Government Information Quarterly最新文献_第10页

Open government data and self-efficacy: The empirical evidence of micro foundation via survey experiments 开放政府数据与自我效能：通过调查实验的微观基础实证

IF 7.8 1区管理学

Government Information Quarterly Pub Date : 2024-12-01 Epub Date: 2024-10-18 DOI: 10.1016/j.giq.2024.101975

Kuang-Ting Tai , Pallavi Awasthi , Ivan P. Lee

{"title":"Open government data and self-efficacy: The empirical evidence of micro foundation via survey experiments","authors":"Kuang-Ting Tai , Pallavi Awasthi , Ivan P. Lee","doi":"10.1016/j.giq.2024.101975","DOIUrl":"10.1016/j.giq.2024.101975","url":null,"abstract":"<div><div>Research on the potential impacts of government openness and open government data is not new. However, empirical evidence regarding the micro-level impact, which can validate macro-level theories, has been particularly limited. Grounded in social cognitive theory, this study contributes to the literature by empirically examining how the dissemination of government information in an open data format can influence individuals' perceptions of self-efficacy, a key predictor of public participation. Based on two rounds of online survey experiments conducted in the U.S., the findings reveal that exposure to open government data is associated with decreased perceived self-efficacy, resulting in lower confidence in participating in public affairs. This result, while contrary to optimistic assumptions, aligns with some other empirical studies and highlights the need to reconsider the format for disseminating government information. The policy implications suggest further calibration of open data applications to target professional and skilled individuals. This study underscores the importance of experiment replication and theory development as key components of future research agendas.</div></div>","PeriodicalId":48258,"journal":{"name":"Government Information Quarterly","volume":"41 4","pages":"Article 101975"},"PeriodicalIF":7.8,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142535130","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}

引用次数: 0

Explainable AI for government: Does the type of explanation matter to the accuracy, fairness, and trustworthiness of an algorithmic decision as perceived by those who are affected? 为政府提供可解释的人工智能：在受影响者看来，解释的类型对算法决策的准确性、公平性和可信度有影响吗？

IF 7.8 1区管理学

Government Information Quarterly Pub Date : 2024-12-01 Epub Date: 2024-09-13 DOI: 10.1016/j.giq.2024.101965

Naomi Aoki , Tomohiko Tatsumi , Go Naruse , Kentaro Maeda

{"title":"Explainable AI for government: Does the type of explanation matter to the accuracy, fairness, and trustworthiness of an algorithmic decision as perceived by those who are affected?","authors":"Naomi Aoki , Tomohiko Tatsumi , Go Naruse , Kentaro Maeda","doi":"10.1016/j.giq.2024.101965","DOIUrl":"10.1016/j.giq.2024.101965","url":null,"abstract":"<div><p>Amidst concerns over biased and misguided government decisions arrived at through algorithmic treatment, it is important for members of society to be able to perceive that public authorities are making fair, accurate, and trustworthy decisions. Inspired in part by equity and procedural justice theories and by theories of attitudes towards technologies, we posited that the perception of these attributes of decisions is influenced by the type of explanation offered, which can be input-based, group-based, case-based, or counterfactual. We tested our hypotheses with two studies, each of which involved a pre-registered online survey experiment conducted in December 2022. In both studies, the subjects (<em>N</em> = 1200) were officers in high positions at stock companies registered in Japan, who were presented with a scenario consisting of an algorithmic decision made by a public authority: a ministry's decision to reject a grant application from their company (Study 1) and a tax authority's decision to select their company for an on-site tax inspection (Study 2). The studies revealed that offering the subjects some type of explanation had a positive effect on their attitude towards a decision, to various extents, although the detailed results of the two studies are not robust. These findings call for a nuanced inquiry, both in research and practice, into how to best design explanations of algorithmic decisions from societal and human-centric perspectives in different decision-making contexts.</p></div>","PeriodicalId":48258,"journal":{"name":"Government Information Quarterly","volume":"41 4","pages":"Article 101965"},"PeriodicalIF":7.8,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0740624X24000571/pdfft?md5=79e232415d01bd4e88037e2540f7bb9f&pid=1-s2.0-S0740624X24000571-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142229033","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

Bridging the gap: Towards an expanded toolkit for AI-driven decision-making in the public sector 缩小差距：为公共部门的人工智能驱动决策开发扩展工具包

IF 7.8 1区管理学

Government Information Quarterly Pub Date : 2024-12-01 Epub Date: 2024-10-11 DOI: 10.1016/j.giq.2024.101976

Unai Fischer-Abaigar , Christoph Kern , Noam Barda , Frauke Kreuter

{"title":"Bridging the gap: Towards an expanded toolkit for AI-driven decision-making in the public sector","authors":"Unai Fischer-Abaigar , Christoph Kern , Noam Barda , Frauke Kreuter","doi":"10.1016/j.giq.2024.101976","DOIUrl":"10.1016/j.giq.2024.101976","url":null,"abstract":"<div><div>AI-driven decision-making systems are becoming instrumental in the public sector, with applications spanning areas like criminal justice, social welfare, financial fraud detection, and public health. While these systems offer great potential benefits to institutional decision-making processes, such as improved efficiency and reliability, these systems face the challenge of aligning machine learning (ML) models with the complex realities of public sector decision-making. In this paper, we examine five key challenges where misalignment can occur, including distribution shifts, label bias, the influence of past decision-making on the data side, as well as competing objectives and human-in-the-loop on the model output side. Our findings suggest that standard ML methods often rely on assumptions that do not fully account for these complexities, potentially leading to unreliable and harmful predictions. To address this, we propose a shift in modeling efforts from focusing solely on predictive accuracy to improving decision-making outcomes. We offer guidance for selecting appropriate modeling frameworks, including counterfactual prediction and policy learning, by considering how the model estimand connects to the decision-maker's utility. Additionally, we outline technical methods that address specific challenges within each modeling approach. Finally, we argue for the importance of external input from domain experts and stakeholders to ensure that model assumptions and design choices align with real-world policy objectives, taking a step towards harmonizing AI and public sector objectives.</div></div>","PeriodicalId":48258,"journal":{"name":"Government Information Quarterly","volume":"41 4","pages":"Article 101976"},"PeriodicalIF":7.8,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142421899","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

Does trust in government moderate the perception towards deepfakes? Comparative perspectives from Asia on the risks of AI and misinformation for democracy 对政府的信任会缓和对深度假新闻的看法吗？从亚洲的比较视角看人工智能和错误信息对民主的风险

IF 7.8 1区管理学

Government Information Quarterly Pub Date : 2024-12-01 Epub Date: 2024-10-19 DOI: 10.1016/j.giq.2024.101980

Taberez Ahmed Neyazi , Arif Hussain Nadaf , Khai Ee Tan , Ralph Schroeder

{"title":"Does trust in government moderate the perception towards deepfakes? Comparative perspectives from Asia on the risks of AI and misinformation for democracy","authors":"Taberez Ahmed Neyazi , Arif Hussain Nadaf , Khai Ee Tan , Ralph Schroeder","doi":"10.1016/j.giq.2024.101980","DOIUrl":"10.1016/j.giq.2024.101980","url":null,"abstract":"<div><div>There have recently been growing global concerns about misinformation, and more specifically about how deepfake technologies have been used to run disinformation campaigns. These concerns, in turn, have influenced people's perceptions of deepfakes, often associating them with threats to democracy and fostering less positive views. But does high trust in government mitigate these influences, thereby strengthening positive perceptions of deepfakes? In a cross-national survey conducted in Malaysia, Singapore, and India, we found no evidence of a negative association either between concern about the spread of misinformation online or perceived risks of AI to democracy, with positive attitudes towards deepfakes. However, when accounting for the moderating factor of trust in government, respondents in Singapore who have high trust levels exhibited more positive attitudes towards deepfakes, despite their concerns about misinformation. Similarly, higher trust in government correlated with more favorable perceptions of deepfakes even among those who view AI as a risk to democracy; this effect is evident across all three countries. In the conclusion, we spell out the implications of these findings for politics in Asia and beyond.</div></div>","PeriodicalId":48258,"journal":{"name":"Government Information Quarterly","volume":"41 4","pages":"Article 101980"},"PeriodicalIF":7.8,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142535131","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}

引用次数: 0

Open Government Data (OGD) as a catalyst for smart city development: Empirical evidence from Chinese cities 开放政府数据（OGD）作为智慧城市发展的催化剂：来自中国城市的经验证据

IF 7.8 1区管理学

Government Information Quarterly Pub Date : 2024-12-01 Epub Date: 2024-12-03 DOI: 10.1016/j.giq.2024.101983

Ruoyun Wang, Corey Kewei Xu, Xun Wu

{"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}

引用次数: 0

A more secure framework for open government data sharing based on federated learning 基于联合学习的更安全的开放式政府数据共享框架

IF 7.8 1区管理学

Government Information Quarterly Pub Date : 2024-12-01 Epub Date: 2024-11-11 DOI: 10.1016/j.giq.2024.101981

Xingsen Zhang

{"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":"2024-12-01","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}

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 电子政务中基于人工智能的聊天机器人的公众价值立场和设计偏好。证据来自市民和市政前台官员的联合实验

IF 7.8 1区管理学

Government Information Quarterly Pub Date : 2024-12-01 Epub Date: 2024-12-03 DOI: 10.1016/j.giq.2024.101985

Sebastian Hemesath , Markus Tepe

{"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}

引用次数: 0

Transforming towards inclusion-by-design: Information system design principles shaping data-driven financial inclusiveness 通过设计实现包容性转型：信息系统设计原则塑造数据驱动的金融包容性

IF 7.8 1区管理学

Government Information Quarterly Pub Date : 2024-12-01 Epub Date: 2024-10-17 DOI: 10.1016/j.giq.2024.101979

Reni Sulastri, Marijn Janssen, Ibo van de Poel, Aaron Ding

{"title":"Transforming towards inclusion-by-design: Information system design principles shaping data-driven financial inclusiveness","authors":"Reni Sulastri, Marijn Janssen, Ibo van de Poel, Aaron Ding","doi":"10.1016/j.giq.2024.101979","DOIUrl":"10.1016/j.giq.2024.101979","url":null,"abstract":"<div><div>Digitalization and datafication of financial systems result in more efficiency, but might also result in the exclusions of certain groups. Governments are looking for ways to increase inclusions and leave no one behind. For this, they must govern an organizational ecosystem of public and private parties. We derive value-based requirements through a systematic research methodology and iteratively refine design principles for achieving inclusivity goals. This refinement process is enriched by interviews with field experts, leading to the formulation of key Design principles: the essential role of inclusive metrics, leveraging alternative data sources, ensuring transparency in loan processes and the ability for decision contestation, providing tailored credit solutions, and maintaining long-term system sustainability. The government's role is to ensure a level playing field where all parties have equal access to the data. Following the principles ensures that exclusion and discrimination become visible and can be avoided. This study underscores the necessity for system-level transformations, inclusion-by-design, and advocacy for a new system design complemented by regulatory updates, new data integration, inclusive AI, and organizational collaborative shifts. These principles can also be used in different data-driven governance situations.</div></div>","PeriodicalId":48258,"journal":{"name":"Government Information Quarterly","volume":"41 4","pages":"Article 101979"},"PeriodicalIF":7.8,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142446915","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

Critical constraints on high performance of provincial E-governments in China: A necessary condition analysis 中国省级电子政务高绩效的关键制约因素：必要条件分析

IF 7.8 1区管理学

Government Information Quarterly Pub Date : 2024-09-01 Epub Date: 2024-07-24 DOI: 10.1016/j.giq.2024.101959

Xiaomin Zhang , Bin Chen , Bo Yan , Yao Liu , Long Wu

引用次数: 0

A conceptual digital policy framework via mixed-methods approach: Navigating public value for value-driven digital transformation 通过混合方法建立概念性数字政策框架：为价值驱动型数字化转型的公共价值导航

IF 7.8 1区管理学

Government Information Quarterly Pub Date : 2024-09-01 Epub Date: 2024-07-24 DOI: 10.1016/j.giq.2024.101961

Joong-Yeup Lee , Beomsoo Kim , Sang-Hyeak Yoon

引用次数: 0