Martin Rigelsky

The objective of the research was to identify statistically significant differences in selected engagement indicators on Facebook – likes and shares in relation to the different types of content that brands on this platform add to. The analysis was performed on a sample of three global companies from the top 25 most valuable brands in the world and their posts. Using quantitative statistical methods – MANOVA (Multivariate analysis of variance) and Gammes-Howell post hoc test, a total of 1,280 brand posts were analyzed in order to differentiate the liking and sharing of content types. Data collection was carried out in the first half of 2018. The findings pointed to two statistically significant differences that were also interpreted in the discussion of the research. The findings have shown that in case of liking, in two cases out of three, there is a statistically significant difference in terms of the type of content added, when photos came out as those with the greatest potential to get like from Facebook users and fans. At the same time, the same finding appeared in the case of sharing, which is an even stronger form of engagement. Likewise, photos were shown to be the most promising in terms of potential content sharing by Facebook users and fans. The study provided some clues as to where this research should go further and explore the relationship more deeply in view of the more extensive quantitative research, and also the potential qualitative approach. The future research directions include analyzing companies of different types and sizes and also taking into account the contribution from other social networks with the same or similar engagement indicators.

The study aims to evaluate the impact of selected factors of viral campaigns on Millennials customers’ consumer behavior. This goal was achieved in two steps: in the first step, the authors determined the impact of selected attributes on purchasing behavior in general, and in the second step, they compared the impact of the selected research campaigns – the guerrilla campaign of the company 4KA and the viral campaign of the company ABSOLUT. The inputs to the analyses were obtained through answers from 360 respondents, which completed the questionnaire on a sample of Millennials customers generation (1975–2000) – social generation, which collaborate and cooperate, expect technology to simply work for adventure and passionate about values (Smith, Nichols, 2015). The survey part of the questionnaire consisted of 8 attributes (Novelty, Relevance, Aesthetics, Clarity, Humor, Emotion arousal, Surprise, Design, Purchase intention). Data were collected based on participants’ availability and their will to participate in the questionnaire and quota selection. The PLS PM method was used to assess the impact, and the bootstrap-based parametric method was used to assess the difference in the impact. One of the most important findings is that attributes such as Novelty, Relevance, Humor, and Surprise significantly affect purchasing behavior. Concerning the company 4KA, significant impacts were seen in Relevance and Surprise, and with the company ABSOLUT, significant impacts were seen in Relevance, Humor, and Surprise. When analyzing the difference in the impact, there were no significant differences between the campaigns.

Acknowledgment
This article is one of the partial outputs under the scientific research grant VEGA 1/0694/20, VEGA 1/0609/19.

Smoking, as one of the main causes, is a negative factor associated with many diseases. The primary objective of the research is to determine the effect of innovation on selected smoking indicators in a sample of countries of the Organization for Economic Co-operation and Development (OECD). Four variables enter the analytical processing, such as Global Innovation Index, Population ratio of daily smokers (age 15+), Daily smokers (age 15-24), and Tobacco consumption in grams per capita (age 15+). These variables were included in the research from 2011 to 2018. The simple linear regression – the Ordinary Least Squares (OLS) model – and correlation analysis – Spearman’s rank correlation – was used for statistical processing. The results show that the effect of innovation on the ratio of daily smokers over the age of 15 to the total population may be considered a highly significant relationship. The effect on the annual tobacco consumption per capita is the second most significant relationship, and the effect on the ratio of daily smokers over 15 and under 24 years to the total population is the least significant compared to the previous two cases. Correlation analysis shows similar outputs. All these relationships may be considered negative. It is possible to talk about the lost innovation potential associated with smoking, primarily in the productive part of the population. A higher level of smoking can be associated with a lower level of innovation. Also, innovation negatively affects the tendency to smoke. Therefore, public policies should promote a healthy lifestyle.

Acknowledgments
This research is funded by the RVO 2020 internal grant scheme of the Tomas Bata University in Zlín titled “Economic quantification of marketing processes aimed at increasing value for the patient in the process of construction of system in order to measure and to manage performance in healthcare facilities in the Czech Republic.”