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To model the best place to live, there would be a database of top 150 cities based on population and attractions (150 is just a recommended cut-off). These cities are then divide into three categories such as large cities, medium cities, and small cities with a population range for each category, in which CNN did not take city size into consideration. The database will then have standard characteristics that are assigned to each city such as types of attractions: trout fishing, surfing, American battleground, Indian reservation, and attractions as such. In addition, other city characteristics such as climate, unemployment level, affordable housing, architectural styles, proximity to certain landmarks, and number of businesses' corporate headquarters are taken into consideration. The user will choose what factors are important to them, and the places with the most matches will show up as the best places to live. Also, the user can choose points on a map, where the decision support system can calculate the center of gravity and match the closest top-city as the best place to live. This DSS should also have current or real-time data since cities are constantly growing and changing.
This DSS can help individuals each time they want to relocate. Relocation is due to many reasons: college graduation, divorce, career change, or other reason.
ReferencesMoney Magazine's Best Places to Live. CNNmoney.com. Retrieved April 9, 2008 from http://money.cnn.com/magazines/moneymag/bplive/2007/top100/
1 comment:
Unfortunately, I could not find the original article. But, I was intrigued by the issues you recommended taking into consideration, and your critique of the items they took into consideration. I find that younger people are concerned with "things to do" where as new parents are concerned with living environment and schools, and older people are concerned with safety and affordability. Perhaps should the model differentiate by age group? Or some measure of lifestyle?
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