714
Econometric Simulation for E-Business Strategy Evaluation
is adapted as a general guidance for the system
development.
Forgionne’s (2000) architecture delineates the
major inputs, processing, and outputs of a general
DMSS. It can be tailored for different research
VLWXDWLRQV)RUJLRQQH)RUWKLVVSHFL¿F
research, the diagram (Forgionne, 2000) suggests
that the targeted system mainly should contain the
following functions in order to simulate e-business
strategy and make recommendations:
a. A data management function that can gather
strategy relevant data,
b. A model management function that can dy
-
namically operationalize the model with the
related data and use the operational model
to help evaluate strategy, and
c. A dialog management function that plays
as an interface between the system and a
decision maker.
For different systems, the data and dialog (or
interface) management functional parts can be
exactly the same. What makes different systems
unique is the model(s) in the model management
component. As a result, this research focuses on
WKHPRGHOVSHFL¿FDWLRQDQGVWUDWHJ\HYDOXDWLRQ
functions. The development of data and dialog
management components will follow the general
practices and will not be explained in detail.

Guided by these considerations and following
the general architecture, Figure 2 presents a
basic structure for the targeted DMSS of this
research.
As seen in Figure 2, the system mainly will
have three modules: Data Management, Model
Management, and Forecast. The Data Manage-
ment module allows the examination (viewing,
HGLWLQJRUTXHU\LQJRIGDWD¿OHVRUWKHFUHDWLRQ
of new data for model estimation or policy evalu-
ation purposes. The Model Management module
Feedback
Mechanism
E-Business Management
INPUTS PROCESSES OUTPUTS
Information Technology
Data Component
Problem relevant
dt
Model Component
Problem related
models and
methods
Manage relevant
problem data
Operationalize the
specified model(s)
Simulate and
evaluate strategies
for best solutions

Status report s and
p
arameter estimates
Evaluation and
forecast resul ts
Recommendations
and explanations
Feedback Mechanism
Figure 1. Adapted DMSS Architecture*
7KLV¿JXUHLVDQDGDSWDWLRQRI)RUJLRQQH¶VZRUNSS
715
Econometric Simulation for E-Business Strategy Evaluation
allows the dynamic model estimation and updat-
ing capabilities. The Forecast module enables
strategy evaluation with an operational model
provided by the Model Management module.
The Forecast module is separated from the model
management function, as suggested by Figure 1,
and will perform the major simulation function
of the system.
Validation, Experimentation,
and Data Analysis
After a computer program has been developed
for the DMSS, which delivers the operational
model(s), the authors will validate the program,
evaluate system performance, implement strategy
evaluation experimentations through the valid
system, and compare and analyze the experi-
PHQWDWLRQUHVXOWVLQRUGHUWRHVWDEOLVKVDWLV¿HG
strategies.

ECONOMETRIC SIMULATION
THROUGH A DMSS
In order to simulate strategy-making processes,
the general econometric model (equations (1)-(10))
established in the authors’ prior work needs to be
operationalized empirically. In two independent
empirical studies (described in detail elsewhere
2
),
WKHDXWKRUVVSHFL¿HGWKHPRGHOIRUWZRUHODWHG
EXWGLIIHUHQWHEXVLQHVVDSSOLFDWLRQV,QWKH¿UVW
study (Ha & Forgionne, 2004), the authors col-
lect online auction data across different sellers
for one manufacturer’s products and estimate the
model for this manufacturer’s e-auction strategy
development situation. In the second study (Ha
& Forgionne, 2005),
2
the authors still use the
same online business Web site, but data are col-
lected for one seller across different products and
across two different Internet channels used by
the selected seller.
The two independent studies used different
data at different time periods based on one opera-
tional e-business Web site, and they both validate
the general model for their corresponding situa-
DMSS for E-Business Strategy
Evaluation
Data

Management
Examine
current data
Create new
data
Forecast
Test and
evaluate
different
strategies
Model
Management
Organize
model
paramete rs
Estimate
and validate
the model
Figure 2. System structure for econometric simulation
716
Econometric Simulation for E-Business Strategy Evaluation
WLRQV$OVRWKHVHUHVXOWVIXUWKHUFRQ¿UPHGRXU
belief that the e-business strategy model follows
the essential general business principles that do
QRWFKDQJHRYHUWLPH,WLVPDLQO\WKHVSHFL¿FD-
tion of the model variables that differentiates
e-business strategy from its traditional business
counterpart.
Since the detailed empirical studies are pre-
sented as separate studies, this article does not list

the details (the data and statistical analysis results
of the two studies are available upon request). Once
the general model is operationalized empirically,
the simulation logic presented by this article can
c o m e i n t o p l ay b y d e l i ve r i n g a n o p e r a t i o n a l m o d e l
through a DMSS to e-business management for
strategy evaluation purposes. This section em-
ploys the operational model from the authors’
¿UVWHPSLULFDOVWXG\
2
(Ha & Forgionne, 2004) in
order to illustrate the proposed simulation ap-
proach. The details in this section are based on
one author’s dissertation.
2
The computer program, a DMSS, as discussed
during the methodology, developed for the selected
e-auction strategy development application
2
(Ha
& Forgionne, 2004) is named E-Business Strat-
egy Planner (EBSP). The authors developed this
system based on Forgionne’s (2000) architecture
and Figure 2 with the SAS
3
software system,
mainly the SAS/AF and SAS/ETS modules. For
further information, please see the SAS
3
help

and some SUGI
4
papers (Davis, 1998; Imken &
Wilson, 2003; Phan, 1999; Wilson, 2000, 2001).
SAS is used here due to its powerful development
environment, which can integrate data generation,
model estimation and forecast, and application
GHYHORSPHQWZLWKRXWPXFKGLI¿FXOW\
First, after a user chooses to use the system
on the system welcome page, the Main System
Functions screen (Figure 3) will come up.
ORGANIZE INFORMATION, DEFINE THE
PROBLEM, and TEST SOLUTIONS are the
three main functions of the system. Compared
with Figure 2, the ORGANIZE INFORMATION
function corresponds to the Data Management
module, the DEFINE THE PROBLEM function
corresponds to the Model Management module,
Figure 3. System main page
717
Econometric Simulation for E-Business Strategy Evaluation
and the TEST SOLUTIONS function represents
the Forecast module.
When the TEST SOLUTIONS button on the
system main page (Figure 3) is clicked, the So-
lutions Test page (Figure 4) will be shown. This
Solutions Test page enables a user to evaluate
policies with the system using an operational
model at the back end.
The table in Figure 4 contains a list of exog-

enous variables with their default values. This
group of values forms a scenario. What a user
needs to do is to select the certain values and
change them to their desired ones. When a user
wants to resume the system defaults, he or she
can click the RESET button. The Help button on
the screen provides context-related information,
the detailed explanations for the listed variables
RQWKLVSDJH,Q)LJXUHDIWHUDXVHUVSHFL¿HVD
scenario, clicking on the TEST button will take
him or her to a Solutions Test Report window
(Figure 5) to see the resulting endogenous vari-
ables. The system simulates the values of the
endogenous variables through utilizing the model
at the back end.
The table in Figure 5 lists the test results. The
number of rows in this table equals the number of
scenarios a user has tested, and each row shows
the results of one corresponding scenario. More
VSHFL¿FDOO\LQRUGHUWRHYDOXDWHSROLFLHVDXVHU
¿UVWHQWHUVDVFHQDULRLQ)LJXUHKHRUVKHWKHQ
clicks the TEST button to go to the Solutions Test
Report window (Figure 5) to see the resulting
YDULDEOHVDQGYDOXHVLQWKH¿UVWURZRIWKHWDEOHLQ
Figure 5. If this user decides to test more scenarios
before developing strategy, clicking the SENSI-
TIVITY ANALYSIS button on the Solutions Test
Report page (Figure 5) will navigate him or her
back to the Solutions Test page in Figure 4 in order
to enter and test another scenario, and so forth.

In the example of Figure 5, the table shows the
testing results of 11 scenarios. On the Solutions
Test Report window (Figure 5), the PRINT and
Figure 4. Solutions test page
718
Econometric Simulation for E-Business Strategy Evaluation
SAVE buttons give users a choice to print or to
save their reports.
The report in Figure 5 shows a user the outcome
HQGRJHQRXVYDULDEOHVHJSUR¿WWRWDOFRVWDQG
revenue) of different scenarios tested by him or
her. When users test many scenarios (e.g., more
than 10 scenarios, as in Figure 5), the results table
ZLOOEHFRPHWRRORQJWR¿WLQWRRQHVFUHHQDQGLW
will be hard for a user to compare those results and
to pick the most desired scenario(s). As a result,
a GRAPHIC COMPARISON button is included
in Figure 5 to allow graphical comparison of the
outcomes of different scenarios. If a user clicks
the GRAPHIC COMPARISON button, a Graphic
Comparison page will show up.
In Figure 6, the list box on the left lists the
scenarios that the user has entered (the scenario
HQWHUHG¿UVWLVFDOOHGVFHQDULRWKHRQHHQWHUHG
second is called scenario 2, and so on). A user
may select several scenarios at a time to compare
(also, users always can come back to this page to
do more comparisons). For example, in Figure 6,
scenarios 2, 3, 4, 7, 8, and 9 have been selected,
and then, the VIEW button should be clicked to be

able to do the comparison. With the VIEW button
being clicked, the system will get to the screen,
Graphic Comparison View, in Figure 7.
In Figure 7, the table shows the details of the
selected scenarios (scenarios 2, 3, 4, 7, 8, and 9
in this example). The scenarios contain the exog-
enous variables and their values that are entered
by the system user for evaluation purposes. In the
list box are the outcome variables (endogenous
variables or decision criteria) that are calculated
by the system given the user entered scenarios
and the model. While looking at the scenarios
that he or she has entered in the table, a user may
choose one result variable at a time from the list
ER[WRFRPSDUH$IWHUVHOHFWLQJDYDULDEOH3UR¿W
is selected in this example), click the COMPARE
button and a chart will appear to the right of the
list box, as in Figure 7.
With such a graphical representation (the
chart), the user easily can tell that scenario 9
SURGXFHVWKHKLJKHVWSUR¿WZKLOHVFHQDULR
JHQHUDWHVWKHORZHVWSUR¿W
The logic is the same for selecting other de-
cision criteria listed in the list box to compare.
Figure 5. Solutions test report page
719
Econometric Simulation for E-Business Strategy Evaluation
For future reference, a user also may print (by
clicking the PRINT button) the chart for each
comparison. With the support of these graphical

views and the solutions test reports (as shown in
Figure 5), a decision maker will be able to evalu-
ate different scenario(s) with multiple criteria and
decide the policies that will best satisfy his or her
organization’s goals.
The foregoing presents a system example
showing the major computer simulation process
of using an econometric model to evaluate the e-
auction strategy under different scenarios. Given
Figure 6. Graphic comparison page
Figure 7. Graphic comparison view
720
Econometric Simulation for E-Business Strategy Evaluation
the straightforward and user-friendly navigation
within the system, a decision maker can gain ef-
fective and timely support in manipulating busi-
ness data and in simulating e-business strategy
without much effort or complications. Although
this article presents only one example for one
VSHFL¿F HEXVLQHVV VLWXDWLRQ RWKHU e-business
strategy evaluation applications also can employ
the same simulation methodology and the major
system functions and features proposed here with
WKHJHQHUDO HFRQRPHWULFPRGHOEHLQJ VSHFL¿HG
and some system requirements being adjusted
accordingly.
DISCUSSION
The current stage of this research focuses mainly
RQ¿QGLQJDQGHVWDEOLVKLQJDWRROIRUe-business
strategy evaluation. Due to the nature of the prob-

lem situation, a simulation methodology, instead of
analytical tools, is applied. To implement simula-
tion and to experiment with different e-business
policies, the major issues include the selections
of a model and model delivery mechanism or
computer program to do experimentation with
the model. The previous sections of this article
present the major logics of simulating e-business
policies with a prototype DMSS, called EBSP,
that utilizes an econometric model at the back
end. The major lesson learned from this research
is that, in practice, it is the actual problem under
investigation that decides which model(s) or tool(s)
to use and not the reverse (Gass, 1985).
There are several limitations at this stage of
the study. First of all, the EBSP system has been
tested with many trials in order to see whether
it can provide consistent outputs with the inputs.
However, the validation, experimentation, and
outcome analysis of the simulation through the
EBSP system, which is a separate study, is incom-
plete at this stage and requires further testing and
evaluation. Then, the current system development
is tested with only one expert as a potential user;
the involvement of more e-business applications
will be a valuable addition to this project.
Next, the model management module of the
current EBSP system is not developed. For the
example presented in this article, the system
simulation is based on one operational model

for e-auction strategy evaluation; as new busi-
ness data become available, it is desirable for the
system to be able to manage and to estimate the
model dynamically. Finally, the data management
function of the system, which currently allows
viewing and editing of the selected historical
business data, can be enhanced further by allow-
ing additional capabilities like data mining. Also,
with further development, the data management
function should have the capability of providing
data for strategy evaluation. Users then will have
the choice either to specify the inputs themselves
or to use the data provided by the system for
forecast or evaluation objectives.
Although there are limitations with this study,
empowered by the prior research in the existing
literature, it establishes a comprehensive quan-
titative tool for e-business strategy evaluation.
0RUH VSHFL¿FDOO\ WKH PDMRU FRQWULEXWLRQV RI
this research are listed as follows. First, due to
the nature of the simulation approach, e-business
policies can be evaluated and tested in laboratories
ZLWKKLJKHUHI¿FLHQF\DQGORZHUFRVWV1H[WLQWKLV
Web-based world where everything is dynamic,
the proposed simulation approach that utilizes
an econometric model through a DMSS enables
an e-business manager to better evaluate market
conditions with up-to-date business data.
In addition, this research is based on long-
standing general business economics and other

general notions. However, the EBSP system that
utilizes the econometric model to simulate e-
business strategy is a new contribution to and is
DPRQJWKH¿UVWDWWHPSWVLQWKHHEXVLQHVV¿HOG
Finally, the development of a DMSS based on the
general DMSS architecture (Forgionne, 2000)
makes the future extension of the strategy evalu-
ation capabilities possible.
721
Econometric Simulation for E-Business Strategy Evaluation
CONCLUSION
How to establish effective and timely e-busi-
ness strategy becomes the critical factor for a
company to win and to secure a position in the
electronic marketplace. This article, together
with the authors’ other prior studies, is among
WKH ¿UVW DWWHPSWV WR LGHQWLI\ DQG WR HVWDEOLVK
a comprehensive, quantitative tool in order to
support the strategy development processes of
e-businesses. Employing the econometric model
from the authors’ previous related research (Ha &
Forgionne, 2004; Ha et al., 2003a, 2003b),
2
this ar-
ticle focuses mainly on delivering the econometric
model though a DMSS (EBSP system) in order to
help e-businesses to simulate and thus evaluate
and establish their strategies in an easy-to-do
DQGLQIRUPDWLYHPDQQHU$VSHFL¿FH[DPSOHLV
SURYLGHGLQWKH³(FRQRPHWULF6LPXODWLRQWKURXJK

A DMSS” section for this purpose.
To further the e-business strategy research, the
authors mainly will consider the following aspects
in the future. First, the econometric model, as a
major component of the strategy simulation, will
undergo further tests, validation, and potential
revisions. Next, the EBSP system needs to be
developed fully, and the concept can be extended
WRRWKHU¿HOGV)LQDOO\IXUWKHUH[SHULPHQWDWLRQ
validation, and analysis with the system are neces-
sary, and both the model and the system should
be tested in a broader scope of applications with
corresponding potential users.
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