Theories on value creation, co-innovation and co-development and lean enterprise have gained in popularity in recent times. This research has taken aim at extending the investigation on how to quantify companies’ capabilities in creating value for their stakeholders. A theoretica
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Theories on value creation, co-innovation and co-development and lean enterprise have gained in popularity in recent times. This research has taken aim at extending the investigation on how to quantify companies’ capabilities in creating value for their stakeholders. A theoretical framework was adopted to build the performance measurement method on. This framework identifies five performance indicators of company performance: competition performance, financial performance, manufacturing capability, innovation capability and supply chain relationships. Due to the limited availability of data in aviation industry, use was made of data from the automotive industry. Data from 33 automotive OEMs was collected from which a set of variables was constructed. The behavior and relations of these variables were investigated and eventually five variables were selected, one for each performance indicator. Using multiple regression techniques weight factors were determined for each variable and a linear model was constructed, expressing a company performance index. This linear model allows assessing and comparing the performance of different companies over an arbitrary period of time. For the automotive OEMs this was qualitatively shown to work. The model was then adapted to fit the aerospace OEMs and the weight factors were recalculated. Unfortunately, due to the limited availability of data for aerospace OEMs, it was not possible to obtain great insights into the behavior and relations of the variables for these aerospace companies. Moreover, the weight factors of the linear model could not be determined with much accuracy. To solve this, it is recommended that for future research data collection continues and that in some years the research is redone with more data, allowing statistical analysis to be able to detect smaller effects.