Between institutions and narratives : understanding collective action in innovation policy processes

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dc.contributor.authorESPOSITO, Giovanni
dc.contributor.authorTAFFONI, Gaia
dc.contributor.authorTERLIZZI, Andrea
dc.contributor.authorCRUTZEN, Nathalie
dc.date.accessioned2024-10-16T10:48:39Z
dc.date.available2024-10-16T10:48:39Z
dc.date.issued2024
dc.descriptionPublished online: 16 October 2024en
dc.description.abstractExplanations for collective action focus on both institutions and narratives. On the one hand, institutional approaches emphasize the role of rules that guide human behavior. On the other hand, accounting for the narratives through which policy actors make sense of their actions helps in understanding strategic behavior. However, applying institutional and narrative perspectives together is daunting, in part because there has not been a common way to integrate the two approaches. In this article, we draw from Actor-Network Theory (ANT) to elaborate a novel analytical approach that combines ANT with the Institutional Grammar Tool (IGT) and the Narrative Policy Framework (NPF). We use IGT's and NPF's analytical categories in a processual perspective to examine how policy-makers strategically use institutions and narratives to create and stabilize a network of actors in innovation policy processes. We illustrate our approach through an in-depth analysis of the development of a smart city.en
dc.identifier.citationEuropean policy analysis, 2024, OnlineFirsten
dc.identifier.doi10.1002/epa2.1224
dc.identifier.issn2380-6567
dc.identifier.urihttps://hdl.handle.net/1814/77366
dc.language.isoenen
dc.orcid.uploadtrue*
dc.publisherWileyen
dc.titleBetween institutions and narratives : understanding collective action in innovation policy processesen
dc.typeArticleen
dspace.entity.typePublication
eui.subscribe.skiptrue
person.identifier.orcid0000-0003-0561-5410
person.identifier.other45384
relation.isAuthorOfPublication63e08d87-8ac7-48bf-8eb5-7c60d2abbb98
relation.isAuthorOfPublication.latestForDiscovery63e08d87-8ac7-48bf-8eb5-7c60d2abbb98
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