This paper aims to explore which macroeconomic factors affect the volatility of the automakers stock prices by employing a multifactor model. The study uses quarterly panel data of 39 automakers quoted on the stock exchanges in the 11 countries. It studies the effects of 19 macroeconomic variables from January 2000 to December 2017, and proposes the mixed-effect model constructed based on employing genetic algorithm and AIC criterion, and compares its explanatory power with the existing multifactor model (El Khoury, 2015 El Khoury, R. M. (2015). Do macroeconomic factors matter for stock returns? Evidence from the European automotive industry. International Journal of Monetary Economics and Finance, 8(1), 71–84. doi: 10.1504/IJMEF.2015.069170 [Crossref] , [Google Scholar] ). This paper suggests that the proposed model can shed more light on explaining the variability of stock prices of the quoted automakers. The findings show there are positive linkages between automaker's stock return volatility and explanatory variables such as stock market development, GDP and unemployment. Conversely, an inverse linkage between the dependent variable and money supply and IPI was found. The study demonstrates that selected macroeconomic factors can also be used as predictors.

This paper evaluates the usage of analytical programming and different fitness functions for software effort estimation. Analytical programming and differential evolution generate regression functions. These functions are evaluated by the fitness function which is part of differential evolution. The differential evolution requires a proper fitness function for effective optimization. The problem is in proper selection of the fitness function. Analytical programming and different fitness functions were tested to assess insight to this problem. Mean magnitude of relative error, prediction 25 %, mean squared error (MSE) and other metrics were as possible candidates for proper fitness function. The experimental results shows that means squared error performs best and therefore is recommended as a fitness function. Moreover, this work shows that analytical programming method is viable method for calibrating use case points method. All results were evaluated by standard approach: visual inspection and statistical significance.

Successful timing of INDUSTRY 4.0 projects in businesses can be disrupted by the coming of a recession. The authors assume a close link between INDUSTRY 4.0 and research and development (R&D) projects. R&D projects are statistically internationally monitored and have a significant impact on European Union economic policies. This article explores the impact of the two economic recessions in 2009 and 2012–2013 on the number of R&D entities and human resources involved in R&D in the Czech Republic. The method of multivariate statistics with dummy variables was used. Research has shown that different sectors (business sector, government sector, higher education sector, and non-profit sector) show a different development of the number of R&D entities in times of economic crisis. The research findings indicate that current European Union grant support, tax relief, and other specific factors appear to be more important for the development of R&D projects in the Czech Republic than the effects of economic recession. In terms of longer time horizons, however, the effects of the business cycle cannot be ignored. In order to predict economic development, enterprises and other subjects can use leading macroeconomic indicators.

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Purpose: The present paper evaluated the connections between the degree of fulfilment of the EFQM model's requirements and the organisation's size, key results, social responsibility, employee satisfaction and customer satisfaction. Methodology/Approach: The dataset was acquired via an internet-based survey hosted on Google Forms. The survey targeted managerial personnel within manufacturing entities situated within the geographical boundaries of the Czech Republic. Findings: Research on the relationship between the degree of fulfilment of the EFQM model requirements and the organisation's size, critical organisational results, social responsibility, employee satisfaction, customer satisfaction and overall organisational results demonstrated a moderately significant to strong correlation for all monitored indicators. Research limitation/implication: The data is collected only in one specific country, but the production organisations in which the research was carried out are mainly foreign-owned. Originality/Value of paper: The current research results offer practical and theoretical implications. Theoretically, the research expands the literature on the EFQM model and its connection with current trends, which are the higher innovative activity of organisations and correlation with Industry 4. Practically, the research results will benefit managers, directors, and leaders of companies by allowing them to maintain an optimal level of quality management and estimate future requirements for complex enterprise integration.