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Negotiating Identity Conflicts in Green Mega-Infrastructure Projects

Matthias Vanhullebusch

Negotiation Journal2026https://doi.org/10.1162/ngtn.a.57article
AJG 2ABDC B
Weight
0.50

What the paper says

Abstract Green mega-infrastructure projects are increasingly central to the global green energy transition. Yet they often generate conflict when stakeholder engagement fails to address underlying issues of identity, recognition, and belonging. These dynamics unfold against a backdrop of institutional logics that prioritize efficiency, planning authority, and investment security. This article re-examines stakeholder engagement through the lens of negotiation theory, arguing that existing frameworks often remain conflict-blind and reduce identity to procedural categories. Drawing on Rothman’s ARIA framework, it extends the logic of interest-based negotiation by introducing a relational, identity-sensitive approach to conflict in green mega-infrastructure project governance. Accordingly, the article advances the concept of identity narratives—dynamic and relational storylines through which actors, communities, and developers alike articulate identity claims of belonging, legitimacy, and recognition in conflict. It integrates this typology within the ARIA framework by structuring antagonism, resonance, invention, and action around contested identities to promote a more recognition-sensitive approach to stakeholder engagement.

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https://doi.org/https://doi.org/10.1162/ngtn.a.57

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@article{matthias2026,
  title        = {{Negotiating Identity Conflicts in Green Mega-Infrastructure Projects}},
  author       = {Matthias Vanhullebusch},
  journal      = {Negotiation Journal},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1162/ngtn.a.57},
}

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Negotiating Identity Conflicts in Green Mega-Infrastructure Projects

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Evidence weight

0.50

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

F · citation impact0.50 × 0.4 = 0.20
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.