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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. [ABSTRACT FROM AUTHOR]

Purpose – Amidst the ongoing digital transformation in the maritime industry, this study aims to interrogate the application of electronic certification (e-certification) to seafarers globally. Design/methodology/approach – Data and methodological triangulation were used in the study. This included a scoping review to analyze the components of effective e-certificates; document analysis to evaluate the nature and functions of the international legal framework of seafarers’ e-certification and thematic and statistical analyses of responses from survey questionnaires and interviews to examine the merits, demerits and challenges to global implementation of seafarers’ e-certification. A modified Unified Theory of Acceptance and Use of Technology (UTAUT) model was used to determine the stakeholders’ usage behavior regarding seafarers’ e-certification. Findings – The results revealed several merits associated with the implementation of seafarers’ e-certificates, outweighing the presence of certain drawbacks. It also identified various challenges to global application along with potential solutions. Despite the strong industry support for the entire replacement of seafarers’ traditional printed certificates with e-certificates, the study concludes that the coexistence of both formats will persist until crucial challenges are effectively addressed. The International Convention on Standards of Training, Certification and Watchkeeping for Seafarers (STCW), 1978, as amended, along with the relevant International Maritime Organization (IMO) guidelines, functions as the international legal framework for the effective global application of electronic certification for seafarers. Originality/value – The study addresses a significant aspect of the contemporary digital transformation of seafarers’ certification under the STCW Convention, 1978, as amended.

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.

Although the maritime industry has introduced technological improvements, shipping activity is still a major contributor to greenhouse gas emissions. Using more intelligent incentive policies, such as subsidies, seems a way to increase green technology adoption. Our proposal is to engineer micro-level incentives to target a reduced set of adopters to optimize subsidies while encouraging adoption by shipowners. We focus on wind-assisted propulsion technology in shipping and test the effectiveness of targeting using agent-based simulations. The agent-based model employs a three-phase process, influenced by awareness of technology, economic factors, and networking. Experiments under different scenarios robustly analyze targeting policies and their impact on adoption rates. Our findings reveal that targeted incentives significantly improve adoption compared to a uniform distribution. The most effective targeting policies are those that select receptors based on their social activity and energy consumption, although the available budget affects the selection of criteria. [ABSTRACT FROM AUTHOR]