To date there has been little actual evidence of this at broad consensus level.
This study addresses this potential effect of information load on the consensus level in a collaborative GIS MCDA context.
The second algorithm is designed to assist the group in achieving a predefined consensus level.
In order to describe how exactly the consensus is achieved, the notion of consensus level is introduced.
In a regime characterised by such low levels of regulation, recently termed the "Wild East", numerous companies have chosen to define a consensus level of socially responsible behaviour.
Additionally, visual representation of experts' consensus position within the group before and after implementing their feedback advice is also provided, which help an expert to revisit his evaluations and make changes if considered appropriate to achieve a higher consensus level.
Additionally, a group consensus index is introduced to measure the degree of deviation between the individual HMPRs and the group HMPR, and a consensus-reaching process is provided to help the individual HMPRs achieve a predefined consensus level.
To achieve a predefined consensus level, an interactive consensus reaching process is provided where the group reciprocal preference relation is seen as a reference when experts change their preferences.
Based on these, a suboptimal method of resource allocation to reduce such effect of quantization error is proposed, and a dynamic quantizer is designed to meet the requirement of the consensus level, under the constraints that the total quantization rate of overall system is limited.
The main characteristics of our model are that: (1) it is independent of the prioritization method used in the consensus process; (2) it ensures that each individual multiplicative preference relation is of acceptable consistency when the predefined consensus level is achieved.
Our research work implemented strategies contained in Delphi studies through which it was possible to triangulate the data obtained from the panel of experts: a) Central tendency and dispersion measures; b) Analysis of consensus level between rounds (IQR, RIR, VCV); c) Reliability analysis (Cronbach's alpha); and d) Analysis of group stability in answers (median test and U Test).
