Battery electric vehicles (BEVs) are considered an important contribution to the global task of creating a greener society as it allows for the benefits of commuting to sustain, without the consequence of pollution. Consequently, central and local governments across the globe are attempting to spark the diffusion of BEVs through various measures such as financial incentives, developing charging networks or other distinctive benefits. In this process, understanding and exploring the factors which affect consumers to transition from Internal Combustion Engine Vehicles (ICEVs) to BEVs is essential for the salient actors attempting to increase the adoption rates. In this thesis, we aim to add to this branch of BEV research by investigating the factors influencing consumers’ adoption intention of BEVs while introducing the element of consumers’ BEV knowledge and familiarity. To analyse these effects, a conceptual structural model based on an extended Technology Acceptance Model (TAM) was developed and analysed. The conceptual model involved a total of eight variables: Consumer’s knowledge, risk perception, perceived usefulness, attitude towards BEVs, BEV incentives, incentive awareness, intention to adopt a BEV, and the side-by-side comparison to ICEVs as a vehicle alternative. The model was then empirically tested through an extensive questionnaire survey involving data from 266 consumers in the BEV pioneer Norway. To collect this data, the researcher utilized a combination of snow-ball and convenience sampling where the survey was spread through online platforms. Further, the data was analysed through Structural Equation Modelling (SEM) in the software IBM SPSS AMOS to determine the validity of the conceptual model as well as the effect among the variables. To evaluate the results, a Confirmatory Factor Analysis (CFA) was performed. The results of this analysis indicated that the conceptual model was a good fit despite its complexity. In regard to consumer’s knowledge, the analysis indicated that there was a strong and significant total effect on the adoption intention of BEVs. More specifically, knowledge functioned as a strong predictor through mediating effects of increased perceived usefulness, improved attitude and reduced risk perception related to BEVs. In addition, Knowledge was found to have a strong and significant positive total effect on the mentioned side-by-side “comparison to ICEVs” variable. Further, through a separate regression analysis, the results also revealed the knowledge variables was found to have an explained variance of .3 in regard to the “intention to adopt” variable. This was significantly higher than any other variable in the analysis. Further, the analysis showed that perceived risks could be a considerable psychological barrier against accepting and adopting BEVs. This barrier, however, was significantly reduced in accordance with increasing levels of consumers’ BEV knowledge. Lastly among the SEM key findings, attitude towards BEVs was found to have the strongest direct effect on adoption intention in the model. A variable which again was found to be strongly positively influenced by consumer’s knowledge about the vehicles. The descriptive statistics of the analysis also found noteworthy characteristics in the sample population. For instance, the data revealed that the average knowledge and familiarity levels among the population were as high as 5.82 on the 7-point Likert scale used in the survey research. In combination with the discovered effect of knowledge (on “intention to adopt” and “comparison to ICEV”), this finding could indicate that high levels of BEV knowledge might be an important contributor to Norway’s disproportionately large adoption rates compared to that of other salient actors. One should be cautious, however, to draw this conclusion without performing a similar study in a comparable setting and location. Further, the statistics revealed an average score of 6.29/7 on the variable measuring the awareness of the government incentives in Norway. This is another strong sign that the country has succeeded in spreading information on the topic among its population. Another interesting finding in this regard was the low satisfaction levels with the Norwegian charging networks. With an average score of 3.62/7 (SD=1.57) among the sample, it is clear that a large part of the respondents are dissatisfied with the charging infrastructure. However, the low satisfaction levels do not seem to have a large impact on the intention to adopt BEVs as there was found no significant effect among these variables. A demographic regression analysis with the independent variables of gender, age and education on the dependent variable “intention to adopt” was also performed. This revealed that both gender and education had a small, yet significant effect on the dependent variable where men and high education was associated with higher adoption intentions. Age, on the other hand, had no significant effect. In sum, the main takeaway from this study is that consumers’ knowledge of BEVs should be taken into consideration when attempting to manage the adoption of the "green vehicles". Norway has succeeded in diffusing knowledge of BEVs and fiscal incentives within its population, and this might be part of the explanation for their disproportionally large adoption rates compared to other salient actors. The recommendation based on the results in this research is therefore that governments aiming to substitute ICEVs with BEVs should take measures to spread information and educate potential adopters on BEVs and its technology. Achieving this would improve the overall attitude towards BEVs, increase the perceived usefulness and limit the existing risk barriers. In turn, this would increase consumers’ willingness to adopt BEVs and contribute to the global task of creating a greener society.