| Abstract |
The concept of Mobility as a Service is still a fresh concept, yet growing fast and have great potential to exploit, nevertheless, it requires a good understanding and a clear perception of its ecosystem, business models and data to define the right strategies of development. The research is about MaaS data exploitation for city planning, we are trying to uncover more on the exported MaaS data features and their compatibility with the good practices of city planning. To assess and measure the appropriability of this idea, Natural Language Processing algorithms were used to extract keywords related to "data" from the websites and the official documents of MaaS corporations and matched them with the relevant smart city and SDGs domains using machine learning. Measuring the compatibility and the possibilities of exploitation, is a great step towards discovering and introducing more data sources and opportunities to enhance the city planning practices and improve the decision-making system with data-integrated solutions. It also enlarges the vision of the researchers, mobility and city planning experts to develop and explore more in the urban mobility data. |
