Government Information Quarterly最新文献

英文中文

Evaluating incident reporting in cybersecurity. From threat detection to policy learning

IF 7.8 1区管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE

Government Information Quarterly

Pub Date : 2024-12-24 DOI: 10.1016/j.giq.2024.102000

Simone Busetti, Francesco Maria Scanni

The escalating threat of cyber risks has propelled cybersecurity policy to the forefront of governmental agendas worldwide. Incident reporting, a cornerstone of cybersecurity legislation, may facilitate swift responses to cyberattacks and foster a learning process for policy enhancement. Despite its widespread adoption, there are no analyses on its efficacy, implementation, and avenues for improvement. This article provides a theory-based evaluation of incident reporting using the methods of realist synthesis and process tracing. We develop a program theory of incident reporting hypothesizing its dual role as a fire alarm and a catalyst for policy learning. The program theory is tested by drawing upon a range of literature and official documents, supplemented by insights from the Italian context through interviews with key informants. The evaluation reveals mixed findings. While incident reporting effectively serves as a fire alarm, particularly for organizations with limited cybersecurity capacity, challenges persist due to capacity gaps and a reluctance to report incidents. The link between incident reporting and policy learning remains tenuous, with evidence of inertia hindering the implementation of more radical changes. Policy recommendations include streamlining internal communications, combining rapid and in-depth reporting, fostering data-sharing agreements, ensuring dedicated communication of lessons from central cyber actors, and streamlining organizational procedures for implementing changes.

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引用次数: 0

Exploiting GPT for synthetic data generation: An empirical study

IF 7.8 1区管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE

Government Information Quarterly

Pub Date : 2024-12-19 DOI: 10.1016/j.giq.2024.101988

Tony Busker , Sunil Choenni , Mortaza S. Bargh

There are many good reasons to use synthetic data instead of real data for research purposes. These reasons may range from the business sensitiveness of real data to increased cost of collecting real data in accordance with GDPR requirements. In this paper, we elaborate upon the potentials of the Large Language Model GPT as a tool to generate synthetic data for analytical purposes when there is no real-data available or accessible. Primarily, we show that by varying the scope of probes adequately, we can generate data of different granularities. To show this, we generated stereotypical data with three levels of granularity by posing more than 18,500 probes to GPT. In total, we generated stereotypical data for eight different views, which can be categorized in three view types corresponding to the three levels of granularity. Secondarily, we show that by varying the scope of probes one can create meaningful information. To show this, we performed a so-called similarity analysis on the generated stereotypical data. We used data visualizations, e.g. heatmaps, to show the views and categories within the views that are similar and those that are at odd with each other. We elaborate upon the application areas of the insight gained about such similarities and differences. Furthermore, we discuss several other types of analysis that can be performed on the generated stereotypical data.

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引用次数: 0

Leave it to the parents: How hacktivism-as-tuning reconfigures public sector digital transformation

IF 7.8 1区管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE

Government Information Quarterly

Pub Date : 2024-12-17 DOI: 10.1016/j.giq.2024.101996

Claire Ingram Bogusz , Johan Magnusson , Mattias Rost

Extant research on public sector digital transformation has emphasised the process of deliberate digital technology use by public organizations in pursuit of efficiency and innovation. Studies of the unintended or contrarian uses associated with digital technologies have been scarce. This study explores a case in which parents of schoolchildren in the City of Stockholm react to the perceived poor usability of a learning management system through citizen “hacktivism”. The parents developed a challenger app on top of an existing platform, to which the city reacted by trying to obstruct development work, both technically and through litigation. We interpret this as a case of digital transformation reconfiguration through boundary object tuning, legal tuning and digital transformation tuning. These lead to, respectively, reconfiguration of 1) the site of transparency and engagement, 2) the boundaries of responsibility and ownership and 3) the locus of control over public services. We contribute to the public sector digital transformation literature by offering tuning as a way to understand (re)configuration of the non-linear and dialectical and materially embedded process of digital transformation. We also empirically explore the phenomenon of citizen hacktivism, offering insights into associated processes and effects.

{"title":"Leave it to the parents: How hacktivism-as-tuning reconfigures public sector digital transformation","authors":"Claire Ingram Bogusz , Johan Magnusson , Mattias Rost","doi":"10.1016/j.giq.2024.101996","DOIUrl":"10.1016/j.giq.2024.101996","url":null,"abstract":"<div><div>Extant research on public sector digital transformation has emphasised the process of deliberate digital technology use by public organizations in pursuit of efficiency and innovation. Studies of the unintended or contrarian uses associated with digital technologies have been scarce. This study explores a case in which parents of schoolchildren in the City of Stockholm react to the perceived poor usability of a learning management system through citizen “hacktivism”. The parents developed a challenger app on top of an existing platform, to which the city reacted by trying to obstruct development work, both technically and through litigation. We interpret this as a case of digital transformation reconfiguration through <em>boundary object tuning</em>, <em>legal tuning</em> and <em>digital transformation tuning</em>. These lead to, respectively, reconfiguration of 1) the site of transparency and engagement, 2) the boundaries of responsibility and ownership and 3) the locus of control over public services. We contribute to the public sector digital transformation literature by offering tuning as a way to understand (re)configuration of the non-linear and dialectical and materially embedded process of digital transformation. We also empirically explore the phenomenon of citizen hacktivism, offering insights into associated processes and effects.</div></div>","PeriodicalId":48258,"journal":{"name":"Government Information Quarterly","volume":"42 1","pages":"Article 101996"},"PeriodicalIF":7.8,"publicationDate":"2024-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143136133","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

What determinants influence citizens' engagement with mobile government social media during emergencies? A net valence model

IF 7.8 1区管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE

Government Information Quarterly

Pub Date : 2024-12-12 DOI: 10.1016/j.giq.2024.101995

Houcai Wang , Zhenya Robin Tang , Li Xiong , Xiaoyu Wang , Lei Zhu

Citizens proactively engage in public deliberation during emergencies, which is pivotal for the success of emergency management. Drawing on the net valence model, the current manuscript investigates the antecedents for citizens' engagement in mobile government social media during emergencies. Using an online payment survey service provider, data were acquired from 740 subscribers to mobile government social media in mainland China. The research findings show that source credibility and perceived transparency, but not mobility, increased perceived benefits, which further increased citizens' engagement during emergencies. The findings also demonstrate that privacy risk and perceived Internet censorship increased perceived risk; however, perceived risk did not affect citizens' engagement during emergencies. These findings can inform future research on public participation with mobile government social media in emergencies and provide insights for emergency management practitioners.

引用次数: 0

Data-driven intelligence in crisis: The case of Ukrainian refugee management

IF 7.8 1区管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE

Government Information Quarterly

Pub Date : 2024-12-11 DOI: 10.1016/j.giq.2024.101978

Kilian Sprenkamp , Mateusz Dolata , Gerhard Schwabe , Liudmila Zavolokina

The ongoing conflict in Ukraine has triggered a humanitarian crisis, leading to a substantial increase in refugees. This situation presents a significant challenge for European countries, emphasizing the urgent need for effective refugee management strategies. Hence, effective decision-making is needed for the public sector to create a better livelihood for refugees. In this study, we propose using the concept of intelligence defined by Herbert Simon for effective refugee management. Following the Design Science Research Methodology, we utilize 58 semi-structured stakeholder interviews within Switzerland to identify problems and define design goals that facilitate intelligence in refugee management. Based on the design goals, we developed R2G – “Refugees to Government”, an application that utilizes community data and state-of-the-art NLP, including a chatbot interface, to offer an interactive dashboard for identifying refugee needs. The chatbot allows policymakers to interact with refugee data through dynamic, conversational queries, enabling real-time identification of refugee needs and providing data-driven intelligence. Our assessment of R2G, facilitated through 28 semi-structured interviews, resulted in four design principles for data-driven intelligence in refugee management: community-driven insight, spatial-temporal knowledge, multilingual data synthesis and visualization, and interactive data querying through chatbots. Additionally, we provide policy recommendations emphasizing the ethical use of community data, the integration of advanced NLP techniques in government processes, and the need for shifting governmental roles towards data analytics.

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引用次数: 0

Analyzing digital government partnerships: An institutional logics perspective

IF 7.8 1区管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE

Government Information Quarterly

Pub Date : 2024-12-06 DOI: 10.1016/j.giq.2024.101987

Yiwei Gong, Yan Yang

Digital government is transforming public service provision through collaboration between governments and companies. However, establishing digital government partnerships is complex and challenging, with governments often lacking a clear view of the influencing factors in various configurations and their underlying logics. Based on the theory of institutional logics, this study discusses the state, market, and corporation logic in digital government partnerships, and identifies six influencing factors. Employing a multiple qualitative comparative analysis method, the analysis of 31 provincial regions in Chinese mainland over five years derived 19 solutions that lead to a high digital government performance. These findings reveal the causal relationships between the configurational strategies for digital government partnerships and the different outcomes in terms of digital government performance. A series of propositions are derived to explain the logic multiplicity behind the configurations. This study theorizes the configurational relationships of the influencing factors and their underlying logics to enhance the understanding of the intricate diversity and dynamics exhibited within digital government partnerships.

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引用次数: 0

Examining public managers' competencies of artificial intelligence implementation in local government: A quantitative study 地方政府公共管理者实施人工智能能力的定量研究

IF 7.8 1区管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE

Government Information Quarterly

Pub Date : 2024-12-01 DOI: 10.1016/j.giq.2024.101986

Rodrigo Sandoval-Almazan , Adrian Osiel Millan-Vargas , Rigoberto Garcia-Contreras

The implementation of artificial intelligence in the public sector is a fast-evolving tendency in recent years. Despite much research on AI in government- ethics, algorithms, chatbots, AI systems-implement- there is very little data and understanding of the public manager's perception, adaptation, challenges, and resistance on this topic. What are the skills and knowledge needed to implement AI in the government? This research aims to investigate public managers' competencies to face AI challenges in the public sector. A survey was conducted among 38 key public managers from the government of the State of Mexico in the central region to assess their perceptions of AI. Using the competences for civil servants' framework from Balbo di Vinadio et al. (2022), we analyze three competences: (1) Digital Management and Execution (2) Digital Planning and Design (3) Data use and governance and their levels of. The findings point out that there is a lack of skills, and the competence of digital management and execution is the one that explains better this perception of AI in the local government.

近年来，人工智能在公共部门的应用是一个快速发展的趋势。尽管有很多关于政府中人工智能的研究——伦理、算法、聊天机器人、人工智能系统的实施——但很少有关于公共管理者对这个话题的感知、适应、挑战和抵制的数据和理解。在政府推行人工智能所需的技能和知识是什么？本研究旨在调查公共部门管理者应对人工智能挑战的能力。对中部地区墨西哥政府的38名主要公共管理人员进行了一项调查，以评估他们对人工智能的看法。使用Balbo di Vinadio等人（2022）的公务员能力框架，我们分析了三种能力：(1)数字管理和执行(2)数字规划和设计(3)数据使用和治理及其水平。调查结果指出，缺乏技能，数字管理和执行的能力可以更好地解释地方政府对人工智能的这种看法。

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引用次数: 0

Open Government Data (OGD) as a catalyst for smart city development: Empirical evidence from Chinese cities

IF 7.8 1区管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE

Government Information Quarterly

Pub Date : 2024-12-01 DOI: 10.1016/j.giq.2024.101983

Ruoyun Wang, Corey Kewei Xu, Xun Wu

While existing smart city models recognize the importance of data, they often overlook the specific role of Open Government Data (OGD) for urban development. This study addresses this gap by adapting the Smart City Model to explicitly include OGD as a critical component. Drawing on panel data from the 2022–2024 Chinese Cities Digitalization Evolution Index, we employ Structural Equation Modeling (SEM) to empirically examine the direct and indirect effects of OGD, digital infrastructure, and digital economy on smart city development. Our analysis identifies four key pathways, revealing that while digital infrastructure positively influences smart city development directly, the indirect pathways incorporating OGD demonstrate stronger effects. OGD plays a pivotal role by significantly enhancing the digital economy and digital infrastructure, as well as directly contributing to smart city development. This research contributes to the smart city literature by moving beyond discussions of individual components to empirically test the relationships between these elements. By positioning OGD as a catalyst, we provide a nuanced understanding of the mechanisms through which data-driven initiatives empower smart city development. Our findings offer valuable insights into the multifaceted ways OGD serves as a driving force for urban innovation, challenging the traditional view of government data as a passive resource. This study highlights the importance of OGD as a strategic asset for policymakers seeking to harness the potential of data-driven urban governance. We conclude with policy recommendations for leveraging OGD to support sustainable and efficient smart city development.

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引用次数: 0

Public value positions and design preferences toward AI-based chatbots in e-government. Evidence from a conjoint experiment with citizens and municipal front desk officers

IF 7.8 1区管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE

Government Information Quarterly

Pub Date : 2024-12-01 DOI: 10.1016/j.giq.2024.101985

Sebastian Hemesath , Markus Tepe

Developing a chatbot to handle citizen requests in a municipal office requires multiple design choices. We use public value theory to test how value positions shape these design choices. In a conjoint experiment, we asked German citizens (n = 1690) and front desk officers in municipalities (n = 267) to evaluate hypothetical chatbot designs that differ in their fulfillment of goals derived from different value positions: (1) maintaining security, privacy, and accountability, (2) improving administrative performance, and (3) improving user-friendliness and empathy. Experimental results show that citizens prefer chatbots programmed by domestic firms, value chatbots taking routine decisions excluding discretion, and strongly prefer human intervention when conversations fail. While altering the salience of public sector values through priming does not affect citizens' design choices consistently, we find systematic differences between citizens and front desk officers. However, these differences are qualitative rather than fundamental. We conclude that citizens and front desk officers share public values that provide a sufficient basis for chatbot designs that overcome a potential legitimacy gap of AI in citizens-state service encounters.

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引用次数: 0

Regulating generative AI: The limits of technology-neutral regulatory frameworks. Insights from Italy's intervention on ChatGPT 监管人工智能的生成：技术中立监管框架的局限性。意大利干预 ChatGPT 的启示

IF 7.8 1区管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE

Government Information Quarterly

Pub Date : 2024-11-23 DOI: 10.1016/j.giq.2024.101982

Antonio Cordella , Francesco Gualdi

Existing literature has predominantly concentrated on the legal, ethical, governance, political, and socioeconomic aspects of AI regulation, often relegating the technological dimension to the periphery, reflecting the design, use, and development of AI regulatory frameworks that are technology-neutral. The emergence and widespread use of generative AI models present new challenges for public regulators aiming at implementing effective regulatory interventions. Generative AI operates on distinctive technological properties that require a comprehensive understanding prior to the deployment of pertinent regulation. This paper focuses on the recent case of the suspension of ChatGPT in Italy to explore the impact the specific technological fabric of generative AI has on the effectiveness of technology-neutral regulation. By drawing on the findings of an exploratory case study, this paper contributes to the understanding of the tensions between the specific technological features of generative AI and the effectiveness of a technology-neutral regulatory framework. The paper offers relevant implications to practice arguing that until this tension is effectively addressed, public regulatory interventions are likely to underachieve their intended objectives.

现有文献主要集中在人工智能监管的法律、伦理、治理、政治和社会经济方面，往往将技术层面置于边缘，反映了技术中立的人工智能监管框架的设计、使用和发展。生成式人工智能模型的出现和广泛使用，对旨在实施有效监管干预的公共监管机构提出了新的挑战。生成式人工智能具有独特的技术特性，需要在部署相关监管措施之前对其进行全面了解。本文以最近意大利暂停 ChatGPT 的案例为重点，探讨了生成式人工智能的特定技术结构对技术中立监管的有效性的影响。通过利用探索性案例研究的结果，本文有助于理解生成式人工智能的特定技术特征与技术中立监管框架的有效性之间的紧张关系。本文认为，在这种矛盾得到有效解决之前，公共监管干预很可能无法实现其预期目标，从而为实践提供了相关启示。

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