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)RUWKLVVSHFL¿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 WKHPRGHOVSHFL¿FDWLRQDQGVWUDWHJ\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, HGLWLQJRUTXHU\LQJRIGDWD¿OHVRUWKHFUHDWLRQ 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¿JXUHLVDQDGDSWDWLRQRI)RUJLRQQH¶VZRUNSS 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- PHQWDWLRQUHVXOWVLQRUGHUWRHVWDEOLVKVDWLV¿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 ), WKHDXWKRUVVSHFL¿HGWKHPRGHOIRUWZRUHODWHG EXWGLIIHUHQWHEXVLQHVVDSSOLFDWLRQV,QWKH¿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$OVRWKHVHUHVXOWVIXUWKHUFRQ¿UPHGRXU belief that the e-business strategy model follows the essential general business principles that do QRWFKDQJHRYHUWLPH,WLVPDLQO\WKHVSHFL¿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’ ¿UVWHPSLULFDOVWXG\ 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 GHYHORSPHQWZLWKRXWPXFKGLI¿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 RQWKLVSDJH,Q)LJXUHDIWHUDXVHUVSHFL¿HVD 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\LQRUGHUWRHYDOXDWHSROLFLHVDXVHU ¿UVWHQWHUVDVFHQDULRLQ)LJXUHKHRUVKHWKHQ clicks the TEST button to go to the Solutions Test Report window (Figure 5) to see the resulting YDULDEOHVDQGYDOXHVLQWKH¿UVWURZRIWKHWDEOHLQ 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 HQGRJHQRXVYDULDEOHVHJSUR¿WWRWDOFRVWDQG 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 ZLOOEHFRPHWRRORQJWR¿WLQWRRQHVFUHHQDQGLW 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¿UVWLVFDOOHGVFHQDULRWKHRQHHQWHUHG 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[WRFRPSDUH$IWHUVHOHFWLQJDYDULDEOH3UR¿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 SURGXFHVWKHKLJKHVWSUR¿WZKLOHVFHQDULR JHQHUDWHVWKHORZHVWSUR¿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 HEXVLQHVV VLWXDWLRQ RWKHU e-business strategy evaluation applications also can employ the same simulation methodology and the major system functions and features proposed here with WKHJHQHUDO HFRQRPHWULFPRGHOEHLQJ VSHFL¿HG and some system requirements being adjusted accordingly. DISCUSSION The current stage of this research focuses mainly RQ¿QGLQJDQGHVWDEOLVKLQJDWRROIRUe-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 ZLWKKLJKHUHI¿FLHQF\DQGORZHUFRVWV1H[WLQWKLV 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 DPRQJWKH¿UVWDWWHPSWVLQWKHHEXVLQHVV¿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 DQGLQIRUPDWLYHPDQQHU$VSHFL¿FH[DPSOHLV SURYLGHGLQWKH³(FRQRPHWULF6LPXODWLRQWKURXJK 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. 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Hershey, PA: Idea Group Publishing. . 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. evaluation applications also can employ the same simulation methodology and the major system functions and features proposed here with WKHJHQHUDO HFRQRPHWULFPRGHOEHLQJ VSHFL¿HG and some. validation, and potential revisions. Next, the EBSP system needs to be developed fully, and the concept can be extended WRRWKHU¿HOGV)LQDOOIXUWKHUH[SHULPHQWDWLRQ validation, and analysis