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Mao Q, Chen J, Lv J, Guo M, Tian M. A hybrid DEMATEL-COPRAS method using interval-valued probabilistic linguistic term set for sustainable hydrogen fuel cell supplier of new energy vehicles. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023:10.1007/s11356-023-27470-8. [PMID: 37204570 DOI: 10.1007/s11356-023-27470-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Accepted: 05/02/2023] [Indexed: 05/20/2023]
Abstract
With the continuous development of the global economy, global environmental pollution, climate degradation and global warming are becoming increasingly serious. In order to deal with the increasingly serious environmental problems, the government is vigorously supporting and promoting the development of new energy vehicles (NEVs). As the core unit of NEVs, one of the main challenges faced by hydrogen fuel cell (HFC) supplier is to select the best supplier for their business among all possible suppliers. Selecting the optimal supplier is a key decision in green supplier management. Therefore, it is extremely important and meaningful to select an optimal HFC supplier to provide power for NEVs. This paper proposes a new decision-making framework based on Decision-Making Trial and Evaluation Laboratory (DEMATEL) method and Complex proportional assessment (COPRAS) method under interval-valued probabilistic linguistic environment to select the appropriate HFC supplier of NEVs. Firstly, this paper establishes the evaluation criteria system of HFC supplier assessment which is the synthesis of economical, environmental, social, technical, organisation and service aspects. Then, in order to express the uncertainty of expert decision-making, this paper uses interval-valued probabilistic linguistic term set (IVPLTS) to describe the evaluation information. Next, the interval-valued probabilistic linguistic term set decision-making trial and evaluation laboratory (IVPLTS-DEMATEL) method is applied to calculate the criteria weights. Moreover, this paper constructs the interval-valued probabilistic linguistic term set Complex Proportional Assessment (IVPLTS-COPRAS) model for the selection of HFC supplier of NEVs. Finally, a case in China with sensitivity analysis and comparison analysis are executed to illustrate the feasibility and validity of the proposed approach. This paper provides valuable references for investors and companies to select the most appropriate HFC supplier of NEVs under uncertain environment.
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Affiliation(s)
- Qinghua Mao
- School of Economics and Management, Yanshan University, Qinhuangdao, 066004, China
| | - Jinjin Chen
- School of Economics and Management, Yanshan University, Qinhuangdao, 066004, China.
| | - Jian Lv
- School of Economics and Management, Yanshan University, Qinhuangdao, 066004, China
| | - Mengxin Guo
- School of Economics and Management, Yanshan University, Qinhuangdao, 066004, China
| | - Mingjun Tian
- School of Economics and Management, Yanshan University, Qinhuangdao, 066004, China
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Tubis AA, Rohman J. Intelligent Warehouse in Industry 4.0-Systematic Literature Review. SENSORS (BASEL, SWITZERLAND) 2023; 23:4105. [PMID: 37112446 PMCID: PMC10146052 DOI: 10.3390/s23084105] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 04/16/2023] [Accepted: 04/18/2023] [Indexed: 06/19/2023]
Abstract
The development of Industry 4.0 (I4.0) and the digitization and automation of manufacturing processes have created a demand for designing smart warehouses to support manufacturing processes. Warehousing is one of the fundamental processes in the supply chain, and is responsible for handling inventory. Efficient execution of warehouse operations often determines the effectiveness of realized goods flows. Therefore, digitization and its use in exchanging information between partners, especially real-time inventory levels, is critical. For this reason, the digital solutions of Industry 4.0 have quickly found application in internal logistics processes and enabled the design of smart warehouses, also known as Warehouse 4.0. The purpose of this article is to present the results of the conducted review of publications on the design and operation of warehouses using the concepts of Industry 4.0. A total of 249 documents from the last 5 years were accepted for analysis. Publications were searched for in the Web of Science database using the PRISMA method. The article presents in detail the research methodology and the results of the biometric analysis. Based on the results, a two-level classification framework was proposed, which includes 10 primary categories and 24 subcategories. Each of the distinguished categories was characterized based on the analyzed publications. It should be noted that in most of these studies, the authors' attention primarily focused on the implementation of (1) Industry 4.0 technological solutions, such as IoT, augmented reality, RFID, visual technology, and other emerging technologies; and (2) autonomous and automated vehicles in warehouse operations processes. Critical analysis of the literature also allowed us to identify the current research gaps, which will be the subject of further research by the authors.
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Tian G, Lu W, Zhang X, Zhan M, Dulebenets MA, Aleksandrov A, Fathollahi-Fard AM, Ivanov M. A survey of multi-criteria decision-making techniques for green logistics and low-carbon transportation systems. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:57279-57301. [PMID: 37016261 DOI: 10.1007/s11356-023-26577-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/26/2022] [Accepted: 03/16/2023] [Indexed: 05/10/2023]
Abstract
With the increasing severity of environmental problems, low-carbon development has become an inevitable choice. Nowadays, low-carbon green sustainable development is influenced by a variety of factors such as social, environmental, technological, and economic development levels, making its development complex, which in turn imposes challenges on decision-makers. In this context, the application of multi-criteria decision-making (MCDM) in different areas of sustainable development engineering has become a hot topic. Although many reviews of MCDM techniques already exist, there is a lack of holistic review efforts on MCDM in the field of low-carbon transport and green logistics. Considering these shortcomings in the state of the art, this paper systematically reviews more than 190 papers from 2010 to 2022, constructs a general structure of MCDM techniques for this research topic, provides a comprehensive review and analysis of it, and clarifies the current practices. Furthermore, future directions for the development of MCDM techniques for green logistics and low-carbon transportation systems are presented as well.
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Affiliation(s)
- Guangdong Tian
- School of Mechanical-Electronic and Vehicle Engineering, Beijing University of Civil Engineering and Architecture, Beijing, 100044, China
| | - Weidong Lu
- School of Mechanical-Electronic and Vehicle Engineering, Beijing University of Civil Engineering and Architecture, Beijing, 100044, China
| | - Xuesong Zhang
- School of Transportation, Northeast Forestry University, Harbin, 150000, China
| | - Meng Zhan
- Department of Social Development, Northeast Forestry University, Harbin, 150000, China.
| | - Maxim A Dulebenets
- Department of Civil & Environmental Engineering, FAMU-FSU College of Engineering, Tallahassee, FL, 32310, USA
| | - Anatoly Aleksandrov
- Department of Ecological and Industrial Safety, Bauman Moscow State Technical University, Moscow, 105005, Russian Federation
| | - Amir M Fathollahi-Fard
- Peter B. Gustavson School of Business, University of Victoria, 1700, Victoria, BC V8P5C2, Canada
| | - Mikhail Ivanov
- Department of Ecological and Industrial Safety, Bauman Moscow State Technical University, Moscow, 105005, Russian Federation
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Hosseini Dolatabad A, Heidary Dahooie J, Antucheviciene J, Azari M, Razavi Hajiagha SH. Supplier selection in the industry 4.0 era by using a fuzzy cognitive map and hesitant fuzzy linguistic VIKOR methodology. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:52923-52942. [PMID: 36843168 DOI: 10.1007/s11356-023-26004-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Accepted: 02/14/2023] [Indexed: 06/18/2023]
Abstract
Organizations will be increasingly concerned about maintaining their positions in today's changing world, the high-tech era, and the emergence of innovative technologies because of the industrial revolutions. Everyone has come to believe that to survive and continue their constructive roles, they must achieve competitive advantages by working based on the trends. It is undeniable that the introduction of Industry 4.0 has had a significant impact on enterprises, organizations, and, of course, supply chains. In the meantime, selecting a supplier is one of the main strategic decisions of the organization because choosing the right supplier leads to increasing profitability, improving market competition, better accountability, enhancing product quality, and reducing costs. While the issue of supplier evaluation has been one of the interesting topics for researchers in recent decades, its development in the fourth supply chain generation needs further consideration. In this regard, current technologies in the fourth-generation industrial revolution, methods, and criteria used in previous studies based on industry 4.0 and before that are reviewed separately. By reviewing previous articles and experts' opinions, thirteen sub-criteria considering industry 4.0 have been identified for selecting suppliers in three categories, economic, environmental, and social. The weight of each criterion has been determined using a set of fuzzy cognitive maps (FCMs) and considering the centrality of criteria in the concept of communication networks. To prioritize the suppliers, the hesitant fuzzy linguistic term sets (HFLTS) VIKOR method has been used in hesitant fuzzy linguistic terms. Finally, a case study is introduced to illustrate the effectiveness and usefulness of our integrated methodology and prioritize its four suppliers.
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Affiliation(s)
- Asana Hosseini Dolatabad
- Faculty of Management, University of Tehran, Jalal Al-E-Ahmad Ave., Nasr Bridge, Tehran, 14155-6311, Iran
| | - Jalil Heidary Dahooie
- Faculty of Management, University of Tehran, Jalal Al-E-Ahmad Ave., Nasr Bridge, Tehran, 14155-6311, Iran
| | - Jurgita Antucheviciene
- Department of Construction Management and Real Estate, Vilnius Gediminas Technical University, Sauletekio Al. 11, 10223, Vilnius, Lithuania.
| | - Mostafa Azari
- Faculty of Management, University of Tehran, Jalal Al-E-Ahmad Ave., Nasr Bridge, Tehran, 14155-6311, Iran
| | - Seyed Hossein Razavi Hajiagha
- Department of Management, Faculty of Management and Finance, Khatam University, Hakim Azam St., North Shiraz St., Mollasadra Ave., Tehran, 19395-3486, Iran
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Kaya SK. A novel two-phase group decision-making model for circular supplier selection under picture fuzzy environment. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:34135-34157. [PMID: 36508096 DOI: 10.1007/s11356-022-24486-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Accepted: 11/26/2022] [Indexed: 06/18/2023]
Abstract
Circular supply chain management (CSCM), which incorporates circular thinking into supply chain management, promotes supply chain sustainability by offering a novel and compelling viewpoint. In the CSCM, supplier selection is crucial in establishing a competitive edge among businesses by decreasing environmental degradation and related supply chain expenses. This paper aims to propose a novel two-phase group decision-making approach, which combines the picture fuzzy Analytical Hierarchical Process (PF-AHP) and grey Measurement of Alternatives and Ranking According to Compromise Solution (MARCOS-G) model to select railway material suppliers within the scope of circular economy perspective. In group decision-making, a picture fuzzy number-based approach aggregates individual decision makers'(DMs) opinions and provides a lower level of computing complexity and a higher level of performance. The PF-AHP has been used to produce the weights of the criteria, and the MARCOS-G technique has been used to rank the suppliers and choose the most appropriate one. The results and verification of the novel method are carried out throughout a comprehensive sensitivity analysis. For this purpose, 50 scenarios with changes in the weight values of criteria were developed. In the validation analysis, a comparison with other grey COPRAS, TOPSIS, ARAS and WASPAS methods were performed. Due to the ranking results obtained from Spearman's correlation analyses, the MARCOS-G is almost consistent and it can be seen that the A4 remains the top supplier in all 50 scenarios.
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Consideration of reciprocal judgments through Decomposed Fuzzy Analytical Hierarchy Process: A case study in the pharmaceutical industry. Appl Soft Comput 2023. [DOI: 10.1016/j.asoc.2023.110000] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
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A Two-Stage Multi-Criteria Supplier Selection Model for Sustainable Automotive Supply Chain under Uncertainty. AXIOMS 2022. [DOI: 10.3390/axioms11050228] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Sustainable supplier selection (SSS) is gaining popularity as a practical method to supply chain sustainability among academics and practitioners. However, in addition to balancing economic, social, and environmental factors, the emergence of the COVID-19 pandemic has affected the selection of long-term suppliers to ensure sustainable supply chains, recover better from the pandemic and effectively respond to any future unprecedented crises. The purpose of this study is to assess and choose a possible supplier based on their capability to adapt to the COVID-19 epidemic in a sustainable manner. For this assessment, a framework based on multi-criteria decision making (MCDM) is provided that integrates spherical fuzzy Analytical Hierarchical Process (SF-AHP) and grey Complex Proportional Assessment (G-COPRAS), in which spherical fuzzy sets and grey numbers are used to express the ambiguous linguistic evaluation statements of experts. In the first stage, the evaluation criteria system is identified through a literature review and experts’ opinions. The SF-AHP is then used to determine the criteria weights. Finally, the G-COPRAS method is utilized to select sustainable suppliers. A case study in the automotive industry in Vietnam is presented to demonstrate the proposed approach’s effectiveness. From the SF-AHP findings, “quality”, “use of personal protective equipment”, “cost/price”, “safety and health practices and wellbeing of suppliers”, and “economic recovery programs” have been ranked as the five most important criteria. From G-COPRAS analysis, THACO Parts (Supplier 02) is the best supplier. A sensitivity study was also conducted to verify the robustness of the proposed model, in which the priority rankings of the best suppliers are very similar. For long-term development and increased competitiveness, industrial businesses must stress the integration of response mechanisms during SSS implementation in the COVID-19 epidemic, according to the findings. This will result in significant cost and resource savings, as well as reduced environmental consequences and a long-term supply chain, independent of the crisis.
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Integrating Triple Bottom Line in Sustainable Chemical Supplier Selection: A Compromise Decision-Making-Based Spherical Fuzzy Approach. Processes (Basel) 2022. [DOI: 10.3390/pr10050889] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023] Open
Abstract
As a consequence of increased awareness of environmental preservation and the associated rigorous regulations, the adoption of sustainable practices has become a crucial element for corporate organizations in regard to their supply chains. In the chemical industry, which is characterized by high risks, high pollution, and high efficiency, these characteristics can help businesses analyze their long-term development and sustainability. The goal of this research is to analyze and choose possible suppliers based on their sustainability performance in the chemical sector. A methodology based on multi-criteria decision making (MCDM) is proposed for this evaluation, using spherical fuzzy analytical hierarchy process (SF-AHP) and combined compromise solution (CoCoSo) methods, in which the novel spherical fuzzy sets theory is employed to present the ambiguous linguistic preferences of experts. In the first stage, an evaluation criteria system is identified through literature review and experts’ opinions. The SF-AHP is used to determine the criteria weights, while the CoCoSo method is utilized to select the right sustainable supplier. A case study in the chemical industry in Vietnam is presented to demonstrate the effectiveness of the proposed approach. From the SF-AHP findings, “equipment system and technology capability”, “flexibility and reliability”, “logistics cost”, “green materials and technologies”, and “on-time delivery” were ranked as the five most important criteria. From the CoCoSo analysis, Vietnam National Chemical Group (CHE-05) was found to be the best supplier. A sensitivity study and a comparison analysis of methods were also conducted to verify the robustness of the proposed model, and the priority rankings of the best suppliers were very similar. To the best of our knowledge, this is the first study that has proposed SF-AHP and CoCoSo to prioritize SSS evaluation criteria and determine the best alternatives. The suggested method and findings can be used to make well-informed decisions that help businesses to achieve supply chain sustainability, capture opportunities, and maintain competitiveness through reconfiguring resources. The method could be useful for case studies in other countries and for other sustainability problems.
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Selection of Cold Chain Logistics Service Providers Based on a Grey AHP and Grey COPRAS Framework: A Case Study in Vietnam. AXIOMS 2022. [DOI: 10.3390/axioms11040154] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
Choosing the most suitable cold chain logistics service providers (CLPs) is a vital strategic decision for businesses aiming to achieve an effective and sustainable cold supply chain. A sustainable CLP is one that integrates sustainable practices across its whole operation cycle to achieve product quality, on-time deliveries, and satisfied customer requirements, while preventing products from going to waste, which is especially important in the context of a developing country. This study aims to evaluate and select the best CLP regarding their sustainability performance. For this evaluation, a multi-criteria decision making (MCDM)-based framework is proposed that integrates the grey analytic hierarchy process (G-AHP) and grey complex proportional assessment (G-COPRAS) methodologies, in which grey numbers are used to express the linguistic evaluation statements of experts. Initially, the evaluation criteria based on service level, economic, environmental, and social dimensions were determined by means of a literature review and experts’ opinions to employ the MCDM approach. The G-AHP was utilized to identify the criteria weights, and then, G-COPRAS was used to select the best CLP among the alternatives. A case illustration in Vietnam is presented to exhibit the presented approach’s applicability. From the G-AHP findings, product quality, logistics costs, innovation, and effectiveness of cold chain processes, customer experience, and CO emissions of refrigerated vehicle were ranked as the five most important criteria. From the G-COPRAS analysis, Yoshida Saigon Cold Logistic (CPL-05) is the best CLP. The robustness of the applied integrated MCDM approach was also tested by conducting a comparative analysis, in which the priority rankings of the best CLPs were very similar. The assessment in this study is directed towards enabling managers, practitioners, and stakeholders of cold chain businesses to assess the most efficient CLP in the supply chain in the market and also to devise suitable strategies toward sustainable development.
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Zhu Y, Wang X, Chen W, Guo H, Li D. A variable weight-based interval type-2 fuzzy rough comprehensive evaluation method for curtain grouting efficiency assessment. Neural Comput Appl 2022. [DOI: 10.1007/s00521-021-06864-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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