To begin with, I needed to set up an analysis that favoured areas with the higest proportions of the target age, income, and sex ratios, that also took into account the cost to build on different land types and the distance from bus stops, skytrain stations, major roads, and other pubs. Furthermore, I considered the effect of aspect on business, and decided that as a constraint, I wanted a new pubs to face in a southerly direction.
Constraints:
1) Had to be situated on a south facing slope
2) Had to be situated on Open/Undeveloped, Residential-Townhouse, Lowrise/Highrise Appartments, Commercial, Residential/Commercial Mixed, or Industrial landuse types.
I decided on a south facing slope as a constraint so that people could dine out on a patio on nice days. Also, the landuse types listed above were the best ones for a new pub; open and undeveloped lands were cheapest, but high-density residential buildings were also viable for the large client base.
Factors:
1) Aspect
2) Landuse types
3) Distance from major road
4) Distance from a skytrain station
5) Distance from a bus stop
6) Distance from another pub
7) Roughly equal sex ratios
8) High proportion of individual income over $7,000
9)
High proportion of target age
For landuse types, different land uses offered different attractions, as mentioned previously. For aspect, the more it faced south, the better. I wanted a pub to be located near a major road so that people passing by would notice it and amybe stop by for lunch. I wanted it to be located near a Skytrain Station for people drinking at night, likewise for bus stops, although they had different suitabilities at different distances based on their services. Distance from another pub was key, as I will show later, pubs in Burnaby are located no more than 2 km apart, but most, with the expection of 1 pair, are closer than 100m; this factored in to my final analysis. Furthermore, I wanted sex ratios to be approximately the same, so that there would be a good chance that euqual proportions of the sexes would visit the pub. I wanted a high proportion of individual after-tax income over $7,000. The reason why this number is somewhat low is because, from my own experience,many university students make about this much. Additionally, i was looking mostly to attract people between the ages of 19-34; 15 years to make my analysis somewhat rounded, and this age bracket because they are most likely to go to pubs quite often.
Once this was established, I began building my analysis with the use of Macro Modeller; this is what the set up looked like:
Figure 1. How I set up my analysis.