1 Introduction

Information systems engineering (ISE), the interdisciplinary field between software engineering (SE) and information systems (IS), is undergoing rapid and considerable changes. This special issue addresses the urgent call for initiatives to facilitate interaction between the fields IS and SE (Fitzgerald 2024), offering a fresh perspective on building, implementing, and managing IS in the face of recent, substantial contextual developments.

Several forces have profoundly reshaped the ISE landscape over the past two decades. The increasing prominence of digital business strategies (Bharadwaj et al. 2013), relying on digital innovation across almost every industry (Vial 2021), has redefined the role of information technology (IT). This ubiquity of IT leads to an ontological reversal, where technology is no longer merely a tool but a defining force which shapes organizational processes and structures (Baskerville et al. 2020), thereby unleashing the potential of generativity in designing digital products (Lehmann et al. 2022). Alongside this shift, the nature of collaboration between IT and business professionals has undergone profound changes (Urbach et al. 2019). Finally, the rise of data-driven technologies such as machine learning (ML) and artificial intelligence (AI) (Janiesch et al. 2021) has considerably transformed ISE capabilities.

These forces have driven a re-evaluation of traditional SE and IS paradigms. There is an enhanced focus on “product over project” perspectives and the need for new success measures (Wiedemann et al. 2020). The democratization of software development facilitated through low-code/no-code (LC/NC) platforms (Bock and Frank 2021; Karl et al. 2020), the emergence of integrated agile and DevOps teams (Maruping and Matook 2020), and the advent of generative AI tools and platforms such as CoPilot, Gemini, or Claude (Feuerriegel et al. 2024) all present both new challenges and opportunities for ISE practitioners and researchers alike. Ensuring scalability, managing technical debt, and retaining skilled personnel in an era of increasingly autonomous and hybrid work environments are paramount (Conboy et al. 2023).

This special issue brings together research exploring this dynamic frontier, which offers valuable insights for both researchers and practitioners who are navigating the evolving landscape of ISE and looking for a fresh perspective on building, implementing, and managing IS.

2 A Framework and Research Agenda for Information Systems Engineering

We propose a framework structured around seven critical themes, informed by the trends and challenges highlighted above, to systematically categorize the contributions within this special issue and guide future inquiries. Current themes in ISE research comprise: (1) factors impacting individual IS engineers, particularly job satisfaction and stress; (2) factors impacting team collaboration and teamwork; (3) the effects of NC/LC ecosystems on ISE; (4) the impact of emerging technologies on ISE; (5) the effects of artificial intelligence on ISE (e.g., impacts on productivity, accountability, or dealing with missing transparency); (6) ISE education and training; and (7) ethics of and ethical considerations in ISE (see Table 1). These seven themes each represent a complex area of importance for ISE, where several key topics and research questions should be investigated.

Table 1 Emerging research themes in information systems engineering
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3 Overview of the Special Issue Contents

The papers in this special issue each address one or more of these themes. For example, LC/NC platforms are changing the software development landscape by enabling citizen developers, individuals without formal programming backgrounds, to create applications. Sabine Matook, Yazhu Wang, and Micheal Axelsen’s study “Experiential Learning for Citizen Developers: Training IT Talent in Low-code Development and Metacognitive Reflections” addresses themes 3 and 6 by examining the emerging role of citizen developers, highlighting the skills and competencies needed for citizen developer success. Using a quantitative approach, the study examined how practice-based learning that uses low-code development platforms impacts the metacognitive reflection of students who act as citizen developers. Through a quantitative survey, it found that experiential learning factors like authenticity, active learning, self-relevance, and utility had a positive impact on metacognitive reflection, while team-based learning had mixed effects. The results suggest that practice-based learning with LC platforms can effectively train developers in the citizen developer model and equip them with important self-learning skills. The research theoretically contributes to understanding evolving IT roles and socio-technical approaches in ISE. As LC/NC platforms continue to grow, this research offers valuable insights for navigating this new phenomenon.

The surge in citizen development has prompted further investigation into the specific characteristics, skills, and organizational implications of this new breed of developer. Edona Elshan, Björn Binzer, and Till Winkler explore the rise of citizen developers as a response to the growing IT skills shortage in their study “From Software Users to Software Creators: An Exploration of the Core Characteristics of the Citizen Developer Role and the Related Re- and Upskilling Programs” (themes 1, 3, and 6). Through combining a literature review with an analysis of job postings and an interview study, the study provides a detailed characterization of the citizen developer role, emphasizing its supplementary nature and the need for versatile skill sets. The research identifies critical technical, business, and soft skills required for citizen developers, highlighting discrepancies between theoretical expectations and real-world demands. It also proposes a comprehensive framework for integrating citizen developers into organizational IT strategies, focusing on aligning re- and upskilling initiatives with organizational goals. This framework offers a strategic roadmap for organizations to leverage citizen developers, mitigate the developer shortage, and enhance organizational agility in software development.

Agile methodologies are increasingly the de facto dominant paradigm in software development, promising increased job satisfaction for developers. However, the research on this claim has produced mixed results, prompting a closer examination. Investigating themes 1 and 2, Veronika Huck-Fries, Rosa Spitzer, Jason Thatcher, and Helmut Krcmar review the literature on job satisfaction within agile software development, analyzing its antecedents, moderators, and consequences. Their study “(No) Need to Apply Agile? A Review of the Literature and Agenda for Future Research on Job Satisfaction in Agile Information Systems Development” finds that while agile practices are generally associated with higher satisfaction, the relationship is complex and influenced by various factors. Crucially, the review identifies gaps in understanding how specific agile practices, roles, and leadership styles impact job satisfaction. The authors develop a conceptual model and call for more research on the consequences of job satisfaction in terms of motivation, retention, and performance. They propose a detailed research agenda, advocating for multi-level approaches that consider individual, team, and organizational dynamics. This agenda encourages longitudinal studies and mixed-methods research to overcome the limitations of existing studies.

Continuing the exploration of agile, “How an Agile Software Process Increases Developers’ Job Satisfaction: A Stress Perspective based on the Effort-Reward-Imbalance Model” examines the impact of agile software development practices on job stress and developer job satisfaction through the lens of the effort-reward imbalance framework. René Riedl, Christian Oettl, Fabian Stangl, and Alan R. Hevner argue that agile practices can reduce stress by fostering a better balance between the effort developers invest and the rewards they receive. This directly taps into themes 1 and 2. They propose and empirically test a moderated mediation model with data from 178 software developers in Austria. The findings confirm that agility indirectly increases job satisfaction by reducing perceived stress, particularly through increased reward perceptions. The findings also reveal that different agile practices have varying effects on stress, with some increasing and others reducing stress. Morevoer, developers with a high level of overcommitment, a personality trait reflecting excessive work dedication, experience a weaker positive effect from agility due to increased stress levels. This offers a novel theoretical perspective on the relationship between agility and job satisfaction, highlighting the crucial role of reward perceptions and individual personality traits. The findings have practical implications for organizations that seek to improve developer well-being and optimize agile implementation strategies by fostering a balanced and rewarding work environment.

Finally, diving into ISE for AI (theme 5), the study “Elevating Developers’ Accountability Awareness in AI Systems Development: The Role of Process and Outcome Accountability Arguments” by Jan-Hendrik Schmidt, Sebastian Clemens Bartsch, Martin Adam, and Alexander Benlian examines how different types of accountability arguments affect AI developers’ perceptions of responsibility in AI systems development. The authors used a randomized online experiment to test the effectiveness of process and outcome accountability arguments, visualized as user interface elements in integrated development environments (IDEs). The results show that process accountability arguments, focusing on immediate development decisions, have a more robust initial impact on perceived accountability than outcome-focused arguments. However, when supported by evidence, both argument types prove similarly effective. Follow-up qualitative interviews with AI developers revealed a nuanced understanding of accountability, with a substantial distinction emerging between process and outcome accountability. AI developers generally feel more accountable for development processes than for potentially unpredictable outcomes, a perception shaped by their perceived influence over different development stages. This research makes three key contributions to IS research. It distinguishes process and outcome accountability as separate theoretical constructs. It advances our understanding of communicating accountability in different AI development phases. Finally, it demonstrates how established ISE tools like IDEs can be adapted to meet emerging governance challenges in AI systems development.

4 Conclusion

Our special issue seeks to ignite discussion and further explore how our framework’s themes interact and inform ISE’s evolution. Each paper in this issue reflects on these themes and pushes the boundaries of current understanding, offering empirical insights and theoretical advancements that represent progress in ISE. By addressing the emerging challenges and opportunities highlighted, researchers and practitioners can contribute to a deeper understanding of ISE and help improve effective implementations of next-generation IS.