Conference Agenda

Artificial Intelligence (AI) is emerging as one of the most significant technological innovations, with the potential to profoundly shape the design and delivery of various public services and facilitate the development of innovative service models (Mergel et al., 2024). Despite its relevance, relatively little attention has been given to public service management issues. Only recently has the use of AI in public service design and delivery become an increasingly prominent subject of scholarly debate (Madan & Ashok, 2023).

Within this context, four distinct roles of AI in the interaction between users and service providers have been identified (Osborne & Nasi, 2024). AI technologies can act as an interface, providing users with information, streamlining access, and guiding them to the appropriate services. AI can function as data processor, collecting and analyzing big data to inform better service delivery, and as a service enabler automating tasks, personalizing services, and enhancing accessibility. Furthermore, AI can serve as an active partner in the process of co-designing, co-producing and co-delivering public services.

While academic literature on AI's role as a partner in the public sector is still emerging, the topic has been more explored in the private sector (Behera et al., 2024), highlighting its potential as a promising area for future research. Exploring what role AI can have in public service delivery, how it is being used and whether it generates value contributes to advancing the literature on public administration and public service logic and may offers insights for public managers.

For this reason, we carried out a systematical literature review to synthesize existing literature across both sectors to identify the current state of conceptual and empirical studies, as well as outline a future research agenda.

To fill this gap, this study addresses the following research question:

RQ: What is the current state of research on human-AI collaboration in service delivery?

Through a systematic literature review conducted in accordance with the PRISMA framework (Liberati et al., 2009), this study examines 50 articles and 5 book chapters on the use of AI as a collaborative tool, exploring how AI tools contribute to the creation and delivery of services, and how it supports both employees and citizens. The reviewed literature is systematically charted and clustered according to several critical dimensions, including: (i) antecedents of collaboration (ii) outcomes of collaboration (iii) the role of AI in such contexts.

Based on these findings, the study maps the current state of research on this topic, identifying future research directions on AI as a tool for enhancing collaboration, and providing practical recommendations for public organizations seeking to establish more effective partnerships with AI.

There is a demonstrated positive relationship between the quality of public institutions and governance and socioeconomic development. Parallel to this, as a component of technological progress, information and communication technologies (ICT) have triggered changes across industries and contributed to socioeconomic development. Recent advancements in artificial intelligence (AI) add a new dimension to this relationship. The interplay between PG and AI in driving socioeconomic outcomes remains underexplored. To address this gap, we employ a two-stage network Data Envelopment Analysis (DEA), complemented by ordinary least squares (OLS) regression and multivariate analysis of variance (MANOVA), using data from 52 high- and middle-income countries. The first DEA stage evaluates the efficiency of countries in transforming AI inputs (AI funding and talent) into intermediate outputs (AI research papers and patents). The second stage assesses how effectively these intermediate outputs translate into economic outcomes (ICT-service exports, high-tech exports, GDP per person employed). The subsequent OLS and MANOVA analyses further investigate the influence of governance quality, measured via World Governance Indicators, on both AI efficiencies derived from DEA and raw AI capabilities. This study contributes to interdisciplinary discussions on how the public governance interacts with AI technologies to foster socioeconomic welfare.

Successful e-government initiatives depend on the alignment of the objectives of public services with its stakeholders. While stakeholder engagement is widely acknowledged as essential, debates persist around the definition and categorisation of stakeholders within e-government contexts. This paper critically examines how stakeholder categorisations can support e-government public service design and delivery, and discusses engagement methods to align stakeholders with with e-government.

The study is grounded in stakeholder theory, particularly the foundational work of Freeman and Reed (1983) and its adaptation to e-government by Scholl (2001, 2004), who highlights the benefits and limitations of applying stakeholder theory in digital governance contexts. The latter work in particular underscores the importance of moving beyond technocratic views and advocates comprehensive inclusion of salient stakeholders to foster more effective and inclusive public services. Flak and Rose have also noted the benefits of using stakeholder theory in governance; in particular how e-government could provide a “sensitizing filter” (2005, S. 659) for understanding stakeholders as well as provide tools and techniques to support them. Therefore, in this study, we include both Flak and Rose’s (2005) as well as Rowley’s (2011) arguments regarding stakeholder alignment in e-government contexts, emphasizing the critical need to reconcile public service objectives with diverse stakeholders. Building on Bryson’s (2004) systematic stakeholder analysis methods, this paper applies structured approaches for identifying and prioritizing stakeholders in complex e-government scenarios and then combines the results with insights about engagement methods relevant in e-government services.

The empirical basis of this research includes a systematic review of 24 peer-reviewed academic articles, which were selected according to the PRISMA protocol (Page et al., 2021). The literature reviewed specifically addresses stakeholder categorisation and examines methods for stakeholder engagement tailored to e-government public services. The study addresses two primary research questions: (1) How do stakeholder categorisations support e-government public service design and delivery? And (2) Which engagement methods align stakeholders with e-government service provision?

The results show how different stakeholder categorisations and engagement methods can improve public service provision in e-government. By identifying and categorizing stakeholders involved in e-government, and critically evaluating engagement methods, the paper offers theoretical contributions and practical recommendations aimed at enhancing stakeholder interactions, communication, and participatory mechanisms in e-government. Effectively identifying and engaging stakeholders contributes to public services that are user-centered and draw on co-creation principles. The findings highlight that a nuanced and context-sensitive understanding of stakeholders significantly enhances engagement, contributes positively towards public service provision and the long-term sustainability of e-government.