Previous research has pointed out that Industry 4.0 will lead to more sustainable production; however, it may have profound effects on European competitiveness. Today, firms in the CEE countries face a limited scope for continued economic expansion, and hence there is a growing pressure on them to move upward in the global value chain by investing heavily in advanced technology. Consequently, the authors argue that B2B firms from the CEE countries can have a massive impact on Europe’s long-term competitiveness by reversing the effect of digital transformation due to their strong interdependencies on other European economies. Therefore, in a cross-country survey, research data were collected (n = 302) about the driving forces, barriers, and role of stakeholders in the implementation of digital transformations. The authors found that some technologies are implemented much more frequently compared to others, with some indication for country specialization. The leading driving force is customer satisfaction followed by productivity and financial motives. Shortage of skilled human resources and high implementation costs are the main barriers. The firms tend to rely on universities and research centers, while the government is perceived only as a financial provider. The results are also informative for practitioners and policymakers—providing them with benchmarks.

There are several available measures that can help us to distinguish between two general types of processing, usually known as intuitive and deliberative. In the current study we examined two of them, Rationality-Experiantility Inventory a nd Preference for Intuition/Deliberation Scale in Slovak sample of 860 working adults and students (Study 1). In Study 2 (with N = 428 participants) we verified the 2-factor structure of REI after rephrasing problematic items shown in Study 1. The results showed that both PID and REI have good internal consistency, structures of Slovak versions correspond with the original versions. We found also some gender and age differences, and identified three factors (decision-making based on affect and holistic processing, decision-making based on creativity and cognitions, and planned, deliberate decision-making).

Accurate perception of medical probabilities communicated to patients is a cornerstone of informed decision making. People, however, are prone to biases in probability perception. Recently, Pighin and others extended the list of such biases with evidence that “1-in-X” ratios (e.g., “1 in 12”) led to greater perceived probability and worry about health outcomes than “N-in-X*N” ratios (e.g., “10 in 120”). Subsequently, the recommendation was to avoid using “1-in-X” ratios when communicating probabilistic information to patients. To warrant such a recommendation, we conducted 5 well-powered replications and synthesized the available data. We found that 3 out of the 5 replications yielded statistically nonsignificant findings. In addition, our results showed that the “1-in-X” effect was not moderated by numeracy, cognitive reflection, age, or gender. To quantify the evidence for the effect, we conducted a Bayes factor meta-analysis and a traditional meta-analysis of our 5 studies and those of Pighin and others (11 comparisons, N = 1131). The meta-analytical Bayes factor, which allowed assessment of the evidence for the null hypothesis, was very low, providing decisive evidence to support the existence of the “1-in-X” effect. The traditional meta-analysis showed that the overall effect was significant (Hedges’ g = 0.42, 95% CI 0.29–0.54). Overall, we provide decisive evidence for the existence of the “1-in-X” effect but suggest that it is smaller than previously estimated. Theoretical and practical implications are discussed.