Christian Bartelheimer, University of Göttingen

Daniel Beverungen, Paderborn University

Sara Hofmann, University of Agder

Lysanne Lessard, University of Ottawa

Digital transformation continues to reshape how organizations create, deliver, and capture value. At the same time, service has become a crucial lens for understanding contemporary information systems (IS) phenomena. Value is co-created across organizational boundaries, enacted through digital technologies, and embedded in networks, platforms, and ecosystems. The Topical Collection on Digital Transformation & Service at Electronic Markets seeks to advance theoretically grounded and relevant IS research at the intersection of digital transformation and service.

We invite submissions that foreground service and digital transformation as they are established, debated, and further developed within the IS discipline, and in particular in Electronic Markets. Submitted articles should demonstrate a clear engagement with core IS literature to identify a well-defined research gap that matters for practice and theory, and articulate a convincing contribution to recent IS conversations. We are particularly interested in papers that move beyond broad claims about the consequences of digital transformation and instead examine how information technology (IT) artifacts ought to be designed and how they can be applied to foster value co-creation.

A central expectation of this Topical Collection is that submissions 'white-box' the role of IT artifacts. We seek papers that explicate how IT artifacts shape and are shaped by the digital transformation of organizations, for instance by enabling or transforming customer relations, value propositions, and service exchange. Studies may focus on (smart) service systems or ecosystems at varied levels, including communities, organizations, inter-organizational arrangements, platforms, data spaces, and society. In contrast, we do not seek papers that treat information systems as 'black boxes' or limit their analysis to summative business implications without theorizing the underlying structures, mechanisms, and affordances of IT artifacts through which these implications emerge. Manuscripts presenting IT artifacts that use or expand large language models or other large-scale artificial intelligence technologies must also be unpacked and contextualized, and presented in a way that is theoretically anchored and generates contributions at the intersection of digital transformation, service, and information systems.

We invite contributions from various epistemological positions and methodological traditions common in the IS discipline. Suitable submissions may include (action) design science, conceptual papers, qualitative studies, including case studies and Delphi studies, quantitative research, including experiments, surveys, and data-driven studies, and mixed-methods work. Literature reviews are also welcome, provided that they deliver strong theoretical implications and develop a forward-looking research agenda that reaches considerably beyond reporting the current state of research.

We particularly encourage submissions that investigate the role of digital technologies in real-world service scenarios. Studies that focus on inter-organizational contexts such as service networks, digital platforms, data spaces, or business ecosystems are especially relevant, as they touch on core topics of Electronic Markets. Submissions may examine established organizations, start-ups, public-sector organizations, communities, or other actor constellations in which digital technologies enable, constrain, or transform service exchange and value co-creation.

Potential topics

• Digital transformation and service in information systems
• Design and application of IT artifacts to foster value co-creation
• Smart service systems and ecosystems at multiple levels (communities, organizations, inter-organizational arrangements, platforms, data spaces, and society)
• Customer relations, value propositions, and service exchange enabled by digital technologies
• Role of digital technologies in real-world service scenarios
• Inter-organizational contexts such as service networks, digital platforms, data spaces, and business ecosystems
• Digital transformation in established organizations, start-ups, public-sector organizations, and communities
• IT artifacts using or expanding large language models and other large-scale artificial intelligence technologies
• Generative AI and digital responsibility in service contexts

Timeline

• Invalid DateTime: Submission deadline

Timeline

• December 20, 2026: Full paper submission deadline

This special issue is associated with the Pacific Asia Conference on Information Systems (PACIS) 2026 and will be published in Information & Management.

Timeline

• June 1, 2027: Full paper submission deadline

René Riedl, University of Applied Sciences Upper Austria & Johannes Kepler University Linz

Jan vom Brocke, University of Münster

Jella Pfeiffer, Karlsruhe Institute of Technology

Robert Gleasure, Copenhagen Business School

The advent of increasingly powerful artificial intelligence systems (e.g., large language models such as ChatGPT, diffusion models, graph neural networks, or vision transformers) used in domains such as healthcare, manufacturing, software development and finance, together with other contemporary digital technologies (e.g., autonomous cars, immersive worlds, and neuroadaptive interfaces), has fundamentally reshaped human interaction with information systems. As these technologies become embedded in work, consumption, private life, and society in general, the ways in which they affect human cognition, emotion, and social interaction remain poorly understood.

A growing body of research highlights that neurophysiological methods can provide unique insights into these phenomena across a broad range of IS contexts. NeuroIS—the interdisciplinary field that integrates neuroscience and psychophysiological approaches with information systems—has been at the forefront of this movement. Originating at the International Conference on Information Systems in Montréal in 2007, NeuroIS celebrates its 20-year anniversary in 2027. This milestone provides an opportune moment to reflect on the progress achieved, highlight challenges, and chart new directions for NeuroIS research in an era of rapid technological change.

Over the past two decades, NeuroIS research has established the potential of neurophysiological methods such as electroencephalography (EEG), functional magnetic resonance imaging (fMRI), functional near-infrared spectroscopy (fNIRS), eye tracking, and various other neurophysiological measures to enrich IS theory. These approaches have been shown to improve prediction accuracy of different IS phenomena, uncover hidden cognitive and affective mechanisms, and open new methodological horizons. A particularly important trajectory in this research stream has been the integration of neurophysiological and behavioral levels of analysis by linking neural responses to observable IS-related behaviors and self-report measures.

In an era of pervasive digitalization, this integration becomes even more essential. Understanding not only what individuals do when interacting with advanced digital systems, but also how their brains and bodies adapt, allows researchers to explain emergent behaviors such as overreliance, automation bias, algorithm aversion, new forms of collaborative cognition, or cognitive debt. Neurophysiological measures enable the study of phenomena that may remain inaccessible to self-reports or behavioral observation alone, such as unconscious biases, implicit trust, or neural markers of attention and memory.

Beyond neurophysiology, this special issue also welcomes work that integrates genetic perspectives into IS research. Prior publications have demonstrated the promise of genetics for explaining individual differences in IS-related behaviors. Combining genetic and neurophysiological approaches may provide a powerful multi-level framework to understand how contemporary digital technologies affect humans at both biological and behavioral levels.

This special issue seeks high-quality, theory-driven, and methodologically rigorous research that examines the neurophysiological and related biological foundations, mechanisms, and effects of contemporary IS technologies and sociotechnical systems—incorporating AI as an important case, but not limiting the scope to AI. We invite submissions from information systems scholars, neuroscientists, psychologists, computer scientists, geneticists, and other disciplines to advance understanding of how contemporary IS reshapes human cognition, affect, decision-making, and social interaction.

This special issue encourages contributions across the full range of IS research traditions. Neurophysiological and genetic insights may advance design-oriented research by informing new principles for human-centered and neuroadaptive system design. They may also enrich IS economics research by offering a biological basis for understanding productivity, well-being, or value creation in digitally mediated contexts. Studies grounded in organizational behavior, strategy, or societal perspectives are highly relevant if they integrate or reflect on neurophysiological evidence.

In line with EJIS' tradition of intellectual openness, this special issue explicitly welcomes visionary, provocative, and contrarian contributions that challenge taken-for-granted assumptions, problematize dominant narratives, or open up unconventional research directions.

Potential topics

• How does sustained interaction with AI-enabled systems (e.g., LLMs) and other advanced digital tools reshape neural networks associated with language, reasoning, and memory?
• Does reliance on AI systems and other forms of automation/digital decision support alter attentional control, working memory, metacognition, or problem-solving processes at the neurophysiological and behavioral levels?
• What are the implications of digitally augmented cognition for neuroplasticity, skill acquisition, and expertise development over time?
• How can integrated neurophysiological and behavioral measures provide a fuller picture of technology-mediated cognitive processes?
• How do individuals' brains respond to empathetic or anthropomorphic cues exhibited by conversational AI and other interactive systems?
• What neurophysiological correlates underlie trust, reliance, distrust, or skepticism toward AI systems and other algorithmic or platform-based systems?
• How does emotional regulation change when decision-making is mediated by AI support, algorithmic decision aids, or digital nudges?
• What are the neurophysiological mechanisms of stress, fatigue, or overload in contexts of AI-assisted work and other digitally intensified work settings?
• How does technological mediation in team collaboration influence the neurophysiological foundations of social coordination, empathy, and shared attention?
• What neural mechanisms underlie shifts in authority, leadership, and influence when AI becomes a co-decision-maker?
• How do cultural differences modulate neurophysiological responses to AI and other digitally mediated collaboration settings?
• How do gender, age, or personality differences modulate neurophysiological responses to IS artifacts?
• How might AI-driven systems and other algorithmic designs reinforce or mitigate cognitive biases?
• What neural signatures accompany ethical dilemmas and moral decision-making in AI-mediated contexts?
• How does long-term use of AI and other digitally intensive work systems shape neurophysiological well-being, stress, or mental health?
• How can neurophysiological insights inform the design of AI systems and other digital systems?
• What are the neurophysiological underpinnings of productivity, efficiency, or value creation in digitally mediated economic interactions?
• How can genetic and neurophysiological approaches together explain individual differences in the adoption and use of digital systems?
• Which neurophysiological tools are best suited for investigating contemporary IS phenomena?
• How can hybrid approaches combining neurophysiology with computational methods enrich IS theory development?
• How can multi-level research designs integrate genetic, neurophysiological, behavioral, self-report, and organizational data?

Timeline

• March 31, 2026: Two-page abstracts due
• April 30, 2026: Feedback on abstracts
• May 31, 2026: Paper development workshop (in person event in Vienna, Austria, and virtual)
• August 31, 2026: First-round paper submission
• November 30, 2026: First-round decisions
• February 28, 2027: First-round revisions due
• May 31, 2027: Second-round decisions
• August 31, 2027: Second-round revisions due
• October 31, 2027: Final decisions

Associate editors

• Bonnie B. Anderson, Brigham Young University
• Dinko Bačić, Loyola University Chicago
• Colin Conrad, Dalhousie University
• Verena Dorner, Vienna University of Economics and Business
• Nadine R. Gier-Reinartz, Heinrich-Heine-University Düsseldorf
• Milena Head, McMaster University
• Alan R. Hevner, University of South Florida
• Qiqi Jiang, Copenhagen Business School
• Marion Korosec-Serfaty, University of Québec in Montréal
• Alexander Maedche, Karlsruhe Institute of Technology
• Gernot R. Mueller-Putz, Graz University of Technology
• Pierre-Majorique Léger, HEC Montréal
• Mario Nadj, University of Duisburg-Essen
• Fiona Nah, Singapore Management University
• Adriane Randolph, Kennesaw State University
• Ofir Turel, University of Melbourne
• Eric A. Walden, Texas Tech University
• Peter Walla, Sigmund Freud Private University Vienna
• Dezhi Wu, University of South Carolina

Kieran Conboy, University of Galway

Sirkka L. Jarvenpaa, The University of Texas at Austin

Brian T. Pentland, Michigan State University

Efpraxia D. Zamani, Durham University

Technology has fundamentally transformed the way we experience time and temporality, having permeated all aspects of our lives. It influences the way we work, how we live, and aspects of our identity, by shifting the way we communicate with others, accelerating information flows and enabling constant connectivity. As technologies evolve and digital infrastructures increasingly shape organisational and societal life, questions of temporality—speed, duration, sequencing, rhythm, and timing—become central to how we design, adopt, use, and study Information Systems (IS).

While time is an inherently complex, multifaceted, subtle concept and is by nature socially embedded, it is often examined simplistically, adopting a clock-time perspective, with the focus being on speed and duration. Some disciplines such as Organisation Studies are making significant progress in understanding and theorising various aspects of temporal complexity and structuring. Yet, within the IS discipline, IS researchers are often quick to highlight the impact of information systems on the speed of organisational and social life, but can be slow to address the polymorphous, complex and nuanced nature of time in IS research. Despite a few notable exceptions, studies with a temporal dimension tend to address temporal complexity partially rather than comprehensively. Time remains theoretically elusive in contemporary studies of information systems, often excluded or included only as a 'hidden dimension'. IS literature on time and temporality emerges as fragmented and lacks the cumulative tradition and theoretical glue necessary. As the field matures, treating time as a central concept and construct is essential to theory development and progress.

This is particularly problematic in IS, given the centrality of time to many aspects of study in the field. Time, and more specifically speed, is often the raison d'etre of emerging technology, with promises of enabling real-time decision-making and implementation of action at unprecedented speed and scale. Data typically has a time value, where a data report five minutes before a meeting may be incredibly valuable, but one second after the meeting the value drops to zero. However, data can also increase in value over time as it is combined or new uses are found. Technology is usually developed under time pressure, with a rarely questioned assumption that organisations' use of technology must help them survive and thrive in the seemingly never-ending environment of dynamism and acceleration. IS researchers often use speed as a methodological proxy and even a synonym for IS value and success. However, technological speed and acceleration can undermine learning and collective creativity, and limit participation by those who are irreversibly impacted.

Temporality in information systems manifests across multiple temporal scales, ranging from moment-to-moment interactions to decades-long institutional transformations. The special issue encourages submissions that illuminate how digital technologies shape, mediate, or are embedded within temporal structures, rhythms, paths, and trajectories at any of these scales.

Across all temporal scales, the special issue especially welcomes work that advances theoretical and methodological discussions of time in Information Systems research. This includes analyses of flows, sequences, rhythms, tempos, trajectories, paths, and path nets, with more explicit attention to how temporal constructs are represented, theorised, and operationalised in IS scholarship.

The special issue also encourages contributions that link IS, temporality, and grand challenges such as climate change, pandemics, inequality, and social movements, which require multi-generational coordination, long-term data stewardship, and sustained digital infrastructures. Additionally, the special issue seeks cross-level insights into how temporal assumptions are embedded in IS and how they reshape experiences and outcomes.

The majority of empirical IS studies use time from a methodological perspective to merely strengthen causal claims. The special issue contends that the IS field is uniquely positioned to not just apply temporal techniques gleaned from other disciplines, but to inform and lead how the study of time and temporal complexity can be conducted. IS researchers can now analyse vast amounts of trace data on an unprecedented scale and engage in computationally intensive theory construction, with many emerging techniques that could be used or adapted for studying the complexities and nuances of time and technology.

The special issue envisions providing a deeper understanding of time to clarify and enhance knowledge that can explain phenomena important to IS. While contributions from other disciplines are welcome, papers where the IS artefact is foregrounded, being the central focus of the paper, are prioritised. The special issue welcomes empirical and conceptual contributions, all methodological approaches and paradigms, and studies at different levels of analysis. The journal values contrarian papers that challenge conventional assumptions, theories, and methods.

Potential topics

• How digital interfaces, notifications, and data streams reconfigure everyday temporal experience, including attention, interruption, multitasking, and asynchronous collaboration
• How people make sense of their digital pasts through data archives or online traces, and how they anticipate algorithmic or digitally mediated futures
• How workflow systems, dashboards, collaboration platforms, enterprise analytics, or predictive tools recalibrate shared temporal expectations and influence coordination
• How temporal orientations embedded in tools or analytics shape decision processes, innovation, or strategic flexibility
• Digital artefacts' temporal properties—update cycles, data retention logics, algorithmic refresh rates, and security time horizons—and how they interact with user and organizational temporal practices
• How data governance, privacy regimes, or AI systems handle conflicting temporal demands
• Temporal sensemaking challenges in artefact-centred networks, decentralised autonomous organisations (DAOs), or other digitally constituted arrangements
• Why certain digital transformations accelerate rapidly while others evolve slowly and unevenly
• How digital standards, platforms, and protocols sediment, diffuse, or become institutionalised over time
• How temporal imaginaries, time horizons, or long-term digital trajectories shape fields, industries, and societies
• Theoretical and methodological discussions of time in IS research, including analyses of flows, sequences, rhythms, tempos, trajectories, paths, and path nets
• Explicit attention to how temporal constructs are represented, theorised, and operationalised in IS scholarship
• Linking IS, temporality, and grand challenges such as climate change, pandemics, inequality, and social movements
• Cross-level insights into how temporal assumptions are embedded in IS and how they reshape experiences and outcomes
• Algorithmic schedules, design and development methods such as design science, agile, continuous development and flow, and real-time vs. asynchronous communication
• How temporal assumptions align or collide with individual or cultural constructions of time
• Methodological papers and techniques for studying time and temporal complexity in IS research

Timeline

• November 1, 2026: Initial paper submission deadline
• February 1, 2027: First round authors notification
• April 15, 2027: Invited revisions deadline
• July 15, 2027: Second round authors notification
• September 30, 2027: Final revision deadline

Associate editors

• Jeremy Aroles, University of York
• Reza M. Baygi, Vrije Universiteit Amsterdam
• Catriona Burke, University of Limerick
• Omar El Sawy, University of Southern California
• Anne-Laure Fayard, NOVA School of Business and Economics
• Thomas Grisold, Vienna University of Economics and Business
• Amir Haj-Bolouri, University West
• Susan Hilbolling, Aarhus University
• Robin Holt, University of Bristol
• Astri Moksnes Barbala, SINTEF
• Rohit Nishant, Queen's University
• Mahya Ostovar, University of Galway
• Omid Omidvar, Warwick Business School
• Henri Pirkkalainen, Tampere University
• Frantz Rowe, University of Nantes
• Markus Salo, University of Jyväskylä
• Yingqin Zheng, University of Essex
• Aljona Zorina, NEOMA

As digital technologies increasingly transform industrial operations, integrating industrial management with information systems (IS/IT) research has become essential. Key domains such as supply chain resilience, digital innovation, and data-driven decision-making require methodological approaches that can address both technical complexity and organizational dynamics.

However, many existing studies still rely predominantly on either primary or secondary data, with relatively few exploring the benefits of strategically combining the two. Integrating primary data (e.g., surveys, interviews, experiments) with secondary data (e.g., ERP logs, platform analytics, archival datasets) enables deeper theory development by revealing both behavioral patterns and underlying mechanisms.

Mixed-methods purposefully integrate qualitative and quantitative data to provide both explanatory breadth and contextual depth—enabling researchers to explore "how" and "why" phenomena unfold. Multi-methods, which combine multiple techniques within the same paradigm, can improve robustness, triangulation, and construct validity. Both approaches are particularly valuable for studying evolving topics such as AI deployment, digital trust, platform governance, and organizational resilience.

Despite their promise, challenges persist: integration logic is often implicit, philosophical tensions may arise, and quality assessment frameworks are still emerging. Key areas remain underexplored, including how to align methodological choices with research aims, how to evaluate integration rigorously, and how to distinguish among mixed, multi, and hybrid methods in IS research.

This special issue aims to address these gaps by encouraging submissions that embrace methodological pluralism, combining primary and secondary data to produce practically relevant, empirically grounded, and theoretically robust contributions. By crossing methodological borders, we hope to foster innovative approaches that better reflect the complex realities of digital transformation in industrial systems.

Potential topics

• Mixed-/Multi-Method Designs in Digital Transformation and Process Innovation - Exploring methodological integration, trade-offs, and complementarities in examining technology-enabled changes in workflows, decision-making, and organizational processes.
• Integrated Analytical Approaches to Supply Chain Innovation and Resilience - Applying mixed-/multi-method strategies to investigate logistics transformation, disruption management, and sustainable operations in volatile environments.
• Human-AI Collaboration and Decision-Making Coevolution - Combining qualitative and quantitative methods to understand trust, cognition, and co-production dynamics in evolving human-AI systems.
• Social Media, Digital Marketing, and E-Commerce Ecosystem - Utilizing mixed-/multi-method approaches to study online engagement, influencer strategies, consumer behavior, and brand reputation in digital platforms.
• Sustainability and Green IS through Methodological Pluralism - Investigating environmental performance, circular economy practices, and sustainable innovation through integrated technical, organizational, and social lenses.
• Contextualized Adoption of Generative AI Technologies - Examining sector-specific adoption patterns, drivers, challenges, and impacts of GAI using comprehensive, multi-perspective research designs.
• Ethical, Educational, and Security Dimensions of AI - Addressing privacy, trust, risk, and AI literacy through mixed-/multi-method inquiries into responsible and secure use of AI in organizational and societal contexts.

Timeline

• April 2, 2026: Opening date for manuscript submissions
• September 30, 2026: Closing date for manuscript submissions

Thomas Hess, University of Munich (LMU)

Ioanna Constantiou, Copenhagen Business School

Niki Panteli, Lancaster University

Generative AI (GenAI) has rapidly become a general-purpose technology that reshapes how information is created, curated, and consumed. GenAI broadly refers to a class of AI models that generate seemingly new content in the form of text, images, audio, or video. In the media context, where value is built around the provision and use of content, GenAI has attracted particular attention. For instance, it enables the near-instant creation of journalistic articles, marketing texts, or audiovisual material, and it supports personalization by dynamically adapting media offerings to individual user preferences. The advent of the Internet had already marked a profound transformation in the delivery and consumption of content. It made user-generated content possible, catalyzed multi-sided platforms, and enabled unprecedented personalization. This transformation brought new players into the media sector, as technology companies entered the market and traditional media firms were forced to develop significant digital competencies for the first time.

GenAI is expected to have an equally profound impact on the media industry by expanding complementary innovation, lowering barriers for content creation, and altering the economics of matching and recommendation at scale. Despite recent advances, our knowledge is still limited. Existing research has begun to shed light on the impact of GenAI on textual news app users’ willingness to pay, yet it is unknown whether similar effects extend to audiovisual content. Moreover, there are initial indications of how journalists’ productivity may change with the use of GenAI. At the same time, the potential for entirely new GenAI-based products remains largely unexplored. In particular, little is known about the extent to which audience discussions can be moderated and managed, or about the new forms of public media provision that GenAI might enable. These questions are especially pressing given the central role of media in shaping public opinion and broader societal developments, including political attitudes.

The aim of this special issue is to advance IS research on this emerging field. We invite contributions that examine the role of GenAI in the provision and use of media offerings. Analyses may focus on individuals, organizations, or industries. Studies may address GenAI on the level of systems, their effects, or their management. Submissions should be firmly grounded in the technology itself and its implications for media ecosystems. This special issue aims to stimulate innovative investigations of the transformative role of GenAI in the provisioning and use of public media. In contrast to closed settings, such as private messaging services, the recipients of public communication cannot be predetermined or exhaustively specified in advance. Accordingly, the domain of interest spans both online media, including digital platforms and social media, and traditional media such as print and television. We welcome qualitative and quantitative empirical studies as well as design-oriented research. Submissions should provide a clear academic contribution by advancing theory and knowledge in the Information Systems discipline. While practical relevance and managerial implications are highly valued, they are not sufficient on their own; academic advancement is essential.

Potential topics

• Provision of Content for the Media
• Use of Content provided by the Media
• Embedding of the Media in Society

Timeline

• December 1, 2025: Full paper submission opens
• April 30, 2026: Full paper submission closes
• June 30, 2026: Desk check
• September 30, 2026: Feedback on the first version
• January 31, 2027: Submission revision 1
• April 30, 2027: Feedback on revision 1
• June 30, 2027: Submission revision 2
• July 31, 2027: Final decision