These relationships shown in Fig. 2 constitute a network of impact relations expressed by the cross-impact matrix. They constrain the space of plausible scenarios for the system state because a scenario chosen arbitrarily will in general contain contradictions to the "rules" of the network. Contradictions are made visible by calculating the impact balances of a scenario. In Fig. 3 this is done for the test scenario
[ A2 B1 C3 D1 E1 F1 ]
The states of the test scenario:
A2. Government: "Prosperity party"
B1. Foreign policy: Cooperation
C3. Economy: Dynamic
D1. Distribution of wealth: Balanced
E1. Social cohesion: Social peace
F1. Social values: Meritocratic
Summing up the highlighted rows in Fig. 3 summarizes the influences impacting the descriptors. The scores of the impact balances which correspond to the given scenario are marked by arrows in the row "Scenario assumptions".
In five cases (Government, Foreign policy, Economy, Social cohesion, Social values), the arrows of the row "Scenario assumptions" indicate the maximum score of the descriptor impact balance (cf. arrows in the row "Maximum"). Consider the descriptor "C. Economy" as an example. Economy is assumed to be dynamic and this coincides with the assumptions that the government is led by the "Prosperity party", the foreign policy facilitates cooperative relations with Somewherelands neighbours, the internal state of society is peaceful and the majority of the people show a meritocratic attitude. In one descriptor balances (D. Distribution of wealth) the upper arrow does not point to the maximum impact score and this indicates an inconsistency in the assumed scenario: The distribution of wealth is assumed to be balanced, although the policy of the "Prosperity party", the dynamic growth of the economy and the meritocratic values of the society positively forster strong income contrasts. I.e. descriptor D violates the "rules" which are coded in the cross-impact matrix.
To avoid such violations, the scenario assumptions must depict a well-balanced configuration that reflects the dual role of each descriptor as both impact source and impact target. More precisely, the internal consistency of a scenario requires that every state is chosen in such a way as to ensure that no other state of the same descriptor is preferred more strongly by the combined influences of the other descriptors. In CIB this is denoted as the principle of consistency. In Fig. 3 this principle is violated and the shown scenario is inconsistent.
It should be mentioned that the switching of the inconsistent descriptor "Distribution of wealth" does not automatically result in a consistent scenario. The descriptor D then would correspond to the influences having an impact on it. But new inconsistencies would arise in other places, caused by the change in this descriptor. Impact nets are complex systems and usually they are not easy to understand. CIB analysis, although a qualitative method, mirrors this fact.
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The archive provides a compilation of older notes on CIB projects and publications...