Varun Grover, University of Arkansas

Nik Rushdi Hassan, University of Minnesota Duluth

Tina Blegind Jensen, Copenhagen Business School

Paul Lowry, Virginia Tech

Kalle Lyytinen, Case Western Reserve University

Angsana Techatassanasoontorn, Auckland University of Technology

The pervasive and unprecedented digitization of organizational and human experience represents a major challenge to past and existing theorizing methods. As Zuboff (2019) argues, we suffer from the unrecognizability of the unprecedented, which continues to elude society’s oversight. Zuboff calls for a new naming and a new set of concepts so we can effectively tame them. While new concepts are essential, they are not enough on their own. Recent efforts, such as the MIS Quarterly special issue on “Next-Generation Information Systems Theorizing” (Burton-Jones et al., 2021), emphasize that with the rise in complexity in this digitized world, we need to “rethink our theories and create new theories to guide us” and that “theorizing is even more critical than ever” (p. 301, original emphasis). We need theories to help us “make sense of this complex world and to act wisely” (p. 302). What is needed are new theories that connect the new concepts that can grasp the unprecedented and link them to existing concepts or other new concepts, that explain and answer why such phenomena are happening (Grover & Lyytinen, 2015, 2023; Hassan et al., 2022; Hassan et al., 2023; Rivard, 2021). It is useful to know that fake news travels six times faster and 20 times deeper than truth (answering the “how?” question) (Vosoughi et al., 2018) but it is more useful to know “why” it is happening, so we can address such problems and establish our field as a socially and intellectually influential discipline.

This call requires not just theorizing but also building native IS theories that explain the nexus between digital technology and social and organizational phenomena. Building theories is highly challenging, as the editors of another special issue by the Journal of the Association for Information Systems on “Envisioning Digital Transformation–Advancing Theoretical Diversity” (Rowe & Markus, 2023) found. In their call for papers (Markus & Rowe, 2020), the editors alluded to the problematic situation with theory in IS—"Everything about theory is contested in our field today … Is a good theory a boxes-and-arrows diagram followed by the more-X-the-more-Y type propositions?” Theory should not be restricted to causal mechanisms or viewed too inclusively, like any loose framework or set of propositions. Theory takes any form of scientific understanding and systematic explanation that contains logically interconnected sets of propositions, symbolic conjectures, and empirical generalizations, tied to the IS discourse from which knowledge, practice, and empirical uniformities can be derived.

This definition extends Bacharach’s (1989) oft-repeated definition for theory as “a statement of relations among concepts within a set of boundary assumptions” (p. 496), which may seem to be too inclusive and will admit any model or box-arrow diagram or “a system of constructs and variables in which the constructs are related to each other by propositions and the variables are related to each other by hypotheses” (p. 498) which others consider to only admit a positivist epistemology. Authors can build models, sets of propositions, or hypotheses, but they need to be logically connected parts of a whole—a theory that answers the “why?” question and can describe, explain and predict. In the interpretive vein, even if the goal of theory in qualitative or interpretive studies is not necessarily to predict but to interpret and understand adequately, theories from these studies also contain logically interconnected sets of propositions, symbolic conjectures, and empirical generalizations.

To fulfill the criterion that the theory be tied to the IS discourse, the SI seeks studies that focus on the uniqueness of phenomena, assumptions, boundary conditions, concepts, and logic to IS. To do this, every theory proposed should be tied to an explicit “why” question about an IS phenomenon. This could be an anomaly in the phenomenon that needs to be explained or a mismatch between an established theory and the phenomenon. For example, an article on digital strategy should explain that, because digital phenomena have properties x, y, and z, established theories of resources and industrial organization, as reflected in RBV or position frameworks, cannot explain why a specific digital strategy works or fails. Hence, the focus should be on premises, inferences, and outcomes that characterize native and original theories in the IS field, where theorizing about digital technology and its nexus with social/organizational phenomena takes center stage. Articles submitted to the SI may apply one of two major approaches, either (1) deeply engage with existing theory that may or may not explain unprecedented IS phenomena, and demonstrate how these existing theories address or don’t address such phenomena, or (2) propose novel native IS theories that are different from established theories, why we need these new theoretical positions, and how they significantly enhance the IS field’s ability to describe, explain and predict such unprecedented phenomena.

It is inconceivable that a field researching IT-enabled fake news, the technology-infused hyperconnected society, disruptive technologies, surveillance capitalism, Big Data, destructive social media, generative artificial intelligence, and their impacts is not brimming with its own explanations for these unprecedented phenomena. This special issue seeks articles that either deeply engage with existing theories or propose new native IS theories on these unprecedented emergent IS phenomena. We do not want to limit this special issue to specific topics since this is an open call for native theorizing. At the same time, we would like our researchers to not recycle old topics, and instead investigate emerging phenomena that are capturing the attention of society and in need of better explanations such as digital technologies that are shaping public opinion, algorithmic amplification of social tendencies, threats to cybersecurity and privacy from technology-enabled organizations, addressing deepfakes and synthetic newsrooms, ethical and legal implications from such technologies, disruption from artificial intelligence (AI) generative content and increasing societal and political violence and upheaval from misinformation and disinformation. There are also opportunities to leverage the same technologies in areas such as energy informatics, green IS, and sustainability digital initiatives, which can benefit from native IS theories. Whatever the domain or topic, it is the authors' responsibility to demonstrate where existing or novel theories are needed.

Potential topics

• Open call for native IS theorizing on emerging IS phenomena
• Digital technologies shaping public opinion
• Algorithmic amplification of social tendencies
• Threats to cybersecurity and privacy from technology-enabled organizations
• Deepfakes and synthetic newsrooms
• Ethical and legal implications of such technologies
• Disruption from artificial intelligence (AI) generative content
• Increasing societal and political violence and upheaval from misinformation and disinformation
• Energy informatics, green IS, and sustainability digital initiatives

Timeline

• June 29, 2026: Deadline for Extended Abstracts [Abstract submission via email]
• December 1, 2027: Deadline for Paper submissions
• Official launch of the Special Issue by EJIS
• Workshops and Tutorials at ECIS and AMCIS
• Workshop at SIGPHIL@ICIS 2026 to refine research
• Workshops at ECIS and AMCIS
• Expedited editorial process
• Submit approved articles to journal
• Targeted publication date