{"title":"Exploiting GPT for synthetic data generation: An empirical study","authors":"Tony Busker , Sunil Choenni , Mortaza S. Bargh","doi":"10.1016/j.giq.2024.101988","DOIUrl":"10.1016/j.giq.2024.101988","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":48258,"journal":{"name":"Government Information Quarterly","volume":"42 1","pages":"Article 101988"},"PeriodicalIF":7.8,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143136134","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}
Claire Ingram Bogusz , Johan Magnusson , Mattias Rost
{"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}
Houcai Wang , Zhenya Robin Tang , Li Xiong , Xiaoyu Wang , Lei Zhu
{"title":"What determinants influence citizens' engagement with mobile government social media during emergencies? A net valence model","authors":"Houcai Wang , Zhenya Robin Tang , Li Xiong , Xiaoyu Wang , Lei Zhu","doi":"10.1016/j.giq.2024.101995","DOIUrl":"10.1016/j.giq.2024.101995","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":48258,"journal":{"name":"Government Information Quarterly","volume":"42 1","pages":"Article 101995"},"PeriodicalIF":7.8,"publicationDate":"2024-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143136132","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Data-driven intelligence in crisis: The case of Ukrainian refugee management","authors":"Kilian Sprenkamp , Mateusz Dolata , Gerhard Schwabe , Liudmila Zavolokina","doi":"10.1016/j.giq.2024.101978","DOIUrl":"10.1016/j.giq.2024.101978","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":48258,"journal":{"name":"Government Information Quarterly","volume":"42 1","pages":"Article 101978"},"PeriodicalIF":7.8,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143136131","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}
{"title":"Analyzing digital government partnerships: An institutional logics perspective","authors":"Yiwei Gong, Yan Yang","doi":"10.1016/j.giq.2024.101987","DOIUrl":"10.1016/j.giq.2024.101987","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":48258,"journal":{"name":"Government Information Quarterly","volume":"42 1","pages":"Article 101987"},"PeriodicalIF":7.8,"publicationDate":"2024-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143136130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Rodrigo Sandoval-Almazan , Adrian Osiel Millan-Vargas , Rigoberto Garcia-Contreras
{"title":"Examining public managers' competencies of artificial intelligence implementation in local government: A quantitative study","authors":"Rodrigo Sandoval-Almazan , Adrian Osiel Millan-Vargas , Rigoberto Garcia-Contreras","doi":"10.1016/j.giq.2024.101986","DOIUrl":"10.1016/j.giq.2024.101986","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":48258,"journal":{"name":"Government Information Quarterly","volume":"41 4","pages":"Article 101986"},"PeriodicalIF":7.8,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142742944","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Open Government Data (OGD) as a catalyst for smart city development: Empirical evidence from Chinese cities","authors":"Ruoyun Wang, Corey Kewei Xu, Xun Wu","doi":"10.1016/j.giq.2024.101983","DOIUrl":"10.1016/j.giq.2024.101983","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":48258,"journal":{"name":"Government Information Quarterly","volume":"41 4","pages":"Article 101983"},"PeriodicalIF":7.8,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143171984","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"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","authors":"Sebastian Hemesath , Markus Tepe","doi":"10.1016/j.giq.2024.101985","DOIUrl":"10.1016/j.giq.2024.101985","url":null,"abstract":"<div><div>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 (<em>n</em> = 1690) and front desk officers in municipalities (<em>n</em> = 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.</div></div>","PeriodicalId":48258,"journal":{"name":"Government Information Quarterly","volume":"41 4","pages":"Article 101985"},"PeriodicalIF":7.8,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143171985","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}
{"title":"Regulating generative AI: The limits of technology-neutral regulatory frameworks. Insights from Italy's intervention on ChatGPT","authors":"Antonio Cordella , Francesco Gualdi","doi":"10.1016/j.giq.2024.101982","DOIUrl":"10.1016/j.giq.2024.101982","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":48258,"journal":{"name":"Government Information Quarterly","volume":"41 4","pages":"Article 101982"},"PeriodicalIF":7.8,"publicationDate":"2024-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142705244","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}
{"title":"A more secure framework for open government data sharing based on federated learning","authors":"Xingsen Zhang","doi":"10.1016/j.giq.2024.101981","DOIUrl":"10.1016/j.giq.2024.101981","url":null,"abstract":"<div><div>Open government data, abbreviated as OGD, attracts significant public interest with substantial social value recently, which enables the government to make more accurate and efficient decisions based on real and comprehensive data. It also helps break down information silos, improve service quality and management efficiency, and enhance public trust in government activities. This is crucial for advancing public management modernization, fostering technological innovation, and strengthening governance capabilities. The focus of this study is how to solve the problem of more secure sharing of OGD. And we developed a more secure framework for open government data sharing based on federated learning. Inspired by the government data authorization operation model, this framework includes four categories of participants: OGD providers, OGD collectors, OGD operators, and OGD users. We further analyzed modeling techniques for horizontal federated learning, vertical federated learning, and federated transfer learning. By applying this framework to typical scenarios in China, its actual effectiveness has been illustrated in preventing information leakage, protecting data privacy, and improving model security, providing more reliable and efficient solutions for government governance and public services. Future research can continuously explore the application of privacy-computing-related technologies in secure sharing of OG to further enhance data security and the potential of OGD.</div></div>","PeriodicalId":48258,"journal":{"name":"Government Information Quarterly","volume":"41 4","pages":"Article 101981"},"PeriodicalIF":7.8,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142652533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}