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公共行政

Supply‐Side Policy Feedback

·432 字·1 分钟
Polihot 公共政策 公共行政 Policy Feedback Supply-Side Public Policy Service Providers Research Agenda
PSJ 54/3 2026-08-07 Original Supply‐Side Policy Feedback Isabel M. Perera Abstract ABSTRACT The scholarship on policy feedback has been among the most plentiful and successful of the policy sciences. Much of it has focused on the demand‐side, or on the political relationship between a public policy and its recipients. Less attention has been paid to the supply‐side: the political relationship between a public policy and its providers. Parents may care about education, patients about health care, and prisoners about criminal justice—but an emerging literature shows that teachers, hospital employees, and the police care just as, if not more, about these areas. This article builds on new work to introduce a theory of supply‐side policy feedback and outline a research agenda for its further investigation.

Institutional Pressures or Organizational Capacity? Antecedents of Digital Maturity in Local Governments

·505 字·2 分钟
Polihot 公共行政 Digital Government Local Government Digital Maturity Administrative Capacity Institutional Pressures
PA — 2026-08-06 Original Institutional Pressures or Organizational Capacity? Antecedents of Digital Maturity in Local Governments Sarah Van Impe, Lieselot Danneels, Ben Suykens Abstract ABSTRACT Public administration research has identified institutional pressures and organizational capacity as digital maturity (DM) antecedents, yet these are typically considered in isolation. Taking the proverbial next step, this study draws on primary survey data to explain the variation of DM among local governments in Flanders (the northern region of Belgium) by juxtaposing the explanatory power of institutional pressures on the one hand, and political and administrative capacity on the other hand. Using multiple regression analyses, our findings highlight the critical role of administrative capacity in advancing DM among local governments. In contrast, and somewhat surprisingly, political capacity and institutional pressures appear to play a more limited role. These findings challenge conventional assumptions in existing literature, indicating that institutional pressures may catalyze the initial stages of DT, whereas organizational capacity seems to be more influential in sustaining and advancing DM.

Rising Engagement and Substantive Responsiveness: 13 Years of Online Petitioning in China

·593 字·2 分钟
Polihot 比较政治 公共行政 中国研究 China Online Petitioning Government Responsiveness Citizen-State Relations E-Government
CQ — pp. 1-17 2026-08-05 Original Rising Engagement and Substantive Responsiveness: 13 Years of Online Petitioning in China Matt DeButts, Tongtong Zhang Abstract Abstract The Chinese government has invested heavily in online petition platforms to channel public grievances, yet systematic longitudinal evidence on citizen–state interactions within these venues remains limited. This research report presents nationwide evidence showing that both public participation and government responsiveness through e-petition institutions have increased markedly since Xi Jinping took office. Analysing more than four million citizen appeals submitted to the country’s largest online petition portal, Message Board for Leaders, from January 2011 to January 2024, we find a twelvefold rise in petition volume and a fivefold increase in users, largely driven by urban residents in eastern provinces. Appeals have also diversified, with notable growth in housing-related issues and more strategic appeals directed at Party secretaries. Meanwhile, local governments have raised response rates from 50 per cent to 98 per cent, shortened average wait times from 176 to 19 days, and increased the substantive resolution rate from 17 per cent to 31 per cent over the past decade.

Large language models and conversational counter-arguments to antipublic sector bias

·785 字·2 分钟
Polihot 公共行政 政治行为 LLM相关 Large Language Models Persuasion Public Sector Bias Conversational Styles Preregistered Experiments
JPART — 2026-08-05 Original Large language models and conversational counter-arguments to antipublic sector bias John D Marvel, Sheeling Neo, Rachel Cho, Sangwon Ju Abstract Abstract Can a good argument change an individual’s mind? In three preregistered experiments, we explore this question in the domain of public sector organizational performance. We observe human subjects as they engage in conversations with a generative artificial intelligence programmed to argue in one of seven distinct “styles,” including a confrontational challenger style, a didactic style, and a sycophantic style. We develop a theory of effective argumentation predicting that conversational styles which are pleasant and engaging will be more persuasive than styles which are unpleasant or unstimulating. Contrary to this prediction, we find that conversational styles which challenge subjects’ negative views of government agencies produce significant positive attitude change, while sycophantic styles that indulge those views do not. Troublingly, subjects find the sycophantic styles more enjoyable, less frustrating, and more credible than the challenger styles. This dissociation between user experience and persuasive outcome—what we call “grudging persuasion”—suggests that attitude change does not require a pleasant conversational experience, and that the styles subjects enjoy most may be precisely the ones least likely to move them. Our findings point to a potentially dark side of large language model-based persuasion: sycophantic styles that users find most appealing are the least effective at correcting misinformed views.