Acceptance of Mobility-as-a-Service: Insights from empirical studies on influential factors

In ﬂ


Introduction
In the age of the digital revolution, technological advancements are influencing the field of urban mobility (Kamargianni and Matyas, 2017;Turetken et al., 2019aTuretken et al., , 2019b)).Mobility-as-a-Service (MaaS) has emerged as a digital innovation, creating changes in the mobility landscape (Mola et al., 2020).The use of MaaS as a smart mobility solution has the potential to capitalize on benefits, including reductions in consumption and emissions, and improvements in service and data access, which can result in the development of efficient and effective transportation services (Yigitcanlar and Kamruzzaman, 2019).While these benefits are contingent on the extent to which travelers transition to eco-friendly modes (Jang et al., 2021).It is important to acknowledge that MaaS implementation may introduce new challenges related to social equity, as highlighted by Groth (2019).Nevertheless, MaaS is generally considered a socially and environmentally efficient travel demand management tool with subscription plans customized to the users' preferences (Kamargianni and Matyas, 2017).Supporters of MaaS emphasize the role of MaaS in reducing private vehicle ownership and, eventually, transportation-related costs (Jittrapirom et al., 2017).
The notion of the MaaS emerged in the early 2010s as an integrated platform that provides customers with a wide range of mobility services by multiple mobility service operators (Heikkila, 2014).Instead of using multiple mobility platforms and separate individual modes, customers have the flexibility of using a single digital platform that combines and tailors mobility services to the customer's needs.The emerging literature provided several definitions of the topic as a distribution model that integrates a range of traditional and innovative transportation modes combined with transport services, such as booking, ticketing, payment, and travel recommendation (Jittrapirom et al., 2017;Kamargianni et al., 2016;Sochor et al., 2015a).
In the case of widespread adoption of these platforms, the shift towards MaaS is expected to result in substantial societal benefits, such as reductions in emissions and traffic congestion and an increase in the provisioning of personalized transport solutions (Coconea et al., 2019b;Yigitcanlar and Kamruzzaman, 2019).However, achieving these positive outcomes relies heavily on individuals willing and able to use the service (Lopez-Carreiro et al., 2021a).Here comes the importance of understanding the underlying factors influencing the adoption of MaaS and the diverse consumer choices.Researchers have discussed the public acceptance and adoption of MaaS as a precondition for its successful implementation (Caiati et al., 2020;Smith et al., 2020), which is a common concern for innovative services or products when introduced in a new or existing market.Users establish an understanding of the technology followed by an attitude before deciding to adopt or reject it (Davis, 1989).Various innovations throughout history failed to achieve widespread diffusion because of their misalignment with the user's needs, values, preferences, or past experiences (Rogers, 1995).Given this background, it is evident that a comprehensive understanding of the wide range of factors influencing the user's acceptance of MaaS is needed.
As a result of an increase in popularity, MaaS research is growing significantly.While this increase is expanding the understanding of the topic, there is a large set of factors that play a role in influencing users' decisions to accept, adopt, and use MaaS solutions.Although several factors show similar influence on user acceptance, some are underrepresented or reveal different influencing signals, resulting in inconsistent outcomes among the various empirical studies.For instance, the average annual income was found to influence MaaS adoption both negatively (Farahmand et al., 2021;Kim et al., 2021a;Ko et al., 2021;Matyas and Kamargianni, 2021) and positively (Agbe and Shiomi, 2021;Brezovec and Hampl, 2021;Caiati et al., 2020).Another interesting factor is car use, which was revealed to influence MaaS acceptance both negatively (Fioreze et al., 2019;Ho et al., 2020;Mulley et al., 2020) and positively (Brezovec and Hampl, 2021;Ho et al., 2018).This results in the disorientation of future empirical work and potentially delays the diffusion of MaaS.
The extant literature offers a wide range of empirical studies and review articles focusing on the user perspective, willingness, or intention to pay and adopt MaaS.However, the majority of these studies do not rely on a structured review of the existing literature in settling for these factors (e.g., Caiati et al. (2020); Hoerler et al. (2020); Polydoropoulou et al. (2020a); Ye et al. (2020)) or focus on a selected number of factors given their interest in a particular theory or a set of factors (e.g., Alonso-Gonz alez et al. (2020); Mola et al. (2020); Schikofsky et al. (2020)).In brief, the available literature is limited as it takes a particular stance in analyzing the influential factors.Therefore, there is a need to synthesize and extend the research on MaaS acceptance and examine the indicators used in empirical studies to understand their influence on users' decisions on the acceptance and adoption of MaaS.To the best of our knowledge, no structured literature review provides a comprehensive overview of all factors reported in the literature on the user acceptance of MaaS.Therefore, we pose the following research questions for our study: 1) What factors have the current literature considered influential on the user acceptance/adoption of MaaS? 2) What future research directions do the findings on the user acceptance/adoption of MaaS suggest?
Consequently, the broad aim of this study is to establish a foundation for future research by building on empirical research directed toward MaaS acceptance.Our work not only considers the influential factors but also examines the actual impact of each factor on user acceptance.
To answer our research questions, we conducted a systematic literature review (SLR), studying empirical works investigating the factors that influence MaaS user acceptance.To locate these studies, we searched the Web of Science digital library for the articles published between 2010 and 2022.From 363 peer-reviewed journal articles that were initially retrieved, 51 were finally selected, given the selection criteria of this study.These studies were thoroughly analyzed to identify their objective, methodology, investigated factors, and findings.As a result, this research builds on a comprehensive set of empirically investigated factors and aims to serve as a reference point for future research on user acceptance of MaaS.
The remainder of this paper is structured as follows.Section 2 discusses the MaaS concept and key insights into individual adoption in the mobility field.Section 3 presents the research design of this study.Next, the key findings of the literature review and the factors influencing MaaS adoption are presented in Section 4. This is followed by a discussion of our findings and directions for future research in Section 5. We conclude with a summary of the findings and limitations of our study in Section 6.

Background and related work
In this section, we briefly present a background to the concept of MaaS and discuss related works that involved literature reviews on several concepts around MaaS, particularly on the factors potentially influencing its acceptance.

Concept of MaaS
MaaS has attracted worldwide attention and witnessed a number of successful trials in several countries (Boer, et al., 2022a;Butler et al., 2021;Jittrapirom et al., 2017).Several MaaS initiatives were launched, such as Whim in Finland, UbiGo in Sweden, Moovel in Germany (Jittrapirom et al., 2017), and Mobility4All in North America (Lopez-Carreiro et al., 2020).
Although various authors attempted to define MaaS (Arias-Molinares and García-Palomares, 2020), the core elements of MaaS are considered to revolve around a single platform that provides real-time information on available private or public modes in a specific region, multi-modal transportation, that integrates planning, booking, and payment for mobility needs and personalized packages (Athanasopoulou et al., 2022a;Sarasini et al., 2017).The transportation modes offered by the MaaS platform are not limited to public transportation.They can include taxis, car-sharing, ridesharing, bike-sharing (Hoerler et al., 2020), electric scooters, and motorcycles (Str€ omberg et al., 2018), allowing for multimodal trip options based on user choices with a seamless combination of public and private transportation options without needing a private car or ownership of cards from different service providers (Boijens et al., 2021;Utriainen and P€ oll€ anen, 2018).
The younger generation showed increased interest in changing technology trends and increased use of ride-sourcing apps (Casey et al., 2017).MaaS represents a new way of offering transport services to users (Arias-Molinares and García-Palomares, 2020).It provides a system with a wide set of mobility services that allow users to plan, pay, and access their mobility requirements any time they want in a single app (Kamargianni and Goulding, 2018).As a result of the development of the system and increased interest in MaaS, previous research has addressed its importance in promoting change in the transport sector (Alonso--Gonz alez et al., 2020;Jittrapirom et al., 2017;Kamargianni and Goulding, 2018;Matyas and Kamargianni, 2019a).
The travelerthe MaaS useris the leading actor in the MaaS ecosystem (Arias-Molinares and García-Palomares, 2020).MaaS places travelers at the center of transport services by providing them with tailored mobility solutions that fulfill their expectations (Ho et al., 2018).This provides users easy access to appropriate modes of transport included in a package with flexible and personalized options tailored to user needs and offers an interesting alternative to private car ownership (MaaS Alliance, 2019).A MaaS platform may cover any available mobility operator to provide flexible, convenient, and personalized travel options for different users (Kamargianni et al., 2016).However, most journey planners available for users do not combine more than one transport mode (except walking to reach the final destination) (Kamargianni and Matyas, 2017).This means that for users to travel from one destination to another, they must use transport modes run by different operators and accept particular modes of payment (cash, cards, PayPal, etc.).In this case, the user is not able to access all these modes with just one interface or smart card; this problem restricts the spread of inter-modality, that is, using two or more transport modes in one trip; and multimodality, which refers to the use of different transport modes for different trips.The research indicates that about 40% of adults are willing to adopt MaaS under the condition that their mobility needs will be met and that the MaaS expenditures will be lowered (Kamargianni and Goulding, 2018;Liljamo et al., 2020;Vij et al., 2020).

Related work
To date, several review articles focusing on MaaS have been published.A bibliographic review by Arias-Molinares and García-Palomares (2020) focuses on the definition of MaaS, identifying its main actors, and understanding the motivations behind its implementation.In their study, they review 57 MaaS-related articles and conclude that the field is still encountering various developments that delay reaching a unified definition of MaaS.Although the paper provides a holistic view of what MaaS is, who the main actors are, and how it can be implemented, it does not investigate the effect of user preferences and travel behavior on the acceptance and adoption of MaaS.The review by Utriainen and P€ oll€ anen (2018), which includes 31 scientific articles, focuses on the role of different transport modes on MaaS, ongoing pilots and trials, and the effects of MaaS.They address various MaaS schemes in the literature without tapping into their direct impact on acceptance.Butler et al. (2020) conducted a systematic literature review (SLR) on how smart mobility innovations can ease the disadvantages of transportation.
The literature also features reviews that investigate the influencing factors.The SLR by Pham et al. (2021) studies the indicators and the interactions between users, service providers, and platform operators.From 50 peer-reviewed articles, they present the interactions among three types of stakeholders (grouped as demand side and supply side) under the impacts of physical and psychological indicators/factors.However, their work does not consider the effect of a broad set of factors on MaaS acceptance and adoption.Calder on and Miller (2020) focus on the supply side of mobility services and present a literature review on the insights at the conceptual, operational, and modeling levels.Their review points out that mobility services have a high degree of generality and that human factors should be better considered during the modeling efforts.Another review by Butler et al. (2021) focuses on barriers and risks associated with MaaS adoption in cities.Their study includes 91 peer-reviewed articles focused on outcomes and risks, and demand-side and supply-side barriers.Their findings show that MaaS does not appeal to older generations, public transport users, or private vehicle users.Although the study focuses closely on adoption from the demand side, it does not tackle the comprehensive list of factors affecting MaaS acceptance.
The study by Lopez-Carreiro et al. (2021a) confirms the wide agreement in the literature that the success of MaaS is reliant on travelers' engagement.However, limited studies have explored why and how individuals accept and adopt MaaS.A few empirical works focus on users' intention to use and willingness to adopt MaaS (Ko et al., 2021;Lopez-Carreiro et al., 2021a, 2021b;Ye et al., 2020).The study by Lopez-Carreiro et al. (2021b) applies the technology acceptance model (TAM) theory to explore individuals' willingness to adopt MaaS with the support of a systematic literature review focusing on attitudinal factors.Another important set of studies focuses on the willingness to pay (Liljamo et al., 2020;Tsouros et al., 2021).These works, however, do not rely on systematic reviews.
In a similar line, several empirical studies investigate the different user characteristics and segments and their potential to adopt MaaS (Feneri et al., 2022Schikofsky et al., 2020;Zijlstra et al., 2020).User preferences for MaaS bundles and their intention to subscribe are also addressed in the literature (Ho et al., 2021).The pricing schemes are investigated to understand the user preference for MaaS (Feneri et al., 2022).Several studies are built on MaaS pilots to understand user choices.For instance, the UbiGo platform in Sweden was tested to understand user choices and future decisions (Sochor et al., 2016) and how it influenced travel behavior (Str€ omberg et al., 2018).Other important influential factors are the user expectations of the MaaS service, which helps in the design of MaaS schemes (Lopez-Carreiro et al., 2020;Polydoropoulou et al., 2020a), and the readiness of users to change their travel behavior (Hensher et al., 2021;Storme et al., 2020), and travel habits towards available travel modes (Fioreze et al., 2019;Kim et al., 2021b).Lastly, user expectations, preferences, and motivations are found to be important in driving the adoption of MaaS services (Lopez-Carreiro et al., 2021b).The findings of these studies focus on a wide set of variables that extend to the transport modes and transport infrastructure in particular regions.
In conclusion, despite several empirical works on various aspects of MaaS, the research and practice of MaaS still require a comprehensive and systematic review of the factors that have been empirically studied in the literature, along with their respective influence on the acceptance of MaaS.This paper aims to address this need.

Research design
In conducting our review, we adopted the guidelines proposed by Kitchenham and Charters (2007) for performing systematic literature reviews (SLRs).This section presents the SLR protocol that we developed based on the guidelines.Fig. 1 shows the steps that we followed.
In steps 1 and 2, we defined the research problem, accordingly, formulated our research objective and related questions.We present our research problem, objective, and questions in the introduction section of this paper.In step 3, we conducted several pilot searches to review the scope and refine the search string we used to locate relevant studies in digital libraries.Subsequently, we selected the Web of Science digital library as our primary data source (step 5) to identify relevant studies, as it is known to cover venues that publish high-quality papers that are most relevant to the objective of our study (Wohlin, 2014).
After several iterations of pilot searches, we adopted a broad perspective in formulating the search string (step 4) to capture most of the articles that studied the concept of MaaS.As a result, we formulated the following string to locate relevant work "mobility as a service*".Using this search string in the Web of Science resulted in 509 articles prior to applying the inclusions and exclusion criteria as explained in step 6.
In step 6, based on our research objective and questions, we defined the inclusion and exclusion criteria for selecting the primary studies.Articles that were not MaaS and adoption-focused were excluded from the selection, in addition to articles that were from a different field of study (such as mathematics, remote sensing, computer science, and automation control systems).Table 1 presents these criteria.
The main search (step 7) was performed for articles published in academic journals between 2010 and 2022.The query string was applied to the title, abstract, and keywords of the publications, reducing the number of articles to 363 articles.In step 8, the complete list of articles was screened against the established inclusion/exclusion criteria.The screenings were performed by one of the authors of this work and subsequently checked independently by the other authors for confirmation.The differences in the views regarding included or excluded articles were discussed until a consensus was reached.Step 8 resulted in 45 articles for further investigation.
In step 9, we performed the forward snowballing technique proposed by Wohlin (2014) to locate relevant works that cited one or more of these 45 articles but were not found in our search on the Web of Science.With the addition of 9 articles, the total number increased to 54 articles.After analyzing the full text of the articles to ensure their proper alignment with the topic and focus of the study, the finalized list included 51 articles.The final step involved extracting and analyzing the key factors and their operationalizations in each empirical study, including the data collection method and the results of the studies in terms of the impact each factor has on the acceptance of MaaS.

General findings
In this section, we present the general findings of our review by outlining the distribution of MaaS-related articles in the existing literature.Fig. 2 shows the distribution of the primary studies published in peer-reviewed journals (the earliest from 2015 and the latest to 2022).The 51 articles included in this review show that the interest in the topic started growing in the past 4 years and has reached its current peak in 2020 with 21 studies.
Most of the reviewed studies (n ¼ 35) were conducted across Europe, reflecting European researchers' interest in the MaaS topic.This could be related to the fact that most implemented trials were conducted in Europe (Sakai, 2019) (some of the studies included multiple countries).Furthermore, the studies focusing on user acceptance of MaaS showed a noticeable increase also in Australia and East Asia, reflecting the maturity of the technology and the advancements that it has been partaking in.The list of articles, study region, and data collection method used per study is listed in Appendix A.
Table 2 lists the sources and the number of empirical studies listed in each source.Among the 51 empirical studies, most of the studies (i.e.Most of the reviewed empirical studies relied on quantitative data collection methods, such as surveys (n ¼ 48).The use of interviews for data collection was the second highest with n ¼ 7, followed by focus groups (n ¼ 5).Several studies that used a questionnaire in their data collection are coupled with specific field trials of MaaS services, such as the UbiGo (Sochor et al., 2016) or the trial studied in Karlsson et al. (2016).Other studies applied a mixed-method approach, such as in-depth interviews or focus groups combined with surveys (e.g., Matyas and Kamargianni, 2019a;Polydoropoulou et al., 2020a;Schikofsky et al., 2020;Str€ omberg et al., 2018).Only a few studies relied on a qualitative method, such as interviews (n ¼ 1) (Caiati et al., 2020;Matyas, 2020) or focus groups (n ¼ 1) (Casey et al., 2017).

Investigated factors
This section discusses the results from the reviewed empirical studies and outlines the factors that have been studied in extant literature.Following a consensus-building approach (Susskind et al., 1999) and relying on the comprehensive review of the existing literature, we have undergone multiple rounds of discussions and iterations for categorizing these factors.The consensus-building approach is a collaborative method that can be used to categorize concepts into meaningful clusters by facilitating discussions and achieving agreement among a group of individuals (Susskind et al., 1999).While reviewing each factor, we initiated the process of forming groupings based on the shared characteristics and relationships among the factors.In cases where a factor could not be readily assigned to an existing category, a new category was established.This process continued until all 71 factors were thoroughly analyzed and discussed, and a consensus was reached among the authors.
As a result, we grouped the factors into three categories: the traveler and trip characteristics, the service and technology characteristics, and the urban environment characteristics.Table 3 shows the list of all factors under these categories, followed by Tables 4-6, presenting in more detail the definitions and results of the factors investigated in the primary studies.Detailed mapping of primary studies and factors is shown in Appendix B.

Discussions and future research
This section discusses the key results of this paper.First, we focus on the factors that are deemed most and least influential.The factors encompass those for which empirical research is in unanimous agreement regarding their positive or negative impact (or lack of impact).We delve into a number of these factors that have been extensively studied, as indicated by the abundance of research papers reporting their analysis.Following that, we also elaborate on those factors that have been studied frequently but have yielded contradicting results in empirical studies (We designated a factor as contradictory if there was at least one study indicating a positive or negative influence that contradicted the findings of Table 1 Inclusion and exclusion criteria for the SLR.

Inclusion criterion Exclusion criterion
(1) Publications in the English language (2) Publications published between 2010 and 2022 (3) Full-text articles available online (4) Publications with quantitative or qualitative analysis (5) Publication related to MaaS and user (6) MaaS and user adoption relevance to the research questions of the study (1) Conference proceedings, books, book chapters, editorial reports, working papers (2) Literature review articles (3) Publications that do not address the user perspective (4) Publications that approach MaaS from a scope outside the interest of this study.
H.E. Mustapha et al. Communications in Transportation Research 4 (2024) 100119 the majority of other empirical studies examining that factor).As we present these factors, we also explore potential avenues for future research to address the key findings.

Most influential factors
Age is among the key socio-demographic factors when evaluating the expectations of MaaS technologies (Casey et al., 2017).Results show that it has a negative impact on the willingness to pay (Brezovec and Hampl, 2021;Ho et al., 2020;Vij et al., 2020), intention to use (Fioreze et al., 2019), and stated preferences (Kim et al., 2021b).Therefore, it is anticipated that younger generations will be more inclined to adopt the service compared to older generations.On the other hand, it is recognized that the demand for travel and trip frequency (Farahmand et al., 2021)) and the inclination to adopt emerging technologies (Lopez-Carreiro et al., 2021a;Ye et al., 2020) vary across different age groups.Hence, it is important to not solely emphasize the overall influence of specific socio-economic indicators in isolation but also to investigate the variances in the factors that either facilitate or obstruct MaaS acceptance among diverse demographic groups.An interesting avenue for further research lies in the exploration of divergent determinants that shape the   Negatively related to MaaS choices (Brezovec and Hampl, 2021;Ho et al., 2020;Vij et al., 2020) Gender Male or female (Caiati et al., 2020;Lopez-Carreiro et al., 2021a, 2021b).
Men have higher willingness to pay and intention to use MaaS [S21, S23, S42, S44].(The references labeled with 'S' specifically denote the primary studies listed in Appendix A).

Education
The highest level of education completed by the traveler by the time the study was conducted (e.g., undergraduate, graduate, post-graduate studies, nonuniversity level (Hoerler et al., 2020;Lopez-Carreiro et al., 2021b).
Positive relation between employment status and the use of MaaS.Full-time employees are considered most likely to use MaaS [S41, S42, S30].

Household composition
The possible combinations of the total number of children and adults in a household (Johnson et al., 2021).The household situation of the travelerwhether being single (with or without children), living with someone/married with or without children, living with other adults (non-family), or living with parents/family (Caiati et al., 2020).

Negative relation between the income of individuals and their intention to use MaaS [S5, S20, S21, and S51]. A positive correlation between income and MaaS adoption [S1, S4]. Vehicle ownership
The influence of the ownership of one or more types of vehicles, such as car, motorbike, scooter, or others, has also been empirically investigated in the literature in different forms (Caiati et al., 2020;Matyas and Kamargianni, 2019a;Vij et al., 2020;Zijlstra et al., 2020).Private car ownership (Caiati et al., 2020;Farahmand et al., 2021), the number of private cars in the household (Ho et al., 2021;Krauss et al., 2022), or the availability of a car for personal use (Brezovec and Hampl, 2021;Ho et al., 2020;Tsouros et al., 2021) are examples of such forms.
The majority of the studies (e.g., [S2, S26, S30]) agree that private car ownership is negatively associated with the use of MaaS.The studies [S42], [S45], and [S49] found that the ownership of a car, van, motorcycle, or bicycle had no real impact on MaaS acceptance.

Driving license ownership
Whether a traveler holds a valid (car) driving license at the time of the study or not (Caiati et al., 2020;Hensher et al., 2021;Ho et al., 2020).
The study in [S14] found that owning a driver's license is not a significant predictor of MaaS acceptance.Whereas the study in [S10] indicates a negative correlation with the number of licensed drivers in the household.

Health condition
Self-declared physical condition of an individual (Kim et al., 2021b).
Positive relation between good health and the individual potential to adopt MaaS (e.g., [S32] and [S45]).

Dress code
Refers to a strict dress code which is manifested in wearing a suit and tie, or a non-strict dress code indicating that employees are allowed to wear business casual or casual clothes (Hoerler et al., 2020).
One study found that employees who have the option to wear a flexible dress code have a higher preference for carpooling services in a MaaS bundle [S19].

Pro-environmental attitude
The concerns about the impact of human behavior on the environment (Lopez-Carreiro et al., 2021a) and traveler's concern to act in an environmentally friendly manner and preserve natural resources (Hoerler et al., 2020).
MaaS and MaaS bundles are more preferred by individuals who show concern for the environment and who consider MaaS as an ecological friendly choice [S16, S15, S16, S25, S21, S51].

Sharing service membership
Ease of access and usage of shared vehicles or shared rides (Krauss et al., 2022).A sharing service membership occurs when an individual is registered to a car-sharing (Caiati et al., 2020) or a bike-sharing scheme (Jang et al., 2021).
Membership in any existing scheme or the use of different mobility platforms increases the preferences of individuals for MaaS and for the use of public transport [S5, S17], and [S49].

Habit
Maintaining the same number of trips and travel modes in conducting a trip (Schikofsky et al., 2020).
Studies in [S27, S32, S36] agree that habits play an important role in choosing MaaS plans.

Smart phone ownership
Whether an individual owns and uses a smart mobile phone or a similar device on a regular basis (Caiati et al., 2020).
Only few studies explicitly investigated this factor, many assumed ownership of smart devices as their analysis relate to some MaaS [S25] and [S43] agree that the degree of comfort users usually have while using technology positively influences the intention to use MaaS.

Individual innovation
Ability of an individual to be good at discovering and trying new things with enthusiasm (Fioreze et al., 2019), or accepting new things (Ye et al., 2020).Traveler characteristic Definition Finding The individual's receptivity to consider alternatives, enjoy new activities (or ideas), and be curious (Lopez-Carreiro et al., 2021a).
Studies in [S1, S19, S27] point out that individuals' openness increases their acceptance for MaaS.

Need for control
Travelers' demand for total control on the entire transport network, such as the availability of mobility services and parking possibilities to manage uncertainty (Lopez-Carreiro et al., 2021a).
The study in [S25] indicates a positive relationship between the need for control and MaaS acceptance.

Hedonic motivation
Intrinsic motivation that captures the emotional benefit derived from the use of a technology-based product or service solution (Sochor et al., 2015b;Str€ omberg et al., 2018).
Hedonic motivation has positive effects on the behavioral intention to use MaaS [S36].

Trip characteristic Definition Finding
Mode egress time The time in the end of the trip, the door-to-door service (Krauss et al., 2022

Mode access time
The time by which an individual accesses a mobility service, such as the public transportation (Kim et al., 2021a) or the time spent searching for and accessing a shared mobility service or a private car (Krauss et al., 2022).
The access time to public transport stations had a negative influence on choosing MaaS as shown in [S20].

Trip frequency
The number of times an individual uses a specific transport mode per week based on a trip purpose (Farahmand et al., 2021;Ho et al., 2020).
Majority of the studies agree that the individuals who perform more frequent trips are more likely to adopt MaaS [S12, S18, S26, S45], or to have a higher probability of selecting MaaS bundles [S14].

Trip purpose
Objective of the mobility service use, such as commuting to work or school, traveling for shopping (Agbe and Shiomi, 2021), or for social trips or leisure (Fioreze et al., 2019).

Trip duration
The average time spent per day in traveling using various transport modes to and from the desired location (Caiati et al., 2020).This time may also include walking and/or waiting time to use the desired transportation mode [25,65].
An insignificant effect of the trip duration on the intention to use MaaS [S2, S14, S22, S51].

Expectation of mobility mode integration
The individuals' expectations of the level of integration (of the services) provided by MaaS applications.Individuals must be willing to combine different modes of transport as part of their travel patterns (Lopez-Carreiro et al., 2021a).
Multimodal travelers are more likely to adopt MaaS than unimodal travelers [S1, S25].

Travel cost
The cost per person to perform one trip using a transport mode of choice (Jang et al., 2021).This factor also represents the total fare spent on the current travel record of the individual (Kim et al., 2021a).
The higher the perceived travel cost of an individual the higher the likelihood that the individual will adopt MaaS [S42].The more the individual spends on transportation the less likely the individual is to pay for a MaaS mobility package [S23].

Search time for parking
The time often spent at the end of a journey to search for and park a vehicle in a specified space (Krauss et al., 2022).
The search time for parking positively influences MaaS acceptance.This is especially true in the end of the journey where e-bikes or e-scooters can be easily parked and reduce the disutility [S22].

The parking time is insignificant in MaaS acceptance [S7]. Multiple mode use
The willingness to integrate different modes of transport into one's travel patterns (Alonso-Gonz alez et al., 2020) and being comfortable combining multiple modes to optimize one route (Kim et al., 2021b).

Trip pattern
The number of activities, locations, and times that travelers have in their plans (Storme et al., 2020).
The traveler performs different activities to different locations [S39] and at different times this might result in a stressful situation and might not be very feasible with MaaS.

Number of transfers in a chosen mode
The number of times the passenger needs to change from one to another transportation mode or within the same mode for a single trip (Kim et al., 2021b).
This factor has a negative influence on MaaS [S19], [S22], and car users have high resistance for transferring between modes, therefore a lower preference for intermodal MaaS options (such as public transport and bike-sharing) [S19].

Traveling with stranger
Whether travelers are comfortable traveling with other individuals (Storme et al., 2020).
Individuals who do not like to travel with strangers are less likely to subscribe to MaaS [S8].

Crowding percentage
The density of passengers.When passengers have access to this kind of information, it is assumed that their satisfaction level with the service increases (Casey et al., 2017).
The high density of passengers in vehicles, access ways, and stations influence modal choice (Alyavina et al., 2020), or has insignificant influence on MaaS mode choices [S22].

Communications in Transportation Research 4 (2024) 100119
Table 5 Service and technology characteristicsdefinitions and findings.

Quality characteristic of the service Definition Finding
Price/cost The total monthly cost for all transport modes included in a MaaS package/bundle (Brezovec and Hampl, 2021), i.e., the financial cost of a package including public transportation, and/or bike sharing, and/or taxi, and/or car sharing, etc. (Biehl and Stathopoulos, 2020).
The interest in MaaS packages drops with the increase in the package price [S16] as users tend to prefer cheaper MaaS bundles.Users are less sensitive for long term costs of vehicle ownership than the MaaS subscription costs [S11].Monthly subscription price to MaaS scheme The total subscription price for a bundle on a monthly basis (Caiati et al., 2020;Hensher et al., 2021).Accordingly, users are expected to pay a monthly fee to access a predetermined amount of mobility services (Caiati et al., 2020;Hensher et al., 2021;Vij et al., 2020).
The higher the monthly subscription costs, the lower the predicted share of the population that will use it.
In their case, pay-as-you-go with unlimited access to all modes has a high preference [S42].

Perceived usefulness
The extent to which a technology is expected to improve a potential user's performance (Davis, 1989;Dikici et al., 2018;Lopez-Carreiro et al., 2021a).
The perceived usefulness positively influences behavioral intention, attitudes and willingness to use MaaS [S31, S36, S44, S46].Perceived ease of use The amount of effort required to effectively use a technology (Davis, 1989;Lopez-Carreiro et al., 2021a).
A weak direct effect on willingness to use MaaS [S36].Perceived ease of use positively influences perceived usefulness and individual attitudes towards multimodal mobility apps [S46].Perceived value A consumer's overall assessment of the trade-off between the benefits and the costs (Chen and Chen, 2023;Coconea et al., 2019a).
A direct and significant effect of perceived mobility value on the individual attitude towards multimodal trip-planning apps [S46], and a direct positive effect between the perceived value and level of satisfaction and the intention to adopt MaaS [S48].

Awareness
Whether individuals have previous experience in the use of membership transportation methods and are familiar with the use of the app (Ye et al., 2020).
Individuals who find MaaS familiar and necessary have a higher intention of using the service [S21, S44, S47].

Convenience
A state where individuals access a private vehicle close at hand, or car-sharing or car rental without having to deal with parking or maintenance (Sochor et al., 2016).
Having the convenience and a sense of flexibility positively influences the likelihood to use MaaS [S8, S34, S38, S47].

Usability
The usability aspects of the digital interface, a medium commonly used with software systems (Turetken et al., 2019a(Turetken et al., , 2019b) that allow trip planning, booking, ticketing, payment, and real-time information provision that can be personalized and customized to meet the end users' needs (Hoerler et al., 2020).
The majority of participants suggested having a unified interface in all the countries in which MaaS operates in [S34].

Reliability
The importance of the trust of users in the functionality of MaaS services (Alyavina et al., 2020).
The studies in [S3, S27, S48, S49] agree on the importance of the reliability of MaaS services in the use of the service.

Perceived risk
The uncertainty about the outcomes of a particular decision (Ye et al., 2020).

A negative influence of perceived risk on behavioral intention [S44]. This risk decreases when individuals rely on journeys within their own city [S47]. Privacy protection
The potential of sharing or limiting the access of the service to sensitive information, such as location tracking (Caiati et al., 2020).

Platform features Planning
A user requesting for a trip between point A and point B, the app checking the location of services from a provider and their estimated costs and time for the trip, and mapping out a route for the user such as a journey planner (Ho et al., 2021).It includes route optimization by suggesting the most efficient route for travelers (Casey et al., 2017).
The use of route planners and route travel applications positively influences the adoption of MaaS [S8, S26].

Payment
Smart ticketing or integration of the payment, balance checking, invoicing, and discounts (Casey et al., 2017).
Users appreciate the pay-per-use concept with the flexibility of topping up credit [S17, S30].

Booking
The ability of a user to seamlessly book a service to complete a trip from the app (Ho et al., 2021).It can be considered as a reservation of a service (Casey et al., 2017).
The users are concerned about validating the ticket and proving the subscription in case of network failure [S34].Personalization Functionality to allow user to make choices based on personal needs (Hoerler et al., 2020), or customized recommendations (Casey et al., 2017).
Personalized support and recommendations are very important for users in the acceptance of MaaS [S30, S34, S37].

Social media
The social networking of users within their connectivity network (Casey et al., 2017).Users are not interested in enabling the MaaS feature to be part of a social network of other users who have already subscribed to MaaS [S34].

Rating
The positive and/or negative reviews and critiques from the general public (Caiati et al., 2020) or other users of the service (Casey et al., 2017).
Positive ratings from other users positively influence the intention to subscribe to MaaS [S5].

Assistance
Personal support or alerts/notifications that are sent to the user (Casey et al., 2017).
Several studies agreed on the importance of personal support in the acceptance of MaaS, by which users expect mobility brokers to take care of incidents when they arise [S24, S34, S37].

Enhancing service
Providing individuals with personalized services that match their needs and habits and therefore enhance the attractiveness of MaaS and other similar mobile service technologies (Athanasopoulou et al., 2022b).
Young participants were interested in having information about charging points in vehicles [S24].

Service configuration Public transportation (PT) as a transport mode
If the PT is included as a transport mode in a MaaS (Agbe and Shiomi, 2021).The travel behavior, in this case, is related to public transport services, such as trains, buses, or trams (Karlsson et al., 2016).
The users of PT are more likely to subscribe to MaaS services [S1, S15, S21, S45].
Train as a transport mode Inclusion of train as a transport mode in a MaaS package (Agbe and Shiomi, 2021).
Including the train as a transport mode in a MaaS package increases the chances of the package being selected by users [S1, S5, S8, S41].

Bus as a transport mode
If the transportation by bus as a form of PT is included in a service package (Agbe and Shiomi, 2021).Users who travel with only one companion are more likely to pick up a package that includes a bus as a mode of transport [S18].Car-sharing as a transport mode The possibility of having car-sharing as an alternative mode in a MaaS package (Matyas and Kamargianni, 2019a).Ride-sharing as a transport mode If the ride-sharing as a demand-responsive mode is included in a MaaS package (Caiati et al., 2020).
Travelers usually use ride-hailing for short trips and leisure purposes and frequent ride hailing users are often willing to use MaaS [S49].

Private car as a transport mode
An ownership model of a private vehicle, namely a car for use in trips (Caiati et al., 2020).Individuals who mainly use their private cars to commute are less likely to subscribe to MaaS (e.g., [S5, S6]).

Car rental as transport mode
A service where users pay a fixed fee for an hourly or mileage allowance and a per-minute or per-kilometer marginal price for the use of a car in travel (Caiati et al., 2020).
Car rental as a transport mode is insignificant to the willingness to pay for MaaS [S1, S5].
Taxi as a transport mode If the taxi service as a form of a demand-responsive mode is included in the MaaS package (Caiati et al., 2020).
A service as the least preferred mode of transportation and a mode that is negatively associated with adding it to a MaaS plan (e.g., [S1, S5, S16, S29]).Bike-sharing as a transport mode If the bike sharing or service offered by particular providers is included in the MaaS package (Matyas and Kamargianni, 2019a).
The presence of bike-sharing in a MaaS plan positively influences the individual likelihood of choosing the plan [S33].

MaaS subscription plan
The duration of having monthly subscriptions instead of paying per individual trip to use transport modes (Alonso-Gonz alez et al., 2020).
Monthly subscription plans were found to be appealing for non-frequent car users [S12].The more alternatives available for users the more 'mentally' accessible they feel due to having to reflect on their travel needs [S17, S38].

Table 6
Urban environment characteristicdefinitions and findings.

Urban environment characteristic
Definition Finding

Transportation facility
The attributes of the transportation facilities in the urban environment of the traveler, including the existence of public or bike-sharing stations (Kim et al., 2021a).
Having good coverage of public transportation encourages users to subscribe to MaaS [S20, S28, S29, S49].

Cost of parking
The parking tariff for a chosen parking space given the duration of parking (Farahmand et al., 2021).Users are more likely to change to other modes of transportation in case of available parking spaces [S6].

Residential type
The urban or rural classification of the place of residence of the respondent (Liljamo et al., 2020), such as city, countryside or agglomeration (Hoerler et al., 2020).
Individuals living in denser environments are more likely to adopt MaaS [S25, S45].The study in [S23] reports that individuals living in densely populated urban areas have a lower willingness to pay for MaaS.

Social influence
The idea that one's own behavior is moderated by the actions of others, be their family members, friends, other people in their social network, or complete strangers (Hoerler et al., 2020).Their use of the service (Caiati et al., 2020) or their reviews of the service (Jang et al., 2021) is considered influential in adoption.
Social influence found to have a positive impact on the willingness to use MaaS as users start perceiving the service to be easier

Local policy and regulations
Relevant policies and regulations that are applicable to the urban environment where the traveler resides (Hoerler et al., 2020).
No significant effect of policy treatment on the openness to MaaS services [S15].

Cost of car ownership
The financial commitments associated with owning a carthe estimates considered in the purchase of a car being gasoline, taxes, maintenance, and parking fees (Agbe and Shiomi, 2021).
The high maintenance and parking costs of cars lead individuals to accept other modes and not appreciate cars given their high costs [S37, S38].

Network stability
The importance of appropriate mobile network coverage during individuals' travel (Alyavina et al., 2020).Bad network coverage negatively affects the service that the users receive [S3].

Communications in Transportation Research 4 (2024) 100119
use of MaaS among the younger generation and the older demographic.
Understanding the nuanced factors that influence MaaS acceptance within these age groups can shed light on how technology preferences, travel habits, and socio-economic considerations vary, offering valuable insights for the development of targeted strategies to promote MaaS adoption and meet the diverse needs of these demographic segments (Caiati et al., 2020).As indicated above, the socio-economic and demographic factors (Alonso-Gonz alez et al., 2020;Feneri et al., 2022;Fioreze et al., 2019;Zijlstra et al., 2020) have a significant influence on the acceptance of MaaS.Several primary studies that investigated trip frequency agreed that this factor positively influences MaaS acceptance.In that case, older generations perform fewer trips than younger individuals (Kim et al., 2021b).Zijlstra et al. (2020) discuss that individuals who frequently use public transportation are more likely to adopt MaaS.Car ownership (as a type of vehicle ownership) revealed a negative association with MaaS acceptance (Alonso-Gonz alez et al., 2020; Alyavina et al., 2020).A similar factor that was also heavily investigated is the availability of a car for personal use.This factor goes beyond the ownership of a private vehicle yet explores whether cars available in the household are frequently used.Most of the primary studies agreed that frequent car users are less likely to adopt MaaS (Fioreze et al., 2019;Ho et al., 2020;Kim et al., 2021a) or are less likely to select complex MaaS plans (Tsouros et al., 2021).
At the technology level, the cost of MaaS is among the most influential factors and the most significant factors in attracting potential users, especially car users (Casey et al., 2017).All the primary studies agreed that cost has a negative influence on the acceptance and use of MaaS.The convenience of advance booking and flexibility of choosing a mobility mode and selecting packages (Fioreze et al., 2019;Polydoropoulou et al., 2020a).Concerning the platform features, planning is considered the most important feature that positively influences the acceptance of MaaS.Individuals who use route planners on a weekly basis are more likely to adopt MaaS (Fioreze et al., 2019).
At the urban environment level, the factors related to the transportation facility are among the most influential factors when it comes to MaaS acceptance.Matyas and Kamargianni (2021) discuss that MaaS packages are not a viable option for individuals living in the suburbs and needing proper access to transportation.Another highly investigated factor is the residential type, by which the majority of the empirical studies agreed that potential adopters of MaaS mostly live in densely populated urban areas (Alonso-Gonz alez et al., 2020;Liljamo et al., 2020), or in high-income zones (Lopez-Carreiro et al., 2021a).

Least influential factors
At the traveler level, gender is found insignificant in influencing the propensity to adopt MaaS (Feneri et al., 2022;Liljamo et al., 2020;Schikofsky et al., 2020), with little influence on the willingness to pay for particular MaaS bundles.Factors such as the mode of egress time, waiting time in the station, mode access time, parking time, and search time for parking are investigated in very few studies and either have a low or no direct influence on the acceptance of MaaS.They rather affect the perceived utility of a particular transport mode.For instance, they weigh whether a shared vehicle would be a better option than a private car if the egress time is higher (Krauss et al., 2022).Traveling with strangers is investigated in a single study and found to negatively influence the acceptance of MaaS (Fioreze et al., 2019).
Similarly, crowding is found insignificant in its influence on mode choice (Krauss et al., 2022).These factors might be an outcome of other factors, such as the extent to which an individual is open to trying different modes to reach their destination or whether they are stricter regarding their habits and choices.At the technology level, social media appeared only in a few studies (Lopez-Carreiro et al., 2020;Polydoropoulou et al., 2020a) and did not show importance in the intention to use MaaS packages.Given the importance of social media in our daily lives, social networks and social influence may require more thorough empirical work.

Contradicting factors
The primary studies showed that public transportation card ownership has both a negative (e.g., [S1]) and a positive (e.g., [S29]) influence on the individual willingness to pay for MaaS service (Caiati et al., 2020;Karlsson et al., 2016).Income also shows contradicting results in the primary studies investigated.For instance, the studies [S5], [S34], and [S45] report that the individuals of higher income are more likely to adopt MaaS.However, other primary studies contradicted this result.They indicate that individuals of lower income have fewer private vehicles and, therefore, have a higher intention to use MaaS and select multimodal plans (Kim et al., 2021b;Matowicki et al., 2022).As for the household composition, larger households or households with children have higher acceptance of MaaS and are more likely to pay for the service (Vij et al., 2020;Zijlstra et al., 2020).However, a few studies show that travelers living alone (Alonso-Gonz alez et al., 2020;Lopez-Carreiro et al., 2021a) or with fewer than two children (Ho et al., 2018) are the most likely adopters of MaaS.
Some studies found trip duration as an insignificant factor for the intention to use MaaS (Ho et al., 2021;Ko et al., 2021).Feneri et al. (2022) found that an increase in trip duration leads to a decrease in bike sharing mode in a MaaS.Future research should investigate this factor further by considering the transport mode and whether the transfers are included in the trip duration.Many studies indicate public transport card ownership as a factor with a positive influence on selecting a MaaS plan, especially if it includes public transportation as an option (Alonso--Gonz alez et al., 2020;Lopez-Carreiro et al., 2021b;Matyas and Kamargianni, 2019b).However, some studies found a negative influence of commuter pass ownership on MaaS subscriptions (Krauss et al., 2022;Mulley et al., 2020) and willingness to pay (Agbe and Shiomi, 2021).
At the user characteristics level, the trip purpose is among the factors that led to contradictory outcomes and require further investigation.Individuals taking many leisure trips are likelier to adopt MaaS (Butler et al., 2020).For instance, individuals with flexible working schedules or who are unemployed are more likely to have a different trip pattern and less consistency in travel time, purpose, and destination.
At the technology level, assistance and enhancing services were tested only in a few studies.Understanding the elements that enhance the MaaS service and assist the users in easing the traveling experience can make the service more attractive to a broad segment of users.The payment type also showed different preferences for users.In a few studies, individuals preferred a pay-as-you-go option in MaaS (Karlsson et al., 2016;Matyas and Kamargianni, 2021).Individuals who seek high convenience choose a fixed contract with flexible termination (Brezovec and Hampl, 2021).Hence, further research is required to investigate the interplay between diverse payment types and MaaS acceptance.
As for the urban environment, limited results were found in the primary studies on the role of social influence on the acceptance of MaaS.Altay and Okumus ¸(2022) and Kim and Rasouli (2022) found that social influence has a positive effect on the willingness to use MaaS, while the study by Hoerler et al. (2020) indicates an insignificant effect of peers, which is considered a key part of the social influence factor.It is evident that each local context should be highlighted and investigated further in terms of the available mobility services, especially those delay individuals from adopting MaaS.

Further research directions
Given the differences in culture, socio-economic, and political characteristics that shape the mobility domain in different countries (Caiati et al., 2020), it is also important to further investigate the lifestyle and cultural differences between users in different countries or regions of a country.Public transportation and cycling are part of the everyday life of individuals in a number of European countries, such as the Netherlands, while the infrastructure and lifestyle of individuals show significant differences in countries such as Australia and USA, where private cars play an essential role.The availability and quality level of transport facilities (Kim et al., 2021a) and other factors regarding the urban environment and established mobility culture (Matyas and Kamargianni, 2019a) exhibit substantial diversity from one country or region to another.Hence, a promising avenue for exploration entails conducting a comprehensive examination and comparative analysis, utilizing insights from prior studies, to illuminate the regional disparities.
In collaboration with private entities, governmental bodies play an important role in building and facilitating the uptake of new services that use the latest technology to make MaaS a viable option for citizens.The development of a real-time computing platform provides swift and reliable support for the users with the aim of increasing the trust and convenience of service (Butler et al., 2021;Kamargianni et al., 2016).Incorporating autonomous vehicles into public transportation and shared mobility services brings additional challenges and factors that require further studies (Goodall et al., 2017).In such settings, for instance, safety would be critical for user acceptance and for public and private institutions to ensure within their urban landscape.
It is essential to acknowledge that the worldwide implementation of MaaS is an ongoing endeavor.Consequently, current studies have predominantly focused on comprehending the preferences and perceptions of potential MaaS users, relying heavily on scenario-based methods to collect this information.Given the current maturity of the service and the limited number of MaaS platforms in operation, it is still challenging to measure the actual adoption of MaaS.Hence, future research should also aim at investigating the level of alignment between these findings and the factors influencing real-world adoption and use.More implementations in different contextual settings will provide room to study the adoption rates of the individuals based on their real experience.

Conclusions
As a system that aims to provide customers with a comprehensive range of mobility services (Heikkila, 2014), MaaS shows great potential for reshaping the mobility domain and promoting flexible multimodal mobility (Caiati et al., 2020).In this paper, we aim to provide an understanding of the factors that potentially influence the acceptance of MaaS and pinpoint areas for future research.To this end, we conducted a systematic literature review of 51 empirical works.A thorough analysis of these works yielded 71 factors that potentially play a role in MaaS acceptance and adoption.We categorized them into three main groups related to (1) traveler and trip characteristics, (2) service and technology characteristics, and (3) urban environment characteristics.We elaborate on the findings regarding each factor and discuss the results to provide a baseline for future research.
Our review has identified several factors that are proven to have a significant influence on MaaS acceptance.However, there are different sets of factors that appeared in several studies and showed an influence on the willingness to pay or intention to adopt.Acceptance of MaaS is influenced by a combination of (1) user characteristics and traveler attributes, such as car ownership, frequency of travel, or the use of multimodality services; (2) service and technology, such as the impact of mobility costs, platform features, and assistance, and the use of different transport modes; and (3) urban environment, such as the residential area of the user and the efficiency of transportation infrastructure.Some factors were intensively studied in the literature, such as the socio-demographic factors (Hensher et al., 2021;Ho et al., 2018;Lopez-Carreiro et al., 2020;Mulley et al., 2020) and costs (Agbe and Shiomi, 2021;Brezovec and Hampl, 2021;Kim et al., 2021b;Liljamo et al., 2020), whereas other factors, such as convenience (Karlsson et al., 2016;Matyas and Kamargianni, 2021) and social influence (Hoerler et al., 2020;Ye et al., 2020) are the focus of fewer empirical works.These studies also point out that several respondents still value and prefer a private car with the burden of ownership over alternative modes of transportation (Kim et al., 2021a).When MaaS becomes capable of fulfilling the daily mobility needs of individuals living in different areas (suburban and urban), individuals will become more comfortable in changing their choices (Utriainen and P€ oll€ anen, 2018).
MaaS becomes interesting in terms of sustainable people-centered mobility when multimodal transport modes are integrated using additional digital services, and users get easy access to the mobility services without having to think about the means of transport or the respective providers.A major responsibility lies with cities, municipalities, and states, which must create an appropriate framework for MaaS (M€ oller et al., 2019;Pankratz et al., 2018).In addition to technical and infrastructural measures, a MaaS framework should also include rules and policies to ensure meaningful integration of public and private MaaS offerings and the highest level of accessibility and affordability for these offerings.Once again, open collaboration between all local, regional, and national stakeholders is essential to establish trust among the actors of the MaaS ecosystem (Boer et al., 2022b;Jittrapirom et al., 2020).
This study contributes to both research and practice.Researchers will find this work useful as a comprehensive source that presents the factors investigated in the literature and points out areas where future research can focus.Our study shows that there is still a limited understanding of the interplay between many factors and their influence on MaaS acceptance.By studying, categorizing, and describing these factors, our review also contributes to the consistency and coherence in operationalizing them, thereby furthering the rigor of future empirical works in this field.
Practitioners will also consider this study valuable as it serves as a pointer to the factors that should be considered and tackled in the design and implementation of new MaaS platforms.For instance, the factors related to the urban environment reveal an important aspect that shows individuals living in cities and areas that have a good transportation infrastructure are inclined to switch from using their private vehicles to using MaaS (Butler et al., 2021).However, in rural areas or areas where the public transport system is underutilized and lacks sufficient coverage, individuals find it hard to stop using their private vehicles (Dick et al., 2020).In this case, a different mode of transportation that is affordable and provides a reasonable connection time should be explored.The government may need to provide subsidies in collaboration with the businesses that offer such mobility modes to achieve greater acceptance and coverage.At the technology level, the price of MaaS packages is among the critical factors influencing the acceptance of the service.Therefore, policies focusing on the financial element that shows private vehicles and unsustainable choices as costly and expensive will trigger individuals over time to switch to a better alternative.
The limitations of this research are related mainly to the underlying research method of the conducted systematic literature review.Given the research objective of this paper, we relied only on empirical studies.The inclusion and exclusion criteria used to locate relevant works limited the type of studies to be reviewed thoroughly.Furthermore, this study excluded books, conference proceedings, and gray literature (such as white papers, consultant reports, and magazine articles).Including a wider set of published works (e.g., by searching digital libraries other than Web-of-Science, such as Scopus) can positively contribute to a broader understanding of the influential factors on MaaS.However, we accommodated this limitation by conducting forward snowballing on the primary set of peer-reviewed articles iteratively to locate relevant works published in other channels.Since there is an ongoing flow of new research published on different channels, it is important to update the current work to reflect the latest findings regarding the influential factors of MaaS acceptance and use.

Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.).His research centers on digital business models.He studies and develops methods and tools that aid in designing and implementing innovative digital solutions.In doing so, he leverages the practices and technologies from information systems and business process management fields.Specifically, he is interested in collaborative digital business models, which enable value co-creation among various stakeholders and contribute to effective and sustainable outcomes for all actors involved.His recent projects include designing and implementing digital platforms that facilitate the seamless integration of different mobility services in urban areas.
, 17 articles) are published in the journal of Transportation Research part A: Policy and Practice.Of the remaining 31 articles, Travel Behavior and Society journal corresponded to the second highest publication with 6 studies, followed by 4 publications in the Transportation Research Record and Transportation.The rest of the journal publications are spread over 15 different journals.Most of the reviewed empirical studies are published in journals with a transportation focus, showing the increased interest in the MaaS topic in the field.
field trials [S8, S36].Public transport card ownership A season (Lopez-Carreiro et al., 2021b), a travel card, or a bus pass (Matyas and Kamargianni, 2019b) used often for the public transportation services, such as the train or the bus.A direct relationship between the availability of this pass and the intention to adopt MaaS [S26].Individuals who own a travel card have a higher intention to include public transport in their plans [S29].Technology affinity The individual's openness, interest in, and competence with (new) technologies (Lopez-Carreiro et al., 2021b).
Individual innovation related positively to MaaS acceptance [S8, S25, S43].Openness to try (continued on next page) H.E. Mustapha et al.Communications in Transportation Research 4 (2024) 100119 Individuals who perform several leisure trips are more likely to adopt MaaS [S45].Individuals who have high variety in their trip purposes are willing to use MaaS [S49].
[S44].Social influence impacts the attitudes and intention to adopt multimodal trip apps [S46].A low share of individuals belonging to the peer followers' segment is negatively associated with MaaS adoption [S50].
is an affiliated Postdoctoral Researcher in the Department of Industrial Engineering and Innovation Sciences at Eindhoven University of Technology (TU/e) and a Lecturer in the Institute for International Business Studies at the University of Applied Sciences Utrecht (HU).Her research interests center around sustainability and energy transition with the use of behavior change theories and strategic niche management research concept.Her current research focuses on developing a comprehensive understanding of individuals' behavior and underlying intentions to use mobility-as-a-service and similar services.Baris Ozkan is an Assistant Professor in the Department of Industrial Engineering & Innovation Sciences at Eindhoven University of Technology (TU/e).His research interests are centered around Service Systems Engineering, with a specific focus on developing methods and tools for designing, implementing, and improving business processes, business models, organizational capabilities, and digital artifacts such as digital platforms in a digitally-enabled service ecosystems context.Oktay Turetken is a Professor in the Department of Industrial Engineering & Innovation Sciences at Eindhoven University of Technology (TU/e

Table 2
List of journals of reviewed empirical studies.

Table 3
Factors and categories.

Table 4
Traveler and trip characteristicsdefinitions and findings.
[S25] indicate a likely service uptake of individuals that are living alone or with no children.Whereas other studies, [S5, S45, S14] show that individuals with children or living with family are more likely to uptake MaaS services.
IncomeAverage annual or monthly income represented in a scale (e.g., low, middle, high) (Agbe and Shiomi

Table 4
(continued ) ). Ride-pooling may result in shorter egress time; making egress time more important for individuals with private cars than individuals who use shared services [S22].Waiting time in the station Time required for waiting in stations or at stops (Ko et al., 2021).In this case, waiting time is added for public transportation and ride pooling since the vehicle usually takes some time to arrive at the user's location (Alonso-Gonz alez et al., 2020).Individuals having a relatively short commute time (30-60 min) show lower intention to use MaaS than those with longer commute time [S21].