Peter Štetka

This study delves into the impact of visual marketing stimuli on consumer response times, focusing on the complexity and subjectivity of the questions posed. Conducted in Slovakia, the research involved 40 participants (20 men and 20 women, aged 30 to 50 years), all holding university degrees in economics to ensure consistent decision-making experience. Participants were presented with visual stimuli representing four well-known FMCG brands. The stimuli included simple brand preference questions and complex evaluative judgments of offer efficiency. Response times were measured in milliseconds and analyzed using statistical methods, including the Mann-Whitney U test and one-way ANOVA. Results revealed that responses to simple stimuli averaged 1212 ms, while complex stimuli elicited slower responses, averaging 2504 ms. A significant difference was observed for “No” answers in the offer evaluation tasks, with correct “No” responses taking 3000 ms compared to 2297 ms for incorrect ones (p < 0.05), highlighting the cognitive load involved in accurate decision-making. These findings provide valuable insights into the cognitive processes driving consumer decision-making and contribute to the theoretical understanding of how question complexity and subjectivity influence response times.

Acknowledgment
This paper was funded by research grant VEGA 1/0462/23 entitled “Circular economy in the context of societal demands and market limitations“ (100% share).

Type of the article: Research Article

Abstract
Artificial intelligence (AI) is reshaping how firms design work, yet firm-level evidence compresses employment implications into a single net figure that hides simultaneous hiring and cutting within one firm. The study examines how AI adoption stage, self-assessed AI maturity, orientation, and ownership are associated with the incidence and co-occurrence of realized or planned job creation and elimination. The analytical sample is 693 AI-engaged Slovak firms from a cross-sectional survey (351 current users, 211 pilot firms, 131 planning adoption). Two binary items record whether AI-related positions have been introduced or are planned, and whether AI has led or is expected to lead to layoffs. Each item merges realized with planned or expected action, so the outcomes indicate the incidence of an actual or anticipated event, not the number of positions. We applied exact tests, logistic and multinomial logistic regression, and a bivariate probit model with Benjamin-Hochberg false-discovery-rate (FDR) adjustment. Reported or planned creation was more frequent than elimination (18.0% vs. 9.2%; p < 0.001), and the two co-occurred well beyond chance (odds ratio 7.23; ρ = 0.54). A more advanced adoption stage was associated with a higher incidence of creation (OR 1.49; FDR-adjusted p = 0.004), and employee job-threat concern was associated with a higher incidence of elimination (OR 1.58; p = 0.014). Foreign ownership was associated with joint occurrence of both outcomes in an exploratory model only (RRR 2.29; unadjusted p = 0.027). The study contributes a descriptive typology of four incidence patterns; the cross-sectional design supports associational reading only.

Acknowledgments
The authors thank the AI-ImpactSK project team and all responding firms.
This paper was supported by the European Union – NextGenerationEU through the Recovery and Resilience Plan for Slovakia under project No. 09I05-03-V02-00003/2025/VA (AI-impactSK); 100% share.