Journal of the Association for Information Systems (JAIS) is organizing a workshop on what it means in the current times, to be an Information Systems scholar. Never before has the scholarly work of IS researchers had the scope and potential to address such a wide range of topics, reach such a varied audience and transform so many areas of human life. And yet, with the seeming abundance of socially generated data, rapidly developing computational social science methods, and generative AI, never before have we faced the prospect of fundamental transformations as we do now, in what we do, and how and why we do it. At such an inflection point in the IS discipline’s evolution, this workshop will bring together IS colleagues from across the AIS regions, to reflect on the goals, means and ends of our research. Such reflection is necessary, for scoping out our spheres of influence as scholars and for our personal journeys of learning and contributing.
Charles J. Dockendorff Endowed Professor
University of Massachusetts Amherst
Professor of Innovation and Information Management
The University of Hong Kong
Pick any two questions from the list below and write your thoughts about them. Your write-up should – (1) mention your professional affiliation/details; (2) be contextualized to your own experiences and challenges regarding things you have done; (3) indicate why you think the workshop will be helpful for you; and (4) not exceed 2 sides of double-spaced TNR 12. Send your write-ups in an MS word file to the following email: jaisws2023@gmail.com by August 31, 2023.
Selected submissions will be grouped into discussion round tables, mentored/facilitated by IS scholars from the JAIS editorial board. The workshop will be a mix of roundtable and plenary activities. We invite submissions from all IS scholars who are tenure-track/tenured/post-doc.
We wish to encourage diverse views. Within that framing, we are particularly interested in innovative and proactive stances and approaches to – (1) building and strengthening cumulative IS knowledge; (2) influence outside academia – practice and policy; (3) working with socially generated large data sets; (4) working in multidisciplinary teams and projects; (5) using generative AI technology in the research process.
Hillol Bala
Indiana University
Roberta Bernardi
University of Bristol
Michelle Carter
Manchester University
Daniel Chen
Texas Christian University
Yulin Fang
Varun Grover
University of Arkansas
Dirk Hovorka
University of Sydney
Mathew Jones
University of Virginia
David Preston
Texas Christian University
Ulrike Schultze
University of Groningen
Heshan Sun
The University of Oklahoma
Monideepa Tarafdar
University of Massachusetts Amherst