ArticlePloS one2023
Stakeholder engagement variability across public, private and public-private partnership projects: A data-driven network-based analysis.
Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Palliative care national plan implementation through stakeholder analysis.BMC palliative care · 2024Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Stakeholder engagement is generally considered one of the most pertinent factors impacting project outcomes. However, there is lacking empirical evidence documenting patterns of stakeholder engagement and their potential differences between public, private and public-private partnership (PPP) projects. This study leverages social network research methods to capture and quantitively compare these engagement structures. Stakeholder network data were collected by an online questionnaire from 17 public, 30 private and 9 PPP projects. A series of network-based analyses were subsequently applied to the data at both the level of individual project stakeholders and entire project stakeholder ecologies. A statistically significant difference (p<0.05) exists among the network-level measures of network size, edge number, density and betweenness centralization across the three project types. Among these four network measures, the density varies significantly (p<0.05) between 'within budget' and cost overrun projects for the private and PPP projects. The top-5 stakeholder lists with respect to three node-level centrality values reveal distinctive differences across the three project types. To further interpret the data, exponential random graph models were also applied to determine the most statistically prevalent network motifs within each type of project. Again, statistically significant differences were found across these three project types. The findings consistently point to structural differences in patterns of stakeholder engagement across the public and private domain and illustrate the applicability of network data and analytical techniques to monitoring and managing complex webs of relationships among actors who affect and are affected by diverse types of projects.
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