Winning isn't everything: Guilt proneness and competitive vs. non-competitive motivation.

OBJECTIVE: Guilt proneness is associated with both high motivation to succeed and enhanced concern for others. However, in competition, achieving success requires harming others' interests, which demotivates guilt-prone individuals. Given the prevalence of competition in social and professional life, we examine the relation between guilt proneness, general motivation, and competitive motivation. METHOD: Two experiments and two laboratory studies (N = 1735) measured guilt proneness, general motivation, and competitive motivation, and their effects on competitive preferences and choices. Study settings included students' choice of playing a game individually vs. competitively (Study 1), physicians' likelihood to seek residency in medical fields characterized by high competitiveness (Study 2), amateur athletes' preferences between inclusive and win-oriented team strategies (Study 3), and online workers' evaluations of a hypothetical scenario (Study 4). RESULTS: Guilt proneness was related positively to general motivation, but negatively to competitive motivation. Guilt proneness, indirectly through lower competitive motivation, predicted a lower likelihood of pursuing competitive paths and preference for non-competitive strategies. Emphasizing prosocial aspects of competitiveness attenuated these effects. CONCLUSIONS: Guilt proneness is related to high general motivation but to a lower desire to win. Guilt-prone individuals strive for excellence, but through non-competitive paths, whereas people with lower guilt proneness prefer competing.

Are car safety systems associated with more speeding violations? Evidence from police records in Israel.

Over the past decade, the popularity of installing advanced driver-assistance systems (ADAS) in cars has increased markedly. However, the effectiveness of ADAS is subject to debate, primarily because these systems intervene in drivers' perceptions and actions and could lead to adaptive behavior. Using complete national data for the installation of three leading safety systems and speeding tickets issued over the course of an entire year, allowed us to pinpoint the impact of these safety systems at a national level. Employing zero-inflated negative binomial regression models, we found that the installation of the three safety systems was associated with higher number of speeding tickets. These findings are in line with the literature that indicates adaptive behavior in the context of risk. However, when we accounted for the proneness to commit other traffic violations, the effect of the safety systems on the prevalence of speeding tickets was evident only for those prone to violations. Further research should be conducted to identify which drivers will be more likely to be affected and under what circumstances and safety system types.

Assessing the emission consequences of an energy rebound effect in private cars in Israel.

The UN Sustainable Development Goal, SDG 7.3, is to double the global rate of improvement in energy efficiency by 2030. To meet this and other energy targets, countries encourage the development and adoption of energy-efficient products. An extensively researched phenomenon in this context is the energy rebound effect, especially in transportation. However, the direct relationship between the energy rebound effect and car emission levels has barely been investigated. Understanding this relationship is important, because energy-related emissions are closely linked to mortality, morbidity, and climate change. We assess the emission consequences in the private car market in Israel of a rebound effect associated with a policy promoting energy-efficient cars. We find that the baseline rebound before introduction of the policy was 40%. In the following three periods marked by policy changes, it grew to 54%, 69%, and 88%. Using household data with specific car characteristics and usage, we calculate the added greenhouse gas (GHG) emission consequences of this rebound by the end of the studied period to be about 5% of the country's per-capita target. Notably, estimates for the emission consequences using "average car" values were almost twice as high. The reason for this gap derives from the co-dependance between car usage and car efficiency. We discuss the implications of this gap in meeting emission goals.