Overview of the conceptual model

 Purpose of the Model

The purpose of the model is to simulate how urban spatial structure and mobility patterns co- evolve as a function of the interaction between the residential and job location choice behaviour of heterogeneous households and individuals in the urban property and job markets and existing urban structural conditions.

 Model Structure: sub-components, entities and variables

The overall structure of the conceptual model is illustrated in figure 6.1. The framework comprises six main interacting model sub-components. The entities, key variables and data required are outlined under each of the sub-components. In the sections that follow, a description of the individual sub-components of the framework is presented.

I. Spatio-environmental sub-component

The spatio-environmental sub-component represents the geographical context of the model. As shown in figure 6.1, this sub-component is divided into two main elements namely; the urban spatial or physical units of analysis and the urban functional attributes. The first elements comprise macro-level geo-spatial input data such the metropolitan boundary and existing administrative sub-divisions.

The conceptual model recognizes the need for further spatial differentiation beyond the administrative boundaries. Consequently, three broad urban-zones (𝑈_𝑍), of unique socio- spatial characteristics namely; Historical-core (𝑈_𝑍1), Inner-suburb (𝑈_𝑍2) and Outer-suburb (𝑈𝑍3) are identified as meso-scale spatial units for anchoring the model input data during implementation. The second element of the spatio-environmental sub-component is the urban functional attributes in the metropolitan context. Thus, at the implementation stage of the conceptual model, the spatio-environmental sub-component takes as inputs, real-world geo- spatial data and uses that to generate the initial structural conditions of opportunities and constraints that characterize the environment of the case study metropolis.

ii. Socio-demographic sub-component

The socio-demographic sub-component specifies the model entities and their characteristics. In this model, the main decision-making entities are heterogeneous households who make residential decisions and individuals within the households who make job location and travel decisions. A household consists of a family unit and could be an individual or a group of persons who live together and share house-keeping arrangements.

As with existing agent-based models (see for example Tannier et al., 2015; Li and Liu, 2006; Hosseinali et al. 2013; Haase et al.., 2010), households as the primary decision-making agents are differentiated based on socio-economic characteristics (i.e. income, ethnicity, levels of educational attainment, skill levels and number of adult working members), and life-cycle stage attributes such (i.e. marital status, family size, the presences of children and age of adult members). The socio-demographic sub-component also provides the foundation for the encoded mechanism by which new household agents are generated endogenously. A detailed description of the procedure used to initialize and differentiate household agents in the model is presented later in chapter seven where the empirical model is implemented.

iii. Property market sub-component

As depicted in figure 6.1, the property market sub-component generates the housing and land market conditions as the main spatial goods that constitute the object of households’ residential choice. It defines the types of dwelling and their intrinsic attributes as well as land parcels, their size and prices. The valuation of a dwelling unit 𝜒𝐷 is a function of its attributes, immediate meso-scale locational attributes and the wider environment within which it is located. This is expressed as follows:

𝛘

= 𝐟(𝛘

, 𝛘

, 𝛘

, 𝛘

, 𝐔

, 𝐏

)

(6.1)

𝜒𝐷𝑡 _{denotes dwelling type (e.g. detached, semi-detached, flat and compound);} 𝜒𝐷𝑜 _{denotes occupancy/tenure type offered with the dwelling;}

𝜒𝐷𝑝 _{denotes dwelling ask price for rental or owner-occupier tenancy;}

𝑃_{𝑎𝑚𝑡𝑦}𝑥 denotes proximity of dwelling to amenities (e.g. school, shopping, terminals) 𝑈_𝑍 denotes one of three urban-zones (i.e. historical-core, inner-suburb and

The macro and meso-level spatial characteristics combine with the intrinsic attributes of the dwelling to determine the unique characteristics of spatial goods evaluated by households in the residential location choice process.

iii. Job market sub-component

The job market sub-component, as shown in figure 6.1, links with the employment locations defined by the spatio-environmental component of the model to generate the initial job market conditions in the model. Following the assumption of Batty (2005), the main employment zones are exogenously determined and become the active locations where would be individual working members of the household look for employment. Within each employment zones are jobs categorized by work industry and by skills requirements for the job. There exists a direct feedback between the number of active individual agents and the number of available jobs. As will be described later at the model implementation stage, this feedback mechanism mimics a demand-supply interaction by which new jobs are created within the model to match increasing population over time. Moreover, the initial conditions of the job market sub-components provide the basis for home-based jobs—jobs located within the immediate vicinity of the dwelling of agents in the model to emerge endogenously. Details of the characterization and evolution of the job market are provided under the model implementation processes in chapter seven.

iv. Travel choice sub-component

The travel choice sub-component depends on the other three sub-components of the model. it is directly shaped by the urban structural and functional attributes such as the location of jobs and amenities as well as the socio-demographic. This sub-component of the model tracks the travel choices of individuals as well as the emergent patterns of mobility (i.e. trip production and attraction, work-home distances and travel mode choice) that results from the home-work location combinations attainable within the urban context.