Izvorni znanstveni članak
https://doi.org/10.30765/er.3382
A business intelligence framework for assessing the impact of foreign labour on enterprise performance
Ljerka Luić
orcid.org/0000-0002-2707-9367
; Department of Media and Communication, University North, Koprivnica, Croatia
Silvija Drvarek
orcid.org/0009-0005-2594-7465
; Department of Media and Communication, University North, Koprivnica, Croatia
*
* Dopisni autor.
Sažetak
Building on preliminary research for the study A Conceptual Business Intelligence–Driven Tripartite Model for Assessing Foreign Labour Effects in Small Open Economies, which defined key constructs, elements, and outputs of foreign labour markets as a basis for further model integration, this paper presents an integrative conceptual framework for a human resource analytics model, supporting operational, tactical, and strategic decision-making on foreign worker management. The proposed framework establishes a Business Intelligence and Analytics-driven tripartite architecture that integrates microeconomic, organisational, and macroeconomic dimensions across three core constructs: Foreign Workers as the resource input, Business Activity at the organisational level, and Economic Activity at the macroeconomic level. To process these constructs, the underlying system architecture integrates four functional components: data collection, central business intelligence analytics, reporting, and predictive–prescriptive decision support. By routing all information flows through the central BI&A hub, the model ensures semantic consistency, data traceability, and compliance with data governance standards. Ultimately, this framework operationalises empirical insights to deliver interactive dashboards, performance predictions, and prescriptive recommendations, optimizing worker allocation, risk management, strategic planning, and budgeting across all organizational levels in small open economies.
Ključne riječi
business intelligence; information flows; analytics; foreign labour; enterprise performance
Hrčak ID:
349875
URI
Datum izdavanja:
28.7.2026.
Posjeta: 0 *