Agent-based micro-simulation of business establishments

This paper describes the development and testing of a microsimulation of the evolution of individual ''business establishments'' (BEs) in an economy. The work is part of a larger program of research and development of a model of all the transportation and land development processes in an entire spatial economic system. The simulation uses comparatively simple, yet behavioural, rules and probabilistic models, using a Monte Carlo process to simulate behaviour from the probabilistic models. A BE is described primarily by its business transactions - its purchases and sales of standard commodity categories, called its "consumption function" and "production function" respectively. Make and Use tables from traditional input-output models are used to determine these relationships for a particular industry, and individual BEs randomly vary around the industry average. Labour, floorspace and final demand are included as commodities, to bind the BEs to a given built form in a spatial system and to the patterns of population. Thus a BE is described in terms of how big it is, and its "technical coefficients" describing what it purchases and sells. The market for each commodity type is spatially disaggregated, and BEs in a given location can sell or purchase their commodities in a variety of different "exchange zones" that they are willing to ship goods or services from or to. Prices at exchange zones are adjusted over time so that, if the system is allowed to reach equilibrium, the market for each commodity in each exchange will be cleared. The BE''s market choice model is used to develop measures of the attractiveness of selling or purchasing commodities when located in a zone. These measures of commodity attractiveness are used with the production function and consumption function to determine how attractive a location is for a given BE and how well it is performing. A BE''s growth (positive and negative) and its probability of bankruptcy (death) are based on the measure of location attractiveness. Relocation pressures are based on the measure of location attractiveness, as well as a composite measure of the attractiveness of all other zones in the system and the (fixed) attractiveness of leaving the model region entirely. Relocating BEs vacate floorspace in a particular physical location (a "grid cell") and then, if necessary, acquire new floorspace in a grid cell in a different zone. As a successful BE grows it is increasingly likely to split into two separate BEs, either as a duplication of function into another location, or a separation of business functions into separate locations. In addition, entrepreneurial business ideas are set up as "Proto BEs", which are business ideas that are being evaluated in any one year. A "Proto BE" that is in an attractive location in one year is likely to become an actual BE in the next year. Within each zone, the land is represented as "grid cells", which are finite quantities of land with a particular type and quantity of floorspace and a particular building age. The prices for each floorspace type in each zone, along with the age, type and quantity of floorspace in each grid cell, are used to calculate the probability that the land owner will choose to undertake development, redevelopment, renovation or demolition in the grid cell. The test system is represented using a 10x10 system of zones and a network of transport connecting the zones with reasonable travel times and costs. This system is used to test the role of the various parameters, to determine reasonable values for the parameters, how the model behaves when parameter values are unreasonable, and how each parameter influences the model system. A set of "policy input" scenarios are also developed, to show how the modelling system can be used to test the policy response. These include decreased development costs, increased travel costs and changed land-use zoning regulations.