An E-DSS for Strategic Planning of
E-Commerce Website Development
Ranjit Bose
Associate Professor of MIS
Anderson School of Management
University of New Mexico
Albuquerque, NM 87131
USA
E-mail: bose@anderson.unm.edu
ABSTRACT
In this new millennium, entirely new
markets, products, and services are
emerging from digital technologies such as
Internet based businesses or e-commerce.
Strategic planning of e-commerce website
development is one of the critical activities of
an organization within the context of its ecommerce investment and success. The
unstructured nature of this problem-solving
activity makes it an appropriate candidate
for decision support systems (DSS) based
solution design. In this paper, we propose
the development of such a DSS, which we
call an e-DSS, since it is Internet based. The
purpose of this research is to analyze the
requirements for creating the e-DSS. The
research findings are organized and
presented as detailed requirements and
content assessment of each of the e-DSS
components, which include the user
interface, model base and database. In
particular, these findings will immensely
help the information technology managers
and professionals who are considering
construction of such a DSS for their
organization.
1. INTRODUCTION
Today’s e-commerce environment is
increasingly becoming complex, the focus is
towards using “The Web” and its enabling
technologies to strategically create a web
presence or website that can provide valueadded capabilities and integration in all
aspects of a business’s functional and
operational areas. More businesses are
moving toward these electronic processes
and procedures that use e-commerce,
pushing the rest of the businesses to take
action or be “e-lagers,” that is, left behind.
For example, Lai and Yang (2000) predict
that, “total value of goods and services
traded over the web in the United States
alone will reach US$327 billion in the year
2002, an average annual growth rate of
110%.” Interestingly, Ince (2000) notes that,
“only about half of small businesses even
have Internet access. Of those, only a small
percentage has continuous Internet access.
To really open up this market, you have to
get people to understand that the Internet is
something that can be useful to their
business.”
E-commerce can be defined as internal
and external operations of businesses that are
performed at high speed and response rate to
satisfy the customers, who expect real time
communication and guaranteed satisfactory
outcomes in products and services. The
foundation
of
e-commerce,
in
an
organization,
relies
on
developing
appropriate websites based on its business
strategies. It is then critical for decisionmakers to strategically plan the e-commerce
website development, as well as for them to
know what tools and technologies could be
used, and how they could be used to analyze
and to act effectively on this new paradigm.
In an unprecedented manner, today’s ecommerce
requirements
are
placing
increasing strain on decision-makers to have
the channels available and the infrastructure
visible and effective. Therefore, a specific
Internet-based DSS which would provide
insight into the critical and complex activity
of strategic planning of e-commerce website
development could be quite beneficial to a
range of companies from startup to Fortune
500. The decisions that would be made based
on the strategic planning of e-commerce
website development will directly impact the
ability to satisfy customers, suppliers, and
key stakeholders.
This research contends that in this “eera,” a specific Internet-based DSS for
strategic planning of e-commerce website
development, which we call an e-DSS, is
needed. The unstructured nature of the above
problem makes it appropriate for a DSS
based solution. The e-DSS would be able to
provide alternative strategies, as well as
facilities to analyze and evaluate these
strategies for selecting the best strategy for
an organization for its e-commerce website
development. The implications of such a
system are, first, the e-DSS would bring
together new models, new data as well as
information, and expert e-commerce
knowledge
that
many
individual
organizations
and
researchers
have
successfully utilized and are seen as critical
in such development. Second, the e-DSS
would provide the decision-makers such as
marketing managers, IS managers, and
executives the expectations, investment
resources, threats, risks, costs, and
opportunities of e-commerce website
development.
The purpose of this research is to
analyze the requirements for creating the eDSS. The research findings are organized
and presented as detailed requirements and
content assessment of each of the e-DSS
components, which include the user
interface, model base and database. In
particular, these findings will immensely
help the information technology managers
and professionals who are considering
construction of such a DSS for their
organization.
2.
CHALLENGES AND ISSUES FOR
E-DSS
Creating a strategic website for ecommerce has many challenges and impact
on an organization’s functional, managerial,
and strategic levels. Specifically, the major
groups impacted are strategic planning, IS
departments and marketing. Although, other
groups, such as accounting, operations and
procurement could be included. For the
purpose of this research, only the major
groups have been studied and analyzed.
Strategic planners such as small
business owners, CEO, CFO, and VP
marketing are continuously looking to
improve business but are also inherently risk
adverse which in itself creates challenges in
web
development
and
e-commerce
integration. In this technology era
organizations are more prone to demand risk,
innovation risk, and inefficiency risk, the
goal would be to use the web to reduce these
risks and have a clear risk analysis.
Therefore, at the same time there has to be
controls and audits in place for websites
development and e-commerce projects
before hand. Creating a web environment
will impact current customers, suppliers,
partners, B2B (business to business)
(Papazoglou and Tsalgatidou, 2000), and
B2C (business to consumer) relationships.
Opportunities for focused, quality, highspeed communications products and
components for communications could fulfill
the need or concept of immediacy; where
customers, partners, banks, etc. want
everything right now. Therefore, the
challenge is to know how to strategically go
about integrating websites and e-commerce
into the business functions that currently
exist to solve business problems. Such
critical success factors can impact what
decision-makers must take into consideration
and how they should take them into
consideration when investing in developing
new or redeveloping existing website
infrastructure.
The IS department deals with issues
such as the development and resources of
websites that include high performance and
high availability, web design, security risks,
authentication and privacy issues. The
challenges of maintaining user-friendly
websites and their applications, and the
testing process of middleware technologies
are also critical. One of the critical tasks of
the IS departments in organizations is
prioritization
of
the
above
issues.
Furthermore, they are challenged with
selecting algorithms, design models, agent
technologies, and doing analysis of business
and market planning.
From the marketing perspective the
challenge
of
e-commerce
website
development is to define the Internet
customer prior to establishing an Internet
presence (Kiang, Raghu and Shang, 2000).
“Firstly, how many existing or potential
customers are likely to be Internet users? If a
significant proportion of a firm’s customers
are Internet users, and the search cost for the
products and services are reasonably (even
moderately)
high,
then
clearly
an
organization should have a presence;
otherwise, it is missing an opportunity to
inform and interact with its customers… If a
firm does not have a website, there is a risk
that potential customers, who are web savvy,
will flow to competitors who have a web
presence. Also, what is the information
intensity of a company’s products and
services?” (Watson, Zinkhan and Pitt, 2000).
Marketing then has to answer the question,
what web enabling technologies are geared
for their target market? The website must be
able to identify and target customer groups
and individuals, personalize and give
guidance in the buying process, use
innovative ways of packaging information
and services, such as video clips. Although,
the “marketing goal will be the same as ever:
deliver the right product to the right
customer at the right time,” (Kenny and
Marshall, 2000). The question then is what
new marketing models can be followed to
create an effective website.
The complexity and unstructured nature
of the problem-solving process for
addressing the above challenges and issues,
clearly indicate that an e-DSS is needed. The
e-DSS, like any DSS, would consist of the
following components: (a) the users, (b) the
user interface, (c) the model base, and (d) the
database. A brief review of DSS is provided
in the next section, which is followed by
sections
that
identify
the
detailed
requirements and contents of each of the
above
components
of
the
e-DSS
respectively.
3.
DSS BACKGROUND
Decision support systems (DSS) allow
people at many different levels to
systematically analyze problems before
making a decision (Turban 2001). In the
process, these systems extend the range and
capability of the decision-making process,
increasing its effectiveness. DSS are
especially useful in supporting semistructured and unstructured problems. DSS
are very different from traditional
information systems that are based on fixed
logic patterns and are mainly report
generators. In contrast, DSS are customized
management systems that support nonroutine decision-making and evaluation by
offering a variety of options to develop
various logic methodologies.
DSS are integrated multi-platform
system focused on specific decisions that
combines corporate data, models, and
interactive, user-friendly software into a
single powerful support system under user
control. DSS occupy a wide band in the
spectrum of data versus model-oriented
systems. DSS are always a combination of
both data and models, but one system will
differ in emphasis from another. The
interactive and user-friendly software in DSS
is designed to be as easy to use as possible. It
is geared primarily toward corporate users
who are not very computer-oriented. The
system does exactly as it is titled. Its function
is to provide decision support. It does not
make decisions for the user, nor does it
simply supply reports.
DSS assist managers in assessing the
future impact of current decisions. The
system provides this support by returning
results based on “what if?” questions, or
assumptions about future conditions.
Through an iterative process, a DSS can
provide the following types of information to
decision makers: (a) decision objectives or
criteria, (b) decision alternatives or
strategies, and (c) consequences of decision
alternatives. In deriving these results, the
process may be either model-oriented or
data-oriented. Model-oriented processes
make comparisons and perform analyses
based on an objective model. The model is a
coordinated set of parameters or conditions
and their relationships. Models usually are
derived from analysis of historical data and
trends. Data-oriented processes focus on
responses for specific inquiries and data
analysis. While models deal with sets of
conditions, data inquiries and data analysis
are concerned with specific questions.
4.
E-DSS USERS
The users of the e-DSS would include
but not limited to the following members:
strategic planners, VP of marketing
communications, project leader of web
development, marketing design team leader,
technical IS managers, programming leaders,
web server managers, and database
administrators. Other decision-makers that
might be involved would be project auditors,
human resource managers, enterprise
business application leaders who may need
large application integration to systems such
as Peoplesoft, Oracle Financials, SAP
systems, and procurement.
5. E-DSS USER INTERFACE
Given that the e-DSS itself is Internet
based, the user interface would have to be
very user friendly. The e-DSS would be a
true example of what a website might
ultimately provide (Conway and Koehler,
2000). The user interface must be “adaptable
to different users’ needs and communicate
consistent commands to the internal
components of the DSS,” (Hoffman and
Novak, 2000). In order for the user interface
to be adaptable, at the level mentioned
above, it must incorporate collaborative
technology capabilities and integration
facilities and additionally, be able to provide
each of the major user groups, specific
abilities and functions for them to carry out.
In order for the market planners to
generate ideas, that could use animation and
video clips, to facilitate marketing products,
the e-DSS must be able to display these
utilities in a general format so as to help
these market planners in the determination of
whether such technology might be included
in their own site. Data capturing samples
from web server logs, and agents or
algorithms should be provided to assess what
type of critical data must be captured for
marketing analysis. Additionally, the user
interface must allow the users to use the
models interactively, for example, use of
cost models must be web form based so that
variables could be easily inputted by
strategic decision makers; what-if scenarios
could be analyzed and saved for later
decision ranking by the user group.
Integration, for example, with MS FrontPage
and Netscape enterprise Web Server could
allow web designers and web programmers
to jointly create prototypes, then have the
group vote or rank website prototypes or
integration functions.
Collaborative
utilities
such
as
brainstorming engine and workflow engine
such as Action Technologies might be
integrated with project task applications and
vote and ranking process to facilitate the
decision-maker’s progress. Additionally, an
EDM system such as WebFileShare, where
“documents in an electronic form are
provided by a single repository (typically a
web server), only the current version needs
to be provided. Access can be restricted as is
required. Essentially, electronic document
management (EDM) system provide
information to decision-makers in a usable
format, much like an executive information
system,” (Turban, 2001). This would be ideal
for the formation of website strategic
planning,
proposals,
audits,
ranking
evaluations, and executive acceptance
documents. The user interface must also be
able to provide input to web models that are
within the model base.
6.
E-DSS MODEL BASE
It is increasingly becoming difficult for
organizations to adjust their business models
to accommodate emerging e-commerce
technologies that could potentially provide
sources for business opportunities. The eDSS model base would provide a
representation of models that organizations
would use to understand and analyze the
domain problems and their possible
solutions. In the model base, the models
would
include
traditional
strategic,
marketing, and IS models that have been
time-tested and proved to be effective such
as SWOT (strength, weakness, opportunity
and threat) analysis, CBB (customer buying
behavior), Systems Life Cycle analysis,
Feasibility analysis, decision tree analysis,
costing models, NPV analysis, ROI analysis,
etc. Additional models, obtained from
research literature, that are specific to
different aspects of the strategic planning of
e-commerce website development process
would also be included in the model base.
These models can be categorized, by the
major user groups’ involvement in the
decision process, into three categories:
strategic planning, marketing and IS.
6.1 Strategic planning models
Research was conducted to find new
strategic planning models that have a clear
focus towards expected costs, benefits or
expectations, and ability to narrow options
for developing e-commerce websites. Three
of the most critical strategic planning models
found are described below.
Larsen and Bloniarz (2000) developed a
model called “the cost-performance model,”
(see Figure 1), that is very insightful for the
purpose. This model consists of three tools.
“The first tool – the system features and
functionality worksheet – helps identify the
business goals a web service has to serve, as
well as the delivery mechanisms that will be
used to support the service (see Table 1).
This tool provides a framework for making
decisions supported by the model. The
second tool – called the performance
worksheet – identifies the important factors
defined through the first tool (see Table 2).
These factors are fleshed out as performance
variables, measures, and targets. The factors
give an organization a method for defining in
detail the goals of a service, as well as a
framework for measuring whether the
service meets these goals after its
implementation. The third tool – the cost
worksheet – helps address comprehensive set
of cost areas and calculates a rough estimate
of the system’s costs (see Table 3). Though
any one of the three tools can be used alone
or be customized to fit a specific
organization’s
process
of
system
development, the three together are
complementary, providing a comprehensive
perspective of the planned system,” (Larsen
and Bloniarz, 2000).
The decision-makers, using this model,
could then look at the cost and benefits
analysis, or use a more formal project cost or
resource
allocation
methods,
or
a
combination
of
traditional
project
evaluations such as multiple attribute utility
models. Advantages of this model was that it
was simple and straightforward to
understand, and it also provided the
opportunity to organizations that were
considering expanding their websites with
additional services or upgrades or integration
with B2B functions and e-business
functionality. It captured the critical
information from the planner and gave a
detailed process of evaluation and use.
Fellenstein and Wood (2000) provide
two models for strategic planning. The
graphical representations of these models as
shown in Figures 2 and 3, help understand
where an organization might be and what
direction it wants its website development to
go. “The new business strategies” model
shows what critical factors such as human
resources, marketing, partnerships, and
knowledge acquisitions are required. The
“importance of the value chain” model
shows how multiple enterprises have
relationships
focused
on
integrating
information flows to exploit information and
knowledge for strategic business objectives.
It focuses on increasing value through
internal relations among firms. A dynamic
market configuration involves a marketmediated set of relations focused on
increasing flexibility and opportunity for
strategic business objectives (Gray, 2000). It
is interesting to see that all three strategic
models above greatly emphasize knowledge
and data management prior to and during the
operation of a website.
6.2 Marketing models
Extensive, new marketing models were
found
from
literature
for
website
development. Marketing on the web
emphasizes on seeing where revenue can be
developed. These new marketing models are
fundamentally designed to derive revenue
from new sources that have not been thought
of before. Examples of these models are:
New imaginative models that focus on
finding
innovative
combinations
for
advertising – like subscription fees,
transaction costs, and referral fees. Affiliate
models, use other websites to bring
customers to the organization’s site. Internet
realities models – focus on wide distribution
that can allow companies to keep customers,
suppliers, and personnel informed of latest
changes, thereby lowering costs and
improving customer satisfaction. E-branding
market models – focus on branding strategies
to immerse customers in an experience that
can reinforce and amplify the organization’s
brand thereby securing repeat customers to
their website.
Another useful marketing model, called
I2 M (see Figure 4), provides a detailed
structured approach of determining what
types of companies would be effective in
using the Internet for coordination of their
planned marketing strategy. The model
defines using a grid, what types of industries
should be using the Internet as a tool, using
two parameters: proportion of customers
with web access, and information content of
product. Organizations that fall on the topright quadrant are prime candidates because
many of their customers have Internet access
and their products have a high-information
content. Whereas, firms falling on the other
quadrants, particularly on the low-small
quadrant, have less need to invest in ecommerce websites (Watson, Zinkhan and
Pitt, 2000). More importantly, this model
provides a matrix (I2 M Matrix) which
matches appropriate web technologies such
as search engines, audio, video, FTP,
NewWire, VR, etc., with important market
attributes such as atmospherics (retail
environment), personalization experience,
advertising, culture and news. This enables
organizations to promote differentiation,
develop new markets, create one-to-one
customized interaction, facilitate product
development, diversify new products to new
markets, and be continuously innovative.
6.3 Information systems models
Information systems models for ecommerce website development focus on
project management, web performance,
network traffic pricing for high availability
and security. Technology assessments models
provide project management in comparing
technologies by having host and control
projects. This is similar to having
production, quality, and development regions
for moving new technologies such as
middleware, upgrades, and patches to
production systems. Congestion is a problem
for web performance and therefore, is a
critical factor in each of the web
development phases. Capacity planning
encompasses many models such as
workload, prediction, and performance
models. Experts have developed probability
density functions, mathematical structures by
the use of fractal models, and LRU stack
models to characterize workload. The
technology of proxy servers has been derived
from many expert studies (see Figure 5),
where caching has proven to be very costeffective because of its ability of adjusting
the rate at which files are pre-fetched, and of
minimizing the network load (Menasce,
2000). Predicting web performance can be
done through simulation models where web
server transactions, requests, and load testing
are mocked. Also, there are analytical
models, which encompass formulas and
algorithms that can relate server and work
load parameters.
The QN (queuing network) models are
important models to understand and use for
making informed decisions on sizing web
servers and the underlining infrastructures.
“QN models represent each resource by
a queue composed of the resource and a
waiting queue for the resource. A request
may visit a given resource more than once
during its execution. For example, an HTTP
request may require several I/O operations
on a given disk. The total time spent by a
request obtaining service from a resource is
called the service demand. Service demands
do not include any queuing and constitute
one of the important types of input
parameters to QN models. In queuing
network terminology, the entity that flows
from one network terminology, the entity
that flows from one queue to another is a
customer. Customers may represent HTTP
requests, database transactions, and remote
file service request. A customer is the model
representation of the workload unit of work.
Since a system may contain many different
types of workloads contending for resources,
a QN model may contain many different
classes of customers. For example, different
classes of customers in a QN may model
requests for small text documents and large
image files store at a web server since they
represent substantially different usage of
server and network resources,” (Ince, 2000).
These models provide critical insights
that become useful in making decisions
regarding
network
topology
interconnections, proxy servers (see Figure
6), and the needed infrastructure of servers,
routers, and LANs for optimal performance
of a website.
Network management and pricing
models are available in the areas of taxation
policy, resource allocation, and competitive
advantage, mainly because different parts of
a network are owned by different entities and
at any given time a customer’s transaction or
request travels through multiple networked
infrastructures. The idea of QOS (quality of
service) models have come into play in web
services, by providing different customers
with their request rates of network service
class or performance level. For example, in
this model a customer who pays for higher
class gets to have a priority in transmission
than other service classes. Interestingly, this
model was proved by simulation, and it
showed that significant performance
enhancement and monetary benefits can be
achieved by using dynamic prices as
compared to the two other standard pricing
approaches: fixed charges and time based
charges (Gupta, Stahl and Whinston, 1999).
Models like QOS are needed in the model
base to study and understand possible future
directions of network management pricing
policies.
Web design is extremely critical for any
website. Web programmer models that are
currently available are geared more toward
what not to do and what principles to follow.
A model called TAM (technology
acceptance model), which has been
validated, shows the perceived usefulness,
perceived ease of use, perceived attitude
towards use, and behavioral intention of use
of an IS system, could be very useful
(Lederer, Maupin, Sena and Zhuang, 2000).
The IS group often has to find answer to the
question, what makes a website useful and
easy to use? Eight critical principles such as
speaking the user’s language, consistency,
minimization of the user’s memory load,
flexibility and efficiency of use, aesthetics
and minimalist design, chunking, progressive
levels of detail, and navigational feedback,
used in the TAM model, are needed in a
website’s ability to make it more useful and
easy to use. Understanding the culture of the
audience is also critical but there were no
specific models found in this area.
Use of new web intelligent agents is
important for IS to understand and be able to
apply. The website must have many different
agents that are able to work anonymously
and collaboratively to provide both what
marketing wants as one-to-one and
customized web serving personalization.
“The personalized, continuously-running
autonomous nature of agents make them
well-suited for mediating those consumer
behaviors involving information filtering and
retrieval, personalized evaluations, complex
coordination and time-based interactions,”
(Guttman, Moukas and Maes, 1998). The
model, called “system architecture for
intelligent browsing on the web,” created by
Lai and Yang (2000) describes the use of
agents that IS developers can follow. Their
website system architecture (see Figure 7)
can provide insight into how agents can
capture and help the customer by enhancing
the experience as they are browsing on the
website. Specifically, it includes a DSS
within the agent itself and defines five
separate agents that could be used for
personalization.
Computer security, at all levels of IS, is
important and it is also difficult to determine
the legal level of security and the way in
which that level is to be achieved (Shaw,
1998). Most security procedures are varied
and can include a combination of algorithms
for encryptions such as the use of private key
or public key certifications that are used as
digital signatures to ensure privacy, use of
SSL (secure socket layer), integration with
EDI (electronic data interchange) and having
the intelligent agents provide negotiation
processing. The key to security is that each
organization must formulate a combination
and an objective plan that it would require
from file locking through the use of SSL
transmission. The idea of standardization of
security procedures has been greatly argued.
For example, the use of SET versus SSL.
SET uses “digital certificates to verify the
identity of both consumer and the merchant,”
(Demarais, 2000). Although, it requires
supporting APIs on both sides to work but
“with the backing of the two largest creditcard organizations, Visa and MasterCard,
SET is poised to become the standard means
for credit-card transactions via the Internet,”
(Stalling, 2000).
Rohm and Pernul (2000) have
developed the COPS security model. They
note, “users want to have integrated tools
guaranteeing privacy, security, and fair trade,
that are embedded in a legal system which
protects from criminal behavior and
technical failure. On the other hand, users,
especially suppliers, want to freely chose and
eventually change after sometime the market
structure in which they are trading their
digital goods.” This model can explain five
market players and the three common
practice market transactions of information
phase, negotiation phase and the execution
phase that would possibly provide security
solutions. The model focuses on four
components: (a) a framework of the designer
of a market transaction, (b) an execution
environment
for
specified
market
transactions, (c) different basic (trusted and
non-trusted) services in the network, and (d)
appropriate security mechanisms provided
through an API. Ideally the model should
have a method such as a workflow engine to
collaborate between the phases.
Each of the models that are mentioned
in this section will need specific data that
need to be collected, stored and used for
analysis by the e-DSS. Therefore, the next
section will focus on the database component
of the e-DSS. The database component must
have the ability to communicate with the
models, which will reside in the model base,
for providing the values of variables and
parameters in them for analysis.
7.
E-DSS DATA BASE
The data that will be required for
supporting the strategic planning of ecommerce website development can be
categorized into three main categories:
strategic planning data requirements,
marketing data requirements, and IS data
requirements. Strategic planning data would
mainly be internal data such as each of the
cost elements for the organization’s website.
This would consist of proposed and/or actual
cost of developing the web page process,
networking or Internet service provider,
security, business and management such as
accounting functions for the web project,
marketing budgets, overall IS middleware
components, IS project development,
maintenance, computer systems, and
outsourcing. Additionally, data from vendors
would also be required.
The required marketing data is extensive
compared to the other two categories mainly
due to the need for continuous data capture
related to the customers or target audience.
To be able to have a website that focuses and
redefines the marketing strategy, it will need
to “continue to acquire and analyze huge
volumes of information on millions of
consumers to enable delivery across multiple
channels,” (Powell, 2000). Intelligent agents
need to be used to collect both users’ profile
and site contents. The users’ profile would
contain background information such as web
user’s name, gender, preferences, location, email address, time of web surfing,
information about the process on what and
how a user followed the site path such as
transaction processing logs. The site
database would contain the site relationship
data, metadata about the site, and actual
contents of the site such as product content,
descriptions, prices, and inventory levels.
IS would also require up to date data on
different technology uses and methods.
Much of these data that will be needed by the
e-DSS would come from the web itself such
as from web performance logs, from web
servers, IP, router information from network
utilities to determine throughput, disk and
CPU usage.
Additionally, the e-DSS metadata and
data objects would also need to be stored.
The e-DSS would in itself need to be able to
store user profile information of its users
such
as
managerial
preferences.
Furthermore, metadata about the decision
making processes, ranking results, time laps
for each of the decision processes, version
control for integration to other packages or
middleware also need to be stored. Lastly,
the e-DSS should be able to store metadata
on what data was most used by the
organization in the decision-making sessions
by its different decision-makers.
In order to store and organize these vast
amounts of data, a data warehouse will be
necessary. A data warehouse is a
“centralized repository that must support
complex decision support queries at high
performance. A data warehouse typically
utilizes relational database technology due to
the
maturity
of
this
technology,”
(Rundensteiner, Koeller and Zhang, 2000). A
data warehouse such as an Oracle 8i RDMS
would have to be one of the core members of
the database component of the e-DSS.
“In data warehousing, data from
operational systems and other external
systems are periodically extracted and
transformed by data warehouse generation
tools and loaded into a data warehouse. After
extraction, the transformation process
includes the following activities: (1) filtering
the data to eliminate unnecessary details or
fields; (2) cleaning the data to remove
duplicate records, correct typographical
errors in strings, and add missing field
values; (3) converting and translating the
extracted operational data to the OLAP
database format; (4) consolidating and
aggregating the data from multiple sources;
and (5) loading the data into the data
warehouse,” (Bose and Sugumaran, 1999).
the investments. Clearly, a cohesive decision
support system, such as the e-DSS, can help
organizations start out with an effective
website and continuously use the system to
improve and integrate the website with new
technologies, partners, suppliers and
ultimately satisfy their stakeholders and
customers. This research analyzed the
requirements for creating the e-DSS.
Two of the most important abilities in
the warehouse should be OLAP (on-line
analytical processing) and data mining, both
of which allow decision-makers the ability to
structure the data for greater analysis and
findings that would not be possible
otherwise. OLAP is a utility that is tightly
integrated with a modern RDMS such as
Oracle 8i (Karpain and Myers, 2000). Data
mining would use intelligent agents, AI
technologies and possibly an expert system
module that will contain algorithms to
extract unknown relationships from within
the data warehouse, to help the decisionmaker. “The data mining tasks can involve
the discovery of association rules, sequential
patterns, pagesview clusters, user clusters or
any other pattern discovery method in a
website,” (Mobasher, Cooley and Srivastava,
2000). Both OLAP and data mining abilities
require mass preprocessing tasks; however,
they are increasingly becoming very
important in web environment for providing
problem-solving capabilities such as the ones
identified for the e-DSS.
To construct a successful e-DSS for
planning e-commerce website development
for an organization, there are several
implementation steps which need to be
addressed. These steps include: (a)
evaluating the needs, (b) examining the
technology and process capabilities, (c)
assessing the website security requirements,
and (d) determining the related hardware and
software. The research findings provided the
specifications for these steps for each of the
e-DSS components, which included the user
interface, model base and database. These
findings should be of immense help to the
information technology managers and
professionals
who
are
considering
construction of such a DSS for their
organization.
8. CONCLUSION
Why do some e-commerce websites
deliver real benefits to both buyers and
suppliers while others struggle to establish
their “offerings?” Because an organization
needs to have a strategic plan for ecommerce website development that is in
line with its business strategy before it makes
More research must be done to
incorporate all areas of business that should
participate in creating an effective strategic
plan for e-commerce website development,
that is integrated with the organization’s
business
strategy.
For
example,
incorporating HR (human resource) for
allocating the core competencies skills,
supply chain model dynamics and the new
CRM (customer relationship management)
models. Another important area of research
will be analyzing the dynamics of B2B and
how partnership models can impact website
development. Research should also be done
on how manufacturing relationships and web
mining technologies and EDI technologies
be integrated for capturing critical data.
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***
COST-PERFORMANCE MODEL
Figure 1: The cost-performance model
Table 1: Worksheet for system features and functionality.
Modest
Identification
System features
and functionality
Identification
Benefits and
Performance
Identificatio
n Costs
Who are your customers?
What information-based
services will you provide?
How will customers get
access to these services?
What will customers be
able to do?
Modest
Moderate
What system features will
be included?
Elaborate
What information sources
(internal and external)
must be coordinated?
Benefit/Cost
Multiple Attribute
Analysis
Utility Model
Resource
Allocation
Method
Decision
Source: Larsen, K.A and Bloniarz, P. ./ Cost Performance Model
What security and
confidentiality measures
must be implemented?
What activities will be
outsourced?
Moderate
Elaborate
Cost-Performance Worksheet
Table 2: Cost Worksheet
MODEST
First Year
Cost
Organizational Readiness
Training for Technology Awareness
Planning for Internet Presence
1
2
Access for Staff and Other Users
Hardware for End Users
Software for End Users
Network and Internet Access for End Users
Other Vendor Services
3
4
5
6
Human Resources
Start-up Process for Equipment Procurement
Establish and Manage Vendor and ISP Contracts
7
8
Content Development and Maintenance
Hardware for Content Developers
Software for Content Developers
Network and Internet Access for Content Developers
Other Vendor Services
14
15
16
17
Human Resources
Start-up Process for Equipment Procurement
Establish and Manage Vendor Contracts
Development and Delivery of Staff Training
Staff Time in Training
Webmaster
Editorial Review
Content Creation and Coordination
Web Site Design and Development
Staff Support for Service
Programming Support
Database Administration
18
19
20
21
22
23
24
25
26
27
28
Subseq.
Annual
MODERATE
First Year
Cost
Subseq.
Annual
ELABORATE
First Year
Cost
Subseq.
Annual
Table 3:
Cost-Performance Form
Host of Site Infrastructure
Hardware
Software
Network and Internet Access
Other Vendor Services
Human Resources
Front-end Research and Technical Evaluation
Start-up Process for Equipment Procurement
Establish and Manage Vendor and ISP Contracts
Development and Delivery of Staff Training
Staff Time in Training
Network and Systems Administration
Web Server Management
Operations Support
Clerical Support
INFRASTRUCTURE AND OTHER SUBTOTAL
HUMAN RESOURCES SUBTOTAL
TOTAL COSTS
31
32
33
34
35
36
37
38
39
40
41
42
43
New Business
Strategies
Interacting with Consumers
Across
Enterprises
BTB Commerce
Manage Multifirm Value
Nets
Sense & Responds
Behavior
Within the
Enterprise
Develop Strong
Brands
Build &
Manage Core
Competencies
Extranet
Enterprise
Intranet
Enterprise
Knowledge
Figure 2:
Micro Market
Mass Custom
Management
Materials
Data
Finance
Process
Supplier
Information
Trading
Partners
Customer
Figure 3:
Marketing
Distribution
Figure 4:
Internet Presence Grid With Illustrative Examples
Information content of products
Low
High
Large
Proportion
of
Customers
with Web
Access
Office
Supplies
Industrial
Products
Food and
Beverages
Consumer
Electronics
Small
Figure 5:
An Intranet with a Proxy Server: Menasce
Proxy
Server
External
Web
Servers
router
Internet
LAN (10 MBps Ethernet)
Figure 6:
QN Model Corresponding to the Intranet: Menasce
Clients
LAN
router
outgoing link
ISP
Internet
web server
cpu
cpu
disk
proxy cache server
incoming
link