The Morbidity of Multivariable Grey Model MGM<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M1"><mml:mo stretchy="false">(</mml:mo><mml:mn fontstyle="italic">1</mml:mn><mml:mo>,</mml:mo><mml:mi>m</mml:mi><mml:mo stretchy="false">)</mml:mo></mml:math>

Wang, Haixia; Zhao, Longsheng; Hu, Mingzhao

doi:10.1155/2017/2495686

Cited by 9 publications

(2 citation statements)

References 9 publications

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“…In this case, the government has adopted a means to control and improve the environment by command and supervision [17]. This approach seeks to motivate companies that consume considerable resources and generate considerable pollution to modify their operations and to motivate them to embrace sophisticated science and technology to enhance effectiveness [18]. In this way, we can promote sustainable economic development and help our society to move towards a more harmonious future.…”

Section: The Indirect Influence Of Green Innovation On Total Factor P...mentioning

confidence: 99%

Impact of Environmental Regulatory Types and Green Technological Innovation on Green Total Factor Productivity in Polluted Areas of China

Sun,

Zhao

2024

Sustainability

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Compared to regions with lighter pollution, the areas heavily affected by pollution in China face more severe environmental problems due to rapid economic growth, which creates a greater urgency for government and corporate environmental requirements. This study innovatively applies mediation and threshold models to explore the potential correlation between green technology innovation, types of environmental regulation, and provincial-level green total factor productivity (GTFP). Additionally, it examines inter-regional differences, determines threshold effects, and introduces regional heterogeneity and mediator variables. The research findings demonstrate that progress in green technology innovation significantly impacts the improvement of provincial-level GTFP. Further mechanism analysis reveals the crucial role of environmental regulation in facilitating sustained enhancement of GTFP through green technology innovation. The promotion of GTFP is more pronounced in eastern and central provinces compared to western regions, and the positive influence of green technology innovation varies significantly among provinces. By investigating the regional differences of polluted areas and introducing mediating variables, this paper explores the environmental regulation mechanism, which has important guiding significance for formulating more effective environmental regulation policies, promoting green technology innovation, and improving GTFP.

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Section: The Indirect Influence Of Green Innovation On Total Factor P...mentioning

confidence: 99%

Impact of Environmental Regulatory Types and Green Technological Innovation on Green Total Factor Productivity in Polluted Areas of China

Sun,

Zhao

2024

Sustainability

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“…One possibility is to modify the combined methods, where we analyze for latent clusters and relationships with stability and reproducibility [39]. Alternatively, we may employ grey models for short-term predictive modeling of firms' technological innovation capabilities with limited samples [40]. Furthermore, Future research could be in a more specific direction, studying the business model of the innovation of NEV firms and the business model of the innovation of traditional fuel vehicle firms and how the two types of firms may cooperate.…”

Section: Contributions Limitation Future Researchmentioning

confidence: 99%

The Impact of Firm Heterogeneity and External Factor Change on Innovation: Evidence from the Vehicle Industry Sector

Feng

Zhao

et al. 2022

Sustainability

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We explore the connection between firms’ technological innovation capabilities and their internal and external factors. To empirically test this relationship, we use panel data for new energy vehicle (NEV) firms and traditional fuel vehicle firms in China from 2010 to 2020. Our findings show that public subsidies do have a positive impact on firms’ technology innovation capability, and there are consistent findings for both NEV and traditional fuel vehicle firms. Firms have a supportive effect on their innovative ability when they satisfy conditions of high profitability, low leverage, high equity concentration, and highly educated employees. The inability to maximize the effectiveness of public subsidies is due to an imbalance in the internal and external factors of firms. Therefore, we innovatively analyze the internal and external factors of NEV firms as an integrated system, taking into account the high correlation between them, rather than discussing them separately. The paper is not only of academic significance to the development of NEV firms to improve their technological innovation capability and the transformation of traditional fuel vehicle firms, but also of practical significance to the reduction of greenhouse gas emissions and the achievement of the “double carbon” goal.

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Multivariate understanding of income and expenditure in United States households with statistical learning

2022

Comput Stat

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In recent decades, data-driven approaches have been developed to analyze demographic and economic surveys on a large scale. Despite advances in multivariate techniques and learning methods, in practice the analysis and interpretations are often focused on a small portion of available data and limited to a single perspective. This paper aims to utilize a selected array of multivariate statistical learning methods in the analysis of income and expenditure patterns of households in the United States using the Public-Use Microdata from the Bureau of Labor Statistics Consumer Expenditure Survey (CE). The objective is to propose an effective data pipeline that provides visualizations and comprehensive interpretations for applications in governmental regulations and economic research, using thirty-five original survey variables covering the categories of demographics, income and expenditure. Details on feature extraction not only showcase CE as a unique publicly-shared big data resource with high potential for in-depth analysis, but also assist interested researchers with pre-processing. Challenges from missing values and categorical variables are treated in the exploratory analysis, while statistical learning methods are comprehensively employed to address multiple economic perspectives. Principal component analysis suggests that after-tax income, wage/salary income, and the quarterly expenditure in food, housing and overall as the five most important of the selected variables, while cluster analysis identifies and visualizes the implicit structure between variables. Based on this, canonical correlation analysis reveals high correlation between two selected groups of variables, one of income and the other of expenditure.

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The Morbidity of Multivariable Grey Model MGM(1,m)

Cited by 9 publications

References 9 publications

Impact of Environmental Regulatory Types and Green Technological Innovation on Green Total Factor Productivity in Polluted Areas of China

Impact of Environmental Regulatory Types and Green Technological Innovation on Green Total Factor Productivity in Polluted Areas of China

The Impact of Firm Heterogeneity and External Factor Change on Innovation: Evidence from the Vehicle Industry Sector

Multivariate understanding of income and expenditure in United States households with statistical learning

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