Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/329296 
Year of Publication: 
2025
Citation: 
[Journal:] Economies [ISSN:] 2227-7099 [Volume:] 13 [Issue:] 1 [Article No.:] 16 [Year:] 2025 [Pages:] 1-27
Publisher: 
MDPI, Basel
Abstract: 
This study examines the effectiveness of digital recruitment platforms in addressing labor shortages within Norway's shipbuilding and ship-repair industry. Through a data analysis of 446 job applications over a 12-month period, this study evaluates key recruitment metrics, including application response times (ARTs), candidate acceptance rates (CARs), and the impact of machine learning on hiring outcomes. The findings reveal that specialized digital platforms can significantly improve recruitment efficiency, with 70% of applications being received within 24 h, highlighting the platforms's great potential for time-sensitive sectors. Additionally, pre-vetting candidates enhances hiring precision, achieving a CAR of 90% and reducing mismatches. The application of machine learning algorithms provides predictive insights that support real-time adjustments to job postings, optimizing recruitment strategies. This study contributes uniquely to the literature on cross-border digital recruitment, aligning with the European Union goals of sustainable labor mobility and economic resilience.
Subjects: 
digital recruitment
labor mobility
labor shortages
Norway shipyards
maritime industry
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.