From open-loop energy revolutions to closed-loop transition: What drives carbon neutrality?

Millot, Ariane; Mäızi, Nadia

doi:10.1016/j.techfore.2021.121003

Cited by 40 publications

(11 citation statements)

References 40 publications

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“…A transition away from fossil fuel energy sources and toward renewable energy sources is critical to attaining future carbon neutrality. Millot and Maïzi examined previous energy transitions and discovered that they occurred spontaneously as a result of technology advancements, economic, social, and political benefits such as lower prices and increased living comfort (Millot and Maïzi 2021 ). On the other hand, the shift to carbon neutrality cannot occur spontaneously because carbon neutrality is primarily motivated by environmental concerns and offers no immediate financial benefits to individuals or corporations.…”

Section: Achieving Carbon Neutralitymentioning

confidence: 99%

Strategies to achieve a carbon neutral society: a review

et al. 2022

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The increasing global industrialization and over-exploitation of fossil fuels has induced the release of greenhouse gases, leading to an increase in global temperature and causing environmental issues. There is therefore an urgent necessity to reach net-zero carbon emissions. Only 4.5% of countries have achieved carbon neutrality, and most countries are still planning to do so by 2050–2070. Moreover, synergies between different countries have hampered synergies between adaptation and mitigation policies, as well as their co-benefits. Here, we present a strategy to reach a carbon neutral economy by examining the outcome goals of the 26th summit of the United Nations Climate Change Conference of the Parties (COP 26). Methods have been designed for mapping carbon emissions, such as input–output models, spatial systems, geographic information system maps, light detection and ranging techniques, and logarithmic mean divisia. We present decarbonization technologies and initiatives, and negative emissions technologies, and we discuss carbon trading and carbon tax. We propose plans for carbon neutrality such as shifting away from fossil fuels toward renewable energy, and the development of low-carbon technologies, low-carbon agriculture, changing dietary habits and increasing the value of food and agricultural waste. Developing resilient buildings and cities, introducing decentralized energy systems, and the electrification of the transportation sector is also necessary. We also review the life cycle analysis of carbon neutral systems.

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Section: Achieving Carbon Neutralitymentioning

confidence: 99%

Strategies to achieve a carbon neutral society: a review

et al. 2022

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“…Carbon emissions may be precisely measured and tracked throughout an organization's activities via AIdriven technologies. AI is also useful in helping to choose and execute carbon offsetting plans, such funding renewable energy projects or encouraging reforestation efforts (Bag, 2023;Millot & Maïzi, 2021;A. Zhang, Tay, et al, 2023).…”

Section: Ai-driven Business Model Innovation and Carbon Neutral Businessmentioning

confidence: 99%

Artificial intelligence (AI)‐driven strategic business model innovations in small‐ and medium‐sized enterprises. Insights on technological and strategic enablers for carbon neutral businesses

Shaik,

Alshibani,

Jain

et al. 2023

Bus Strat Env

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This study investigates the enhancement of technological and strategic enablers for carbon‐neutral businesses (CNB) through artificial intelligence (AI)‐driven business model innovation (AIDBMI). Drawing upon the insights gained from the literature review, the study employs structural equation modeling (partial least squares structural equation modeling [PLS‐SEM]) as the methodology to examine the relationships between AIDBMI, technological enablers, strategic enablers, and the attainment of carbon neutrality. The sample size consists of 326 small‐ and medium‐sized enterprises (SMEs) in the United States of America. The findings of this study affirm the significant positive relationships between AIDBMI and both technological and strategic enablers for CNB. The utilization of AI technologies proves to be instrumental in fostering the development and implementation of innovative business models that integrate sustainability practices and address environmental challenges. By leveraging AIDBMI, SMEs can harness technological advancements to adopt energy‐efficient processes, embrace renewable energy solutions, and implement effective carbon reduction strategies. Moreover, the study highlights the critical role of strategic enablers in driving the transition towards carbon neutrality. The alignment of sustainability goals with organizational strategies, stakeholder collaboration, and employee engagement emerge as pivotal factors in enabling SMEs to effectively utilize AIDBMI and leverage technological advancements to achieve carbon neutrality. The implications of this study contribute to the existing literature by highlighting the importance of technological and strategic enablers in creating CNB. By integrating AIDBMI, organizations can drive sustainable transformations, optimize their operations, and align their resource management with sustainable practices. These insights provide valuable guidance for SMEs, policymakers, and researchers seeking to foster sustainable practices, promote carbon neutrality, and contribute to the advancement of a low‐carbon economy.

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“…The global harm caused by the greenhouse effect has become the focus of attention of all countries in the 21st century. Therefore, the concept of carbon neutrality has been promoted in more and more countries (Millot and Maizi, 2021;Huovila et al, 2022). Similarly, to reverse the trend of environmental degradation, China has proposed reaching carbon dioxide peak levels by 2030 and carbon neutrality by 2060.…”

Section: Introductionmentioning

confidence: 99%

Can artificial intelligence achieve carbon neutrality? Evidence from a quasi-natural experiment

et al. 2023

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IntroductionAs the global climate crisis worsens, carbon neutrality has attracted the attention of various nations.MethodsBased on panel data from 282 Chinese prefecture-level cities from 2008 to 2019, this research considers the execution of the artificial intelligence strategy as a quasi-natural experiment. It uses the difference-in-differences (DID) model to evaluate the effect of artificial intelligence construction on carbon emission reduction.ResultsThe findings indicate that implementing the artificial intelligence strategy into practice can lower carbon emissions and advance carbon neutrality, and this conclusion still passes after various robustness tests. The mediating effects reveal that developing green technologies and upgrading the industrial structure are crucial mechanisms for achieving carbon neutrality. The implementation effect varies with time, geographical location, natural resource endowment, and city level.DiscussionThis article examines the influence of artificial intelligence on urban carbon neutrality at the city level, adding to the notion of urban carbon neutrality and providing research support for urban development transformation.

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From open-loop energy revolutions to closed-loop transition: What drives carbon neutrality?

Cited by 40 publications

References 40 publications

Strategies to achieve a carbon neutral society: a review

Strategies to achieve a carbon neutral society: a review

Artificial intelligence (AI)‐driven strategic business model innovations in small‐ and medium‐sized enterprises. Insights on technological and strategic enablers for carbon neutral businesses

Can artificial intelligence achieve carbon neutrality? Evidence from a quasi-natural experiment

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