Information Technology Reference
In-Depth Information
6. Companies that process waste, process any waste that they have received.
7. Finances of waste producing companies are updated.
8. Any company that has no money goes bust.
9. New contacts are made - how often depends on the contacts-rate slider.
10. New waste processors are created - how often depends on the slider called
company-creation-rate. Biodiesel plants are created providing there is enough
waste oil available to operate. Either composters or AD plants are started (50/50)
depending on whether there is solid waste and, for AD plants, only if a “profitabil-
ity” measure is satisfied.
11. Update any contract details - end any contracts that have reached the end of their
contract period.
The above resulted in a toy ABM, which already reproduces some of the properties
that we observed in the real world at the macro-level. For example, we can see from
the model the impact that the RO incentives have in reducing organic waste going to
landfill, or the volatility in waste prices, and the effect of this in the spread of company
profitability. The macro data used for this hands-on validation exists in the form of
reports and other qualitative data as well as quantitative data of particular material flows.
Additionally, we can probe the relationship between the level of RO incentive and the
proportion of anaerobic digesters to composters, and more generally the extent to which
policy driven financial incentives affect the financial viability of different agents within
the model.
In developing an ABM one problem is the difficulty in distinguishing between en-
dogenous and exogenous drivers because they are commonly entangled in practice.
Waste policy had clearly initiated the drive towards a bio-based economy but the in-
troduction of a variety of climate change policy measures overlaid the initial patterns.
HCF and HINCA were clearly facilitating endogenous growth of the knowledge net-
work that might be considered one layer of the multiplex regional network, but both
stand outside the production network. Furthermore, despite the empirical evidence we
found for the coordinating role of HCF and HINCA we are unaware of a defendable
method to determine the importance of these actions (in particular not in comparison to
the exogenous influence on the network through, for instance, climate change policies).
Since the ERIE model was intended to have the primary objective of representing the
dynamic flows of biomass in the industrial production system, regulation not directly
aimed at these flows has not been considered in the initial toy model. Even if such reg-
ulation may have indirectly induced additional and sometimes qualitatively important
incentives.
The toy model does not allow discrimination between policy instruments. This does
not allow for the intended comparison between a weak (facilitation) and strong policy
instrument (economic incentives). Yet, interdependences also existed in practice, for
example where facilitation was added to the existing UK waste policy, whereas the
economic incentives were introduced as part of climate change policy. This shows the
difficulty to empirically distinguish between and analytically model the co-evolution
of policies and also the area network and national and international policies. This is
partly because political actors (Local Authorities) are only represented in the model
as suppliers of organic waste. They do not appear in their regulatory function, where
