All disciplinary fields operate under specific beliefs and assumptions and commit to specific ontologies, values, goals, and topics. These define what is ‘in’ and what is ‘out’, what method is acceptable and what is not; what assumptions guide research, and what is an appropriate code of conduct. Healthy and open academic communities occasionally reflect on such issues by engaging in arguments and debates to settle such issues when new theories, phenomena or puzzles emerge in the field. Sometimes such arguments are triggered by provocateurs who poke sacred cows and ask the contrarian questions. The information systems field is, in this regard, no different. Though the field has occasionally engaged in debates about its core, identity, preferred research method or nature of technology or value of causal explanations such debates are rarely part of our community meetings (a legendary meeting of this sort was the IFIP 8.2 meeting in Manchester under title ‘IS a dubious science’). This track seeks to fill this gap and invites submissions that propose a structured debate or a provocation on topics relevant for the IS field.

Track Chairs
Varun Grover, University of Arkansas, USA. Email:
Kalle Lyytinen, Case Western Reserve University, USA. Email:

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Friday, June 14th

Generative AI: The Emptiness Within

Dirk Hovorka, University of Sydney

Have Is Researchers Wasted The Last 10 Years By Simply Relabeling It Transformation Research As Digital Transformation?

Gabriele Piccoli, Louisiana State University at Baton Rouge
Joaquin Rodriguez, Grenoble Ecole de Management
Roxana Ologeanu-Taddei, TBS Business School,

Information Systems Research Should Influence The Digital Policy Process

Edgar Whitley, London School of Economics and Political Science

Is Behavioral Cross-Sectional Information Systems Research Just Linguistic Manipulation?

Kai R. Larsen, University of Colorado
Sen Yan, University of Colorado

The Harsh Review Culture In Our Discipline A Symptom For A Bigger Issue?!?

Karlheinz Kautz,, RMIT University

Vanquishing “Theory As King” By Focusing Instead On Rigorous Generalizations

Steven Alter, University of San Francisco