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This paper aims to investigate the nonlinear effects of bank regulation stringency on bank lending in 23 sub-Saharan African (SSA) countries over the period 1997–2017.

This study employs the dynamic panel threshold regression (PTR) model, which addresses endogeneity and heterogeneity problems within a nonlinear framework. It also uses indices of entry barriers, mixing of banking and commerce restrictions, activity restrictions and capital regulatory requirements from the updated databases of the World Bank's Bank Regulation and Supervision Surveys as measures of bank regulation.

The linearity test results support the existence of nonlinear effects in the relationship between bank lending and entry barriers or capital regulations in the selected SSA economies. The dynamic PTR estimation results reveal that bank lending responds positively when the stringency of entry barriers is below the threshold of 62.8%. However, once the stringency of entry barriers exceeds that threshold level, bank credit reacts negatively and significantly. By contrast, changes in capital regulation stringency do not affect bank lending, either below or above the obtained threshold value of 76.5%.

These results can help policymakers design bank regulatory measures that will promote the resilience and safety of the banking system but at the same time not bring unintended effects to bank lending.

To the best of the authors’ knowledge, this is the first study to examine the nonlinear effects of bank regulatory measures on bank lending using the dynamic PTR model and SSA context.

The study aims to estimate the short- and long-run effects of monetary policy on residential property prices in South Africa. Over the past decades, there has been a monetary policy shift, from targeting money supply and exchange rate to inflation. The shifts have affected residential property market dynamics.

The Johansen cointegration approach was used to estimate the effects of changes in monetary policy proxies on residential property prices using quarterly data from 1980 to 2022.

Mortgage finance and economic growth have a significant positive long-run effect on residential property prices. The consumer price index, the inflation targeting framework, interest rates and exchange rates have a significant negative long-run effect on residential property prices. The Granger causality test has depicted that exchange rate significantly influences residential property prices in the short run, and interest rates, inflation targeting framework, gross domestic product, money supply consumer price index and exchange rate can quickly return to equilibrium when they are in disequilibrium.

There are limited arguments whether the inflation targeting monetary policy framework in South Africa has prevented residential property market boom and bust scenarios. The study has found that the implementation of inflation targeting framework has successfully reduced booms in residential property prices in South Africa.

Exploring the intrinsic connection between the ecological environment and the digital economy and empirically testing how the level of digital economic development affects the ecological environment. Using the entropy weighting method to analyze the weights of the indicators in the digital economic development level and ecological environment system to explore the factors that have the greatest impact on the ecological environment in the indicator system of the digital economic development level so as to deepen the theoretical understanding of the relationship between the level of development of the digital economy and the ecological environment. Explore the regional heterogeneity of the level of development of the digital economy to promote the healthy development of China’s ecological environment proving the difference in the level of development of the digital economy in the east west and central regions of China and the difference in the effect on the ecological environment.

Based on the panel data of 30 provinces in China from 2013 to 2021 this paper fits the index system of digital economy development level with three factors. A digital infrastructure digital industry and digital application combines environmental pollution and energy consumption to construct ecological environment indicators and explored the impact of digital economy development level on the ecological environment by using the entropy weight method and the random effect model.

The findings indicate that the degree of digital economic development has a positive and significant impact on promoting the healthy development of the ecological environment, in which the digital industry has the greatest impact on the ecological environment. Meanwhile, the improvement of industrial structure also has a positive effect on the improvement of the ecological environment, whereas the level of human capital inhibits the healthy development of the ecological environment, and the governmental support fails to effectively and significantly promote the improvement of the ecological environment. Furthermore, the empirical research indicates that the level of digital economy development has obvious regional heterogeneity on the healthy development of the ecological environment: the eastern and central regions have a significant effect, while the western region has a less significant effect.

Although domestic and foreign scholars and experts have conducted sufficient studies on the ecological environment and the development level of digital economy respectively, there are few studies on the empirical analysis of the positive significance and regional heterogeneity of the impact of the development level of digital economy on the ecological environment, which can be supplemented and referred to in this study. At the same time, it also provides intellectual support for our country to achieve high-quality development of digital economy and efficient governance of ecological environment.

The study aims to examine how the information disclosed by the managers in the management discussion and analysis (MD&A) reports varies at the different levels of corporate performance.

To understand this quantile effect, first OLS technique was adopted and then, the quantile regression method was applied to explore the impact of MD&A disclosures on the firm performance across the lower and upper quantiles. The sample size for the study is 490 firms’ year observations for the period 2016–2022.

The results of the study demonstrate the negative but significant relationship between MD&A disclosures and corporate performance, supporting the two management strategies of “competitive disadvantage” in case of good performance and “management impression strategy” in case of poor performance. Furthermore, with other corporate governance variables, both the size of the board and the number of independent directors on the board are positively significant only in the case of the upper quantile indicating the heterogeneity in the relationship between the performance and the MD&A disclosures. Therefore, the overall findings of the study support that these results contradict the agency theory and the stakeholders’ theory as managers are not acting well as agents on behalf of the investors and work well only when they are controlled by the large board having more independent directors.

To the best of the authors’ knowledge, no study so far has incorporated quantile regression to assess the effect of MD&A disclosures on company performance at various levels of the firm performance, which gives more robust insights about the viewpoint of the managers on the different level of the firm performance. In other words, this study highlights the important information as to how the information provided in the MD&A reports varies as per the good or poor performance of the companies.

This study aims to analyse the impact of digital divide (DD) on income inequality in sub-Saharan Africa over the period 2004–2016.

In applying a finite mixture model (FMM) to a sample of 35 sub-Saharan African (SSA) countries, this study posits that DD affects income inequality differently.

The findings show that the effect of DD on income inequality varies across two distinct groups of countries, which differ according to their level of globalization. In addition, the study shows that most globalized countries are more inclined to be in the group where the effect of DD on income inequality is negative. The results are consistent with several robustness checks, including alternative measures of income inequality and additional control variables.

This study complements that extant literature by assessing linkages among the DD, globalization and income inequality in sub-Saharan African countries contingent on cross-country heterogeneity.

This paper aims to investigate the relationship between employee training and bank risk to verify whether and to what extent an increase in employee training, as a soft component of total quality management (TQM), affects bank risk.

The research adopts a panel regression, based on a unique dataset of a sample of Italian banks over the period 2011–2018, to test whether employee training affects bank risk, measured alternatively in terms of Z-score, a proxy of bank stability and non-performing loans (NPLs)/gross loans ratio as a proxy of credit risk.

Research findings reveal that increasing employee training leads to growing bank stability. In contrast, credit risk is not affected by employee training. However, by investigating training heterogeneity, this study found that the increase in the number of managerial training hours, as a proxy for soft skills training, negatively impacts credit risk. Therefore, an increase in soft skills leads to a reduction in bank credit risk.

This study provides empirical evidence in support of the relationship between employee training and bank risk, which seems novel in the literature. From a managerial point of view, this study highlights the need for banks to pay attention to the skills, particularly soft skills, that banks' employees must possess to effectively manage bank risk and, more specifically, the core bank risk.

Empirical evidence on the relationship between employee training, soft/hard skills and bank risk appears limited if not absent. Therefore, the findings provide insights for a more nuanced interpretation of variables that affect bank risk.

The goal of this paper is to examine the mediating role of organizational social capital between family firms' organizational culture, characterized by their group vs individual orientation and external vs internal orientation, and their performance.

A structural equation model is developed and tested in a sample of 176 US family firms recruited through Prolific Academic.

The authors show that group vs individual cultural orientation fosters bonding social capital, while external vs internal cultural orientation fosters bridging social capital. In turn, family firm performance is only enhanced by bridging social capital, not bonding social capital, which appears to have neutral to negative direct performance effects. Nevertheless, it is noteworthy that bonding social capital facilitates the establishment of bridging ties, leading to overall positive performance outcomes.

The understanding of how organizational culture influences family business heterogeneity and performance, along with the clarification of how bonding social capital fosters or hinders performance, provides novel insights for researchers and practitioners seeking to understand the complexities within the unique context of family businesses.

With new hybrid working models in place post COVID-19, it is requisite that knowledge workers (KWs) stay agile. Knowledge-oriented leadership (KOL) can help employees with essential knowledge acquisition (KA) facilitating the journey toward hybrid work agility (HWA). This study, thus, aims to explore the impact of KOL and KA on HWA and reveal whether this effect stems uniformly from a single homogenous population or if there is unobserved heterogeneity leading to identifiable segments of agile KWs.

Data was collected through stratified sampling from 416 employees from 20 information technology enabled services companies involved in knowledge-intensive tasks. Partial least squares (PLS) structural equation modeling approach, using SMART PLS 4.0, has been applied to examine the effect of KOL and KA on HWA. Finite mixture PLS, PLS prediction-oriented segmentation and multigroup analysis have been used to identify segments, test segment-specific path models and analyze the significance of the differences in the path coefficients for unobserved heterogeneity. Predictive relevance of the model has been determined using PLS Predict.

Results indicate that KOL contributes to employees’ KA and HWA. A significant positive relationship is also reported between KA and HWA. The model has medium predictive relevance. A two-segment solution has been delineated, wherein independent agile KWs (who value autonomy and personal agency over leadership for KA) and dependent agile KWs (who depend on leaders for relational and structural support for KA) have been identified. Thus, KOL and KA play a differential role in determining HWA.

The authors’ major contribution to the knowledge body constitutes the determination of antecedents of HWA and a typology of agile KWs. Future researchers may conduct segment-wise qualitative analysis to delineate other variables that contribute to HWA.

Technological advances necessitate that knowledge-intensive industries foster agility in employees for strategic agility of the organization. For effecting agile adaption of an organization to the knowledge economy conditions, it is pertinent that the full potential of this human resource be used. By profiling HWA of KWs on the basis of dimensions of KOL and the level of their KA, organizations will be able to help employees adapt better to rapidly changing work conditions.

HWA is a novel concept and very germane in a hybrid working environment. To the best of the authors’ knowledge, this is the first study to examine the effects of the dimensions of KOL and KA in relation to HWA, along with an empirical examination of unobserved heterogeneity in the aforementioned relationship.

Quality of life is a concern of banking customers, but it has received little attention in studies conducted within the banking context. This study aims to investigate the influence of mindfulness on customers’ quality of life and the mediating role of service value, satisfaction and loyalty to the company in this relationship.

Three hundred banking customers participated in the survey. In this study, partial least square structural equation modeling (PLS-SEM) was used to test the relationship between the variables. Then, complementary methods were used to assess the robustness of the PLS-SEM results.

In this study, it was found that mindfulness directly influences service value, satisfaction and quality of life. Service value was also found to directly influence satisfaction. Satisfaction directly influences loyalty to the company. In addition, loyalty to the company, but not satisfaction, directly influences quality of life. However, this study did not find any evidence that service value, satisfaction and loyalty to the company mediate the influence of mindfulness on quality of life.

Banking marketing managers need to ensure that their customers have an impressive moment-to-moment experience with the services provided to support improving their quality of life.

The findings help to advance the understanding of how banks can improve their customers’ quality of life while maintaining the well-being of other stakeholders.

La calidad de vida es una preocupación de los clientes de banca, pero ha recibido poca atención en los estudios realizados en el contexto bancario. Este estudio pretende investigar la influencia del mindfulness en la calidad de vida de los clientes y el papel mediador del valor del servicio, la satisfacción y la lealtad a la empresa en esa relación.

Trescientos clientes de banca participaron en la encuesta. Este estudio utilizó la modelización de ecuaciones estructurales por mínimos cuadrados parciales (PLS-SEM) para comprobar la relación entre las variables. A continuación, se utilizó métodos complementarios para evaluar la solidez de los resultados del PLS-SEM.

Este estudio halló que mindfulness influye directamente en el valor del servicio, la satisfacción y la calidad de vida. El valor del servicio también influye directamente en la satisfacción. La satisfacción influye directamente en la lealtad a la empresa. Además, la lealtad a la empresa, pero no la satisfacción, influye directamente en la calidad de vida. Sin embargo, este estudio no encontró pruebas de que el valor del servicio, la satisfacción y la lealtad a la empresa medien la influencia de mindfulness en la calidad de vida.

Los hallazgos ayudan a avanzar en la comprensión de cómo los bancos pueden mejorar la calidad de vida de sus clientes al tiempo que mantienen el bienestar de otras partes interesadas.

Los directores de marketing bancario deben asegurarse de que sus clientes tienen una experiencia impresionante en cada momento con los servicios prestados para apoyar la mejora de la calidad de vida de los clientes.

生活质量是银行业客户关心的问题, 但在银行业范围内的研究中, 它很少得到关注。本研究旨在研究正念对客户生活质量的影响, 以及服务价值、满意度和对公司的忠诚度在这种关系中的中介作用。

三百名银行业客户参与了调查。本研究采用偏最小平方结构方程模型（PLS-SEM）来检验各变量之间的关系。然后, 本研究使用补充方法来评估PLS-SEM结果的稳健性。

本研究发现, 正念直接影响了服务价值、满意度和生活质量。服务价值也被发现直接影响满意度。满意度直接影响到对公司的忠诚度。此外, 对公司的忠诚度, 但不是满意度, 直接影响了生活质量。然而, 本研究没有发现任何证据表明服务价值、满意度和对公司的忠诚度可以调解心态对生活质量的影响。

研究结果有助于推进人们对银行如何在保持其他利益相关者福祉的同时提高客户的生活质量的理解。

银行营销经理需要确保他们的客户对所提供的服务有令人印象深刻的时刻体验, 以支持改善客户的生活质量。

This article aims to investigate the financial constraints and nonlinearity of farm size growth.

Farm size growth is measured with land, labor and output using data from the Farm Accountancy Data Network (FADN) for Hungary and Slovenia. A dynamic panel model is applied to assess financial constraints and nonlinearity of farm size growth.

Results show that, except for land in Slovenia and output in Hungary, liquidity constraints are less important for farm size growth than endogenous factors based on farm size growth expectations and steady farm size restructuring. Smaller farms are growing faster than larger ones. The hypothesis that a higher level of subsidies would increase farm size is not supported for Hungary. When farms reach a certain size, the land area of the largest farms increases. Farm debts in Hungary are linked with land growth and in Slovenia with output growth.

Further research on the impact of liquidity constraints and subsidies can be conducted at a disaggregate farm-type level to examine whether there is variability in the underlying interlinkages at the farm-type specialization level.

The implication that farm size growth is dependent on initial size and that smaller farms are growing faster than bigger ones indicates that it is not necessary to favor the fastest growing smaller farms thus supports the application of a non-discriminatory farm size policy for observing farm size structural changes.

The dynamic panel econometric model that incorporates cash flow as a measure of financial constraints provides insight into farm size growth in cross-country comparison in relation to potential farm liquidity constraints, farm debt and the nonlinearity of farm size, which information is of relevance to policy makers and practitioners.