Optimizing Sustainable Manufacturing: An Integrated Approach of Green Information's Systems and Knowledge-Based Decisions in Industry 4.0: A Comparative Analysis
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作者:
Wu, Shengliang
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机构:
Henan Univ, Kaifeng, Peoples R ChinaHenan Univ, Kaifeng, Peoples R China
Wu, Shengliang
[1
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Gao, Yarui
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机构:
Henan Univ, Kaifeng, Peoples R ChinaHenan Univ, Kaifeng, Peoples R China
Gao, Yarui
[1
]
Alam, Sajjad
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机构:
Zhengzhou Univ, Zhengzhou, Peoples R ChinaHenan Univ, Kaifeng, Peoples R China
Green system;
green information technology;
knowledge management process;
manufacturing firms;
statistical analysis;
organization & work system design;
knowledge management;
CHAIN MANAGEMENT-PRACTICES;
COMPETITIVE ADVANTAGE;
PERFORMANCE;
INNOVATION;
CAPABILITY;
RISK;
D O I:
10.1080/10429247.2024.2422734
中图分类号:
T [工业技术];
学科分类号:
08 ;
摘要:
Adopting green information technology (IT) systems has become crucial for improving the environmental sustainability of manufacturing firms. To drive the manufacturing process more appropriately, management and administrators recognize the importance of developing green IT systems aligned with knowledge management (KM) practices. To accomplish the study objective, experts were engaged in a study conducted in Henan manufacturing firms to share their knowledge on the factors that influence management's intention to adopt green IT systems concerning KM. The study collected 324 valid responses from industrial experts in Henan manufacturing industries through survey questionnaires. Using structural equation modeling (SEM), the hypotheses were evaluated, and the significance of each factor in the model was determined. The SEM results revealed that the KM process interpretation significantly influences green IT systems to improve manufacturing process development. Furthermore, the study found that combining KM processes and green practices has a more substantial impact on improving the manufacturing process. This suggests that integrating knowledge management practices with green IT systems can lead to better environmental sustainability and overall performance in manufacturing firms. The findings of this study offer valuable insights for decision-makers and policymakers in formulating policies and programs to implement a green information system with green implementation processes effectively in the manufacturing sector. By adopting these strategies, manufacturing firms can contribute to environmental sustainability while simultaneously improving their overall performance.
机构:
Shenzhen Univ, Coll Management, Shenzhen, Peoples R ChinaShenzhen Univ, Coll Management, Shenzhen, Peoples R China
Qu, Yuanju
Wang, Yangpeng
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机构:
Shenzhen Univ, Coll Management, Shenzhen, Peoples R ChinaShenzhen Univ, Coll Management, Shenzhen, Peoples R China
Wang, Yangpeng
Ming, Xinguo
论文数: 0引用数: 0
h-index: 0
机构:
Shanghai Jiao Tong Univ, Sch Mech Engn, Shanghai, Peoples R ChinaShenzhen Univ, Coll Management, Shenzhen, Peoples R China
Ming, Xinguo
Chu, Xianghua
论文数: 0引用数: 0
h-index: 0
机构:
Shenzhen Univ, Coll Management, Shenzhen, Peoples R China
Shenzhen Univ, Inst Big Data Intelligent Management & Decis, Shenzhen, Peoples R ChinaShenzhen Univ, Coll Management, Shenzhen, Peoples R China
机构:
KTH Royal Inst Technol, Dept Prod Engn, Brinellvagen 68, S-11428 Stockholm, SwedenKTH Royal Inst Technol, Dept Prod Engn, Brinellvagen 68, S-11428 Stockholm, Sweden
Iunusova, Eleonora
Gonzalez, Monica Katherine
论文数: 0引用数: 0
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机构:
KTH Royal Inst Technol, Dept Prod Engn, Brinellvagen 68, S-11428 Stockholm, SwedenKTH Royal Inst Technol, Dept Prod Engn, Brinellvagen 68, S-11428 Stockholm, Sweden
Gonzalez, Monica Katherine
Szipka, Karoly
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机构:
KTH Royal Inst Technol, Dept Prod Engn, Brinellvagen 68, S-11428 Stockholm, SwedenKTH Royal Inst Technol, Dept Prod Engn, Brinellvagen 68, S-11428 Stockholm, Sweden
Szipka, Karoly
Archenti, Andreas
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机构:
KTH Royal Inst Technol, Dept Prod Engn, Brinellvagen 68, S-11428 Stockholm, SwedenKTH Royal Inst Technol, Dept Prod Engn, Brinellvagen 68, S-11428 Stockholm, Sweden
机构:
Univ Skovde, Sch Engn Sci, Div Intelligent Prod Syst, S-54128 Skovde, SwedenUniv Skovde, Sch Engn Sci, Div Intelligent Prod Syst, S-54128 Skovde, Sweden
Mahmoodi, Ehsan
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h-index:
机构:
Fathi, Masood
Ghobakhloo, Morteza
论文数: 0引用数: 0
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机构:
Uppsala Univ, Div Ind Engn & Management, POB 534, S-75121 Uppsala, SwedenUniv Skovde, Sch Engn Sci, Div Intelligent Prod Syst, S-54128 Skovde, Sweden
Ghobakhloo, Morteza
Ng, Amos H. C.
论文数: 0引用数: 0
h-index: 0
机构:
Univ Skovde, Sch Engn Sci, Div Intelligent Prod Syst, S-54128 Skovde, Sweden
Uppsala Univ, Div Ind Engn & Management, POB 534, S-75121 Uppsala, SwedenUniv Skovde, Sch Engn Sci, Div Intelligent Prod Syst, S-54128 Skovde, Sweden
Ng, Amos H. C.
5TH INTERNATIONAL CONFERENCE ON INDUSTRY 4.0 AND SMART MANUFACTURING, ISM 2023,
2024,
232
: 3121
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3130
机构:
Beijing Jiaotong Univ, State Key Lab Rail Traff Control & Safety, Beijing 100044, Peoples R ChinaBeijing Jiaotong Univ, State Key Lab Rail Traff Control & Safety, Beijing 100044, Peoples R China
Yin, Jiateng
Ren, Xianliang
论文数: 0引用数: 0
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机构:
Beijing Jiaotong Univ, State Key Lab Rail Traff Control & Safety, Beijing 100044, Peoples R ChinaBeijing Jiaotong Univ, State Key Lab Rail Traff Control & Safety, Beijing 100044, Peoples R China
Ren, Xianliang
Liu, Ronghui
论文数: 0引用数: 0
h-index: 0
机构:
Univ Leeds, Inst Transport Studies, Leeds, W Yorkshire, EnglandBeijing Jiaotong Univ, State Key Lab Rail Traff Control & Safety, Beijing 100044, Peoples R China
Liu, Ronghui
Tang, Tao
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h-index: 0
机构:
Beijing Jiaotong Univ, State Key Lab Rail Traff Control & Safety, Beijing 100044, Peoples R ChinaBeijing Jiaotong Univ, State Key Lab Rail Traff Control & Safety, Beijing 100044, Peoples R China
Tang, Tao
Su, Shuai
论文数: 0引用数: 0
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机构:
Beijing Jiaotong Univ, State Key Lab Rail Traff Control & Safety, Beijing 100044, Peoples R ChinaBeijing Jiaotong Univ, State Key Lab Rail Traff Control & Safety, Beijing 100044, Peoples R China