PROJECT DESCRIPTION

Buying an appropriate laptop could sometimes be a hard decision for many people because several decision factors get involved in the decision making process. This problem inspires our team to develop an innovative decision support system providing laptop buyers with a short list of recommended laptop models retrieved from the laptop database, which can be updated as often as needed, resulting in the extensible and flexible decision support system.

PROJECT OBJECTIVE

The main project objective is to develop a decision support system that can help laptop buyers decide which laptop models to buy based on their budget, preferences and intended uses.

System Input
Personal preferences and laptop data are two system main inputs. In the beginning, several kinds of questions are used to identify personal preferences, which will be then interpreted as a set of desired computer specification. For example, an intense gamer then DSS would interpret that a suitable laptop should have a good 3D accelerator and a high-speed CPU. Another example is if a regular programmer wants to buy a laptop, then the DSS will interpret that the user requires a high-memory laptop. To solidify this kind of information, we created an analytical model in Excel before passing the information to DSS.

Core Decision Model (developed by GENIE)

Our team brainstormed and developed a decision model where three main aspects are taken into consideration: tangible aspect (i.e., computer specification), intangible aspect (e.g., brand reputation, warranty information, custom service, reliability), and price satisfaction (user's budget).

User activities are the key to define the tangible expected value for each laptop component. For example, if the activities require intensive calculation, a laptop with higher CPU tend to get a higher score. All components then pass the values to the Tangible Expected Value (EV) node to aggregate the overall tangible expected value for each laptop.

To calculate the intangible value, our team rely on both the model reviews (available on the Internet) and the user's preferences. The model reviews can be obtained from various sources such as consumer review websites, computer magazines, and laptop buying guides while the user's preference bases on the information from the input page. For example, if the user values the brand reputation and the customer service of a particular brand, the system will give more weight on brands offering great customer service.

After all the laptops receive the assigned values, the laptop price is the last determinant to screen out the laptops that the price goes beyond specified budget. At the end, the laptop with a higher value is shown at the top in the list, indicating the greatest match to users' needs.

System Output

A list of three recommended laptops with their specification and price is presented as a DSS output, which is ordered by the greatest match to the interpreted needs of the user (obtained from the input page). Hyperlinks to the manufacture webpage of each particular model are available for users to find more about laptop features, laptop apperance and detailed technical information and how to purchase.

PROJECT CONTRIBUTION

Researching; Decision Modeling; User Interface Design; Documentation

PROJECT CREDITS

Team Member: Jaruwan Laptrakool, Korporn Panyim, Warat Chesdavanijkul

PROJECT ARTIFACTS

Final Report

Final Presentation