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The purpose of this paper is to investigate whether firms with high environmental disclosure have a low possibility of non-standard audit opinions and audit fees and whether this trend is more obvious after than prior to the Measures for the Disclosure of Environmental Information (Measure) implemented in 2008.

Based on the Measures implemented in 2008, the authors select data for the listed manufacturing firms from 2004 to 2006 (Pre-Measure) and from 2009 to 2011 (Post-Measure) as research samples to investigate the relationships between environmental disclosures, audit opinions and audit fees with difference in difference models. In addition, we also consider the influence of media attention, the polluting industry and internal control on the audit effect of environmental disclosure.

The results show that the level of environmental disclosure is significantly negatively correlated with the possibility of issuing non-standard audit opinions and audit fees after measure is implemented, especially hard environmental information. Further evidence indicates that the auditing effect of environmental disclosures is stronger on firms that receive less media attention, in firms with better internal controls, and in firms belonging to industries with heavy pollution.

In the Chinese setting, a high level of environmental information disclosures can effectively reduce the audit risk and lead to a high possibility of standard audit opinions and low audit fees. This effect is pronounced after issuing Measure. The conclusions suggest that measure and increasing environmental disclosure have an obvious positive audit effect and that firms should be forced or encouraged to disclose more environmental information from the perspective of auditors in China.

Although materializing the benefits of social media substantially depends on sustained user participation, social media service providers are experiencing a decline in the number of users. Despite the relevance of studying and managing discontinuance behaviors, a systematic empirical investigation remains lacking. The present study draws on the idea of a two-factor model and aims to examine the enabler, inhibitor and their antecedents in the context of social media discontinuance.

The proposed theoretical model was empirically validated through an online survey study of 238 social media users in China.

Findings indicated that two negative outcomes of social media use (i.e. social overload and invasion of privacy) induce regret experience and ultimately foster discontinuance intentions. The development of discontinuance intentions was undermined by the level of inertia, which is rooted in social media habit, sunk costs and affective commitment.

This study draws attention to the fundamental difference between continuance and discontinuance behaviors, advances the existing understanding of postadoption behaviors by focusing on discontinuance inhibitors (e.g. inertia) and develops the first two-factor model for social media discontinuance by integrating the regret and status quo bias literature.

The purpose of this study was to explore the relationship between paradoxical leadership and organizational citizenship behaviour (OCB), including the serial mediating role of a paradoxical mindset and personal service orientation, by applying social cognitive theory and planned behaviour theory.

The hypotheses proposed in this study were empirically tested using data from 411 supervisor–subordinate paired samples from six Chinese enterprises at two time points. The bootstrap method was applied using PROCESS macro v 3.3 for SPSS 24.0 software.

The results demonstrate the following relationships: paradoxical leadership positively affects OCB; paradoxical mindset significantly mediates the relationship between paradoxical leadership and OCB; personal service orientation significantly mediates the relationship between paradoxical leadership and OCB; and paradoxical mindset and personal service orientation play serial mediating roles in the relationship between paradoxical leadership and employees' OCB.

The results of this study show that managers' paradoxical leadership behaviours can effectively stimulate employees' OCB, which in turn influence employees' attitudes and behavioural intentions towards conflict.

This study enriches the antecedents of OCB and the consequences of paradoxical leadership. From an attitude and behaviour perspective, this study explores the internal transmission path of the impact of paradoxical leadership on employee behaviour and expands existing research on intermediary mechanisms.

Researchers continue to address the concept of self-disclosure because it is foundational for helping social networking sites (SNS) function and thrive. Nevertheless, the authors' literature review indicates that uncertainty remains around the underlying mechanisms and factors involved in the self-disclosure process. The purpose of this research is to better understand the self-disclosure process from the lens of dual-process theory (DPT). The authors consider both the controlled factors (i.e. self-presentation and reciprocity) and an automatic factor (i.e. social influence to use an SNS) involved in self-disclosure and broaden The authors proposed a model to include the interactive facets of enjoyment.

The proposed model was empirically validated by conducting a survey among users of WeChat Moments in China.

As hypothesized, this research confirms that enjoyment and automatic processing (i.e. social influence to use an SNS) are complementary in the SNS self-disclosure process and enjoyment negatively moderates the positive relationship between controlled factor (i.e. self-presentation) and self-disclosure.

Theoretically, this study offers a new perspective on explaining SNS self-disclosure by adopting DPT. Specifically, this study contributes to the extant SNS research by applying DPT to examine how the controlled factors and the automatic factor shape self-disclosure processes and how enjoyment influences vary across these processes – enriching knowledge about SNS self-disclosure behaviors. Practically, the authors provide important design guidelines to practitioners concerning devising mechanisms to foster more automatic-enjoyable value-added functions to improve SNS users' participation and engagement.

This study aims to systematically review the literature in the fields of liquidity, informational efficiency and default risk. The authors outline the key research streams and provide possible pathways for future research.

The study adopts bibliographic mapping to identify the most influential studies in the research fields of liquidity, informational efficiency and default risk from 1984 to 2021.

The study identifies four key research themes that include efficiency and transparency of markets; corporate yield spreads; market interactions: bonds, stocks and cryptocurrencies; and corporate governance. By assessing publications published from 2018 to 2021, the authors also document seven key emerging research trends: cross markets, managerial learning and corporate governance, state ownership and government subsidies, international evidence, machine learning (FinTech approaches), environmental themes and financial crisis. Drawing on these emerging trends, the authors highlight the opportunities for future research.

Keyword searches have limitations since some studies might be overlooked if they do not match the specified search criteria, even though their relevance to the topic is under investigation. Adopt the R project to expand this review by incorporating more literature from other databases, such as the Scopus database could be a possible solution.

The four key research streams contribute to a comprehensive understanding of liquidity, informational efficiency and default risk. The emerging trends integrate existing knowledge and leave the chance for innovative research to expand the research frontier.

This study fulfills the systematic literature review streams in the fields of liquidity, informational efficiency and default risk, and provides fruitful opportunities for future research.

Electrical capacitance tomography (ECT) and electrical resistance tomography (ERT) are promising techniques for multiphase flow measurement due to their high speed, low cost, non-invasive and visualization features. There are two major difficulties in image reconstruction for ECT and ERT: the “soft-field”effect, and the ill-posedness of the inverse problem, which includes two problems: under-determined problem and the solution is not stable, i.e. is very sensitive to measurement errors and noise. This paper aims to summarize and evaluate various reconstruction algorithms which have been studied and developed in the word for many years and to provide reference for further research and application.

In the past 10 years, various image reconstruction algorithms have been developed to deal with these problems, including in the field of industrial multi-phase flow measurement and biological medical diagnosis.

This paper reviews existing image reconstruction algorithms and the new algorithms proposed by the authors for electrical capacitance tomography and electrical resistance tomography in multi-phase flow measurement and biological medical diagnosis.

The authors systematically summarize and evaluate various reconstruction algorithms which have been studied and developed in the word for many years and to provide valuable reference for practical applications.

Food safety risk brought by environmental pollution seriously threatens human health and affects national economic and social development. In particular, heavy metal pollution and nutrient deficiency have caused regional diseases. Thus, the purpose of this paper is to present a risk early warning method of food safety considering environmental and nutritional factors.

A novel risk early warning modelling method based on the long short-term memory (LSTM) neural network integrating sum product based analytic hierarchy process (AHP-SP) is proposed. The data fuzzification method is adopted to overcome the uncertainty of food safety detection data and the processed data are viewed as the input of the LSTM. The AHP-SP method is used to fuse the risk of detection data and the obtained risk values are viewed as the expected output of the LSTM. Finally, the proposed method is applied on one group of sterilized milk data from a food detection agency in China.

The experimental results show that compared with the back propagation and the radial basis function neural networks, the proposed method has higher accuracy in predicting the development trend of food safety risk. Moreover, the causal factors of the risk can be figured out through the predicted results.

The proposed modelling method can achieve accurate prediction and early warning of food safety risk, and provide decision-making basis for the relevant departments to formulate targeted risk prevention and control measures, thereby avoiding food safety incidents caused by environmental pollution or nutritional deficiency.

This study aims to examine how the interactions between the entrepreneur’s technical and market knowledge and the intra- and extra-industry ties affect resources acquisition.

The authors made a questionnaire from a sample of 300 high-technology companies located in the incubator in Xi’an, of which 165 were usable, and the final response rate was 55 per cent, the authors used optimal scaling regression analyses to analyze the data and test the hypotheses.

There is a positive relationship between the entrepreneurs’ knowledge and the resources acquisition. The effects of the technical knowledge and the market knowledge are contingent on the intra-industry ties and the extra-industry ties in different ways. In particular, an entrepreneur with technical knowledge has an easier access to required resources from the intra-industry ties than extra-industry ties. In contrast, an entrepreneur with market knowledge can obtain more easily the needed resources from the extra-industry ties than the intra-industry ties.

The paper conducted an empirical test of how the interactions between the entrepreneurs’ knowledge and industry ties affect the resources acquisition in the context of China’s emerging economy, which has not been studied in the current literature. This paper provides implications for entrepreneurs with technical and market knowledge in finding the right way to obtain needed resources through their industry ties.

Fake news refers to intentionally fabricated or misleading information designed to deceive the public and manipulate opinions for personal, political or financial gain. Most existing detection methods primarily focus on capturing language features from news content. However, these methods neglect the varying importance of different news entities. Additionally, these methods tend to overlook the auxiliary role of external knowledge, resulting in an incomplete understanding of the entity. To address these issues, this paper aims to propose a Dual-layer Semantic Information Extraction Network with External Knowledge (DSEN-EK) for fake news detection.

This approach is proposed to comprise three parts: Dual-layer Semantic Information Extraction Network, Entity Integration Network with External Knowledge and Classifier. Specifically, Dual-layer Semantic Information Extraction Network is designed to enhance relationships between entities and the influence of important entity representations. The Entity Integration Network with External Knowledge is proposed to extract entity descriptions from external knowledge bases.

The DSEN-EK model performs well on the Liar, Constraint, Twitter15 and Twitter16 data sets, achieving accuracy of 98.02%, 94.61%, 90.09% and 93.65%, respectively. These results highlight its effectiveness in detecting fake news across different types of content.

The Dual-layer Semantic Information Extraction Network is proposed to capture the relationships between entities and enhance the continuous semantic information of the news. The Entity Integration Network with External Knowledge is designed to enrich entity descriptions, leading to a more comprehensive capture of semantic details.

This paper aims to conduct research on the role of vertical interlocks of executives in blocking adverse loops between research and development (R&D) investment and the cost of equity capital and explore the action path of vertical interlocks of executives. This paper also analyzes the differences in the effect of vertical interlocks of chairman, vertical interlocks of chief executive officer (CEO) and vertical interlocks of CEO duality.

This paper uses 28,078 firm-year samples from Chinese A-share listed companies to study the impact of R&D investment on the cost of equity capital using univariate group analysis and multiple regression methods. This paper analyzes the role of vertical interlocks of executives in reducing the positive impact of R&D investment on the cost of equity capital by constructing interaction variables, by using group testing method to analyze the differences in the vertical interlocks of executives. This study also uses propensity score matching and instrumental variables to conduct robustness tests.

The vertical interlocks of executives can block adverse loops between R&D investment and the cost of equity capital. The role of executive vertical interlocks is more prominent in non-state-owned firms, mainly exerting the resource effect that supports the innovation of non-state-owned firms, including the information resource effect and the financial resource effect. Through heterogeneity analysis, this paper discovered that the role of vertical interlocks of chairman is greater than that of the CEO and the CEO duality.

Based on the perspective of the correlation effect generated by vertical interlocks of executives, this paper analyzes the path of promoting corporate innovation. This provides new empirical evidence for studying the collaborative governance effect of vertical interlocks of executives “supervision effect, financial resource effect and information resource effect.” This study provides useful insights for regulatory authorities to regulate and guide development of the vertical interlocks of executives.