Academic journal article Academy of Strategic Management Journal

Economic Forecasting and Personnel Management of Small and Medium Enterprises

Academic journal article Academy of Strategic Management Journal

Economic Forecasting and Personnel Management of Small and Medium Enterprises

Article excerpt

(ProQuest: ... denotes formulae omitted.)


Small and medium-sized companies due to their mobility and flexibility may mitigate the negative processes in the field of employment, ensure social adaptation of employees disengaging from large enterprises as well as create new market niches in terms of economic growth.

At the same time, the contribution of small and medium-sized businesses to the overall economic performance in Russia is much lower than in most not only developing but also developed countries.

For forecasting of training, retaining and advanced training of personnel for enterprise system, it is requires the studies of quantitative and qualitative characteristics, including the definition of forecasting demand.

At the same time economic forecasting should be considered as the system of scientific research of quantitative and qualitative character, aimed at identifying the trends in the development of economic relations and the search for optimal solutions to achieve the goals of this development. (Abulkhanova, 2011)

Economic forecasts of personnel of business is closely connected with other forecasts, particularly with the measures of GDP, the number of active small and medium-sized enterprises in the country on the whole, including in the regions of cross-section, the number of trained personnel, the account of which, of course, increases the reliability of economic forecasting . The important in forecasting is a selected method as well as techniques. The set of special rules, techniques and methods is forecasting methodology, including the search methods of extrapolation using annual average growth rates, trends and econometric models, and normative target.


The search forecast (or research, trend) is forecast of determining possible states of the phenomenon in the future while maintaining the trends prevailing in the past (extrapolation).

In the medium-term forecasting of demand (from one year to 5 years), when in the development of indicators of demand there is a stable tendency to its increase or decrease, for predicting the state of future levels of the indicator under study, it is appropriate, in our view, to use the indicators of average annual growth rates. The method is based on the assumption that a number of indicators of the development of demand in time is a geometric progression. This means that each subsequent member of the dynamic series (ai+1) is equal to the previous one, multiplied by the average annual growth rate (kp). (Abulkhanova, 2015)


where kp- average annual growth rate;

n - number of periods of dynamic series;

Yn - value Y in the reporting year;

Y1- value Y in the base year.

Forecast extrapolation of a trend is the curves of correlation and regression dependencies based on factor analysis. It is typical for the trend to find a smooth line, reflecting time development patterns. In this case, it is essential to use it as a main component of the forecast time series, requiring the construction of a graph of dynamic timeline on which the function line is mathematically defined. The line of trend in the general form for the linear dependence is defined by the formula


where у - dependent rate (the quantity of trained personnel);

t - studied time interval;

a- parameter characterizing the effect of factors not accounted for in the model;

b - parameter characterizing the effect of the time factor on the change of dependent indicator.

To determine the parameters, the system of equations is solved by the method of least squares (MLS). The trends are calculated by means of equations, i.e. aligned values of demand over the past years are determined and the forecast for the future is calculated.

In practice of the medium-term forecasting, correlation and regression or econometric models (static and dynamic, single-factor and multi-factor) are also widely used. …

Search by... Author
Show... All Results Primary Sources Peer-reviewed


An unknown error has occurred. Please click the button below to reload the page. If the problem persists, please try again in a little while.