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When ecology thrives, civilization thrives, and when ecology declines, civilization declines. Based on panel data from 30 provinces in China from 2000 to 2021, this study used marginal abatement costs to estimate the co-benefits of pollution reduction and carbon reduction. Two-way fixed effect and two-stage intermediary effect models were used to e...
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Innovation is an eternal theme of human development, and green innovation efficiency serves as the basis for achieving innovation-driven development in a country or region, as well as an important aspect of ecological civilization construction. In this context, based on the panel data of 30 Chinese provinces during 2003–2020, this study explores th...
Citations
... AI technology also improves production efficiency and reduces the introduction of raw materials through efficient allocation and reuse of resources. From the perspective of technological innovation, DT is not only conducive to the rapid screening, sorting and analysis of existing stock knowledge, but also can give optimization suggestions, and improve the efficiency of R&D personnel to obtain external knowledge (Shen and Zhang, 2024b;. The digital experimental platform provides BI with the conditions for simulation and data analysis, reducing the risk of innovation failure. ...
Introduction
Digital transformation (DT) refers to the process of leveraging digital technologies to drive innovation in business models, thereby enabling enterprises to create greater value and deliver innovative solutions for efficient agricultural production.
Methods
Using data from 211 listed agricultural companies in China from 2009 to 2022, this study investigates the impact and pathways through which DT influences financial performance (FP), employing a range of methodologies. To enhance text mining accuracy, the research incorporates natural language processing (NLP) and large language models (LLM).
Results
The findings indicate that DT within agricultural enterprises’ production, purchasing, and sales departments significantly enhances FP. To address potential endogeneity concerns, robustness checks were conducted using propensity score matching (PSM), the Heckman two-stage model, and the two-stage least squares (2SLS) method. Mechanism analysis reveals that DT improves FP through three primary channels: reducing sales expenses, easing cost stickiness, and promoting breakthrough innovation. However, the positive effects of DT exhibit heterogeneity. These effects are more pronounced in non-state-owned enterprises, larger firms, and enterprises located in major grain-producing regions.
Conclusion
This study validates the necessity for enterprises to use digital technology to improve financial performance in the digital age. By expanding the measurement methods for DT, the research provides valuable insights for enterprises seeking to leverage digital tools to optimize agricultural production efficiency.
... First, we provide a more comprehensive and detailed pathway for reducing the CEI of manufacturing enterprises. Previous studies have mostly focused on individual factors, such as the impact of digital transformation [2,9,15,31,66,67], green technological innovation [30,32,33,36,68,69], and environmental regulations [37,39,70] on corporate carbon emissions. However, carbon emissions in enterprises represent a complex system that is subject to multiple constraints, such as technological capabilities, organizational resources, and external environments [18]. ...
... Through intermediary channels, such as digital collaboration platforms, these technologies can support the promotion of innovations in green technologies, reduce energy intensity, and improve the energy structure. Furthermore, the development of digital solutions can contribute to better energy demand forecasting and increase the efficiency of entire energy systems, which is crucial for achieving carbon neutrality goals [21]. ...
The energy transition requires substantial financial investments and the adoption of innovative technological solutions. The aim of this paper is to analyze the economic and technological aspects of implementing zero-emission strategies as a key component of the transition toward a carbon-neutral economy. The study assesses the costs, benefits, and challenges of these strategies, with a particular focus on wind farms and nuclear power, including small modular reactors (SMRs). The paper presents an in-depth examination of key examples, including onshore and offshore wind farms, as well as nuclear energy from both large-scale and small modular reactors. It highlights their construction and operating costs, associated benefits, and challenges. The investment required to generate 1 MW of energy varies significantly depending on the technology: onshore wind farms range from 2,100,000, offshore wind farms from 5,500,000, traditional nuclear power plants from 5,000,000, while small modular reactors (SMRs) require between 10,000,000 per MW. The discussion underscores the critical role of wind farms in diversifying renewable energy sources while addressing the high capital requirements and technical complexities of nuclear power, including both traditional large-scale reactors and emerging SMRs. By evaluating these energy solutions, the article contributes to a broader understanding of the economic and technological challenges essential for advancing a sustainable energy future.
... Environmental pollution, a severe human-induced environmental issue, has a negative externality that affects the overall welfare of society. Research shows that a variety of factors can mitigate environmental problems, such as digital technology and green innovation [2][3][4]. Green innovation, which can be defined as creating new products or technologies to reduce environmental risks [5], contributes to alleviating environmental pollution problems [6]. However, enterprises lack incentives for green innovation because its positive externality prevents them from fully benefiting from R&D results [7]. ...
Based on an analysis of 643 listed firms in clean technology sectors, this study explores the nonlinear impact of the government’s environmental attention (GEA) on firms’ green innovation by exploiting threshold and quantile regression techniques on Stata 17. We show that a double threshold exists when the level of the GEA is 51 or 104, above which the positive impact of the GEA on green innovation in cleantech firms significantly diminishes. The results from the quantile regression further indicate that cleantech firms receive almost no benefits from the GEA at lower levels of green innovation. Thus, policy-makers designing environmental policies should consider that the marginal benefit of environmental attention on green innovation wanes beyond certain levels, especially for firms that lack sufficient enthusiasm for innovation.
... In order to verify the channel mechanism of digital transformation to green transformation of agricultural-related enterprises, combined with the empirical route of published literature [60][61][62], this study used a three-stage intermediary effect model for verification. ...
The advent of new digital technologies has catalyzed a disruptive technological revolution, fostering significant industrial changes and advancing the green transformation of the economy and society. This paper investigates the influence of digitization on the green transformation of agribusiness firms, focusing on agriculture-related companies listed on the Shanghai and Shenzhen A-share markets from 2013 to 2021. Employing fixed-effect and mediated-effect models, the study examines the mechanisms through which digitization impacts these enterprises. The findings indicate that the relationship between digitization and green transformation in agribusiness is non-linear; a certain threshold of digitization must be achieved before it positively affects green transformation. The effect of digitization on green transformation varies according to the nature of business ownership, company size, supply chain flexibility, and regional environmental regulations. The study reveals that digitization influences green transformation through several mechanisms that promote economies of scale, technological innovation, and structural adjustments. While economies of scale derived from digitization do not directly support green transformation, they facilitate technological innovation and structural adjustments that enhance green initiatives in agribusiness.
Policy synergy, the evidence-based coordination of public policies, can aid in more rapidly achieving air pollutant and carbon dioxide (CO2) emission reduction targets. Using logarithmic mean Divisia index (LMDI) decomposition, coupling coordination degree (CCD), and geographically and temporally weighted regression (GTWR) models, we analyzed the emission characteristics, drivers, and reduction pathways of residential air pollution across 30 Chinese provinces from 2001 to 2020. The southern provinces produced more air pollution than the northern provinces, with the gap widening after 2015. In the residential sector, energy emission factors (LMDI decomposition result, 686,681.9) and population size (14,331) had greater impacts on air pollutant emissions than the energy structure, energy intensity, synergies, or GDP per capita. The GTWR analysis of the CCD mechanism indicated that hydroelectricity and urbanization enhanced coupling coordination in the southeast. Meanwhile, in the west, coupling coordination was improved by R&D investment, government spending on industrial pollution control, electricity consumption, per capita cropland, temperature, and urbanization. This analysis provides a valuable reference for optimizing emission reduction strategies.
