Intelligent Agents for Competitive Advantage: Requirements and Issues

Intelligent Agents for Competitive Advantage: Requirements and Issues

Mahesh Raisinghani (University of Dallas, USA) and John H. Nugent (University of Dallas, USA)
DOI: 10.4018/978-1-59140-206-0.ch002
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Abstract

This chapter presents a high-level model for employing intelligent agents in business management processes, much like has been successfully accomplished in complex telecommunications networks, in order to gain competitive advantage by timely, rapidly, and effectively using key, unfiltered measurements to improve cycle-time decision making. The importance of automated, timely, unfiltered (versus “end of period” filtered) reports is highlighted, as are some management issues relative to the pressures that may result concerning an organization’s employees who must now take action in near real time. Furthermore, the authors hope that understanding the underlying assumptions and theoretical constructs through the use of employing intelligent agents in business management processes as a sub element of, or tool within Business Intelligence (BI), will not only inform researchers of a better design for studying information systems, but also assist in the understanding of intricate relationships between different factors.

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Dedication
Table of Contents
Foreword
Thomas L. Hill
Preface
Mahesh S. Raisinghani
Acknowledgment
Mahesh S. Raisinghani
Chapter 1
Clare Brindley, Bob Ritchie
This chapter proposes that the initial perceptions of uncertainty and risk relating to decision making are unlikely to be modified irrespective of... Sample PDF
Reducing Risk in Information Search Activities
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Chapter 2
Mahesh Raisinghani, John H. Nugent
This chapter presents a high-level model for employing intelligent agents in business management processes, much like has been successfully... Sample PDF
Intelligent Agents for Competitive Advantage: Requirements and Issues
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Chapter 3
Andi Baritchi
In today’s business world, the use of computers for everyday business processes and data recording has become virtually ubiquitous. With the advent... Sample PDF
Data Mining and Knowledge Discovery
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Chapter 4
Ulfert Gartz
Although capacity and functionality of information management systems increased remarkably in the last years, the information and knowledge supply... Sample PDF
Enterprise Information Management
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Chapter 5
Rahul Singh, Lakshmi Iyer, Al Salam
This chapter presents an Intelligent Knowledge-Based Multi-Agent Architecture for Collaboration (IKMAC) in B2B e-Marketplaces. IKMAC is built upon... Sample PDF
An Intelligent Knowledge-Based Multi-Agent Architecture for Collaboration (IKMAC) in B2B e-Marketplaces
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Chapter 6
Dan Sullivan
As the demand for more effective Business Intelligence (BI) techniques increases, BI practitioners find they must expand the scope of their data to... Sample PDF
Text Mining in Business Intelligence
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Chapter 7
James E. Skibo
This chapter describes both the nature of trade allowances and the unique approach taken by one major retailer in overcoming legacy system obstacles... Sample PDF
Bypassing Legacy Systems Obstacles: How One Company Built Its Intelligence to Identify and Collect Trade Allowances
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Chapter 8
Edilberto Casado
This chapter explores the opportunities to expand the forecasting and business understanding capabilities of Business Intelligence (BI) tools with... Sample PDF
Expanding Business Intelligence Power with System Dynamics
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Chapter 9
Jeffrey Hsu
Most businesses generate, are surrounded by, and are even overwhelmed by data — much of it never used to its full potential for gaining insights... Sample PDF
Data Mining and Business Intelligence: Tools, Technologies, and Applications
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Chapter 10
Somya Chaudhary
This chapter focuses on the factors necessary for strategic Business Intelligence (BI) success from a managerial point of view. BI results from the... Sample PDF
Management Factors for Strategic BI Success
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Chapter 11
Hércules Antonio do Prado, José Palazzo Moreira de Oliveira, Edilson Ferneda, Leandro Krug Wives, Edilberto Magalhaes, Stanley Loh
Business Intelligence (BI) can benefit greatly from the bulk of knowledge that stays hidden in the large amount of textual information existing in... Sample PDF
Transforming Textual Patterns into Knowledge
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Chapter 12
John D. Wells, Traci J. Hess
Many businesses have made or are making significant investments in data warehouses that reportedly support a myriad of decision support systems... Sample PDF
Understanding Decision-Making in Data Warehousing and Related Decision Support Systems: An Explanatory Study of a Customer Relationship Management Application
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Chapter 13
Hamid R. Nemati, Christopher D. Barko, Ashfaaq Moosa
Electronic Customer Relationship Management (e-CRM) Analytics is the process of analyzing and reporting online customer/visitor behavior patterns... Sample PDF
E-CRM Analytics: The Role of Data Integration
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About the Authors