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As artificial intelligence (AI) continues to make inroads into several industries, it has taken over tasks previously performed by humans. However, given that individuals frequently have their self-esteem, identity and feelings of self-worth wrapped up in financial matters, will there be a difference in their satisfaction when their credit applications are processed and approved through AI versus humans?

This work uses five studies, including a field study, three online experiments and one laboratory study, to underline the difference in customer satisfaction when credit application processing occurs via AI versus humans.

The authors find that customers are more satisfied when credit application processing is performed through an AI algorithm rather than by humans. This effect is explained by reduced embarrassment. Furthermore, the authors show that for emotionally intelligent individuals, credit application processing through humans will mitigate the impact of embarrassment, leading to higher customer satisfaction. Finally, the authors identify an individual’s relationship with the financial organisation as the boundary condition stating that for first-time customers (vs continuous customers), credit application processing through humans causes less embarrassment.

This research makes significant contributions in the realm of consumer psychology and credit application processing. First, it advances the existing literature on AI versus human interactions by investigating their comparative impact on customer satisfaction within financial processes such as credit approval. In addition, it identifies credit application processing (whether by AI or humans) as an unexplored antecedent of embarrassment. Moreover, this study enhances the body of work on emotional intelligence by demonstrating its role as a coping mechanism for dealing with embarrassment. Finally, it uncovers a novel driver of embarrassment: the nature of individuals’ relationships with financial organisations, differentiating between continuous customers and first-time applicants.

This study suggests deploying AI for credit approval and adopting strategies to reduce customer embarrassment to boost consumer satisfaction. In addition, managers should consider customers’ emotional intelligence levels and use humans for first-time credit applications to minimise embarrassment.

Arguably, to the best of the authors’ knowledge, this study is the first to identify AI versus human processing as a novel factor influencing customer embarrassment in financial service satisfaction. It also provides a new aspect of emotional intelligence as a coping mechanism for embarrassment. Furthermore, it uncovers a unique driver of embarrassment: the nature of individuals’ relationships with financial organisations, distinguishing between continuous customers and first-time applicants.

This study aims to examine whether and how the presence of co-opted directors (directors appointed after the incumbent CEO) influences corporate climate risk disclosure.

This study comprehensively analyses 2,975 firm-year observations of US-listed companies, using ordinary least squares with industry and year-fixed effects. To confirm the reliability of the study results, the authors used several techniques, including propensity score matching, to address potential issues with functional form misspecification, analysed a subset of companies where co-option persisted over two consecutive years to mitigate concerns regarding reverse causality and difference-in-differences estimation, using the cheif executive officer’s (CEO’s) sudden death as an exogenous shock to board co-option to mitigate endogeneity concerns.

The findings indicate that the presence of a large number of co-opted directors negatively influences corporate climate risk disclosure. Mediation analysis suggests that managerial risk-taking partially mediates this negative association. Moderation analyses show that the negative impact of co-opted directors on climate risk disclosure is more pronounced in firms with greater linguistic obfuscation, limited external monitoring and in environmentally sensitive industries. Moreover, co-opted directors intentionally withhold or obscure the disclosure of transition climate risks more than physical climate risks.

This research has important implications for policymakers, regulators and corporate governance practitioners in designing board structures by highlighting the adverse impact of co-opted directors in contexts with lax regulatory enforcement and managerial discretion. The authors caution against relying on such directors for providing climate-related risk disclosures, especially in companies with poor external monitors and based in environmental sensitivities, as their placement can significantly undermine transparency and accountability.

This study adds to the existing body of knowledge by highlighting the previously unexplored phenomenon of intentional obscurity in disclosing climate risks by co-opted directors. This research provides novel insights into the interplay between board composition, managerial risk-taking behaviour and climate risk disclosure. The findings of this study have significant implications for policymakers, regulators and corporate governance experts, and may prompt a re-evaluation of strategies for improving climate risk disclosure practices.

The study examines the effects of corporate governance and countrywide institutions and risk factors on corporate liquidity.

Using firm-level data, the authors analyze the effect of corporate governance and various economic, regulatory and social institutions on the liquidity of firms operating in the Middle East and North Africa (MENA) region. The authors use fixed-effects, firm-specific and country-level controls, disaggregated analysis, sensitivity and endogeneity analysis to test the robustness of the estimates.

The corporate governance characteristics of firms influence in diverse ways their liquidity decisions. The independence and diversity of the board and institutional ownership are especially strong predictors. The effect also depends on the size of the firm and the degree of economic development and exhibits time sensitivity and nonlinearity. Enforcement institutions and risk factors play a strong role.

The analysis contributes to the literature by using a large sample of countries and firms over a larger period, distinguishing between poorer and richer countries and using sensitivity and endogeneity analysis. The analysis considers explicitly the role of regulatory and enforcement conditions, social structures and religious beliefs.