A methodology is proposed for evaluating the level of service within an airport landside system from the passenger's point of view using linguistic service criteria. The new concept of level of service for a transport system, particularly within the airports indicates that there must be strong stimulation in order to proceed with the current stereotyped service standards which are being criticised due to their being based on, either physical capacity/volume or temporal/spatial standards that directly incorporates the perception of passengers, the dominant users. Most service evaluation methodologies have been concentrated on the factors of the time spent and the space provided. These quantitative factors are reasonably simple to measure but represent a narrow approach. Qualitative service level attributes are definitely important factors when evaluating the level of service from a user's point of view. This study has adopted three main evaluation factors: temporal or spatial factors as quantitative measurements and comfort factors and reasonable service factors as qualitative measurements. The service level evaluation involves the passenger's subjective judgement as a perception for service provision. To evaluate the level of service in the airport landside system from the user's perception, this research proposes to apply a multi-decision model using fuzzy set theory, in particular fuzzy approximate reasoning. Fuzzy set theory provides a strict mathematical framework for vague conceptual phenomena and a modelling language for real situations. The multi-decision model was applied to a case study at Kimpo International Airport in Seoul, Korea. Results are presented in terms of passenger satisfaction and dissatisfaction with a variety of different values.

The increasing population leads to higher passenger travel demand in Stockholm. The public transport becomes more and more crowded in rush hours. However, passengers carry out decisions usually based on limited traffic information and their travel experience. Passengers cannot take the initiative to avoid crowding based on existing SL traffic information. Real time crowding information (RTCI) research aims to help passenger to have more initiative to plan their travel in metro system, and assist operator to have higher space utilization efficiency. RTCI system contains4 subsystems: projection system, communication system, speaker system and recording system. The practical test was applied in Tekniska Högskolan metro station for two weeks in May 2015 with the permission from SL. The triangle analysis was applied to analyze the impacts of RTCI. The analysiscontains three analysis methods: passenger load data analysis, video record analysis and interview result analysis. The interview result shows RTCI increased round nine tenth of passengers ‘satisfaction and 43% of interviewees thought it was very useful for them. The calculation based on video record and interview result shows that 25% of passengers consulted this information and changed their behaviors on platform. According to the video record, the path became wider and passenger flow became smoother while RTCI system was activated. Passenger distribution was more even in metro based on passenger load data. The number of passengers who got into last unit train increased 8%, and the number in first and second unit train decreased 4% during RTCI practical test. The thesis mainly focused to analyze the impacts of RTCI instead of solving technical challenges. But the technical solution for RTCI system was proposed in thesis. The concept - “Smart Travel” was discussed in chapter11 which mainly considers travel time, crowding information and travel cost as most important factors to passenger.

While there has been considerable research regarding the role of Mobility Hubs in cities and transport networks, significant investment is required to develop these facilities. It is the correlation between investment, new users’ attraction and revenue generation that is the key for a sustainable development of Mobility Hubs and this investment must, therefore, be correctly assessed and targeted. This study aims to develop a methodology to determine the viability of investing in Mobility Hub features, weighing the investment on different Hub features and services against expected potential benefits and revenue generation, addressing the question: Can investment in Mobility Hub features be justified and, if so, which features maximize its expected positive impact? Based on a review of literature and definition of possible Hub features as variables, secondary research data was compiled to enable the analysis of expected impacts of each variable/feature in terms of new user’s attraction and revenue generation, which was then used to develop individual Net Present Value analysis of each feature. The result of these analysis demonstrates and concludes that different Hub features have the potential to generate substantially different investment outcomes, and that each feature should be analyzed individually prior to investment decision. It was also concluded by this research that the proposed assessment methodology can be used for future research on other listed Hub features, albeit with the constraint that primary data will be required when secondary research data is not available.