---------- Forwarded Message ---------- Subject: Call for Book Chapters: Organizational Data Mining Book Date: Tue, 9 Oct 2001 10:04:02 -0400 From: "Dr. Hamid Nemati" nemati@uncg.edu To: ISWORLD@LISTSERV.HEANET.IE
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CALL FOR BOOK CHAPTERS Chapter proposals submission deadline: November 30, 2001, Full chapter submission deadline: April 1, 2002
ORGANIZATIONAL DATA MINING: LEVERAGING ENTERPRISE DATA RESOURCES FOR OPTIMAL PERFORMANCE
A book Edited by: Hamid Nemati and Christopher Barko, The University of North Carolina at Greensboro
For more information, please see: http://elvis.uncg.edu/bae/hrnemati/odmcfp.htm
This book is the result of the observation that data mining is gaining greater acceptance within organizations and delivering colossal benefits, yet there are few scholarly books devoted to exploration of both the organizational and technical factors of how organizations leverage data resources to gain a competitive advantage. This is the essence of Organizational Data Mining (ODM). Organizational Data Mining (ODM) is defined as leveraging organizational data, information and knowledge assets to acquire and maintain a competitive advantage.
RECOMMENDED TOPICS This edited peer reviewed scholarly book seeks original contributions that explore a wide range of issues addressing all aspects of ODM. Manuscripts ranging from conceptual frameworks to case studies and empirical research are encouraged. Acceptable topics will include (but are not limited to) any of the following topics as related to ODM:
Research frameworks, methods, methodologies, architectures, and infrastructure issues in the design, implementation and maintenance of ODM projects and initiatives; Technical and organizational issues in the design, implementation and maintenance of processes that generate, share, use, disseminate and protect organizational data, information and knowledge; Issues surrounding the articulation and communication of the purpose and the nature of ODM and connecting it to other strategic and operational initiatives and activities of the organization; Strategic implications of ODM; Organizational learning; Decision support systems; Knowledge management; Data warehousing; Data mining tools, technologies and algorithms; Artificial Intelligence in Organizations; Knowledge discovery from databases; Web and E-commerce integration, strategies and challenges; Technical and database challenges in ODM; Measuring ODM effectiveness; Organizational, managerial, personnel, cultural, procedural and political issues in ODM; Global and cultural aspects and considerations in ODM; Case studies in all aspects of ODM; and ODM future trends.
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