A Realist Perspective on AI-era Public Management

Recent years have witnessed a number of significant ideas and approaches to addressing the shortcomings of the New Public Management paradigm. Three of these recent ideas, which include Digital Era Governance, Public Value Management, and New Public Governance, emphasise partnerships collaboration and engagement of citizens; performance governance and innovation and recognize the transformational potentials of digital technologies. Artificial Intelligence (AI) is one of the digital technologies attracting the greatest interest in public administration in terms of its potential impact. There are already a number of reports on how AI is being deployed in the public sector with good outcomes. By employing a realist review approach, this study investigates the specific mechanisms across post-NPM, organisational, individual and innovation contexts which are associated with positive outcomes from AI initiatives in the public sector. The study further examined the specific applications of AI initiatives within Post-NPM agendas. Our findings provide some empirical evidence for a better understanding of the conditions and where to target AI-based solutions in post-NPM context for positive outcomes

Towards a Smart Sustainable City Roadmap : Identifying Competency Gaps

This workshop of the CAP4CITY (Erasmus+ Strengthening Governance Capacity for Smart Sustainable Cities) project is to promote and stimulate the discussion and networking in the area of Digital Government. Smart Sustainable Cities and related concepts of Digital, Intelligent and Smart Cities represent a progression of how cities around the world apply digital technology to serve their populations, pursue sustainable socio-economic development, and transform themselves in the process, and require strong capacity for public governance in the digital world. In order to identify the gaps concerning missing knowledge and training needs in this area we propose to validate a Smart Sustainable Cities roadmap through a scenario-building approach.Trabajo publicado en Chen, Y. C., Salem, F., Zuiderwijk, A. (eds.). dg.o 2019: Proceedings of the 20th Annual International Conference on Digital Government Research. Association for Computing Machinery: New York, 2019.Facultad de Informátic

From experimentation to public service delivery in social media. An analysis of institutionalization dynamics in Dutch local governments

Social media is being used by a large part of local administrations. As a highly disruptive adopted innovation, it is important to understand the process of institutionalization through empirical variables. This paper studies the Dutch case to analyze to what extent social media technologies have being institutionalized within major city councils in Netherlands. The study tries to answer the following research question: What is the level of institutionalization of social media in Dutch city councils with more than 50,000 inhabitants? Taking this into account, this work is based on two analytical levels: on the one hand, it performs a comparative analysis of Dutch city councils that responded to a survey on social media institutionalization. On the other hand, based on previous descriptive empirical results, the paper studies Utrecht as a case of success to analyze the level of social media institutionalization through Social Network Analysis and automated natural language processing with data crawled from Twitter. Overall, results show that social media institutionalization in Dutch city councils has been high, developing decentralized practices with formal commitments for social media use and with a high sense of leadership, showing interesting participatory and public service delivery logics. At the same time, the case of Utrecht confirms that a high level of institutionalization requires management capabilities and goals definition and implementation, including a conversational approach to citizens, and an emerging approach to public service delivery

Problem Conceptualization as a Foundation of Data Analytics in Local Governments: Lessons from the City of Syracuse, New York

The use data and data analytics (DA) has been attracting the attention of academics and practitioners in the public sector and is sometimes seen as a potential strategy for process and service innovation. While research on the many possible uses of data have clearly increased - open data, big data, data analytics- empirical research on the socio-technical process that local governments followed when using data analytics to improve services and policies is still scarce. Based on existing literature about data analytics in the public sector and the data lifecycle concept, this paper examines how data analytics is actually used in a local government and what are the main steps in this process. It analyzes the experience of a mid-size American city that had a dedicated task force to data analytics use to support decision making at the local level – Syracuse, New York. Findings suggest that data analytics as a process not only involves data analysis and representations (such as visualizations), but also data collection and cleaning. Further, it seems clear that the conceptualization of the problem is a critical step in producing meaningful data analytics, but also in thinking about innovations even when data is not readily available

Smart Technology and the Emergence of Algorithmic Bureaucracy:Artificial Intelligence in UK Local Authorities

In recent years, local authorities in the UK have begun to adopt a variety of ‘smart’ technological changes to enhance service delivery. These changes are producing profound impacts on the structure of public administration. Focusing on the particular case of artificial intelligence, specifically autonomous agents and predictive analytics, a combination of desk research, a survey questionnaire, and interviews were used to better understand the extent and nature of these changes in local government. Findings suggest that local authorities are beginning to adopt smart technologies and that these technologies are having an unanticipated impact on how public administrators and computational algorithms become imbricated in the delivery of public services. This imbrication is described as algorithmic bureaucracy and it provides a framework within which to explore how these technologies transform both the socio‐technical relationship between workers and their tools, as well as the ways that work is organized in the public sector

Educational Open Government Data in Germany: The Landscape, Status, and Quality

This paper examines the educational datasets of Open Government Portals (OGPs) in Germany. While OGPs has become an important player in making public data available, the quality and coverage are increasingly problematized. This study analyzes the quality of 28 OGPs, 18 on the city-level, seven on the state-level (the city-states of Berlin, Hamburg, and Bremen were counted as states), and three at the national level. The focus of this study is on identifying the gap in open educational data. The results show that the total number of datasets and the educational data varies very much between the portals. While the portals contain 94% ‘open’ datasets, most of the portals do not provide comprehensive usage metrics like the data download, evidence of usage in research or applications. Finally, the paper highlights the main shortcomings of the existing open data portals regarding the quality of datasets and the lack of findability and granularity

Populism, Twitter, and COVID-19: narrative, fantasies, and desires

10.3390/socsci10080294During a global pandemic, the great impact of populist discourse on the construction of social reality is undeniable. This study analyzes the fantasmatic dimension of political discourse from Donald Trump's and Jair Bolsonaro's Twitter accounts between 1 March and 31 May. To do so, it applies a Clause-Based Semantic Text Analysis (CBSTA) methodology that categorizes speech in Subject-Verb-Object (SVO) triplets. The study findings show that in spite of the Coronavirus pandemic, the main beatific and horrific subjects remain the core populist signifiers: the people and the elite. While Bolsonaro's narrative was predominantly beatific, centered on the government, Trump's was mostly horrific, centered on the elite. Trump signified the pandemic as a subject and an enemy to be defeated, whereas Bolsonaro portrayed it as a circumstance. Finally, both leaders defined the people as working people, therefore their concerns about the pandemic were focused on the people's ability to work

The Proceedings of the 23rd Annual International Conference on Digital Government Research (DGO2022) Intelligent Technologies, Governments and Citizens June 15-17, 2022

The 23rd Annual International Conference on Digital Government Research theme is “Intelligent Technologies, Governments and Citizens”. Data and computational algorithms make systems smarter, but should result in smarter government and citizens. Intelligence and smartness affect all kinds of public values - such as fairness, inclusion, equity, transparency, privacy, security, trust, etc., and is not well-understood. These technologies provide immense opportunities and should be used in the light of public values. Society and technology co-evolve and we are looking for new ways to balance between them. Specifically, the conference aims to advance research and practice in this field. The keynotes, presentations, posters and workshops show that the conference theme is very well-chosen and more actual than ever. The challenges posed by new technology have underscored the need to grasp the potential. Digital government brings into focus the realization of public values to improve our society at all levels of government. The conference again shows the importance of the digital government society, which brings together scholars in this field. Dg.o 2022 is fully online and enables to connect to scholars and practitioners around the globe and facilitate global conversations and exchanges via the use of digital technologies. This conference is primarily a live conference for full engagement, keynotes, presentations of research papers, workshops, panels and posters and provides engaging exchange throughout the entire duration of the conference

The continued usage of artificial intelligence in the United Arab Emirates public sector organisations: An extended information system success model

In the past years, government around the globe showed significant interest in Artificial Intelligence (AI) technologies, more governments are setting their AI related strategies and using Artificial Intelligence technologies separately or integrated with other technologies such as Internet of Things (IoT) or Big Data (BD) to enhance their citizens’ offering, or increase the efficiency of their processes. Nevertheless, empirical research on what determines successful Artificial Intelligence (AI) usage and usage continuance in public settings remains scarce, especially regarding the impact of organisational constructs on the intention to continue usage of Artificial Intelligence in Public Sector Organisations in the United Arab Emirates. Therefore, this study was conducted to offer a better understanding of the impact of various organisational and technological factors on Intention to continue using Artificial Intelligence (AI) in organisations in the Public Sector in the United Arab Emirates. This study tests the constructs identified from the updated Delone & McLean Information System Success Model (2013) and Technology-Organisation-Environment (T.O.E.) Framework and their impact on the successful usage and intention to continue usage of Artificial Intelligence in the Public Sector organisations in the United Arab Emirates. This was conducted through reviewing the existing literature in AI technologies and IS acceptance theories, which led to the introduction of a hybrid model from both the Delone & McLean Information Success Model (2013) and the Technology-Organisation-Environment Framework (TOE) with seven proposed constructs. A survey approach has been followed to collect primary data from 223 participants who use AI technologies in their respective federal and local public sector organisations. Structural Equation Modelling (SEM) has been used to test the conceptual model to measure the relationships impact significance of identified variables. The analysis of the data revealed that all seven constructs in the Delone & McLean Information Success Model and TOE framework hybrid model are accepted. The tested model showed moderate to high positive statistically significant correlations with intentions to continue usage of AI technologies. The results of the study revealed that Organisational Performance has a strong and positive significance impact on In Intentions to Continue Usage of AI technologies. In addition to that, analysis revealed that Organisational Culture and Digital Organisational Culture can be added to the model, as the results indicated that Organisational Culture has a strong and positive impact on Digital Organisational Culture. Moreover, the study demonstrates the importance of culture in public sector. When comparing impact significance, the study showed that Actual Usage of AI systems is positively impacted by the two variables; System Quality and Digital Organisational Culture, nevertheless Digital Organisational Culture has greater positive impact than System Quality. Moreover, Organisational Culture and Data Management both have positive impact on System Quality and Digital Organisational Culture, but Organisational Culture has greater positive impact on System Quality and Digital Organisational Culture more than the positive impact of Data Management on System Quality and Digital Organisational Culture. This study makes important theoretical contributions to both Delone & McLean Information Success Model (2013) and the Technology-Organisation-Environment Framework by providing a novel framework and model that integrates key concepts and mechanisms from both theories, which enables a more comprehensive and nuanced understanding of the research of interest. Specifically, the model developed in this study enhances our understanding of the complex interplay between various cognitive, affective, and behavioral factors that influence the outcomes predicted by these theories, and sheds new light on the underlying processes and mechanisms that drive these effects. Moreover, this research has several managerial contributions and implications, provides insights for Public Sector Organisations to understand the factors affecting AI systems usage success, which will help them in prioritizing and utilizing their resources more effectively. A new conceptual model was tested and validated which would help Directors, ICT specialists and programmers, and data scientists in identifying new ways to facilitate AI technologies adoption and usage. In addition, the study highlighted the importance of organisational culture in the usage of AI related technologies. Thus, this research through the introduced model may enhance the ability of public sector organisations in the United Arab Emirates to better manage data, and the quality of the AI systems used, in addition to instilling a corporate culture and digital organisational culture that would enhance the actual usage of AI system which would enhance the organisational performance, and accordingly influence the organisation’s intention decision to continue using AI technologies