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It is imperative for policymakers, financial institutions, and individual investors to comprehend the factors that impact stock market participation, given the growing significance of the stock market in terms of personal and national wealth. This study endeavours to explore the relationship between cognitive ability and participation in the stock market. We examine the relationship between cognitive abilities and stock market participation, and further explore the mechanism of their influence.

The data from the China Family Panel Studies is utilized, and Tobit and Probit regressions are employed. Additionally, an instrumental variable approach (IV-estimate) is implemented to address the endogeneity issue linked to cognitive ability, and the study’s findings are resilient.

The results reveal a significant positive relationship between cognitive ability and stock market participation. Additionally, the findings suggest that households with higher cognitive ability tend to aggregate more information, expand social networks, and take more risks. A likely explanation is that individuals with higher cognitive ability are more likely to process more external information and evaluate the subjective uncertainty of stock markets based on a well-defined probability distribution. Our findings indicate that the impact of cognitive ability on stock market participation varies among families with differing education levels, genders, marital statuses, and geographical locations.

Therefore, the roles of cognitive abilities in accelerating stock market participation should be fully considered. More information channels and sources that contain financial markets’ information (e.g. mobile applications and financial education) should be provided. Thus, the significance of cognitive ability in increasing stock market participation should be fully considered. Providing more information channels and sources, such as mobile applications and financial education, that contain financial markets’ information would be helpful. Our study contributes to promoting financial literacy and inclusion by highlighting the significant positive impact of cognitive ability, where institutions can tailor their outreach efforts and information channels to better serve individuals with different cognitive ability.

This study aims to investigate how a firm's management team's capacity to efficiently use its resources affects the firm's exposure to climate change. Specifically, the authors investigate the intriguing question – does managerial ability affect a firm's climate change exposure?

The authors use an unbalanced panel dataset of 4,230 US based firms listed on Compustat from 2002–2019 and test the hypothesis by panel regression analysis. To mitigate endogeneity concerns, difference-in-differences and instrumental variable approaches are used.

The baseline analysis shows a negative, statistically significant impact of managerial ability on climate change exposure. The findings hold after controlling for endogeneity using two-stage least squares regression and difference-in-differences tests. The authors find the negative effect is stronger for managers engaged in socially responsible activities, and after climate change issues receiving greater public awareness following the 2006 release of the Stern Review and the 2016 signing of the Paris Accord.

Motivated by the resource-based theory and the natural resource-based view of the firm model, the empirical results support the view that greater managerial ability protects the firm against environmental challenges through efficient use of firm resources. Compared with traditional climate change measures that are plagued by disclosure issues, the use of the Sautner, Van Lent, Vilkov and Zhang's machine learning based dataset utilizing earning conference calls provides stronger, robust findings that will be useful to management and investors in environmental performance assessments.

Motivated by the resource-based theory and the natural resource-based view of the firm model, the empirical results support the view that greater managerial ability protects the firm against environmental challenges through efficient use of firm resources. Compared with traditional climate change measures that are plagued by disclosure issues, the use of the machine learning based dataset utilizing earning conference calls provides stronger, robust findings that will be useful to management and investors in environmental performance assessments.

It has been ten years since the policy was implemented, but the effect of the policy needs to be tested empirically. This paper aims to explore the mechanism of policy influence on regional innovation ability by measuring the effectiveness of policy by innovation ability indicators. Further, it reflects the problems in the process of the transformation and development of resource-based cities in recent years and points out the direction for the development of the cities in the future. In addition, this paper discusses the differences between regions and cities in China and seeks the path to narrow the gap.

This paper mainly uses the difference-in-difference method for the research. This study divided China’s resource-based cities and non-resource-based cities into experimental groups and control groups, and explored the effect of the transformation and development of resource-based cities and the changes of their innovation ability under the influence of the National Sustainable Development Plan for Resource-based Cities (NSDPRC). More carefully, this paper uses the fixed effects regression model, propensity score matching method, bootstrap method and other methods to improve the empirical results.

This paper finds that NSDPRC significantly improves the innovation ability of resource-based cities, although there is some lag in this effect. Research on the influence mechanism of policies shows that NSDPRC improves the marketization degree of resource-based cities and reduces the proportion of the secondary industry in such cities. Finally, the results of the heterogeneity analysis confirm that policies are more popular in western China and that resource-based cities in growth, maturity and decline are more vulnerable to policy influence. The development of policy effectiveness also requires the size of a city, and maintaining a healthy and reasonable scale is necessary for urban development.

First, the existing research on the development of resource-based cities is mainly from the perspective of economy and environment, but rarely from the perspective of innovation ability, and the index to measure urban development is relatively single. This paper will compensate for this deficiency. Second, different from the European and American countries that have basically completed the industrial transformation, the research on Chinese cities will provide a reference for the transformation of developing countries. Finally, from the perspective of resource endowment theory and innovation theory, this paper discusses the influence of SDPNRBC mechanism on the innovation ability improvement of resource-based cities, and further improves and enriches the theory.

This study aims to define, classify and interconnect the wide range of known entrepreneurial abilities with terms such as skills, capabilities and competencies, which have been used inconsistently within the entrepreneurial field.

This investigation is based on a systematic literature review and strengthened by a meta-analysis equipped with a bibliometric study to assist the generation of outcomes with a quantitative investigation.

This study proposes an evolving entrepreneurial ability model which interconnects genetic and acquired skill types, capabilities and competencies and is equipped with an Entrepreneurial Skills Map essential to operate in the 21st century.

The proposed model is specific to the entrepreneurial field.

This study supports universities and government agencies for the development of educational programs to prepare current and future entrepreneurs to match the changes in the new environment that has emerged with the COVID-19 pandemic.

This research contributes to the entrepreneurship research domain by shedding light on the inconsistent use of non-standardised terminologies and providing an entrepreneurial model and updated skills map to guide scholars to frame research in the post-COVID era with more clarity.

The study aims to study the effect of non-cognitive ability in human capital on the wages of rural migrant workers in China. The study also examines the mechanisms by which career choice, career development and social capital influence.

Based on the new human capital theory, this paper empirically investigates the effects and mechanisms of rural migrant workers' non-cognitive ability on wages using the 2018 China Family Panel Studies database and Stata 17.0 for construct validation and hypothesis testing.

The results showed that non-cognitive ability has a significant positive effect on rural migrant workers' wages. Subsequently, the mechanism of non-cognitive ability was examined. In further analysis, the study found that non-cognitive ability has a greater effect on the wages of vulnerable individuals (females, low and medium skills) among the rural migrant workers.

The originality of this study is to break through the existing research perspectives, overcome the limitations of scholars' existing research perspectives focusing on the employment and competitiveness of rural migrant workers in China and explore the factors affecting the rural migrant workers' wages from the perspective of non-cognitive ability as a new entry point by combining psychology. At the same time, the study design is more rigorous, avoiding the measurement error of variables.

Executive decisions regarding capital financing are an important management aspect, especially during financing constraints and growth opportunities. The current study examines the impact of managerial skills of a company on capital financing decisions. Furthermore, it analyzed this nexus in financing constraints and growth opportunity situations.

The authors use the GMM (generalized method of moments) estimation approach on a dataset of 20,651 firm-year observations of Chinese A-share companies from 2010 to 2019.

The authors’ findings are compatible with management signaling and reputation enhancement theories, since they show that managerial skill is connected with more substantial debt financing. Managers with high management skills are likely to have more debt financing as they can foresee the economic future of their companies and tactfully convey private information, lowering information inequality and enhancing their reputation. Furthermore, the authors also show that firms with restricted financial resources and growth opportunities make this relationship stronger. Capital structure and managerial skill findings are unaffected by alternative specifications, omitted factors, industry group bias and endogeneity.

This study sheds fresh light on the essential manager personality trait of managing ability and how it influences complicated corporate decision-making, particularly in the tough environment due to financing constraints and competitive growth. The authors argue that high-ability managers are compelled to use debt financing not only to lessen information asymmetry but also to guarantee that the market finds their superior ability. This work contributes significantly to the managerial ability literature and the capital structure literature supporting signaling theory.

This study adopts the perspective of dynamic capabilities to investigate influencing factors and proposes improvement strategies of supply chain resilience of prefabricated construction.

The structural equation model (SEM) is used to identify and verify the relationship between factors influencing supply chain resilience of prefabricated construction from the perspective of dynamic capabilities. The system dynamics (SD) model is constructed to dynamically simulate the specific effects of different influencing factors.

Results indicate that: (1) An evaluation index system for supply chain resilience of prefabricated construction containing five first-level indicators and 36 second-level indicators is constructed; (2) Ability to anticipate, ability to respond, ability to adapt, ability to recover and ability to learn are positively correlated with the supply chain resilience of prefabricated construction and (3) ANT3 (information system), RES1 (quick response), ADA3 (buffer stock) and LEA4 (trust) are the most leading factors influencing supply chain resilience of prefabricated construction over time.

This study fulfills the need for an in-depth exploration of the various influencing factors on supply chain resilience of prefabricated construction from the perspective of dynamic capabilities. Furthermore, this study provides improvement strategies to enhance supply chain resilience of prefabricated construction in China.

Successful digital transformation requires a change in organisational structures, processes, capabilities and competencies. Digital transformation research is more influenced by the technology adaptation model and hence focuses on people's attitudes, behaviour and abilities. Recently, employee agility has attracted attention in the context of technology adoption and Industry 4.0. The current research explores the relationship between employee agility and digital technology adoption in the context of digital transformation by adopting the systematic literature review method.

Following the attitude–ability-behaviour–outcome framework, the research explored the specific agile ability, attitude and behaviour characteristics useful for digital transformation. Following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) framework consisting of (1) initiation, (2) screening, (3) evaluation and (4) confirming inclusion (Ambika et al., 2023), the study identified 19 papers from SCOPUS indexed journals.

The study result found that agile attitude characteristics such as collaborative mindset, computer self-efficacy, ambiguity aversiveness, etc. are influencing the digital transformation process. Agile abilities like basic computer knowledge, previous technical experience, cognitive abilities, innovation capability, digital competence training and supporting proper knowledge management practices also influence digital transformation. Finally, agile behaviour such as relationship building, knowledge-sharing behaviour, promoting values of learning, risk-taking and experimenting, rewarding innovativeness and customer-centric innovation and displaying adaptability, resilience and commitment to change, etc. are found to drive digital transformation.

Research on workforce agility and digital transformation is scarce. The current study contributes to benchmarking research by exploring specific agile attitudes, abilities and behaviour characteristics relevant to digital transformation, especially in the era of Industry 4.0.

The increasing complexity of civil engineering projects necessitates focusing on new competencies of project participants. Based on the research on team performance and design processes that are more closely linked to the relevance of the project context, it is hypothesised that empathic abilities could play an important role in the performance of civil engineering projects. Therefore, this study aims to investigate whether performance can be improved by focusing on empathic abilities during the integrated design phase.

Semi-structured in-depth interviews with experts were conducted to explore the relevance of empathic abilities and their interaction with performance in a real-life infrastructure project. The project team’s empathy level was measured by means of a survey using Davis’ Interpersonal Reactivity Index method. Finally, differences between expected and measured levels of empathy were analysed.

The results provide insights into how empathic abilities interact with performance. The measurement indicates that, on average, professionals in the civil engineering industry score relatively low on empathy. In addition, differences were identified between the expected distribution and the measured empathy levels of the team, implying a potential for improvement, in particular by increasing the empathic abilities of the project management and increasing gender diversity.

To the best of the authors’ knowledge, this study is the first to investigate a relationship between empathy and the performance of civil engineering projects. The results provide initial insights into the empathic ability of civil engineering project teams and the potential of empathy to improve performance. Furthermore, from an empathy perspective, this study advocates increasing the gender diversity of project teams to improve performance.

This paper aims to examine and compare the dividend ratios’ statistical and economic ability to predict the equity premium in the UK and US markets and two US sub-indices (S&P 500 Growth and S&P 500 Value).

In this paper, the authors use the linear regression models to examine the dividend ratios’ statistical ability to predict the equity premium. The in-sample and out-of-sample approaches, including Diebold and Mariano (1995) statistics, and Goyal and Welch’s (2003) graphical approach, are used. Also, the mean-variance analysis is used to test the economic significance.

The paper findings indicate that the dividend ratios have in-sample and out-of-sample predictive abilities in both UK and US markets and both US sub-indices. However, the results show that the dividend ratios have a less impressive predictive ability in the US market compared to the UK market and less in the US value index than the US growth index. This could indicate that there is no relation between the number of companies that distribute dividends in each index and the informativeness of dividends ratios. Furthermore, the tests show the dividend ratios’ predictive ability departure during particular periods and in some indices.

Results and implications of this research are exclusively applied to the US and UK markets. These results can also be applied with caution to other markets, taking into consideration the distinctive characteristics of these markets.

Results revealed in this paper imply that the investors in any of the indices may experience economic gain by adopting a dynamic trading strategy using the information content of the dividend ratios prediction models instead of the benchmark model, which is the prevailing simple moving average model.

This paper adds value through testing the prediction models’ economic significance in two well-developed markets, in addition to exploring the relationship between the number of companies distributing cash dividends and the dividends ratio prediction ability. Unlike most of the previous studies in which dividend ratios’ prediction ability is attributed to the number of companies that distribute dividends in the market, this paper denied this interpretation by studying two S&P 500 sub-indices. To the best of the authors’ knowledge, this is the first study to test the prediction models’ ability for these sub-indices.