The focus of this research is on Multi Criteria Decision Making (MCDM) in complex multi actor environments. Within the field of MCDM, the Analytical Hierarchy Process (AHP) is known for its usage in complex situations. Therefore the focus will be on AHP as a well-known and often used MCDM. This study can function as a benchmark for other MCDM applications in complex multi actor environments. A case study, regarding the widespread acceptance of electric cars, is conducted in order to test for differences in results while applying AHP in homogeneous versus heterogeneous environments. When multiple decision makers are interviewed, for the purpose of AHP application, their judgments will differ and they should, as a group, take all criteria into consideration and seek political consensus. This works well in a decision situation where one decision has to be made and the group of decision-makers is homogeneous; in situations where the group is heterogeneous it is difficult to come to a consensus. When consensus cannot be reached the other option is to calculate the mean. When for example comparing the maximum range and the amount of reduced CO2 footprint in the case study, someone with a background in green energy production thinks the CO2 part is much more important than range. On the other hand someone from the traditional car industry thinks range is way more important than the CO2 footprint. The representing values in the AHP analysis will then be: 1/9 & 9. When applying the geometric mean, a 1 is used in the model. Which basically says these two criteria are equally important. This means these criteria will not play a key role in the calculations. However when looking at the individual preferences this pairwise comparison is a very important one. The assumption is that this misinterpretation of values is due to heterogeneity in groupings, while homogeneity is assumed. Therefore better grouping, which seeks more homogeneity, is needed when the AHP method is applied in complex multi actor situations. In order to reach this homogeneity, multiple tools have been investigated. The technique found to be most suitable for this research is market segmentation. Usually this tool is applied in marketing and its usage in combination with the AHP method is applied for the first time in this research. After the tool selection process it needed to be tested. This is done by means of the case study. In this case study a survey is conducted that consisted of two types of questions. Part one consists of market segmentation questions, which enables us to segment the participants based on generic features such as gender and age. Part two consists of AHP related questions that enables us to calculate the weights per (sub) criterion. After the survey is conducted two different analyses were performed. The first one, method A, applied the AHP method as it currently exists. The second, method B, includes the market segmentation part. First the heterogeneous group is reordered into several homogeneous groupings and for each of these groupings the AHP analysis can be conducted. When homogeneous segments provide the input, the homogeneity axiom is met again. The aim was to find differences in results for method A and B. In order to analyze all possible scenarios a special software tool has been developed which is able to calculate 500,000 scenarios within 8 hours. These calculations provided the knowledge that different market segments indicated different criteria as being their most important one. The application of method A indicated that ‘emissions’ is the most important factor regarding the widespread electric car acceptance. However, when applying method B, multiple segments are indicated in which other factors are more important. Therewith the added value of the newly suggested method has been proven. It is interesting that different segments can be identified when using different factors. Since there is freedom in which factors are being used, the analysis ensures a wide range of applicability, from policy makers towards executive boards. The findings of this research can introduce a future standard in MCDM, and especially in AHP application, in complex multi actor situations. Besides this it can be a basis for further research in this new field of application. In order to provide a robust basis a framework has been developed: “The two-step approach towards group decision making in complex multi actor environments”. Better use of the AHP method in complex multi-actor situations can be accomplished by ensuring that all groups that provide input, for the actual AHP analysis, are homogeneous. When groups are heterogeneous, as often is the case in complex multi-actor scenarios, the suggested framework should be applied in order to ensure better use.