## 6 Review of Studies Related to Micromobility in the Context of Multi-Modal Mobility
### Potential Future Research Directions  
The above review of the recent papers related to bike, micromobility and scooter in the context of multi-modal mobility indicates that several research issues or questions have been studied. Several potential future research directions based on the review of the papers in the previous subsection are summarized in this subsection. Impacts and substitution effects of micromobility  
The study [92] focused on developing a spatial agent-based model to study the impacts of bike-sharing on travelers' usage of other transport modes through simulation. There are several directions for future research: (1) introducing weather factor in the model and studying the effects of weather, (2) studying the leisure travel and (3) incorporating psychological factors such as comfort and perceptions of safety in the agent decision-making model. Although the study [93] lacks consideration of the substitution of private cars by dockless bike sharing, the proposed analysis framework is general and can be used for analyzing the mode substitution of e-scooter and e-moped sharing. An interesting future research direction is to compare the mode substitution rates of dockless bike sharing and e-scooter sharing systems. Performing similar analysis for other cities with distinct urban structures/culture and comparing the results to identify potential new findings is an interesting research direction. The study [94] focused on the co-evolution between taxi demand and shared-bike demand to understand the connection between these two transport modes. An interesting direction for further study is the investigation of the co-evolution patterns between other transport modes such as subway demand and taxi demand. The paper [95] identified potential temporal and weather-related determinants for station-based round-trip bike sharing rentals by applying multiple linear regression and an in-depth analysis. Validity about whether the findings of the study hold during post COVID-19 period requires further study. As the limitations of the proposed approach is due to multiple linear regression, conducting a similar study based on advanced methods to identify determinants is an interesting issue. Capturing other determinants of station-based round-trip bike sharing, e.g., events and service disruptions, is a potential future research direction. The work [96] studied the characteristics of different modes of micromobility as well as the complementation or competition between them. The results of [96] were obtained without the information of the actual trip purpose of the different traffic modes. A future research direction is to incorporate a survey of trip purposes to derive more detailed results, including the usage between micromobility and geographical information as well as the reasons for using micromobility. Characteristics and adoption factors of micromobility in multi-modal transport networks  
The analysis of the distributions of trip distance and trip duration of bike sharing travel patterns in the study [61] was based on bike sharing trip data with only trip origin, destination time and location. An extended study is required for the detailed trajectory data of the bike sharing trips. The study [61] focuses on the analysis of the bike sharing travel patterns for station-based bike sharing systems. Analysis of dockless bike sharing systems is an interesting future research direction. The goal of the study [60] was to study the propensity for public transport users to shift to the bicycle to access bus stops, train and metro stations in Rio de Janeiro. There are several directions for future research:  
1. An urgent research issue is to study the effectiveness of using bicycle to access different transport modes (metro, bus and train). 2. The results of the study were based on work/school trips. Whether the results will be the same for other trip purposes requires a further study. 3.