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Social media data from financial websites contain information related to enterprise credit risk. Mining valuable new features in social media data helps to improve prediction performance. This paper proposes a credit risk prediction framework that integrates social media information to improve listed enterprise credit risk prediction in the supply chain.

The prediction framework includes four stages. First, social media information is obtained through web crawler technology. Second, text sentiment in social media information is mined through natural language processing. Third, text sentiment features are constructed. Finally, the new features are integrated with traditional features as input for models for credit risk prediction. This paper takes Chinese pharmaceutical enterprises as an example to test the prediction framework and obtain relevant management enlightenment.

The prediction framework can improve enterprise credit risk prediction performance. The prediction performance of text sentiment features in social media data is better than that of most traditional features. The time-weighted text sentiment feature has the best prediction performance in mining social media information.

The prediction framework is helpful for the credit decision-making of credit departments and the policy regulation of regulatory departments and is conducive to the sustainable development of enterprises.

The prediction framework can effectively mine social media information and obtain an excellent prediction effect of listed enterprise credit risk in the supply chain.

The high occurrence of procurement fraud requires the management of an enterprise, the risk manager of the enterprise and the internal auditor to address procurement fraud risks effectively within the enterprise risk management concept. The purpose of the article is to explain a procurement fraud risk management process which will serve as a comprehensive framework for enterprise risk managers and for internal auditors to limit the enterprise’s exposure to procurement fraud as far as possible. The study by Venter (2005) on which the article is based proposes a procurement fraud risk matrix which can be used to manage fraud risks within the procurement function efficiently. This matrix is based on the Committee of Supporting Organizations of the Treadway Commission’s (COSO’s) Enterprise Risk Management ‐Integrated Framework which is specifically applied to address the procurement fraud risk problem.

The aim of this study is to analyze the influence mechanism of real estate enterprises' status on debt default risk and explore the heterogeneity effect of the characteristics of enterprises.

Against the background of the “three red lines” regulation of the financing of real estate enterprises and the COVID-19 pandemic, the authors select 123 real estate enterprises listed on China's Shanghai and Shenzhen A-shares markets from the first quarter of 2021 to the second quarter of 2022 as a research sample. The social network analysis method and Z-score financial risk early warning model are used to measure real estate enterprises' status and debt default risk. The authors construct a panel regression model to analyze how the status of real estate enterprises influences their debt default risk.

The results show that the status of real estate enterprises negatively and significantly affects their debt default risk. Economic policy uncertainty and financing constraints play negative moderating and mediating roles, respectively. Further research has found that the effect of real estate enterprises' status on debt default risk is characterized by heterogeneity in equity characteristics, i.e. it is significant in the sample of nonstate-owned enterprises but not in the sample of state-owned enterprises.

It is helpful for real estate enterprises to attach importance to the value of social networks, and the authors provide policy suggestions for real estate enterprises to constantly improve their risk management systems.

Using economic policy uncertainty as the moderating variable and financing constraints as the mediating variable, the authors analyze how the status of real estate enterprises influences debt default risk, which contributes to a better understanding of the formation of the debt default risk of real estate enterprises.

Purpose – This article aims to focus on raising awareness of the limitations of traditional “enterprise‐centric” views of enterprise risk management that ignore the risks that are inherited from key business and supply chain partners. In essence, enterprise systems implementations have allowed organizations to couple their operations more tightly with other business partners, particularly in the area of supply chain management, and in the process enterprise systems applications are redefining the boundaries of the entity in terms of risk management concerns and the scope of financial audits. Design/methodology/approach – The prior literature that has begun to explore aspects of assessing key risk components in these relationships is reviewed with an eye to highlighting the limitations of what is understood about risk in interorganizational relationships. This analysis of the prior research establishes the basis for the logical formation of a framework for future enterprise risk management research in the area of e‐commerce relationships. Findings – Conclusions focus on the overall framework of risks that should be considered when interorganizational relationships are critical to an enterprise's operations and advocate an “extended‐enterprise” view of enterprise risk management. Research limitations/implications – The framework introduced in this paper provides guidance for future research in the area of interorganizational systems control and risk assessment. Practical implications – The framework further highlights areas of risk that auditors and corporate risk managers should consider in assessing the risk inherited through interorganizational relationships. Originality/value – The paper highlights the need to shift from an enterprise‐centric view of risk management to an extended‐enterprise risk management view.

Tax risks are common in China but often ignored by enterprises. Determining how to measure tax risks and effectively identify and control influencing factors is the key to the sustainable development of enterprises. This study aims to explore the key factors affecting corporate tax risks and analyze influencing factors from external and internal perspectives.

After selecting a data set comprising 11,503 firm-year observations of Chinese firms in the Shanghai and Shenzhen Stock Exchanges from 2008–2017, this study applied a panel regression model to identify the factors’ impact.

The results indicate that the more standardized the institutional environment and stronger the tax supervision, the lower the tax risks. Taking into account the internal factors of a firm, private companies with political connections have lower tax risks than those without.

This study enriches the literature on the factors affecting tax risks. The conclusion provides significant insights for enterprises to effectively control tax risks and maintain sustainability. The research findings also provide a new perspective for the government to guard against corporate risks and maintain the stable development of the economy.

The quantitative understanding of the safe input management practices of vegetable producers is essential for both food safety and environmental protection. The purpose of this study is to investigate the current status of safe production in vegetable enterprises and examine the key risk factors affecting the safe production of vegetables from the perspective of agricultural inputs.

Based on the theory of risk analysis, a framework of safe vegetable production risk analysis is constructed from the perspective of production input behaviour. Based on 202 valid questionnaires in Beijing, China, this paper identifies direct risks in input management through statistical descriptive analysis; determines weights through an expert elicitation process and calculates weighted safety values accordingly; and finally uses a categorical regression model to explore the indirect risks affecting corporate safety production.

The results show that direct risk factors include seed treatment risk, pesticide and fertilizer use criteria risk, pesticide and fertilizer operation risk, and pesticide application object risk. The production safety value of Beijing's enterprises is found to be high in the north and south regions, and low in the central region. Finally, some indirect risk factors, namely the cognition of agricultural product safety laws, the cognition of pesticide safety intervals, the cognition of prohibited pesticides and the possession of brands, are found to have positive and significant impacts on the safe production behaviour of enterprises.

These findings provide entry points for interventions aimed at reducing dependence on pesticides and fertilizers and promoting input management for safe vegetable production in enterprises, thus avoiding vegetable safety incidents due to improper practices in the production chain.

This study investigates the impact of economic policy uncertainty on corporation innovation in innovative cities. The study sheds light on different results from the previous literature by testing the moderator effects of entrepreneurial risk appetite on such impact.

A static panel estimator is applied to a Chinese sample of 416 firm-year observations from 2010 to 2019. This paper uses regression model to test the impact of uncertainty on enterprise innovation in innovative cities, and to test the regulatory role of entrepreneurial risk appetite. For a series of robustness analysis conducted by the author to deal with endogeneity, the results are robust.

The author finds reliable evidence that the economic policy uncertainty can promote corporations to invest more in R&D in innovative cities. In addition, the role of the entrepreneurial initiative is significant, and there is a positive moderating effect of entrepreneurial risk appetite between policy uncertainty and corporation innovation.

From a practical point of view, this study examines the impact of economic policy uncertainty on corporation innovation in innovative cities for the first time. It emphasizes the role of entrepreneurial risk-taking in the development of corporation innovation in Shenzhen, an innovative city. This research is of great significance to the formulation of government policies and the innovative choice of entrepreneurs. In addition, the research shows that the entrepreneurial risk appetite in innovative cities can have a positive impact on enterprise innovation. Therefore, when formulating policies, the government should take the subjective factors of entrepreneurs into account and support enterprises with innovation potential. The evidence of this study also helps entrepreneurs make innovative decisions and enhance their confidence in enterprise development.

By studying the impact of economic policy uncertainty on enterprise innovation under the regulation of enterprise risk appetite, this study shows the subjective and positive role of entrepreneurs in risk grasp in innovative cities for the first time. In addition, it fills the gap of the impact of policy uncertainty on innovative urban enterprises. In fact, although it is traditionally believed that economic policy uncertainty has a negative impact on enterprise innovation, the sensitive findings of this study reveal completely different results from previous studies.

The industrial chain network is a complex system consisted by many members of the enterprise, and the complex relationship and the interaction with the external environment among the node enterprises and the existence of various uncertainty all increase the risk of the industry chain. The risk of some individual node enterprises will not only affect the normal operation but also spread the risk to other enterprises by network relationship because of their own mismanagement or deterioration of the external environment. The purpose of this paper is to make an attempt to establish the risk spread model of the industrial chain based on complex networks.

By improving Lobos disaster diffuse model, the paper introduces two indexes: the risk spread range and the risk propagation velocity to measure of industrial chain risk communication effects, and design algorithm for industrial chain complex network structure. The risk spread range can be used to measure the coverage of the risk communication influence produced by the propagation enterprises in the industry chain and to analyse the risk spread breadth on the industrial chain network .The speed index of risk communication represents the total numbers of infection enterprises in unit simulation time.

This paper proposes the universal industrial chain risk propagation model.

Through proposed algorithm constructs industrial chain network, and enterprise class divide, the importance of the product chain enterprises in the industry chain is strengthened.

There is a relatively low risk management (RM) level and maturity in China’s state-owned construction enterprises (CSCEs). The purpose of this paper is to find the main factors impacting RM in practice to promote rapid, sound and sustained development in CSCEs.

There are a few state-owned CSCEs in China. Most enterprises know little about RM. Because of the limited number of RM departments in these enterprises, 200 questionnaires were sent to the enterprises to investigate the RM strategies employed by them. The research is quantitative and used a questionnaire survey to determine the important factors influencing RM practice. The collected data were analyzed with the Statistical Package for the Social Sciences to identify the most important factors affecting RM as well as the extent of influence of these factors, in order to facilitate further research.

The survey revealed the top eight factors (i.e. leaders’ support, personnel’s responsibility, comprehensiveness of identification, costs and benefits, risk appetite, understanding of language, frequency of training and performance management) that highly impact RM in CSCEs and the extent to which these factors impact RM. The data reveal that the average RM level is low. Some methods have been recommended to improve RM.

The research lays the foundation for further RM development in CSCEs. The low RM level in CSCEs should encourage researchers to find better ways to improve RM. Some factors in the research will function as valuable guides for China’s private and public-private partnership enterprises.

A quantitative analysis methodology for RM has been developed for CSCEs that can reflect their RM level. In addition, the degree of impact of key factors on RM has been shown. The results can act as a reference to improve RM quantitatively, making the RM system more explicit in dealing with risks more accurately and instructively.

Structural RM research is utilized to evaluate RM in CSCEs by following an empirical method. With the continuous improvement in RM, CSCEs can cooperate well with construction enterprises of other countries for infrastructure projects and gain more benefits.

The purpose of this paper is to explore whether financial risk management (FRM) can improve enterprise value in China's current economic environment.

A theoretical model is constructed which decomposes firms by different combinations expressed by cash flow and risk scale. Then, regression testing is conducted, taking the non‐ferrous metal industry in Shanghai and Shenzhen Stock Exchanges (2002‐2008) as the sample, and using the fixed effects model.

The results support the hypothesis that risk management can raise enterprise value. It is also found that risk management behavior has different representations among firms with different characteristics.

This paper has modified Boyer's mean‐variance model and then testified to the effectiveness of FRM. It also explores the influence of enterprise characteristics on the efficiency of risk management, providing some theoretic support for China's enterprises, which could borrow ideas from successful experience.