The accelerating climate change, which is mainly driven by human-caused CO2 emissions, requires not only the rapid introduction of new technologies and the far-reaching implementation of national and international regulations and laws, but also changes in human behavior. In this regard, behavioral changes in the transport sector are of special importance, not only because CO2 emissions of the transport sector have remained at a particularly high level for years, but also because many behavioral changes in this sector are associated with high CO2 emission savings potential (e.g., reducing vehicle use, using public transportation). Therefore, this dissertation investigated different eco-driving behaviors that have a positive effect on the climate due to reduced fuel or energy consumption and affect not only the driving task itself (operational decisions; e.g., driving at moderate speed) but also decisions before and after driving (tactical decisions; e.g., charging electric vehicles with renewable electricity) and decisions in the mobility context in general (strategic decisions; e.g., carpooling). Although the determinants of eco-driving have been intensively studied in the past, some determinants (e.g., different motivational reasons, behavioral difficulty) have been neglected and some of the identified impact factors were found not to be sufficient to deeply understand and effectively change eco-driving behaviors. In addition, the investigation of the relationship between multiple impact factors has been scarce to date. Therefore, one aim of this dissertation was to investigate the role of motivational (i.e., motivational reasons; e.g., environmental protection) and contextual factors (i.e., behavioral costs; e.g., time losses, physical/monetary effort) and their relationship for predicting eco-driving behaviors (studies 1, 2, 3). Moreover, past studies investigating interventions to promote eco-driving behaviors showed inconsistent and diminishing effects and missed to consider the impact of contextual factors. Therefore, another aim of this dissertation was to develop and identify effective eco-driving interventions, and to examine whether and how their effectiveness depends on the presence of contextual factors (studies 3, 4, 5). Study 1 was designed to investigate the relevance of motivational factors for eco-driving based on the theory of self-concordance (i.e., the consistency between a behavior/goal with the person’s pre-existing values and interests). For this, data of 539 German drivers of a cross-sectional online survey was analyzed. The findings indicate that self-reported eco-driving was significantly predicted by sustained effort towards eco-driving, which in turn was predicted by self-concordance. Therefore, individuals pursuing eco-driving out of strong interest or deep personal beliefs (i.e., autonomous motivation) as opposed to external forces or internal pressure (i.e., controlled motivation) reported greater effort towards this behavior. Furthermore, biospheric striving coherence, i.e., the coherence between biopsheric values (addressing the well-being of the environment/biosphere) and eco-driving, significantly predicted effort towards eco-driving. These findings allow the conclusion that autonomous rather than controlled motives and coherence between behavior and intrinsic rather than extrinsic values are relevant predictors of eco-driving. To gain insights into the relationship between autonomous motivations and behavioral costs for eco-driving, in study 2, data of two online surveys was analyzed (NStudy2.1 = 207, NStudy2.2 = 539). The analyses indicate that high autonomous motivations for eco-driving can buffer the negative effect of behavioral costs on eco-driving. Furthermore, the results indicate that high autonomous motivations predicted eco-driving behaviors better when these behaviors are associated with moderate than with very low behavioral costs. Therefore, eco-driving interventions should focus on how autonomous motivations can be influenced. However, changing (perceived) behavioral costs of eco-driving may also be a promising intervention technique. Study 3 examined the interactive influence of contextual factors (i.e., charging delay, walking distance, price saving) and behavioral interventions (i.e., CO2 emission cues, collecting points, information about others’ behavior) on pro-environmental charging decisions in an online experiment with current and potential future electric vehicle owners (N = 286). The results show that the interventions influenced the decision to choose a pro-environmental charging station over a convenient non-sustainable alternative when behavioral costs were small to moderate. In situations with no or only negligible extra costs, participants did not need additional persuasion, whereas in high-cost situations, behavioral interventions were insufficient to influence pro-environmental behavior. To extend these insights, study 4 aimed at investigating if eco-driving behaviors could be motivated by symbolically and/or monetarily framed benefits (i.e., framing interventions). Hence, to investigate if and how eco-driving tips with framed behavioral consequences promote eco-driving motivations and behaviors in everyday life, a longitudinal online experiment with German vehicle owners over the course of one month (NT1 = 281; NT2 = 228) was conducted. Participants were randomly assigned to a framing group, in which either CO2, pollutant (e.g., NOx), or monetary savings of eco-driving were highlighted, or the control group. The findings indicate that participants rated the CO2/pollutant savings (i.e., symbolical benefits) as worthier than the monetary savings. However, individuals who were exposed to framed eco-driving information independent of framing content reported an increase of eco-driving behavior, compared to the control group. Therefore, differently framed eco-driving tips motivated self-reported eco-driving behaviors that are associated with low to moderate behavioral costs. Because psychological and contextual factors were identified as relevant impact factors of eco-driving behaviors, study 5 set out to explore if a combined intervention addressing multiple motives could influence actual eco-driving behavior change. Therefore, an experimental driving study with 94 German drivers was conducted to analyze how combined interventions affect pro-environmental charging and eco-driving behavior with an electric vehicle. The findings suggest that a combined intervention with informational cues (i.e., CO2 emission savings) as well as gamified (i.e., a competitive task) and monetary incentives did not significantly motivate individuals to choose a charging station that provides renewable electricity but requires a walking detour. However, the intervention did motivate individuals to seek eco-driving information (e.g., use eco mode). Being interested in eco-driving behaviors helped to improve (i.e., reduce) energy consumption during a real-world drive. To summarize, the present dissertation contributes valuable empirical results that broaden and deepen the understanding of various eco-driving behaviors (e.g., charging an electric vehicle with renewable electricity, driving at moderate speed). First, the findings indicate that environmental and autonomous motivations as well as behavioral costs are important determinants of eco-driving behaviors and that these two factors have interactive instead of additive effects on pro-environmental driver behaviors (studies 1, 2, 3). Second, the findings of the dissertation indicate that interventions that inform individuals why and how to behave pro-environmentally and stimulate environmental and autonomous motivations provide promising results for low- and moderate-cost eco-driving behaviors (studies 3, 4, 5). However, for high-cost driver behaviors, informational interventions are not sufficient but should be combined with hard measures instead, e.g., structural changes or financial incentives. Hence, researchers and policy makers should consider that eco-driving interventions need to a) address environmental and autonomous motivations and b) be tailored to the contextual factors (i.e., behavioral costs) of the behavior that is aimed at being changed or tailored to the situation in which the behavior arises.