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This study aims to explore the impact of the chief executive officer’s (CEO) age on adopting global reporting initiative (GRI) framework for corporate social responsibility (CSR) reporting. It also underlines how board social capital moderates the relationship between CEO age and the adoption of the GRI framework.

Chinese A-listed companies during 2010–2018 were used. The authors applied a logistic regression model due to the binary nature of the dependent variable. For robustness, two-step generalized method of moments (GMM) and lagged independent variables are used.

The study finds that CEO age negatively impacts the firm’s choice of GRI reporting framework. The social capital of the board positively moderates this relationship. This finding is based on the notion that as a CEO grows older or headed toward retirement age, his/her interest in CSR diminishes due to a shorter career horizon. Boards with external links provide better advice on CSR issues and mitigate the negative impact of CEO age.

The study results are important for understanding the GRI framework’s development and implementation, particularly in China.

To the best of the authors’ knowledge, this is the first study that deeply examines how CEO age affects GRI adoption in the Chinese context and how the board’s social capital moderates this relationship.

This study aims to examine the relationship between board capital and firm performance in the Chinese tourism industry.

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.

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.

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.

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.

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.

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.

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.

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.

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.

This study aims to determine the role of intellectual capital (IC) on financial performance (FP), the mediating effect of high-performance work practices (HPWPs) and the moderating role of big data analytics on the banking sector operating in Pakistan.

This study collected quantitative and cross-sectional data using structured questionnaire forms distributed to selected targeted respondents using a convenient sampling technique. The 518 useable questionnaires were analysed using the SmartPLS software through a structural equation modelling technique to test the proposed research hypotheses.

The study results revealed that IC has shown an impact on FP. The role of HPWP significantly mediates between IC and FP, while the moderating role of big data analytics remains insignificant.

This study highlights IC's role in enhancing FP in the Pakistani banking sector. It will bring a higher quality IC in the banking sector, and they will be better positioned to serve the community. Policymakers need to invest in IC and HPWP and utilise BDA, which will boost FP and uplift the quality of the banking sector.

This study extends the concept of IC and adds the theoretical role of HPWPs and big data analytics in the literature on IC, along with the contextual application. The study also develops a unique role of the integrated IC model theory with a relationship to the banking sector of Pakistan.

This study aims to examine how career commitment (CC) affects hospitality employees perceived subjective career success (SCS) using a serial mediation system that uses career resilience (CR) behaviour and self-efficacy (SE) as serial mediators.

To examine the proposed relationships, a comprehensive theoretical serial mediation model was constructed. The proposed hypotheses were tested on a sample of 316 hospitality employees from India using regression analysis (Process Macro Model 6) with 5,000 bootstrapping at 95% confidence interval.

The regression analysis confirmed a strong, positive relationship between CC and SCS. It also highlighted a significant indirect effect, involving a serial mediation through CR and SE, demonstrating how CC influences SCS.

Drawing from three prominent theories – career self-determination theory (CSDT), career construction theory (CCT) and the contextual action theory of career development (CATCD), this research underscores the importance of fostering career-committed behaviour among employees and advocating for strategic career development initiatives. Understanding CC elements may help firms retain and encourage individuals, which can boost job satisfaction and performance. Importantly, the results advocate for the implementation of targeted career development strategies and the promotion of career-committed behaviour within hospitality organisations. This, in turn, fosters resilience and competence, ultimately contributing to individual career success and organisational excellence.

A serial mediation model with CR and SE introduces a fresh perspective that, to the best of the authors’ knowledge, has not been extensively explored in previous research examining the relationship between CC and SCS.