## 2 Literature Review
### MaaS Concept  
MaaS, in general, aims to integrate the offerings of mobility service providers into a single digital platform for journey planning, booking, payment and (e-)ticketing [6,14]. They state that mobility service integration can be broken down into four hierarchical levels: (1) journey planning (which is the most basic function of a MaaS app and the theme of this work); (2) purchase and ticketing; (3) bundles and subscription plans; (4) addressing societal goals such as reducing emissions and congestion using behaviour-nudging incentives. MaaS apps can also provide live routing navigation once a journey is begun, which helps to ensure that the most efficient routes are followed. Ref. [15] shows that people do not always opt for the shortest paths without the aid of navigation. A central goal of MaaS is to reduce high private car dependency [16]. Ref. [17] outlines a research agenda for MaaS enablement, highlighting that a move away from private car ownership comes with a natural increase in demand for convenient and seamless shared mobility offerings. According to [18], the convenience benefits of MaaS include smart ticketing, which also provides an institutional coordination mechanism for facilitatingcooperation. MaaS is also touted as a means for improving social equity. Ref. [19] proposed the MaaSINI: a MaaS inclusion index to evaluate the inclusivity and accessibility of MaaS considering vulnerable social groups' needs, such as the elderly, people with disabilities and low-income people. Ref. [20] attempts to answer the question of whether or not MaaS can change user travel behaviour and deliver commercial and societal benefits. It is reported that MaaS may help to reduce car ownership, but this may be offset by an increase in the use of other car-based modes, such as taxi services or Uber. Evidence was found that suggests that investment in MaaS does bring about net reductions in CO\({}_{2}\). Regarding the demographic groups that are most likely to adopt MaaS as their alternative to private car ownership, [PERSON]. [21] performed a latent class cluster analysis of attitudes and found that the largest cluster is most likely to adopt MaaS, while current uni-modal car users are least likely to adopt MaaS. This suggests that the natural bias against car-based transport modes of many MaaS trials may be counter-productive to the aims of the MaaS movement. Instead, by embracing car-sharing and taxi services in MaaS apps, current uni-modal car users may be more inclined to explore the many benefits of MSP integration through MaaS apps. Emerging convenient demand responsive bus services [22] may also sway private-car users and/or those undergoing life changes. The success of MaaS trials relies on different aspects, such as business models and how MaaS can match MSP offers with a traveller's needs. [PERSON]. [23] evaluated different business models and structures in the context of MaaS and concluded that it is important to consider different market structures since, in certain cases like intermediary settings, prices tend to be significantly higher with low profitability. Recently, [PERSON]. [24] developed a novel mechanism for MaaS to solve matching and pricing problems between MSPs and travellers. They presented an initial approach that utilised a static offline mechanism employing a pricing scheme derived from the Vickrey-Clarke-Groves model. The proposed mechanism is designed to prioritise incentive compatibility, individual rationality and system efficiency. Additionally, they introduced an online mechanism that employs a dynamic learning algorithm to generate a solution that closely approximates optimality. A customised greedy-based algorithm is used for comparison alongside this online approach. Ref. [25] also developed incentive-compatible mechanisms for the online mobility-resource-allocation problem.