Management Science Letters Integration of DEMATEL, ANP and DEA methods for third party logistics providers' selection (original) (raw)
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Integration of DEMATEL, ANP and DEA methods for third party logistics providers’ selection
Management Science Letters, 2016
In a competitive environment many companies usually outsource their logistics functions to the Third Party Logistics (TPL) providers to focus on their core businesses. However, the selection of proper TPL provider is not an easy task because of conflicting quantitative and qualitative criteria. This study presents an integrated model based on three well-known methods Decision Making Trial and Evaluation Laboratory (DEMATEL), Analytical Network Process (ANP) and Data Envelopment Analysis (DEA) for the evaluation and selection of TPL providers. DEMATEL computes the effects between selection criteria while ANP derives the weights of each criterion related with TPL providers' selection problem. Finally DEA presents a mathematical model for ranking TPL providers alternatives with respect to various criteria. The application of integrated model is demonstrated with a case study. The novelty of this study comes from the fact that there is no research in the literature integrating DEMATEL, ANP and DEA for the TPL selection problems.
Evaluation and Selection of a Third Party Logistics Supplier in a Chemical Company
ICTE 2015, 2015
Third party logistics service providers (3PLSPs) evaluation and selection for a long-term as well as a strategic partnership is a very crucial and critical task and it is continually associated with uncertain challenges. To remain efficient and competent in the dynamically changing world of 21st century, organisations have reinforced their supply networks by building strategic partnership among both local and international suppliers. Adding to these, there are growing concerns from stakeholder for ensuring implementation of sustainability dimensions. The aim of this paper is to measure and compare the relative efficiency of the existing 3PLSPs based on the technical and sustainable criteria by using a data envelopment analysis (DEA), to find the best among the 3PLSPs portfolios, for the purpose of selection. Finally, a case study in a manufacturing firm is presented to demonstrate the potential use of the model.
Journal of Multi-criteria Decision Analysis, 2012
When a business decides to outsource its logistics operations to improve its performance, the organization will need to select a third-party logistics provider (3PL) that shares common goals and satisfies service level requirements. In this paper, we identify a set of 3PL performance measures from the perspective of the supply chain and organize them into a time-phased format, beginning with the post production stage and continuing through the delivery of the goods to the customer distribution center. The supply chain flow is presented as a Metrics Arrow. To integrate the performance metrics (PM) into one model, we propose an analytical network process (ANP) to capture all PM and to understand the interrelated influences among them. Additionally, to derive the weights for PM, the proposed ANP model offers managerial insight into the relative impact of each metric as well as warning signals or trigger points within the network of PM. The model provides a realistic framework to choose the 3PL that can help achieve the greatest improvements within the supply chain.
Today, as organizations improve their ability to compete globally, we see that competition innovation and creativity are now shifting to the supply chain. Increased competitive advantage can be achieved only if all supply chain stakeholders are coordinated and integrated with one another. This integration must be created among suppliers, intermediaries, third-party providers, and customers. In addition to the forward supply chain, reverse logistics must also be considered. Amid business complexities, smart organizations are reusing, recycling, and remanufacturing using third-party reverse logistics providers (3PRLP), which affect the performance of the entire organization. The selection and evaluation of reverse logistics providers is important to improving outcomes. Several attributes should be used to select and evaluate 3PRLP. In this paper, an analytic network process (ANP) is used to investigate feedback and relationships among attributes and to identify the most important attributes in the selection and evaluation of 3PRLP. Then a multi-criteria group decision-making is upgraded in uncertainty conditions to guide the process of selecting the best 3PRLP. To deal with uncertainty, intuitionistic fuzzy set (IFS) and grey relation analysis (GRA) will be used. [Mohsen Zareinejad, Habibollah Javanmard. Evaluation and selection of a third-party reverse logistics provider using ANP and IFG-MCDM methodology. Life Sci J 2013;10(6s):350-355] (ISSN:1097-8135).
International Journal of Production Research, 2011
Saaty's AHP is helpful in evaluating alternatives thanks to its effective procedure to determine the relative weights of several comparison criteria. Combining the results of expert interviews, AHP can be very useful for a company in choosing a third party logistics service provider (3PL). However, in the traditional AHP procedure, several results may be rejected when the consistency ratio (CR) of the respondent exceeds a certain threshold. As a consequence, AHP interviews may be repeated several times with a consequent waste of time. In many industrial domains, a faster way to choose a supplier would thus be appreciated. In this paper we propose a mathematical method that combines AHP, DEA and linear programming in order to support the multi-criteria evaluation of third party logistics service providers. The proposed model aims to overcome the limitation of the AHP method, merging experts’ indications with objective judgments which originate from historical data analysis. Suppliers' past performance is thus used to correct eventual errors resulting from the acceptance of interviews where the consistency ratio is high. The proposed model has been validated on the real case of an international logistics service provider.
Evaluation of third‐party logistics (3PL) providers by using a two‐phase AHP and TOPSIS methodology
Benchmarking: An International Journal, 2009
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 ...
A Hybrid MCDM Approach in Third-Party Logistics (3PL) Provider Selection
Mathematics, 2021
Third-party logistics (3PL) is becoming more and more popular because of globalization, e-commerce development, and increasing customer demand. More and more companies are trying to move away from their own account transportation to third-party accounts. One reason for using 3PLs is that the company can focus more on its core activities, while the 3PL service provider can provide distribution activities in a more professional way, save costs and time, and increase the level of customer satisfaction. An emerging issue for companies in the logistics industry is how they can decide on the 3PL evaluation and selection process for outsourcing activities. For the first time, the entropy and the criteria importance through intercriteria correlation (CRITIC) methods were coupled in order to obtain hybrid criteria weights that are of huge importance to decide on the 3PL provider evaluation and selection process. The obtained criteria weights were further utilized within the additive ratio as...
Supplier Evaluation and Selection for Logistics Outsourcing: A Conceptual Framework
The Third North American Conference On Industrial Engineering and Operations Management, 2018
Outsourcing is hiring an external company to do one or more internal activities because these activities are either difficult to achieve, or costly to do in-house. This external hired company is known as Third Party Logistics (3PL). 3PL selection decision inherently is a multi-criterion problem, sometimes with strategic importance to companies. Management science techniques might be helpful tools for these kinds of decision-making problems. Multi-Criteria Decision-Making (MCDM) techniques are often used to solve 3PL problems. In this paper, different types of MCDM are overviewed, and then a framework for 3PL selection is proposed by using a hybrid two-phase Fuzzy Analytic Hierarchy Process (FAHP) to select the best 3PL company providing the most satisfaction for the criteria determined, and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to evaluate the performance of 3PLs. This integration provides a good methodology to rank 3PLs.
Transport Problems
A large number of criteria, the very diverse use of terminology and different classifications of criteria used to select a logistics service provider (LSP) reflect the lack of consensus in defining criteria. Moreover, whether the criteria are consistent with external requirements has not been analysed, which are vitally important for the success and competitiveness of the supply chain. This paper therefore presents a carefully prepared and evaluated classification system of criteria aligned with the requirements of the external environment. A multi-stage methodological approach was used. Selection criteria obtained from the systematic review of literature were first carefully analysed to find potential shortcomings. After that, a cluster method was used to reduce the number of criteria and to aggregate similar criteria. A Pareto analysis (75/25 rule) was further used to rank the criteria according to their frequency of use and consequently according to importance. The obtained categories of criteria (vitally important criteria (C1), very important criteria (C2), important criteria (C3) and less important criteria (C4), using the AHP method, were compared by the experts to define their weights. This paper summarizes and extends the recent literature through a six-step methodological approach and proposes a new classification system of selection criteria.