The impact of digital government on corporate green innovation: Evidence from China

Technological Forecasting and Social Change, Год журнала: 2024, Номер 206, С. 123570 - 123570

Опубликована: Июль 8, 2024

Язык: Английский

---

Digital Transformation and Enterprise Risk-Taking

Finance research letters, Год журнала: 2024, Номер 62, С. 105139 - 105139

Опубликована: Фев. 21, 2024

Язык: Английский

---

Does urban innovation policy accelerate the digital transformation of enterprises? Evidence based on the innovative City pilot policy

China Economic Review, Год журнала: 2024, Номер 85, С. 102167 - 102167

Опубликована: Апрель 6, 2024

Язык: Английский

---

Unlocking Carbon Reduction Potential of Digital Trade: Evidence from China’s Comprehensive Cross-border E-Commerce Pilot Zones

SAGE Open, Год журнала: 2025, Номер 15(1)

Опубликована: Янв. 1, 2025

As an important driving force for economic growth, digital trade provides opportunities urban green development. Using city-level data in China from 2005 to 2020, we take the cross-border e-commerce comprehensive pilot zone (CBEC) as a policy shock construct spatial difference-in-difference (SDID) model, which is adapted quantitatively examine carbon reduction effects and impact mechanisms of CBEC policy. The results confirm that implementation significantly reduces emissions (CE) cities about 4.5%, mainly due resource allocation efficiency promotion, industrial structure upgrading, technology boosting. Meanwhile, there significant spillover effect, resulting 3.9% CE decrease neighboring cities. In addition, has more effect resource-based high-degree information Our provide evidence accelerate development

Язык: Английский

---

Artificial intelligence and green product innovation: Moderating effect of organizational capital

Heliyon, Год журнала: 2024, Номер 10(7), С. e28572 - e28572

Опубликована: Март 22, 2024

Green product innovation (GPDI) is crucial for addressing ecological issues and essential enterprises' green operations long-term growth. Digitization offers new possibilities enhancing corporate practices. Nevertheless, previous studies have predominantly addressed the association between overall digitalization innovation, research on outcome of specific digital technology categories lacking. Within this framework, study broadens investigation into connection distinct technologies innovation. The period 2013–2022 was selected as sample observation period, with companies listed China's A-share market objects. fixed-effects model applied to investigate impact artificial intelligence (AI) firms' GPDI while exploring interaction effect organizational capital. findings indicate that AI beneficial in businesses. This enhanced by employee board human capital but diminished social These results remained valid after two-stage least squares regression. utilization resource-based view dynamic capacity theory business implementation. Furthermore, it extends resulting provides a enhancement pathway GPDI. has significant theoretical practical implications.

Язык: Английский

---

Talking and walking: Corporate digital transformation and government subsidies

Finance research letters, Год журнала: 2024, Номер 64, С. 105444 - 105444

Опубликована: Апрель 23, 2024

Язык: Английский

---

The Digital Empowerment Promotes Synergistic Efficiency in Regional Pollution Reduction and Carbon Emission Reduction—Analysis of the Moderating Effects of Market Structure and Government Behavior

Journal of Cleaner Production, Год журнала: 2025, Номер unknown, С. 144867 - 144867

Опубликована: Янв. 1, 2025

Язык: Английский

---

Business group affiliation and corporate digital transformation

Economic Modelling, Год журнала: 2025, Номер unknown, С. 107068 - 107068

Опубликована: Март 1, 2025

Язык: Английский

---

The impact of digital transformation on corporate supply chain management: Evidence from listed companies

Finance research letters, Год журнала: 2023, Номер 60, С. 104890 - 104890

Опубликована: Дек. 20, 2023

Язык: Английский

---

Driving forces of digital transformation in chinese enterprises based on machine learning

Scientific Reports, Год журнала: 2024, Номер 14(1)

Опубликована: Март 14, 2024

Abstract With advanced science and digital technology, transformation has become an important way to promote the sustainable development of enterprises. However, existing research only focuses on linear relationship between a single characteristic transformation. In this study, we select data Chinese A-share listed companies from 2010 2020, innovatively use machine learning method explore differences in predictive effects multi-dimensional features enterprises based Technology-Organization-Environment (TOE) theory, thus identifying main drivers affecting fitting models with stronger effect. The study found that: first, by comparing traditional regression models, it is that prediction ability ensemble earning generally higher than tradition measurement method. For sample selected research, XGBoost LightGBM have strong explanatory high accuracy. Second, compared technical driving force environmental force, organizational greater impact. Third, among these characteristics, equity concentration executives’ knowledge level dimension greatest impact Therefore, enterprise managers should always pay attention decision-making role level. This further enriches literature enterprises, expands application economics, provides theoretical basis for enhance

Язык: Английский

---