Theoretical and Applied Economics
No. 2 / 2020 (623), Summer
Investigating personnel dynamics within SMEs: A survey analysis for the case of Romania
Bucharest University of Economic Studies, Romania
National Scientific Research Institute for Labour and Social Protection, Romania
Larisa STĂNILĂ
National Scientific Research Institute for Labour and Social Protection, Romania
Maria Denisa VASILESCU
Bucharest University of Economic Studies, Romania
National Scientific Research Institute for Labour and Social Protection, Romania
Abstract. Recently and especially within emerging economies such as Romania, most of the uncertainties and risks of the economic and business environment stem mainly from the changes in the wage and fiscal policies, as well as from the conditions on the labour market.
In this paper we focus on the main causes of personnel dynamics within the Romanian SMEs, using survey data on 1200 companies. The survey was conducted at the end of 2019 and is representative at national level in terms of size, regions and main fields of activity.
Through this survey analysis we investigate aspects related to both wage and personnel policy for the Romanian companies, looking as the proportion of temporary employees, the types of nonwage incentives offered by the Romanian SMEs to their employees and the participation of their own employees in vocational training programs.
Among the most frequently offered non-wage incentives to their employees we identify: flexible work schedule, subscriptions to medical clinics, meal vouchers or transportation to work. To a much lower extent, however, they may offer subscriptions to gyms or even company shares. Our findings highlight the following main determinants of recent personnel fluctuations: lower wage attractiveness than competition, too high labour taxation, as well as limited attractiveness of non-wage incentives to their employees. Moreover, it is relevant to also point out the proportion of employees who decided to leave their job in order to start their own business, which represented about 26% of the cases reported by the surveyed SMEs.
The regional analysis of the effects of these factors on personnel dynamics ranks the Bucharest- Ilfov region first with the most notable recent personnel fluctuations, followed by the North-West region. In addition, the results also show that the effects of personnel fluctuations are more visible in urban areas as compared to the rural area.
Contents
Mathematical model used in substantiating optimal contract
Examining the drivers of business cycle divergence between Euro Area and Romania
Migration, economic causes and decisions
The voluntary pension funds – a viable solution to supplement the pensioners' incomes
An approach to measuring credit risk in a banking institution from Romania
Study on the evolution of tourism and perspectives
Investigating personnel dynamics within SMEs: A survey analysis for the case of Romania
Causes of the curve: Assessing risk in public and private financial economics
An approach to the index of economic freedom using the data mining technique in the economic environment context
Banking sector and bank liquidity – key actors within financial crises?
Existence of rewards for a sustainable enterprise in the context of the human resources strategy
Do export, financial development, and institutions affect FDI outflows? Insights from Asian developing countries
Are resources a curse or blessings? Evidence from panel ARDL model
Investigating factors affecting cooperative and non-cooperative behavior: An experimental game in the classroom
Impact of exchange rate regimes on inflation: An empirical analysis of BRICS countries
Tax structure and economic growth in general category states in India: A panel auto regressive distributed lag approach
Banking Sector Reforms and the Goals of Nationalised Commercial Banks in India
Determinants of economic growth in India: A time series perspective
Impact of credit guarantee on the output gap: A panel data analysis of Asian sovereigns
Analyzing the robustness of ARIMA and neural networks as a predictive model of crude oil prices
Does the agriculture value-added contribute to the economic growth in 30 African countries?