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This paper investigates the impact of trade liberalization measured by trade openness (OPN) and tariffs on women empowerment measured by the gender gap index and gender development index, for two groups of Arab countries divided based on their income levels using annual data for the period 1995–2020. The study also considers other factors that may influence the gender gap, such as GDP growth and the female unemployment rate. The purpose of this paper is to address these issues and explorers whether the effects of trade liberalization differ based on the countries' income levels.

This study employs the fully modified ordinary least squares (FM-OLS) regression model for heterogeneous cointegrated panels to examine the impact of trade liberalization on women empowerment. The study constructs an empirical two regression model of women empowerment measured by the gender gap model and gender development model for the two groups of higher-income countries and lower and middle-income countries.

The authors’ findings reveal that the impact of OPN on the gender gap varies between the two groups of Arab countries where more OPN within the higher-income group may increase the gender disparity, while it may reduce disparity within the lower and middle-income countries. In addition, GDP growth may reduce the gender disparity, while female unemployment raises the gender disparity between the two groups of countries in the long run. Findings also reveal that more OPN, tariffs and female unemployment may reduce gender development within the two groups, but more GDP growth may support the gender development in the long run.

This paper not only assesses the impact of trade liberalization on women empowerment generally, but also assess the women empowerment via two indices that are the gender gap and gender development in Arab countries which is – to the knowledge of the researchers – not yet investigated; further it explores if the effects of trade liberalization differs based on the countries' income levels.

Previous research assumes that technologies 4.0, particularly big data, may be highly relevant for organizations to increase human resources (HR) communication strategies, but the research provides little or no evidence on whether and how these tools are applied in employees and labor market relations. This study intends to offer a first insight on the adoption of data-driven HR/talent management approach, contributing to the ongoing debate on the Industry 4.0. This study aims to investigate the use of 4.0 technologies in HR and talent management functions, focusing also on the adoption of big data analytics for internal and recruitment communication.

The analysis of the literature enables to define the research questions and an exploratory web survey was carried out through a structured questionnaire. The analysis unit of the empirical survey includes the communication and marketing managers of 90 organizations in Italy, examined in the Mediobanca Report on the “Main Italian Companies.”

Findings highlight a lack of the use of 4.0 technologies and big data analytics in employee and labor market relations and reveal some sectoral differences in the adoption of 4.0 technologies. Moreover, the study points out that the development of HR analytics is hampered by short-term perspective, data quality problems and the lack of analytics skills.

Due to the exploratory research design and the circumscribed sample from a single country (Italy), further cross-national evidence is needed. This study provides digital communication managers with useful insights to improve the data-driven HR/talent management approach, which is a strategic asset for ensuring a sustainable competitive advantage and optimizing business performance.

The study offers an overview about the use of big data analytics in internal and recruitment communications. Considering the alignment between Italian and European trends in the use of big data and in the adoption of HR analytics, the study can provide insights also for other European organization.