City Development: Basic Model

Purpose:

To study the pattern of development of different areas of cities.

Origin:

Triggered by a lack of understanding of why city center areas in Indian cities tend to deterioriate in standards of living, traffic, pollution, aesthetic sense, etc. whereas that is not the case in countries like the USA.

In the US one can look at a city from afar and say which part is the center of the city. They usually have the swankiest buildings, highest land prices, most number of corporate offices and is the cleanest part of the city.

In India however the center of the city does have the highest land prices, many corporate offices, it is mostly the dirtiest part of the city, has a very poor traffic/pollution/congestion rating and the worst in terms of aesthetic sense, swankier buildings, etc. It usually contains the oldest buildings in the city which do not undergo enough redevelopment.

My suspicion is that the cause of this is the following aspects:

• Development and redevelopment policies of the municipalities
• Large undeveloped tracts of land in the outskirts of the city that make development of these lands still cheaper than redevelopment of existing city land. Obviously this includes peoples willingness to shift to such outskirts.

Overview:

Consider a square city with perfectly square 'wards' on a 10 x 10 matrix. Each ward will have a 'popularity' and a 'cost'. The city has 10 retailers who operate 10 shops each. Each retailer has a 'weight' being the effect of a retailer on the popularity in the ward. Each retailer tends to spread his outlets a bit so will not operate more than one outlet in one ward. Each ward can house a total of 5 outlets.

Definitions:

Absolute Popularity: The popularity of a ward measured as a decimal value. It is an absolute popularity and not a relative one. By definition the ward that has the highest popularity in a city is called the city center

Popularity Function: It is the function that calculates an absolute popularity based on different parameters. The potential parameters that can be used in this function are:

1. Retail Outlets Count: The number of retail outlets in this ward
2. Retailer weight: The weight of the retailers who have retail outlets in this ward
3. Retail Outlets Age: The age of the retail outlets in this ward
4. Time: The passing of time may have effect on the popularity simulating new generations of people associating themselves more with other wards than this ward.

Relative Popularity: Popularity of a ward relative to all wards in the city. It will be measured as a relative value ranging between 0-10. 10 being the most popular and 0 being the least. By definition the ward with 10 popularity is the city center.

Cost: An average land cost of the ward. This value will vary based on popularity and time variable.

Cost Function: The function that calculates the Cost of a ward. This can be based on the following potential factors:

1. Popularity: The cost will be based on the popularity of the ward
2. Popularity Time series: The cost may be based on the average popularity over some period of time in history.
3. Number of available retail outlets: The number of retail outlets available to be purchased
4. Time: As a function of time the cost could slowly inflate to display real estate growth.

Time: This is the variable to represent the passing of time. It will basically be the incrementing count of rounds that the simulation is played out.

Purchase Decision: This is the function of the simulation that will determine whether or not a retailer will shift an existing store in one ward to another ward. The return value of this function will be boolean signifying a "yes shift" or a "no don't shift" decision. There are several factors that will affect the retailer's purchase decision:

1. Popularity of new ward vs current: Tendency to move to a more popular ward than current.
2. Cost of new ward vs current: Tendency to move to a less costly ward than current.
3. Total Cost Portfolio of stores: Total Cost of all stores of the retailer.
4. Total Popularity Portfolio of stores: Total Popularity portfolio of stores.

Initial setup:

1. Setup the city with popularities in such a manner as having a maxima at the 8th row, 8th column and falling linearly in all directions
2. Setup retailers having weights in linear fashion from 1-10
3. Randomize store ownership all over the city.