Intelligent Support Systems Technology

IRM PRESS

Vijayan Sugumaran

Intelligent Intelligent

Support Support

Systems Systems

Technology: Technology: Technology:

Knowledge Knowledge

Management Management

TEAMFLY

Team-Fly®

Intelligent Support

Systems:

Knowledge Management

Vijayan Sugumaran, Ph.D.

Oakland University, USA

Hershey • London • Melbourne • Singapore • Beijing

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Library of Congress Cataloguing-in-Publication Data

Intelligent support systems : knowledge management / [edited by] Vijay Sugumaran.

p. cm.

Includes bibliographical references and index.

ISBN 1-931777-00-4 (paper)

1. Database management. 2. Artificial intelligence. 3. Knowledge management. I.

Sugumaran, Vijay, 1960-

QA76.9.D3 I5495 2002

006.3--dc21 2002017310

eISBN: 1-931777-19-5

British Cataloguing-in-Publication Data

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Intelligent Support Systems:

Knowledge Management

Table of Contents

Foreword ............................................................................................................ vii

Vijayan Sugumaran

Oakland University, USA

Preface .................................................................................................................. x

Chapter 1. Intelligent Agents and the World Wide Web: Fact

or Fiction? ............................................................................................................ 1

Sudha Ram, University of Arizona, USA

Chapter 2. Comparing U.S. and Japanese Companies on Competitive

Intelligence, IS Support and Business Change ....................................... 4

Tor Guimaraes, Tennessee Technological University, USA

Osamu Sato, Tokyo Keizai University, Japan

Hideaki Kitanaka, Takushoku University, Japan

Chapter 3. Knowledge Assets in the Global Economy: Assessment of

National Intellectual Capital ..................................................................... 22

Yogesh Malhotra, @Brint.com and Syracuse University, USA

Chapter 4. Knowledge-Based Systems as Database Design Tools: A

Comparative Study ..................................................................................... 43

W. Amber Lo, Millersville University and Knowledge-Based Systems,

Inc., USA

Joobin Choobineh, Texas A&M University, USA

Chapter 5. Policy-Agents to Support CSCW in the Case of HospitalScheduling ................................................................................................... 72

Hans Czap, University of Trier, Germany

Chapter 6. Building an Agent: By Example ................................................. 84

Paul Darbyshire, Victoria University of Technology, Australia

Chapter 7. Intelligent Agents in a Trust Environment .............................. 98

Rahul Singh, University of North Carolina, Greensboro, USA

Mark A. Gill, Arizona State University, USA

Chapter 8. A Case Study on Forecasting of the Return of Scrapped

Products through Simulation and Fuzzy Reasoning ............................109

Jorge Marx-Gómez and Claus Rautenstrauch

Otto-von-Guericke-University, Magdeburg, Germany

Chapter 9. Newshound Revisited: The Intelligent Agent That Retrieves

News Postings ..........................................................................................124

Jeffrey L. Goldberg, Analytic Services Inc. (ANSER), USA

Shijun S. Shen, Tygart Technology, Inc., USA

Chapter 10. Investigation into Factors That Influence the Use of the Web

in Knowledge-Intensive Environments................................................135

Yong Jin Kim and H. Raghav Rao, SUNY at Buffalo, USA

Abhijit Chaudhury, Bryant College, USA

Chapter 11. A Study of Web Users’ Waiting Time ....................................145

Fiona Fui-Hoon Nah, University of Nebraska-Lincoln, USA

Chapter 12. Stickiness: Implications for Web-Based Customer Loyalty

Efforts.........................................................................................................153

Supawadee Ingsriswang and Guisseppi Forgionne

University of Maryland, Baltimore, USA

Chapter 13. “Not” is Not “Not” Comparisons of Negation in SQL and

Negation in Logic Programming ............................................................164

James D. Jones, University of Arkansas at Little Rock, USA

Chapter 14. Knowledge Management and New Organization Forms: A

Framework for Business Model Innovation ........................................177

Yogesh Malhotra, @Brint.com, L.L.C. and Florida Atlantic University,

USA

Chapter 15. Implementing Virtual Organizing in Business Networks: A

Method of Inter-Business Networking ................................................200

Roland Klueber, Rainer Alt and Hubert Osterle

University of St. Gallen, Switzerland

Chapter 16. Managing Knowledge for Strategic Advantage in the Virtual

Organization ..............................................................................................225

Janice M. Burn and Colin Ash, Edith Cowan University, Australia

Chapter 17. Virtual Organizations That Cooperate and Compete: Managing the Risks of Knowledge Exchange .................................................248

Claudia Loebbecke, Copenhagen Business School, Denmark

Paul C. van Fenema, Erasmus University, The Netherlands

Chapter 18. Becoming Knowledge-Powered: Planning the

Transformation ................................................................................................274

Dave Pollard, Ernst & Young, Canada

About the Editor .............................................................................................296

Index .................................................................................................................297

Foreword

Organizations use a variety of computer-based systems such as management

information systems, decision-support systems and executive information systems to

support decision making. These systems deliver business data and information in a

highly aggregated form. However, they have not been able to keep up with the new

flood of information, particularly with the explosion in the amount of data being

generated, stored, accessed and processed by the ubiquitous Internet technologies.

This information overload coupled with competitive pressures signal the need for

“intelligent support systems” that can minimize the cognitive load on the knowledge

workers and decision makers.

In addition, fierce competition, globalization, and the digital economy have

forced organizations to search for new ways to improve customer satisfaction and

competitive advantage. This has created tremendous pressure on businesses to

minimize cost, increase quality, and reduce time-to-market for products to meet

customer demand. In order to satisfy these objectives, businesses are reorganizing

themselves into smaller and efficient units by pruning the organizational hierarchy

and becoming decentralized. Consequently, there is great need for improving

communication and information flow, and providing decision-making capabilities to

sites that have to respond quickly to market changes. Organizations are increasingly

turning to technologies to support their problem-solving and decision-making activities. To gain dramatic improvement in organizational productivity, emerging

information technologies (such as intelligent agents) are being applied to create a

cooperative and group-based work environment. Although artificial intelligence (AI)

technologies such as expert systems and neural networks have been successfully

used in aerospace, communication, medicine, finance, etc., they have not made a

significant impact on improving overall productivity due to their narrow scope. In

contrast, the new breed of “intelligent support system technologies” hold greater

potential in that they can be applied to a large number of domains and a diverse set

of problems. For example, a generic intelligent agent-based application can be

customized for different domains and a variety of problem scenarios.

Intelligent support systems are generally characterized as systems that help

users in carrying out difficult tasks by minimizing complexity and, hence, the users’

cognitive load. These systems have a learning component and gain “experience”

over time. They respond to changes in the environment and new situations with

minimal human intervention. They are context sensitive and capable of making sense

out of ambiguous or contradictory information. They also maintain user profiles

vii

including user preferences and previous actions, and serve as a tutor, critic,

consultant or advisor by providing suggestions and/or courses of action to take.

These systems exhibit “intelligent” behavior by dealing with complex situations and

applying their knowledge to manipulate the environment by recognizing the relative

importance of different elements within a problem scenario. The following is a partial

list of enabling technologies that are used in creating intelligent support systems: a)

intelligent agents, b) data mining and knowledge discovery, c) data warehousing, d)

fuzzy computing, e) neural networks, f) machine learning, g) client-server and web

technologies, h) business components, i) java and XML technologies, and j)

evolutionary algorithms. This book discusses the various aspects of designing and

implementing intelligent support systems using one or more of the afore-mentioned

technologies.

Intelligent agent technology is finding its way into many new systems,

including decision-support systems, where it performs many of the necessary

decision-support tasks formerly assigned to humans. Agents are loosely defined as

“software entities that have been given sufficient autonomy and intelligence to enable

them to carry out specified tasks with little or no human supervision.” Software

agents are useful in automating laborious and repetitive tasks, such as locating and

accessing necessary information, filtering away irrelevant and unwanted information,

intelligently summarizing complex data, and integrating information from heterogeneous

information sources. Like their human counterparts, intelligent agents can have the

capability to learn from their managers and even make recommendations to them

regarding a particular course of action. Generally, agents are designed to be goal

driven, i.e., they are capable of creating an agenda of goals to be satisfied.

Organizations are investing heavily in systems that help capture and manage

Business Intelligence (BI). One technology used to generate BI is data mining and

knowledge discovery. Data mining applications are coming to the forefront of

business data analysis and decision making. However, to successfully execute these

applications, a significant amount of a prioriknowledge is required about data mining

techniques, their applicability to different scenarios, relevant data selection and

transformation, etc. Hence, for a casual user interested in deciphering trends and

buying behaviors from customer “digital footprint” data, shielding some of the

nuances of normal data mining operations would be a welcome change. Intelligent

agent technology can play a major role in the design and development of such data

mining systems, particularly in hiding the complexity and implementing a scaleable

system. For example, the “interface agent” can assist decision makers (users) to

perform actions on a data warehouse that they cannot, or prefer not, to do

themselves.

Thus, intelligent agent technology is emerging as one of the most important,

and rapidly advancing areas in support system technologies. A number of agentbased applications and multi-agent systems are being developed in a variety of fields,

such as electronic commerce, supply chain management, resource allocation,

intelligent manufacturing, mass customization, industrial control, information retrieval

viii

and filtering, collaborative work, mobile commerce, decision support, and computer

games. While research on various aspects of intelligent agent technology and its

application is progressing at a very fast pace, there are still a number of issues that

have to be explored in terms of agent design, implementation, integration, and

deployment. For example, identifying salient characteristics of agents in different

domains, developing formal approaches for agent-oriented modeling, designing and

implementing agent-oriented information systems, collaborating and coordinating

multi-agent systems, and analyzing the organizational impact of agent-based systems

are some of the areas in need of further research. Intelligent support system

technologies will attain a permanent place in industry and will be deployed for the

purpose of increasing industrial productivity in many roles, such as assistants to

human operators and autonomous decision-making components of complex systems.

One can easily envision a world filled with millions of knowledge agents where the

boundary between human knowledge agents and machine agents is invisible.

Intelligent agents have the potential to radically change the way organizational work

is currently performed. Human agents can delegate a range of tasks to personalized

software agents that can not only make decisions based on the criteria provided by

their human counterparts, but also model the reasoning, action, communication, and

collaboration skills involved in performing human job functions. Capturing organizational

knowledge in a reusable form, and designing intelligent agents having access to this

corporate knowledge, is going to revolutionize organizational work environment in the

near future.

Vijayan Sugumaran

Department of DIS

School of Business Administration

Oakland University

Rochester, MI 48309

Preface

The Internet and associated technologies are playing an ever-increasing role

in the lives of businesses and academic organizations. As these technologies grow

in use, organizations are striving to improve their use within the organization.

Intelligent Support Systems play an important role in developing competitive technologies

in the Internet world. Additionally, knowledge capture, use and sharing are extremely

timely issues for businesses as they deal with virtual communities and virtual

organizations. In order to get the most from these emerging technologies and

understand how to best manage knowledge, academics, researchers and practitioners

must have access to latest information describing the most current research and best

practices in the use and development of these technologies. This book provides just

that. The chapters in this timely new book are a compilation of research on how to

develop and implement information systems. Additionally, the authors tackle the

difficult topics of defining virtual organizations and utilizing them to gain advantage.

Furthermore, the chapters describe the optimal knowledge management techniques

and practices. The authors represent a wide variety of organizational and cultural

backgrounds and share their insights in the following chapters.

Chapter 1, “Intelligent Agents and the World Wide Web: Fact or Fiction” by

Sudha Ram of University of Arizona (USA), proposes that collaborative multi-agent

systems are a very promising approach for managing information overload. The

author indicates that it will be necessary to move beyond the current Web interaction

paradigm of direct manipulation to indirect management of the Web. The author

describes how multi-agent systems have the capabilities to make the transition from

the current paradigm more smoothly.

Chapter 2, “Comparing U.S. and Japanese Companies on Competitive

Intelligence, IS Support and Business Change” by Tor Guimaraes of Tennessee

Technological University (USA), Osamu Sato of Tokyo Keizai University and

Kideaki Kitanaka of Takushoku University (Japan), reports on the findings of a field

test of how effectively U.S. and Japanese business organizations are identifying

strategic problems and opportunities, and how effectively they implement business

changes and use IS technology to do so.

Chapter 3, “Knowledge Assests in the Global Economy: Assessment of

National Intellectual Capital” by Yogesh Malhotra of Syracuse University (USA),

discusses the developing need for assessing knowledge capital at the national

economic level. The chapter further reviews a national case study of how intellectual

capital assessment was undertaken, suggests implications of such assessment

methods, and offers areas needing advancement.

TEAMFLY

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Chapter 4, “Knowledge-Bases Systems as Database Design Tools: A

Comparative Study” by W. Amber Lo of Millersville University and KnowledgeBased Systems, Inc. and Joobin Choobinch of Texas A & M University (USA),

surveys tools used in prototype database design and compares these tools with

respect to four aspects: database design support, tool flexibility, expert system

features and implementation characteristics. The results of the study indicate that,

in general, there is a lack of support for all phases of design, for group database design,

for graphic support, for empirical verification of the tools’ effectiveness, for long-term

maintenance of the tools, and for specialized knowledge representation.

Chapter 5, “Policy Agents to Support CSCW in the Case of Hospital

Scheduling” by Hans Czap of University of Trier, demonstrates the concept of a

policy agent used in hospital scheduling. This agent is able to represent individual

preferences and goals, and thus may act as a personal assistant to support solving

standard problems like operating room scheduling. The chapter demonstrates the

representation of preferences and goals in order to make adaptations to changes in

the environment and shows how the interaction works.

Chapter 6, “Building an Agent: By Example” by Paul Darbyshire of Victoria

University of Technology (Australia), is written in response to the growing need of

people who are interested in the emerging Web-based technologies and desire to build

their own agents. This chapter demonstrates the problems of building an agent using

the example of an email helper.

Chapter 7, “Intelligent Agents in a Trust Environment” by Rahul Singh of

University of North Carolina, Greensboro, and Mark Gill of Arizona State University

(USA), addresses the need for intelligent agents to include a mechanism for handling

trust. The chapter then discusses how the agents can be used as intermediaries in

electronic commerce. This work responds to the growing use of the Internet for

commerce and banking activities and acknowledges the important role trust plays in

online transactions.

Chapter 8, “A Case Study on Forecasting of Scrapped Products through

Simulation and Fuzzy Reasoning” by Jorge Marx-Gómez and Claus Raustenstrauch

of Otto-von Guericke University, Magdeburg (Germany), suggests a method to

forecast the timing and quantities of scrapped products. The method combines a

simulation approach with fuzzy reasoning. The prediction model presented is based

on life-cycle data, such as sales figures and failures and impact factors such as

lifetime wear and tear. The chapter presents the results of an empirical study wherein

the model was to use life-cycle data of photocopiers to forecast the returns.

Chapter 9, “Newshound Revisited: The Intelligent Agents That Retrieves

News Postings” by Jeffrey Goldberg of Analytic Services (ANSER)and Shijun Shen

of Tygart Technology (USA), reports on the authors’ experiences implementing an

Intelligent Internet Agent, Newshound. Newshound can be trained to recognize a

desired topic and scan Usenet newsgroups looking for new examples of that topic.

The chapter also introduces two additional intelligent agents: Chathound and Webhound.

Finally, the authors discuss the inter-agent communication layer, the facilitator for

cooperation between ANSER’s intelligent agents.

xii

Chapter 10, “Investigation into Factors That Influence the use of Web in

Knowledge-Intensive Environments” by Yong Jin Kim and H. Raghav Rao of

SUNY, Buffalo and Abhijit Chaudhury of Bryant College (USA), develops a set of

hypotheses regarding the relationship between the Technology Acceptance Model

(TAM) constructs and external variables The study reported here give insights

regarding the questions of when to implement a new technology and who is an eager

user of new technologies to learn. The chapter also is one of the first papers to use

TAM in the context of knowledge-management systems.

Chapter 11, “A Study of Web Users’ Waiting Time” by Fiona Fui-Hoon Nah

of University of Nebraska—Lincoln (USA), evaluates Nielsen’s hypothesis of 15

seconds as the maximum waiting time of Web users and provides approximate

distributions of waiting time for Web users. The chapter discusses the literature on

waiting time and reports on a study conducted by the author. The chapter

recommends that researchers and practitioners understand users’ waiting time

behavior, propose and evaluate techniques to reduce users’ perception of waiting

time, and recommend a trade-off between aestheticism of Web page design and

download/access time.

Chapter 12, “Stickiness: Implications for Web-Based Customer Loyalty

Efforts” by Supawadee Ingsriswang and Guisseppi Forgionne of University of

Maryland (USA), applies the concept of customer loyalty in traditional businesses to

digital products or services in order to describe a conceptual model of online

stickiness. Using the conceptual model, the authors identify the measures that

determine the stickiness of the Website and describe the applications of the stickiness

value.

Chapter 13, “’No’ is Not ‘Not’ Comparisons of Negation in SQL and

Negation in Logic Programming” by James Jones of University of Arkansas at Little

Rock (USA), focuses on the expressive power of weak negation in logic programming.

Weak negation is not presently well understood and is easily confused with negation

in SQL. The author describes weak negation and, to a lesser extent, discusses strong

negation in logic programming.

Chapter 14, “Knowledge Management and New Organization Forms: A

Framework for Business Model Innovation” by Yogesh Malhotra of Syracuse

University, proposes a sense-making model of knowledge management for new

business environments. The chapter then applies this framework in order to facilitate

business model innovations necessary for sustainable competitive advantage in the

new business environment, characterized by dynamic, discontinuous and radical pace

of change.

Chapter 15, “Implementing Virtual Organizations in Business Networks: A

Method of Inter-Business Networking” by Roland Klueber, Rainer Alt and Hubert

Österle of University of St. Gallen (Switzerland), describes a method that addresses

the need for a holistic view and methods that support implementation for business

networks. The method described includes the dimensions of strategy, process and

IS required for establishing and managing business networks. The authors describe

xiii

a project implementing a business-networking solution for electronic procurement.

The scenario described shows how a structured approach helps to identify scenarios,

aids in implementation, and applies previously created and newly created knowledge.

Chapter 16, “Managing Knowledge for Strategic Advantage in Virtual

Organization” by Janice Burn and Colin Ash of Edith Cowan University (Australia),

looks at the virtual organization and suggests that the basic concepts of virtual

management are so poorly understood that there are likely to be very few such

organizations gaining strategic advantage from their virtuality. The authors provide

clear definitions of virtual organizations and different models of virtuality that can

exist. The chapter presents six virtual models with a dynamic framework of change

and offers specific examples applying the models to organizations.

Chapter 17, “Virtual Organizations That Cooperate and Compete: Managing

the Risks of Knowledge Exchange” by Claudia Loebbecke of Copenhagen Business

School (Denmark) and Paul van Fenema of Erasmus University (The Netherlands),

explores the art of controlling knowledge flows in cooperative relationships. The

chapter conceptualizes types of knowledge flows and dependencies, resulting in four

configurations. The authors propose control strategies that allow companies engaged

in cooperation to anticipate deviant trajectories and define adequate responses.

Chapter 18, “Becoming Knowledge Powered: Planning the Transformation”

by Dave Pollard of Ernst & Young (Canada), identifies possible strategies, leading

practices and pitfalls to avoid in each phase of his award-winning process to

transform the company from a knowledge-hoarding to knowledge-sharing enterprise.

The chapter describes the challenges involved in identifying and measuring intellectual

capital, encouraging knowledge creation, capturing human knowledge in structural

form, and enabling virtual workgroup collaboration.

The role of intelligent agents in optimizing Website performance and

development and in enhancing security of Websites, as well as knowledge management’s

place in the virtual organization and in establishing and maintaining competitive

business advantage are just some of the timely topics contained in this important new

book. The information contained herein will be useful to academics as they attempt

to understand the theory of intelligent agent systems, to researchers as they attempt

to evaluate the efficacy of these systems and understand the intricacies of the

emerging field of virtual organizations, and to business people and practitioners as they

strive to implement the most current, best practices in knowledge management,

intelligent systems and virtual organizations. This book is a “must have” for all those

who want to understand how to achieve and maintain competitive advantage in this

increasingly virtual world.

IRM Press

January 2002

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