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The traditional failure mode and effect analysis (FMEA) has some limitations, such as the neglect of relevant historical data, subjective use of rating numbering and the less rationality and accuracy of the Risk Priority Number. The current study proposes a machine learning–enhanced FMEA (ML-FMEA) method based on a popular machine learning tool, Waikato environment for knowledge analysis (WEKA).

This work uses the collected FMEA historical data to predict the probability of component/product failure risk by machine learning based on different commonly used classifiers. To compare the correct classification rate of ML-FMEA based on different classifiers, the 10-fold cross-validation is employed. Moreover, the prediction error is estimated by repeated experiments with different random seeds under varying initialization settings. Finally, the case of the submersible pump in Bhattacharjee et al. (2020) is utilized to test the performance of the proposed method.

The results show that ML-FMEA, based on most of the commonly used classifiers, outperforms the Bhattacharjee model. For example, the ML-FMEA based on Random Committee improves the correct classification rate from 77.47 to 90.09 per cent and area under the curve of receiver operating characteristic curve (ROC) from 80.9 to 91.8 per cent, respectively.

The proposed method not only enables the decision-maker to use the historical failure data and predict the probability of the risk of failure but also may pave a new way for the application of machine learning techniques in FMEA.

This study aims to identify the intellectual structure of expanded audit reporting (EAR), offers a quantitative summation of prominent themes, contributors and knowledge gaps and provides suggestions for further research.

This research uses various bibliometric techniques, including co-word and co-citation analysis for EAR science mapping, based on 123 papers from Scopus Database between 1991 and 2022.

The results show EAR research is focused on Audit Quality; Auditor Liability and Litigation; Communicative Value and Readability; Audit Fees; and Disclosure. Regarding EAR research, Brasel et al. (2016), article is the most cited paper, Bédard J. is the most cited author, Laval University is the most influential university, The Accounting Review is the most cited journal and USA is the leading country. Furthermore, the results show that in common law countries, in which shareholder rights and litigation risk is high, topics such as disclosure quality and audit litigation have been addressed more; and in civil legal system countries, which usually favor stakeholders’ rights, topics of gender diversity or corporate governance have been more studied.

This research has practical implications for standard setters and regulators, who can identify important, overlooked and emerging issues and consider them in future policies and standards.

This paper contributes to the literature by providing a more objective and comprehensive status of the accounting research on EAR, identifying the gaps in the literature and proposing a direction for future research to continue the discussion on the value-relevance of EAR to achieve more transparency and less audit expectation gap.

The purpose of this paper is to investigate whether audit committee characteristics, in particular audit committee size, audit committee activity and audit committee gender diversity, are associated with financial performance in Egyptian banks. The second purpose of this paper is to explore the moderating role of board gender diversity on the relationship between audit committee characteristics and financial performance.

A multiple regression analysis is used to estimate the moderating role of board gender diversity on the relationship between audit committee characteristics and financial performance of a sample of Egyptian banks during the period between 2018 and 2022.

The results indicate that audit committee size has a negative and insignificant effect impact on return on assets (ROA) and return on equity (ROE), respectively. The results also indicate that the audit committee gender diversity has a significant positive impact on ROA and ROE, respectively. Regarding audit committee activity, the number of board meetings has a negative and insignificant effect on ROA and ROE, respectively. Regarding gender diversity as a moderating variable, in general there is a positive effect of gender diversity on the relationship between audit committee characteristics and financial performance.

The study was limited to 20 banks in one country, but it sets the tone for future empirical research on this subject matter. The study also relied on one moderating variable, which is board gender diversity. This study provides an avenue for future research in the area of corporate governance and financial performance in other emerging countries, especially other African countries.

This study provides useful insights for managers and policymakers to better understand which audit committee characteristics can best encourage a company to improve financial performance. Furthermore, regulators should ensure that banks strictly adhere to corporate governance principles to build a strong banking industry capable of achieving economic development.

Banks will benefit equally from valuable qualities across demographic groupings in society by having females on the audit committee and appropriate audit committee meetings. Additionally, if audit committee members are correctly selected, banks with more females in audit committee and suitable audit committee meetings can successfully contribute to strengthening financial performance and social welfare of diverse segments of society. A culture of good banking governance must emerge to improve bank financial stability and, as a result, greater stability and economic growth.

To the best of the authors’ knowledge, the study is, perhaps, the first to examine the moderating role of board gender diversity on the relationship between audit committee characteristics and financial performance in Egyptian banks. This study adds to the literature by investigating such an issue in a developing economy that operates in a different context than those in developed countries.

Inventory models are quantitative ways of calculating low-cost operating systems. These models can be either deterministic or stochastic. A deterministic model hypothesizes variable quantities like demand and lead time, as certain. However, various types of research have revealed that the value of demand and lead time is still ambiguous and vary unanimously. The main purpose of this research piece is to reduce the uncertainties in such a dynamic environment of Industry 4.0.

The current study tackles the multiperiod single-item inventory lot-size problem with varying demands. The three lot sizing policies – Lot for Lot, Silver–Meal heuristic and Wagner–Whitin algorithm – are reviewed and analyzed. The suggested machine learning (ML)–based technique implies the criteria, when and which of these inventory models (with varying demands and safety stock) are best fit (or suitable) for economical production.

When demand surpasses a predicted value, variance in demand comes into the picture. So the current work considers these things and formulates the proper lot size, which can fix this dynamic situation. To deduce sufficient lot size, all three considered stochastic models are explored exclusively, as per respective protocols, and have been analyzed collectively through suitable regression analysis. Further, the ML-based Classification And Regression Tree (CART) algorithm is used strategically to predict which model would be economical (or have the least inventory cost) with continuously varying demand and other inventory attributes.

The ML-based CART algorithm has rarely been seen to provide logical assistance to inventory practitioners in making wise-decision, while selecting inventory control models in dynamic batch-type production systems.

This study aims to examine the mediating effects of corporate governance mechanisms like the board of directors on the association between disruptive technology adoption by audit clients and the risk of material misstatements, including inherent risk and control risk. In particular, the authors study the mediating effects of board characteristics such as board size, independence and gender diversity.

Based on a sample of 100 audit clients listed on the FTSE 100 from 2015 to 2021, this study uses structural equation modelling to test the research objectives.

The findings indicate a significant and negative association between disruptive technology adoption by audit clients and inherent risk. However, there is no significant evidence observed for control risk. The utilisation of disruptive technology by the audit client has a significant impact on the board characteristics, resulting in an increase in board size, greater independence and gender diversity. The authors also find strong evidence that board independence mediates the association between disruptive technology usage and both inherent risk and control risk. In addition, board size and gender exhibit distinct and differential mediating effects on the association and across the two types of risks.

The study reveals that the significant role of using disruptive technology by audit clients in reducing the risk of material misstatements is closely associated with the board of directors, which makes audit clients place greater emphasis on the construction of effective corporate governance.

This study offers essential primary evidence that can assist policymakers and standard setters in formulating guidance and recommendations for board size, independence and gender quotas, ensuring the enhancement of effective governance and supporting the future of audit within the next generation of digital services.

With respect to relevant stakeholders, it is imperative for audit clients to recognise that corporate governance represents a fundamental means of addressing the ramifications of applying disruptive technology, particularly as they pertain to inherent and control risks within the audit client.

This study contributes to the existing literature by investigating the joint impact of corporate governance and the utilisation of disruptive technology by audit clients on inherent risk and control risk, which has not been investigated by previous research.

With the growing concern of various sectors of society regarding environmental issues and the promotion of sustainable development, green technology innovation is generally considered to be conducive to the long-term development of enterprises. However, because of the existence of agency problems, managers may have shortsighted behaviors. Then how will managers' shortsighted behaviors affect enterprises' green technology innovation?

This paper uses machine learning-based text analysis methods to construct a manager myopia index based on the data from A-share listed companies on the Shanghai and Shenzhen Stock Exchanges from 2015 to 2020. We examine the impact of manager myopia on green technology innovation in companies.

Our study finds that manager myopia significantly inhibits green technology innovation in companies. However, when multiple large shareholders coexist and the proportion of institutional investors' holdings is high, it can alleviate the inhibitory effect of manager myopia on green innovation. Heterogeneity tests show that the impact of manager myopia on green technology innovation is relatively significant in non-state-owned and manufacturing companies, as well as in the electricity industry. Robustness tests demonstrate that our conclusions remain valid after using propensity score matching to eliminate endogeneity problems.

From the perspective of corporate governance, this paper incorporates managers' shortsightedness, multiple large shareholders and institutional investors' shareholding ratios into the same logical framework, analyzes their internal mechanisms, helps improve corporate governance, enhances green innovation capabilities and has strong implications for the implementation of national innovation-driven development strategies and the achievement of “carbon peak” and “carbon neutrality” targets.

This study examines the relationship between green intellectual capital (GIC) and competitive advantage (CA) and proposes the moderating role of corporate philanthropy types (cash, in-kind and both) during the COVID-19 pandemic. In particular, this study investigates the types of corporate philanthropy, strengthening the link between GIC and CA for Chinese listed firms during a pandemic.

Cross-sectional data were collected from 248 chief executive officers (CEOs) of Chinese firms listed on the Shanghai Stock Exchange through a structured questionnaire. Regression analysis was employed to test the proposed hypotheses.

The findings reveal that all types of GIC positively influence a firm's CA. Furthermore, all three types of philanthropy – cash, in-kind and both – moderate the relationship between GIC and CA. However, the intensity of moderation was higher in the case of in-kind philanthropy than in the other two types.

To the best of the authors' knowledge, this is the first empirical study to examine the relationship between GIC (considering its three components: human, structural and relational capital) and CA in China. The study finds different types of philanthropy as moderating variables to better explain the relationship between GIC and CA. Further, it contributes to a new line of research that aims to study philanthropic aspects connected to the GIC debate.

This study aims to systematically review the health risk assessment of the concentration of heavy metals in Pistacia species globally.

The authors systematically searched PubMed, Science Direct, Scopus and Google Scholar to identify all articles published between 1 January 2002 and 20 August 2022. A total of 33 studies met the authors’ inclusion criteria, and their data were extracted. Additionally, the potential risk to human health was assessed by calculating the target hazard quotient and hazard index for both child and adult consumers.

The estimated daily intake for heavy metals in the included studies ranged from 9.72 × 10^–9 to 7.35 (mg/day) in the following order: zinc (Zn) > mercury (Hg) > iron (Fe) > lead (Pb) > copper (Cu) > aluminum (Al) > nickel (Ni) > chromium (Cr) > manganese (Mn) > cadmium (Cd) > arsenic (As) > selenium (Se) > cobalt (Co). Among the studies that investigated heavy metals in Pistacia species around the world, the non-carcinogenic risk for all species of Pistacia was determined to be less than 1, except for Pb and Hg in Pistacia lentiscus.

The soil near the industrial area contained excessive amounts of heavy metals, which led to the transfer of heavy metals to plants. Owing to the insufficiency of the number of studies that examined heavy metals in Pistacia species, further monitoring and investigations were recommended.

This paper aims to examine the relationship between environmental, social and governance (ESG) performance and systemic risk sensitivity of Chinese listed companies. From the consumer loyalty and investor structure perspectives, the relationship between ESG performance and systemic risk sensitivity is analyzed.

Since Morgan Stanley Capital International (MSCI) ESG officially began to analyze and track China A-shares from 2018, 275 listed companies in the SynTao Green ESG testing list for 2015–2021 are selected as the initial model. To measure the systematic risk sensitivity, this study uses the beta coefficient, from capital asset pricing model (CPAM), employing statistics and data (STATA) software.

The study reveals that high ESG rating companies have high corresponding consumer loyalty and healthy trading structure of institutional investors, thereby the systemic risk sensitivity is lower. This paper reveals that companies with high ESG rating are significantly less sensitive to systemic risk than those with low ESG rating. At the same time, ESG has a weaker impact on the systemic risk of high-cap companies than low-cap companies.

The study helps the companies understand the influence of market value on the relationship between ESG performance and systemic risk sensitivity. Moreover, this paper explains explicitly why ESG performance insulates a firm’s stock from market downturns with the lens of consumer loyalty theory and investor structure theory.

The paper provides new insights on the company’s ESG performance that significantly affects the company’s systemic risk sensitivity.

Considering the greenwashing risk of symbolic environmental management, this study aims to distinguish the motivation for environmental investment growth (EIG) from the corporate cost stickiness and anti-stickiness perspectives.

This study analyzes the impact of substantive and symbolic environmental management on cost stickiness. Subsequently, competing hypotheses are proposed. Finally, empirical tests are conducted on Chinese A-share listed companies from 2010 to 2019.

EIG significantly improves enterprises’ cost stickiness. The cost of high EIG enterprises does not decrease significantly with a decline in income compared to other enterprises, which is consistent with the motivation for substantive environmental management. Enterprises with high asset specificity and optimistic management expectations show more obvious substantive environmental management. Government and public environmental concerns cause more pronounced substantive environmental management.

An evaluation of corporate environmental responsibility should take into account both what the company has disclosed and what it has actually done.

Governments and the public should have a comprehensive understanding of corporate environmental management. They need to strengthen their ability to recognize symbolic environmental management and support substantive environmental management.

Fundamental to the evaluation of corporate environmental responsibility, this study distinguishes the motivations for corporate EIG disclosures from the cost stickiness perspective to avoid the risk of greenwashing. Hypotheses on the impact of substantive and symbolic environmental management on cost stickiness are presented. This study verifies the substantive environmental management characteristics of listed Chinese companies.