README documentation of the supplements to Brughmans and Poblome, 'Roman bazaar or market economy? Explaining tableware distributions in the Roman East through computational modelling’.


SUPPLEMENT 1

This supplement consists of seven excel tables:
‘25-1BC’
‘1-25AD’
‘25-50AD’
‘50-75AD’
‘75-100AD’
‘100-125AD’
‘125-150AD’
,
Each holds the ceramics data for a given 25-year period. The rows are individual forms (or types) of tablewares, and the columns are sites at which these were excavated. In each cell the proportion is given of all sherds published and included in the ICRATES database of a form found at a site that can be dated to this 25-year period following a normal probability distribution.

The first column indicates the fabric or ware of the form (i.e. ESA, ESB, ESC or ESD). The second column gives the standard name of the form. The third and fourth columns present the lower and upper dates of the circulation of this form, according to the standard typo-chronologies followed.



SUPPLEMENT 2

An excel spreadsheet listing the experiments presented in this paper in its columns. The rows are divided into five sections providing information about the variable settings, network structure and summary results of each experiment.

The first section titled ‘variable settings’ lists all independent variables in the first column, and the subsequent columns present the settings of these variables for each experiment. A summary description of each variable is provided below. A detailed technical description of the model and all variables is published as: ‘BRUGHMANS, T. & J. POBLOME. 2016. MERCURY: an agent-based model of tableware trade in the Roman East, Journal of Artificial Societies and Social Simulation.’

The second section titled ‘Links’ lists per experiment the number of links that are created in each of the five network creation steps of the model, and the total number of links. The results given here are examples taken from one simulation of each experiment with the randomisation seed = 10; other seeds give similar results.

The third section titled ‘Network measures’ provides summary network structure statistics for the networks created in each experiment. The results given here are examples taken from one simulation of each experiment with the randomisation seed = 10; other seeds give similar results.

The fourth section titled ‘Width of all products’ distributions’ provides summary statistics on the distributions of wares per experiment: i.e. of all simulations per experiment, the average, median, mode, standard deviation, minimum, maximum, NUMBER of sites on which wares were deposited.

The fifth section titled ‘Range of distributions’ provides summary statistics on the range of distributions of wares per experiment: i.e. of all simulations per experiment, the average, median, mode, standard deviation, minimum, maximum, DIFFERENCE between the number of sites on which the most widely distributed ware in the simulation is deposited and that of the least widely distributed ware in the simulation.



DESCRIPTION VARIABLES

A summary non-technical description of the variables mentioned in supplement 2 is provided below. A more elaborate technical description of MERCURY and each variable mentioned in supplement 2 is published in: ‘BRUGHMANS, T. & J. POBLOME. 2016. MERCURY: an agent-based model of tableware trade in the Roman East, Journal of Artificial Societies and Social Simulation.’

Global variables	
num-traders: the total number of traders to be distributed among all sites.
num-sites: the total number of sites.
equal-traders-production-site: determines whether the number of traders at production sites will be equal and determined by the variable 'traders-production-site' or whether it will follow the same frequency distribution as all other sites determined by the variable 'traders-distribution'.
traders-distribution: determines how the traders are distributed among the sites; this can be either 'uniform' or 'exponential' frequency distributions.
traders-production-site: determines the number of traders located at production sites.
network-structure: when set to 'hypothesis', this connects traders to create a small-world structure that represents the hypothesised social network structure; when set to 'random', this connects traders to create a random structure with the same number of nodes and edges as would be expected in a'hypothesis' network with the same global variable settings. (Not tested here.) 
maximum-degree: The maximum number of connections any single trader can have
proportion-inter-site-links: the proportion of all pairs of traders that are connected in step two of the network creation procedure by inter-site links.
proportion-intra-site-links: the proportion of all pairs of traders that are considered for becoming connected in step three of the network creation procedure by intra-site links.
proportion-mutual-neighbors: the proportion of all pairs of traders with a mutual-neighbor that are considered for becoming connected in step four of the network creation procedure by intra-site-links.

Trader-specific variables	
max-demand: the maximum demand each trader aims to satisfy.
local-knowledge: the proportion of all traders a trader is connected to that they receive commercial information (supply and demand) from in each turn.