Organizational Efficiency through Intelligent Information Technologies

Sugumaran, Vijayan

កញ្ញា 2012 · IGI Global

អំពីសៀវភៅ​អេឡិចត្រូនិកនេះ

Intelligent information technologies are continuing to be utilized by a number of organizations to improve productivity. While a large amount of progress has been made, a number of issues still remain unexplored regarding the design and implementation of multi-agent systems for support of organization efficiency.

Organizational Efficiency through Intelligent Information Technologies explores various aspects of design and development of intelligent technologies by bringing together the latest in research in the fields of information systems, intelligent agents, collaborative works, and much more. This reference source also highlights insights on agent-based problem solving as well as economic issues and organizational impact.

អំពី​អ្នកនិពន្ធ

Vijayan Sugumaran is Professor of Management Information Systems and Chair of the Department of Decision and Information Sciences at Oakland University, Rochester, Michigan, USA. He received his Ph.D in Information Technology from George Mason University, Fairfax, USA. His research interests are in the areas of Big Data Analytics, Ontologies and Semantic Web, Intelligent Agent and Multi-Agent Systems, and Component Based Development. He has published over 200 peer-reviewed articles in Journals, Conferences, and Books. He has edited twelve books and serves on the Editorial Board of eight journals. He has published in top-tier journals such as Information Systems Research, ACM Trans on Database Systems, IEEE Trans on Engineering Management, Communications of the ACM, and IEEE Software. He is the editor-in-chief of the International Journal of Intelligent Information Technologies. He is the Chair of the Intelligent Agent and Multi-Agent Systems mini-track for Americas Conference on Information Systems (AMCIS 1999 - 2019). He has served as the program co-chair for the International Conference on Applications of Natural Language to Information Systems (NLDB 2008, 2013, 2016, and 2019). [Editor]