طبقه بندی ADVIAN ؛ یک روش طبقه بندی جدید برای رتبه بندی ضریب تاثیر

A new classification scheme for the impact analysis based on an impact matrix is presented. In contrast to the state-of-the-art methods the impact factors of a social system are not grouped into 4 or 5 groups but ranked according to different criteria. The criteria include for instance the driving impact factors as keys for improvements to the system and the driven impact factors that may be indicators for the improvement success. The ranking for each criterion is on a scale from 0 to 100, independent of the number of impact factors.

Many authors from different fields in business administration like strategic management, performance measurement or scenario analysis refer to important resources of organisations as drivers, key values or key success factors (e.g. [1], [2], [3], [4] and [5]). They should serve as ‘adjusting screws’ of the organisation. For intervening activities organisations must be able to reflect which resources they should influence to improve organisational results. However, to understand an organisation as a system of resources [6] and [7] one does not only have to classify the resources as drivers but also to classify them according to other criteria. For instance, resources that mainly depend on other resources are good indicators of the success of changes to the organisation. But, most authors argue along with [4] and identify drivers with reference to their importance without a more detailed specification. If we want to distinguish specific resources or influencing factors as drivers for instance, we need to find a way to identify them in a comprehensible manner. Some interesting approaches can be found in the literature on impact analysis. A system is classified by its impact factors (resources) and their strengths [5] and [8]. However, we state that the question of how resources can be qualified as drivers is not indisputably solved. Realising the mutual impacts of resources in organisations and the different importance of single resources (drivers and non-drivers) within social systems on the one hand, and the insufficient demarcation and methodology on the other hand, the aim of this paper is to develop an advanced methodical access. In another paper we have already introduced an enhanced method for data processing in the cross impact analysis [9]. This method (ADVanced Impact ANalysis, ADVIAN®) considers direct and — even more important — indirect impacts. This is only the first step in order to classify the impact factors (IFs) according to several criteria. Every existing reference on cross impact analysis so far suggests a classification scheme (see [5], [10] and [11]). However, these schemes are often not universal and are valid only for a specific number of impact factors or the classification is very rudimentary and divides the IFs in groups rather than giving them a specific order. In this paper we will suggest a more universal classification method that is independent of the number of IFs, allowing the classification of the IFs according to different criteria and finally to find the driver resources. In Section 2 we will summarise the most important methods given in literature for the classification of the impact factors. Section 3 will present the new approach for the classification according to different criteria.

A new classification scheme for resources (named impact factors) has been introduced. The new scheme has made some improvements in comparison to state-of-the-art classifications, but in some points it is consistent to existing methods. The new classification is independent of the number of impact factors. The impact factors are classified according to different criteria on a scale between 0 and 100. This allows the ranking of the impact factors according to different viewpoints. The assignment of a number between 0 and 100 is considered to be better than the state-of-the-art classification into 4 to 5 different groups because IFs with similar active and passive sum will get similar ratings while the group classification may lead to a different group allocation for such IFs. The presented method allows the classification of the impact factors of a system by their integration into the system and their contribution to the system stability. But also critical IFs can be identified. They should be observed with care but not be the aim of intervening activities. The most important classification, however, is the identification of driving IFs and driven IFs. The driving IFs are good starting points for intervening activities as they have impact on the other IFs in the system. Driving IFs are considered as the key resources in organisations for improvements. If the number of IFs with a high ‘driving’ ranking is too high for a suitable improvement approach, a smaller selection can be made by excluding the IFs with the highest ‘precarious’ ranking. The driven IFs are the most influenced by the system. Therefore they are good indicators of the success of the intervening activities taken on the driving resources. In other words, the conditions of driving resources should be improved by intervening activities while the condition of the driven resources is a measure of the success of these interventions. Of course, the classification of the IFs is only one step. The decision of how the identified impact factors have to be handled is not the topic of this paper. The classification presented here, however, can be applied to all systems and to the various needs which require the identification of IFs and the evaluation of impact strength between the IFs.