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Education system stimulates the development of human capital and provides informative signaling allowing to differentiate productivity of individuals. If education system is efficient then higher levels of education usually associated with greater returns on labor market. To evaluate the efficiency of Russian education system we aim to estimate the effect of vocational education and different levels of higher education on wages.

We use data on 8,764 individuals in the years 2019–2021. Our statistical approach addresses two critical issues: nonrandom selection into employment and the endogeneity of education choice. To tackle these problems, we employed Heckman’s method and its extension that is a structural model which addresses the issue of self-selection into different levels of education.

The results of the analysis suggest that there is a significant heterogeneity in the returns to different levels of education. First, higher education, in general, offers substantial wage premiums when compared to vocational education. Specifically, individuals with specialist’s and bachelor’s degrees enjoy higher wage premiums of approximately 23.59–24.04% and 16.43–16.49%, respectively, compared to those with vocational education. Furthermore, we observe a significant dis-parity in returns among the various levels of higher education. Master’s degree provides a substantial wage premium in comparison to both bachelor’s (19.79–20.96%) and specialist’s (12.64–13.41%) degrees. Moreover, specialist degree offers a 7.16–7.55% higher wage premium than bachelor’s degree.

We identify a hierarchical pattern in the returns associated with different levels of higher education in Russia, specifically “bachelor-specialist-master.” These findings indicate that each level of education in Russia serves as a distinct signal in the labor market, facilitating employers' ability to differentiate between workers. From a policy perspective, our results suggest the potential benefits of offering opportunities to transition from specialist’s to master’s degrees on a tuition-free basis. Such a policy may enhance access to advanced education and potentially lead to higher returns for individuals in the labor market.

There are many studies on returns to higher education in Russia. However, just few of them estimate the returns to different levels of higher education. Also, these studies usually do not address the issue of the endogeneity arising because of self-selection into different levels of education. Our structural econometric model allows addressing for this issue and provides consistent estimates of returns to different levels of education under the assumption that individuals with higher propensity to education obtain higher levels of education.

This study aims to examine the relationship of Indonesia’s Sharia Stock Index (ISSI) firms on environmental, social and governance (ESG) disclosure. This study is interesting because ISSI firms are supposed to comply with Islamic values as this has been reflected in good corporate governance activities, demonstrating responsibility to others and participating in preserving nature/environmental activities.

The authors use sample firms that are listed on the Indonesia Shariah-compliant Stock Index (ISSI) from 2011 to 2020, which also published sustainability reports.

The study found that sharia firms are positively related to ESG disclosure. The authors also found that ESG disclosure of sharia firms is more pronounced in the reporting section of general, economic, environmental and social. Other findings suggest differences in the segments reported in the COVID and pre-COVID periods. This result is also robust by conducting a self-selection bias test with Heckman’s two-stage regression and Coarsened Exact Matching regression.

For policymakers, these results indicate that different characteristics of firms can affect ESG disclosure, and economic conditions will determine which sectors are disclosed the most.

This study provides empirical evidence that Indonesian Shariah-compliant stock index firms carried out their mission to disclose more information about their environmental and social responsibilities and governance issues.

This study aims to explore the effects of long-term orientation (LTO) and strategy formation mode on corporate social responsibility. While many researchers have investigated how large businesses address corporate social responsibility (CSR), there is little empirical evidence on how small- and medium-sized businesses implement CSR or what individual drivers shape this process.

The paper surveyed 282 small and medium-sized managers from the United Kingdom. The respondents were recruited using platform Prolific Academic.

The findings reveal that LTO is a prerequisite for developing CSR and shapes strategy formation mode. The findings also suggested that deliberate strategies are positively related to CSR. The results are consistent across different components of LTO (futurity, continuity and perseverance) and CSR types (internal and external).

The results show that all aspects of LTO are relevant for CSR in SMEs. Besides LTO, deliberate strategy formation model is an important factor contributing to CSR. The paper presents as first an empirical contribution to the strategy literature by examining positive relationship between LTO and deliberate strategy formation mode.

This study examines the impact of the Association to Advance Collegiate Schools of Business (AACSB) accreditation on education quality. We discern the prospective influences of AACSB, focusing on shifts in teaching methods and content and assessment procedures.

Using a case study approach, in-depth interviews are conducted with a Japanese-accredited business school’s faculty members to understand their perceptions of the school’s education-quality issues. The data were thematically analyzed.

Respondents acknowledged that AACSB accreditation has positively influenced teaching, encouraging active learning and the case method. However, they also indicated that accreditation had a restrictive effect on assessment activities, pushing toward compliance rather than genuine learning evaluation. This dichotomy suggests a need for balancing standard adherence with the flexibility to maintain educational depth and assessment integrity.

Convenience sampling may introduce self-selection bias. Furthermore, the qualitative case study approach does not allow for statistical generalization. However, when combined with existing literature, the findings can be analytically generalized and transferred to other contexts.

We provide insights regarding AACSB accreditation’s impact on business education, encompassing shifts in teaching methods and content and faculty perceptions of assessment. This study enhances the scholarly understanding of business school accreditation and offers guidance to accredited or accreditation-seeking academic institutions.

Efforts to reduce farmers' market risks and improve buyers' access to farm commodities have encouraged contract farming (CF) in Ghana's cashew sector in recent years. Consequently, the existence of CF shows that farmers who use it may be benefiting from it, as it is their economic responsibility to decide how to sell agricultural products. However, the magnitudes of these benefits or otherwise have been inadequately explored. This paper aims to empirically estimate the impact of CF on farm performance and welfare of smallholder cashew farmers.

The study used probit-two-stage least square (probit-2sls) as a primary estimator to account for self-selection bias and endogeneity that could arise from both observed and unobserved heterogeneities among farming households to estimate the causal effects of CF on farm performance and household welfare.

The results indicated that participation in CF contribute significantly to the gains in farm performance (price margins, yields and net farm revenue) and welfare (consumption expenditure per capita), and that the non-participants of CF would have benefited substantially if they had participated. An analysis of the farm size disaggregated into small, medium and large with regards to the outcome variables produces mixed results.

It can be concluded that participating in CF enhances farm performance and household welfare.

While many other studies do not account for changes in farm performance and welfare due to differences in farm size or other observed factors, this study fills a crucial void.

This paper aims to examine the impact of the COVID-19 pandemic on the private label food products, specifically assessing the stability and changes in factors influencing purchasing decisions, and comparing pre-pandemic and post-pandemic datasets.

The study employs the Extra Tree Classifier method, a robust quantitative approach, to analyse data collected from questionnaires distributed among two distinct consumer samples. This methodological choice is explicitly adopted to provide a clear classification of factors influencing consumer preferences for private label products, surpassing conventional qualitative methods.

Despite the profound disruptions caused by the COVID-19 pandemic, this research underscores the persistent hierarchy of factors shaping consumer choices in the private label food market, showing an overall stability in consumer behaviour. At the same time, the analysis of individual variables highlights the positive increase in those related to product quality, health, taste, and communication.

The use of online surveys for data collection may introduce a self-selection bias, and the non-probabilistic sampling method could limit the generalizability of the results.

Practical implications suggest that managers in the private label industry should prioritize enhancing quality control, ensuring effective communication, and dynamically adapting strategies to meet evolving consumer preferences, with a particular emphasis on quality and health attributes.

This study contributes to the existing body of literature by providing insights into the profound transformations induced by the COVID-19 pandemic on consumer behaviour, specifically in relation to their preferences for private label food products.

This study aims to examine the impact of consumer risk appetite, biases (specifically negative recency bias), and the importance of reviews in enhancing information quality. By analyzing these variables, the authors gain insights into their role in enriching the overall information spectrum available to consumers. The findings contribute to a better understanding of how risk appetite, biases and consumer reviews shape the quality of information.

The questionnaire assessed the relationship between dependent and independent variables by asking participants to rate their experiences in relevant scenarios. Variance-based structural equation modeling with the ADANCO program was used to examine the data. ADANCO software is used explicitly for variance-based structural equation modeling. To evaluate research models and test hypotheses, partial least square path modeling is used.

The efficiency of reviews and ratings is greatly influenced by consumer risk appetite. Businesses should focus on clients who are willing to take risks and balance positive and negative feedback. It is essential to comprehend how customers understand reviews. Credibility is increased by taking biases into account and encouraging unbiased criticism. Promoting thorough reviews strengthens influence. Monitoring and making use of these elements improve online reputation and commercial success.

The research has limitations due to the simplicity of the attributes taken into account and the requirement for a larger sample size. Overcoming barriers to promote consistent client feedback is essential, and tailored emails can help with assessment generation. Increased customer participation in writing evaluations can be achieved by removing obstacles and highlighting the advantages of participation.

Businesses and buyers rely on this “organically” generated content as the basis of their promotional strategy and buying decisions. Most of the research is related to consumer reviews, their behavior and the importance of social validation. However, some critical aspects related to this need further investigation.

The purpose of this study is to examine the impact of industry specialization of audit partners and audit committee members on the level of tax avoidance in Australian banks.

This study uses a multivariate regression analysis based on hand-collected data consisting of 180 observations from Australian domestic banks between 2010 and 2018.

The primary results of the empirical analysis indicate that audit partner industry specialization is negatively associated with the level of tax avoidance in Australian banks. Regarding the audit committee, the proportion of industry specialists among audit committee members reduces the magnitude of tax avoidance. These results are robust, as they hold the same for alternative measures of tax avoidance and industry specialization of audit partner and audit committee members. Results from supplementary analysis reveal that the interactive effect of both audit firm and audit partner industry specialization strengthens the auditors’ effectiveness in reducing the level of tax avoidance.

As this study highlights the importance of the industry specialization in decreasing tax avoidance, it can be beneficial for policymakers to assess the impact of good governance on the level of tax avoidance in the banking industry.

Even though the existing studies examine the link between the governance actors’ industry specialization and tax avoidance in nonfinancial firms, this paper explores the banking industry that differs from nonfinancial firms in among others; accounting and fiscal regulations. This study further provides unique evidence indicating that industry specialization of the audit partner constitutes a significant determinant of minimizing the bank’s level of tax avoidance.

Corporate digital transformation (CDT) has challenged traditional tax administration systems. This study examines the impact of CDT on tax avoidance behavior and tests whether tax authorities can identify this behavior.

Using data on listed companies on the Shanghai and Shenzhen Stock Exchanges from 2008 to 2020, this study applies the Heckman two-stage and cross-section models.

The results show that the higher the degree of CDT, the more aggressive the tax avoidance behavior. The CDT's impact on corporate tax avoidance is more significant under strong government tax efforts.

This study expands research on the economic consequences of CDT and the factors influencing corporate tax avoidance behavior. Moreover, it has important implications for governments to monitor tax avoidance behavior under the CDT, improve digital tax systems, and pay more attention to the tax administration of digital assets.

Considering rapid digitalization development, this study examines the impacts of digital technology innovation on social responsibility in platform enterprises.

The study applies the event study method and cross-sectional regression analysis, taking 168 digital technology innovations for social responsibility issued by 88 listed platform enterprises from 2011 to 2022 to study the impact of digital technology innovations for social responsibility announcements of different announcement content and platform attributes on the stock market value of platform enterprises.

The results show that, first, the positive stock market reaction is produced on the same day as the digital technology innovation announcement. Second, the announcement of the platform’s public social responsibility and the announcement of co-innovation and radical innovation bring more positive stock market reactions. In addition, the announcements mentioned above issued by trading platforms bring more positive stock market reactions. Finally, the social responsibility attribution characteristics of the announcement did not have a significant differentiated impact on the stock market reaction.

Most scholars have studied digital technology innovation for social responsibility through modeling rather than second-hand data to empirically examine. This study uses second-hand data with the instrumental stakeholder theory to provide a new research perspective on platform social responsibility. In addition, in order to explore the different impacts of digital technology innovation on social responsibility, this study has classified digital technology innovation for social responsibility according to its social responsibility and digital technology innovation characteristics.