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A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA) 
Pesqueira, A., Machado, A. de. B., Bolog, S., Sousa, M. J. & Pereira, R. (2024). Exploring the impact of EU tendering operations on future AI governance and standards in pharmaceuticals. Computers and Industrial Engineering. 198
Exportar Referência (IEEE) 
A. M. Pesqueira et al.,  "Exploring the impact of EU tendering operations on future AI governance and standards in pharmaceuticals", in Computers and Industrial Engineering, vol. 198, 2024
Exportar BibTeX 
@article{pesqueira2024_1732267554899,
	author = "Pesqueira, A. and Machado, A. de. B. and Bolog, S. and Sousa, M. J. and Pereira, R.",
	title = "Exploring the impact of EU tendering operations on future AI governance and standards in pharmaceuticals",
	journal = "Computers and Industrial Engineering",
	year = "2024",
	volume = "198",
	number = "",
	doi = "10.1016/j.cie.2024.110655",
	url = "https://www.sciencedirect.com/journal/computers-and-industrial-engineering"
}
Exportar RIS 
TY  - JOUR
TI  - Exploring the impact of EU tendering operations on future AI governance and standards in pharmaceuticals
T2  - Computers and Industrial Engineering
VL  - 198
AU  - Pesqueira, A.
AU  - Machado, A. de. B.
AU  - Bolog, S.
AU  - Sousa, M. J.
AU  - Pereira, R.
PY  - 2024
SN  - 0360-8352
DO  - 10.1016/j.cie.2024.110655
UR  - https://www.sciencedirect.com/journal/computers-and-industrial-engineering
AB  - This research examines the incorporation of artificial intelligence (AI) into the domain of tender management (TM) within the pharmaceutical industry, with a particular emphasis on operational efficiency, governance, and compliance with European regulatory standards. A comparative analysis of four companies—two that have adopted AI and two that have not—reveals significant discrepancies in the management of TM processes between AI-driven and traditional companies.
The study employs the Delphi method to ascertain expert consensus on eight critical areas of AI governance, including data privacy, transparency, and ethical AI use. The findings indicate that companies integrating AI demonstrate enhanced decision-making capabilities, accelerated processing times, and enhanced stakeholder engagement. However, they also encounter challenges pertaining to ethical governance and regulatory compliance.
The research highlights the necessity of aligning the adoption of AI with the latest European directives, such as the AI Act and General Data Protection Regulation (GDPR), to ensure both operational efficiency and adherence to ethical standards. The broader implications of the study underscore the necessity for pharmaceutical companies to develop robust governance frameworks, prioritize ethical considerations, and maintain regulatory compliance to fully leverage the potential of AI. Additionally, the study contributes to the ongoing scholarly discourse by providing empirical evidence on the interplay between AI, ethics, and governance, thereby encouraging further interdisciplinary research. This work emphasizes the critical role of strategic AI adoption in maintaining competitive advantage while safeguarding societal trust and adhering to legal requirements.
ER  -