|Editor-in-Chief:||Suprateek Sarker, University of Virginia, USA|
|Past Editor-in-Chief:||Shirley Gregor, The Australian National University, Australia|
|Kalle Lyytinen, Case Western Reserve University, USA|
|Phillip Ein-Dor, Tel Aviv University, Israel|
|Sirkka Jarvenpaa, University of Texas, Austin, USA|
The Journal of the Association for Information Systems (JAIS), the flagship journal of the Association for Information Systems, publishes the highest quality scholarship in the field of information systems. It is inclusive in topics, level and unit of analysis, theory, method and philosophical and research approach, reflecting all aspects of Information Systems globally. The Journal promotes innovative, interesting and rigorously developed conceptual and empirical contributions and encourages theory based multi- or inter-disciplinary research.
- Call For Papers - Theory Development Workshop, held at ICIS 2014 in Auckland. Click for details
- Call For Papers - Information Systems Solutions for Environmental Sustainability
- Call For Papers - The Role of Information Systems in Enabling Open Innovation
- Call For Papers - Methods, Tools, and Measurement in NeuroIS Research
- Call For Papers - Innovation in Information Infrastructures (III) - Published April/May 2014.
(Please indicate in your cover letter that your manuscript is for a special issue.)
JAIS Best Paper Award 2013
Work System Theory: Overview of Core Concepts, Extensions, and Challenges for the Future, Vol. 14, Issue 2, pp. 72-121.
JAIS Best Paper Award 2012
A Glorious and Not-So-Short History of the Information Systems Field, Vol. 13, Issue 4, pp. 188-235.
Rudy Hirschheim and Heinz K. Klein
JAIS Best Paper Award 2011
Secondary Design: A Case of Behavioral Design Science Research, Vol. 12, Issue 10, pp. 662-683.
Matt Germonprez, Dirk Hovorka, and Uri Gal
Current Issue: Volume 15, Issue 8 (2014)
Effects of Emoticons on the Acceptance of Negative Feedback in Computer-Mediated Communication
Weiquan Wang, Yi Zhao, Lingyun Qiu, and Yan Zhu
Generating Effective Recommendations Using Viewing-Time Weighted Preferences for Attributes
Jeffrey Parsons and Paul Ralph