Analysis of China’s Manufacturing Industry Carbon Lock-In and Its Influencing Factors

Wang, Xia; Zhang, Lijun; Qin, Yaochen; Zhang, Jingfei

doi:10.3390/su12041502

Cited by 28 publications

(10 citation statements)

References 27 publications

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“…The transformation and upgrading of industrial structure and high-quality industrial development in China's coastal space will be an important tool to promote quality change, efficiency change, and power change in regional economic development. The difficulty in the spatial governance of China's coastal industry lies in the fact that the regional level requires both "planning the overall situation" and "planning a region," and the industrial level requires both "taking care of the whole" and "grasping the focus" [2]. The difficulty lies in the fact that at the regional level, it is necessary to "plan the whole picture" as well as "plan a region," and at the industrial level, it is necessary to "take care of the whole" as well as "focus."…”

Section: Introductionmentioning

confidence: 99%

Economic Development Analysis of China’s Coastal Industries Based on Deep Learning and SDA Model Weighting

2022

Wireless Communications and Mobile Computing

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China’s coast is the main spatial carrier and important geographical unit for future industrial development in China. We propose a weighted average decomposition method based on three basic problems in the theory of SDA model decomposition method, investigate the relevant properties of this method, and prove that two decomposition methods widely used in the literature—bipolar decomposition method and midpoint power decomposition method—are the approximate solutions of this decomposition method. Based on the idea of the Wasserstein distance algorithm for machine learning, the Wasserstein distance algorithm and its solution are improved by using the matrix expansion Sinkhorn algorithm and the entropy regularization constraint method, and the industry copolymerization index is constructed through hypothesis testing and Monte Carlo simulation to measure the level of industry copolymerization in coastal China. The results show that the level of industry copolymerisation within the same quantile industry is greater than that between industries across quantile industries in China’s coasts.

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Section: Introductionmentioning

confidence: 99%

Economic Development Analysis of China’s Coastal Industries Based on Deep Learning and SDA Model Weighting

2022

Wireless Communications and Mobile Computing

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“…Energy production is caught on a path dependency on fossil fuels. Organizations caught in such non-virtuous feedback forsake alternative sources for energy production, continuing the way indicated by initial conditions, hooked to the expectation [31] of increased returns to scale [32], while crystallizing habitus in social corporative behavior.…”

Section: The Actants Organizations As Social Systemsmentioning

confidence: 99%

Harnessing Ethical AI Surveillance for Climate Change Governmentality

Herrera-Vega¹

2022

tjes

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Achieving sustainability in respect to the natural environment necessitates a changing paradigm in climate’s governmentality, as to discipline complex modalities of techno-social agency that underlie the current climate crisis. From a transdisciplinary approach, the analysis recalls the science of climate change with the existing frame of international law (hard and soft law), analyzing the conditions for the accountability of organizations (Nations and corporations) in the production of anthropogenic emissions. Organizations are deciphered as complex techno-social systems of communication responding to reflexivity, feature that precludes them from understanding natural environment limitations. Reflexivity triggers carbon lock-in, a special form of path dependency at the base of the current schism between knowledge, intention, and actions. Reflexivity threatens long-term sustainability while endangering life and social systems. Artificial Intelligence can help overcome reflexivity, only if AI is restrained by an ethical approach constructed by the protection of human rights, the notion of environmental stewardship and the sustainability goals. Idealized ethical AI needs to take the form of hard law regulation.

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“…Resource endowment effect: Factors that influence product layout. The geophysical location, climatic conditions and availability of certain fossil resources influence coal, oil, metal, and mining development levels, which critically affect the product layout of the carbon-intensive industry [126]. [127].…”

Section: Case Analysis: Learning From Mexico's Energy Transitionmentioning

confidence: 99%

Carbon Lock-In and Contradictions—Applied Guide to Academic Teaching of Mexico’s Energy Transition

Pacheco-Rojas

Villaverde

2021

Applied Sciences

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The energy sector plays an important role in Mexico’s development trajectory. Mexico makes an interesting case study because it shows how difficult it is to reduce fossil energy dependence despite geographic and climatic conditions that favour renewable energy deployment and use. Resolving path dependencies and the related carbon lock-in are key to Mexico’s sustainable energy transition. This applied teaching guide contemplates the use of a case-illustration typology to identify and discuss how the politics about carbon lock-in affects Mexico’s sustainable energy transition. This methodology is an innovative endeavour that aims to apply the case study in classrooms with the intention to encourage discussions and solution-oriented approaches when tangible actions are identified by the educator and students. This methodology elevates the case study to a “living” case study that leads to recommended actions. The applied teaching guide allows educators, who are mostly researchers, to reflect on how Mexico’s case study could be explained not only to promote the students’ understanding of the challenges, but also to provide educators/researchers the skills on how to effectively disseminate knowledge. Mexico’s carbon lock-in involves oil and oil-run power plants that are costly to build but relatively inexpensive to operate. To conclude, this case study identifies potential entry points for transitioning towards sustainable energy in Mexico—resources that can promote the use of clean energy despite carbon lock-in. For example, focusing on electrification—particularly the carbon-intensive sectors—can help Mexico transit towards sustainable energy despite institutional constraints. Complementing this case study is a teaching guide with recommendations for using Mexico’s energy transition in courses on sustainability. By understanding how to explain the case study, the educator/researcher can better structure the complexity of the case study. This approach introduces a “learning activation framework” to identify emerging opportunities that can advance sustainable energy transitions in different cases of carbon lock-in. The framework also gives students a chance to help dismantle or cope with carbon lock-ins. Mexico’s energy transition makes a valuable teaching example because its energy transition is part of a broader developmental goal. This teaching guide’s systematic approach can maximise the students’ learning experience.

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Analysis of China’s Manufacturing Industry Carbon Lock-In and Its Influencing Factors

Cited by 28 publications

References 27 publications

Economic Development Analysis of China’s Coastal Industries Based on Deep Learning and SDA Model Weighting

Economic Development Analysis of China’s Coastal Industries Based on Deep Learning and SDA Model Weighting

Harnessing Ethical AI Surveillance for Climate Change Governmentality

Carbon Lock-In and Contradictions—Applied Guide to Academic Teaching of Mexico’s Energy Transition

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