Foreign direct investment (FDI) has often been cast as a straightforward engine of growth, yet its record across Central and Eastern Europe tells a more tangled story where outcomes hinge on the interplay of education, governance, and the timing of external shocks. This study embeds fixed effects panel econometrics within a systems framework, treating FDI as a subsystem of socio-economic dynamics. Using a long-run panel of eleven economies from 2000 to 2023, the analysis models path dependence and regime shifts through interaction terms and period-specific dummies set against a systems-thinking backdrop. The analysis shows that for the average CEE economy, FDI’s contribution has waxed and waned: it dragged on growth during the early transition years (2000–2007), settled into a neutral role after the global financial crisis, and proved unpredictable in the pandemic era. Romania stands out, however, with a marked “FDI premium” quantified as approximately 0.7 pp of growth per pp of FDI that seems to stem from reinforcing loops between rising tertiary enrolment and productivity spillovers. Mapping these feedbacks brings to light virtuous circles where human capital and resilience make or break the benefits of foreign capital. The policy message is plain: nurture the positive loops through investment in skills and firm linkages, keep institutions nimble enough to adapt, and watch for early warning signs of systemic strain.

Digitalisation is reshaping commercial systems in Europe, yet the joint evolution of national digital capabilities, e-commerce and macroeconomic performance remains imperfectly understood. This article develops a parsimonious Digital Maturity Index for the EU-27 over 2015–2023 and examines its association with the share of enterprise turnover generated through e-commerce using a systems-oriented econometric design. Two-way fixed-effects and dynamic panel models show that e-commerce turnover is strongly persistent within countries and systematically higher in more trade-open economies and in labour markets with slightly higher unemployment, after controlling for income and unobserved heterogeneity. The marginal effect of digital maturity on e-commerce intensity is small and statistically fragile, suggesting that digital capabilities act more as a slow-moving state variable than as a direct short-run driver of online sales. The marginal within-country effect of digital maturity on e-commerce intensity is small and statistically fragile once unobserved heterogeneity is controlled for, whereas trade openness and labour-market conditions remain robust correlates. The PVAR results suggest a stable system with strong persistence in e-commerce and digital maturity, limited spillovers to growth and a pronounced temporary contraction in output during the COVID-19 shock.

Leadership models in the times of COVID-19 is surely the topic of the hour, yet this hour might last for some few years. By the end of it, we will reach the point of no return and a new set of rules and paradigms would have been created. Many researchers and leadership representatives investigate this topic. The available and reviewed literature is rather shaping the discrepancies of the past-embedded practices, as opposed to the current challenges. In this context of constant change, the current paper is aiming to investigate some current leadership practices, which are targeting the level of productivity, different ways of working and communicating in the work from home context. Moreover, the research would be setting the stage for something that is not there yet, in the current leadership patterns. The research methodology based on top management and senior leaders’ interviews, covering multiple industries from Romania, like banking, energy, manufacturing at large scale and outsourcing. The questions were designed to investigate the realities on their new job definition, from a personal perspective, as people managers and the business value outcomes envisioned in the new scheme of work. The theoretical contribution of the paper is to define a set of guidelines and filtering areas of leadership focus. The set of information gathered for new business metrics of performance, the ownership, efficiency and business value creation is pushed at all levels. One major change is the new definition of discipline, shifting from authority into entrepreneurial attitudes.

Policymakers in small open economies need reliable signals of incipient private consumption downturns, yet traditional indicators are revised, noisy, and often arrive too late. This study develops a Romanian-specific early warning system that combines a time-varying parameter VAR with stochastic volatility and exogenous drivers (TVP-SV-VARX) with modern machine learning classifiers. The structural layer extracts regime-dependent anomalies in the macro-financial transmission to household demand, while the learning layer transforms these anomalies into calibrated probabilities of short-term consumption declines. A strictly time-based evaluation design with rolling blocks, purge and embargo periods, and rare-event metrics (precision–recall area under the curve, PR-AUC, and Brier score) underpins the assessment. The best-performing specification, a TVP-filtered random forest, attains a PR-AUC of 0.87, a ROC-AUC of 0.89, a median warning lead of one quarter, and no false positives at the chosen operating point. A sparse logistic calibration model improves probability reliability and supports transparent communication of risk bands. The time-varying anomaly layer is critical: ablation experiments that remove it lead to marked losses in discrimination and recall. For implementation, the paper proposes a three-tier WATCH–AMBER–RED scheme with conservative multi-signal confirmation and coverage gates, designed to balance lead time against the political cost of false alarms. The framework is explicitly predictive rather than causal and is tailored to data-poor environments, offering a practical blueprint for demand-side macroeconomic early warning in Romania and, by extension, other small open economies.