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The Right Key for the Right Lock: How Government Response Methods and Demand Types Affect Citizen Satisfaction

PA

2026-09-17

Original

The Right Key for the Right Lock: How Government Response Methods and Demand Types Affect Citizen Satisfaction

Na Tang, Wenjia Huang, Nana Huang, Mengyao Zhang

Abstract

ABSTRACT Faced with diverse and complex demands from citizens, the government has consistently sought ways to enhance its ability to respond. Metaphorically, citizens' needs can be viewed as locks, and the government requires keys to unlock them. Artificial intelligence (AI) is an innovative new key offering a fresh paradigm for unlocking the door to high citizen satisfaction. Drawing on government responsiveness theory, this study applies a 2 × 3 between‐subjects survey experiment to explore the impact of government response methods (traditional responses, AI‐enabled responses) and citizen demand types (consultation, complaint/help‐seeking, suggestions) on citizen satisfaction. Findings show that AI‐enabled government responses significantly increase citizen satisfaction compared to traditional approaches. Among demand types, consultation yields the highest satisfaction, while suggestion results in the lowest. Further, the satisfaction level is significantly influenced by the interaction effect between response method and demand type. Perceived fairness mediates the relationship between government responses and citizen satisfaction, with citizen participation experience having a moderating effect. This study offers new insights into increasing citizen satisfaction from the perspective of government responses. It reveals the content‐dependent nature of AI‐enabled government responses, helping the government create unique AI response strategies and enhance digital interaction with citizens.

中文

正确的钥匙配正确的锁:政府回应方式与需求类型如何影响公民满意度

Na Tang, Wenjia Huang, Nana Huang, Mengyao Zhang

摘要

摘要 面对公民多样且复杂的需求,政府一直在寻求提升其回应能力的方式。隐喻而言,公民需求可被视为锁,而政府需要钥匙来打开它们。人工智能(AI)是一种创新性的新钥匙,为开启高公民满意度之门提供了新范式。基于政府回应性理论,本研究采用2×3被试间调查实验,探讨政府回应方式(传统回应、AI赋能回应)与公民需求类型(咨询、投诉/求助、建议)对公民满意度的影响。研究发现,与传统方式相比,AI赋能的政府回应显著提高了公民满意度。在需求类型中,咨询带来最高满意度,而建议带来最低满意度。此外,满意度水平显著受到回应方式与需求类型交互效应的影响。感知公平在政府回应与公民满意度之间起中介作用,公民参与经历则具有调节作用。本研究从政府回应视角为提升公民满意度提供了新见解。它揭示了AI赋能政府回应的内容依赖性,有助于政府制定独特的AI回应策略并增强与公民的数字互动。

关键词

政府回应方式、需求类型、公民满意度、人工智能、调查实验、感知公平、公民参与