To date, there is no developed and validated way to assess urban smartness. When evaluating smart city mobility systems, different authors distinguish different indicators. After analysing the evaluation indicators of the transport system presented in the scientific articles, the most relevant and influential indicators were selected. This article develops a hierarchical evaluation model for evaluating a smart city transportation system. The indicators are divided into five groups called “factors”. Several indicators are assigned to each of the listed groups. A hybrid multi-criteria decision-making (MCDM) method was used to calculate the significance of the selected indicators and to compare urban mobility systems. The applied multi-criteria evaluation methods were simple additive weighting (SAW), complex proportional assessment (COPRAS), and technique for order preference by similiarity to ideal solution (TOPSIS). The significance of factors and indicators was determined by expert evaluation methods: the analytic hierarchy process (AHP), direct, when experts evaluate the criteria as a percentage (sum of evaluations of all criteria 100%) and ranking (prioritisation). The evaluation and comparison of mobility systems were performed in two stages: when the multi-criteria evaluation is performed according to the indicators of each factor separately and when performing a comprehensive assessment of the smart mobility system according to the integrated significance of the indicators. A leading city is identified and ranked according to the smartness level. The aim of this article is to create a hierarchical evaluation model of the smart mobility systems, to compare the smartness level of Vilnius, Montreal, and Weimar mobility systems, and to create a ranking.

The development of science and technology parks (STPs) has become a trendy tool for promoting the economy, innovation, and technology for more than 30 years worldwide. However, STPs poses challenges for urban planners seeking a vision of sustainable urban development. These places become an object of attraction for many highly skilled workers who create daily traffic flows. The proper accessibility and provision of transport infrastructure and services become the challenge for the development of such places because the availability of services influences the choice of travel mode and the possible employees’ travel behaviour. The authors of the research aim to assess the level of development of infrastructure and transport services conducive to the sustainable mobility of science and technology park staff in Vilnius city. Changing mobility behaviour into a more sustainable way is of interest to many scientists and practitioners, so the authors think that STP staff can represent a group of educated, working-age stakeholders within the city population, who has an interest in sustainable mobility travel options and can set an example of sustainable travel. Besides, recommendations for the planning and sustainable development from the sustainable urban mobility point of view of science and technology parks and similar institutions are provided. To achieve this goal, the authors use scientific empirical and theoretical research as well as multi-criteria decision-making (MCDM) methods. The results show the link between the distance from the developed STP site to the city centre and the more sustainable mobility of workers. Therefore, it is suggested to develop STPs closer to the urban centre as it often does not require large-scale development, nor do they engage in the polluting industry. Moreover, the authors suggest the key criteria that should be considered for STP development.