Improving urban energy efficiency: What role does the digital economy play?

Wang, Jie; Lin, Kexin; Sun, Jiasen

doi:10.1016/j.jclepro.2023.138104

Cited by 34 publications

(19 citation statements)

References 54 publications

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“…Accountability in addressing environmental effects can be enhanced through impact assessment processes and the integration of blockchain technology. Impact assessments provide a systematic approach to evaluate and manage potential environmental impacts, enabling informed decision-making and promoting sustainability (Kwilinski, 2023;Leong et al, 2023;Soori et al, 2023;Wu et al, 2023). Blockchain technology, with its transparency, security, and traceability, strengthens accountability by securely storing impact assessment data and fostering collaboration among stakeholders.…”

Section: Accountability Through Impact Assessmentmentioning

confidence: 99%

“…While inclusive innovation corridors bring together diverse stakeholders to collaborate on innovation-driven initiatives, their development can often lead to negative environmental impacts, including pollution, habitat destruction, and resource depletion. Therefore, it is imperative to integrate sustainable practices and conduct comprehensive environmental impact assessments during the planning and implementation stages (Leong et al, 2023;Soori et al, 2023;Wu et al, 2023). By incorporating sustainable design principles, such as renewable energy sources, energy-efficient infrastructure, and green spaces, these corridors can minimize their ecological footprint and contribute to biodiversity conservation and resource conservation.…”

Section: Inclusive Innovation Corridorsmentioning

confidence: 99%

“…Inclusive innovation corridors should also prioritize community engagement, particularly with marginalized groups, to ensure equitable distribution of benefits and address potential social and environmental injustices. By adopting a holistic and sustainable approach, inclusive innovation corridors can harness economic growth, technological progress, and social inclusivity while mitigating their environmental impacts, ultimately paving the way for a more sustainable and equitable future (Zkik et al, 2023a;Leong et al, 2023;Richey et al, 2023;Saeed et al, 2023;Soori et al, 2023;Wu et al, 2023).…”

Section: Inclusive Innovation Corridorsmentioning

confidence: 99%

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Exploring the structure of the digital economy through blockchain technology and mitigating adverse environmental effects with the aid of artificial neural networks

Cai,

Hong

2024

Front. Environ. Sci.

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The rapid expansion of the digital economy has had a transformative impact on society, presenting both opportunities and challenges. This article aims to examine the structure of the digital economy and its implications, with a specific focus on the adverse environmental effects associated with its rapid growth. To address these challenges, the utilization of artificial neural networks is proposed as a viable solution. ANNs have proven to be effective in analyzing large volumes of data and extracting valuable insights. By integrating blockchain technology and harnessing the power of ANNs, this study seeks to develop management strategies that optimize resource allocation, reduce waste, and promote sustainability within the digital economy. Through comprehensive data analysis, patterns and trends can be identified, providing decision-makers with valuable information to make informed choices that minimize the environmental impact of digitalization. This research significantly contributes to the existing body of knowledge by enhancing our understanding of the digital economy’s structure, particularly in the context of blockchain technology. The ANN in this study estimated the impact of digital economy growth and structure improvement on adverse environmental effects, waste reduction, and environmental sustainability. The predictions showed that increasing digital economy growth led to increased waste reduction and promotion of environmental sustainability, while adverse environmental effects exhibited sinusoidal behavior. Linear regression confirmed the acceptable error of the network’s predictions compared to experimental results. Furthermore, it sheds light on the potential of ANNs to mitigate the adverse environmental effects associated with the digital economy. By emphasizing the importance of sustainable practices and exploring the applications of emerging technologies, this study offers valuable insights for policymakers, researchers, and industry practitioners seeking to navigate the complex landscape of the digital economy while minimizing its environmental consequences.

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Section: Accountability Through Impact Assessmentmentioning

confidence: 99%

Section: Inclusive Innovation Corridorsmentioning

confidence: 99%

Section: Inclusive Innovation Corridorsmentioning

confidence: 99%

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Exploring the structure of the digital economy through blockchain technology and mitigating adverse environmental effects with the aid of artificial neural networks

Cai,

Hong

2024

Front. Environ. Sci.

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“…On one hand, improving EEE can reduce pollution emissions 38 , enhance sustainable resource utilization 39 , stimulate of technological innovation, effectively address environmental issues 40 and promoting sustainable development 41 . On the other hand, EEE is influenced by various factors such as technological innovation 42 , policy regulations 43 , absorptive capacity of foreign direct investment 44 , economic development level 45 , industrial structure 45 , and energy structure 46 . EEE is a complex indicator that requires in-depth research and comprehensive consideration.…”

Section: Literature Reviewmentioning

confidence: 99%

Assessment of green technology innovation on energy-environmental efficiency in China under the influence of environmental regulation considering spatial effects

Li,

Xu,

Huang

et al. 2023

Sci Rep

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Enhancing energy-environmental efficiency (EEE) is crucial for achieving energy conservation and emission reduction goals. Investigating the mechanism through which green technology innovation (GTI) affects EEE and understanding the role of environmental regulation (ER) in this process provides a theoretical basis for efficient utilization of GTI and ER. This study employs a Dynamic Spatial Durbin Model and utilizes panel data from 2003 to 2017 for 30 Chinese provinces to examine the impact of GTI on EEE in the presence of ER. The empirical results reveal: (1) GTI has a U-shaped impact on EEE, primarily driven by SubGI. (2) GTI’s influence on EEE is predominantly reflected in PTE, also stemming from SubGI. (3) The interaction term between ER and GTI is 0.0022, while the GTI coefficient is − 0.0741, and the GTI quadratic term coefficient is 0.0007, all statistically significant. This implies that ER mitigates the negative impact of GTI on EEE while strengthening its positive effect. These findings provide empirical evidence and policy insights for more effectively utilizing GTI and ER to enhance EEE and achieve energy conservation and emissions reduction goals.

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“…The adoption of cleaner energy vehicles can be important for achieving energy efficiency, according to the work of Xiong and Cheng [6]. Another central issue that is under analysis and discussion is the effect of the digital economy on energy efficiency [7,8]. Decarbonization, which is linked to energy consumption and energy efficiency, is vital and is a target for most countries [9,10].…”

Section: Introductionmentioning

confidence: 99%

Energy and Circular Economy: Nexus beyond Concepts

Martins,

Castro,

Smitková

et al. 2024

Sustainability

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Energy and materials are increasingly important in industrialized countries, and they impact the economy, sustainability, and people’s future. The purpose of this work was to study the relationship between energy and the circular economy using methods such as Pearson’s correlation and a principal component analysis. Thus, 12 strong correlations were found, with 5 of them between the following relevant variables from two different subjects: the correlations of the raw material consumption, the domestic material consumption, and the material import dependency with the final energy consumption in transport (0.81, 0.92, and 0.81); the correlation of the circular material use rate with the final energy consumption in households (0.70); and the correlation of the material import dependency with the final energy consumption in industry (0.89). The time series forecast was only conclusive for the waste generated, showing that it will increase in the next 10 years.

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Improving urban energy efficiency: What role does the digital economy play?

Cited by 34 publications

References 54 publications

Exploring the structure of the digital economy through blockchain technology and mitigating adverse environmental effects with the aid of artificial neural networks

Exploring the structure of the digital economy through blockchain technology and mitigating adverse environmental effects with the aid of artificial neural networks

Assessment of green technology innovation on energy-environmental efficiency in China under the influence of environmental regulation considering spatial effects

Energy and Circular Economy: Nexus beyond Concepts

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