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As an important engine of economic growth, the digital economy is bringing new opportunities for the promotion of entrepreneurship. However, key questions regarding the extent of the effect of the digital economy on entrepreneurship remain unanswered. This study examines how the digital economy influences entrepreneurship in China using provincial data from 2011–2020, applying convergence tests and spatial econometric models.

Based on theoretical analysis and using macro provincial data covering the period of 2011–2020, we adopt a diversified empirical analytical method and apply a combination of the convergence trend test, spatial auto correlation test, and spatial Durbin model to test the research hypotheses.

First, there is spatial correlation between the digital economy and entrepreneurship. Second, the overall trend of China’s digital economy shows s convergence, with the whole country and the eastern region showing absolute β convergence and the whole country as well as the central and western regions showing β conditional convergence. Third, the digital economy can significantly promote entrepreneurship and has spatial spillover effects. Moreover, higher education has a negative moderating effect on the process of digital economy empowering entrepreneurship.

Studying the spatially correlated impacts of the digital economy on entrepreneurship enhances our understanding of its contribution to economic growth. Policy-makers can use these findings to develop targeted digital infrastructure investments in lagging provinces, guide entrepreneurs to better grasp the opportunities of the digital economy, and provide support for innovation and entrepreneurship. The findings also could offer Chinese experience that can be used to guide developing countries in utilizing the digital economy to enable entrepreneurship.

This paper expands and enriches the analytical focus on digital economy-empowered entrepreneurship and complements the current theoretical research on the moderating effect of the digital economy in empowering entrepreneurship.

This study aims to examine the complex effects of foreign direct investment (FDI) on China’s agricultural total factor productivity (TFP) from 2005 to 2020. It also explores the role of absorptive capacity as a moderating factor during this period.

Employing provincial panel data from China, this research measures agricultural TFP using the Stochastic Frontier Approach (SFA)-Malmquist method. The impact of FDI on agricultural productivity is further analyzed using a nondynamic panel threshold model.

The results highlight technological progress as the main driver of agricultural TFP growth in China. Agricultural FDI (AFDI) seems to impede TFP development, whereas nonagricultural FDI (NAFDI) shows a distinct positive spillover effect. The study reveals a threshold in absorptive capacity that affects both the direct and spillover impacts of FDI. Provinces with higher absorptive capacity are less negatively impacted by AFDI and more likely to benefit from FDI spillovers (FDISs).

This study provides new insights into the intricate relationship between FDI, absorptive capacity and agricultural productivity. It underscores the importance of optimizing technological progress and research and development (R&D) to enhance agricultural productivity in China.

In autonomous driving, the inherent sparsity of point clouds often limits the performance of object detection, while existing multimodal architectures struggle to meet the real-time requirements for 3D object detection. Therefore, the main purpose of this paper is to significantly enhance the detection performance of objects, especially the recognition capability for small-sized objects and to address the issue of slow inference speed. This will improve the safety of autonomous driving systems and provide feasibility for devices with limited computing power to achieve autonomous driving.

BRTPillar first adopts an element-based method to fuse image and point cloud features. Secondly, a local-global feature interaction method based on an efficient additive attention mechanism was designed to extract multi-scale contextual information. Finally, an enhanced multi-scale feature fusion method was proposed by introducing adaptive spatial and channel interaction attention mechanisms, thereby improving the learning of fine-grained features.

Extensive experiments were conducted on the KITTI dataset. The results showed that compared with the benchmark model, the accuracy of cars, pedestrians and cyclists on the 3D object box improved by 3.05, 9.01 and 22.65%, respectively; the accuracy in the bird’s-eye view has increased by 2.98, 10.77 and 21.14%, respectively. Meanwhile, the running speed of BRTPillar can reach 40.27 Hz, meeting the real-time detection needs of autonomous driving.

This paper proposes a boosting multimodal real-time 3D object detection method called BRTPillar, which achieves accurate location in many scenarios, especially for complex scenes with many small objects, while also achieving real-time inference speed.

This paper originally proposed the fuzzy option pricing method for green bonds. Based on the requirements of arbitrage equilibrium, this paper draws on Merton's corporate bond option pricing model.

Describing the asset value behavior of green bond issuing enterprises through diffusion-jump processes to reflect the uncertainty brought by carbon emission reduction policies and technologies, using approximation methods to get the analytical pricing formula and then, using a fuzzification technique of Choquet expectation under  λ-additive fuzzy measures after considering fuzzy factors, the paper provides fuzzy intervals for the parity coupon rates of green bonds with different subjective levels for investors.

The paper proposes and argues the classical and fuzzy option pricing methods in turn for both corporate ordinary bonds and green bonds, considering carbon risk or climate risk. It implements the scenario analysis varying with industry emission standards and discusses the sensitiveness of the related key parameters of the option.

The fuzzy option pricing for the green bonds provides the scope of the variable equilibrium values, operational theoretical supports and some policy implications of carbon reduction and promoting green funding.

The logic of introducing the fuzziness of the option pricing for the green bonds lies with considering the existence of fuzzy information about the project supported by the green bond and the subjectivity of investors and it also responds to changes in technological uncertainty and policy uncertainty in the process of “carbon peaking and carbon neutrality.”

This study aims to acquire a better understanding on the characteristics and risks of heavy metals (HMs) in PM_2.5 from an industrial city – Handan, China.

PM_2.5 samples were collected on the basis of daytime and nighttime at the state controlling air sampling site in Handan city. Ten metal elements (V, Cr, Mn, Fe, Ni, Cu, Rb, Sr, Cd and Ba) in PM_2.5 were determined with an inductively coupled plasma mass spectrometry. The pollution levels of metals were characterized by enrichment factors, and the sources of metals were identified with principle component analysis and cluster analysis. The ecological and health risks of metals were assessed using ecological and health risk indexes.

Results showed that the highest and lowest PM_2.5 concentration appeared in winter and summer, respectively. The concentration of PM_2.5 at night was higher than in the daytime in winter, yet it is the opposite in other seasons. The total mass concentration of detected metals was the highest in winter, and the total mass concentration in the daytime was higher than at night in all four seasons. The elements V, Rb, Sr and Ba exhibited a deficient contamination level; Cr, Ni and Cu exhibited a moderate contamination level; while Fe and Cd were at an extreme contamination level. The metals in PM_2.5 originated from a mixture source of fossil fuel combustion and manufacture and use of metallic substances (34.04%), natural source (26.01%) and construction and traffic-related road dust (17.58%). Results from the ecological risk model showed that the ecological risk of metals was very high, especially risks related to Cd. Health risk model presented that both the non-carcinogenic and carcinogenic risk coefficients of metals were above the tolerance level of the human body.

The significance of the study is to further know the pollution characteristics of PM_2.5 and related HMs in Handan city, and to provide references for ensuring local resident health and ecological environment.

This study examined the influence of corporate governance (CG) in relation to venture capital (VC) investment on invested firm's corporate social responsibility (CSR) performance in the Chinese context. More specifically, this paper examined the mediation of the proportion of independent directors (INDD), management shareholding (MSH) and executives' political connections (POLC) in the above-mentioned relationship.

This empirical study performed multiple mediation testing and bootstrap mediation robustness test on data from Chinese A-class shares IPO companies between 2010 and 2018.

The results of direct relationship analysis showed that VC support is detrimental to firm' CSR performance, consistent with previous research studies. The indirect effect analysis showed that VC reduced firm' CSR through reduction of INDD on board and increased MSH. Conversely, VC contributed to firm's CSR through higher POLC, which confirmed the significance of the joint mediation model.

This study offers stakeholders the opportunity to develop a deeper understanding of the role of VC institutions, independent directors and executives, in terms of firm's CSR, as well as provides insights on control rights allocation and policy drafting on independent directors when considering accessing VC support.

By analyzing the mediation model of the VC–CSR relationship, this paper provides evidence to enrich the debate on the role of CG in the relation between VC and firm's CSR.

Currently, ubiquitous smartphones embedded with various sensors provide a convenient way to collect raw sequence data. These data bridges the gap between human activity and multiple sensors. Human activity recognition has been widely used in quite a lot of aspects in our daily life, such as medical security, personal safety, living assistance and so on.

To provide an overview, the authors survey and summarize some important technologies and involved key issues of human activity recognition, including activity categorization, feature engineering as well as typical algorithms presented in recent years. In this paper, the authors first introduce the character of embedded sensors and dsiscuss their features, as well as survey some data labeling strategies to get ground truth label. Then, following the process of human activity recognition, the authors discuss the methods and techniques of raw data preprocessing and feature extraction, and summarize some popular algorithms used in model training and activity recognizing. Third, they introduce some interesting application scenarios of human activity recognition and provide some available data sets as ground truth data to validate proposed algorithms.

The authors summarize their viewpoints on human activity recognition, discuss the main challenges and point out some potential research directions.

It is hoped that this work will serve as the steppingstone for those interested in advancing human activity recognition.

The purpose of this paper is to establish a synthetic evaluation index system of new socialist countryside (NSC) development at county level in China, and by which to evaluate the level of NSC construction among different regions in China. Then, some problems of rural development can be found and corresponding measures can be proposed, which could provide references for policymaking.

First, from agricultural, rural and farmers' perspective, a preliminary index system which containing 44 indicators was put forward. Then, combining with a series of subjective and objective indicator screening methods, such as fuzzy synthetic evaluation, clustering analysis, correlation and variation coefficient analysis, the final index system containing 22 indicators was established. Third, combining with factor analysis, the final index system was used to evaluate the level of NSC construction in 28 counties of China in 2007. Finally, we calculated district factor scores by a model and gave an aggregate index ranking of different regions.

NSC construction at county level is not well developed in China and there are significant geographical differences among different districts. First, NSC construction in Shanghai, Beijing, Nanjing, Guangzhou and Hangzhou is relatively better. Second, NSC construction of East China is better than that of North China and Central China. Northeast of China is better than Southwest and Northwest. Third, NSC construction in municipalities is higher than non‐municipalities. Rural development in Western regions of China needs to be paid special attention.

A final evaluation index system including 22 indicators was designed. These indicators are complete, independent, weakly correlative and stable. The index system can be further applied to evaluate other regions' NSC development. The evaluation results can provide useful references for NSC reform in the whole nation.

This paper aims to investigate the influence of the regional business environment on local firm innovation, considering various dimensions such as administrative, financial and legal environments.

Multiple regression analysis is employed to analyze archival data for firms listed on Chinese stock markets.

We find that the optimizations of the administrative and financial environments positively affect firm innovation, whereas the legal environment does not exert a similar impact. Our analysis also reveals that the business environment’s optimization significantly influences innovation in firms that are small, non-state-owned and operating in high-tech industries. Furthermore, the business environment acts as a moderating variable in the relationship between firm innovation and firm value.

This study contributes to a more comprehensive understanding of institutional-level determinants of firm innovation, highlighting the nuances of the legal environment and the importance of context-specific analysis, especially in emerging markets like China.

Developing countries can significantly enhance firm innovation by improving the business environment, including the optimization of administrative and financial systems, reducing transaction costs and ensuring capital supply. Tailored legal frameworks and alternative institutional strategies may also be explored.

This study explicitly emphasizes the governmental role in promoting firm innovation, shedding light on policy formulation and strategic alignment with local administrative policies.

To the best of our knowledge, this paper is the first to explore the relationship between the business environment and firm innovation using World Bank indicators in an emerging market context, providing novel insights into the unique dynamics of legal, financial and administrative sub-environments.