Human-centric and ecosystem-based approaches to human resource management (HRM) have gained increasing attention in public administration reform, particularly in transitional states. However, large-scale empirical evidence remains limited, especially in Central Asia. This study investigates the individual and institutional determinants of perceived HRM quality in Kazakhstan’s civil service and examines why the adoption of artificial intelligence (AI) remains constrained. Using a nationally representative survey of 12,562 civil servants conducted in June 2025, the analysis employs ordinary least squares regression with heteroskedasticity-robust standard errors and binary logistic regression. The findings show that perceived HRM quality is driven primarily by access to education and training, public service motivation (patriotism), and participation in innovative projects, with the model explaining 39.8% of the variance. In contrast, AI adoption is influenced more by organisational position and institutional access than by individual motivation. Managers are substantially more likely to use AI tools, whereas women and longer-tenured civil servants exhibit lower adoption rates. Notably, 44% of respondents report wanting to use AI but lacking access, pointing to a significant implementation gap. The study makes three principal contributions. First, it provides the first large-scale empirical assessment of the ecosystem-based and human-centric HRM framework in a post-Soviet context. Second, it demonstrates that the AI adoption gap is primarily structural rather than motivational. Third, it translates these empirical findings into actionable policy recommendations. The results suggest that narrowing the AI aspiration gap and creating more transparent and accessible career pathways should constitute key priorities for civil service reform, requiring coordinated system-level interventions rather than isolated organisational initiatives.
This study investigates whether public-sector digitalisation is associated with real GDP per capita growth in the EU-27 and whether this relationship depends on time dynamics and governance quality. The analysis combines two measures of digital government development: a behavioural indicator capturing the share of individuals interacting online with public authorities (Eurostat), with adjustments for the 2021-2022 series break, and the Public-Sector Digital Capacity Index (PSDCI), developed from the eGovernment Benchmark dimensions for a shorter panel. The empirical strategy applies two-way fixed-effects models with country and year effects, including lagged specifications, an interaction between digitalisation and Government Effectiveness (WGI), and robustness checks using Driscoll-Kraay standard errors and placebo lead tests. The findings show no statistically significant average contemporaneous relationship between e-government use and economic growth. PSDCI estimates are positive but remain statistically uncertain due to the limited time dimension. However, when lagged effects and institutional conditions are considered, a relationship between digitalisation and growth becomes evident, particularly at lower levels of governance effectiveness. The results suggest that public-sector digitalisation does not automatically translate into higher economic growth. Its contribution depends on the timing of effects, the measurement approach, and the institutional environment in which digital reforms are implemented. These findings highlight the importance of considering governance capacity and dynamic effects when evaluating the economic impact of digital government transformation.
The reconfiguration of global supply chains has renewed debate on the macroeconomic implications of global value chain (GVC) integration. This study examines the relationship between GVC exposure and growth volatility in G20 economies from 1995 to 2023. Macroeconomic vulnerability is measured by the rolling standard deviation of real GDP growth, while GVC exposure is proxied by the foreign value-added content of exports. Trade openness is included to distinguish the effects of supply chain integration from broader international trade exposure. Using a fixed-effects panel model with country and time effects, the analysis controls for structural differences and common global shocks. The findings suggest that GVC integration and trade openness primarily transmit external shocks rather than independently generate macroeconomic instability. The results underscore the importance of supply chain diversification, domestic productive capacity, and credible stabilization policies in strengthening economic resilience.
Water scarcity has become one of the most serious structural constraints on development in the Middle East and North Africa, or MENA. Despite substantial investment in supply-side technologies, including groundwater development, irrigation modernization, desalination, and wastewater reuse, regional water stress remains persistently high. This study examines whether these technological responses reduce water stress or whether their effects are offset by agricultural dependence and rebound dynamics. Using a balanced macro panel of ten MENA countries from 1990 to 2024, we estimate several econometric specifications and conduct robustness checks. Agricultural water dependence is consistently associated with greater water stress, whereas the relationship between technology and stress varies across specifications. It is negative in pooled models but positive after controlling for country heterogeneity. Combined with evidence of bidirectional Granger causality, these results suggest that infrastructure expansion often responds to existing scarcity rather than resolving it. Sustainable water security therefore requires not only technological innovation but also institutional reform, demand management, and agricultural transition.
In the context of climate change and the growing need for sustainable development, green finance and technological innovation have become important instruments for achieving economic growth while ensuring environmental protection. This study investigates the effects of green finance and technological innovation on sustainable growth in 86 countries, including 40 developed and 46 developing countries, over the period 2010 to 2024. The study applies pooled ordinary least squares regression, fixed effects models, random effects models and generalized method of moments estimation to address endogeneity and the dynamic characteristics of panel data. The empirical findings indicate that green finance may have a negative short-term effect on sustainable growth, whereas technological innovation contributes positively to sustainable growth, particularly in developing countries. Institutional quality is also identified as a key condition that enhances the effectiveness of green finance and technological innovation in promoting sustainable growth. The results suggest that countries should strengthen institutional quality, improve the efficiency of resource allocation and support technological innovation to maximize the benefits of green finance in the transition toward sustainable growth.
