Journal
JOURNAL OF CLEANER PRODUCTION
Volume 310, Issue -, Pages -Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2021.127377
Keywords
Green supply chain; Clean technology innovation; Supply chain management direction; Multinational enterprises
Ask authors/readers for more resources
The study indicates that GSCM benefits CTI, especially with a stronger effect seen in backward GSCM. Light-polluting and capital-intensive industries are more incentivized to adopt GSCM, while domestic companies outperform foreign companies in this regard.
This study identifies the impact of green supply chain management (GSCM) on clean technology innovation (CTI) by enterprises in China as well as compares the effects of forward and backward GSCM and the differences by industry and home country. The effect of CTI on GSCM is tested by 501 samples of mostly multinational enterprises in China from 2014 to 2016. The results indicate that CTI benefits from GSCM, which remains robust to a series of sensitivity test. And different management directions show great differences, where the backward GSCM has a stronger promotion effect on CTI than the forward GSCM. Moreover, light polluting industries and capital-intensive industries have stronger incentives to adopt GSCM than heavy-polluting industries and labourintensive industries. And domestic companies perform better than foreign companies.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
Article
Green & Sustainable Science & Technology
Relative evaluation of probabilistic methods for spatio-temporal wind forecasting
Lars odegaard Bentsen, Narada Dilp Warakagoda, Roy Stenbro, Paal Engelstad
Summary: This study investigates uncertainty modeling in wind power forecasting using different parametric and non-parametric methods. Johnson's SU distribution is found to outperform Gaussian distributions in predicting wind power. This research contributes to the literature by introducing Johnson's SU distribution as a candidate for probabilistic wind forecasting.
JOURNAL OF CLEANER PRODUCTION (2024)
Article
Green & Sustainable Science & Technology
Comparison of ethane recovery processes for lean gas based on a coupled model
Xing Liu, Qiuchen Wang, Yunhao Wen, Long Li, Xinfang Zhang, Yi Wang
Summary: This study analyzes the characteristics of process parameters in three lean gas ethane recovery processes and establishes a prediction and multiobjective optimization model for ethane recovery and system energy consumption. A new method for comparing ethane recovery processes for lean gas is proposed, and the addition of extra coolers improves the ethane recovery. The support vector regression model based on grey wolf optimization demonstrates the highest prediction accuracy, and the multiobjective multiverse optimization algorithm shows the best optimization performance and diversity in the solutions.
JOURNAL OF CLEANER PRODUCTION (2024)
Article
Green & Sustainable Science & Technology
A novel deep-learning framework for short-term prediction of cooling load in public buildings
Cairong Song, Haidong Yang, Xian-Bing Meng, Pan Yang, Jianyang Cai, Hao Bao, Kangkang Xu
Summary: The paper proposes a novel deep learning-based prediction framework, aTCN-LSTM, for accurate cooling load predictions. The framework utilizes a gate-controlled multi-head temporal convolutional network and a sparse probabilistic self-attention mechanism with a bidirectional long short-term memory network to capture both temporal and long-term dependencies in the cooling load sequences. Experimental results demonstrate the effectiveness and superiority of the proposed method, which can serve as an effective guide for HVAC chiller scheduling and demand management initiatives.
JOURNAL OF CLEANER PRODUCTION (2024)
Article
Green & Sustainable Science & Technology
The impact of social interaction and information acquisition on the adoption of soil and water conservation technology by farmers: Evidence from the Loess Plateau, China
Zhe Chen, Xiaojing Li, Xianli Xia, Jizhou Zhang
Summary: This study uses survey data from the Loess Plateau in China to evaluate the impact of social interaction on the adoption of soil and water conservation (SWC) technology by farmers. The study finds that social interaction increases the likelihood of farmers adopting SWC, and internet use moderates this effect. The positive impact of social interaction on SWC adoption is more pronounced for farmers in larger villages and those who join cooperative societies.
JOURNAL OF CLEANER PRODUCTION (2024)
Article
Green & Sustainable Science & Technology
Study on synergistic heat transfer enhancement and adaptive control behavior of baffle under sudden change of inlet velocity in a micro combustor
Chenghua Zhang, Yunfei Yan, Kaiming Shen, Zongguo Xue, Jingxiang You, Yonghong Wu, Ziqiang He
Summary: This paper reports a novel method that significantly improves combustion performance, including heat transfer enhancement under steady-state conditions and adaptive stable flame regulation under velocity sudden increase.
JOURNAL OF CLEANER PRODUCTION (2024)
Share Paper
