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Purpose The purpose of this study is to explore whether different board diversity attributes (corporate governance aspect) can be used to predict financial distress. This study also aims to identify what type of prediction models are more applicable to capture board diversity along with conventional predictors. Design/methodology/approach This study used Chinese A-listed companies during 2007–2016. Board diversity dimensions of gender, age, education, expertise and independence are categorized into three broad categories; relation-oriented diversity (age and gender), task-oriented diversity (expertise and education) and structural diversity (independence). The data is divided into test and validation sets. Six statistical and machine learning models that included logistic regression, dynamic hazard, K-nearest neighbor, random forest (RF), bagging and boosting were compared on Type I errors, Type II errors, accuracy and area under the curve. Findings The results indicate that board diversity attributes can significantly predict the financial distress of firms. Overall, the machine learning models perform better and the best model in terms of Type I error and accuracy is RF. Practical implications This study not only highlights symptoms but also causes of financial distress, which are deeply rooted in weak corporate governance. The result of the study can be used in future credit risk assessment by incorporating board diversity attributes. The study has implications for academicians, practitioners and nomination committees. Originality/value To the best of the authors’ knowledge, this study is the first to comprehensively investigate how different attributes of diversity can predict financial distress in Chinese firms. Further, this study also explores, which financial distress prediction models can show better predictive power.

Purpose This study aims to examine the relationship between board capital and firm performance in the Chinese tourism industry. Design/methodology/approach The study’s sample includes firms from the Chinese hotel, air transportation/travel and catering industries. This study explores the governance environment in tourism industries. This study estimates three dimensions of the board, including education, expertise and directors interlock. These dimensions are further grouped as human capital (i.e. education and expertise), social capital (interlocks) and board capital (sum of social and human capital). Ordinary least square regressions with multiple robustness tests are used to investigate the effect of board capital on firm value in Chinese listed tourism firms during 2005–2018. Findings This study finds that board capital positively impacts firm performance in its dimensions of human and social capital. This study also highlights the two important ownership contexts, namely, institutional investors and state-ownership, that shape the board capital-firm performance association in the Chinese tourism industry. Practical implications The findings suggest that board capital plays a significant role in corporate decisions. The results illustrate that higher board capital improves both governance mechanisms and resource provision roles of the board, resulting in higher firm value. The results further offer implications for managers and shareholders of tourism firms when electing directors as shareholders’ representatives. Originality/value The study has two important contributions. First, it extends the prior literature of firm value by considering the board’s human and social dimensions in the tourism sector. Second, contrary to prior research on board, this study takes three facets of board capital, education, expertise and interlocks that improve governance mechanisms and bring new resources in the shape of skills, knowledge and expertise.

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This study comprehensively reviews the theoretical and empirical literature on the relationship between corporate governance and financial distress and provides future research directions. We follow several different approaches by identifying, reviewing, and classifying related articles during the period 1985 to 2021. We used a set of keywords that included a combination of different terms of corporate governance and financial distress. Our review indicates that the majority of the studies based their arguments considering a single theory. The generalizability of different results in less explored countries is a serious concern and the one‐size‐fits‐all approach does not apply to the corporate governance‐financial distress relationship. Several different theories and confounding factors need consideration when examining the relationship between corporate governance and financial distress. Our review highlights future avenues by suggesting that studies should consider different governance attributes and test those factors in different and diverse contexts. Our review of the literature provides implications for academics and practitioners.