Government-citizen Interactions Research Articles

OECD COUNTRIES' EXPERIENCE IN TRANSFORMATION OF PUBLIC SERVICE DELIVERY SYSTEMS

The article discusses the growing importance of digital transformation in public administration, with a focus on the experiences of various countries like South Korea, the U.S., and Sweden. It examines how governments worldwide are leveraging new technologies such as artificial intelligence, cloud computing, and mobile applications to enhance public service delivery. Key objectives include improving efficiency, transparency, and citizen satisfaction while fostering stronger government-citizen interactions. The article also touches on challenges faced during the digital transformation, such as data protection, coordination, and legal frameworks. The research highlights successful strategies in digital governance, such as South Korea’s leadership in e-government, which enabled it to excel in global rankings. It underscores the significance of strong leadership and comprehensive strategies, including the use of a "control room" to manage inter-departmental coordination. Kazakhstan, which has adopted a new Concept of the development of civil service for 2024-2029, is seeking to apply these international best practices to develop proactive, citizen-centered public services and enhance government efficiency through digitalization.

The decision-making by citizens: Evaluating the effects of rule-driven and learning-driven automated responders on citizen-initiated contact

While many studies have investigated the impact of artificial intelligence (AI) deployment in the public sector on government-citizen interactions, findings remain controversial due to the technical complexity and contextual diversity. This study distinguishes between rule-driven and learning-driven AI and explores their impact as automated respondents on citizen-initiated contact, an important scenario for public participation with initiative. Based on a conjoint experiment with 763 participations (4578 observations), this study suggests that AI deployments enormously reduce the likelihood of citizen-initiated contact compared to human response, with learning-driven AI having a higher negative effect than rule-driven AI. In addition, the causal effects of respondent image, contact channel, contact purpose, and matter attributes on citizen-initiated contact, as well as their moderating effects, are explored. These findings make theoretical implications and calls for public participation in the roaring AI deployment in the public sector.

Uncovering the Results of AI Chatbot Use in the Public Sector: Evidence from US State Governments

The use of artificial intelligence (AI) chatbots in the public sector worldwide has increased in recent years. Despite its increasing use, public administration research in this area faces some limitations. First, much of the current research is theoretical and normative, lacking substantial empirical data to assess the results of chatbots. Second, the specific effects of chatbots on government organization operations and their interactions with the public are not well understood. The purpose of this empirical study is to explore how chatbots influence government operations and their relationship with citizens. We conducted in-depth interviews with officials and employees from twenty-two state agencies in the United States. Leveraging insights from public sector innovation and digital transformation literature, our study reveals various process- and product-related outputs and outcomes within organizations and in government-citizen interactions stemming from chatbot use.

A three-model approach to understand social media-mediated transparency in public administrations

The use of social media has promised to enhance administrative transparency. Whether having positive or negative impacts, some scholars agree that such impacts could come from the mediating effects of the perceived characteristics of social media. This is a similar idea to that proposed by the concept of computer-mediated transparency. However, social media has certain properties that might influence transparency in different ways. This article tries to understand social media-mediated transparency. The study uses the affordances theory to approach the perception of social media properties, conducting interviews with community managers from three Spanish city councils. The results show several ways of understanding social media-mediated transparency: the guarantor model (focuses on availability and accessibility of information, while ensuring neutrality), the conversational model (reinforces effective transparency through continuous conversations), and the proactive model (anticipates citizen informational needs). The article signals the differential nature of social media-mediated transparency and its limits, with implications for digital government–citizen interactions. Points for practitioners The article proposes three different ways of looking at social media-mediated transparency. Social media-mediated transparency will vary depending on how public managers navigate through social media affordances. Different models of social media-mediated transparency might link with different ways of institutionalizing these digital platforms, as well as with different considerations on citizens’ roles. Transparency through social media is more than just pushing information, but also an opportunity to improve effective monitoring through continuous conversations.

Activating Co-production of Rural Service Delivery: Examining the Role of Nonprofit Organizations Using a Case Study in China

Although co-production between the government and society can improve service outcomes, the two parties may lack the willingness and the capacity to cooperate. Can nonprofit organizations play an active role in facilitating government–citizen co-production? If so, how? The role of nonprofits in social services co-production has received increasing attention, but studies on developing countries are limited. Therefore, this study conducts an in-depth case study of a rural social work institute in Z village, Beijing, China. Using on-site observations, semi-structured interviews, and secondhand materials, we found that social workers adopted four strategies to engage community officials and rural residents in service co-production. They established trustworthy relationships, facilitated effective communication, fostered shared motivation, and built co-productive capacity. The results showed that nonprofit organizations use third-party roles and professional skills to shape government-citizen interactions through service co-production. These findings can improve rural service provision in developing countries.

Mechanisms Influencing the Digital Transformation Performance of Local Governments: Evidence from China

The transformation of the government into a digital entity is imperative, serving not only as a catalyst for the modernization of China’s governance system and capacity but also as a cornerstone for advancing the digital economy and the establishment of a digital China. This paper presents a multi-level analytical framework designed to assess the digital transformation performance of local governments. Utilizing a dataset comprising macro-regional and micro-individual data from Hubei province, we conduct an extensive analysis to examine the underlying mechanisms that influence the digital transformation performance of local governments and employ the hierarchical linear model (HLM) as the primary analytical instrument. The results of our analysis show that individual-level government–citizen interactions, government image, and district-level department collaborative capacities exert substantial and positive influences on the digital transformation performance of local governments. Furthermore, it is worth noting that department collaborative capacity plays a significant and positive moderating role in the relationship between government image and the digital transformation performance of local governments. These findings not only offer valuable insights for optimizing policy formulation but also contribute to a more comprehensive understanding of the mechanisms underlying the digital transformation performance of local governments.

Sentiment Analysis to Measure Public Trust in the Government Due to the Increase in Fuel Prices Using Naive Bayes and Support Vector Machine

The study examines public sentiment on the government's fuel price policy using an experimental approach and Twitter data obtained through API scraping. It applies sentiment analysis methods like Naïve Bayes, SVM, and Majority Voting. SVM achieved 85% accuracy, excelling in identifying negative sentiments, while Majority Voting reached 70% by considering confidence levels. Naïve Bayes struggled with neutral sentiments. They are combining methods to enhance the understanding of public sentiments on fuel price changes. The study highlights sentiment analysis' effectiveness in gauging reactions to fuel policies, with SVM offering more profound insights into sentiments related to fuel price hikes. Challenges remain in identifying neutral sentiments due to social media text brevity. These findings underscore the contextual importance of interpreting sentiment analysis. Leveraging these insights, governments can understand public perceptions better and devise improved communication strategies for sensitive economic policies like fuel price hikes, fostering better government-citizen interactions. The study aims to guide stakeholders in comprehending public perspectives within public policy, emphasizing the relevance of sentiment analysis for policy evaluation.

Citizen-initiated interactions in urban water governance: How public authorities respond to micro-level opinions related to nature-based solutions

Public opinions have become increasingly salient in water environmental governance, especially in implementing nature-based solutions (NBS) projects. However, current studies stay short of focusing on user-generated data on online participation platforms and the real public opinions and concerns on NBS revealed through spontaneous and interactive participation. In response to insufficient explorations on micro-level government-citizen interactions, this study adopts text mining analysis to evaluate different NBS-related topics and investigates targeted government responses from Jan 1st, 2020 to Apr 1st, 2022 in China. The results indicate that public participation on online government-citizen interaction platforms is no longer an instrumental level of “pseudo participation”. Based on dialogic communication theory (DCT), the silent majority affected by NBS started to express diverse opinions, i.e., seeking help, complaint, and suggestion. Moreover, instead of top-down or one-way communication, authorities are beginning to shift towards an open and responsive government. Hence, most public opinions can receive online feedback from authorities with targeted strategies (i.e., explaining, coordinating, and guiding), forming a “dialogic loop”. Nevertheless, there is still a lack of timely government response in NBS communication. Findings can contribute to developing a systematic understanding of micro-level demands associated with NBS and supplement relevant policies and decision-making for urban water governance.

Assessing inclusivity in online platforms through usability evaluation with Google Analytics

AbstractAs online platforms are swiftly becoming a dominant interface of government–citizen interactions, it is crucial that these platforms are inclusive. This article considers the potential of using digital trace data for assessing inclusivity in online platforms. Given that Google Analytics (GA) is a popular tool for collecting and analyzing digital trace data, this article asks to what extent GA is useful in usability evaluation for assessing inclusivity. This article reports on a case study in which GA was used for the usability evaluation of an online participation platform of a local government in The Netherlands. The usability evaluation via GA highlights that the platform was less inclusive toward two categories of users, namely, mobile users and users who access the platform via social media or referral. We conclude that GA is helpful for assessing inclusivity in online government platforms, particularly to the extent that it can be used to monitor whether there are differences in usability for different categories of users. Shortcomings of GA are that it gives limited insights into underlying reasons for identified behavioral patterns, that data quality can be compromised, and that functionalities of GA are restricted based on privacy or legal considerations.

End-User Satisfaction Through Mobile Governance: A Case Study in Hyderabad, Telangana State

In terms of technology, the Government of Telangana has made an effort to rebuild mobile-based services for its citizens with the goal of providing functional services 24 hours a day, 7 days a week at the press of a button. This study, therefore, examines the elements that influence mobile governance in the context of end-user’s satisfaction. Such assessments are needed for better government–citizen interactions. Furthermore, the major findings suggest that the functional status, privacy concerns, informational quality, grievance redressal and customer’s satisfaction are all linked to the quality of the m-governance services delivery mechanism in Hyderabad. This study contributes to a better understanding of service quality components in order to boost end-user acceptance of mobile services in practice.

AI-based Twitter framework for assessing the involvement of government schemes in electoral campaigns

The government schemes (also known as programs and plans) or social welfare policies can be defined as the set of assistance and aids provided by the country’s governance body. These schemes focus on the improved well-being of needful citizens. Some researchers have shown that introducing such policies and schemes has had an electoral impact in democratic countries. These earlier studies relied upon the post-poll and public survey data to reach conclusions. However, this data source has limitations and has to be collected manually, which makes it time-consuming and costly. The readily available internet inculcates the sharing of opinions freely on social media, facilitating government–citizen interactions. These interactions may show fluctuations in frequency and intensity on social media with the success and failure of some government schemes. Thus, this research proposes utilizing the Twitter data related to the government welfare schemes during the election duration to uncover the spatial and temporal relationships between the tweets’ information diffusion pattern and political elections. To start with, we perform tweet classification to identify the target communities or groups and multiple user-engagements by employing deep learning-based pre-trained language representation (LR) models. The scarcity of labeled data limits the application of the supervised classification models on real-time data. Thus, we propose Mod-EDA, a text augmentation method to upscale the labeled data for reduced overfitting. Going further, we propose two modules, where the classified tweets are studied to investigate the scheme tweets’ information diffusion pattern in correspondence to the election duration in terms of the voting phase and the electing parties, respectively. The proposed framework is evaluated for a case study of the 2019 Indian general elections. This study depicts that the voting phases and election duration trigger high government schemes related tweet generation. However, it is not affected by the location of the voting phase. The generation of complaints and negative tweets in one voting phase is covered with the positive news in subsequent voting phases. It is also seen that there is a strong influence of the ruling party on the scheme-related Twitter data generation.

Are emerging technologies helping win the fight against corruption? A review of the state of evidence

Information and Communication Technology (ICT) is often thought of as a uniformly positive tool making governments more transparent, accountable, and less corrupt. However, the evidence on it is mixed and often misunderstood. Hence, this article carries out a systematic stocktaking of ICT tools’ impact on corruption, offering a nuanced and context-dependent assessment. The tools reviewed are digital public services, crowdsourcing platforms, whistleblowing tools, transparency portals, distributed ledger technology, and artificial intelligence. We scrutinise the evidence both on ICTs’ anticorruption effectiveness and misuse for corruption. Drawing on the commonalities across technologies, we find that ICT can support anti-corruption by impacting public scrutiny in numerous ways: enabling reporting on corruption, promoting transparency and accountability, facilitating citizen participation and government-citizen interactions. However, ICT can also provide new corruption opportunities through the dark web, cryptocurrencies, or the misuse of technologies such as centralised databases. The introduction of ICT tools does not automatically translate into anti-corruption outcomes; rather, impact hinges on the matching between ICT tools and the local context, including support for and skills in using technology.

Analyzing and Visualizing Government-Citizen Interactions on Twitter to Support Public Policy-making

Twitter is widely adopted by governments to communicate with citizens. It has become a major source of data for analyzing how governments communicate with citizens and how citizens respond to such communication, uncovering important insights about government-citizen interactions that could be used to support public policy-making. This article presents research that aims at developing a software tool called Twitter Analytics for Government Intelligence and Public Participation (TA4GIP) that applies sentiment analysis and visualization techniques to information collected from Twitter and presents the findings to policy-makers and other non-technical users to facilitate understanding and interpretation. The use of the tool is illustrated through the case study of Twitter communication carried by five government secretaries responsible for health, education, social development, labor, and environment sectors in Mexico, and corresponding citizen responses over a nine-month period. The case study demonstrates that TA4GIP helps identify and analyze relevant aspects of government presence and citizen participation on social media, such as abnormal activity, salient topics being discussed, citizen views about enacted public policies, correlations between types of emotions in responses to particular government announcements, topics that generate polarized reactions from citizens, and many others.

Can the use of government Apps shape citizen compliance? The mediating role of different perceptions of government

Although government applications (Apps) have developed rapidly in recent years, few studies have paid attention to the consequences of government App use on citizen compliance. In response to this gap, this study divides citizens' government App use into informational use, service use and participatory use, and explores the impact of such use on citizen compliance, and the mediating role of trust in government, government transparency and government reputation on that relationship, by conducting a study of citizens in Guangzhou, Wuhan and Chengdu. The findings confirm that the service use and participatory use of government Apps positively predict trust in government and government reputation to varying degrees, while any one type of government App use cannot directly influence citizen compliance. This study also reveals the mediating mechanism of different perceptions of government on different types of government App use and citizen compliance, confirms the single mediation pathway to be the most effective pathway, and trust in government to be the most important mediator in the mediating process. Our findings further demonstrate that deep m-government usage behaviors under the condition of more sophisticated digital services and higher levels of government-citizen interactions can not only play a more effective role in promoting trust in government and government reputation, but also exert a potential impact on citizen compliance.

Public participation in the Geoweb era: Defining a typology for geo-participation in local governments

Advancements in citizen sensing and geospatial big data have enabled new opportunities for government-citizen interactions and have played important roles in developing smart(er) cities. In addition to city governments and citizens actively using maps to communicate spatial planning issues, the increasing capabilities of citizens generating spatial data either actively or passively allow city governments to collect local spatial knowledge with unprecedented breadth at finer spatiotemporal resolutions. New methods for citizens collaborating with city governments are also emerging to enhance citizen engagement and to spur social innovation. By synthesizing recent advancements in geo-enabled citizen participation, this paper proposed a new typology for classifying and characterizing concepts and practices related to geospatial technology-mediated public participation in local governments (e.g. city and municipal governments). Practical examples are used to illustrate how new dynamics between local governments and citizens are formed, new methods of collecting local spatial knowledge are enabled, and new opportunities for improving the openness and operational efficiency of local governments have emerged. The proposed conceptualization and examples give rise to emerging needs of advancing geo-participation by developing geospatial methods and infrastructure and by investigating the social and spatial implications of geo-participation.

Towards a theory of SocioCitizenry: Quality anticipation, trust configuration, and approved adaptation of governmental social media

The past few years have witnessed growing governmental interest in engaging citizens through social media. With this interest comes a genuine need to understand the process and outcomes of government–citizen interactions. Therefore, this article seeks to address this important issue by proposing and validating a SocioCitizenry theory that depicts government–citizen interaction through social media. The present study uses data gathered through two field surveys and analyses the relationships among three main SocioCitizenry constructs: quality anticipation, trust configuration, and approved adaptation. The following factors are examined with respect to the aforementioned three constructs: differential influences of familiarity with social media and government services; perceived importance of interactions with government services; social media quality reputation; and family members’ and friends’ perceptions of social media quality. Overall, results show that anticipated governmental social media quality influences configured trust, which in turn influences the extent of approved adaptation. The implications of these results in research and practice are discussed.

A Perception study on public response to E-service delivery in Bangladesh

Like others, Bangladesh government has taken initiative to deliver government services electronically in addition to traditional format. At present, Bangladesh is implementing e-government scheme under a political vision—Digital Bangladesh. The National ICT Policy of the country is also very much specific in spelling out the actors, allotted time-periods, and outcomes. Such endeavor is providing citizens with the convenience of receiving government information and services on their own terms, which has brought a key change in the government-citizen interactions. This study, therefore, intends to find the perception of citizens about the electronic delivery of services comparing it to the traditional format using mass-user survey. The findings indicate that occupational track affects the perception. The paper concludes that most of the stakeholders in Bangladesh favor the electronic format over the conventional one regarding efficiency in service delivery.

The Influence of Group Communication, Government–Citizen Interaction, and Perceived Importance of New Media on Online Political Discussion

Online political discussion is a growing form of political behavior and plays an important role in political deliberation in the new media age. This article examines “daily talk” as a type of political deliberation, and emphasizes two overlooked factors that influence online political discussion: direct government–citizen interactions and perceptions of the importance of new media for online political discussion. It also examines the moderation effects of perceived importance of new media on group communication and government–citizen interaction. Survey data analysis from the 2008 Civic Engagement survey from the Pew Internet & American Life Project (n = 2,251) reveals that citizens' interactions with both members of their political group and government officials have positive influences on the frequency of online political discussion. Meanwhile, the association between online political discussion and online group communication becomes stronger when one perceives that new media are less important as source of political information. The theoretical and policy implications of the findings are discussed.

Visual events and electronic government: What do pictures mean in digital government for citizen relations?

Abstract E-government is becoming more picture-oriented. What meaning do stakeholders attach to visual events and visualization? Comparative case study research show the functional meaning primarily refers to registration, integration, transparency and communication. The political meaning refers to new ways of framing in order to secure specific interests and claims. To what the institutional meaning relates is ambiguous: either it improves the position of citizens, or it reinforces the existing bias presented by governments. Hence, we expect that the emergence of a visualized public space, through omnipresent penetration of (mobile) multimedia technologies, will influence government–citizen interactions.

Customized Delivery of E-Government Web Services

The Web is revolutionizing the way citizens interact with businesses and government agencies. Almost all key functions of modern society are being reshaped to exploit opportunities the Web opens. As part of an effort to improve government-citizen interactions, government agencies are providing a wide spectrum of online services. Virginia Tech is collaborating with the Virginia Department for the Aging (VDA) on a project called WebSenior. A middleware infrastructure, WebSenior automatically delivers e-government services customized for seniors. It uses ontologies to automatically generate Web services customized to senior citizens' needs and government program laws and regulations.