Sürdürülebilir Kalkınma Amaçları
Yazarlar
Yayınlar
- MakaleYalnız künye2025Scopus SJRQ1Artificial intelligence, automation and employment dynamics: empirical evidence from G7 economies
Okur, Fatih; Özdemir, Enes
Purpose – This study examines how the rapid adoption of artificial intelligence (AI) and automation affects employment dynamics across G7 economies. While previous research has often focused on either AI or robotics in isolation, their combined and long-term effects on employment remain poorly understood. Addressing this gap is crucial for policymakers seeking to balance technological progress with labor market stability. Design/methodology/approach – Using a balanced panel dataset covering 2010–2024 for the G7 countries, the study investigates the relationships between AI investment (proxied by information and communication technology (ICT) investment), robot density (ROBOT), wages, productivity (PRD) and education spending (EDU), and their impact on employment. The analysis employs panel unit root and cross-sectional dependence tests, a panel autoregressive distributed lag (ARDL) framework estimated via the pooled mean group (PMG) estimator, and robustness checks using Driscoll–Kraay fixed effects, common correlated effects (CCE) estimators, country-specific regressions and Dumitrescu–Hurlin panel causality tests. Findings – The results reveal that AI investment has a significant negative effect on employment in the long run, whereas ROBOT shows a positive but context-dependent relationship. Wage levels are negatively associated with employment, while PRD shows only a modest positive influence. Education expenditure exhibits mixed behavior – positive in the short run but negative in the long run – suggesting potential misalignment with evolving labor market needs. Causality tests confirm a unidirectional link from AI investment to employment, underscoring its structural role in labor market change. Research limitations/implications – This study is limited by data availability, particularly the lack of detailed sectoral or occupational breakdowns across countries. As a result, it cannot fully capture the distributional effects of AI and automation across different worker groups. The use of proxies, such as ICT investment for AI, may not reflect the full scope of AI deployment. Despite these limitations, the findings highlight important macro-level dynamics and suggest that technological investments significantly shape employment trends. Future research should utilize micro-level data to explore sector-specific impacts, wage effects and labor force transitions in response to digital transformation. Practical implications – The findings suggest that without targeted policy interventions, increased AI investment may displace workers in the long run. Policymakers should prioritize reskilling, adapt education systems to evolving technological needs, and differentiate strategies across sectors and worker skill levels. Social implications – This study highlights the potential for AI and automation to reshape labor markets, with implications for income distribution, job security and social cohesion. The displacement of routine jobs may disproportionately affect low-skilled and vulnerable workers, increasing the risk of inequality and social exclusion. To prevent deepening divides, social policies must focus on equitable access to education, digital literacy and lifelong learning. Supporting workforce adaptability through inclusive training programs and social safety nets is essential. The results underscore the urgent need for collaborative efforts between governments, educational institutions and industries to ensure a socially sustainable digital transformation. Originality/value – This study is among the first to jointly analyze AI and robotics within a dynamic panel framework, offering new cross-country evidence on their heterogeneous employment effects in advanced economies. By integrating multiple estimation strategies and country-specific perspectives, the paper contributes to a more nuanced understanding of how technological transformation reshapes labor markets and highlights the institutional conditions that mediate these effects.
AtıfScopus5WoS5OpenAlex3
İncele - Kitap BölümüYalnız künye2022Discrimination in the Employment Process
Yurttas, Süleyman
Discrimination is a phenomenon that feeds on attitudes, prejudices and stereotypes, embodies itself with behaviors, and spreads to the whole of daily life. When business life and the recruitment process in particular are considered as a part of daily life, it can be said that it is “normal” to see discrimination practices here as well. Even in a very simple news search on the Internet, it is possible to see the problems experienced by individuals who are discriminated against in the recruitment process due to their age, religious belief, gender, sexual orientation, hometown or even pregnancy. This phenomenon, which is inevitably encountered in Turkey, also manifests itself in institutionalized companies. 900 thousand people are employed in the organized food retail market throughout Turkey. Employment is increasing by around 20 thousand every year (www.dunya.com). Chain stores such as A101, BIM and Sok operating in Turkey provide considerable employment in the organized food retail market. These companies, which increase their employment with their market shares, carry out their recruitment processes through regional managers. This shows that the discrimination practices that appear in recruitment have individual sources and that the attitudes, prejudices and stereotypes of the responsible person are effective. The aforementioned chain stores, which have great power in the Turkish market, increase the number employed day by day, and this situation also causes the discrimination potential to grow in the recruitment processes. Examining the recruitment processes carried out in these chain stores and revealing the discrimination practices will be beneficial in terms of both identifying the existing problems and taking the necessary measures to prevent discrimination. The aim of this study is to reveal the discrimination practices seen in the recruitment processes in chain stores. In the research, semi-structured interviews were conducted with the regional managers who are responsible for recruitment in the relevant chain store markets. In addition, the relevant literature has been included in order to reveal the relationship between recruitment processes and discrimination, and information about the recruitment processes of chain stores has been shared.