Sürdürülebilir Kalkınma Amaçları

• 1
• 1

• MakaleYalnız künye2025Scopus SJRQ1/r/bayburt/11444
  Artificial 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.

  • 
  AtıfScopus5·WoS5·OpenAlex3

  İncele
• MakaleAçık Erişim2023Scopus SJRQ2/r/bayburt/12983
  Investigating the impact of ICT-trade nexus on competitiveness in Eastern and Western European countries

  Soylu, Özgür Bayram; Adeleye, Bosede Ngozi; Ergül, Murat; Okur, Fatih; Lorente, Daniel Balsalobre

  Purpose: Since competitiveness is crucial in international trade, this paper contributes to the literature by interrogating the information and communication technology (ICT)-trade nexus on competitiveness in Eastern and Western European countries. Does ICT usage promote or hinder the impact of trade openness on competitiveness? This study attempts to answer two questions: (1) is the interaction of trade and ICT significant in promoting competitiveness? (2) Is the effect significantly different by European classification? Design/methodology/approach: With data on 17 European countries from 2007 to 2020 and using mobile phones and fixed telephone usage as ICT indicators, the study engages the bootstrapped ordinary least squares (BOLS) and method of moments quantile regression (MM-QR) techniques to probe the discourse. Findings: The empirical findings reveal that (1) the interaction of trade and ICT boost competitiveness; (2) the effect of mobile phone is consistent across the full, East, and West European samples; (3) the interaction effect is also significant across the conditional distribution of competitiveness and (4) mobile phones and fixed broadband usage reveal “leapfrog” effect across the quantiles. Overall, the study submits that ICT usage will enhance the impact of trade, and thus, ICT is a critical enabler of competitiveness in Europe; policy recommendations were discussed. Originality/value: To the best of the authors' knowledge, this is the first study examining the interaction effect of trade openness and ICT usage on competitiveness in Europe. In other words, the authors attempt to analyze how ICT usage influences trade-competitiveness dynamics. To fill the gap in the literature, the authors' use a sample of 17 European countries from 2007 to 2020. The variables of interest are the competitiveness index, trade openness, and four ICT indicators (mobile phone, fixed telephone subscriptions, fixed telephone subscriptions, and Internet users).

  • 
  AtıfScopus16·WoS13·OpenAlex16

  İncele