Cooperation-Oriented Multi-Modal Shared Mobility for Sustainable Transport: Developments and Challenges

Abstract

There is an increasing adoption of shared mobility for improving transport systems performance, reducing excessive private vehicle use, and making full utilization of existing infrastructure in urban traveling. Despite numerous studies in exploring the use of shared mobility for sustainable transport from different perspectives, how it has improved the sustainability of existing transport and what impact it has on various stakeholders are unclear. Therefore, a systematic literature review was carried out in this study on developing and adopting shared mobility for pursuing sustainable transport in urban traveling. Four emerging themes were identified, including attitude and intention, cooperation behaviors, operations and decisions, and performance evaluation, and some research gaps and challenges are discussed. An integrated framework for developing cooperation-oriented multi-modal shared mobility is proposed. This leads to better understanding of shared mobility and its use for sustainable transport in urban traveling.

1. Introduction

With the growing population and increasing urbanization, the number of vehicles across the world is increasing rapidly [1,2]. As a result, urban transport systems are facing numerous challenges due to growing traffic congestion, increasing environmental pollution, and accelerating greenhouse emissions [3,4]. Therefore, developing sustainable transport in urban traveling through adopting cooperation-oriented mobility solutions is becoming critical [5].

Cooperation-oriented transport is about sharing and integrating all transport resources in urban traveling to improve the mobility of individuals [1]. This involves various stakeholders such as government departments, enterprises, public organizations, and individuals taking cooperative decisions from planning, design, construction, and management for the operations and maintenance of transport systems to meet multiple, often conflicting objectives [2,4]. Cooperation-oriented transport provides stakeholders with more flexible, reliable, safe, and convenient transport services [6]. This helps to address the growing challenge of urbanization and sustainable development.

The increasing use of cooperation-oriented transport leads to the wide adoption of innovative mobility solutions, including mobility as a service (MaaS) [2] and multi-modal shared mobility (MSM) [7]. MaaS bundles transport options from multiple providers into consolidated digital platforms for delivering integrated mobility services [5]. It provides travelers with the latest technologies to combine information from different transport modes and services with payment models and product packages [8,9]. MSM is a flexible and low-collaboration requirement transport form that links available transport modes through shared mobility, non-shared mobility, public transit, and automatic driving for enhancing mobility [7,10]. Such mobility solutions share many common features and are, therefore, often lumped together in pursuing sustainable transport in urban traveling. The adoption of such innovative solutions has demonstrated their potential in addressing the emerging challenges of urbanization and enhancing the sustainability of urban transport systems [11].

The growing adoption of innovative mobility solutions has led to numerous studies to understand their use in urban traveling [11]. Despite such studies exploring the application of shared mobility solutions in urban transport, how such applications have improved the sustainability of existing transport systems and what impact they have on individuals are unclear. Therefore, a research question was formulated in this study for addressing these issues as follows: What are the latest developments and challenges in pursuing cooperation-oriented multi-modal shared mobility for sustainable transport?

This study carried out a systematic review of the related research in shared mobility for sustainable transport. The review was conducted based on Emerald, ScienceDirect, SpringerLink, and Web of Science during the last ten years. Four emerging themes from existing studies including (a) attitude and intention, (b) cooperation behaviors, (c) operations and decisions, and (d) performance evaluation have been identified, and existing research gaps and challenges are discussed. An integrated framework is proposed for developing cooperation-oriented multi-modal shared mobility, leading to better use of shared mobility for pursuing sustainable transport in urban traveling.

In what follows, the systematic review method is given in Section 2. A descriptive analysis of the identified literature is then described in Section 3. The emerging themes on shared mobility use for sustainable transport are identified and discussed in Section 4. Existing research gaps and challenges in utilizing shared mobility for sustainable transport are then elaborated in Section 5. An integrated framework and the conclusion are finally presented in Section 6 and Section 7, respectively.

2. The Review Method

This study followed a structured approach in conducting a systematic review in exploring the utilization of shared mobility for developing sustainable transport [12]. The adoption of this approach required defining the review scope first before determining the terms for searching the selected database [13]. This led to the determination of the review sample and the examination of the selected sample. Finally, the review results could be summarized for reporting. This systematic review process is presented in Figure 1.

The review scope determines the boundary of the topic, the sources, the type of literature, and the criteria and methods that the study used to select, evaluate, and synthesize the literature [13]. This study sourced the literature from Emerald, ScienceDirect, SpringerLink, and Web of Science because these databases have an extensive coverage and strong representation in the publication of quality articles in shared mobility [14,15].

Several search terms have been used for ensuring a broad coverage of the study including ‘shared mobility’, ‘cooperation consciousness’, ‘conscious cooperation’, ‘travel behavior’, ‘ridesharing’, ‘ride-hailing’, ‘car sharing’, ‘bike sharing’, ‘on-demand service platforms’, ‘MaaS’, ‘MSM’, and ‘sustainable transport’. Adopting these search terms in the search ensured that the major relevant literature in shared mobility could be identified [16].

Several criteria were adopted in the study to ensure the selection of the most relevant articles for further analysis. The document type, for example, was restricted to scholarly journals. The language was limited to English. The selected articles were published between 2014 and 2024. Conference papers, book chapters, and white reports were not considered. Such articles may offer valuable insights. Peer-reviewed journal articles, however, are more indicative of cutting-edge research with higher impact [13].

The determination of the review scope and the search terms led to the implementation of the search queries in the selected databases. This resulted in the retrieval of 2172 articles from these four databases, which showed that shared mobility is a widely covered concept for developing sustainable transport in urban traveling.

The initial search result above was further screened to determine the final sample for detailed analysis. Such a screening process was carried out manually with the focus on the title and the abstract of each article for checking their relevance to this study [12]. As a result, 201 articles were selected. After removing the duplicated articles, 84 articles were obtained for further analysis.

The selected sample was finally coded and analyzed manually. Similar themes were grouped together. Four emerging themes were then identified. Existing research gaps and challenges in developing shared mobility for sustainable transport are discussed.

3. Descriptive Literature Analysis

The sample of the identified articles was examined with respect to (a) publication trend, (b) publication outlet, (c) article distribution across the databases, and (d) study context (approaches, methods, and theoretical lens). Figure 2 presents an overview of the publication trend over time. It reveals that there is a non-linear time trend across the past ten years. However, there appears to be increasing interest in shared mobility. Of the 84 articles identified, 78 articles were published in 2019 and after.

The publication outlets of the sample articles were analyzed. Figure 3 presents the distribution of the articles across different outlets. It shows that most selected articles are from high-quality outlets, as listed in Figure 3. It reveals that Transportation Research Part A and Part B published the most articles on shared mobility, followed by Part C and Travel Behaviour and Society.

The distribution of the articles in the four databases was analyzed. As shown in Figure 4, ScienceDirect and Web of Science are the two prevailing databases that track the publication of most articles.

The study context of the sample was examined.

Table 1. Studies on research approaches, methods, and theoretical lens.

Approaches	Methods	Theories/Models	No. of Articles
	Review	None	7
Qualitative	Interview	Social practice theories, dynamic capability theory, systems theory	3
	Case study	Innovation theory, stakeholder theory, supply–demand value proposition, technology–organization-environment framework	8
	Field study	Stakeholder theory, organizational socialization framework	4
Quantitative	Survey	Econometric model, behavioral theory	17
	Modeling, Simulation	Game theory, evolutionary game theory	7
		Mathematical model	16
	Experiment	Data mining, statistical techniques	9
Mixed-methods	Interview + Survey	None	4
	Case study + Survey	None	6
	Other	None	3

presents the results. It shows that survey and simulation are the prominent methods in quantitative studies and case studies, and field studies are the mainstream method in qualitative research. The study further reveals that econometric modeling with behavioral theories is the prevailing framework. It also finds that mixed-methods approaches and experiments demonstrated their applicability in shared mobility studies.

4. Emerging Research Themes

An examination of the sample led to the identification of four themes in exploring the use of shared mobility for sustainable transport in urban traveling. These four themes include (a) attitude and intention, (b) cooperation behaviors, (c) operations and decisions, and (d) performance evaluation, discussed as follows.

4.1. Attitude and Intention

Exploring individuals’ attitudes and intentions in utilizing shared mobility for pursuing sustainable transport has attracted increasing interest, leading to numerous studies being conducted. Such studies can be classified into sub-themes of (a) understanding individuals’ attitudes, (b) exploring individuals’ intentions, and (c) investigating the willingness of individuals to pay (WTP).

Attitude-based studies focus on what motivates individuals in adopting shared mobility for sustainable transport. Ciasullo et al., for example, explored the use of carpooling in urban traveling based on text analysis, finding that economic performance, environment consideration, comfort, traffic, socialization, reliability, and curiosity are critical to carpooling use [17]. Moody et al. investigated the adoption of Uber and Lyft, revealing that individuals’ discriminatory attitude is critical to their use [18]. Ahmed et al. examined how user satisfaction in adopting ridesharing is influenced, discovering that perceived quality and value for money are the critical determinants for its use [19]. Li et al. showed that the critical determinants for utilizing ride-hailing services depend on user orientation, travel characteristics, and perceived performance in urban traveling [20].

Intention-oriented studies concentrate on investigating what affects the intention of individuals to adopt shared mobility products and services in urban traveling. Mattia et al. and Chahine et al., for example, revealed that subjective norm, perceived behavioral control, and attitude affect individuals’ intention to adopt shared mobility products and services [21,22]. Herberz et al. found that environmental concerns, status, financial situation, independence, safety, and hedonic motives are critical for individuals’ intentions to utilize shared mobility solutions [23]. Duan et al. discovered that costs, network externality, institutional factors, behavioral factors, environmental concerns, travel options, and socio-economic influence are critical to the intentions of individuals in using MaaS [5]. van Veldhoven et al. demonstrated that environmental value, ease of use, time saving, ownership, price, compatibility, digital savviness, and hedonic motivations are critical to individuals’ intentions to utilize shared mobility [24]. Molla et al. stated that platform personalization, customizability, functional integration, network integration governance, and information schema congruity affect individuals’ intentions to utilize shared mobility solutions such as MaaS [2].

WTP-aligned studies examine how much individuals are prepared to pay for mobility products and services and identify what influences their WTP. Asgari and Jin, for example, investigated individuals’ WTP for the use of autonomous vehicles, finding that driving pleasure, reasons for mode choice, trust, and technical savvy are the critical determinants [25]. Liljamo et al. explored individuals’ WTP for MaaS offerings, discovering that mobility costs, household’s income and gender are the dominant factors [26]. Vij et al. surveyed 3985 representative Australians about their use of MaaS, revealing that age and lifecycle stage are the critical determinants in predicting individuals’ WTP for MaaS products [27]. Lopez-Carreiro et al. discovered that the need for control, privacy concerns, environmental awareness, and services integration are the critical determinants of individuals’ WTP for MaaS [28]. Lopez-Carreiro et al. examined individuals’ WTP for MaaS, highlighting that demographic, socio-economic, and travel-oriented variables are critical [29].

Table 2. Attitude- and intention-based studies.

Themes	References	Approaches	Critical Factors/Main Findings
Attitude	[17]	Text analytics	Economic and environmental efficiency, comfort, socialization, reliability, curiosity
	[18]	Survey	Discriminatory attitude
	[19]	Survey	Perceived quality, value for money
	[20]	Multinomial logistic model	User orientation, travel characteristics, perceived performance
	[30]	Latent class analysis	Benefits and barriers
Intention	[21]	Structural equation modeling (SEM)	Attitude, subjective norm, perceived behavioral control
	[23]	SEM	Environmental motives, status, financial, independence, safety, hedonic motives
	[5]	Survey	Costs, network externality, institutional factors, behavioral factors, environmental concerns, options, socio-economic influences
	[24]	Confirmatory factor analysis (CFA)	Environmental value, ease of use, time saving, ownership, price, compatibility, digital savviness
	[2]	Survey	Personalization, customizability, functional integration, network integration governance, information schema congruity
	[22]	SEM	Attitudes, perceived behavioral control, and social norms
WTP	[25]	SEM	Driving pleasure, reasons for mode choice, trust, technical savvy
	[26]	Linear regression	Costs, income, gender
	[27]	Survey	Age, lifecycle stage
	[28]	Cluster analysis	Control, privacy, environmental awareness, services integration
	[29]	Gologit model	Demographic, socio-economic, travel-related variables

summarizes these related studies.

4.2. Cooperation Behaviors

Cooperation is about individuals working together to achieve common objectives [31,32]. Individuals make pro-social choices through cooperation, even if such choices impose greater costs or confer less benefits [33]. In transport, cooperation behaviors are about individuals making specific travel decisions for communities’ benefits in a voluntary manner, such as adopting shared mobility solutions [1].

Understanding what cooperation behaviors are and how cooperation behaviors can be formulated directly affect the development of shared mobility for sustainable transport [34]. An examination of such studies in this perspective has identified three sub-themes including (a) behaviors patterns, (b) critical factors for adopting cooperation behaviors, and (c) formulation and evolution of cooperation behaviors.

Behavior pattern-based studies focus on understanding the cooperation behavior in utilizing shared mobility using some common theories. Chen and Deng, for example, presented a conceptual framework to examine the interplay between social networks, information use, and conscious cooperation in shared mobility use, leading to three common cooperative behavior patterns being identified [4]. Biehl et al. investigated the shift from using private vehicles to adopting shared mobility solutions from the community perspective finding that there is a significant difference in the utilization of shared mobility in different communities [35]. Young and Farber examined the difference between ride-hailing users and other mode users regarding their socio-economic characteristics, discovering that ride-hailing is a phenomenon of wealthy young people [36]. Bi and Ye investigated travel behavior of ride-sourcing users, leading to the identification of several user patterns through fusing Didi ride-sourcing data using the Latent Dirichlet Allocation model [37]. Vega-Gonzalo et al. explored how shared mobility use affects car ownership in various population and geographic areas, discovering that the availability of shared mobility solutions can reduce private car ownership [38].

Critical factor-based studies concentrate on understanding what affects the development of cooperation behaviors in shared mobility. Acheampong et al., for example, explored ride-hailing adoption in Ghana, finding that ease of use, safety risks, control, and a car-dependent lifestyle significantly affect ride-hailing use [39]. Schikofsky et al. discovered that autonomy, competence, the need of relating to peer groups, and expected usefulness are critical for the adoption of shared mobility [40]. Lesteven and Samadzad explored the behavior of ride-hailing users in Tehran, finding that smartphone use and income level are critical [41]. Shi et al. revealed that accessibility to bus stations negatively affects the utilization of ride-hailing in Chengdu [42]. Zhou et al. showed that weather conditions, travel time, and safety significantly influence shared mobility adoption in Nanchang [43].

Some studies have been conducted in examining the formulation and evolution of cooperative behaviors in adopting shared mobility. Anagnostopoulou et al., for example, investigated how individuals change their mobility behaviors, finding that there is a positive behavioral change for more sustainable choices in utilizing shared mobility [44]. Chen proved that cooperative behaviors can be developed under specific conditions [45]. Chen presented a dynamic model for developing cooperative behavior in the use of shared mobility, discovering that such behavior is associated with information use and social networks [46]. Li et al. presented a mathematical model for developing cooperative behavior in utilizing shared mobility [47]. Gao et al. revealed that a non-linear relationship exists between bike-sharing and ride-hailing in the adoption of shared mobility for sustainable transport [48].

Table 3. Cooperation behaviors-based studies.

Themes	References	Approaches	Critical Factors/Main Findings
Behavior patterns	[4]	Cluster analysis	Three cooperation behaviors patterns
	[35]	Focus group	The acceptance of shared mobility is different in communities
	[36]	Statistical analysis	Ride-hailing is related to wealthy young people
	[37]	Data mining	Ride-sourcing user patterns
	[38]	Modeling	Shared mobility reduces car use
Critical factors	[39]	SEM	Ease of use, safety risks, control, car dependent lifestyle
	[40]	SEM	Autonomy, competence, feeling of being social groups, usefulness
	[41]	Logit model	Smartphone use and income level
	[42]	Logistic model	Accessibility to bus station
	[43]	Logit model	Weather conditions, travel time, safety
Formulation and evolution	[45]	Game theory	Cooperation behaviors
	[44]	Experiment	Positive results on behavioral changes
	[46]	Latent class cluster analysis	Cooperation is related to information use and social networks
	[47]	Game theory	Cooperation can be developed
	[48]	Random forest model	Bike-sharing and ride-hailing have non-linear effects on the use of metro

summarizes the above discussion.

4.3. Operations and Decisions

Individuals’ attitudes, intentions, and behavior are critical for utilizing shared mobility in pursuing sustainable transport [1]. Understanding cooperation behaviors in shared mobility adoption, therefore, requires exploring shared mobility operations and decisions at strategic, tactical, or operational layers [49]. This results in many studies being conducted from the perspective of specific shared mobility modes, MaaS, and MSM.

Single mode-based studies examine the adoption of specific shared mobility solutions and their impact. Hong et al., for example, developed a ride-matching method to support better decisions for carpool commuters [50]. Chen et al. proposed a dynamic programming model for helping platforms better adjust supply and demand for optimizing their operations performance [49]. Jian et al. presented a comprehensive operation scheme to integrate shared vehicles and shared parking for improving the total social benefit of utilizing shared mobility [51]. Ke et al. constructed a ride-hailing model for investigating how ride-pooling affects traffic congestion and travel time [52]. Sun et al. developed a theoretical model for exploring how ride-hailing platforms allocate customer requests to two (Inform and Assign) matching systems in facilitating the mobility of individuals [53]. Yan et al. found that combining dynamic pricing and waiting mechanisms can optimize ride-hailing platform operations [54]. Nguyen et al. proposed an activity-based travel demand model to understand the operations of car-sharing services [55]. Xu et al. developed a generalized framework for examining how various operations strategies affect transport systems performance in pursuing sustainable transport [56]. Guo et al. presented a theoretical framework to better address the fragmentation of shared mobility markets with healthy competition between shared mobility providers [57].

MaaS-oriented studies explore the strategic or operational decisions of MaaS offerings with a focus on functionalities, customization, and integration of specific societal goals. Karlsson et al., for example, proposed an analytical framework for MaaS development and implementation at the macro, meso, and micro levels in urban traveling [58]. Meurs et al. proposed a comprehensive framework for developing cooperation between and among transport providers in MaaS [59]. Butler et al. developed a conceptual framework to help guide future research and MaaS development [11]. Guyader et al. examined MaaS adoption, revealing that institutional logics are the underlying reason for the tension in stakeholder collaboration [60]. Alyavina et al. discussed the key dimensions of MaaS and contextualized its operational management for long-term sustainability [9]. Athanasopoulou et al. explored the features of MaaS platforms, finding that individuals prefer non-feature requirements more than feature ones [61]. Xi et al. proposed a mathematical model for maximizing the profit of MaaS platforms through making effective operational decisions [62]. Yao and Zhang developed a matching framework for joint pricing and assigning decisions in the multi-modal transport network that incorporated MaaS products and services [63].

MSM-aligned studies explore the impact of MSM operations and decisions on stakeholders. Cohen and Kietzmann, for example, discussed how existing MSM business models affect the relationship between MSM providers and governments for sustainable transport [64]. Ambrosino et al. introduced a conceptual framework for managing different transport services through using services agencies [65]. Meng et al. found that the availability of various mobility modes improves individuals’ accessibility to meet multiple, often conflicting objectives of various stakeholders [7]. Shokouhyar et al. conducted a three-phase study, leading to the identification of 18 challenges and 12 constructs to the sustainability of MSM [66]. Deng et al. designed a profit-sharing scheme for improving the profitability of digital platforms through cooperation in multi-modal transport networks [67]. Narayanan and Antoniou developed a choice model for three shared mobility solutions for understanding how the use of these solutions is influenced by socio-demographic characteristics, trip-related variables, and supply parameters [68]. Bandiera et al. proposed a mathematical model to examine the interplay between MSM providers and individual users [69].

Table 4. Operations and decisions-based studies.

Themes	References	Approaches	Critical Factors/Main Findings
Single shared mobility	[50]	Clustering	Carpooling contributes to less congested traffic and environment-friendly travel
	[49]	Modeling	Dynamic strategies help platforms adjust supply and demand for achieving optimization goals
	[51]	Modeling	Bundled mobility offerings can improve profit and social welfare
	[52]	Macroscopic diagram	An optimal model for minimizing the time cost
	[53]	Queuing theory	Insights on ride allocation
	[54]	Modeling	Price variability is reduced, and capacity utilization, trip throughput, and welfare are increased
	[56]	Modeling	A model for policy control
	[55]	Modeling	A mathematical model
	[57]	Game/integer linear program	Market design can reduce inefficiency and promote healthy competition
MaaS	[58]	Case study	A characterization of business models
	[59]	Case study	A framework for cooperation
	[11]	Review	Desired MaaS outcomes, supply-side barriers and demand-side risks related to MaaS adoption
	[60]	Case study	Experimenting innovative solutions for key learnings about shared mobility ecosystems and stakeholders
	[9]	Review	Areas for affecting MaaS’ capacity
	[61]	Review	Non-features requirements are valued
	[62]	Modeling	A novel e-MaaS ecosystem
	[63]	Modeling	A new MaaS platform design
MSM	[64]	Qualitative exposition	Existing models are fraught with conflicts, a merit model is the best one
	[65]	Review	The role of a shared mobility center in MSM use
	[7]	Review	Shared mobility requires collaborative partnership
	[66]	Delphi approach	18 challenges and 12 constructs are critical to the sustainability of MSM
	[67]	Game theory	Profit increases through cooperation
	[68]	Modeling	A choice model
	[69]	Modeling	A novel mathematical model on the interaction between providers and users

summarizes the above discussion.

4.4. Performance Evaluation

Evaluating the performance of shared mobility is critical for developing sustainable transport [4]. There are many studies being conducted from the perspective of performance evaluation of specific shared mobility initiatives, performance evaluation of shared mobility development, and impact assessment, discussed as follows.

There are many studies assessing the overall performance of specific shared mobility initiatives. Jin et al., for example, conducted a systematic review on how ride-sourcing affects efficiency, equity, and sustainability, finding that ride-sourcing positively affects economic efficiency [70]. Erhardt et al. explored the negative impact of Uber and Lyft, showing that transport network companies (TNCs) contribute the most to traffic congestion in San Francisco [71]. Henao and Marshall examined the change in performance indicators of TNCs, showing that ride-hailing adds approximately 83.5% more vehicle kilometers traveled (VKT) to transport systems in the Denver region [72]. Tirachini and Gomez-Lobo examined how ride-hailing affects VKT, revealing that ride-hailing increases VKT unless its applications can substantially increase the occupancy rate in Mexico City [73]. Tirachini et al. investigated the impact of shared mobility on travel behavior, transport sustainability, congestion, pollution, and crashes [74]. Shen et al. presented a solid empirical basis to state that transport authorities need to work with private mobility service companies by studying a carpool incentive experiment in the Seattle region [75]. Vélez conducted a literature review to investigate the environmental impact of shared mobility solutions including car-sharing, carpooling, bike-sharing, and scooter/moped-sharing [76]. Coenegrachts et al. employed latent class cluster analysis and k-means clustering to provide an explorative analysis of the shared mobility market in 311 European cities, indicating that there are nine shared mobility systems clusters in European cities [77].

Performance-oriented studies explore the development of shared mobility focusing on MaaS. Matyas and Kamargianni examined whether MaaS can be adopted to promote shared mobility, finding that many people are willing to adopt such services [78]. Reck et al. conducted an extensive review on MaaS design, thus developing a framework to compare design, development, and outcome of such design choices [79]. Zhang and Zhang proposed an alliance-based framework for Chinese MaaS systems, summarizing that the key to MaaS project success is related to industry alliance, government support, and data sharing [80]. van den Berg et al. showed that shared mobility products are different in how stakeholders are affected by the utilization and availability of mobility technologies [81]. Muller et al. conducted a review of current simulation tools to assess the sustainability impact of MaaS from a systems perspective [82]. Hensher et al. found that offered MaaS bundles have an encouraging impact on private car use by employing discrete–continuous choice modeling conducted on a Sydney MaaS trial project [83]. Ho et al. developed a mixed logit choice model for understanding individuals’ selection between pay-as-you-go (PAYG) and four MaaS subscription plans, revealing that mobility bundles have a significant market and PAYG is preferred by those with varying travel needs [84]. Lindkvist and Melander examined the MaaS literature, revealing that MaaS promises to deliver both social and environmental sustainability [85]. Kriswardhana and Esztergár-Kiss investigated various critical factors that affect the adoption of shared mobility, leading to the identification of various environmental and individual factors that affect the utilization of MaaS [86]. Carbonara et at. employed a multi-case study to examine the impact of MaaS, revealing that similar strategies have been adopted in the transition to MaaS [87].

Impact-aligned studies examine the availability of shared mobility initiatives and their impact. Arias-Molinares and García-Palomares, for example, conducted a case study to explore the development of MaaS, finding that there is little cooperation between stakeholders in existing shared mobility projects [88]. Becker et al. ran a joint simulation for a city-wide transport system, revealing that MaaS schemes may increase transport systems efficiency and reduce energy consumption [89]. Christensen et al. applied social practice theories to assess the influence of MaaS, discovering that MaaS designs should consider the routinization and entanglement of individuals’ daily mobility practices [90]. Ho assessed the viability and environmental sustainability of MaaS based on a five-month field trial, finding that MaaS use does affect individuals’ travel behavior [91]. Krauss et al. conducted an experiment in Germany to explore the influence of mobility behavior on the use of MaaS bundles, stating that utilizing shared mobility offerings reduces private car use [92]. Aba and Esztergár-Kiss carried out an MaaS pilot study in Budapest with the provision of detailed information about various perspectives of the service providers in MaaS adoption [93].

Table 5. Performance evaluation-based studies.

Themes	References	Approaches	Critical Factors/Main Findings
Specific shared mobility	[70]	Review	Ride-sourcing affects efficiency, equity, and sustainability
	[71]	Regression model	TNCs contribute to growing traffic congestion
	[72]	Experiment	Ride-hailing increases VKT
	[75]	Regression	Carpooling generates promising outcomes
	[73]	Simulation	Ride-hailing increases occupancy rate and VKT
	[74]	Survey	VKT depends on various factors
	[77]	Clustering	Individuals have access to shared mobility
	[76]	Review	Travel behavior, shared mobility modes, and local contexts are critical
Shared mobility performance	[78]	A mixed MNL model	MaaS can introduce more travelers to use shared modes
	[79]	Experiment	A framework
	[83]	Choice model	MaaS changes travel behavior
	[84]	Logit choice model	PAYG is a preferred option
	[85]	Review	Sustainable business models
	[82]	Review	Comparative assessment of simulation tools for shared mobility
	[80]	Review	Cooperation, government support, and data sharing are critical to shared mobility projects
	[81]	Game theory	MaaS benefits consumers by increasing competition and removing marginalization
	[86]	Review	Environmental factors and user groups
	[87]	Case study	The MaaS operations process
Impact assessment	[88]	Case study	Governance and collaboration is critical for developing MaaS
	[89]	Simulation	MaaS increases system efficiency, while substantially reducing energy consumption
	[90]	Interview	MaaS should consider embodied routinization and entanglement of mobility practices
	[91]	Choice modeling	MaaS affects travel behavior
	[92]	Experiment	Shared mobility reduces car use
	[93]	Case study	MaaS is effective for reducing private car use

summarizes the above discussion.

The discussion above shows that shared mobility is an evolving phenomenon that stresses shared use rather than ownership of transport facilities [94]. This means that sustainable transport needs more cooperation between stakeholders [66,95]. Individuals focus on efficiency, economics, and flexibility, while transport authorities pursue more social equity, reliability, and environmental friendliness. Often, such goals are hard to be cooperative in pursuing sustainable transport [77]. To address these challenges, innovative mobility solutions are required [96,97].

5. Research Gaps and Questions

The systematic literature review above helps to identify the gaps and research questions in developing sustainable transport. Such research gaps and questions are discussed with respect to the four themes as follows.

5.1. Attitude and Intention

Attitude and intention are the driving factors that affect individuals’ selection of shared mobility products and services in urban traveling [4]. Despite numerous studies in exploring the attitude and intention from different perspectives, most studies focus on investigating the critical factors that influence the attitude and intention in adopting shared mobility. It is unclear whether existing findings can be applied to the utilization of cooperation-oriented, multi-modal shared mobility. The specific elements and mechanisms that influence individuals’ attitudes and intentions to choose collaborative travel options within a multi-modal shared mobility context for sustainable transport remain largely unknown.

5.2. Cooperation Behaviors

Conscious cooperation behaviors imply proactive acceptance and adoption of shared mobility products and services in pursuing sustainable transport [4]. Exploring the behavioral pattern of individuals leads to many studies with the use of representative behavioral theories. Despite much progress being made, much of the research, however, concentrates on the behavior patterns of specific shared mobility solutions. In pursuing sustainable transport, multi-modal shared mobility is often required for achieving multiple and seemingly conflicting objectives that particularly need more cooperative behavior in travel choice decisions. There is a lack of investigation in examining the formation and evolution of cooperation behaviors in the adoption of multi-modal shared mobility.

5.3. Operations and Decisions

Operations and decisions are crucial to achieving specific objectives that various stakeholders pursue in shared mobility. Existing studies have tried to explore how operations and decisions have affected shared mobility use. However, there are few studies exploring the adoption of various mobility modes in pursuing sustainable transport through developing cooperation-oriented multi-modal shared mobility.

5.4. Performance Evaluation

There are many studies evaluating the performance of shared mobility. Quantitative indicators such as VKT and VMT are considered, as well as qualitative indicators such as traffic congestion, emissions, or environmental hazards. Existing studies explore how the adoption of shared mobility affects individuals’ behaviors in urban traveling, transport performance, and social welfare, and they examine the critical factors and mechanisms for the implementation of shared mobility initiatives. However, here is a lack of studies exploring the economic, environmental, and societal benefits of cooperation-oriented multi-modal shared mobility. It is unclear why some cooperation-oriented multi-modal shared mobility pilots or trials have positive impacts while others do not.

Table 6. Research gaps and questions.

Themes	Topics	Gaps	Research Questions	References
Attitude and intention	Attitude	Few studies examine the critical attitudes in multi-modal shared mobility contexts	What are the influential factors of attitude, intention, and WTP related to cooperation-oriented multi-modal shared mobility? How do influential factors affect attitude, intention, and WTP related to cooperation-oriented multi-modal shared mobility?	[2,11,17,22,24,25,26,27,28,29]
	Intention	Lack of studies in exploring the influence mechanisms of attitude, intention, and WTP in multi-modal shared mobility contexts
	WTP
Cooperation behaviors	Behavior patterns	Most articles focus on the behavior patterns of single shared mobility or MaaS rather than cooperation-oriented multi-modal shared mobility	What are the behavior patterns related to cooperation-oriented multi-modal shared mobility? What affects cooperation-oriented multi-modal shared mobility behavior? How does cooperation-oriented multi-modal shared mobility behavior form and evolve?	[4,36,38,39,40,41,42,43,47,48]
	Critical factors	Only a few studies focus on critical factors influencing single shared mobility or MaaS
	Formulation and evolution	Few studies investigate formulation and evolution of cooperation-oriented multi-modal shared mobility
Operations and decisions	Single shared mobility	Lack of studies addressing operations and decisions issues in cooperation-oriented multi-modal shared mobility	What are the differences between MaaS, MSM, and cooperation-oriented multi-modal shared mobility? How are effective and viable strategies/solutions developed for cooperation-oriented multi-modal shared mobility?	[9,11,27,50,51,56,57,61,62,98]
	MaaS
	MSM
Performance evaluation	Specific shared mobility	Lack of understanding of the causes of different impacts of shared mobility pilots or trials	Why do some cooperation-oriented multi-modal shared mobility pilots have positive impacts while others do not? How are economic, environmental, and societal impacts of cooperation-oriented multi-modal shared mobility pilots assessed?	[70,71,73,79,80,82,83,85,86,92,93]
	Shared mobility development	Most studies on performance evaluation and related impact assessment focus on specific shared mobility or MaaS
	Impact assessment

summarizes the research gaps and questions discussed above.

6. An Integrated Cooperation-Oriented Multi-Modal Shared Mobility Framework

Developing shared mobility for sustainable transport requires holistic consideration of the four themes discussed above. These four themes are closely related based on the collaboration and cooperation between stakeholders. Figure 5 presents a framework for better describing the interplay between these themes and stakeholders.

The acceptance and adoption of shared mobility originate from individuals’ travel demands. These travel demands exert a direct effect on the attitudes and intentions of individuals in the use of shared mobility, and their attitudes and intentions propel various cooperative and non-cooperative behaviors. These behaviors then represent the demand side of the transport system. They provide specific benefits from economic, environmental, and societal perspectives [1].

The supply side of shared mobility includes mobility service providers and operators [4]. They deliver innovative mobility products and services with respect to specific government regulations and rules in their operations and decisions. These operations and decisions are assessed for understanding the performance and impact of such products and services. Transport authorities play the role of coordination and management involving planning, operations, and evaluation of shared mobility.

Shared mobility conforms to carbon footprint reduction advocacy, thus being an attractive solution for sustainable transport [80]. It emphasizes sharing trip-rides or transport equipment rather than exclusive use or ownership [10,99]. Shared mobility, however, does not meet the travel demands of every individual. To address such a challenge, other transport modes are required. This leads to the adoption of multi-modal shared mobility that includes private cars, bikes, and public transit [3].

Excessive use of private cars may exert negative externalities and deviate from sustainable transport [100]. It shows that the adoption of multi-modal shared mobility requires a balance between meeting individual travel demands and satisfying sustainable development goals. This requires individuals to make more cooperative choices in shared mobility [4].

Cooperation and collaboration are the foundation to the pursuit of multi-modal shared mobility for sustainable transport [1]. This is determined by the cooperative features, operational difficulties, and output performance that individual transport modes have in providing mobility services. Cooperative features are about the needs of specific transport modes on how much cooperative consciousness is required in adopting shared mobility. Operational difficulties are linked to the degree of difficulty for the demand side (individuals) to adopt this transport mode and the degree of difficulty for the supply side (providers) to operate related modes. Output performance is the reflection of achievement of sustainable objectives that shared mobility pursues. With the consideration of these three features, existing mobility solutions can be assessed, leading to the development of a summary of the cooperation matrix for developing sustainable shared mobility, shown as in

Table 7. The cooperation matrix for developing sustainable shared mobility.

Transport Mode		Cooperation	Operations	Output	References
Shared mobility	Sharing vehicles	Moderate	Moderate	Moderate	[22,51,68]
	Ridesharing	Moderate	Moderate	Moderate	[38,50,52]
	On-demand ride services	Moderate	Moderate	Moderate	[20,39,53,56,57]
	Micro-mobility	Moderate	Moderate	Moderate	[42,43,101]
Non-shared mobility	Private vehicle	Inconspicuous	Low	Moderate/Inferior	[38,102,103]
	Other ownership modes	Inconspicuous	Low	Moderate/Inferior	[7,66,104]
MaaS		Conspicuous	High	Excellent	[9,11,59,62,105]

.

Table 7 reveals that MaaS needs the highest level of cooperation between various stakeholders for sustainable transport. This means that the use of MaaS requires more conscious cooperation and collaboration between stakeholders. MaaS generates the best output performance with respect to the sustainable objectives; however, it is difficult to adopt due to various challenges in pursuing sustainable transport through cooperation and collaboration between stakeholders. This dilemma calls for novel shared mobility solutions capable of integrating the advantages of MaaS while addressing the challenges that it faces in facilitating the mobility of individuals in urban traveling.

A cooperation-oriented multi-modal shared mobility (COMSM) framework is proposed in this study to better address the challenges that existing shared mobility solutions suffer from. It can facilitate the development of sustainable transport through better satisfying multiple but often conflicting objectives of stakeholders by combining multiple travel modes in urban traveling [87,106,107]. To reduce the collaborative barriers between mobility service providers, COMSM does not require integrating multiple travel services into integrated platforms. It is committed to make the allocation of transport resources in a transparent manner by providing diversified travel modes for reducing traffic congestion and improving mobility services efficiency. COMSM is an effective integration of MSM and MaaS for fulfilling the needs of stakeholders through cooperation and collaboration.

Figure 6 presents an integrated COMSM framework. This framework includes the main components and their relationships in an urban transport ecosystem. It provides flexibility, efficiency, safety, reliability, environmental friendliness, and transport equity for the mobility of people by leveraging every mode’s specific advantages.

A COMSM ecosystem has four components. The first component is users. The second one is mobility service providers including (a) traditional services providers; (b) incumbent services providers such as public transit, paratransit, shuttles, and taxis; (c) self-services providers such as private vehicles, e-scooters, and bicycle delivers; and (d) supportive services providers such as mobile communication operators, information system developers, and data analysts. The third component is mobility operators, often referred to as transport services platforms such as Uber, Lyft, or Didi. These platforms have numerous drivers who provide individuals with required services. They serve as the moderator for connecting providers and users. The fourth component is transport authorities who act as the intermediator and supervisor [14].

There are complicated interplays between these four components. In shared mobility, individuals first send their travel demands through digital platforms, typically via smart-phone apps owned by mobility operators. These demands are transformed as customers order through the platforms. These orders are communicated to mobility service providers as soon as the platform matches the request with appropriate providers. The provider can then supply the individuals with the required services. In this process, transport authorities act in an intermediate role that ensures the mobility market is being operated according to the relevant regulations and policies.

There exist some differences between COMSM and MaaS. The main difference lies in the implementation difficulty of COMSM that is much lower than MaaS. COMSM does not require a single digital interface to provide integrated planning, booking, payment, ticketing, and other functions as required in MaaS [2]. Users’ travel demands could be fulfilled by multi-services providers (MSPs) via multiple digital platforms. Collaboration is one of the essential elements for MaaS, while collaborating sufficiently exerts significant challenges because of the competitive nature among the different MSPs [11,108,109]. MSPs can mitigate the requirements through cooperation among stakeholders. The other prominent difference is that COMSM may not exclude the use of private vehicles [99,110]. All travel modes can be incorporated to achieve more efficient and flexible mobility. This inclusion shows that COMSM can strive to fulfill the multiple goals of stakeholders while providing more flexible services through cooperation and collaboration.

COMSM has several advantages compared to existing shared-mobility solutions. These advantages are reflected in the difficulty of implementation [106] and the output performance [70]. As a flexible and effective transport solution, COMSM has enormous adaptability, which is realized by effective combinations of specific mobility modes. COMSM can incorporate private vehicle use in providing more choices in those suburban areas with low-occupancy public transit or shared mobility travel modes [87,102]. This inclusion brings individuals more flexibility and efficiency in urban traveling. Furthermore, COMSM does not commit to pursue a single online interface. It allows the use of diverse digital platforms with more safety and social inclusion and less collaboration requirements than an integrated online interface [96,111,112,113,114,115]. In summary, COMSM can create compelling value for those pursuing higher efficiency and lower-barrier solutions.

7. Conclusions

A systematic review was implemented in this study on the adoption of shared mobility for pursuing sustainable transport. As a result, the emerging themes and the challenges associated with the use of shared mobility for sustainable transport were identified. An integrated framework through integrating MaaS and MSM was developed to facilitate shared mobility in pursuing sustainable transport. The contribution of this study focuses on extracting prevailing themes of multi-modal shared mobility, analyzing the up-to-date progress in this realm, summarizing the research gaps and questions, and formulating an informative conceptual framework to facilitate the development of cooperation-oriented multi-modal shared mobility for sustainable transport.

There are important distinctions between traditional shared mobility and COMSM. This leads to numerous research challenges and questions that need to be addressed. Firstly, studying users’ attitudes, intentions, and behaviors in COMSM travel choices requires better understanding of the relationship between the critical factors and COMSM adoption. Secondly, exploring how specific COMSM operations and decisions are made is required for more insights on planning and designing COMSM operational strategies and policies. Finally, assessment the implementation of different COMSM initiatives is necessary, as such evaluations can provide appropriate suggestions for tackling the enormous challenges on sustainable transport development in dynamic urbanized environments.