Tutoring Mechanisms of Business Management

Adaptive mechanisms of business management in conditions of uncertainty are based on a cognitive approach and consideration of a human factor. The task of classification of a random business potential is solved if its probabilistic characteristics are known. Otherwise classification with tutor's instructions is used. Then to determine the optimal parameter of the decision rule, a stochastic approximation is used. The problem of asymmetric awareness of management, tutor, and staff about business potential is formulated. It is shown that undesirable activity of staff can provide business output that is not equal to the potential. That shifts the assessment of decision rule parameter. To solve this problem, the manager is considered as Learner using the instructions of the Tutor, when both of them are not aware of the potential of the active element (staff). Learner's classification, ranking and incentive procedures constitute the tutoring mechanism. Then the active system as a whole consists of the active element, and the Center, which has a management subsystem, including Tutor and Learner with tutoring mechanism. The active element selects its state to maximize own aim function. The set of options for the active element is defined. Sufficient conditions are proved for the synthesis of the tutoring mechanism, in which active element uses the potential, and the optimal parameter of the decision rule is determined. The obtained results are illustrated by the example of constructing the tutoring mechanism for increasing energy efficiency of large-scale corporation Russian Railways.