Solving the Issue of Managerial Decision Making in Terms of Ranking by the Effective Rank Method

Abstract

Managerial decision-making process is dependent on complete or asymmetric information that determines logic, reliability and results of the corporate management. Business administration requires the most accurate application of information and communication technologies with possibility of automated decision-making included in the methodology for calculating the rating of the managed items or objects. In the paper, the authors-developed Method of rank analysis was developed and applied based on the replacement of ordinal ranking with the effective series in the set of units or objects of management belonging to a homogeneous set (enterprises and organizations of a particular industry, the territory of a particular country, employees of an enterprise, etc.). This study is based on the following assumptions: whatever rating technique is applied in the analysis and management of this homogeneous set, as a result, a Top 10 or other similar list is obtained that distributes the rated units in an ordinal series. Secondly, incorrectness of such a distribution is obvious and requires a change in the ordinal ranking, namely, its replacement with an effective ranking. By doing so, the latter takes into account the degree of difference in the rating values of the selected objects of analysis and management. Thus, the authors propose to use two approaches to constructing an effective rank: 1) based upon the use of the normalized value formula of the so-called “Linear Normalization Model” (closed ranking scale) and 2) in accordance with linear rank distribution of objects modeling to which one or more rating is applied (e.g. rating of investment attractiveness, quality of life, digitalization, etc.) which characterizes the main (central) part of the objects producing the largest R2 values processing their own calculation system (open ranking scale). As a result, experts responsible for monitoring the system and the managerial decision-making algorithm will obtain the most reliable information on the actual distribution of the ranking objects, taking into account the observed differences in the received ratings of the adjacent rating objects.