How agricultural managers gain, process and use information in decision-making and problem-solving process refers to decision-making styles. A successful decision depends on the flexibility of using decision-making styles in different situations. The research paper monitors the dependence between the decision-making style of agricultural managers and their personal and working parameters. To identify the decision-making styles, the MB-type indicator (Myers-Briggs type indicator) was used. The results of non-parametric testing give proof that there is a statistically significant dependence between the type of decision problem and decision-making style, “Intuitive” and “Sensing”. Parametric test ANOVA was applied to assess potential differences in the score of decision-making style by nominal-level variables. The results gave proof of a strong statistically significant difference in score of decision-making style, “Intuitive” and “Sensing” between groups of current leading position. The difference in scoring for “Thinking” and “Feeling” as decision-making styles was confirmed to be statistically significant even in functional areas of control. Subsequently, the size of this difference was calculated.

Nowadays, wine tourism belongs to the key business activities of a winery. It represents a diversification tool of a typical production company. The research paper aims to explore the relationship between wine tourism and business model parameters according to financial and production performance of a winery. The results of the parametric Independent sample t-test reveal that there is no difference in revenue, profit or gross margin between two groups of wineries with or without wine tourism activities. But the analysis gave proof about the difference in a number of revenue streams, key, and additional business activities. The effect size r for t-test was also calculated. Measuring the association between key performance indicators and wine tourism activities reveals the dependency with the number of revenue streams of a winery. Additional business activities are the most relevant parameter to perform better results in wine tourism.

A decision-making style is the manner through which a manager acquires, processes and uses information in the decision-making process. It is a set of qualitative indicators which within the decision-making process manifest themselves in the form of a decision-making style and is a typical method of implementing a decision. Knowledge of decision-making styles and their active use in a management structure contributes directly to building the competitiveness of the business. Identifying decision-making styles and delegating the right decision tasks to the right employee who possesses the fundamental knowledge to address a particular type of decisionmaking problem (well or poorly structured) is the essence of competent decision-making. This research paper deals with the relationship between the decision-making style of a manager in terms of the type of decision-making problems. Binary logistic regression was used to predict the relationship between the type of decision problem (binary dependent variable) and the overall score in the decision-making style (cardinal independent variable) through which the probability of the occurrence of the dependent value was calculated. Based on these results, we assert that as the unit score in the intuitive decision-making style increases, the odds ratio in a group of ill-structured decision-making problems increases as well. The prediction for the growth of the Sensing and Thinking odds ratio has not been confirmed. Results of non-parametric testing using the Mann Whitney U test confirmed that the preference for the type of decision-making problem has a statistically significant effect on the score achieved in the Sensing and Intuiting decision-making style. The effect size for the Mann Whitney U test was then calculated. To analyze the dependence between the nominal data, the non-parametric Chi Square Test of Independence was used, and Cramer's V was used to determine the strength of association between the variables.

The span of control expresses how many subordinates correspond to one manager, while determined by many factors and unable to be expanded indefinitely. The study monitors the impact of determinants, like the functional area of control, the level of management, the duration of managerial position, the age of the manager, the size and composition of the team. The results of non-parametric testing (Chi-Square Test of Independence) and rates of association between variables (using Cramér's V and Phi coefficient and for ordinal variables, Kendall's tau-b, GoodmanKruskal's Gamma, Kendall's tau-c and Somers' d) indicate that the team size is not related to the level of management, which does not confirm the assumption that the largest teams work at the lowest management level and vice versa, that the team leader at the top level is in charge of the smallest number of people. Instead the size of the team depends on the functional area of control. The assumption that increasing age, and so increasing experience also increases the size of the team, has not been confirmed. However, the fact that the manager works longer in the leading position has been confirmed. With the current manner of managing an organization, the age of the manager is the weak indicator of the duration of the managerial position. JEL classification:M12, M54.

Marketing and management studies are rich in the theoretical backround related to price strategy and pricing. However, consistent with the lack of interest in complexity of decision making process in price management. The purpose of the research study is to identify all stages in decision – making process in price management in Slovak enterprises and to measure their mutual association and their dependence on elements of organizational parameters. Based on the results of descriptive statistics on decision making process in price management, we can say that companies go through an average of four steps in the decision-making process (M = 4.72), with higher variability (SD=3.02), compared to the mean.