Exploring the green innovation effect of the digital economy under the condition of socialist market economy with Chinese characteristics is of great contemporary value. In this paper, we incorporate digital economy development, marketization and green innovation into a unified analytical framework. Based on the theoretical analysis of the intrinsic logical relationship among the three, a panel data of 31 provinces in mainland China from 2011 to 2021 is employed to empirically test the effect and mechanism of digital economy development on green innovation under the condition of marketization. The results show that digital economy development is effective in improving the level of regional green innovation; Marketization is an important transmission mechanism for digital economy to release the effectiveness of green innovation. Besides, marketization has a significant double threshold effect on green innovation driven by digital economy. To promote the synergistic development of China's digital economy, market-oriented reform and green innovation in the future, we should focus on promoting the construction of an “enterprise-public-government” community for digital economy and improving the mechanism of market-oriented green innovation.
This study examines the critical role of telepresence in augmented reality (AR) retail, focusing on the key attributes of interactivity and vividness, and their impact on online marketing effectiveness. Through an online survey, the research reveals that a highly interactive and vivid AR shopping platform enhances media usefulness and media enjoyment. Furthermore, AR technology creates a realistic product experience that closely mimics physical shopping, thereby increasing consumer engagement. The results indicate that media usefulness and media enjoyment significantly enhance consumer engagement, subsequently leading to stronger purchase intentions. The study further demonstrates the sequential relationships between AR attributes, media usefulness, media enjoyment, consumer engagement, and purchase intention. This research provides valuable insights into the theoretical foundations of AR's influence on consumer behavior, shedding light on how this technology can be effectively leveraged to enhance online shopping experiences for consumers.
Effective decision-making in complex environments requires discerning the relevant from the irrelevant, a challenge that becomes pronounced with large multivariate time-series data. However, existing feature selection algorithms often suffer from complexity and a lack of interpretability, making it difficult for decision-makers to extract value, manage risks, and adhere to compliance regulations in a thoroughly explainable way. To address these challenges, we propose a novel causality-based feature selection technique that embeds an explainable unsupervised feature selection algorithm. We refer to our proposed method as Causal Feature Selection with Minimum Redundancy (CFSMR). Our method yields a minimum viable feature set without compromising model performance while ensuring interpretability. We conduct an experimental study to compare the proposed technique with conventional feature selection techniques. Our results demonstrate that our proposed method outperforms or performs on par with existing techniques, making it a promising approach for decision-makers seeking an effective and interpretable feature selection method.
This paper examines the impact of digital governance on inbound tourism using the panel dataset from 151 countries from 2000 to 2019. Fixed-effects and System Generalised Method of Moments estimations show that the internet shutdown capacity and practice decrease inbound tourism. Social media monitoring with strict rules also hinders inbound tourism. It is found that governance capacity and practical censorship implications negatively affect tourism activities. Several policy implications for the proper control of digital communications are also discussed.
The employment sector has suffered an abrupt decline in labour force participation since COVID-19 started. Digital platforms offer virtual workspace, enable remote working, and thus remain the only alternative to maintain stability in the labour market during the lockdown period. Since levels of digital inclusion vary among countries, the pandemic-led employment shocks also differ across countries. This study examines a cross-sectional dataset of 93 countries and analyses the impact of digital inclusion on employment shock during the COVID-19 pandemic using regression analysis. The estimation result suggests that digital inclusion has a significant favourable effect on employment growth in the pandemic. For one unit of increase in the digital inclusion index at the mean value of confirmed COVID-19 cases in natural logarithm, employment growth rises by 0.078 %. This favourable impact remains significant for both high- and low-income countries and is more pronounced in high-income countries. This study provides much-needed cross-country evidence on the importance of digital inclusion for stabilizing employment during the pandemic and helps inform future theoretical work on this issue.
This study estimates the environmental impacts of Bitcoin mining. Employing a top-down measurement approach, this paper assesses the carbon footprint of Bitcoin mining in China from 2017 to 2021. The findings reveal that mining activities during this period contributed to a total of 77.84 million tons of carbon dioxide emissions in China. By utilizing data at the provincial level, we find that the seasonal migration of Bitcoin mining pools will lead to regional power demand shocks in China. Additionally, this study predicts future carbon emissions from Bitcoin mining in China, projecting cumulative carbon dioxide emissions of 76.40 million tons and 722.18 million tons by 2030 and 2060 respectively, in the absence of any policy interventions. Based on these findings, this paper posits that governments worldwide should make efforts to restrict the carbon emissions from Bitcoin mining and opt for environmentally friendly technological methods to fundamentally alleviate Bitcoin's reliance on energy. The implication for central banks is that carbon emission should be taken into consideration when designing the central bank digital currencies (CBDCs).