The job-housing balance (JHB) significantly influences residents’ well-being and the high-quality development of cities. However, existing studies exhibit limitations in accurately measuring JHB, categorizing cities based on JHB patterns, and identifying its influencing factors. Leveraging large-scale datasets, this study offers a more comprehensive analysis of JHB across Chinese cities. Our work makes contributions in three key aspects: (1) We developed a set of bilateral job-housing balance indicators grounded in the “happy commuting” concept, capturing the balance of inflows and outflows at the sub-district level. (2) We conducted a classification of cities based on these indicators, providing a nuanced understanding of urban spatial structures. (3) We employed data analytics to examine the factors affecting the indicators by city type. The results demonstrate that cities with different JHB characteristics are influenced by distinct factors. These findings underscore the necessity of tailored policy recommendations to promote sustainable and high-quality urban development across various city types.

The study uses multiplex network analysis and a panel data model, based on over 100 million multi-sources data from 286 Chinese cities, to explore the impact of multiple factor flows on economic output in the digital age. New measures were developed to measure cities' multi-connectivity, indicative of their ability to connect and enable factor flows. Empirical analysis was subsequently conducted to investigate the impact of multi-connectivity on economic output. The results unveil positive effects of multi-connectivity on economic output, offering a novel perspective on promoting economic output through multiple factor flows.

This study investigates the evaluation of housing policies for migrants in China, focusing on the interplay between rental and purchase decisions under the rent-and-purchase policy (RPP) framework. Employing a system dynamics model, we simulate migrant housing choices from 2001 to 2023 and forecast market trends from 2024 to 2030. The results indicate that RPPs significantly improve housing quality and reduce costs for migrants by mitigating institutional disparities and market distortions. Scenario analyses demonstrate that a coordinated approach combining supply-side interventions (e.g., affordable housing expansion) with rights-based policies (e.g., equalizing renter and buyer rights) effectively balances affordability and demand stability. The findings emphasize the critical role of addressing rights inequalities and advocate for a holistic policy framework to tackle migrant housing challenges, offering actionable insights for policymakers in system science and urban planning.

Utilizing nearly 80,000 patent records and over 540,000 patent references from within China’s banking industry, spanning from 2000 to July 2021, this paper employs network analysis and the main path method to examine the technological evolution of both Chinese and global banks. The contributions of this study encompass the comprehensive collection of 21 years of patent data, the introduction of a distinctive analytical framework for networks, and addressing a research gap in Chinese banking innovation. The research delves into the sources of innovation of China’s banking industry, maps its development, and identifies cutting-edge technologies of the global banking system, with a specific emphasis on the burgeoning role of blockchain. Additionally, this paper presents a valuable list of recent global patents identified by the main path algorithm, serving as a valuable reference for governments and regulatory bodies worldwide.

This study aims to investigate the role of fintech in stimulating innovation and promoting regional economic growth. A Multi-Sector Endogenous Growth Model (MEGM) is constructed by incorporating fintech while internalizing technological progress and human capital accumulation within the framework of creative destruction. Based on this model, we theoretically analyze how fintech influences innovation and regional economic growth, followed by empirical testing using panel data from 246 prefecture-level cities in China during the period from 2012 to 2020. Furthermore, we contextualize these findings within China's fintech development landscape, trends in technological innovation, and patterns of regional economic growth. The results demonstrate that fintech exerts a significant incentive effect on regional innovation and effectively promotes economic growth. Heterogeneity analysis based on cities' endowments reveals that the impact of fintech is more pronounced in financially developed cities, those with high digital endowments, as well as in first- and second-tier cities. The analyses presented herein elucidate how fintech facilitates technology-driven regional economic growth in China, providing valuable insights for fostering innovation-driven development through fintech.

Based on the cross-generational data of the China Family Panel Studies (CFPS) in 2010, 2014, 2018, this paper empirically explores the intergenerational transmission of household housing preference and its underlying mechanism from a perspective of intergenerational transmission. It finds that: (1) There is a distinct intergenerational transmission of housing preference. (2) For offspring under the age of 45, or those who are female, the intergenerational transmission of housing preferences from parents to their children is more pronounced. (3) Fertility intentions exhibit a resource dilution effect on the intergenerational transmission of housing preference. (4) The stronger the belief within a family that a child’s future success depends on the family’s economic status, the more likely it is to negatively influence the child's housing preferences. (5) Parents not only affect their children's consumption preferences regarding housing but also shape their attitudes towards borrowing for home purchases. This paper offers new insights into understanding household housing preference, and provides a foundation for government initiatives aimed at guiding households in rational asset allocation through social mechanisms.

Notable Regional heterogeneity is commonly observed in housing markets. This study examines how multiple factor flows affect urban house prices and the resulting premium. It utilizes over 100 million pieces of Chinese intercity factor flow data to construct a multi-layer network and introduces a new metric called multiple connectivity quality to measure a city's comprehensive factor connection capability. Empirical analysis reveals that cities with higher multiple connectivity quality tend to exhibit higher price premiums, making them more resilient to market fluctuations. This study offers fresh insight into regional heterogeneity within housing markets and holds practical significance for stabilizing these markets.

A scientific understanding of the real estate sector’s role in the national economy is essential for facilitating reasonable and effective regulation and promoting economic development. By analyzing panel data from a sample of 67 countries between 2010 and 2018, we examine the role of the real estate sector in different countries and its determinants. This empirical study yields three main findings. Firstly, there is a strong correlation between the real estate sector and the financial services sector, the construction industry, as well as wholesale and retail trade. Notably, China’s real estate sector exhibits relatively high direct consumption of financial service activities compared to other major countries. Secondly, there is a transition trend in both the input and output of the real estate sector from primary and secondary industries towards service-oriented industries. Lastly, key determinants influencing the economic effects of the real estate sector in a country include economic growth, current national income level, expense structure of the economy, aging population, as well as urbanization speed.

Using a database of more than 1.1 million comments from the largest Chinese stock discussion forum Eastmoney, we explore the value of “brand” in the Chinese stock market by empirically investigating the impact of brand attention on stock performance and the moderation role of investor sentiment, as well as the heterogeneity of these effects across companies with different brand values. It finds that brand attention has a positive impact on stock returns and stock trading volume. Investor sentiment has a positive impact on stock returns while having a negative impact on stock trading volume. Investor sentiment positively moderates the impact of brand attention on stock returns, but negatively moderates the impact of brand attention on stock trading volume. The impact of brand attention and investor sentiment on stock performance varies across companies with different brand values. It is more pronounced in companies with high brand value than in companies with a relatively low brand value, while the negative effect of investor sentiment on stock trading volume is lower in companies with high brand value, which highlights the importance of brand-building to improve stock performance.

Starting with the housing markets of large and medium-sized cities in China, this paper constructs housing market networks with the data of both the price index and the trading volume, and finds the overall decreasing trend of the connectivity of the networks. The analysis of the network characteristics reflected by the indices established in this paper reveals the extreme high level of global network indicators in the first quarter of 2015 and the first quarter of 2020, demonstrating the phenomenon of “bad news traveling fast”, which can be explained from the perspective of information dissemination and herding behavior. Further empirical analysis shows the negative impact on housing market connectivity from both macroeconomic conditions and the frequency of stock market transactions. Based on the findings, this paper makes policy recommendations for preventing systemic risk in the housing market from the perspective of information dissemination and macroeconomics.

Identifying cross-border knowledge flow and innovation trajectory helps a nation to achieve competitive advantages in the technology race. This paper uses a comprehensive patent analysis method and assessment of national innovation capability to visualise the innovation trajectory and core technology flow of 5G technology across countries (regions) from 2002 to 2019. Firstly, we uncover technology leading countries, technology imitating countries, technology participating countries, and technology holding countries by assessing the level of national technology innovation capability and identifying their development trajectory. Secondly, we observe that China, Japan, and South Korea show more prominence in pictorial communication; the United States focuses on waveguide-related technology, while European countries emphasise antenna-related technology. Finally, we study the diffusion and flow of 5G dominated technology and analyze the technology layout of 5G technology leading countries. The novelty of this study lies in revealing the relationship and significance between the national level of innovation trajectory and the technology level of knowledge flow trajectory. The paper provides implications for the investment of scientific research funds and the choice of cooperative countries in the future. The proposed identification framework of cross-border knowledge flow and innovation trajectory can be applied to other science and technology domains.

Could the corporate carbon information disclosure strategy influence a firm’s brand value, and how does corporate carbon information affect it? Previous research mainly examines the impact of ESG information disclosure on firm value and other financial indicators, but little research has focused on the effect of carbon information on brand value. This paper focuses on the influence of corporate carbon information disclosure on brand value, and we find that it positively impacts corporate brand value. In addition, when a company chooses to adopt a more quantitative and diverse carbon information strategy, it increases its brand value. We also examine the potential mechanisms involved in how corporate carbon information disclosure influences brand value. We focus on three types of factor: analyst rating, customer attitude, and corporate financial performance, and find that higher analyst forecasts and positive customer attitudes have a positive impact on the association between the carbon information strategy and corporate brand value. In contrast, corporate financial performance provides only weak evidence. These results are consistent with demands by users for more precise guidelines from regulators and standard-setters for measuring and disclosing carbon-related information.

This paper aims to investigate the peer effects in financial investment of board-interlocked firms from the information sharing perspective. Based on board interlock and financial information of A-share listed nonfinancial firms in China, we construct board interlocking networks where firms share at least one board member in common and conduct an empirical investigation into peer effects in financial investment of board interlocking firms. The results demonstrate that peer effects are noticeably found in nonfinancial firms even after ruling out endogenous concerns by applying peers' peers' characteristics as instrumental variables, and carrying out robustness tests and placebo tests. In addition, the main manifestation of these peer effects is that firms with inferior quality information, i.e., poor financial conditions, low market capitalization, and higher stock idiosyncratic volatility, tend to follow companies that are perceived as having superior quality information in the above-mentioned areas. Firms located in the core position of board interlocking network or with more assets are more likely to be influenced by peers, because they can obtain more high-quality information. Different from existing studies, this paper provides a board interlocking perspective to the study of peer effects, which offers a new explanation for the expansion of financial activities of firms in China.

对我国风电企业国际化发展竞争力进行了模型构建和实证研究,首先基于专家访谈调研与理论综合分析的基础上,构建了包括供应商、购买者、潜在进入者、同行业竞争者、替代品和企业自身六方面的我国风电企业国际化竞争力的模型指标框架;其次,运用信效度分析与验证性因子分析等方法对所构建的国际化竞争力指标体系的结构有效性进行了检验,并根据验证结果调整模型框架;接下来利用结构方程模型得到的路径系数获得了竞争力模型的权重,构建完成风电企业国际化竞争力评价模型;最后基于构建的国际化竞争力评价模型,对我国风电案例企业以及国际风电企业维斯塔斯、西门子歌美飒进行评价,计算得出的案例企业国际化竞争力水平与当前全球风电市场竞争格局和态势基本一致.

针对银行间质押式回购利率受到多种外部因素影响较难预测的问题,本研究提出基于TEI@I思想的EEMD-XGBoost-ARIMA的银行间质押式回购利率预测算法,构建基于宏观经济、货币政策、流动性因素、相关利率指标等多维度的预测指标体系,引入百度搜索指数作为文本指标进一步提升预测精度.结果表明,基于TEI@I的组合预测模型表现优于传统时间序列预测模型ARIMA,对银行间质押式回购利率的有效预测可为金融机构、投资者和相关监管部门进行流动性管理提供有效依据.

In recent years, China has witnessed the rapid development in housing finance, and there have emerged constantly real estate finance innovations; however, there exists no relevant index for measuring the innovations of China's real estate finance. Based on the perspectives of the governments, enterprises and the public, this paper constructs the "innovation index of real estate finance" on a quarterly basis from 2009 to 2019, with the method of empowerment which combines the subjective method (analytic hierarchy process) and the objective one (range coefficient method). It clearly and concretely depicts the innovations in housing finance and the related temporal-spatial characteristics in China since the outbreak of the financial crisis in 2008. The index covers 30 provinces, autonomous regions and municipalities directly under the central government, and analyzes its temporal and spatial characteristics. The findings show that there exist a strong spatial autocorrelation and a big regional difference in innovations.

This paper empirically investigates the heterogeneous impacts of the media sentiment about policies with different themes on the real estate market in China. Based on the policy texts collected from both official and unofficial sources, we construct sentiment indices to capture the sentiment about policies with different themes, including real estate policies, fiscal policies, monetary policies, land policies, healthcare policies, household registration policies, and education policies, using text mining methods. Mediation models and GARCH models are then established to examine the impact of these sentiment indices on the real estate market. The E-GARCH model is established to examine the asymmetric effect of positive and negative sentiment on real estate market. The results show the following: (1) The real estate market in China is more affected by the policy sentiment on official media compared with the unofficial ones. (2) Policy sentiment affects the real estate price through the mediating variables of interest rate, real estate construction area, and real estate sales. (3) The impacts of sentiment with different themes on the volatility of the real estate market are heterogeneous. (4) The impacts of policy sentiment on official media are more pronounced in a tight government-policy environment than those in a loose one. (5) The effect of negative unofficial media policies sentiment on real estate price is bigger than the positive unofficial media policies sentiment.

随着科学技术深度融入产业变革,我国银行业依托业务和技术的"双轮"创新驱动发展,技术创新水平迈上新台阶,创新能力蓬勃成长,但仍面临关键信息基础设施薄弱、核心技术受制于人等问题与挑战,亟待探索构建相对完整、自立自强、稳定安全的银行业技术体系.文章回顾了我国银行业技术创新发展历程与主要成效,从技术实力、人才培养、数据要素治理、组织建设和监管科技发展共5个层面总结提炼了我国银行业技术创新发展面临的关键问题及对应建议,并提出了健全创新引导政策体系、完善技术供需匹配机制等综合性对策.

With technology and finance becoming increasingly integrated, it is imperative to use fintech to improve the capability to forestall and defuse major financial risks. As an area prone to financial risks, the real estate industry deserves in-depth research on the dynamics between risks and technological capability (TC). In this paper, a simulation model was constructed with system dynamics to examine whether an improvement in TC can effectively improve risk management capability (RMC), and to explore the specific interaction between RMC and TC under six policy scenarios. We present the following findings: (1) TC has a significant supporting role in risk management; (2) increasing R&D financial input is more effective than increasing personnel input when it comes to improving TC; (3) whether it is a single input or multiple inputs of different types, increasing R&D financial input is also more effective than increasing personnel input when it comes to improving risk management; (4) overall, improvements in TC and RMC have a positive effect on social and economic development. This study not only makes clear the interconnection between TC and RMC and enriches the research content in this field, but also provide a reference for preventing and resolving major financial risks and promoting stable social and economic development.