Building a Knowledge-Enabled Electronic Commerce Environment

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1

Building a Knowledge
-
Enabled

Electronic Commerce Environment


Minder Chen, Ph.D.*

Associate Professor of Decision Sciences & MIS

MS
-
5F4

4400 University Drive

School of Management

George Mason University

Fairfax, VA 22030
-
4444

U.S.A.

Phone: 703
-
993
-
1788

Fax: 703
-
993
-
1809

E
-
mail: MCHEN@GMU.EDU


Yihwa Irene Liou, Ph.D.

Associate Professor of Information Systems

Merrick School of Business

University of Baltimore

1420 N. Charles Street

Baltimore, MD 21201


U.S.A.

Phone: 410
-
837
-
5269 Fax: 410
-
837
-
5722

E
-
mail:
yliou@UBmail.ubalt.edu






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Special Issue on

Knowledge Management in e
-
Commerce


Vol. XXXXII Number 5 pp. 95
-
101.

2


Building a Knowledge
-
Enabled Electronic Commerce Environment




ABSTRACT


Companies with

electronic commerce (EC) operations have the advantage in
capturing more detailed information about their customers; hence they can obtain
insightful knowledge about marketplaces. We have developed a framework that
enables companies building an electronic

commerce site to take advantage of
knowledge management practices to enhance existing electronic commerce
capabilities. With more in
-
depth knowledge about customers, companies with a Web
presence can offer customized products and services to individual c
ustomers rather
than to large market segments. This framework may be used to assist the planning
and design of a knowledge
-
enabled electronic commerce environment. A detailed
data model that captures information and knowledge about products, customers, an
d
sales is discussed. This model serves as a foundation for building a technical
architecture of a knowledge
-
enabled EC system.


INTRODUCTION



Knowledge management (KM) is a multi
-
disciplinary area of research and practice. Stewart
[22] and Brooking
[3] approach KM from a human and intellectual capital perspective. Leonard
-
Barton [17] links it to innovation. Sveiby [23] tries to measure intangible assets including
knowledge processed by a company. KM development is also driven by technologies such
as data
warehouse systems, expert systems, collaboration tools, and document management tools [6]. More
3

recently, Web
-
based technologies labeled as intranet and corporate portals have been used to support
knowledge management [1]. Companies are quick in

embracing the Web as a KM tool because of
the Web's broad reach and its ability to deliver rich media.


Electronic commerce (EC) sites currently, are slow to adopt knowledge management (KM)
practices and tools. Some Web sites have applied KM principles

in their EC activities, but they have
implemented KM unconsciously and implicitly [14]. Most EC sites are not benefiting fully from
KM research. The objective of this paper is to explore how we can bring KM principles and tools to
enrich the EC environm
ent. We compare the common elements between KM and EC in Section 2.

A framework of integrating KM in an EC environment is proposed in Section 3. Building
knowledge about customers and products is critical to the usage of knowledge in an EC environment
.

We have developed a data model in Section 4 to exemplify how multiple sources of information and
knowledge can be captured and used to support EC activities. A technical architecture for a
knowledge
-
enabled environment that integrates Web servers, data
bases, data warehouses, and KM
tools is discussed in Section 5. The framework and the technical architecture presented in this paper
serve as a guide to assist business planners and system architects to plan and design their EC sites.
Existing Web sites
such as Amazon.com will be used throughout this paper to exemplify the
concepts proposed in this paper.


ENHANCING ELECTRONIC COMMERCE WITH KNOWLEDGE MANAGEMENT:

A COMPARATIVE VIEW


Attracting and retaining customers, as well as making a profit, are the

goals of EC sites. To
4

achieve these goals, EC sites are built on three major pillars:
content
,

community
, and

commerce
.

These three pillars are inter
-
related components that support each other. Understanding how
knowledge can be used to enhance conte
nt, to strengthen community, and to increase commerce is
the first step towards building a knowledge
-
enabled EC environment.


Content
is king in the EC world because useful contents are what attract people to an EC site
in the first place. KM can extend

the notion of content from static Web pages to information and
knowledge that is stored in databases and knowledge bases. Contents of an EC site typically include
product catalog, product reviews, and frequently asked questions (FAQ). A customer can que
ry
product and pricing information stored in a database and the most current information requested will
be generated dynamically for the customer.


Traditional KM effort tends to focus on capturing knowledge of employees, particularly
engineers, research
ers, and consultants. It is more inward looking and tries to capture and tap into
the expertise of its employees regarding products and processes. The focus is shifting to knowledge
of products and customers when applying KM to electronic commerce. Prod
uct knowledge may not
only be provided by employees, but also come from customers and suppliers as important knowledge
sources. Linking and finding people who have expertise in a business domain is an important
requirement of a KM system. We may use expe
rt locator tools to help customers find employees,
partners, and even other customers who may have the expertise needed by some customers.


Tacit knowledge is very difficult to externalize or transfer in a systematic way by domain
5

experts [21]. KM prac
titioners encourage forming
communities

that allow people in these
communities to engage in informal interactions. Through these interactions in the context of
problem solving, the tricks of the trade can be observed, revealed, and shared. Other than fac
e
-
to
-
face meetings or social events, technologies such as groupware and video conferencing are effective
means to assist people in sharing knowledge by means of interaction and collaboration.


The Internet is founded on a strong sense of community. T
here is no surprise that some
successful Web sites have a strong community focus. For example, iVillage.com is for women;
Parentsoup.com targets parents; and verticalnet.com is oriented towards engineers. Experts are often
invited to host an online colum
n to contribute, edit, and distribute knowledge that is of interests to
people in the community. Members of a
community

also contribute to the new
contents

of a Web
site, which draws more people to the site. Once there is enough traffic to the site,
comm
erce

activities including advertising and selling increase. Revenues generated by commerce will be used
to sustain the operations of the site.


Successful sites that started with a
commerce
focus have also developed a strong sense of
community. Amazo
n.com tries to create a virtual community for book lovers. Its environment is
similar in function to the Barnes and Nobles' physical stores that have coffee shops, chairs, and tables
to facilitate customers to interact with each other. For example, Amaz
on.com has
Reader Circle

and

Top Reviewers
. Book reviews from readers and staff members are feature attractions that bring
Amazon.com's customers back to its site. Books are reviewed and rated by site visitors. More
recently Amazon.com introduced a sys
tem to allow other visitors to vote on the reader's review in
6

terms of its helpfulness. Since then, we have seen more lengthy and helpful reviews. Amazon.com's
only reward to reviewers is to create a list of top reviewers and to provide pages to profile
them.
Amazon.com has been very successful in eliciting customers' knowledge about its products.


Tapping into the collective knowledge of a community allows Web users to find out what
online resources are more relevant and credible. For example, the se
arch engine site Google.com
returns a list of pages from a search, based on the number of links and the relevancy of these links
connecting to these pages [10]. It assumes that the more people link their pages to a Web site, the
more valuable the Web site

is. On eBay.com, an auction Web site, sellers and buyers can evaluate
each other via the
Feedback Forum

regarding how they were treated in a transaction. The rating
helps eBay's users to decide whether they should buy or sell from one another. Ebay bel
ieves its
users' "honest feedback shapes the eBay community and specifically impacts the success and
behavior of other eBay members [7]."


There are two major strategies for managing knowledge [12]: codification and networking.
Codification takes the peo
ple
-
to
-
document
-
to
-
people approach and usually involves using electronic
document systems such as Lotus NOTES to codify, store, and disseminate knowledge. Networking
strategy takes the people
-
to
-
people approach to facilitate people interacting with each
other directly.
For example,
certain tacit knowledge can be shared and transferred more effectively via informal
gathering and conversation among people in the same community of practices.
We can use
online
discussion forum and virtual chat room to facil
itate networking and knowledge sharing. Since the
conversation is conducted online, electronic records can be preserved as codified corporate memory.
7


On the Web, the two strategies can be merged.



Although there are some fundamental differences
between KM and EC, they do share some
common goals and use similar technologies. KM practitioners are embracing the Web as a key
technology enabler and are extending their focus from internal employee knowledge management to
the management of supplier and

customer knowledge, i.e., the focus of EC initiatives. The
convergence of KM and EC may produce fruitful results in enhancing each other. In this paper we
focus our discussion on the integration of KM practices and techniques in an EC environment.


A
FRAMEWORK OF A KNOWLEDGE
-
ENABLED

ELECTRONIC COMMERCE ENVIRONMENT


The similarities and complementary natures between EC and KM are obvious. However,
most companies that launch EC projects do not seem to connect KM with EC initiatives. Holsapple
and Sing
h [14, p. 164] proposed an expanded definition of EC that incorporates a knowledge
-
management view as follows:

"EC is an approach to achieving business goals in which technology is used to
manage knowledge for purposes of enabling or facilitating the exe
cution of activities
in and across value chains as well as the making of decisions that underlies those
activities."



We are proposing a framework to integrate KM principles and processes in an EC
environment such that EC activities can be enriched and e
nhanced with knowledge. First, we have
identified the KM activities
that need to be embedded in EC activities from a process perspective.
These KM activities are discussed in the following:

1.

Identify and capture
: Knowledge sources that generate new kn
owledge should be identified
first. One knowledge source can be from existing information systems, such as transaction
8

processing systems and data warehouses. Knowledge sources can be internal employees and
external trading partners of an organization.

In an EC environment, the opportunities for
capturing knowledge from customers are abundant. Customers play a dominant role as an
important source of knowledge.

2.

Adapt and organize
: Knowledge captured needs to be adapted and organized via
condensing, c
ategorizing, and connecting it. A data warehouse is a system that consolidates
data from operational databases and other sources into subject areas; while data mining is
used to connect seemingly unrelated knowledge pieces [5].

3.

Share and distribute
: If p
eople are hoarding information or knowledge, organizations
suffer. The organizational cultures that encourage sharing are critical to the success of
knowledge management initiatives. The KM systems should be designed to provide easy
access to knowledge
while security issues are addressed. They should take a more proactive
role in distributing knowledge to users according to their profiles and activities.

4.

Use and create
: Knowledge once obtained, can be used by people or embedded in a system
to enhance

its functionality. The experiences and feedbacks gained from using existing
knowledge may create new knowledge and that is the beginning of another knowledge cycle.


The proposed framework of a knowledge
-
enabled EC environment as depicted in Figure 1
ha
s knowledge at its center. This knowledge is gathered and used via interactions with customers
from a sequence of EC activities. Three sets of overlapping knowledge that are critical to the
success of knowledge management in an electronic commerce envir
onment are:
customers,
products
, and
sales.

The capturing, organizing, and distributing of such knowledge should be
9

integrated with key electronic commerce processes.
We first define a sequence of major
touch points

that customers interact with an EC site
. These touch points reflect a customer's procurement cycle:
searching and evaluating products (or services), buying products, and seeking resolutions to
problems with acquired products. EC activities and customer interactions conducted online at these
touch points require an in
-
depth knowledge about customers and products. These knowledge
-
enabled and
customer
-
facing
processes in the framework are discussed in the following.



Figure 1. A Framework of a Knowledge
-
Enabled Electronic Commerce Environme
nt


10

1.

Attract
: Companies use various advertising and marketing channels to attract
potential customers to their sites including online advertising banners and offline ads,
registrations with popular search engines, and offering special discounts or coupons.

Sale leads can be generated from visitors by enticing them to register with the site,
that is the first step in gathering information about customers. Web sites should ask
customers only for the information that can help customers and that is required fo
r
completed a transaction. Site contents or product offerings need to be updated
frequently to ensure that visitors are willing to come back again.


2.

Interact
: Visitors of an EC site are looking for information about products or
services. An EC site sh
ould establish a merchandising strategy by choosing and
managing product categories and merchandise to ensure that product offerings are
appealing to its customers. Product information including specifications, pricing,
product images, availability, and c
onfiguration options should be posted online. A
product recommendation expert system can be used to interact with users to elicit
their requirements and to recommend appropriate products.


3.

Transact
: During the transaction phase, a customer sends product
s to an electronic
shopping cart for checking out later. The checkout procedure is where the actual
business transaction occurs. The payment amount including shipping and handling is
determined and reviewed by the customer. The online ordering system sh
ould be
integrated with back
-
end inventory, accounting, billing and distribution applications.
11

Customers may log in to check their order status and review their accounts online. E
-
mail can be used to inform a customer of the progress of an order during it
s
fulfillment cycle.


4.

React
: Customer service is an element that can really provide strategic advantage
given the Internet’s 24x7 nature. Customers increasingly expect great customer
services from online businesses. Capturing comprehensive customer pr
ofiles
including customer's ordering history and products purchased is the first step to
providing better customer service or self
-
service [9]. Case
-
based reasoning systems
have demonstrated great potentials in customer service areas such as in trouble
sh
ooting product problems [6]. New problems solved should be added to the
knowledge base for future reference.



Successful KM initiatives are the ones that support the core business processes. We have
identified a generic process model that captures the

key processes of EC activities for a typical
business
-
to
-
consumer electronic commerce. These processes are formed based on the customer
management activities including acquiring new customers, building relationships with customers,
and servicing customer
s after products and services have been purchased [18].
Customer intimacy
and serving customers better are the major reasons for companies to implement knowledge
management programs. However, without the physical contact with customers, it is very challen
ging
to provide highly personalized and interactive customer experiences.

In cyberspace, customer
service becomes more important than ever.



The KM processes of capturing, organizing, storing, distributing, and using knowledge need
12

to be embedded in
each of these activities in a coordinated manner. Knowledge of the market and
potential customers based on market research and historical data can be used to enhance marketing
and advertising. The effectiveness of these marketing and promotion efforts sh
ould be tracked to
provide feedback for their improvement. Once potential customers are drawn to EC sites, we need to
track their browsing behaviors and analyze it to understand why they decided to buy. The initial
contacts with our potential customers (
the leads) are analyzed to provide follow
-
up with the
customers or to forward the information to the firm's strategic partners.


MANAGING KNOWLEDGE ABOUT CUSTOMERS AND PRODUCTS

FOR ELECTRONIC COMMERCE



Operating in a virtual world, customer relationship

management is important to make the
virtual world as real as possible. Giving customers a sense that a Web site really knows them may
attract them to come back. To achieve such online customer intimacy, a seamless integration of
customer relationship m
anagement application packages and EC systems is required.
Strong
customer relationships depend on effective and timely customer interaction supported by
comprehensive customer knowledge. Effectively m
anaging knowledge about customers is critical to
ensu
re loyalty, growth, and profitability.


Not all customers are created equal, therefore an EC site needs to use data obtained from
customers to develop deeper knowledge about their behaviors. Information about customers may
include not only the basic cus
tomer information, but also the sales data associated with a customer's
purchased products and services. In addition, visitors' activities stored in Web site log files can be
13

used to correlate a customer's potential interest to the goods and services offe
red by the site.


We have developed a baseline data model as depicted in Figure 2 according to our analysis of
several EC software packages' design and customer relationship management (CRM) literature [2,
11, 19, 20]. The model illustrates key conce
ptual constructs required to support the management of
information and knowledge about
customers, products
, and

sales

areas in a knowledge
-
enabled EC
environment. In order to reduce the complexity of the model, the entity
-
relationship diagram does
not sho
w attributes and many
-
to
-
many relationships are not decomposed into one
-
to
-
many
relationships.


14


Figure 2. A Data Model for Managing Customers, Products, and Sales Information


Products Area.

Merchandizing, the categorization and selection of products
to be sold, is
one of the most important strategies in setting up an EC site. In our data model, the
Product

entity
can be classified into the
Category

entity. A category can be refined into subcategories via the
recursive relationship
"has subcategories
."

This information allows users to drill down through a
category hierarchy during their browsing to find products. The
Product

entity may be further
characterized by various attributes. Customers often use these attributes as search criteria.
Attribut
es for different types of products may vary. For books, we may identify attributes such as
author, title, ISBN, and subject keyword. Size, color, style, and brand are examples of attributes for
clothing. Domain experts may help to identify these attribu
tes in their industries. Search criteria
sometimes are related to customer's wants and needs that may not be physical features of products.
A parametric search for products can be implemented by using a query form that allows a user to
enter search crite
ria. The criteria are submitted to a server
-
side script that creates a dynamic SQL
statement to search the product database. Some multi
-
value attributes need to be set up as separate
entities. These entities are related back to the
Product

entity (e.g.,

a relationship between author and
book). The
Keyword

entity is

an example of a multi
-
value attribute about the
Product

implemented as an entity.


Additional product configuration information is needed for companies selling customized
products that hav
e various optional items. For example, the Dell Computer Corporation is well
known for its Web site's (i.e., Dell.com) ability to allow users to pick and choose various options of a
computer's configuration. The
Component

entity and its "
is used in
" rel
ationship to
Product

15

support this configure
-
to
-
order (CTO) feature. The challenge in building such a system is to create
and maintain the knowledge reflecting the changing product configurations and the availability of
components. The constraints among v
arious components are represented by a recursive "depends
on" relationship associated with the
Component

entity (e.g., if you choose a SCSI hard drive, you
need to buy a SCSI interface card). The
Product

entity can be related to the
Cross
-
Sell

entity and
the
Up
-
selling

entity. The cross
-
selling and up
-
selling information can be entered manually based
on employee's experiences about products. It can also be derived from using "market
-
basket
analysis" to correlate products that customers tend to buy by co
mparing purchasing patterns of
different customers [
18
].


Customers Area.

Target marketing and market segmentation rely on data about a customer's
demographics consisting of location, lifestyle, and products purchased. For example, Outpost.com
success
fully uses criteria such as recency (how recently customers have visited a company Web site),
frequency, and monetary value to segment its customers for target marketing [18].
Customers'
feedback regarding products are important knowledge that an EC firm
can collect from its customers.

This information is captured via the
Review

entity between
Customer

and
Product
. Customers are
major contributors for product reviews. Additional product information or reviews may come from
manufacturers, distributors, i
ndustry experts, or employees of the firm. Feedback from customers
about products allows EC sites to establish a knowledge acquisition mechanism to elicit knowledge
about products and their usages.


Sales Area.

Sales data links customers to products
. It includes the
Order

entity and the
Order Item
. Ordering history can be used as inputs to facilitate personalized interaction with
16

customers. By capturing a marketing campaign via the
Promotion

entity and relating it to sales data,
companies can analy
ze the effectiveness of marketing campaigns as compared to a non
-
campaign
period.
Sales data can be consolidated into a subject area of a data warehouse consisting of a sales
fact table

and other factors that may affect the customer purchasing decisions d
efined as dimensions
[15]. This is the first step towards transforming customer data into information and knowledge. We
can then use data mining tools to analyze the information in the data warehouse to create patterns
and rules that may explain customer
s' purchasing behaviors. How these data, information, and
knowledge can be integrated from a technology viewpoint is discussed in the next section.


A TECHNICAL ARCHITECTURE OF A KNOWLEDGE
-
ENABLED

ELECTRONIC COMMERCE ENVIRONMENT



EC has its roots in t
echnology, i.e., the Internet and the World Wide Web. The first
generation Web was created for document sharing using HTML as a documentation specification
standard and using HTTP as the communication protocol to support WWW service. The Common
Gateway I
nterface (CGI) standard became available for building interactive applications such as
guest book, discussion forum, and search engines. More recently, server
-
side scripting languages
such as Java Server Pages (JSP) can integrate with software components
that encapsulate business
logic and run on application servers [8]. This approach allows developers to build scalable EC sites
with integrated customer, order, and product databases. A technical architecture, as depicted in
Figure 3, is presented in this

section to illustrate how existing EC sites can be extended to
incorporate knowledge management tools.

17


Figure 3. A Technical Architecture of a Knowledge
-
Enabled EC Environment


The architecture diagram illustrates how we can integrate database, data w
arehouse, and
knowledge
-
based systems to support an information
-
rich and knowledge
-
enabled EC system. This
technical architecture supports the framework described in Section 3. It is compatible to KM system
architecture proposed by Tiwana [24]. It also
supports the generic process
-
oriented and knowledge
-
based commerce architecture proposed by Kocharekar [16]. This architecture can be viewed as a
multi
-
layer system and the building blocks in each layer have been labeled according to the
description in th
e following:


1.

The static Web content layer.

The first layer includes the Web servers, Web server log
files, and the static Web contents. The Web contents can be in HTML or XML formats.
XML may be used to deliver content to multiple viewing devices. Th
e Web site usage
information is stored in a Web log file. Web site analysis tools such as WebTrends can
18

use log files to study visitors' usage patterns. The result of such a study can be used as a
basis for redesigning a Web site.

2.

The dynamic contents an
d transactional processing layer.

The second layer includes
server
-
side scripts, software components, and the operational databases. Structured
contents that need to be managed and updated in a timely manner are stored in databases.
Database contents ca
n be accessed via server
-
side scripts to be returned dynamically to
Web users. Transaction data is stored in transaction databases containing information
about customers, products, and sales transactions.

3.

The data warehouse and OLAP layer.

The third la
yer consists of data warehouse
systems and front
-
end online analytical processing (OLAP) tools. The transaction data
stored in the operational database is extracted, filtered, and consolidated into a database
managed by the data warehouse environment.
The design of a data warehouse is usually
represented as a star schema or a snowflake schema about a subject area [15]. The star
schema is centered on a fact table that is related to several dimension tables. When some
dimension tables are further refine
d into more abstract dimension tables by extracting low
cardinality attributes into tables of their own, the resulting design is referred to as a
snowflake schema.
OLAP tools can be used to allow managers to access and analyze
information from various dim
ensions. Recently, many data warehouse systems are
becoming Web
-
enabled; access to such systems is more convenient [4].

4.

The knowledge base layer.

The fourth layer includes knowledge base and KM tools.
Via data mining and other knowledge acquisiti
on techniques, rules and heuristics can be
derived and stored in a knowledge base. The term knowledge and knowledge base is used
19

in a very narrow sense in this context. The knowledge can be used to guide the employees
in using information more effectivel
y. The Web site can use such knowledge to provide
customers with more personalized contents or services. Knowledge about products may
help the site to provide better product selection advice. In a broader sense, documents,
databases, data warehouses, a
nd knowledge bases are all considered as sources of
knowledge.


Web has become a standard mechanism used by customers and partners. Server
-
side
scripting languages and components (e.g., ActiveX components, Java Beans, or Enterprise Java
Bean) can be u
sed to connect the Web server with the database, the data warehouse, and the
knowledge base. The knowledge derived from the operational database and data warehouse can be
used by real
-
time inference engines to provide better online customer assistance.


T
racking and identifying Web site visitors or customers is a major challenge in building an
EC Web site. Browser cookies can be used to track visitors who use the same computer to visit a
Web site. Asking users to log in every time they visit a Web site c
an be inconvenient; therefore, this
is only done for Web sites such as eTrade.com where security is extremely important or when a
secured transaction is required during a checkout process.


The scope of a company's EC system needs to expand beyond corpor
ate borders in order to
answer questions such as product availability from customers. Such an EC system needs to be
integrated with its own or with its partner's ERP system and supply chain management software.
Customers visiting an EC Web site often wan
t to know when products they have ordered will be
20

shipped. Only companies that provide such supply chain and logistics visibility will succeed.


CONCLUSIONS



We have observed the gradual introduction of knowledge management principles and tools in
EC envi
ronments. The comparison study presented in this paper may help researchers and
practitioners to reflect on how KM and EC may complement each other and how EC can be
enhanced with knowledge
-
enabled environments. EC systems provide interfaces with custom
ers
and can capture knowledge about customers directly at points of contact
. Then, the knowledge can
be used to support the execution and continuous performance improvement of critical EC activities.
The data model discussed in this paper may provide a b
aseline for building EC sites. Models for
business
-
to
-
business EC activities and auction sites require further research.


Customers and suppliers should become active participants in a knowledge
-
enabled
environment because they are important sources of
knowledge. Involving them in KM activities is a
way to forge a strong sense of community.
To implement KM practice, EC firms need to develop
performance measures and reward systems to encourage knowledge sharing. The valuation of
k
nowledge should be con
ducted from the customer's perspective.
The rewards to customers and
business partners as well as employees need to be explicit and fair.



There are many similarities between KM and EC as presented in this paper. However, the
discussion is limited to
the application of KM principles and tools to EC environments. Several
successful tools and approaches developed in the EC world will be studied to explore how they may
21

be applicable to KM practices. We believe that knowledge is becoming an important com
modity in
the EC world. For example, Guru.com is an EC site that manages and offers knowledge of
worldwide experts. The study of these knowledge
-
focused EC sites may help us to further develop
knowledge
-
enabled environments proposed in this paper.


REFERENCES

[1]

Applehans, W., etc.
Managing Knowledge: A Practical Web
-
Based Approach,
Addison
-
Wesley, Reading, MA, 1998.

[2]

Barrenechea, M. J.,
Customer Relationship Management
, Oracle Corporation, 2001.

[3]

Brooking, A.
Intellectual Capital
, International Thomson

Business Press, London, UK, 1996.

[4]

Chen, L. and Frolick, M. N. "Web
-
Based Data Warehousing
," Information Systems
Management
, Spring 2000, pp. 80
-
86.

[5]

Chen, L, Sakaguchi, T., and Frolick, M. N. "Data Mining Methods, Applications, and Tools,"
Information
Systems Management
, Winter 2000, pp. 65
-
70.

[6]

Davenport, T. H. and Prusak, L.
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