How does the development of the digital economy influence carbon productivity? The moderating effect of environmental regulation

Improving carbon productivity is of great significance to China's "30 · 60" carbon target, while the development of the digital economy is a driving force for green transformation. However, few studies discuss the relationship between the digital economy and carbon productivity. We investigate the influence of digital economic development on carbon productivity using panel data from 30 Chinese provinces from 2011 to 2020. Spatial econometric and moderating effects are considered. The results show that (i) digital economy has a positive direct and negative spatial spillover effect on carbon productivity, and this conclusion is still valid after the robustness test and endogeneity test; (ii) digital infrastructure has a greater impact on carbon productivity than digital industrialization and industrial digitalization; (iii) the mechanism analysis shows that environmental regulation negatively moderates the relationship between the digital economy and carbon productivity; (iv) heterogeneity analysis shows that the effect of the digital economy on carbon productivity is more obvious in the central region compared to the western region, while it is not significant in the eastern region. Overall, this paper not only provides a new analytical perspective for understanding the improvement of carbon productivity in the digital economy but also provides policy inspiration for promoting carbon peak and carbon neutrality goals.

Other's shoes also fit well: AI technologies contribute to China's blue skies as well as carbon reduction

Artificial intelligence (AI) technology represents a disruptive innovation that has garnered significant interest among researchers for its potential applications in ecological and environmental management. While many studies have investigated the impact of AI on carbon emissions, relatively few have delved into its relationship with air pollution. This study sets out to explore the causal mechanisms and constraints linking AI technologies and air pollution, using provincial panel data collected from 2007 to 2020 in China. Furthermore, this study examines the distinct pathways through which AI technology can ameliorate air pollution and reduce carbon emissions. The findings reveal the following key insights: (1) AI technologies have the capacity to significantly reduce air pollution, particularly in terms of PM2.5 and SO2 levels. (2) AI technologies contribute to enhanced air quality by facilitating adjustments in energy structures, improving energy efficiency, and strengthening digital infrastructure. Nonetheless, it is important to note that adjusting the energy structure remains the most practical approach for reducing carbon emissions. (3) The efficacy of AI in controlling air pollution is influenced by geographical location, economic development level, level of information technology development, resource dependence, and public attention. In conclusion, this study proposes novel policy recommendations to offer fresh perspectives to countries interested in leveraging AI for the advancement of ecological and environmental governance.

The impact of digital infrastructure on provincial green innovation efficiency-empirical evidence from China

In the epoch of the digital economy, technological innovation and energy conservation are significantly facilitated by digital infrastructure, leading to substantial improvements in green innovation efficiency at the provincial level. This study employed the feasible generalized least square (FGLS) method to examine the effects of digital infrastructure on the green innovation efficiency across 30 provinces in the Chinese mainland, utilizing panel data from 2011 to 2020. Additionally, this investigation delves into the intervening role of industrial structure upgrading and the amplifying effects of environmental regulation and human capital on the process. Findings indicate that, to begin with, digital infrastructure contributes to the meaningful enhancement of green innovation efficiency within provinces. Subsequently, the industrial structure upgrading partially mediates the impact of digital infrastructure on the efficiency of provincial green innovation. Lastly, both human capital and environmental regulations amplify the beneficial influence of digital infrastructure on the effectiveness of green innovation at the provincial level. This study provides valuable insights into the mechanisms through which digital infrastructure boosts green innovation efficiency, aiding policymakers in formulating appropriate policies to augment digital infrastructure, thereby promoting provincial green innovation efficiency.

Digital infrastructure construction, carbon total factor productivity, and carbon rebound effect

Digital infrastructure construction (DIC) and low-carbon transformation are important engines and objective functions of the superior economic development, and the synergistic drive between the two is essential to achieving lasting economic development. Based on the panel data of 279 cities in China between 2007 and 2019, the econometric model system is used to explore the impact mechanism of DIC on carbon total factor productivity (CTFP), and the impact of DIC on carbon rebound effect (CRE) is further studied. Research findings that, first, the expansion of DIC has a nonlinear effect on CTFP, with a U-shaped link between the two; multiple robustness tests confirm that this is still true. Second, DIC and optimization of the energy consumption structure in a "U" curve relationship, and the major strategy for increasing CTFP is to reduce energy consumption, while industrial structure optimization and technical innovation have less of a intermediary effect. Third, further analysis reveals that there is a "U" shaped nonlinear connection between the DIC and the CRE, and energy savings and emission reductions in the later stages of DIC fall short of expectations. The current DIC is still dominated by episodic expansion. The findings of the study can better enhance CTFP, curb the CRE, put a limit on total carbon emissions and accelerate the decoupling of economic growth from carbon emissions.

The adoption of non-pharmaceutical interventions and the role of digital infrastructure during the COVID-19 pandemic in Colombia, Ecuador, and El Salvador

Adherence to the non-pharmaceutical interventions (NPIs) put in place to mitigate the spreading of infectious diseases is a multifaceted problem. Several factors, including socio-demographic and socio-economic attributes, can influence the perceived susceptibility and risk which are known to affect behavior. Furthermore, the adoption of NPIs is dependent upon the barriers, real or perceived, associated with their implementation. Here, we study the determinants of NPIs adherence during the first wave of the COVID-19 Pandemic in Colombia, Ecuador, and El Salvador. Analyses are performed at the level of municipalities and include socio-economic, socio-demographic, and epidemiological indicators. Furthermore, by leveraging a unique dataset comprising tens of millions of internet Speedtest® measurements from Ookla®, we investigate the quality of the digital infrastructure as a possible barrier to adoption. We use mobility changes provided by Meta as a proxy of adherence to NPIs and find a significant correlation between mobility drops and digital infrastructure quality. The relationship remains significant after controlling for several factors. This finding suggests that municipalities with better internet connectivity were able to afford higher mobility reductions. We also find that mobility reductions were more pronounced in larger, denser, and wealthier municipalities.

Supplementary Information

The online version contains supplementary material available at 10.1140/epjds/s13688-023-00395-5.

The impact of broadband speed on innovation: City-level evidence from China

Previous studies have associated broadband with innovation, but most of them have focused on broadband access or broadband penetration rate rather than broadband speed. However, with the increase in the global broadband penetration rate, network speed is becoming a more important aspect of broadband development. Using a fixed effect model based on panel data from 274 cities in China from 2016 to 2018, we explore the impact of broadband speed on innovation and further validate the relationship by instrumental variable estimation and a series of robustness tests. The main findings are as follows: First, broadband speed significantly promotes patenting, and this effect is greater than the increase in broadband penetration rate. Second, the impact of broadband speed on promoting innovation is more substantial in cities with higher Internet penetration, GDP per capita, science and technology investment, and foreign direct investment. Third, broadband speed could promote innovation by facilitating patenting cooperation among firms. Fourth, we find no evidence of a diminishing marginal effect of broadband speed in this setting. This study has significant practical implications for emerging countries to encourage innovation by increasing broadband speed.

International tourism, digital infrastructure, and CO2 emissions: fresh evidence from panel quantile regression approach

The main motivation behind this study is the importance of tourism and ICT industry in the economic development of a country and their potential effects on the country's environmental quality in the digital era. For empirical analysis, the study applies FMOLS, DOLS, and quantile regression techniques for Asian economies. The findings of the study confirmed that tourism and digitalization improve environmental quality in FMOLS and DOLS models. In the basic quantile regression model, the estimates attached to tourism arrival are positive 5^th quantile to 40^th quantile and then turn negative from 60^th quantile and onwards. Likewise, the estimates attached to tourism receipts in the robust quantile regression model are positive from quantile 5^th to quantile 20^th and negative and increasing from quantile 30^th and onwards. Conversely, the estimates of digital infrastructure are insignificant in the basic quantile model at all quantiles except the 95^th. However, the estimated coefficients of digital infrastructure in the robust model are negative and rising from 40^th quantile to 70^th quantile and negative and declining from 80^th quantile to 95^th quantile. In general, we can say that as the tourism and digital sectors grow, the CO₂ emissions decline.

Online Black-Markets: An Investigation of a Digital Infrastructure in the Dark

This paper investigates the functioning of Online Black-Markets (OBMs), i.e. a digital infrastructure operating in the Dark Net that enables the exchange of illegal goods such as drugs, weapons and fake digital identities. OBMs exist notwithstanding adverse conditions such as police interventions, scams and market breakdowns. Relying on a longitudinal case study, we focus on the dynamics of interactions among actors and marketplace technologies and we identify three mechanisms explaining OBMs operations. In particular, we show that OBMs infrastructure is the result of commoditization, platformization and resilience processes. Our contribution relies on the identification of community-based mechanisms that generate the OBMs infrastructure, extending the current understanding of e-commerce and social commerce.

Integrated Digital Health System Tools to Support Decision Making and Treatment Preparation in CKD: The PREPARE NOW Study

Rationale & Objective

Digital health system tools to support shared decision making and preparation for kidney replacement treatments for patients with chronic kidney disease (CKD) are needed.

Study Design

Descriptive study of the implementation of digital infrastructure to support a patient-centered health system intervention.

Setting & Participants

4 CKD clinics within a large integrated health system.

Exposure

We developed an integrated suite of digital engagement tools to support patients’ shared decision making and preparation for kidney failure treatments. Tools included an automated CKD patient registry and risk prediction algorithm within the electronic health record (EHR) to identify and prioritize patients in need of nurse case management to facilitate shared decision making and preparation for kidney replacement treatments, an electronic patient-facing values clarification tool, a tracking application to document patients’ preparation for treatments, and an EHR work flow to broadcast patients’ treatment preferences to all health care providers.

Outcomes

Uptake and acceptability.

Analytic Approach

Mixed methods.

Results

From July 1, 2017, through June 30, 2018, the CKD registry identified 1,032 patients in 4 nephrology clinics, of whom 243 (24%) were identified as high risk for progressing to kidney failure within 2 years. Kidney Transitions Specialists enrolled 117 (48%) high-risk patients by the end of year 1. The values tool was completed by 30/33 (91%) patients who attended kidney modality education. Nurse case managers used the tracking application for 100% of patients to document 287 planning steps for kidney replacement therapy. Most (87%) high-risk patients had their preferred kidney replacement modality documented and displayed in the EHR. Nurse case managers reported that the tools facilitated their identification of patients needing support and their navigation activities.

Limitations

Single institution, short duration.

Conclusions

Digital health system tools facilitated rapid identification of patients needing shared and informed decision making and their preparation for kidney replacement treatments.

Funding

This work was supported through a Patient-Centered Outcomes Research Institute (PCORI) Project Program Award (IHS-1409-20967).

Trial registration

ClinicalTrials.gov NCT02722382.

The trade-off behaviours between virtual and physical activities during the first wave of the COVID-19 pandemic period

Introduction

The first wave of COVID-19 pandemic period has drastically changed people's lives all over the world. To cope with the disruption, digital solutions have become more popular. However, the ability to adopt digitalised alternatives is different across socio-economic and socio-demographic groups.

Objective

This study investigates how individuals have changed their activity-travel patterns and internet usage during the first wave of the COVID-19 pandemic period, and which of these changes may be kept.

Methods

An empirical data collection was deployed through online forms. 781 responses from different countries (Italy, Sweden, India and others) have been collected, and a series of multivariate analyses was carried out. Two linear regression models are presented, related to the change of travel activities and internet usage, before and during the pandemic period. Furthermore, a binary regression model is used to examine the likelihood of the respondents to adopt and keep their behaviours beyond the pandemic period.

Results

The results show that the possibility to change the behaviour matter. External restrictions and personal characteristics are the driving factors of the reduction in ones' daily trips. However, the estimation results do not show a strong correlation between the countries' restriction policy and the respondents' likelihood to adopt the new and online-based behaviours for any of the activities after the restriction period.

Conclusion

The acceptance and long-term adoption of the online alternatives for activities are correlated with the respondents' personality and socio-demographic group, highlighting the importance of promoting alternatives as a part of longer-term behavioural and lifestyle changes.