A Novel Hybrid Model for the Evaluation of Industry 4.0 Technologies' Applicability in Logistics Centers

被引:7
作者
Miskic, Smiljka [1 ]
Tadic, Snezana [2 ]
Stevic, Zeljko [1 ]
Krstic, Mladen [2 ]
Roso, Violeta [3 ]
机构
[1] Univ East Sarajevo, Fac Transport & Traff Engn, Vojvode Misica 52, Doboj 74000, Bosnia & Herceg
[2] Univ Belgrade, Fac Transport & Traff Engn, Logist Dept, Vojvode Stepe 305, Belgrade 11000, Serbia
[3] Chalmers Univ Technol, Dept Technol Management & Econ, S-41296 Gothenburg, Sweden
关键词
EMPIRICAL-EVIDENCE; NEXT-GENERATION; CHALLENGES; INTERNET; THINGS; TRANSPORT; SELECTION; SYSTEMS; AREAS;
D O I
10.1155/2023/3532862
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
The application of Industry 4.0 (I4.0) in the field of logistics leads to the emergence and development of the concept of logistics 4.0. Many I4.0 technologies have been applied in the field of logistics. The goal of this research is to analyze the applicability of nine key I4.0 technologies in logistics centers (LC). For this purpose, an integrated MEREC (MEthod based on the Removal Effects of Criteria)-fuzzy MARCOS (Measurement of Alternatives and Ranking according to COmpromise Solution) model was developed. The applicability of nine I4.0 technologies was evaluated based on 15 subcriteria within three main groups of criteria, namely, technological, social and political, and economic and operative. Using the MEREC method, the weight values of the criteria and subcriteria were determined, while the technologies were ranked using the fuzzy MARCOS method. Based on the results obtained by applying this integrated MCDM (multicriteria decision-making) model, CC was identified as the best alternative, i.e., the technology that is most applicable in logistics centers, followed by IoT and big data. An analysis of the sensitivity of the obtained results to the change in the importance of the criteria was carried out, which shows certain changes in the ranking when the importance of the most important criterion changes.
引用
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页数:19
相关论文
共 116 条
[11]   Enabling technologies, application areas and impact of industry 4.0: a bibliographic analysis [J].
Bigliardi, Barbara ;
Bottani, Eleonora ;
Casella, Giorgia .
INTERNATIONAL CONFERENCE ON INDUSTRY 4.0 AND SMART MANUFACTURING (ISM 2019), 2020, 42 :322-326
[12]  
Bounie N., 2016, WORLD C TRANSPORT RE, V25, P16
[13]  
Broy M., 2010, Cyber-Physical Systems, P17
[14]   An integrated SWOT based fuzzy AHP and fuzzy MARCOS methodology for digital transformation strategy analysis in airline industry [J].
Buyukozkan, Gulcin ;
Havle, Celal Alpay ;
Feyzioglu, Orhan .
JOURNAL OF AIR TRANSPORT MANAGEMENT, 2021, 97
[15]   The role of logistics performance in promoting trade [J].
Celebi, Dilay .
MARITIME ECONOMICS & LOGISTICS, 2019, 21 (03) :307-323
[16]   Digital technologies, healthcare and Covid-19: insights from developing and emerging nations [J].
Chandra, Mukesh ;
Kumar, Kunal ;
Thakur, Prabhat ;
Chattopadhyaya, Somnath ;
Alam, Firoz ;
Kumar, Satish .
HEALTH AND TECHNOLOGY, 2022, 12 (02) :547-568
[17]   Evaluating Industry 4.0 Technology Application in SMEs: Using a Hybrid MCDM Approach [J].
Chang, Shih-Chia ;
Chang, Hsu-Hwa ;
Lu, Ming-Tsang .
MATHEMATICS, 2021, 9 (04) :1-20
[18]   Barriers to industry 4.0 adoption and its performance implications: An empirical investigation of emerging economy [J].
Chauhan, Chetna ;
Singh, Amol ;
Luthra, Sunil .
JOURNAL OF CLEANER PRODUCTION, 2021, 285
[19]  
Chen L, 2022, Journal of Intelligent Management Decision, V1, P17, DOI [10.56578/jimd010103, 10.56578/jimd010103, DOI 10.56578/JIMD010103]
[20]   Impact of technological innovation on energy efficiency in industry 4.0 era: Moderation of shadow economy in sustainable development [J].
Chen, Maozhi ;
Sinha, Avik ;
Hu, Kexiang ;
Shah, Muhammad Ibrahim .
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE, 2021, 164