Firstly, the article elaborates on the concepts of metaverse and industrial metaverse, pointing out that the metaverse has driven changes and optimizations in multiple dimensions such as urban form, social organization form, and industrial production form; Secondly, the metaverse has empowered urban governance in Guangzhou, improving the efficiency of urban management, enhancing the city's emergency management capabilities, improving the quality of interaction between people and the city, and promoting the construction of a smart city; Once again, the focus was on the practices and good results achieved by Guangzhou in utilizing blockchain technology, digital twin technology, generative artificial intelligence technology, unmanned aerial vehicles+AI and other technologies in urban governance and serving the public; Finally, it is clarified that metaverse related technologies will promote the integration of carbon based civilization and silicon-based civilization in urban and social governance. Humans can use silicon-based civilization technology to expand their living space and improve their quality of life, while silicon-based civilization can also draw inspiration from the culture and emotions of carbon based life, achieving more comprehensive development.

Financial technology, also known as Fintech, is transforming our daily life and revolutionizing the financial industry. Yet at present, consensus regarding the effect of Fintech on green bonds market is lacking. With novel data from China, this study documents robust evidence showing that Fintech development can significantly boost green bonds issuance. Further analysis suggests that this promotion effect occurs by empowering intermediary institutions and increasing social environmental awareness. Additionally, we investigate the heterogeneous effect and find that the positive relation is more pronounced for bonds without high ratings and in cities connected with High-Speed Railways network. The results call for the attention from policymakers and security managers to take further notice of Fintech utilization in green finance products.

As digital technologies proliferate, firms increasingly leverage digital transformation strategically, necessitating new orientations attuned to digital technological change. This study investigates how digital orientation (DORI)- the philosophy of harnessing digital technology scope, digital capabilities, digital ecosystem coordination, and digital architecture configuration for competitive advantage – influences firms’ environmental, social, and governance performance (ESG_per). Analysis of Chinese A-share firms from 2010-2019 reveals DORI is associated with superior ESG_per, operating through the mediating mechanism of enhanced digital finance (DIFIN) as a fund-providing facilitator for sustainability initiatives. Additional analysis uncovers important heterogeneities – private firms, centrally owned state-owned enterprises, politically connected, and emerging companies exhibit the strongest DORI - ESG_per linkages. Prominently, the study findings are validated through a battery of robustness tests, including instrumental variable methods, and propensity score matching. Overall, the results underscore the need for firms to purposefully develop multifaceted digital orientation and furnishes novel theoretical insights and practical implications regarding DORI’s role in improving ESG_per.

The study aims to explain the economic impact of Internet implication in tourism sector by taking sample of mega project listed countries (which provide big pitch to boost tourism business). Our work find the volatility cause of tourism revenue at country i, by examining the inbound tourist expenditures as a factor of technological infrastructure. We deploy data ranging from 1990 to 2017 and uses error correction model as representative of Autoregressive-Distributed Lag (ARDL) model after addressing diagnostic tests (for data reliability concern). We found long- and short-run association between tourism expenditure and information and communication technology (ICT) proxies in case of developed economies, while only short-run association in underdeveloped countries. The startling scenario about underdeveloped economies are also confirmed by one-way causation in our analysis. After sensitive analysis at each slot, the study concludes that tourism revenue is streaming low across those boundaries where tourists a

Many corporate executives believe blockchain technology is broadly scalable and will achieve mainstream adoption, yet there is little evidence of significant shareholder value creation associated with corporate adoption of blockchain technology. We collect a broad sample of firms that invest in blockchain technology and examine the stock price reaction to the “first” public revelation of this news. Initial reac- tions average close to +13% and are followed by reversals over the next 3 months. However, we report a striking differ- ence based on the credibility of the investment. Blockchain investments that are at an advanced stage or are con- firmed in subsequent financial statements are associated with higher initial reactions and little or no reversal. The results suggest that credible corporate strategies involving blockchain technology are viewed favorably by investors.

Software and accounting advances have led to a rapid expansion in and proliferation of loyalty tokens, typically bundled as part of product price. Some tokens, such as in the airline industry, already account for tens of billions of dollars and are a major contributor to revenues. An open question is whether, as technology evolves, firms will have a strong incentive to make loyalty tokens tradable, raising regulation issues, including with monetary and banking authorities. This paper argues that for the vast majority of tokens, issuing firms have a strong incentive to make them non-tradable. The core incentive for token issuance here is that an issuer can earn a higher rate of return on the ``float'' (tokens issued but not yet used) than its retail customers can, much like a bank. Our main finding is that an issuer earns higher revenue by making tokens non-tradable even though the consumer would be willing to pay a higher price for tradable tokens. We further show that an issuer with stronger market power tends to allow more frequent token redemption, and its revenue is more token-dependent. We test the model's predictions with data on airline mileage and hotel reward programs and document consistent empirical results that align with our theory.

The healthy operation of the stock market relies on sound liquidity. We utilize the semantic information from disclosure texts of listed companies on the China Science and Technology Innovation Board (STAR Market) to construct a daily corporate network. Through empirical tests and performance analyses of machine learning models, we elucidate the relationship between the similarity of company disclosure text contents and the temporal and spatial correlations of stock liquidity. Our liquidity indicators encompass trading costs, market depth, trading speed, and price impact, recognized across four dimensions. Furthermore, we reveal that the information loss caused by employing Minimum Spanning Tree (MST) topology significantly affects the explanatory power of network topology indicators for stock liquidity, with a more pronounced impact observed at the document level. Subsequently, by establishing a neural network model to predict next-day liquidity indicators, we demonstrate the temporal relationship of stock liquidity. We model a liquidity predicting task and train a daily liquidity prediction model incorporating Graph Convolutional Network (GCN) modules to solve it. Compared to models with the same parameter structure containing only fully connected layers, the GCN prediction model, which leverages company network structure information, exhibits stronger performance and faster convergence. We provide new insights for research on company disclosure and capital market liquidity.

This paper explores the ethical dimensions of firm-level digitalisation and its impact on ESG metrics during a decade (2010-2020) of rapid technological progress, focusing on Chinese-listed companies. Utilising a text-based index to measure digitalisation, we find that while digitalisation positively influences ESG ratings, supporting resource-based and dynamic capability theories, its relationship with corruption reveals complex dynamics. Surprisingly, corruption strengthens digitalisation’s positive impact on ESG, raising concerns about technology being used to enhance ESG appearances artificially. A distinct difference emerges between state-owned enterprises (SOEs) and non-SOEs; SOEs use digitalisation more ethically and are less influenced by corruption, indicating a more responsible approach to technology adoption. Through examining cash holdings, internal controls, and audit fees, we unpack how corruption influences the digitalisation-ESG nexus. These insights underscore the need for policy that encourages ethical digitalisation and highlight the potential role of SOEs in leading the charge towards sustainable and ethical digitalisation.

This paper studies the impact of AI technology on the mutual fund industry. I develop a new measure of AI adoption based on hiring practices and find that this measure can predict fund performance. The funds with high AI ratio outperform non-AI funds, after I controlling for standard factors and fund characteristics. Further empirical evidence shows that funds with a high AI ratio tilt their portfolios toward high information intensity stocks, indicating that mutual funds benefit from AI technology adoption by improving their information capacity. Consistent with this channel, I find that the outperformance of these mutual funds mainly comes from better stock picking skills. Finally, AI technology adoption has a negligible effect on fund manager turnover.

As digital transformation strategies have emerged as a primary approach for enterprises to enhance their Total Factor Productivity (TFP), it is crucial to empirically examine the impact of these strategies on TFP. For this purpose, this study considers these transformation strategies as a quasi-natural experiment and employees a propensity score-weighted difference-indifferences methodology on data from Chinese firms listed on the A-share market between 2007 and 2020. The key findings include: (1) digital transformation has a significant positive influence on TFP; (2) Generalized boosted regression trees analysis reinforces this finding after controlling for other TFP determinants; (3) notably, non-state-owned and technology-intensive enterprises exhibit a more distinct enhancement in TFP following digital transformation. These results underscore the need for firms to increase investment in research and development capabilities and digital competencies.