Cross Impact Analysis
Topic outline
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Cross-impact analysis was developed for forecasting the future by Theodore Gordan and Olaf Helmer in 1960s.
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Cross-impact analysis was developed by Theodore Gordon and Olaf Helmer in 1966 to determe how signals among a series of events will affect unfolding events and decrease uncertainty in the future. A range of techniques known as ""cross-impact analysis"" are used to evaluate changes in the likelihood that a specific set of events will occur as a result of the actual occurrence of one of them. The cross-impact model was created in order to take into account predicted interactions that might not have been considered when making individual projections. Cross-impact analysis aims to bridge links across elements and actions. In order to assess which occurrences or situations are most likely to occur within a certain time frame, these interactions are then classified either positive or negative with respect to one another. In a way, the Delphi method can also be seen as part of cross-impact analysis. Just as experts working at Delphi make reasoning predictions on events based on a specific timeline, cross-impact analysis can also be included when Delphi's impact on the same topic or area emerges. Although cross-impact analysis was originally associated with the Delphi method, it is not used specifically. Different methods and variants that arise due to the cross-impact method can be used in different ways, thanks to the efficient use of tools that can be used for a possible problem or question that may arise in the future. In addition, the results of the analysis obtained by cross-impact provide examples of possible future events.
Since the early 1900s, the Central Intelligence Agency has used cross-impact analysis as a method to predict the diversions on troops that continue to emerge as a result of decisions taken regarding different situations and options for an event. However, towards the end of the 1900s, many scientists working on the future prediction made connections between different events and used the cross-effect analysis method to predict how the general relationship between them would emerge. In this way, it would be correct to say that the cross-impact analysis method has turned into a perspective. In the early 2000s, institutions and organizations serving in different periods also applied cross-impact analysis as a group.
It seems appropriate to rely on ""opinions"" in this case to determine the a priori probabilities of these events because the causal structure that creates them is unknown. In particular, cross-impact analysis enables the computation of the most probable combination of events under consideration, or the ""most probable scenario,"" which helps with human probability judgements of single and pairs of events, as well as explicitly dealing with higher order interactions. This ""most likely scenario"" can be used as the exogenous circumstances for the central projection during the industrial planning process.
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To design system dynamics models and investigate the effects of different policies on enrolment and academic achievement in primary education, a cross-impact model can be developed. The cross-impact matrix provides a way to identify the impact variables as well as show how one variable affects the others. In order to identify the changes in outcomes that may be directly linked to a particular procedure based on cause-and-effect analysis, outcome measures rely on rigorous methodologies. The method is based on a sequence of follow-up meetings with a group of subject matter experts to determine the major factors influencing a topic's evolution and the likelihood that certain changes will occur in each of these factors. It is especially beneficial for computerized and manual problem solving. The first step in the method is determining the volunteers, who are crucial to the project since they need to be knowledgeable enough to make accurate predictions and committed enough to stay involved throughout the entire research process. Depending on the goal and audience, the implementation process can be divided into two main stages.
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