Web-Based Decision Support System Case Study:
Your client is developing a marketing feasibility study for an ocean-front high-rise condominium project in Boston’s South Shore. The current real estate climate in Boston is very risky. Prices per square foot for condominiums are at an all time high. There has been a significant downturn in the economy which may or may not be reflected in future real estate prices.
The proposed building will have 5 floors with an identical distribution of 1 and 3 bedroom model units on each floor. On each floor there will be 4 of each type of model. The selling price per square foot will vary depending on the model type and the view (higher models will command an increment of $x per square foot for each floor).
The analysis of this project is complicated by the present uncertainty of the New England property market. A project of this size might take 12-24 months to sell out. Your job is to design and develop a decision support system which will simulate optimistic, pessimistic, and most likely revenues to determine whether the project is viable. You can make your own assumptions about the cost of building the project. Your DSS will focus on expected revenues rather than costs.
Your design should enable sensitivity analysis on price per square foot, sales (do units on upper floors sell before cheaper units on lower floor, or do large units sell before small units), and monthly price changes on unsold units. You may have to make a number of simplifying assumptions in your design. Document these assumptions and indicate what effect they are likely to have on the believability of your decision support system.
there is an example attached, thanks.
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