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Business & Economics

STRATEGIC LEADERSHIP AND EMPLOYMENT DYNAMICS IN EUROPEAN COUNTRIES INDUSTRIES: FORECASTING LABOUR FORCE EXPECTATIONS THROUGH SPACE-TIME ANALYSIS⁷
Adriana Grigorescu, Alina Mihaela Dima, Cristina Lincaru, Victor Raul Lopez Ruiz

ABSTRACT: This paper analyses the evolution of employment expectations in industry (BS-IEME-BAL) for the period 1992-2025, using data from the Business and Consumer Surveys (BCS) provided by the Directorate-General for Economic and Financial Affairs (DG ECFIN) of the European Commission. The study examines cyclical fluctuations, long-term trends and the impact of macroeconomic factors on the industrial labour market. To identify recurring patterns and anticipate future changes in employment, the analysis uses spatiotemporal forecasting in GIS, applying the Exponential Smoothing Forecast (Holt-Winters) model. This model allows the decomposition of the time series into trend, seasonality and residual components, providing a robust estimate of the evolution of employment expectations. Anomalies and turning points are also assessed, contributing to the understanding of the vulnerabilities of the industrial sector in times of economic uncertainty. The results obtained provide support for strategic leadership performed by formulating public policies and strategies for adapting to the digital transition, economic fluctuations and labour market challenges. The study highlights the usefulness of spatial analysis and temporal forecasting tools for data-based decision-making in the context of structural transformations of the economy.

KEYWORDS:  strategic leadership; employment; space-time forecasting; industry; public policies.

JEL classification:  C53, E24, J21, J23, J24.

⁷Acknowledgments:  This study was supported by a grant from the Romanian Ministry of Research, Innovation, and Digitalisation, Programme NUCLEU, 2022-2026, Spatio-temporal forecasting of local labour markets through GIS modelling [P5]/Previziuni spatio-temporale pentru pietele muncii locale prin modelare în GIS [P5], PN 22_10_0105.