Abstract: This paper is based on a case study conducted in the frame of the European Union (EU) Framework 7 project IMPRESA which aimed to evaluate the impact of EU research on agriculture. Official data sets were used to show trends in agricultural research expenditure in Hungary from 2008 onwards, focusing on public and private research eff orts, research strategy and priority areas, research staff and evaluation of research, and dissemination of research results. The factors behind these trends were explored through semi-structured, faceto- face interviews with key experts. Total R&D expenditure (not adjusted for inflation) in the field of science ‘agricultural sciences’ increased from HUF 19.7 billion in 2008 to HUF 22.1 billion in 2016. There was a marked decline in expenditure at public-sector R&D institutes and (until 2015) broadly constant R&D activity at universities, while that of the business sector increased. Public-sector R&D institutes have been reorganised in an attempt to improve their efficiency and eff ectiveness, but several further actions are needed. These include the development of a national agricultural research strategy, the recruitment of younger, innovative staff coupled with the provision of motivating conditions of work, and a greater emphasis on applied research together with more eff ective evaluation of research impact.

Keywords: agricultural research, field of science, socio-economic objective, sector of performance, R&D institutes, HE institutes, business enterprises.

JEL code: Q16.

Abstract: Operating cost control is essential to making the right decision for farmers, managers, etc. in the agriculture. Machinery operating costs form a significant proportion of the expenses involved in agricultural production and, thus, the appropriate or inappropriate use of machinery can significantly influence the efficiency of farming. The primary goal of this study is to examine operating costs and analyse the causes of changes in the Hungarian machinery market during the past few years. Expenses can be reduced in every farm and, thus, my aim is to summarise cost reduction possibilities. My research shows that the EU co-financed support for machinery and equipment investment has a great impact on the replacement and average annual usage of power machines because, after the end of EU subsidies, the number of agricultural machines sold has decreased.

Keywords: direct and indirect costs, cooperation, market, performance, production.

JEL codes: O13, Q11, Q13.

Abstract: Corporate management tasks cannot successfully be executed without decisionsupport functions of appropriate quality. The importance of producing and achieving relevant, accurate and up-to-date information is unquestionable as such information provides stand-alone value. According to current trends, the need for reporting systems based on specific expectations, which can be used to provide decision-makers with a long-term competitive advantage, has increased. In our research, we set out to investigate how diff erent management techniques (e.g. performance tracking) can support decision-making. Our findings are based on the data from the World Management Survey carried out in 2004, involving more than 700 companies from 34 countries (Bloom–Van Reenen 2007). The impacts of each management method on company performance are also examined. It is hypothesised that using information support management methods for decision-making can influence the overall success of a company. We also look for relations between the company’s ownership status (i.e. family, founder, institution manager, private, or other ownership) and the corporate internal information system.

Keywords: decision support, management tools, information system, reporting system, business intelligence.

JEL codes: M29, M49.

Abstract: This paper presents diff erent methods for the forecasting of unemployment rates in two Romanian counties. The stationarity of the monthly unemployment rate time series between January 2000 and November 2016 was examined using the ADF and KPSS tests. Based on time series, a forecast was estimated using two approaches: the Box-Jenkins methodology and the Artificial Neural Network-based NAR model. Results showed a decreasing trend by the end of the forecasted period in all cases, except for the NAR model of Harghita County. Comparing the forecasted values with the officially registered unemployment rates from the same period, we observed that, by the end of the period, the diff erences between the real and predicted values became higher in the NAR model than in the ARMA model-based forecasting. These results indicate that, in these particular cases, NAR neuron network model-based forecasts fit well if values are estimated for a short-term period, while for medium-term forecasts the ARMA model-based forecasting is more precise.

Keywords: regional unemployment, time-series models, forecasting and prediction methods, Box-Jenkins methodology, Artificial Neural Network.

JEL codes: C32, C53, R15.