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Multiple Criteria Decision-Making Techniques in Sustainable Supply Chains and Logistics Management

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A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Economic and Business Aspects of Sustainability".

Deadline for manuscript submissions: 15 October 2024 | Viewed by 18505

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Special Issue Editors

Dr. Peng Jiang

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Guest Editor

School of Business, Shandong University, Weihai 264209, China
Interests: multiple attribute decision making; supply chain and logistics management; grey system theory

Prof. Dr. Yi-Chung Hu

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Guest Editor

Department of Business Administration, Chung Yuan Christian University, Taoyuan 32023, Taiwan
Interests: sustainability; soft computing; MCDM; information management
Special Issues, Collections and Topics in MDPI journals

Dr. Jingci Xie

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Guest Editor

School of Management, Shandong University, Jinan 250100, China
Interests: logistics and supply chain management; system innovation; transport economic and geography

Dr. Hang Jiang

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Guest Editor

School of Business Administration, Jimei University, Xiamen 361021, China
Interests: grey system; economics; prediciton

Special Issue Information

Dear Colleagues,

At present, the competition among enterprises has risen, leading to competition among supply chains. Meanwhile, rising carbon emissions have caused global warming, rising sea levels, and frequent extreme climate events, all threatening human survival. Many carbon emissions come from production and logistics, such as the generation of waste materials and the emission of automobile exhausts. As a result, many countries advocate for the development of sustainable supply chains and sustainable logistics. However, both sustainable supply chain and logistics management are affected by many factors, and so they need to be analyzed from different perspectives. Multiple criteria decision making (MCDM) appears as one of the most important fields of operational research in the last 15 years, with newly developed methods and uncertainty approaches. MCDM is a discipline aimed at supporting decision makers who are faced with numerous and conflicting alternatives to make an optimal decision. To achieve this purpose, two critical factors should be established: the preference structure and weights. In this regard, theories such as linear programming, data envelopment analysis (DEA), the analytic hierarchy process (AHP), the analytic network process (ANP), the best-worst method (BWM), decision-making trial and evaluation laboratory (DEMATEL), entropy weight, the technique for order preference by similarity to an ideal solution (TOPSIS), the ELECTRE method, the PROMETHEE method, the fuzzy integral technique, fuzzy set theory, rough set, grey theory and uncertainty theory can provide real-time solutions to uncertainty problems.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

Sustainable supply chain and logistics system construction in the post pandemic era;
Sustainable packaging;
Sustainable transportation and distribution;
Garbage recycling and disposal;
Supply chain operations for a circular economy；
Sustainability and lean production;
Sustainable supply chain design, optimization and data-driven modelling;
Sustainable food supply chain innovation.

I look forward to receiving your contributions.

Dr. Peng Jiang
Prof. Dr. Yi-Chung Hu
Dr. Jingci Xie
Dr. Hang Jiang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (7 papers)

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Research

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19 pages, 931 KiB

Open AccessArticle

Determinants of Low-Carbon Logistics Capability Based on Dynamic fsQCA: Evidence from China’s Provincial Panel Data

by Hang Jiang, Taipeng Sun, Beini Zhuang and Jiangqiu Wu

Sustainability 2023, 15(14), 11372; https://doi.org/10.3390/su151411372 - 21 Jul 2023

Cited by 2 | Viewed by 1261

Abstract

The fast-paced growth of the logistics industry has contributed significantly to China’s high-quality economic development. However, the growth of the logistics industry is frequently accompanied by high levels of pollution, carbon emissions, and energy consumption. How to increase low-carbon logistics capacity has emerged as a research hotspot under the dual carbon goals. This study used entropy weight TOPSIS to evaluate the low-carbon logistics capacity and dynamic fuzzy-set qualitative comparative analysis (fsQCA) to shed light on the antecedent conditions that influenced low-carbon logistics capability by using panel data from 30 Chinese provinces between 2008 and 2021. Based on the empirical results, several conclusions are drawn: (1) The comprehensive score show that while province low-carbon logistics capacity varies, most of them exhibit a general growing tendency in most provinces, where Beijing, Shanghai, Tianjin, Guangdong and Zhejiang rank among the top five. (2) Three configurations, digital empower capital intensive type, digital empower labor intensive type, and green ecology plus technology innovation type that lead to better low-carbon logistics capacity. Related policy recommendations are proposed, including strengthening the synergistic development of the digital economy and the logistics industry, promoting research and development of green and innovative technologies, and reinforcing the constraints of the dual-carbon target. Full article

(This article belongs to the Special Issue Multiple Criteria Decision-Making Techniques in Sustainable Supply Chains and Logistics Management)

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20 pages, 2269 KiB

Open AccessArticle

Identifying Critical Indicators in Performance Evaluation of Green Supply Chains Using Hybrid Multiple-Criteria Decision-Making

by Changlu Zhang, Liqian Tang and Jian Zhang

Sustainability 2023, 15(7), 6095; https://doi.org/10.3390/su15076095 - 31 Mar 2023

Cited by 3 | Viewed by 1630

Abstract

Performance evaluation of green supply chains (GSC) is an important tool to improve their comprehensive management. Identifying critical indicators is crucial to evaluation. This study examines the critical indicators in performance evaluations of GPC and provides relevant suggestions for managers to improve GSCs’ performances. Firstly, we summarized 24 evaluation indicators from five dimensions—financial value, customer service-level, business processes, innovation and development, and the so-called green level. Secondly, the Delphi method was used to determine the formal research framework. The fuzzy decision-making trial and evaluation laboratory based analytic network process (fuzzy DEMATEL-based ANP) model was applied. The weighted prominence of each indicator was calculated to identify those that were critical, and a causality diagram was constructed for them. Finally, corresponding countermeasures and implications regarding those were put forward. The research results show that the critical indicators include the return rate of net assets, the growth rate of profit, the rate of service satisfaction, market share, production flexibility, and the green consensus. Among them, the green consensus, the growth rate of profit and the rate of service satisfaction form a virtuous circle, leading to the improvement of the overall performance of GSC. Full article

(This article belongs to the Special Issue Multiple Criteria Decision-Making Techniques in Sustainable Supply Chains and Logistics Management)

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16 pages, 1203 KiB

Open AccessArticle

The Influence of Green Supply Chain Management Practices on Corporate Sustainability Performance

by Mohammed Taj Hejazi, Bader Al Batati and Ahmed Bahurmuz

Sustainability 2023, 15(6), 5459; https://doi.org/10.3390/su15065459 - 20 Mar 2023

Cited by 5 | Viewed by 8065

Abstract

Sustainability is a major concern for several industries in Saudi Arabia, especially those in the industrial sector. By using green methods, many businesses intend to become sustainable. Green practices provide staff with instructions regarding how to maintain business sustainability while performing necessary production tasks. Accordingly, the purpose of this study was to investigate how green practices affect the sustainability performance of businesses. Partial least squares (PLS) analysis was used to examine data from 250 sets of completed onnaires. Our findings showed that green practices significantly impact corporate sustainability performance. Full article

(This article belongs to the Special Issue Multiple Criteria Decision-Making Techniques in Sustainable Supply Chains and Logistics Management)

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23 pages, 4147 KiB

Open AccessArticle

Identifying Waste Supply Chain Coordination Barriers with Fuzzy MCDM

by Chen Liang, Dongshi Sun and Danlan Xie

Sustainability 2023, 15(6), 5352; https://doi.org/10.3390/su15065352 - 17 Mar 2023

Cited by 1 | Viewed by 1106

Abstract

The stability and efficiency of the waste supply chain (WSC) is related to the urban environment. This study constructed a framework of barriers to coordinating the WSC based on four perspectives: the costs and benefits, mechanisms involved, behaviors of the subjects, and technologies and standards used. We used an analytic network process based on the fuzzy decision-making trial and evaluation laboratory to calculate the centrality and weight of each barrier factor, and we determined the critical barriers to coordination by combining their results. A causality diagram of the barriers was drawn, and a scheme of coordination of the WSC was designed based on a closed-loop supply chain around the critical barriers. The results show that contradictions in benefits between subjects, contradictions between economic and social benefits, excessive subsidies, the failure of the market mechanism, the lack of a mechanism for supervision, and blocked information and distrust among the subjects are the five most critical barriers to the coordination of the WSC, with excessive subsidies the root cause of the lack of coordination. The subsidy for direct waste disposal should be used to reduce the cost of the operation of the WSC, waste recycling should be improved, an information-sharing platform should be built, and the cost of recyclable waste for manufacturers should be reduced to improve the efficiency of the WSC. Full article

(This article belongs to the Special Issue Multiple Criteria Decision-Making Techniques in Sustainable Supply Chains and Logistics Management)

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27 pages, 987 KiB

Open AccessArticle

Using Multicriteria Decision Making to Evaluate the Risk of Hydrogen Energy Storage and Transportation in Cities

by Dongshi Sun, Di Guo and Danlan Xie

Sustainability 2023, 15(2), 1088; https://doi.org/10.3390/su15021088 - 06 Jan 2023

Cited by 3 | Viewed by 1267

Abstract

Hydrogen is an environmentally friendly source of renewable energy. Energy generation from hydrogen has not yet been widely commercialized due to issues related to risk management in its storage and transportation. In this paper, the authors propose a hybrid multiple-criteria decision-making (MCDM)-based method to manage the risks involved in the storage and transportation of hydrogen (RSTH). First, we identified the key points of the RSTH by examining the relevant literature and soliciting the opinions of experts and used this to build a prototype of its decision structure. Second, we developed a hybrid MCDM approach, called the D-ANP, that combined the decision-making trial and evaluation laboratory (DEMENTEL) with the analytic network process (ANP) to obtain the weight of each point of risk. Third, we used fuzzy evaluation to assess the level of the RSTH for Beijing, China, where energy generation using hydrogen is rapidly advancing. The results showed that the skills of the personnel constituted the most important risk-related factor, and environmental volatility and the effectiveness of feedback were root factors. These three factors had an important impact on other factors influencing the risk of energy generation from hydrogen. Training and technical assistance can be used to mitigate the risks arising due to differences in the skills of personnel. An appropriate logistics network and segmented transportation for energy derived from hydrogen should be implemented to reduce environmental volatility, and integrated supply chain management can help make the relevant feedback more effective. Full article

(This article belongs to the Special Issue Multiple Criteria Decision-Making Techniques in Sustainable Supply Chains and Logistics Management)

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10 pages, 2240 KiB

Open AccessArticle

Location Selection for Regional Logistics Center Based on Particle Swarm Optimization

by Yingyi Huang, Xinyu Wang and Hongyan Chen

Sustainability 2022, 14(24), 16409; https://doi.org/10.3390/su142416409 - 08 Dec 2022

Cited by 2 | Viewed by 1756

Abstract

The location of a logistics center is very important in a logistics system, as the success of the location determines the whole logistics system’s structure, shape, and mode, and not only affects the logistics center’s own operating costs, performance, and future development, but also affects the operation of the entire logistics system. Therefore, the selection of the location for a logistics center has great significance for improving the efficiency of regional logistics and optimizing the structure of a logistics system. This study constructed a multi-factor constrained P-median site-selection model to optimize the locations of logistics centers to improve the efficiency of logistics and optimize the structure of the logistics system in a region. The results show that the optimal distribution of logistics center sites and the coverage of freight capacity demand derived from the particle swarm algorithm are more balanced than those derived by the other algorithm. Following the comparison of the results for the utility of the optimized layout points solved by the particle swarm algorithm and the immune genetic algorithm, it is concluded that the optimal fitness value obtained by the particle swarm algorithm is lower than the other. It is proven that the particle swarm algorithm of the P-median site-selection model under this multi-factor constraint has some reference value for the selection of the sites of multi-logistics centers. Full article

(This article belongs to the Special Issue Multiple Criteria Decision-Making Techniques in Sustainable Supply Chains and Logistics Management)

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Review

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21 pages, 997 KiB

Open AccessReview

A Review of Sustainable Supplier Selection with Decision-Making Methods from 2018 to 2022

by Ömer Karakoç, Samet Memiş and Bahar Sennaroglu

Sustainability 2024, 16(1), 125; https://doi.org/10.3390/su16010125 - 22 Dec 2023

Viewed by 2047

Abstract

Sustainable supplier selection (SSS) is an essential part of the decision-making process in sustainable supply chains. Numerous research studies have been conducted using various decision-making methods to attend to this research-worthy issue. This literature review presents a comprehensive SSS analysis focusing on social, economic, and environmental aspects. The present study spans five years (2018–2022) and considers 101 papers. It provides a detailed breakdown of the papers based on their dates of publication, the countries of the writers, application fields, and journals, and it categorizes them based on their approaches. In addition, this review examines the use of single- or hybrid-form methodologies in the papers reviewed. It also identifies that the TOPSIS, AHP, VIKOR, BWM, DEA, DEMATEL, and MULTIMOORA methods and their extensions are the most frequently used methods in SSS studies. It is concluded that hybrid approaches and their rough, grey, and fuzzy extensions are used to solve real-world problems. However, state-of-the-art mathematical tools, such as soft sets and their hybrid versions with fuzzy sets, have not been utilized in SSS studies. Therefore, this study inspires and encourages the use of such tools in SSS research. Full article

(This article belongs to the Special Issue Multiple Criteria Decision-Making Techniques in Sustainable Supply Chains and Logistics Management)

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