THE KÜBLER-ROSS FACTOR IN MANAGING THE PERFORMANCE OF TECHNICAL AND SOCIO-ECONOMIC SYSTEMS
DOI:
https://doi.org/10.37943/AITU.2020.94.59.003Keywords:
The Extended Grief Cycle, Kübler-Ross model, Model R. Belbin roles, Markov model of communications, performance recovery, business continuity, reliability, hazardous event, Business Continuity Management Lifecycle Stages, preparedness for hazardous sitAbstract
The article proposes to consider the possibility of using the Kübler-Ross model as a mandatory and necessary addition when restoring systems after critical failures, accidents, and other catastrophic events. As stages of the model, it is proposed to consider the “extension” of the classical Kübler-Ross model in the form of an Extended Grief Cycle. Moreover, each “stage of the model” is considered as a separate “state” of the system. It is also assumed that the transition from any state of the model is possible not only “linearly forward”, but also in any other direction. Moreover, the probabilities of such transitions do not depend on the previous history of the system. Such an assumption allows us to consider the possibility of interpreting the created model as a Markov model, and, accordingly, to apply the mathematical apparatus of Markov chains for its study. It is proposed to consider such a characteristic of an effective recovery system as the “readiness” of a recovery team to transition to a productive state as soon as possible from the point of view of group dynamics and the effectiveness of the distribution of team roles. For this, it is proposed to use the logic of the team role model of R. Belbin. Minimizing the time to achieve the effect of maximum effectiveness in emergency situations in the context of the concept of incident preparedness and continuity of work, in this case, will depend not only on technical and other means of response but also on the psychological stability of the recovery team members, the effective allocation of roles and readiness for adequate action. This is confirmed by the results of transient modeling. The simulation results show the dominant value of the probabilities of being in the states of “shock” and “inoperative system” if you do not control the system purposefully and do not go through all stages of the Extended Grief Cycle model sequentially, one after another.
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