Government Information Quarterly最新文献_第2页

Complexity, understandability, and compatibility: A comparative study of AI advisory systems for National Security 复杂性、可理解性和兼容性：国家安全人工智能咨询系统的比较研究

IF 1 1区管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE

Government Information Quarterly

Pub Date : 2025-11-06 DOI: 10.1016/j.giq.2025.102088

Brecht Weerheijm, Sarah Giest, Bram Klievink

Artificial Intelligence (AI) advisory systems are being implemented in the public sector for more efficient and effective decision-making. Yet, there is a lack of in-depth qualitative and comparative research focusing on how decision-makers in a real-world setting use different types of AI advisory systems. By asking “How do different AI advisory systems affect use by national security decision-makers?”, this study reveals through a qualitative case study and using scenario-based interviews that decision-makers are more likely to use relatively simple AI systems over complex ‘black box’ systems. Additionally, factors such as accountability concerns and compatibility with existing decision-making processes influence their willingness to use AI advisory systems. Ultimately, a more technically advanced AI system is not necessarily perceived as more competent, as decision-makers view processes like data analysis as integral to nuanced and effective decision-making. This suggests that the fit between the perceived competences and compatibility of the AI system and the decision-making task at hand is highly important for the successful implementation of AI advisory systems.

人工智能（AI）咨询系统正在公共部门实施，以提高决策效率和效果。然而，缺乏深入的定性和比较研究，重点关注决策者在现实世界中如何使用不同类型的人工智能咨询系统。通过提问“不同的人工智能咨询系统如何影响国家安全决策者的使用？”，本研究通过定性案例研究和基于场景的访谈揭示，决策者更有可能使用相对简单的人工智能系统，而不是复杂的“黑匣子”系统。此外，问责问题和与现有决策过程的兼容性等因素影响了他们使用人工智能咨询系统的意愿。最终，技术更先进的人工智能系统并不一定会被认为更有能力，因为决策者认为数据分析等过程是微妙而有效决策的组成部分。这表明，人工智能系统的感知能力和兼容性与手头的决策任务之间的契合对于人工智能咨询系统的成功实施非常重要。

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引用次数: 0

Recovery from AI government service failures: Is disclosing the identity of the AI agent an effective strategy? 从人工智能政府服务失败中恢复：披露人工智能代理的身份是一种有效的策略吗？

IF 1 1区管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE

Government Information Quarterly

Pub Date : 2025-11-01 DOI: 10.1016/j.giq.2025.102087

Zepeng Gong , Xiao Han , Yueping Zheng

Effective recovery from service failures is critical to the sustainable development of artificial intelligence (AI) government services. However, little is known about this subject in the field of public administration. Three survey experiments (N = 2,368) are administered to investigate if the identity disclosure (IDD) of AI agents could be used as a service recovery strategy to increase user tolerance for government service failures. In addition, the mechanisms and boundaries of IDD’s effects on tolerance and the most effective timing for such disclosures are examined. The findings indicate that: (1) IDD can improve tolerance, an effect fully mediated by a user’s performance expectancy of and perceived respect from a service; (2) the paths for perceived respect are not robust across different levels of service failure severity; and (3) the relatively more effective and economical timing for IDD is pre-failure disclosure. Overall, IDD is an effective strategy for AI government service recovery, and the user’s rational assessment (performance expectancy) plays a more extensive role than emotional assessment (perceived respect) in IDD’s effects on tolerance. This study provides new insights into AI service failure and recovery, thus enriching relevant theories.

服务故障后的有效恢复对于人工智能政府服务的可持续发展至关重要。然而，在公共行政领域对这一问题知之甚少。通过三个调查实验（N = 2368），研究人工智能代理的身份披露（IDD）是否可以作为一种服务恢复策略，以提高用户对政府服务故障的容忍度。此外，还研究了碘缺乏症对耐受性影响的机制和界限，以及披露这种情况的最有效时机。研究结果表明：(1)IDD可以提高用户的容忍度，这一效应完全由用户对服务的绩效期望和感知尊重介导；(2)不同服务故障严重程度的尊重感知路径不具有鲁棒性；(3)相对更有效和经济的IDD时机是故障前披露。总体而言，IDD是人工智能政务服务恢复的有效策略，在IDD对容忍度的影响中，用户的理性评估（绩效预期）比情绪评估（感知尊重）发挥更广泛的作用。本研究为人工智能服务故障与恢复提供了新的见解，丰富了相关理论。

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引用次数: 0

How AI assistance enhances work adaptability in the public sector: A mixed-methods study from Southwest China 人工智能辅助如何增强公共部门的工作适应性：来自西南地区的混合方法研究

IF 1 1区管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE

Government Information Quarterly

Pub Date : 2025-10-29 DOI: 10.1016/j.giq.2025.102089

Wei Zhang, Yili Yu

As artificial intelligence (AI) becomes increasingly embedded in public organizations, a critical challenge is how employees adapt to technological change while maintaining effective job performance.The objective of this study is to examine how AI assistance influences public employees' work adaptability. Drawing on Sociotechnical Systems (STS) theory, we develop a moderated mediation model in which AI assistance enhances adaptability through employee creativity, while task complexity serves as a contextual moderator. To test this model, we conducted a 2-by-2 field experiment (AI-assisted vs. non-assisted; complex vs. simple tasks) in the traffic management division of a municipal public security bureau in southwestern China, involving 408 participants and complemented by semi-structured interviews with 20 employees.The results show that AI enhances employees' work adaptability indirectly by stimulating creativity. Moreover, the positive effects of AI are amplified under high task complexity, indicating that AI performs more effectively in cognitively demanding contexts. These findings advance the theoretical understanding of the “technology-task-human” triadic interaction, extend micro-level behavioral research on AI in public administration, and provide practical guidance for the conditional deployment of AI in public organizations.

随着人工智能（AI）越来越多地融入公共组织，一个关键的挑战是员工如何适应技术变革，同时保持有效的工作绩效。本研究的目的是研究人工智能辅助如何影响公共雇员的工作适应性。利用社会技术系统（STS）理论，我们开发了一个有调节的中介模型，其中人工智能辅助通过员工创造力增强适应性，而任务复杂性则作为语境调节因子。为了验证这一模型，我们在中国西南某市公安局的交通管理部门进行了2乘2的现场实验（人工智能辅助与非辅助；复杂任务与简单任务），涉及408名参与者，并辅以对20名员工的半结构化访谈。结果表明，人工智能通过激发创造力间接提高了员工的工作适应性。此外，人工智能的积极影响在高任务复杂性下被放大，这表明人工智能在认知要求较高的环境中表现得更有效。这些研究成果推进了对“技术-任务-人”三元互动的理论认识，拓展了人工智能在公共管理中的微观行为研究，并为人工智能在公共组织中的有条件部署提供了实践指导。

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引用次数: 0

Understanding public acceptance of data collection by intelligence services in the Netherlands: A factorial survey experiment 了解公众对荷兰情报部门收集数据的接受程度：一个析因调查实验

IF 1 1区管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE

Government Information Quarterly

Pub Date : 2025-10-29 DOI: 10.1016/j.giq.2025.102077

E.C. Oomens, R.S. van Wegberg, M.J.G. van Eeten, A.J. Klievink

Intelligence services must balance values such as national security and privacy when collecting data, with each scenario involving specific contextual trade-offs. While citizens benefit from effective intelligence operations, they also risk having their rights infringed upon. This makes citizen perspectives on acceptable data collection for intelligence and national security salient, as their legitimacy is also contingent upon public support. Yet, important aspects of citizen perspectives are understudied, such as the influence of contextual factors related to the use of intelligence collection methods. This study, inspired by Nissenbaum's contextual integrity framework, uses a factorial survey experiment with vignettes among a representative sample of 1423 Dutch citizens to examine the influence of threat type, duration, data subject, collection method, data type, and data retention on public acceptance of surveillance. Additionally, the study considers the impact of respondents' trust and privacy attitudes. The findings reveal significant influence of both contextual variables – particularly threat type, data subject, and data retention – and respondent predispositions – particularly trust in institutions, trust in intelligence services' competence, and privacy concerns for others. The findings imply that more in-depth contextual knowledge among the public may foster support for intelligence activities.

情报机构在收集数据时必须平衡国家安全和隐私等价值，每种情况都涉及特定的上下文权衡。虽然公民从有效的情报行动中受益，但他们的权利也有受到侵犯的风险。这使得公民对可接受的情报和国家安全数据收集的看法变得突出，因为它们的合法性也取决于公众的支持。然而，公民观点的重要方面尚未得到充分研究，例如与使用情报收集方法有关的背景因素的影响。本研究受Nissenbaum的上下文完整性框架的启发，在1423名荷兰公民的代表性样本中使用了一个因子调查实验，以检验威胁类型、持续时间、数据主体、收集方法、数据类型和数据保留对公众接受监视的影响。此外，研究还考虑了受访者的信任和隐私态度的影响。研究结果揭示了上下文变量（特别是威胁类型、数据主体和数据保留）和受访者倾向（特别是对机构的信任、对情报服务能力的信任以及对他人隐私的关注）的显著影响。研究结果表明，在公众中更深入的背景知识可能会促进对情报活动的支持。

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引用次数: 0

Human-centric AI governance: what the EU public values, what it really, really values 以人为中心的人工智能治理：欧盟公众的价值观是什么，它真正的价值观是什么

IF 1 1区管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE

Government Information Quarterly

Pub Date : 2025-10-24 DOI: 10.1016/j.giq.2025.102084

Valentin Wittmann, Timo Meynhardt

The EU and other institutions worldwide have committed to aligning AI with human values to ensure that the technology contributes to the common good. Yet, criticism persists that debates over which values should guide this alignment are dominated by private and public organizations that prioritize technological considerations. Societal perspectives that emphasize broader, non-normative values are often marginalized. This exclusion generates a democratic deficit and risks forgoing the advantages of aligning AI with citizens' public values - namely trust, acceptance and public value creation. To address this gap, we empirically examine EU citizens' regulatory and value preferences regarding AI and its regulation, drawing on two complementary studies and Public Values theory and tools: one mixed-methods study of the EU's Public Consultation and one study based on the quantitative assessment of a newly developed AI Public Value (PV) Landscape. Our findings show that EU citizens (i) prefer binding regulation of AI, (ii) consider both ethical and technological principles as well as broader, non-normative societal values, especially along the moral-ethical value dimension, important, and (iii) serve as a conciliatory force capable of balancing business interests against those of state and NGO stakeholders. These results underscore the importance of aligning AI with broader PVs, reinforcing ethical foundations, and enhancing public inclusion in AI governance to achieve truly human-centric and socially accepted AI.

欧盟和世界各地的其他机构致力于使人工智能与人类价值观保持一致，以确保该技术为共同利益做出贡献。然而，批评仍然存在，关于哪些价值观应该指导这种一致性的争论，主要是由优先考虑技术的私人和公共组织主导的。强调更广泛、非规范性价值观的社会观点往往被边缘化。这种排斥产生了民主赤字，并有可能放弃将人工智能与公民的公共价值观（即信任、接受和公共价值创造）结合起来的优势。为了解决这一差距，我们利用两项互补研究和公共价值理论和工具，实证研究了欧盟公民对人工智能及其监管的监管和价值偏好：一项是对欧盟公众咨询的混合方法研究，另一项是基于对新开发的人工智能公共价值（PV）景观的定量评估的研究。我们的研究结果表明，欧盟公民(i)倾向于对人工智能进行约束性监管，（ii）同时考虑伦理和技术原则以及更广泛的、非规范性的社会价值观，尤其是道德-伦理价值维度，这很重要，（iii）作为一种调和力量，能够平衡商业利益与国家和非政府组织利益相关者的利益。这些结果强调了将人工智能与更广泛的pv结合起来，加强道德基础，加强公众对人工智能治理的包容，以实现真正以人为中心和社会接受的人工智能的重要性。

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引用次数: 0

From disclosure to discrepancy: How open government data alters ESG rating divergence 从披露到差异：政府数据公开如何改变ESG评级差异

IF 1 1区管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE

Government Information Quarterly

Pub Date : 2025-10-18 DOI: 10.1016/j.giq.2025.102085

Jianhao Hu , Honghui Zou , Qian Wang

Given the impact of environmental, social, and governance (ESG) rating divergence on sustainable practices, its antecedents have garnered increasing attention. In the context of growing demands for transparency from investors and policymakers, the effect of open government data (OGD) policies on ESG rating divergence remains underexplored. To address this gap, this study examines the dynamic relationship between OGD policies and ESG rating divergence. Using panel data from Chinese listed firms and employing a difference-in-differences approach, the analysis reveals that OGD policies significantly exacerbate ESG rating divergence in the short term, with pronounced effects observed among firms subject to mandatory disclosure requirements and those with state ownership. However, over time, OGD policies reduce the ESG rating divergence. By offering a dynamic analysis, this research contributes to the literature on OGD policies and ESG assessment by underscoring the role of city-level policies in driving institutional change, thereby enhancing our understanding of ESG variability and public policy impacts.

鉴于环境、社会和治理（ESG）评级差异对可持续实践的影响，其前身已引起越来越多的关注。在投资者和政策制定者对透明度要求不断提高的背景下，政府公开数据（OGD）政策对ESG评级差异的影响仍未得到充分探讨。为了解决这一差距，本研究考察了OGD政策与ESG评级差异之间的动态关系。利用来自中国上市公司的面板数据，采用差异中的差异方法，分析发现，OGD政策在短期内显著加剧了ESG评级的差异，在强制披露要求的公司和国有公司之间的影响显著。然而，随着时间的推移，OGD政策减少了ESG评级的差异。通过提供动态分析，本研究通过强调城市层面政策在推动制度变革中的作用，从而加强我们对ESG变异性和公共政策影响的理解，为OGD政策和ESG评估的文献做出了贡献。

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引用次数: 0

The trust trifecta: How transparency, ethics, and benefits shape public confidence in government AI 信任三重奏：透明度、道德和利益如何塑造公众对政府人工智能的信心

IF 1 1区管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE

Government Information Quarterly

Pub Date : 2025-10-14 DOI: 10.1016/j.giq.2025.102083

Xiangyu Bian , Bin Wang , Aobo Yang

As governments increasingly adopt artificial intelligence (AI) in public administration, public trust is critical for successful implementation. Using an adapted Technology Acceptance Model (TAM), this study examines how perceived transparency, ethical principles, and perceived benefits of government AI adoption affect public trust. This study is especially applicable in the domain of China's rapid digital transformation and the government's push for AI-driven smart city initiatives, where unique cultural values and governance structures shape public perceptions differently from Western contexts. Data from 608 Chinese citizens were collected through a questionnaire survey to measure perceived AI transparency, ethical principles, perceived benefits, and public trust in government AI use. This research applied structural equation modeling (SEM) to explore the proposed relationships and mediating effects. The findings indicate that both perceived transparency and ethical principles positively affect the perceived benefits of AI technology, which significantly increases public trust in government AI use. Transparency and ethics also directly affect public trust. Notably, perceived benefits mediated the relationship between transparency, ethics, and public trust, suggesting that transparency and ethics indirectly affect trust by influencing perceived benefits. This study validates the extended TAM in the context of government AI applications and shows that improving transparency and ethical compliance in AI use can increase perceived gains and thus public trust in government AI technologies. These insights provide valuable guidance for policymakers to optimize AI application strategies and improve public acceptance, especially in the Chinese context where balancing technological advances with public concerns is becoming increasingly important.

随着政府越来越多地在公共管理中采用人工智能（AI），公众信任对成功实施至关重要。本研究采用技术接受模型（TAM），考察了政府采用人工智能的感知透明度、道德原则和感知效益如何影响公众信任。这项研究特别适用于中国快速数字化转型和政府推动人工智能驱动的智慧城市倡议领域，在这些领域，独特的文化价值观和治理结构塑造了与西方背景不同的公众观念。通过问卷调查收集了608名中国公民的数据，以衡量感知的人工智能透明度、道德原则、感知的利益以及公众对政府使用人工智能的信任。本研究运用结构方程模型（SEM）来探讨二者之间的关系和中介效应。研究结果表明，感知到的透明度和道德原则都对人工智能技术的感知效益产生了积极影响，这显著增加了公众对政府使用人工智能的信任。透明度和道德也直接影响公众的信任。值得注意的是，感知利益在透明度、道德和公众信任之间起中介作用，表明透明度和道德通过影响感知利益间接影响信任。本研究在政府人工智能应用的背景下验证了扩展的TAM，并表明提高人工智能使用的透明度和道德合规性可以增加感知收益，从而增加公众对政府人工智能技术的信任。这些见解为政策制定者优化人工智能应用策略和提高公众接受度提供了有价值的指导，特别是在平衡技术进步与公众关注变得越来越重要的中国背景下。

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引用次数: 0

Parallel learning loops in collaborative innovation: Insights from digital government 协同创新中的平行学习循环：来自数字政府的见解

IF 1 1区管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE

Government Information Quarterly

Pub Date : 2025-10-09 DOI: 10.1016/j.giq.2025.102080

Philipp Trein, Bastien Presset, Thenia Vagionaki

The implementation of digital innovations in the public sector—such as Electronic Health Records (EHRs)—requires decisionmakers to engage in learning processes. This article investigates how collective learning processes unfold in collaborative innovation, focusing on the development of Switzerland's national Electronic Health Record (EHR) system. Building on policy learning and collaborative governance literatures, we conceptualize learning as comprising two interdependent processes: policy-oriented learning (focused on technical effectiveness) and power-oriented learning (concerned with political feasibility). Drawing on 39 semi-structured interviews and extensive document analysis, we find that the EHR initiative followed a sequential learning pattern—technical solutions were developed before sufficient political support was secured—leading to a politically endorsed but technically flawed implementation. The study introduces the concept of parallel learning loops to explain how simultaneous engagement with technical and political dimensions can improve innovation outcomes. These findings advance theoretical understanding of collaborative learning in digital government and underscore the need for institutional designs that support concurrent technical and political deliberation in complex innovation processes.

在公共部门实施数字创新，如电子健康记录（EHRs），需要决策者参与学习过程。本文研究了集体学习过程如何在协作创新中展开，重点是瑞士国家电子健康记录（EHR）系统的发展。在政策学习和协作治理文献的基础上，我们将学习概念化为两个相互依存的过程：政策导向学习（关注技术有效性）和权力导向学习（关注政治可行性）。通过39次半结构化访谈和广泛的文件分析，我们发现电子病历倡议遵循了一个循序渐进的学习模式——在获得足够的政治支持之前就制定了技术解决方案——导致了政治上得到认可，但技术上存在缺陷的实施。该研究引入了平行学习循环的概念，以解释同时参与技术和政治维度如何改善创新成果。这些发现促进了对数字政府协作学习的理论理解，并强调了在复杂创新过程中支持技术和政治同步审议的制度设计的必要性。

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引用次数: 0

An exploration of agile government in the public sector: A systematic literature review at macro, meso, and micro levels of analysis 公共部门敏捷政府的探索：宏观、中观和微观层面分析的系统文献综述

IF 1 1区管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE

Government Information Quarterly

Pub Date : 2025-10-01 DOI: 10.1016/j.giq.2025.102082

Kuang-Ting Tai, Pallavi Awasthi

Originating from private sector software development, agile has permeated the public sector, fostering innovative reforms not just in project management but also in organizational management and collaborative governance. Despite its widespread adoption, there exists a paucity of research delving into the intricacies of agile practices, particularly for the potential conflicts and interactions with the traditional waterfall-based approaches. Employing the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) method, this systematic review aims to address three fundamental research questions concerning the conceptualization, implementation, and impacts of agile government. To deepen theoretical insight and practical application, our study classifies agile into three distinct levels: Micro (project management), Meso (organizational management), and Macro (governance structure). Our analysis uncovers substantial variations in agile practices across these levels, reflecting a deliberate strategy aimed at harmonizing with existing bureaucratic systems. This study concludes by offering policy implications and delineating avenues for future research endeavors.

敏捷起源于私营部门的软件开发，现在已经渗透到公共部门，不仅在项目管理方面，而且在组织管理和协作治理方面都促进了创新改革。尽管敏捷被广泛采用，但是对于敏捷实践的复杂性，特别是与传统的基于瀑布的方法的潜在冲突和相互作用的深入研究仍然很少。采用系统评价和元分析的首选报告项目（PRISMA）方法，本系统评价旨在解决关于敏捷政府的概念、实施和影响的三个基本研究问题。为了加深理论认识和实践应用，我们的研究将敏捷分为三个不同的层次：微观（项目管理）、中观（组织管理）和宏观（治理结构）。我们的分析揭示了敏捷实践在这些层次上的实质性变化，反映了一种旨在与现有官僚系统协调一致的深思熟虑的策略。本研究通过提供政策启示和描绘未来研究努力的途径来结束。

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引用次数: 0

Bridging trust in AI and its adoption: The role of organizational support in AI chatbot implementation in korean government agencies 弥合对人工智能的信任及其采用：韩国政府机构在人工智能聊天机器人实施中的组织支持作用

IF 1 1区管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE

Government Information Quarterly

Pub Date : 2025-09-27 DOI: 10.1016/j.giq.2025.102081

Seongkyung Cho , Joon-Young Hur , Danee Kim

Amid rapid technological advancements, AI-chatbot integration into government workplaces represents a transformative shift to enhance communication, streamline administrative processes, and boost employee efficiency. Through a mixed-methods design combining survey data and employee interviews, this study analyzes how trust in AI chatbots influences employee utilization of chatbots in government organizations and examines organizational support's moderating role. By demonstrating the pivotal roles of trust and organizational support, this study emphasizes their combined effect on driving adoption and digital transformation within government agencies. Findings provide insights for government administrators and policymakers, guiding the development of trust-building strategies and organizational support mechanisms to promote effective chatbot adoption in public-sector workplaces. This research fills the empirical gap in understanding chatbot adoption from the perspective of government employees and illuminates opportunities and challenges as public-sector employees adapt to technological changes in their work environments.

随着技术的快速发展，人工智能聊天机器人融入政府工作场所是加强沟通、简化行政流程、提高员工效率的革命性转变。本研究通过结合调查数据和员工访谈的混合方法设计，分析了政府机构对AI聊天机器人的信任如何影响员工对聊天机器人的使用，并考察了组织支持的调节作用。通过展示信任和组织支持的关键作用，本研究强调了它们在推动政府机构采用和数字化转型方面的综合作用。研究结果为政府管理者和政策制定者提供了见解，指导建立信任战略和组织支持机制的发展，以促进公共部门工作场所有效采用聊天机器人。本研究填补了从政府雇员角度理解聊天机器人采用的经验空白，并阐明了公共部门雇员在适应工作环境中的技术变革时所面临的机遇和挑战。

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引用次数: 0