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This study aims to examine the causal relationship between mandatory CSR disclosure and financial audit efficiency.

The authors use the unique institutional setting of China, where a subset of listed firms are mandated to disclose their corporate social responsibility (CSR) reports. The authors use propensity score matching and difference-in-differences approaches to compare audit efficiency in the pre- and post-mandatory CSR disclosure periods between the treatment and control groups. The regression models are estimated with robust standard errors clustered at the firm level.

This study finds that following China’s adoption of the mandatory disclosure of CSR, audit report lags decreased by 6% on average, suggesting that audit efficiency improved greatly following mandatory CSR disclosure. Moreover, this association is stronger when firms have better CSR performance, higher CSR report preparation costs, more earnings management before disclosure regulations and better internal controls and when firms belong to high-profile industries and in Big 4 (Big 10) accounting firms. Moreover, neither audit quality nor audit fees decrease when shorter audit lags occur for firms with mandatory CSR disclosures. Overall, the evidence suggests that mandatory CSR disclosure has a positive effect on audit efficiency and that the improvement of audit efficiency does not come as a consequence of reducing audit fees or deteriorating audit quality.

The results reported in this study have practical and policy implications for policymakers, accounting firms and auditors to pay more attention to CSR information.

This study provides evidence of the causal relationship between mandatory CSR disclosure regulation and audit efficiency. It enriches the research on audit service production efficiency from the perspective of nonfinancial information disclosure.

Keeping in view the robust growth of Islamic banking around the globe, this study aims to comparatively analyze the association between liquidity creation and liquidity risk for Islamic banks (IBANs) and conventional banks (CBANs) in Pakistan and Malaysia over a period of 2004–2021. The moderating role of bank loan concentration on the aforementioned relationship is also studied.

Regression estimation methods such as fixed effect, random effect and generalized least square are deployed for obtaining results. Liquidity creation Burger Bouwman measure (cat fat and noncat fat) and Basel-III liquidity risk measure (liquidity coverage ratio) are also used.

The results give us insight that liquidity creation is positively and significantly related to liquidity risk in both IBANs and CBANs of Pakistan and Malaysia. This relationship has been moderated negatively (reversed) and significantly by credit concentration showing the importance of risk management and loan portfolio concentration.

It is analyzed that during the process of liquidity creation, IBANs in Pakistan faced more liquidity risk for both on and off-balance sheet transactions in the presence of moderation of loan concentration than IBANs in Malaysia necessitating strategic policy-making for important aspects of liquidity risk management and loan concentration while creating liquidity.

Such studies comparing IBANs and CBANs comparison keeping in view liquidity creation, liquidity risk and loan concentration are either limited or nonexistent.

The vehicle routing problem (VRP) has been widely investigated during last decades to reduce logistics costs and improve service level. In addition, many researchers have realized the importance of green logistic system design in decreasing environmental pollution and achieving sustainable development.

In this paper, a bi-objective mathematical model is developed for the capacitated electric VRP with time windows and partial recharge. The first objective deals with minimizing the route to reduce the costs related to vehicles, while the second objective minimizes the delay of arrival vehicles to depots based on the soft time window. A hybrid metaheuristic algorithm including non-dominated sorting genetic algorithm (NSGA-II) and teaching-learning-based optimization (TLBO), called NSGA-II-TLBO, is proposed for solving this problem. The Taguchi method is used to adjust the parameters of algorithms. Several numerical instances in different sizes are solved and the performance of the proposed algorithm is compared to NSGA-II and multi-objective simulated annealing (MOSA) as two well-known algorithms based on the five indexes including time, mean ideal distance (MID), diversity, spacing and the Rate of Achievement to two objectives Simultaneously (RAS).

The results demonstrate that the hybrid algorithm outperforms terms of spacing and RAS indexes with p-value <0.04. However, MOSA and NSGA-II algorithms have better performance in terms of central processing unit (CPU) time index. In addition, there is no meaningful difference between the algorithms in terms of MID and diversity indexes. Finally, the impacts of changing the parameters of the model on the results are investigated by performing sensitivity analysis.

In this research, an environment-friendly transportation system is addressed by presenting a bi-objective mathematical model for the routing problem of an electric capacitated vehicle considering the time windows with the possibility of recharging.

Health Information Exchange (HIE) is essential for the efficient and cost-effective delivery of health-care services. The provider’s administrative structure and external environment can substantially influence adopting technologies involving inter-organizational linkages, such as HIE. Using the theoretical lens of institutional theory, this study aims to compare how public and private hospitals' engagement in HIE is influenced by corruption and government online services or e-government usage.

The study uses the positivist research design of secondary data analysis to test the six hypotheses proposed. Data from multiple third-party reliable sources, including the European Commission and World Bank, are combined into the final dataset consisting of observations from 1,442 hospitals across 30 countries in Europe. A multilevel modeling approach is used to associate country and hospital-level variables and test the hypothesis.

The study finds that, on average, a 10% increase in corruption leads to a 6.3% decrease, while a 10% increase in e-government leads to a 7% increase in the probability of HIE engagement for a hospital. The negative impact of corruption on average is 18% more in public than private hospitals, while the positive impact of e-government is 75% stronger in public in comparison to private hospitals. The study also finds that HIE engagements in health systems with predominantly public hospitals are more sensitive to corruption and e-government.

To the best of the authors’ knowledge, the study is one of the first to use the institutional view to test the influence of government actions and public providers' concentration on HIE engagement. The comparison of public and private institutions enriches our understanding of promoters and inhibitors of HIE.

This paper aims to examine the association between income smoothing and the cost of debt in two different countries, namely, the UK and Nigeria.

The authors used a sample from listed firms in the UK and Nigeria during 2000–2019. The study hypotheses are examined by implementing quantitative methods, including panel regression analysis, cross-sectional regression analysis and parametric independent samples t-test.

The results reveal that Nigerian companies have a substantially higher cost of debt and are more active in using income-smoothing practices. However, the relationship between income smoothing and the cost of debt is not found to be statistically significant in both countries. Besides, the results of this study show that financial leverage, profitability, company size and asset turnover are significantly associated with the cost of debt.

The study contributes to the existing literature by providing new insights concerning the contrast between developed and developing countries in financial and reporting issues.

The aim is to assess how a policy of tertiary education for all affects the shape of the unconditional earnings distribution.

The paper discusses the quantile-regression literature looking at the link between education and wage inequality, also proving new evidence based on unconditional quantile regressions.

The findings support the idea that a policy of tertiary education for all increases the overall level of wage inequality.

The research has implications for public policy and administration. Among the limitations, the paper does not deal with distributional aspects related to other outcomes (e.g. health outcomes) of the policy of interest.

The analysis highlights a series of potential government interventions aimed at reducing the wage-inequality externalities of the policy of interest.

A policy of tertiary education for all, by itself, is not useful to fight wage inequality.

This paper belongs to the small group of studies using unconditional quantile regressions to study the link between education and wage inequality. It is the first study specifically looking at the distributional effects of a policy of tertiary education for all.

Teleworking seems to be the new future of the workplace. It has been widely adopted during the COVID-19 crisis, which has greatly influenced work organization conditions. This pandemic and its accompanying changes represent significant challenges for employees' performance, depending on their age if the study considers the physical and psychological vulnerabilities of older employees and their assumed or expected difficulties to cope with the new information and communication technologies (ICTs). This study aims at examining the direct effects of teleworking, and age on job performance (in-role). As well as analyzing the moderating effect of age on the relationship between teleworking and in-role job performance in times of crisis.

Data were collected in Canada from 18 companies, with a sample of 272 employees. Multivariate regression and moderation regression analyses were performed using Stata 13.

Results revealed that when teleworking, older age is associated with lower job performance and younger age is associated with higher job performance. Conversely, when working on-site, older age is associated with higher job performance, whereas younger age is associated with lower job performance.

From a practical perspective, these results highlight the importance of decision authority and recognition. As well as the presence of age disparities related to work arrangements. Managers need to adopt an inclusive approach and develop work arrangements that take into consideration employees' needs and ages. Some insights and practical recommendations are presented in this paper to support managers and human resource practitioners.

Studies examining the in-role job performance of teleworkers and the effects of age are sparse. This study helps to expand research on human resources management, job performance and age.

We evaluate the hypothesis of temporal stability in risk preferences using two recent data sets from longitudinal lab experiments. Both experiments included a combination of decision tasks that allows one to identify a full set of structural parameters characterizing risk preferences under Cumulative Prospect Theory (CPT), including loss aversion. We consider temporal stability in those structural parameters at both population and individual levels. The population-level stability pertains to whether the distribution of risk preferences across individuals in the subject population remains stable over time. The individual-level stability pertains to within-individual correlation in risk preferences over time. We embed the CPT structure in a random coefficient model that allows us to evaluate temporal stability at both levels in a coherent manner, without having to switch between different sets of models to draw inferences at a specific level.

The monetary policy implementation and corporate investment are closely intertwined. The aim of modern monetary policy is to mitigate economic fluctuations and stabilise economic growth. One of the ways of influencing the real economy is influencing the level of investment by enterprises.

This chapter provides evidence on how monetary policy affected corporate investment in Poland between 1Q 2000 and 3Q 2022. We investigate the impact of Polish monetary policy on investment outlays in contexts of high uncertainty.

Using the correlation analysis and the regression model, we show the relation between the monetary policy and the investment outlays of Polish enterprises. We used the least squares method as the most popular in linear model estimation. The evaluation includes model fit, independent variable significance and random component, i.e. constancy of variance, autocorrelation, alignment with normal distribution, along with Fisher–Snedecor test and Breusch–Pagan test.

We find that Polish enterprises are responsive to changes in monetary policy. Hence, the corporate investment level is correlated with the effects of monetary policy (especially with the decision on the central bank's basic interest rate changes). We found evidence that QE policy has a positive impact on Polish investment outlays. The corporate investment in Poland is positively affected by respective monetary policies through Narodowy Bank Polski (NBP) reference rate, inflation, corporate loans, weighted average interest rate on corporate loans.

This paper aims to assess gender bias in Italian university student mobility controlling for the field of study. It uses data from the Italian National Student Archive (Anagrafe Nazionale degli Studenti – ANS) for the cohort of freshmen enrolled in the 2017 academic year. The macro-regional comparison unfolds across the following areas: North and Centre, Southern Italy and main Islands (Sicily and Sardinia).

The analysis is firstly carried out at the national level, and secondly, it focusses on macro-geographical areas. University mobility choices are thus investigated from a gender perspective, conditioning upon other theoretically relevant characteristics collected for the prospective first-year university student population enrolled in 2017. The authors analyse data in a regression setting (logit models) within the multilevel framework, which considers students at level 1 and the field of study at level 2. Gender differences in the propensity to be a mover – conditional upon the choice of the field of study – were captured by introducing random intercepts to account for clustering of students in fields of study and random slopes to allow the gender effect to differ among them.

Findings show that university student mobility in Italy leads evidence of gender bias. This has been detected using a multilevel random slope approach that allowed the authors to jointly estimate a slope parameter for gender within each field of study. Moreover, using a regression setting allowed the authors to control for heterogeneity in geographical, educational and socio-demographic characteristics across students. In line with previous empirical findings, the authors' data highlight the presence of a relevant mobility flow of university students from the South toward the North-Centre of Italy and lower mobility of female students compared to male students from the South and Islands.

To the best of the authors' knowledge, there are no studies in Italy, which investigate if families' investment in higher education in terms of selection of no-local universities are affected by gender bias and if geographical differences in this behaviour between macro-areas are in place. Thus, investigating students' choices in tertiary education allows the authors to shed light on the presence of gender bias in families' education strategies addressed to increase the endowment of students' assets for future job opportunities.