysis. The objective of this paper is to propose a combination of Russell model with neutral model for 3PL provider selection. A numerical example demonstrates the application of the proposed model.

A 3PL supplier selection model based on fuzzy sets

Outsourcing is an increasingly important task pursued by enterprises seeking improved efficiency. Logistics outsourcing, or third-party logistics (3PL), involves the use of external companies to perform some or all of the firm's logistics activities. In this paper, through analyzing the features and role of third-party logistics, for 3PL provider selection, we propose an indicator system and a method for data integration. We also establish a comprehensive evaluation model for 3PL suppliers based on fuzzy sets; furthermore, we propose a compound quantification model based on centralized quantification values, a comparison method based on the synthesis effect, and a 3PL supplier selection model. A real-world case analysis is provided. The results show that the proposed 3PL supplier selection model can effectively integrate decision preferences into decision processes.

Rationale for utilizing 3PL in supply chain management: A shippers' economic perspective

In this paper we first propose a conceptual framework for evaluating 3PL (third-party logistics) utilization in SCM (supply chain management), in which it is assumed that shippers may enjoy advantages derived from four contributory sources of 3PL specialization: scale, know-how, searching ability, and IT skills. It is also supposed that shippers may particularly benefit from 3PL when facing uncertain business environments. We also apply principal–agent relationships to shippers and 3PL providers. Further, we see enhancing “agency efficiency” as important to obtaining the benefits of 3PL utilization. We also look at the role of 3PL provider selection, the “hold-up” problem under incomplete contracts, and asset ownership. After that we briefly discuss the utilization of 3PL and environmental concerns. These are the main points that we consider related to 3PL utilization. The main contribution of this study is to identify discussion points from models and theories, such as contract theory, that relate to the utilization of 3PL in SCM.

A new chance-constrained data envelopment analysis for selecting third-party reverse logistics providers in the existence of dual-role factors

Outsourcing in logistics is a very significant theme and third-party reverse logistics (3PL) provider evaluation and selection has to be realized in a careful manner in order to provide the expected benefits. In this paper a new chance-constrained data envelopment analysis (CCDEA) approach is proposed to assist the decision makers to determine the most appropriate third-party reverse logistics (3PL) providers in the presence of both dual-role factors and stochastic data. A numerical example demonstrates the application of the proposed model.

DSS for 3PL provider selection in global supply chain: combining the multi-objective optimization model with experts’ opinions

To provide selections of logistics outsourcing providers in a global supply chain, this paper proposes a decision support system (DSS), based on fuzzy analytic network process (FANP) and preemptive fuzzy integer goal programming (PFIGP). For decision-makers, a suitable method for selecting third-party logistics (3PL) is critical under the trends of globalization and specialization. The proposed DSS for 3PL provider selection takes into consideration flexible resource and interactions among providers. When applying multiple attribute decision-making (MADM) to selection of 3PL providers, it is difficult for decision-makers to determine the feasible solution domain under limited resources, especially if the decision problems are NP-complete. Moreover, traditional mathematical programming does not incorporate experts' evaluation of providers. This paper employs FANP to obtain experts' scores of the providers, and then integrates the scores into PFIGP to facilitate selection of a 3PL provider with flexible resources. Finally, this paper uses genetic algorithms to solve the PFIGP. An illustrative example is also given to demonstrate such DSS. The test result shows that the degree of providers' interaction affects the final weight of FANP.

OR Practice—Supporting 3PL Decisions in the Automotive Industry by Generating Diverse Solutions to a Large-Scale Location-Routing Problem

For the distribution of spare parts to car dealers, many automotive companies use a transport network of intermediate hubs or transport platforms, operated by a set of third-party logistics (3PL) partners. The optimization of this network, particularly the selection of 3PL providers and corresponding transport platforms, is a complex decision that needs to be supported by appropriate software tools. In this paper, we develop such a tool, implement it, and show its results on a real-life case study provided by Toyota. The tool is currently in active use at Toyota to study and improve the distribution of spare parts in Germany. Using a tabu search metaheuristic, the developed tool essentially solves a large location-routing problem, but has several innovative features to increase its usefulness. First, the tool generates a set of high-quality but structurally different solutions, rather than a single one. This increases Toyota's negotiating power, increases its ability to analyze its current transport network against possible alternatives, and allows it to quickly switch between different transport networks if unexpected events occur. Second, a commercial vehicle-routing solver is integrated into the tool, to allow for a far more realistic modeling of the vehicle-routing decision.

Evaluation of third‐party logistics (3PL) providers by using a two‐phase AHP and TOPSIS methodology

PurposeThird‐party logistics (3PL) provider selection has gained great attention in logistics management literature. The purpose of this paper is to provide a good insight into the use of a‐two‐phase analytical hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) approach that is a multi‐criteria decision‐making methodology in the evaluation of 3PL providers.Design/methodology/approachIn this paper, after the selection criteria of 3PL providers are determined by modified Delphi method, the weights of criteria have been calculated by applying the AHP method. The TOPSIS method is then employed to achieve the final ranking results. And an actual case example is presented to clarify the methodology. Sensitivity analysis is also given to demonstrate how sensitive the proposed model is to changes in the weights of different main criteria.FindingsThis model provides decision makers with a simple, flexible, and easy‐to‐use approach to evaluate potential 3PL providers efficiently. Findings demonstrate that the proposed benchmarking framework, with minor modifications, can be useful to all firms in their 3PL provider selection decisions.Research limitations/implicationsA two‐phase AHP and TOPSIS methodology is very flexible and suitable for various decision situations. However, selection of the appropriate 3PL provider requires consideration of multiple alternative solutions and evaluation criteria because of complex methodology, and hence it increases the effort.Originality/valueThis is probably the first time that an attempt has been made to apply the modified Delphi method, AHP and TOPSIS methodology in the decision of 3PL provider selection in a Turkish automotive supplier company. This is the most powerful motivation to consider this problem. In addition, the paper is especially of interest to managers as they make decisions on which criteria should be considered in the evaluation process and how a decision model should be structured by using a two‐phase AHP and TOPSIS methodology.

A mathematical model for selecting third-party reverse logistics providers

Generally, many optimisation models of Third-Party Reverse Logistics (3PL) provider selection assume that cardinal data, with less emphasis on ordinal data, exist. However, to select the best 3PL providers, this assumption is not realistic because ordinal data are vital. To deal with this difficulty and select the most efficient 3PL provider with the condition that both ordinal and cardinal data are present, a methodology which is based on Imprecise Data Envelopment Analysis (IDEA) is introduced. A numerical example demonstrates the application of the proposed method.

An integrated fuzzy approach for provider evaluation and selection in third-party logistics

The demand of third-party logistics (3PL) provider becomes an increasingly important issue for corporations seeking improved customer service and cost reduction. The present paper presents an integrated fuzzy approach for the evaluation and selection of 3PL providers. This method consists of three different techniques: (1) use fuzzy Delphi method to identify important evaluation criteria; (2) apply fuzzy inference method to eliminate unsuitable 3PL providers; and, (3) develop a fuzzy linear assignment approach for the final selection. The proposed method enables decision analysts to better understand the complete evaluation process of 3PL selection. Furthermore, this approach provides a more accurate, effective, and systematic decision support tool for 3PL provider selection. Finally, an actual industrial application is presented to demonstrate the proposed method.