Subject. As economic processes get digitalized, management needs to address issues with new approaches to raising the efficiency of financial resources allocated for remuneration. Thus, the correlation of rewards and ultimate results of entities become a priority. Therefore, factors influencing the motivation and incentives of the staff and its performance underlie the reward system and the effectiveness of the entity. It is important for the management to measure the effect of the factors on the return on financial resources used for remuneration in order to attain goals and operate in the business environment effectively. Objectives. The study is to model the efficiency of rewards with reference to factors influencing the ratio of output to rewards, expertise and qualification of the staff. We use a linear model of multivariate regression on the basis of the Principal Component Analysis (PCA). Methods. The study relies upon the ordinary least squares methods and PCA, and general methods of research, such as an analysis, synthesis, induction, and deduction. Results. Conducting the managerial analysis of reward efficiency with reference of some determinants and their correlation (the output to reward ratio, staff's expertise and incentives), we evaluate internal corporate factors while handling new issues and outline future actions to set up the comprehensive reward system. The information helps improve the corporate performance and ensure the unbiased remuneration with reference to the employee’s contribution to the accomplishment of business goals. Conclusions and Relevance. The methodological approach we propose helps determine how the factors influence the reward mechanism in order to fulfill the corporate strategy objectives. The findings can be used for operational purposes of entities in order to set up the remuneration policy and tactics harmonizing pursuits of the business and staff.
Keywords: remuneration, efficiency, return on salary, rewards, management analysis, linear regression model, principal component method
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