Developing a hybrid evaluation approach for the low carbon performance on sustainable manufacturing environment

被引:57
作者
Ali, Sadia Samar [1 ]
Kaur, Rajbir [2 ]
Persis, D. Jinil [3 ]
Saha, Raiswa [4 ]
Pattusamy, Murugan [5 ]
Sreedharan, V. Raja [6 ]
机构
[1] King Abdulaziz Univ, GC, Coll Engn, Dept Ind Engn, Jeddah 21589, Saudi Arabia
[2] Govt Girls Coll, Panchkula 134001, Haryana, India
[3] Natl Inst Ind Engn, Ind Engn & Mfg Syst, Mumbai, Maharashtra, India
[4] SRM Univ, Sonepat, Haryana, India
[5] Univ Hyderabad, Sch Management Studies, Hyderabad, India
[6] Univ Int Rabat, Rabat Business Sch, Bear Lab, Rabat, Morocco
关键词
Regulatory framework; Low carbon performance; Machine learning; Item response theory; Sustainable society; Sustainable manufacturing; SUPPLY CHAIN MANAGEMENT; DECISION-MAKING; ORDER ALLOCATION; SELECTION; POLICIES; MODELS; SYSTEM;
D O I
10.1007/s10479-020-03877-1
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
Societal emergence and sustainability are results of human actions and practices which can either imbalance it with maximum exploitation or retain it through responsible utilization of resources. Based on theories on institutional and resource-based views, the study explores the enablers of green sustainable practices of procurement, logistics, product and process design and regulatory frameworks for low carbon performance .The study employs a Hybrid approach of step-by-step empirical process to examine the impact of sustainable practices on low carbon performance which further affects the sustainable manufacturing and societies. A theoretical model developed based on hypothesis is tested first using modified Dillman's approach. Then it is tested in in the PLS-SEM package using 380 data responses collected from the various manufacturers. Further robustness of proposed model is validated using different ML (machine learning) followed by post hoc analysis using Item Response Theory to validate the scale and efficacy of the measurement model. The study validates the positive relationships of sustainable practices on the low carbon performance which eventually is responsible for sustainable societies. The area of sustainable manufacturing is found relatively lacking and requires further attention of leadership for better societal establishments. The study hopes to further enrich the literature with its unique Hybrid approach of SEM/PLS Machine Learning and IRT which is used to presents carbon performance as a central entity deriving from green practices and driving sustainable manufacturing and societies.
引用
收藏
页码:249 / 281
页数:33
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