This study develops an improved failure mode and effects analysis (FMEA) method using two-dimensional uncertain linguistic variables (2DULVs) and alternative queuing method (AQM). The 2DULVs are employed to represent the evaluations provided by FMEA team members on the weights of risk factors and the risk of failure modes in the form of pairwise comparisons. The two-dimensional uncertain linguistic best worst method (2DUL-BWM) is used to derive the weights of risk factors. The two-dimensional uncertain linguistic AQM (2DUL-AQM) is proposed for determining the risk ranking of the identified failure modes. Finally, the maintenance of a water treatment plant is presented as an example to demonstrate the applicability and effectiveness of the proposed FMEA method. By comparing its performance with those of other existing methods, the proposed FMEA is shown to be more advantageous in ranking the risk of failure modes.

Nowadays robots have been commonly adopted in various manufacturing industries to improve product quality and productivity. The selection of the best robot to suit a specific production setting is a difficult decision making task for manufacturers because of the increase in complexity and number of robot systems. In this paper, we explore two key issues of robot evaluation and selection: the representation of decision makers’ diversified assessments and the determination of the ranking of available robots. Specifically, a decision support model which utilizes cloud model and TODIM (an acronym in Portuguese of interactive and multiple criteria decision making) method is developed for the purpose of handling robot selection problems with hesitant linguistic information. Besides, we use an entropy-based combination weighting technique to estimate the weights of evaluation criteria. Finally, we illustrate the proposed cloud TODIM approach with a robot selection example for an automobile manufacturer, and further validate its effectiveness and benefits via a comparative analysis. The results show that the proposed robot selection model has some unique advantages, which is more realistic and flexible for robot selection under a complex and uncertain environment.

ESG information disclosure is an essential aspect of corporate ESG responsibility and has gained significant attention in the context of ecological civilization development within the socialist market economy. However, in China’s early stage of ESG development, challenges such as ESG rating discrepancies, “greenwashing”, and corporate “cleansing” accompany ESG information disclosure. This study aims to investigate the impact of corporate ESG information disclosure on audit fees using a sample of non-financial A-share listed companies in China from 2011 to 2020. Drawing on the “deep pocket” theory, risk premium theory, and cost-benefit principle, the research examines the relationship between ESG information disclosure and audit fees. The findings reveal that approximately one-third of Chinese enterprises disclose ESG information, and substantial variation exists in the disclosure scores among the disclosed firms. The empirical analysis further demonstrates that firms disclosing ESG information tend to face higher audit fees, with higher ESG disclosure scores associated with increased audit fees. Moreover, an increase in the disclosure score of any ESG dimension (environment, social responsibility, and corporate governance) leads to higher audit fees. The study also identifies operational risk as a mediating factor in the relationship between ESG disclosure and audit fees. Additionally, media attention can dampen the positive effect of ESG disclosure scores on audit fees. Furthermore, the impact of ESG disclosure scores on audit fees is more pronounced in firms that voluntarily disclose ESG information before the implementation of the new Environmental Protection Law. These findings contribute to the literature and provide theoretical insights for governmental and regulatory decision-making, corporate managers, auditors, and ESG investors in China.

In order to help enterprises to achieve high-quality development and improve the capital market regulatory policies by supporting with more factual basis from China, this paper conducts research on clarifying impact mechanism of digital transformation on M&A efficiency of listed companies. Taking the mergers and acquisitions of listed companies from 2007 to 2021 as a research sample, the influence mechanism of the digital transformation degree of companies on their M&A efficiency was studied. The research results show that the digital transformation of listed companies will improve their M&A efficiency. Digital transformation will reduce the degree of mispricing stocks of M&A companies, curb conflicts between managers and agents of M&A companies, and improve their M&A efficiency. Further research finds that the promotion effect of digital transformation on M&A efficiency is more significant in non-state-owned companies, with a higher degree of financing constraint and high analyst attention. In the future, regulatory authorities should actively promote the digital transformation of listed companies, curb mispricing and management agency problems in the capital market with digital governance, and improve the efficiency of mergers and acquisitions in the capital market. This paper not only provides a more factual basis on concrete case from China but also enriches the related empirical analysis on corporate digital transformation and M&A efficiency.

The sex ratio at birth in China exhibits a major occurrence of “missing women” due to the high son preference in Chinese culture. Clearly, the large gender discrepancy in China can be explained not only by ethical, moral, or social fairness theories but also by the economic benefits of women's particular abilities, experiences, and talents. This article examines the influence of female chief financial officers (CFOs) on information disclosure violations in order to highlight women's positive contributions. Our data imply that having a female CFO can dramatically lower the number of companies that fail to disclose information. The results are strong after controlling endogeneity with propensity score matching, Heckman's two-stage self-selection model, and CFO change, as well as controlling the gender of the chairman and chief executive officer, utilizing different study periods, and using exogenous shock. We further examined the moderate effects of CFO power and external monitoring, and we found that CFO power magnifies the negative effect of female CFO on violations; the more the power, the more the negative effect of female CFO on violations. We also found that when the firm has effective external monitoring, there are fewer future infractions of information disclosure.

Based on the blended teaching of the rain classroom, it can not only utilize the high-quality rain classroom resource, but also meet the needs of students' differentiation and individualization, and make up for the shortcomings of traditional teaching. The college English blended teaching reform based on the rain classroom is on the basis of the data...