The Influence of the Evolution of the Innovative Network on Technical Innovation from the Perspective of Energy Transformation: Based on Analysis of the New Energy Vehicle Industry in China

Wang, Zeqian; Wang, Chengjun; Feng, Tao; Wang, Yalan

doi:10.3390/su15054237

Cited by 7 publications

(4 citation statements)

References 46 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…There is some uncertainty in the calculations in this study, which are primarily affected by limited data for estimating the cropping index and conversion factors for food and equivalent crops. In the former case, due to the inconsistency of the statistical calibre, the data on arable land area have series discontinuities, and this study revises the arable land area according to the revision methods used in existing studies [50][51][52][53]. While this revised data is closer to reality, it also introduces uncertainty.…”

Section: Discussionmentioning

confidence: 99%

Changes in Agricultural Land Requirements for Food Provision in China 1990-2020: A Comparison Between Urban and Rural Residents

Chen,

Yang,

Jiang

et al. 2024

Pol. J. Environ. Stud.

View full text Add to dashboard Cite

China's rapid income growth and urbanization have led to significant changes in food consumption patterns, and these dietary changes may increase the demand for agricultural land for food supply. This study explores the changes in urban and rural residents' cropland demand based on dietary data of Chinese residents from 1990 to 2020, using dietary nutritional analysis and a cropland footprint method. The results show that during the study period, the total cropland demand of rural residents decreased by 31.02%, from 61.31 million hm2 to 42.29 million hm 2 , while the total cropland demand of urban residents increased by 246.83%, from 22.91 million hm2 to 79.46 million hm 2 . The results reveal that the primary drivers of increased cropland demand are urbanization and rising animal-based dietary patterns. However, the contribution of increased agricultural productivity to decreased demand for cropland is relatively small and inadequate to compensate for the increased demand. In short, the pressure to protect arable land in China will continue to rise, and protecting existing arable land, improving cropland productivity, and making full use of international resources are the main ways to alleviate the pressure on arable land protection.

show abstract

Section: Discussionmentioning

confidence: 99%

Changes in Agricultural Land Requirements for Food Provision in China 1990-2020: A Comparison Between Urban and Rural Residents

Chen,

Yang,

Jiang

et al. 2024

Pol. J. Environ. Stud.

View full text Add to dashboard Cite

show abstract

“…When mobile inventors exhibit lower network closures, they are more likely to uncover new opportunities (Burt, 2017). These opportunities assist inventors in gaining a deeper understanding of the diverse activities and domains within the new employing company (Wang et al, 2023). Consequently, this enhances the mobile inventors' capacity to integrate resources, strengthens technological innovation within the new employing company, overcomes relational inertia after mobility and facilitates the better realization of their potential value.…”

Section: Current Network Closurementioning

confidence: 99%

“…In such cases, having a broader information perspective makes it easier for mobile inventors to integrate knowledge, identify and evaluate information, and seize valuable opportunities (Perry‐Smith & Mannucci, 2017). These inventors are more adaptable in changing their priorities, leading to a higher likelihood of generating more technological innovations within their new employing companies (Wang et al, 2023).…”

Section: Theoretically Foundation and Research Hypothesismentioning

confidence: 99%

How do inventors overcome the relational inertia after inter‐firm mobility?

Wang,

Sun

et al. 2024

Creat Innov Manage

Self Cite

View full text Add to dashboard Cite

This study aims to explore strategies for overcoming relational inertia and enhancing their creativity after inter‐firm mobility of inventors. The research sample comprises 591 mobile inventors identified using a patent data‐based model from Chinese communication technology companies. Employing the framework of dynamic network analysis, this study examines the impact of network closure at different time on overcoming relational inertia and investigates the influence of knowledge structure. The findings suggest that a lower level of past and current network closure is more conducive to knowledge sharing and technological innovation after inter‐firm mobility of inventors. Furthermore, mobile inventors with broad and in‐depth knowledge structures demonstrate significantly improved knowledge sharing and technological innovation, effectively mitigating relational inertia. These conclusions offer a systematic research perspective and comprehensive theoretical guidance, emphasizing the importance of optimizing network resources and knowledge structures to help inventors overcome relational inertia after inter‐firm mobility.

show abstract

“…In order to achieve sustainable economic development under the dual constraints of energy consumption and environmental pollution, the government strongly supports technological innovation and the transition from a fossil-fuel-led energy system to a more sustainable low-carbon energy system [7]. Therefore, more scholars are investing in research on energy transformation and energy innovation [8,9].…”

Section: Introductionmentioning

confidence: 99%

Influencing the Variable Selection and Prediction of Carbon Emissions in China

Chang,

Jiao,

Wang

2023

Sustainability

View full text Add to dashboard Cite

In order to study the changing rule of carbon dioxide emissions in China, this paper systematically focused on their current situation, influencing factors, and future trends. Firstly, the current situations of global carbon dioxide emissions and China’s carbon dioxide emissions were presented via a visualization method and their characteristics were analyzed; secondly, the random forest regression model was used to screen the main factors affecting China’s carbon emissions. Considering the different aspects of carbon emissions, 29 influencing factors were determined and 6 main influencing factors were determined according to the results of the random forest regression model. Then, a prediction model for carbon emissions in China was established. The BP neural network model, multi-factor LSTM time series model, and CNN-LSTM model were compared on the test set and all of them passed the test. However, the goodness of fit of the CNN-LSTM model was about 0.01~0.02 higher than the other two models and the MAE and RMSE of the CNN-LSTM model were about 0.01~0.03 lower than those of the other two models. Thus, it was selected to predict China’s carbon dioxide emissions. The predicted results showed that the peak of China’s carbon emissions will be around 2027 and the peak of these emissions will be between 12.9 billion tons and 13.2 billion tons. Overall, the paper puts forward reasonable suggestions for China’s low-carbon development and provides a reference for an adjustment plan of energy structure.

show abstract

The Influence of the Evolution of the Innovative Network on Technical Innovation from the Perspective of Energy Transformation: Based on Analysis of the New Energy Vehicle Industry in China

Cited by 7 publications

References 46 publications

Changes in Agricultural Land Requirements for Food Provision in China 1990-2020: A Comparison Between Urban and Rural Residents

Changes in Agricultural Land Requirements for Food Provision in China 1990-2020: A Comparison Between Urban and Rural Residents

How do inventors overcome the relational inertia after inter‐firm mobility?

Influencing the Variable Selection and Prediction of Carbon Emissions in China

Contact Info

Product

Resources

About