Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal JURNAL ECONOMINA
Karina Dewi Oktaviani
The University of Edinburgh, United Kingdom
Economics, Econometrics & Finance

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Unveiling the Canvas of Collaboration: Exploring Challenges for AI Innovation in Scotland's Healthcare Karina Dewi Oktaviani
JURNAL ECONOMINA Vol. 5 No. 8 (2026): JURNAL ECONOMINA, Agustus 2026
Publisher : LPPM Sekolah Tinggi Ilmu Ekonomi 45 Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55681/economina.v5i8.3618

Abstract

The healthcare landscape is undergoing change, driven by a significant shift towards digital health services aimed at improving care efficiency, within the context of heightened healthcare demands and financial constraints. Open Innovation emerges as a pivotal concept, fostering collaboration between healthcare providers and external partners to drive the creation of innovative healthcare products and services. Concurrently, Artificial Intelligence (AI) emerges as a transformative tool, offering potential to reshape disease management and streamline healthcare operations. However, a notable gap exists in comprehending the nuances of AI innovations and their associated challenges, particularly within collaborative innovation frameworks. Employing a qualitative case study design, this study focuses on Scotland's healthcare innovation landscape, utilising semi-structured interviews with the stakeholders. The findings reveal six challenges in collaborative AI innovations: funding, problem definition, human resources, governance, regulation, and data quality and access. The study also presents recommended strategies for stakeholders to enhance the innovation process. Moreover, the research highlights that contest-based collaborations and strategic partnerships offer distinct models with trade-offs relating to expertise and inclusivity, underlining the significance of understanding these challenges for effective collaborative AI innovation in healthcare.
Co-Authors