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This study delves into the nuanced relationship between financial constraints, ownership structures (state-owned and foreign) and innovation engagement within China’s A-share market, aiming to uncover how these dynamics vary across different industries and regional contexts.

By retrieving data from various datasets in China (2010–2022), this study analyzed the effectiveness of each variable, employing various dimensions to reflect innovation engagement among Chinese listed companies. Meanwhile, for the measurement of financial constraints, this study tested all four typical ones and opted for the KZ Index, as it is the most suitable for China’s A-share market. Then, by fixing the industry and year effects, the study examined the main and moderating effects. At last, in order to address endogeneity issues and capture the dynamic nature of innovation activities, this study follow the suggestion of Khatib (2024) and employed the two-step system Generalized Method of Moments (GMM) estimation.

The results demonstrate that while the government has introduced many policies to promote innovation, state-owned ownership does not consistently enhance innovation engagement as expected, especially when firms are in financial dilemma. Particularly, in Hi-tech industries, foreign ownership demonstrates greater interest and confidence in the innovation capabilities of China’s A-share market. Findings also reveal significant regional heterogeneity in the moderating role of ownership structures. While state-owned and foreign ownerships have a buffering effect against financial constraints in the eastern and western regions, but this effect is notably different in the middle part, even though it is China’s political heartland.

The findings offer a different insight for policymakers and corporate strategists, suggesting that targeted financial and regulatory policies that leverage specific ownership structures can foster innovation in different ways, particularly in financially constrained environments. However, how to stimulate innovation vitality in the middle part of China still requires further research.

Using bibliometric techniques, the author analyzes a dataset of 276 articles on cross-border mergers and acquisitions (CBMAs) published in 13 management and international business journals. The author assesses the scientific impact and visualizes the intellectual landscape of research on CBMAs by analyzing publication and citation data and interconnections between publications. First, the author assesses annual publication trends and identifies highly cited articles and productive journals in the dataset that have significantly contributed to our understanding of CBMAs. Second, the author identifies main themes in recent research on CBMAs by focusing on frequently used keywords in publications. Third, the author identifies clusters of related research and explores their interrelationships to outline emerging trends, new perspectives, and directions for future research on CBMAs. Overall, this chapter contributes to the understanding of CBMAs by documenting the progress made to date and providing important insights for future research.

The aim of this research paper is to analyze the connection between ESG performance and financial performance within the real estate sector. By focusing on ESG ratings and pillar scores as proxies for ESG performance, the study investigates how these factors impact both profitability and market indicators.

With data sourced from over 680 publicly listed real estate companies, the research employs a fixed effects regression model to analyze the findings. By utilizing this method, the study can assess the impact of governance, environmental and social factors on both the accounting and market performance of real estate companies.

The outcomes of this study underscore a link between sustainability, particularly environmental aspects and financial performance. However, the study also reveals a contrasting result: governance factors are associated with adverse financial outcomes. Nevertheless, it is important to highlight the limitations as the results present a mixed picture with limited significant findings.

Companies should prioritize improvements in environment to boost profitability, while they should carefully consider the costs and benefits associated with enhancing their governance structure.

By focusing on this industry and adopting a global perspective, the study addresses a gap in the literature. The research’s innovative approach to utilizing ESG ratings and pillar scores as proxies for ESG performance enhances its originality. Furthermore, the research’s identification of the differing impacts of environmental and governance factors on financial outcomes add novel perspectives to the discourse.

In order to improve the efficiency and reliability of simulation analysis for composite riveting structures in engineering products, a comparative study was conducted on different forms of riveting simulation methods.

Five different rivent simulation models were established using the finite element method, including rigid element CE, flexible element Rbe3 and beam element, and their results were future compared and analyzed.

Under the given technical parameters, the simulation method of Rbe3 (with holes) + beam can meet the analysis requirements of complex engineering products in terms of the rationality of rivet load distribution, calculation error and relatively efficient modeling.

This study proposes a simulation method for the riveting structure of carbon fiber composite materials for engineering applications. This method can satisfy the simulation analysis requirements of transportation vehicles in terms of modeling time, computational efficiency and accuracy. The research can provide technical support for the riveting process and mechanical analysis between carbon fiber composite components in transportation products.

Based on the attention-based view (ABV), this study examines the mechanism of external pressure and internal managerial interpretation affecting the promotion of green entrepreneurial orientation (GEO) of agricultural enterprises.

Based on data collected from 208 agricultural enterprises in China, the conceptual model was tested by using hierarchical regression.

The results show that managerial interpretation can affect the promotion of GEO. Command and control regulation, market-based regulation and green market pressure are important external pressures that affect the promotion of GEO. In addition, managerial interpretation mediates the relationship between command and control regulation and GEO, market-based regulation and GEO, as well as green market pressure and GEO.

This study proposes a key path for promoting the adoption and implementation of GEO by agricultural enterprises. The research results provide experience for emerging and developing countries to promote the GEO of agricultural enterprises, which is helpful to alleviate the environmental problems caused by the development of agricultural enterprises.

For the first time, this study introduced the ABV into the research of GEO. The research results enrich the theoretical perspective of GEO and expand the research field of the ABV. In addition, this study fills the research gap that existing research has not paid enough attention to the internal driving factors of GEO and opens the black box between the external pressure and GEO.

This paper aims to clarify the impact of information asymmetry on users' payment rates and examine the role of perceived uncertainty (PU) and acceptable price (AP) in the relationship between information asymmetry and users' payment rates.

To test the influences of information asymmetry on users' payment rates, this paper collects 18,489 transaction data from the Chinese knowledge payment platform Zhihu with a Python crawler. This paper constructs a mediation model to define the relationship between information asymmetry and users' payment rates by introducing PU and AP as the mediators.

Information asymmetry negatively affects users' payment rates. In addition, PU and AP mediate the information asymmetry in users' payment rates bond.

This study only explores the mediators of the information asymmetry users’ payment rates bond, ignoring the effect of potential moderators, which would be an important direction for future research.

The findings of this paper suggest that information communication is essential in knowledge market transactions. Knowledge providers, as well as knowledge platforms, should enhance information exchange with consumers in order to increase product sales.

This paper provides a new perspective for understanding how information asymmetry affects users' payment rates and helps to guide suppliers to improve product quality. The research framework of this paper is universal to a certain extent.

This paper is one of the first to propose using PU and AP to construct a mediation model to study the information asymmetry between users' payment rates relationship. It provides a new perspective for understanding the channel of information asymmetry in customer behavior.

In the brain imaging based on electrical impedance tomography, it is sometimes not able to attach 16 electrodes due to space restriction caused by craniotomy. As a result of this, the number of boundary measurements decreases, and spatial resolution of reconstructed conductivity distribution is reduced. The purpose of this study is to enhance reconstruction quality in cases of limited measurement.

A new data expansion method based on the shallow convolutional neural network is proposed. An eight-electrode model is built from which fewer boundary measurements can be obtained. To improve the imaging quality, shallow convolutional neural network is constructed which maps limited voltage data of the 8-electrode model to expanded voltage data of a quasi-16-electrode model. The predicted data is compared with the quasi-16-electrode data. Besides, image reconstruction based on L1 regularization method is conducted.

The results show that the predicted data generally coincides with the quasi-16-electrode data. It is found that images reconstructed with the data of eight-electrode model are the poorest. Nevertheless, imaging results when the limited data is expanded by the proposed method show large improvement, and there is a minor difference with the images recovered with the quasi-16-electrode data. Also, the impact of noise is studied, which shows that the proposed method is robust to noise.

To enhance reconstruction quality in the case of limited measurement, a new data expansion method based on the shallow convolutional neural network is proposed. Both simulation work and phantom experiments have demonstrated that high-quality images of cerebral hemorrhage and cerebral ischemia can be obtained when the limited measurement is expanded by the proposed method.

In traditional Chinese medicine (TCM), the mechanism of disease (MD) constitutes an essential element of syndrome differentiation and treatment, elucidating the mechanisms underlying the occurrence, progression, alterations and outcomes of diseases. However, there is a dearth of research in the field of intelligent diagnosis concerning the analysis of MD.

In this paper, we propose a supervised Latent Dirichlet Allocation (LDA) topic model, termed MD-LDA, which elucidates the process of MDs identification. We leverage the label information inherent in the data as prior knowledge and incorporate it into the model’s training. Additionally, we devise two parallel parameter estimation algorithms for efficient training. Furthermore, we introduce a benchmark MD identification dataset, named TMD, for training MD-LDA. Finally, we validate the performance of MD-LDA through comprehensive experiments.

The results show that MD-LDA is effective and efficient. Moreover, MD-LDA outperforms the state-of-the-art topic models on perplexity, Kullback–Leibler (KL) and classification performance.

The proposed MD-LDA can be applied for the MD discovery and analysis of TCM clinical diagnosis, so as to improve the interpretability and reliability of intelligent diagnosis and treatment.

By adopting learning theory and a guanxi perspective, this study aims to investigate the effects of interpersonal guanxi (interpersonal networks or connections) and relationship learning on companies’ business performance when operating in a large emerging market.

Using a sample of 294 sales managers and salespeople in the Chinese hotel sector, the authors empirically test the authors' arguments through a structural equation modeling (SEM) approach.

The authors' findings indicate that strong interpersonal guanxi tends to generate more positive business performance. Furthermore, the authors find that relationship learning plays a mediating role in the association between interpersonal guanxi and hotel companies’ business performance in a Chinese context. Finally, the authors empirically explore the moderating effect of inter-firm dependence on the contribution of interpersonal guanxi to relationship learning. Findings demonstrate that this effect varies significantly based on inter-firm dependence, with interpersonal guanxi exhibiting a greater positive impact if such dependence is high.

This study enriches our understanding of interpersonal guanxi and of how companies can enhance the companies' business performance in an emerging market context.

This paper aims to investigate how digital orientation affects digital process innovation from the dual perspectives of knowledge and capability. It also stresses the mediating effects of digital knowledge creation and strategic flexibility on this relationship, as well as the moderating effect of strategic flexibility on the relationship between digital knowledge creation and digital process innovation.

This paper adopted knowledge- and capability-based views to develop the theoretical model. A total of 193 samples from China were collected to test the model and hypotheses by the partial least squares structural equation modeling method.

The results indicate that digital orientation promotes knowledge creation and strategic flexibility respectively, which in turn facilitates digital process innovation. Also, the effect of digital knowledge creation on digital process innovation is moderated by strategic flexibility.

This study adopts the dual perspectives of knowledge and capability to deepen the relationship between digital orientation and digital process innovation by introducing digital knowledge creation and strategic flexibility as the crucial links, which responds to the call for attaching importance to digital process innovation.