Unpacking the Influence of Policy Advice Using Citation Network Analysis

• 成果类型: Article; Early Access
• 署名作者: Christensen, Johan; van den Bekerom, Petra
• 署名单位: Leiden University - Excl LUMC; Leiden University
• 刊物名称: PUBLIC ADMINISTRATION REVIEW
• ISSN/ISSBN: 0033-3352
• DOI: 10.1111/puar.70014
• 发表日期: 2025
• 关键词: information; centrality; KNOWLEDGE

摘要

Public policy often builds on a large body of policy advice-produced by bureaucrats, advisory bodies, scientists, and consultants-that has accumulated over time about a specific policy problem and appropriate policy responses. Yet, how this body of policy advice develops and which pieces of advice influence subsequent policy recommendations is poorly understood. We seek to fill this gap by proposing a novel conceptualization and methodological approach for unpacking the influence of policy advice on other policy advice. First, we distinguish four conceptual dimensions along which the influence of policy advice varies: lasting influence, broad influence, influential followers, and influence as broker. Second, we propose citation network analysis as a methodological tool for measuring these multiple dimensions of influence. We present a set of citation network measures of influence and illustrate their usefulness by analyzing influence patterns within a large network of Norwegian advisory reports.