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Currently, countries worldwide are embracing digital strategies, enabling enterprises to utilize digital technology, digital supply chains, blockchain, and additional digital measures to increase their competitiveness. This paper analyzed the correlation between the digital transformation of manufacturing export enterprises and their business and export performance, focusing on China's manufacturing export enterprises through empirical analysis. The study investigated the influence of digital transformation on enterprise performance. Using the Resource Based View theory and Trade theory, hypotheses were proposed and regression models were developed to analyze a sample of 1007 enterprises listed on the Shanghai and Shenzhen Stock markets from 2012 to 2019. The study conducted regression analysis, intermediate effect test, robustness test, stage lag, and heterogeneity analysis. The study found that (1) Manufacturing export enterprises listed in the stock market implemented digital transformation, leading to a significant positive impact on their overall performance. (2) Digital transformation led to cost reduction, improved R&D intensity, and enhanced human resources, among other benefits for enterprise performance. (3) According to the fractal analysis, non-state-owned enterprises exhibited more favorable effects on enterprise performance, and the digital transformation of manufacturing export companies in developed regions had a more significant impact on their performance. Finally, the study's empirical results yielded pertinent proposals for digital transformation. [ABSTRACT FROM AUTHOR]

This study explores the peer and economic effects of corporate poverty alleviation behavior. Using the data of A-share non-financial listed corporates in Shanghai and Shenzhen of China from 2016 to 2020, the empirical analysis of this study finds that: corporate poverty alleviation behavior has significant peer effects; the guidance of local poverty alleviation policies weakens the peer effects of corporate poverty alleviation behavior; compared to private enterprises, the poverty alleviation behavior of the peer firms has a more significant impact on state-owned enterprises; and corporate poverty alleviation behavior can result in the backflow of economic benefits and achieve the organic unity of economic and social benefits. The purpose of this paper is to explore the peer effects of corporate poverty alleviation behaviors through empirical analysis using available public data. The results of the study not only increase the motivation of corporate to participate in poverty alleviation from a peer effects perspective, but also reveal key factors for sustaining corporate poverty alleviation behaviors. [ABSTRACT FROM AUTHOR]

Since December 2019, the COVID-19 pandemic has quickly spread across the world. The traditional understanding of the relationship between wealth and the spread of contagious diseases is that similar to many precedent epidemics, the pandemic spread easily in poor neighborhoods in many countries. The environmental and socioeconomic implications of the COVID-19 pandemic are still poorly understood, thus this paper examines the relationship between neighborhood characteristics and the spread of the pandemic through a case study of Shenzhen, a Chinese megacity with many low-income rural migrants. The major finding is that wealthier and larger neighborhoods in Shenzhen were more likely to be infected in the first wave of the pandemic in 2020. This spread pattern is likely to result from China's strict control to prevent the pandemic, human mobility, and demographic characteristics such as income. This finding reveals a new phenomenon that contrasts with the traditional understanding of the influence of wealth on the spread of epidemics. This paper enriches the understanding of the role of neighborhoods in the spread of the pandemic, and it has important public policy implications. [ABSTRACT FROM AUTHOR]

In the era of innovation dividends, whether investors, as the main participants in the capital market, can tolerate enterprise innovation activities is the key to whether the capital market can help enterprises innovate. This paper takes the listed companies of Shanghai and Shenzhen A-shares in China that disclosed quantitative performance forecasts from 2016 to 2021 as samples, obtains the market reaction of performance forecasts through the event study method and uses them as proxy variables of investors' short-term performance expectations, and uses multiple regression analysis to explore the impact of corporate R&D on investors' short-term performance expectations. The results are as follows: (1) corporate R&D investment significantly reduces investors' short-term performance expectations (that is, investors have a significant tolerance effect on enterprises with higher R&D investment); (2) the increase in the shareholding ratio of institutional investors weakens the tolerance effect; and (3) with the implementation of China's innovation-driven strategy, the tolerance effect of its capital market on enterprise R&D gradually increases, especially for high-tech companies, but has a low tolerance effect on state-owned companies' R&D risk. The results show that investors in China's capital market are not completely rational in their response to corporate R&D, and investors are willing to bear more short-term performance losses for high R&D investment, which is consistent with prospect theory. [ABSTRACT FROM AUTHOR]

The majority of insurance investment funds are derived from policy liability debt funds. It differs from other institutional investors in a number of ways, including investment size, horizon, duration, risk, and so on. However, only a small portion of the extant literature focuses on in-depth and extensive analysis of Insurance Institutional Investors' holdings (IIIs). This study analyses the impact of shareholding by insurance institutions on the value of Shanghai and Shenzhen A-share listed companies in China's capital market. The paper offers three major contributions. First, we discovered that long-term equity-holding IIIs have both value selection and value creation functions. Second, the value creation function becomes more significant among long-term stock-holding IIIs with an increase in the period during which they retain the company's shares; Third, fast-in and fast-out (FIFO) IIIs have a value-inhibiting effect on the held company and serve a value selection role, rather than a value creation function. This study provides more insight on the lack of academic interest in insurance institutions and serves as a foundation and reference for the design of regulatory policies for insurance institutions' involvement in stock markets. It also gives empirical evidence for corporations to accurately analyze shareholding by insurance institutions. Furthermore, since this study concentrates on China's capital market, it can serve as a benchmark for other nations, particularly, those designated as developing market economies. [ABSTRACT FROM AUTHOR]

The pressure upon local governments to redeem their debt could affect government fiscal ability. It could consequently affect their fiscal policies on corporations, which might distort corporate innovation. Based on the data of Chinese Shanghai and Shenzhen A-share listed companies and the local government implicit short-term debt financed by local government financing vehicles (LGFVs) in 31 provinces, this paper shows that local government debt (LGD) negatively affects corporate R&D investment in China, thereby suggesting a strong crowding-out effect. The crowding-out effect is more pronounced when the firm is a non-state-owned enterprise (NSOE), the firm's size is small, the firm's age is young, or the firm is in the lower market competition. This paper provide evidence by interacting the terms that local government actions, such as consumption of fiscal resources, strengthening tax collection efforts, or consumption of credit resources, might partially account for the crowding-out effect. This study illustrates the innovation costs of local government debt. [ABSTRACT FROM AUTHOR]

Environmental protection and social obligation fulfillment have become hot subjects as the "dual carbon" approach has been developed and deepened. The ESG system is consistent with China's current policies, abandoning the traditional business philosophy of economic supremacy in favor of comprehensively measuring corporate social responsibility and sustainable development capability across three dimensions: environmental (E), social (S), and corporate governance (G), which receive widespread attention from all sectors of society. Based on observational data from A-share listed businesses in Shanghai and Shenzhen from 2011 to 2020, this study empirically evaluates the influence and mechanism of ESG on government subsidies. The research results indicate that enterprises can receive more government subsidies by improving ESG performance. Mechanism analysis found that corporate transparency plays a positive mediating role in the process of ESG affecting government subsidies. Further research on political affiliation and property rights has found that companies without political affiliation are more inclined to receive more government subsidies by improving ESG performance, and the impact of political affiliation and ESG performance on government subsidies is mutually complementary. Enterprises with different property rights have different strengths of motivation to increase government subsidies by improving ESG performance. State owned enterprises (excluding central enterprises) are the strongest, followed by non-state-owned enterprises, and central enterprises are the weakest. Therefore, enterprises should be further encouraged to strengthen ESG construction, improve the quality of ESG information disclosure, improve resource allocation efficiency, and promote high-quality development of enterprises. [ABSTRACT FROM AUTHOR]

The green credit policy serves as a crucial instrument for achieving the dual objectives of optimal resource allocation and green development. It plays a pivotal role in curbing inefficient investments in innovation by enterprises. This research employs the PSM-DID method to effectively explore the practical effects of the green credit policy on the innovation inefficiency investments of heavily polluting enterprises in China. Examining the impact from the perspectives of environmental regulation and financial constraints, the study utilizes panel data from listed companies on the Shanghai and Shenzhen A-shares markets spanning from 2010 to 2020. The following conclusions are drawn: (1) Green credit policy has proven effective in inhibiting the inefficient investment in innovation by heavily polluting enterprises when compared to non-heavily polluting enterprises. (2) Moreover, this effect is more pronounced in state-owned enterprises and regions with less financial development. (3) Mechanism testing reveals that the green credit policy can discourage corporate over-investment by influencing financing constraints and can alleviate under-investment through commercial credit. [ABSTRACT FROM AUTHOR]

Competitive strategy plays an important role in achieving superior profits, but there is still much to be explored in terms of the effect on firm growth. This study focuses on exploring the relationship between competitive strategy and firm growth in emerging economies. We focus on how the development zone policies moderate this relationship. This study uses a two-way fixed-effect model to analyze data for 527 manufacturing firms listed in China's Shanghai and Shenzhen A-shares from 2012-2021. Our empirical analysis showed that there is a significant positive relationship between low-cost strategy and firm growth and a significant negative relationship between differentiation strategy and firm growth. Compared with national development zones, firms in provincial development zones choose low-cost strategies that are more conducive to growth. Compared with provincial development zones, firms in national development zones choose differentiation strategies that are more conducive to growth. These findings contribute to understanding the mechanisms by which competitive strategy affects firm growth in different regional institutional contexts in emerging economies. The results of the study also have reference value for the government to optimize the development zone policies. [ABSTRACT FROM AUTHOR]

Public transit, especially urban rail systems, plays a vital role in shaping commuting patterns. Compared with census data and survey data, large-scale and real-time big data can track the impacts of urban policy implementations at finer spatial and temporal scales. Therefore, this study proposed a multi-level analytical framework using transit smartcard data to examine urban commuting dynamics in response to rail transit upgrades. The study area was Shenzhen, one of the most highly urbanized and densely populated cities in China, which provides the opportunity to examine the effects of rail transit upgrades on commuting patterns in a rapidly developing urban context. Changes in commuting patterns were examined at three levels: city, region, and individual. At the city level, we considered the average commuting time, commuting speed, and commuting distance across the whole city. At the region level, we analyzed changes in the job accessibility of residential zones. Finally, this study evaluated the potential effects of rail transit upgrades on the jobs-housing relationship at the individual level. Difference-in-difference models were used for causal inference between rail transit upgrades and commuting patterns. In the very short term, the opening of new rail transit lines resulted in no significant changes in overall commuting patterns across the whole city; however, two effects of rail transit upgrades on commuting patterns were identified. First, rail transit upgrades enhanced regional connectivity between residential zones and employment centers, thus improving job accessibility. Second, rail transit improvement increased the commuting distances of individuals and contributed to the separation of workplaces and residences. This study provides meaningful insights into the effects of rail transit upgrades on commuting patterns. [ABSTRACT FROM AUTHOR]

Housing is among the most pressing issues in urban China and has received considerable scholarly attention. Researchers have primarily concentrated on identifying the factors that influence residential property prices and how such mechanisms function. However, few studies have examined the potential factors that influence housing prices from a big data perspective. In this article, we use a big data perspective to determine the willingness of buyers to pay for various factors. The opinions and geographical preferences of individuals for places can be represented by visit frequencies given different motivations. Check-in data from the social media platform Sina Visitor System is used in this article. Here, we use kernel density estimation (KDE) to analyse the spatial patterns of check-in spots (or places of interest, POIs) and employ the Getis-Ord method to identify the hot spots for different types of POIs in Shenzhen, China. New indexes are then proposed based on the hot-spot results as measured by check-in data to analyse the effects of these locations on housing prices. This modelling is performed using the hedonic price method (HPM) and the geographically weighted regression (GWR) method. The results show that the degree of clustering of POIs has a significant influence on housing values. Meanwhile, the GWR method has a better interpretive capacity than does the HPM because of the former method’s ability to capture spatial heterogeneity. This article integrates big social media data to expand the scope (new study content) and depth (study scale) of housing price research to an unprecedented degree. [ABSTRACT FROM AUTHOR]