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This paper investigates the impact of quasi-exogenous and substantial increases in the minimum wage on child labor outcomes in Türkiye. The study aims to provide empirical evidence on how minimum wage policies affect child labor outcomes in a developing country context, with a focus on gender and age differences. It seeks to understand whether minimum wage increases lead to a reduction in child labor and whether the impact is different for various demographic groups.

The research employs a difference-in-differences methodology using data from the 2012 and 2019 Child Labor Force Survey in Türkiye. The treatment group consists of children from households with minimum wage earners, while the control group comprises children from other households. Various labor market outcomes are analyzed, and robustness checks are performed.

Our findings indicate that while the overall effect of minimum wage increases on child labor is statistically insignificant, there are notable heterogeneous impacts across different demographic groups and employment sectors. Specifically, we observe a significant reduction in the employment probability of girls under the age of 15 and unpaid family workers. Additionally, the likelihood of younger children being wage earners decreases, and the minimum wage increase reduces employment in the agriculture and services sectors for certain subgroups. The impact is also more limited for children in single-adult-worker households.

These results underscore the varying effects of minimum wage policies on child labor and highlight the importance of considering demographic and sectoral differences in policy formulation. Policymakers should complement such policies with income-generating programs and targeted education initiatives to address child labor issues more comprehensively and sustainably.

This study fills a critical gap in the limited international literature on the causal effects of minimum wage policies on child labor incidence. One notable exception, Menon and van der Meulen Rodgers (2018) have explored the impact of minimum wage on child labor in India using regional variation, our study uniquely analyzes the effects at the household level in Türkiye. This approach provides valuable insights into how minimum wage changes affect child labor outcomes in a developing economy context with a high prevalence of minimum wage earners. It also contributes to the broader economic understanding of child labor and household income dynamics.

Technostress reduces employees' work performance and increases their turnover intentions, such that technostress harms organizations' success. This paper investigates how the digital mindset of employees, reflecting their cognitive filter while using digital technologies, influences reactions to techno-stressors.

In this quantitative study, the authors conducted a survey among 151 employees who regularly use digital technologies and encounter various techno-stressors in their daily work. To build this research model and evaluate the influence of employees’ digital mindset on technostress, the authors followed arguments from the transactional model of stress. The authors evaluated our research model using the covariance-based structural equation model.

The study findings reveal that employees’ digital mindset influences technostress. Employees with high levels of digital mindset react with less adverse effects on perceived techno-stressors. Further, the authors find that employees with high levels of digital mindset perform well and are satisfied with their job. The authors contribute to technostress research by revealing that digital mindset buffers the adverse effects of techno-stressors. The authors also contribute to research on digital mindset by showing that it influences psychological and behavioral reactions to techno-stressors.

This study develops and empirically tests an integrated model of technostress to explain how digital mindset mitigates technostress. The study findings outline relevant research avenues for studies investigating employees’ characteristics and technostress.

After the COVID-19 epidemic, educational paradigms experienced radical changes, especially in the way that architecture was taught. This chapter explores how architecture education evolved because of the current economic crisis, and how COVID-19 has affected instructional approaches. The main goal is to expose emerging educational strategies and their consequences for encouraging flexibility and resilience in architectural instructors and students. The study used a mixed-methods research methodology to gather information from stakeholders, educators, and students of architecture by combining document analysis of academic theses and publications with semi-structured interviews. Data analysis techniques such as thematic coding and pattern recognition revealed distinct categories of influencing factors, such as technological advancements, pedagogical modifications, student engagement and support, curriculum changes, faculty development, resource allocation, assessment and evaluation, as well as global and cultural considerations. The results highlight the varied and dynamic character of the pandemic’s effect. The crisis sparked a faster adoption of digital technologies, bringing forth blended learning and novel pedagogical approaches. As a significant result, resilience helped instructors and students overcome uncertainty by enhancing flexibility and using transdisciplinary methods. It also demonstrates how architectural education has persevered in the face of the COVID-19 epidemic and has the potential to spur larger changes in education. The possibility of sample bias and the crisis’s dynamic character are limits, though. Future research might examine the long-term effects of these emerging methods beyond crisis situations to expand the study’s results and influence the ongoing development of architectural pedagogy in a continuously changing global environment.

While there is some evidence of a relationship between earnings quality and information asymmetry, there is limited evidence on the moderating role of institutional investors in this relationship. To fill this gap, this study aims to examine how institutional ownership affects the relationship between earnings quality and information asymmetry, with a focus on the impact of different investment horizons.

This study uses a sample of listed European firms from 2000 to 2022. Earnings quality is measured using the McNichols (2002) modification of the Dechow and Dichev (2002) model. The analysis examines the moderating effect of institutional ownership on the relationship between earnings quality and information asymmetry.

This study finds that the relationship between earnings quality and information asymmetry is more pronounced in firms with a higher percentage of institutional ownership. This study finds that the monitoring role of long-term institutional investors is more effective than that of short-term institutional investors. This study also finds that the influence of institutional investors is more significant in firms with incentives to engage in earnings management.

The findings provide evidence suggesting that institutional investors are an important class of investors in terms of exercising an effective monitoring role to mitigate information asymmetry and demand higher earnings quality from their investee firms. These findings are informative for many financial reporting participants, including investors, analysts, regulators and managers.

This study extends the existing research examining the relationship between earnings quality and information asymmetry (e.g. Affleck-Graves et al., 2002; Ascioglu et al., 2012; Bhattacharya et al., 2013; Jayaraman, 2008; Liu and Elayan, 2015) by examining the moderating effect of institutional ownership on this relationship. It further contributes to the literature by distinguishing between long- and short-term institutional investors and their respective monitoring roles. In addition, this study broadens the geographical scope of the research by using cross-country data from European firms, providing evidence that country-specific factors do not uniformly affect the relationship between earnings quality and information asymmetry.

This research aims to investigate the interplay between individuals’ health status and their level of trust in both smart health-care systems and health-care providers and how these factors influence the decision to use such systems.

Drawing upon institution-based trust and affordance theories, the authors developed and empirically examined a research model using a sample from a prominent US university.

The findings reveal that both types of trust, specifically trust in smart health-care systems and trust in health-care providers, positively influence the intention to use these systems. Additionally, the authors identified that health status plays a dual moderating role in this context. It positively moderates the relationship between trust in health-care system providers and the intention to use, suggesting that individuals with better health are more inclined to use smart health-care systems when trust in providers is high. Conversely, health status negatively moderates the relationship between trust in the system and the intention to use it. This implies that trust in the system exerts a more pronounced influence on the intention to use the system among individuals with lower health status. This heightened impact can be attributed to the increased necessity for the system’s benefits among this group.

While the power analyses suggest our sample size is sufficient, caution is warranted when interpreting the study’s conclusions. These results have substantial implications for researchers and providers of smart health-care systems. They underscore the intricate dynamics between trust, health status and technology use, offering valuable insights for future investigations in this domain. Furthermore, they guide the design and implementation of smart health-care systems, emphasizing the need to consider the nuanced influence of health status on trust and use intentions.

Past research has focused on individuals’ trust in understanding the adoption of smart health-care systems; however, it did not consider how individuals’ health status can moderate their trust and intention to adopt such systems. In this study, the authors close this gap by investigating the moderating role of health status in the relationships between two types of trust and intention to use smart health-care systems through the lens of institution-based trust theory and affordance theory.

This paper examines the relationship between tax avoidance and accounting comparability. The authors argue that aggressive tax behavior impairs the comparability of financial statements by altering the accounting function, which maps economic events into accounting data.

The empirical analysis is based on a large sample of United States (US) firms. The authors use raw and industry-adjusted effective tax rates (ETRs) to proxy tax avoidance. The authors use the measure of accounting comparability developed by De Franco et al. (2011), which aims to capture the similarity of the accounting function.

The authors find that firms with more aggressive tax avoidance strategies have substantially lower accounting comparability. The evidence also shows that the negative effect of tax avoidance on accounting comparability is driven by firms with aggressive tax planning strategies beyond the industry norm. Furthermore, using an alternative measure of accounting comparability as a function of pre-tax income, the authors continue to find evidence of the negative effect of tax avoidance behavior. Importantly, this provides evidence that the effect of aggressive tax planning is not limited to the reported tax expense, but affects the comparability of the overall financial reporting system.

The authors identify a new potential cost of tax aggressive activities, being the loss of accounting comparability as driven by tax aggressive activities. The results contribute to the literature on the costs of tax avoidance and on the determinants of accounting comparability.

The purpose of this paper is to develop a commercialization model based on gaining economic benefits through the transfer of technological capabilities in the oil and gas industry. Since commercialization models are mostly based on the implement of technology to produce and sell new products, this study focuses on developing a specific independent technology commercialization model.

The method of this research is qualitative based on the grounded theory. For this purpose, general variables with content analysis were extracted by reviewing documents (Literature review) and then for identifying special components, interviewing experts in the Iranian oil and gas industry. Participations were selected using snowball sampling for semistructured interviews.

The findings of this research were extracted based on grounded theory with data analysis in MAXQDA software. In this research, first, 210 open codes were identified based on qualitative content analysis of relevant documents and results of interviews with experts. Then the classification of open codes was done, and 46 subcategories (variables) were determined in the commercialization model. Finally, 46 subcategories were classified into 10 categories as axial codes in grounded theory as components of the commercialization model.

The results of this research have led to the creation of new practical and theoretical implications. In this research, a new perspective of commercialization with the aim of transferring technology and obtaining its economic benefits for oil and gas industry companies was discussed. Also, based on the practical implications explained in this research, policymakers can use the suggested model to effectively implement independent technology commercialization to acquire economic benefits.

This study is purely original and the outcome of the research conducted by the authors. The research findings are the outcome of in-depth study on technology commercialization in the Iranian oil and gas industry.

The purpose of this study is to shed light on the job resources and demands of employees working in virtual teams and the impact of these job factors on their work engagement levels. Specifically, the authors focus on identifying the differing significance of employee job resources and demands on their virtual work engagement levels.

A qualitative approach grounded on abductive analysis is used to arrive at the findings. The methods for data collection include participant observation and semistructured interviews of 27 software engineers in the Indian information technology sector, working with virtual teams.

The authors identified the virtual-work-induced job demands and resources. Primarily, the authors found 14 job factors related to high and low levels of individual virtual work engagement, and classified them under eight aggregate dimensions: psychosocial hurdles, collaboration challenges, leadership and operational issues, dehumanization under job demands, supportive leadership, personal resources, alternate sources of income and learning goal orientation under job resources. Consequently, the authors built an importance–frequency work engagement map based on how these job factors are related to low and high levels of work engagement.

This study’s qualitative nature limits the generalizability of the findings. Hence, further studies are encouraged to corroborate the findings. There is also a possibility of the social desirability bias that could have affected the results as participants may have perceived an element of risk in sharing all their honest feelings and perceptions. This may have especially been the case for those with higher status or positions in the company.

The findings suggest practical measures either to engage employees in their free time or to improve loyalty. There is a clear potential for the organization and virtual leader to communicate effectively about the expected goals, arrange informal interactions and reduce scrutiny of monitoring, thereby increasing the remote workers’ resources.

The originality of this study comes from multiple factors. First, the authors highlight ta contextual adaptation of the job demands-resources (JD-R) model into a virtual team context. By extension, the authors examine “how much” does both the job resources and demands contribute to the wellbeing of the employees working in virtual teams. Second, the authors construct an importance–frequency work engagement map (specifically for the virtual work context) based on the findings, which categorizes the observed resources and demands into four quadrants. The authors propose that this map could be a possible extension to the JD-R model, highlighting the differing significance of each resource and demand to employee work engagement.

In light of the inequality in access to farming land and the high prevalence of child malnutrition in Sudan, there is a lack of empirical research on the relationship between land ownership and child nutritional status. This study aims to examine the influence of agricultural landholding on the nutritional status of children under the age of five in rural Sudan.

The study utilizes data from Sudan’s 2014 Multiple Indicator Cluster Survey (MICS), covering a sample of 10,753 rural children. The empirical analysis uses the two-stage least squares (2SLS) approach, adopting various estimation methods and model specifications for robustness check and comparison.

The results demonstrate that agricultural land has a positive and significant effect on reducing child malnutrition, signifying that children from families with agricultural land are less susceptible to malnutrition in Sudan. When examining the male and female sub-samples separately, the findings indicate a positive influence of land ownership on child malnutrition in the female sub-sample, while no significant impact is observed in the male sub-sample. This indicates a gender disparity in the effects of land ownership on child nutrition, with girls benefiting more from access to agricultural land compared to boys.

The study has several significant contributions. First, this is the sole study that examines the impact of agricultural land ownership on child malnutrition in Sudan. Second, considering the gender variations in nutritional status, investigating the influence of land ownership on child nutrition across genders addresses a significant gap in the current literature. Finally, the findings resulting from this study can contribute to achieving the United Nations Sustainable Development Goals (SDGs) to be achieved by 2030, precisely focusing on SDG2 Goal 2: Zero hunger and SDG 10: Goal 10: Reduced inequalities.

This study aims to examine the role of employee experience in influencing employee well-being and turnover intentions within organizations. The mediating role of well-being will also be investigated, along with an exploration of whether these relationships differ across genders, specifically in the Indian corporate context.

A descriptive, quantitative study was conducted using structured questionnaires to gather data from 111 employees in the Indian corporate sector. The study used a non-probability judgment sampling method. Data was analyzed through SPSS for descriptive and inferential statistics, and partial least squares was used to explore mediation and model fit.

The study found a significant impact of employee experience on well-being, as well as a negative correlation between both employee experience and turnover intention and well-being and turnover intention. Well-being was found to partially mediate the relationship between employee experience and turnover intention. Gender-based analysis revealed no significant differences in the relationships between these variables for men and women.

This research highlights the universal applicability of employee experience as a predictor of well-being and turnover intention, irrespective of gender. By establishing that gender does not moderate these relationships, this study provides new insights challenging traditional assumptions about gender disparities in workplace outcomes.