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This study aims to investigate the relationship between corporate governance (CG) and financial performance in the case of publicly listed companies in Vietnam for the period from 2019 to 2021. The topic is crucial in understanding how effective governance practices can influence the financial outcomes of companies. The study sheds light on the link between CG practice and firm financial performance. It also provides insights for policymakers and practitioners to improve CG practices.

Due to the potential dynamic endogeneity in CG research, this study uses the generalized system methods of moments to effectively address the endogeneity problem. Financial performance is measured by Tobin’s Q, return on equity (ROE) and return on assets (ROA). Based on organization for economic cooperation and development (OECD) standards, these indices were calculated to assess the influence of CG practices on corporate financial performance, namely, for accounting information (ROA and ROE) and market performance (Tobin’s Q and service à resglement différé (SRD) – stock price volatility) for the period 2019–2021. In addition, the study examines the relationship between changes in the CG index and changes in financial performance.

The study’s main objective is to determine the relationship between CG performance scores and financial performance. The study found a positive relationship between transparency disclosure and financial performance and a positive correlation between CG and company size. The COVID-19 pandemic caused a decrease in transparency and information index scores in 2021 compared to 2019 and 2020 due to delayed General Meetings of Shareholders. The study failed to find a relationship between shareholder rights index (“cg_rosh”) and board responsibility (“cg_reob”) and financial performance, concerning which the findings of this study differ from those of previous studies. Reasons are put forward for these anomalies.

Policymakers need to develop a set of criteria for assessing CG practices. They also need to promulgate specific regulations for mandatory and voluntary information disclosure and designate a competent authority to certify the transparency of company information. The study also suggests that companies should develop CG regulations and focus on regulations relating to the business culture or ethics, as well as implementing a system to ensure equal treatment among shareholders. The study found that good CG practices can positively contribute to a company’s financial performance, which is crucial for investors to evaluate the quality of CG practices for each listed company so that investment risks can be limited.

The study aims to examine the association between corporate transparency and firm value (capital market effect) and investigate whether auditor choice moderates this relationship.

This study uses the Malaysian Institute of Corporate Governance (2017) data set, which provides scores on anti-corruption commitment, organisational transparency and sustainability of Malaysia’s top 100 listed firms. The methodology entails an ordinary pooled least square regression method for empirical research.

The positive association between corporate transparency and firm value is more evident in anti-corruption and sustainability initiatives. More importantly, government-linked companies have higher scores. Firms with enhanced anti-corruption commitment are more likely to have higher firm value, and this relationship is more evident for politically connected firms. This study also finds that auditor choice is associated with the firm value in the sampled listed firms.

The findings provide implications for investors and regulators on the role of corporate transparency in an emerging capital market.

The study recommends that emerging market regulators continue enhancing corporate governance codes and practices to improve reporting transparency for listed firms.

This study contributes to the growing literature on sustainability disclosures by incorporating corporate reporting transparency, explicitly relating to firms’ commitment to anti-corruption, organisational transparency and sustainability.

This study aims to advance knowledge on the direct impact of the investor’s protection level on the stock market volatility, that is, whether investor’s protection is an important stock market volatility determinant.

A panel data was estimated using a sample of 48 countries, from 2006 to 2018, totalizing 31,808 observations. To measure stock market volatility and the investor protection level, a generalized autoregressive conditional heteroskedasticity model and the World Bank Doing Business investor protection index were used, respectively.

The results evidence that the protection of investors’ rights reduces the stock market volatility. This result indicates that a high level of investor protection, which is the result of a better quality of laws and policies in place that protect investor’s rights, promotes the country as a “safe haven.”

The relationship that the authors intend to analyze becomes important, given that investor protection will give outsiders guarantees on the materialization of their investments. This study contributes important knowledge for investors and for the establishment of government policies as a way of attracting investment.

Although there have been a few studies addressing this relationship, to the knowledge, none of them directly analyses the influence of investor protection on the stock market volatility.

The study intends to determine the environment, social and governance (ESG)'s impact on the firm's value. In addition, how ownership concentration (OC) and transparency and disclosures (TD) influence the impact of firm's ESG on its valuation (firm value).

The relevant panel data with a sample of 78 Indian firms for five years (2016–2020) are gathered. Both linear and nonlinear connections of firm's ESG with its value are tested. In addition, TD and two components of OC (stakes of promoters and institutional investors) are empirically tested as moderators on the connectivity of the firm's ESG with its value.

The linear association of firm's ESG with its value is found insignificant. ESG is found to have a positive and nonlinear (U-shaped) impact on the value of the firms. TD does not moderate the connectivity of firm's ESG with its valuation (firm value). The higher stakes of promoters positively affect the association of firm's ESG with the valuation. However, the high stakes of institutional investors retard the ESG's influence on the firm value.

The study is on Indian firms for five years. A sample of more than one nation and a longer duration (10 years) could have helped better determine the associations among the variables. In turn, these limitations can be the present study's future scope. In addition, the authors find a lack of standardisation of the ESG scales, which is a problem in measuring it. Using standardisation scales of ESG for the analysis can also be future scope on the topic.

The investors would be wary of the level of ESG to influence the firms' value positively. Managers also need to be careful to have sincere efforts for ESG to reap its rich dividends. Policymakers may take cognisance that despite having board seats (in a few cases), institutional investors negatively (instead of positively as expected) influences the ESG's association with the firm's value. They may bring some guidelines or legislative changes to fix responsibility on the part of the institutional investors.

No study reports the linear and nonlinear association of ESG on the firm's value to observe clearer connectivity between the two. Similarly, no study is observed to have promoters and institutional investors as moderators on the association of firm's ESG with the valuation (firm value). Hence, the present study considerably augments the extant literature on the topic and its contribution.

This study aims to identify the main factors affecting export competitiveness and its barriers, focusing on the minerals industry so that a scale is achieved for measuring export competitiveness in this industry.

The research was conducted with a mixed method approach in the minerals industry. Among the active companies involved in this industry, 34 export companies and export management companies were selected and evaluated. In the qualitative phase, 18 experts and managers of the industry were interviewed to identify the factors affecting the export competitiveness of these companies and the barriers ahead of them. In the quantitative phase, a questionnaire was distributed among 412 managers and experts in this industry to categorize the identified factors and to measure the relationships among them. For data analysis in the qualitative phase, theme analysis was used. For the quantitative phase, factor analysis and structural equation modeling were adopted.

In addition to identifying the main components affecting the competitiveness of companies in exporting minerals as well as the main barriers ahead of them, the findings of the current research categorized these components using factor analysis. These components were categorized into factors, such as manufacturing factors, demand conditions, related and supporting industries, structural factors, competitive strategy and governmental supports. Afterward, their impacts on export competitiveness were measured and supported.

Although some studies have been conducted to examine the competitiveness in different industries, no research has been found that has examined and identified the main factors affecting export competitiveness and their impacts in the minerals industry with a mixed quantitative and qualitative approach. The findings of this research may help managers and policymakers, at the industrial and national levels, to reach a scale for assessing the export companies involved in this industry by identifying the most essential factors of export competitiveness of minerals. Furthermore, the findings of this research can act as a model for future researchers to develop a scale for export competitiveness in other industries.

Factors of production (labour, land, capital), technology and technical progress are usually cited as the main sources of economic growth and development. However, there are a number of other factors that have a significant impact on the possibilities and extent of their use or their further improvement and development. These factors undoubtedly include the institutional environment, within which corruption is also a consideration. In this chapter, attention will be focused on the various institutional variables that are used to assess the quality of a country's institutional environment, including corruption. A number of studies have shown that a quality institutional environment and low levels of corruption are prerequisites for long-term economic growth. Using an analysis of individual indicators of the Worldwide Governance Indicators (WGIs), published annually by the World Bank, supplemented by the Corruption Perception Index (published by Transparency International), we look at where Czechia has moved over the last decade or two in terms of institutional quality and corruption.

In the global context, artificial intelligence (AI) technology and environmental, social and governance (ESG) have emerged as central drivers facilitating corporate transformation and the business model revolution. This paper aims to investigate whether and how the application of AI enhances the ESG performance of enterprises.

This study uses panel data from Chinese A-share listed companies spanning the period from 2012 to 2022. Through a multivariate regression analysis, it examines the impact of AI on the ESG performance of enterprises.

The findings suggest that the application of AI in enterprises has a positive impact on ESG performance. Internal control systems within the organization and external information environments act as mediators in the relationship between AI and corporate ESG performance. Furthermore, corporate compliance plays a moderating role in the connection between AI and corporate ESG performance.

This paper underscores the pivotal role played by AI in enhancing corporate ESG performance. It explores the pathways to improving corporate ESG behavior from the perspectives of internal control and information environments. This discussion holds significant implications for advancing the application of AI in enterprises and enhancing their sustainable governance capabilities.

The purpose of this research is to evaluate corruption in the context of India, spanning the period between 1988 and 2021. Additionally, it aims to provide an in-depth comprehension of the factors that drive its prevalence and to propose policy directives for addressing these underlying issues.

The study instead of relying on perception-based measures, takes a distinct approach by formulating a corruption index derived from reported instances, thus ensuring a more objective assessment. Furthermore, we employ stochastic frontier analysis to tackle the issue of under-reporting within the corruption index based on reported cases. Subsequently, an auto regressive distributed lag (ARDL) methodology is applied to ascertain the principal drivers of corruption, encompassing both long and short factors.

This study reveals that corruption in India is notably influenced by economic growth and income inequality. Conversely, government effectiveness and globalization display a tendency to mitigate corruption. However, our rigorous analysis demonstrates that financial development does not wield a substantial influence in our study. Moreover, our inquiry uncovers a nonlinear relationship between economic growth and corruption. Additionally, we ascertain that the long run and short run impacts of corruption remain relatively stable across both models utilized in our study.

This study differs from previous research in the subsequent manners. Primarily, we employed an objective measure to formulate the corruption index, coupled with addressing the underreporting issues via stochastic frontier analysis. Moreover, this study pioneers the identification of a non-linear relationship between corruption and economic growth within the Indian context, a facet unexplored in previous investigations.

Pre-construction of a project comprises stages that are pivotal for the procurement performance. It is defined as the duration from the project's initiation to construction. However, Private Public Partnerships (PPPs) have been subjected to a long pre-construction, thereby leading to an inefficient development process. Therefore, the purpose of this paper is to pay attention to the influencing factors elongating the pre-construction duration.

Based on data of 5,677 PPP projects between 2009 and 2021 in China, the authors adopt the Accelerated Failure Time (AFT) model in duration analysis to empirically analyze the following underlying dynamics determining the duration of PPP pre-construction stages: (1) policy uncertainty; (2) corruption; and (3) procurement method selection. To observe the influencing paths more specifically, the authors divided the pre-construction duration into the pre-tendering period and tendering period and regressed them separately.

The results indicate that the pre-construction duration is significantly prolonged with increased policy uncertainty and corruption degree as well as the use of tendering methods. Meanwhile, the above factors have a greater impact on the pre-tendering period than the tendering period.

The contribution of this study is twofold: (1) theoretically, this paper provides new evidence on the impact of PPP policy uncertainty, corruption and procurement method selection on the pre-construction duration. It complements empirical studies on the factors elongating the time efficiency of PPPs projects. (2) In practice, it provides a specific path for the government to improve the time efficiency of PPPs.