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Policy narrative, policy understanding and policy support intention: A survey experiment on energy conservation

Policy narrative, policy understanding and policy support intention: A survey experiment on energy conservation

Mu, Rui ORCID: 0000-0002-5910-1354, Li, Yan and Cui, Tie (2021) Policy narrative, policy understanding and policy support intention: A survey experiment on energy conservation. Policy Studies. pp. 1-21. ISSN 0144-2872 (Print), 1470-1006 (Online) (doi:https://doi.org/10.1080/01442872.2021.1954609)

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Abstract

Nowadays, policy narratives as a communication strategy are frequently used by governments to persuade target populations and obtain policy support. However, few studies have empirically examined whether and through what mechanisms policy narratives can enhance policy support intention. To fill this gap, this study uses the case of energy conservation policy to conduct a survey experiment among 300 industrial enterprises in Liaoning, China. The findings indicate that policy narratives are effective in strengthening policy support intention; this effectiveness is achieved through a mediating variable of subjective policy understanding. In other words, only when policy narratives make target populations think they understand the policy can they show strong policy support intention. Additionally, we examine how policy narratives should be designed to enhance subjective policy understanding. The study finds that a simple narrative form (i.e. reducing policy details and using images and symbols) and a narrative content with positive incentives (i.e. showing material and reputational incentives) are two measures to enhance subjective policy understanding, which then leads to strong policy support intention. The implications of these findings for the policy narrative theory and policy implementation practice are discussed at the end of the article.

Item Type: Article
Uncontrolled Keywords: Policy narrative, policy understanding, policy support intention, energy conservation, survey experiment
Subjects: H Social Sciences > HA Statistics
H Social Sciences > HE Transportation and Communications
Faculty / Department / Research Group: Faculty of Business
Faculty of Business > Networks and Urban Systems Centre (NUSC)
Faculty of Business > Networks and Urban Systems Centre (NUSC) > Connected Cities Research Group
Last Modified: 02 Aug 2021 10:28
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
Selected for REF2021: None
URI: http://gala.gre.ac.uk/id/eprint/33349

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