scholarly journals A Developed Data Envelopment Analysis Model for Efficient Sustainable Supply Chain Network Design

2021 ◽  
Vol 14 (1) ◽  
pp. 262
Author(s):  
Zohreh Moghaddas ◽  
Babak Mohamadpour Tosarkani ◽  
Samuel Yousefi
Keyword(s):  
Supply Chain ◽  
Data Envelopment Analysis ◽  
Social Issues ◽  
Selection Process ◽  
Data Envelopment Analysis Model ◽  
Data Envelopment ◽  
Sustainable Supply Chain ◽  
Efficient Strategy ◽  
Sustainability Concept ◽  
Inputs And Outputs

In recent years, various organizations have focused on considering the sustainability concept in the supply chain (SC) design. Managers try to increase the sustainability of SCs to achieve a competitive advantage in today’s growing market. Designing a sustainable supply chain (SSC) by integrating economic, social, and environmental dimensions affects the SC’s overall performance. To achieve the SSC, decision makers (DMs) are required to evaluate different strategies and then apply the most effective one to design SC networks. This study proposes an assessment approach based on the network data envelopment analysis (DEA) to choose an efficient strategy for each stage of an SSC network. This approach seeks to provide a sustainable design with DMs to avoid imposing additional costs on SCs that result from noncompliance with environmental and social issues. To this end, we consider sustainability-concept-related inputs and outputs in the network DEA model to choose the most efficient strategy for SSC design. The strategy selection process can become an important issue, especially when SCs active in a competitive environment. Accordingly, a crucial feature of the presented model is considering the issue of competition to choose the efficient strategy. Furthermore, undesirable outputs and feedbacks and independent inputs and outputs for intermediate stages in the network system are considered to create a structure compatible with the real world. The output of the proposed approach enables DMs to select the appropriate strategy for each stage of the SSC network to maximize the aggregate efficiency of the network.

Developing a novel data envelopment analysis model to determine prospective benchmarks of green supply chain in the presence of dual-role factor

2015 ◽  
Vol 22 (4) ◽  
pp. 711-730 ◽  
Author(s):  
Amir Shabani ◽  
Reza Farzipoor Saen
Keyword(s):  
Supply Chain ◽  
Data Envelopment Analysis ◽  
Critical Path ◽  
Dual Role ◽  
Green Supply Chain ◽  
Data Envelopment Analysis Model ◽  
Data Envelopment ◽  
Content Type ◽  
Proposed Model ◽  
Inputs And Outputs

Purpose – The purpose of this paper is to develop a model based on data envelopment analysis (DEA) and program evaluation and review technique/critical path method (PERT/CPM) for determining prospective benchmarks. Design/methodology/approach – The idea of determining prospective benchmark is needed for developing a model for future planning where inputs and outputs of systems are influenced by external factors such as economic conditions, demographic changes, and other socio-economic factors. In this paper, the PERT/CPM method estimates prospective inputs and outputs. On the other hand, in particular systems some measures play the role of both input and output. Such factors in DEA literature are called dual-role factors. This paper integrates PERT/CPM technique and the DEA. Findings – The results of the proposed model depict that a present benchmark may not be a benchmark in future. A numerical example validates the proposed model. Originality/value – This paper, for the first time, applies the PERT/CPM technique to incorporate the ideas for identifying prospective benchmarks. Moreover, the proposed model is an alternative solution for classifying inputs and outputs in DEA. Also, the proposed model is utilized in benchmarking green supply chain management.

Evaluation of Supply Chain Efficiency Based on a Novel Network of Data Envelopment Analysis Model

2015 ◽  
Vol 25 (14) ◽  
pp. 1540036 ◽  
Author(s):  
Li Fang Fu ◽  
Jun Meng ◽  
Ying Liu
Keyword(s):  
Supply Chain ◽  
Data Envelopment Analysis ◽  
Decision Makers ◽  
Data Envelopment Analysis Model ◽  
Data Envelopment ◽  
Undesirable Outputs ◽  
Analysis Model ◽  
Multilayer Network ◽  
Supply Chain Efficiency ◽  
Proposed Model

Performance evaluation of supply chain (SC) is a vital topic in SC management and inherently complex problems with multilayered internal linkages and activities of multiple entities. Recently, various Network Data Envelopment Analysis (NDEA) models, which opened the “black box” of conventional DEA, were developed and applied to evaluate the complex SC with a multilayer network structure. However, most of them are input or output oriented models which cannot take into consideration the nonproportional changes of inputs and outputs simultaneously. This paper extends the Slack-based measure (SBM) model to a nonradial, nonoriented network model named as U-NSBM with the presence of undesirable outputs in the SC. A numerical example is presented to demonstrate the applicability of the model in quantifying the efficiency and ranking the supply chain performance. By comparing with the CCR and U-SBM models, it is shown that the proposed model has higher distinguishing ability and gives feasible solution in the presence of undesirable outputs. Meanwhile, it provides more insights for decision makers about the source of inefficiency as well as the guidance to improve the SC performance.

Supply Chain Performance Evaluation With Rough Two-Stage Data Envelopment Analysis Model: Noncooperative Stackelberg Game Approach

2017 ◽  
Vol 17 (4) ◽  
Author(s):  
Morteza Shafiee
Keyword(s):  
Supply Chain ◽  
Performance Evaluation ◽  
Data Envelopment Analysis ◽  
Rough Set Theory ◽  
Stackelberg Game ◽  
Data Envelopment Analysis Model ◽  
Data Envelopment ◽  
Analysis Model ◽  
Managerial Decision ◽  
Two Stage

Rapidly changing environment has affected organizations' ability to maintain viability. As a result, various criteria and uncertain situations in a complex environment encounter problems when using the traditional performance evaluation with precise and deterministic data. The purpose of this paper is to propose an applicable model for evaluating the performance of the overall supply chain (SC) network and its members. Performance evaluation methods, which do not include uncertainty, obtain inferior results. To overcome this, rough set theory (RST) was used to deal with such uncertain data and extend rough noncooperative Stackelberg data envelopment analysis (DEA) game to construct a model to evaluate the performance of supply chain under uncertainty. This applies the concept of Stackelberg game/leader–follower in order to develop models for measuring performance. The ranking method of noncooperative two-stage rough DEA model is discussed. While developing the model, which is suitable to evaluate the performance of the supply chain network and its members when it operates in uncertain situations and involves a high degree of vagueness. The application of this paper provides a valuable procedure for performance evaluation in other industries. The proposed model provides useful insights for managers on the measurement of supply chain efficiency in uncertain environment. This paper creates a new perspective into the use of performance evaluation model in order to support managerial decision-making in the dynamic environment and uncertain situations.

scholarly journals Providing a Model for Ranking Suppliers in the Sustainable Supply Chain Using Cross Efficiency Method in Data Envelopment Analysis

2019 ◽  
Vol 16 (1) ◽  
pp. 43-52 ◽  
Author(s):  
Mohammad Hashemi Tabatabaei ◽  
Ardeshir Bazrkar
Keyword(s):  
Supply Chain ◽  
Data Envelopment Analysis ◽  
Automotive Industry ◽  
Three Dimensions ◽  
Data Envelopment ◽  
Sustainable Supply Chain ◽  
Profit Model ◽  
Analysis Technique ◽  
Secondary Objective ◽  
The Cross

Goals: This research seeks to identify the basic indices of sustainability in three dimensions (economic, social and environmental) in the Iranian automotive industry suppliers by reviewing previous research and ranking the suppliers using a cross efficiency approach.  In this paper, the performance and ranking of sustainable supply chain suppliers are evaluated by presenting a secondary objective model in terms of cross efficiency. Design / Methodology / Approach: In the first step of this research, a preliminary screening of the identified criteria is carried out. the data on the final criteria is collected using a questionnaire. Finally, the evaluation and ranking of suppliers in sustainable supply chain of the automotive industry in Iran is done by the cross-efficiency model presented in this paper. Results: The results showed that, according to the criteria of the triple profit model (including 3 dimensions, 7 criteria), supplier No. 8 was identified as the most efficient decision maker unit (DMU) among 12 suppliers of Iran Khodro Company. Limitations of the investigation:  The main constraints include the timeliness of information gathering and the lack of cooperation of suppliers in providing information. Originality / Value: Using the cross efficiency model in data envelopment analysis technique in the field of evaluating supplier performance is a very practical and unrestricted approach.

scholarly journals Chance-constrained cost efficiency in data envelopment analysis model with random inputs and outputs

2018 ◽  
Vol 20 (3) ◽  
pp. 1863-1898 ◽  
Author(s):  
Rashed Khanjani Shiraz ◽  
Adel Hatami-Marbini ◽  
Ali Emrouznejad ◽  
Hirofumi Fukuyama
Keyword(s):  
Data Envelopment Analysis ◽  
Cost Efficiency ◽  
Data Envelopment Analysis Model ◽  
Data Envelopment ◽  
Analysis Model ◽  
Random Inputs ◽  
Inputs And Outputs
Sign in / Sign up

Export Citation Format

Share Document