Exploring stakeholder interests in the health sector: a pre and post-digitalisation analysis from a developing country context

Mansah Preko & Sheena Lovia Boateng

International Journal of Healthcare Technology and Management2024https://doi.org/10.1504/ijhtm.2024.140385article
AJG 1
Weight
0.30

What the paper says

Underpinned by stakeholder and agency theories, this study adopts a qualitative multiple-case study approach to explore and analyse various stakeholder interests and how they affect digitalisation in the health sector of a developing country (DC). The study's findings revealed that four key stakeholder interests - political, regulatory, leadership, and operational - affect digitalisation in the health sector of DCs. Further, the study found that operational and leadership interests were emergent and were triggered by some digitalisation initiatives, which included, inter alia, the use of new eHealth software and the COVID-19 vaccination exercise, which established new structures and worked better through digitalisation. Conversely, political and regulatory interests were found to be relatively enduring since they existed throughout the pre- and post-digitalisation eras. The study also unearthed principal-agent conflicts arising from technological, organisational and regulatory factors that contribute to the paradoxical outcomes of digitalisation in the health sector.

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https://doi.org/https://doi.org/10.1504/ijhtm.2024.140385

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@article{mansah2024,
  title        = {{Exploring stakeholder interests in the health sector: a pre and post-digitalisation analysis from a developing country context}},
  author       = {Mansah Preko & Sheena Lovia Boateng},
  journal      = {International Journal of Healthcare Technology and Management},
  year         = {2024},
  doi          = {https://doi.org/https://doi.org/10.1504/ijhtm.2024.140385},
}

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Evidence weight

0.30

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.00 × 0.4 = 0.00
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.