Skip to main content

SYSTEMATIC REVIEW article

Front. Sustain. Cities, 25 January 2023
Sec. Urban Transportation Systems and Mobility

A systematic literature review of mobility attitudes and mode choices: MENA and South Asian cities

  • 1Department of Planning and Business Development, Public Transport Agency, Roads and Transport Authority, Dubai, United Arab Emirates
  • 2Department of Work, Technology and Participation, Technische Universität Berlin, Berlin, Germany
  • 3Center for Technology and Society, Technische Universität Berlin, Berlin, Germany
  • 4Department of Transport and Supply Chain Management, College of Business and Economics, University of Johannesburg, Johannesburg, South Africa

Urban mobility behavior is influenced by complex interrelations of personal attitudes, neighborhood design, emerging digitalized shared mobility services, and urban governance. The transformation of urban mobility ecosystems in the Middle East and North African (MENA) and the South Asian (SA) regions lacks an in-depth comparative review to understand the determinants of mobility attitudes and mode choices. The objective of this paper is to systematically study the existing literature on cities in the MENA and SA regions to provide a comparative review of the analyses and the findings on urban mobility attitudes in light of prevailing societal conditions and urban-spatial forms. A systematic methodology was deployed to shortlist recently published journal papers from the years 2000 to 2022 for the MENA and SA regions. Application of the (shortlisting) methodology has identified 43 studies from the MENA region and 43 papers from the SA region to be most suitable for the review of comparative analysis of urban mobility behavior. The review found that travel choices in both MENA and the SA regions are impacted by the usual determinants such as demography, socio-economic characteristics, vehicle ownership, and the quality and maturity of (urban transport) spatial forms. The mobility behavior in these regions, is to some extent, can be said to be in alignment with the observed behavior across the developed western cities elsewhere in Europe and North America. The review identified that in both the MENA and the SA regions, mobility choices are also influenced by certain additional factors, such as cultural norms, adverse climatic conditions and socio-economic standings, etc. The literature indicates that ethnic and income disparities are deeply embedded in the socio-spatial arrangements of the cities in the MENA and SA regions. Future research can assess the relative influence of these factors and to determine correlations between mobility attitudes and urban forms to build better cities.

1. Introduction

Historic and recent research in the field of travel behavior reiterates that relationships between mobility attitudes, travel behavior and the built environment are complex (De Vos, 2022). Before the 1960s the focus of transport research was simplified to the movement of humans between geographical regions and within urban areas rather than explaining the mechanism of behaving acts (Golledge et al., 1972). Then in the early 1960s two thinking streams emerged: one stream highlighted the role of people's perception of the environment in explaining the human-environment relations and the second stream focused on exploring the effects of motivation, aspirations, and goals in the decision-making process (Golledge et al., 1972). Then from the 1970s onwards the inter-relationships between residents' demographics, urban form and travel became formalized as a research field in spatial sciences and transport sciences (Boarnet and Crane, 2001; Ewing and Cervero, 2001; Timmermans, 2003; Hickman and Banister, 2005; Scheiner and Holz-Rau, 2007). This understanding came from the concept that travel might be explained by urban form and this insight gradually arrived in the science of transport planning and led to extensive work (in both academia and industry) in terms of integrated urban and transport planning.

In 1980, Salomon researched attitude as a factor in explaining travel behavior and in the 1990s, transport researchers became more convinced that there are more complex interrelations to explain travel behavior than simply comparing it to spatial elements (Salomon, 1980). Hence, the transport research field added subjective dimensions such as attitudes to the objective dimensions of space and individual life situation (Kitamura et al., 1997; Boarnet and Sarmiento, 1998; Bagley and Mokhtarian, 2002; Golob, 2003; Parkany et al., 2004; Handy et al., 2005). The travel behaviors and their impacts vary markedly by income and other demographic groupings, but recently the disruptive innovations (such as smartphone-based shared mobility and MaaS) have been redefining the transportation industry and changing users' behaviors. Additionally, change in residential neighborhood has a strong impact on travel attitudes as examined by De Vos et al. (2021) in Belgium.

Travel behavior is affected by attitudes both directly and indirectly because travel attitudes are not stable constructs but are subject to change, especially when an inconsistency (or dissonance) exists between attitudes and related behavior (De Vos, 2022). In the same research De Vos (2022) found that five relationships seem present between travel attitudes, travel behavior, and the built environment: that between built environments and travel behavior, and four relations created by the interdependencies between (i) travel attitudes and the built environment, and (ii) travel attitudes and travel behavior. Attitudes mainly affect behavior in the case of high levels of freedom of choice. High-income households, for instance, will mostly have a free choice of where to live and how to travel, likely resulting in a chosen residential neighborhood and travel patterns in line with travel attitudes.

Attitude-based segmentation of the urban mobility market is gaining momentum in Western cities because it helps in differentiating commuters' needs and then drives the evolution of the commercial value of shared mobility modes. This approach is important in understanding customers' relation to time, work, society, money and preferences between price and comfort.

Overall, commuters' attitudinal factors toward the transport mode of interest are the most important determinants of their travel choices.

Positive attitudes toward a mobility mode increase the likelihood of a selected travel mode over other modes. For instance, pro-automobile/pro-driving attitudes are negatively associated with the use of non-motorized modes (De Vos et al., 2018) and public transportation (Ettema and Nieuwenhuis, 2017). Attitudes such as “pro-bike” or “prowalk” are positively associated with biking and walking (Cao et al., 2007; Maldonado-Hinarejos et al., 2014; De Vos et al., 2018; Park and Akar, 2019) and negatively associated with driving (Handy et al., 2005).

Western cities have investigated the complex interrelations of urban form, travel behavior, mobility attitudes for almost six decades but the state of the research in the MENA and the SA cities is limited.

The MENA region has been noted as one of the fastest growing regions (10%) in terms of population between 2006 (355 million) and 2013 (392 million) and by the end of this decade −2030—about 60% of the population in the MENA and SA regions will live in cities (World Economic Forum, 2015). Both the regions are amongst the most populous areas of the Global South and face some common challenges such as urban sprawl, high motorization, and increased urban population. Most of the MENA and SA cities follow a traditional transport planning process, where private cars occupy most space on the street, which is given by a complex set of processes, institutions and actors. The consideration for individualized travel as a norm is creating adverse impacts on societies and the environment.

The two large regions of the Global South include megacities with a wide range of maturity levels in terms of mobility ecosystems, modal choices, and urban forms.

The objective of this paper is to systematically study the existing literature on cities in the MENA and SA regions to provide a comparative review of the analyses and the findings on urban mobility attitudes in light of prevailing societal conditions and urban-spatial forms. First objective of the paper is to review interrelations of travel attitudes, mode choices and socio-spatial attributes in the MENA and SA regions. Secondly it seeks to summarize the determinants of mobility attitudes and urban travel behavior (mode choices) from the literature review and thirdly, it presents the impact of traditional public transport systems and emerging shared mobility modes in the context of mobility attitudes and travel behavior in the MENA and SA regions.

The paper has examined the published journal papers from the first two decades of the 21st century in the MENA and SA regions to understand the factors ranging from built environment to shared mobility trends (which includes sharing vehicles, bicycles, e-scooters, demand-responsive vans, ride-hailing) shaping urban mobility attitudes and mode choices. The paper contributes toward the limited body of research for MENA and SA cities. While the paper is relevant for transportation researchers, it is also beneficial for transport and urban planners; policymakers; and new mobility solution providers addressing urban mobility challenges.

The paper is organized in the following five sections. The subsequent section elaborates the systematic literature search and analysis method. This is followed by the results section illustrating interrelations of travel attitudes, mode choices and socio-spatial issues in the MENA and SA regions. The penultimate section provides a discussion of descriptive perspectives on contextual differences between MENA and SA cities on the one hand and Western cities on the other, and a presentation of knowledge gaps. The final section offers a conclusion and highlights the scope for future research.

2. Research methods

The paper applied a systematic search approach known as the Preferred Reporting Items for Systematic Reviews and Meta Analyses (PRISMA) protocol (Moher et al., 2009). The search was applied to review three online databases: the Web of Science, Google Scholar, and TRB's Transport Research International Documentation (TRID). Due to the novelty of published literature in the fields of mobility attitudes and travel behavior for the MENA and SA regions, a low number of search results were achieved in the search engine. Hence, other databases were used to broaden the scope of analysis, namely, Google Scholar and the TRB's Transport Research International Documentation (TRID) database. Keywords for the literature search included a combination of three categories: “mobility attitudes” (“attitudes” OR “attitude” OR “attitud*”); “travel behavior” OR “travel behavior” (“travel mode choices” OR “public transport” OR “shared mobility” OR “mobility culture” OR “travel patterns”); and “Built Environment” (“urban form” OR “neighborhood design” OR “land use” and related concepts). The time span filter of “2000—April, 2022” was applied and any studies or reports not subject to peer review were not included.

Figure 1 describes the steps taken to systematically conduct search and the results obtained. A search on May 10, 2022 in the Web of Science produced 282 hits, Google Scholar resulted in 4,480 hits, and TRB's TRID showed 1,482 hits. The articles found in the Web of Science and TRID were also repeated in the Google Scholar and hence the duplications were removed. Subsequently, a detailed search was conducted for the terms mentioned above in the papers, looking for sections discussing explanations and causality hypotheses.

FIGURE 1
www.frontiersin.org

Figure 1. Literature research review. Methodology adapted from PRISMA protocol (Moher et al., 2009).

Based on the above approach, the study found 43 publications for MENA cities and 43 papers for SA cities (mapped in Figure 2). An exhaustive analysis of published papers covered six salient features: Correlations studied; transport modes analyzed; sample size; data collection method; analysis method; and summary of relevant insights for this manuscript. The review is detailed in Supplementary Appendices 1, 2 of this paper.

FIGURE 2
www.frontiersin.org

Figure 2. Overview of previous published studies for cities in MENA and SA regions.

3. Results

This section summarizes the findings for each of the research questions. Figure 2 shown below illustrates the number of relevant empirical studies conducted per each country in the MENA and SA regions.

3.1. Review of interrelations of travel attitudes, mode choices and socio-spatial attributes in the MENA and SA cities

Based on the previous conducted research, the section distills the factors influencing mobility attitudes and mode choices in the MENA and SA cities, followed by the influence of emerging shared mobility solutions compared to the traditional public transport.

There are more similarities than differences between the MENA and SA regions in terms of urban mobility behaviors, travel attitudes and urban forms, which are discussed later in more detail (see Supplementary Appendices 1, 2). The main resemblance between the two regions is their large population of millennials, which is one of the highest in the world. Millennials' attitude is unique due to the digital connectivity and flexibility toward a sharing attitude rather than owning a car, which makes it a nurturing place for the new mobility solutions (Lyons and Goodwin, 2014). The centrality of attitudes to urban metabolism and the drive toward collaborative consumption is well studied in Western societies (Lyons et al., 2018; De Vos et al., 2021; De Vos, 2022).

Within the MENA region, the high-income block which consists of Gulf Cooperation Council (GCC) states that includes the UAE, Saudi Arabia, Kuwait, Oman, Bahrain, and Qatar differs in terms of urban mobility systems and maintains high quality transport infrastructure. Due to high GDP and income per capita among GCC countries, the private car has been a dominant mode of transport among residents. Additionally, the private car ownership in the GCC countries is considered a social symbol and a norm, which makes private vehicles a default mode choice for Millennials in the MENA region. However, this trend has been evolving since 2009 when the region's first metro system came into operation in Dubai. Based on the success of the Dubai metro system, other cities in the region such as Doha and Riyadh have followed the trend of deploying a public transport system. The trend seems set to continue in the coming decade as well due to the recent launch of some ambitious giga-projects in the region such as NEOM in Saudi Arabia, which is envisioned as an “accelerator of human progress” and plans to operate a zero-carbon mobility system by offset (NEOM., 2020).

In the MENA region, it is predominantly Iranian cities on which research in the field of urban mobility behavior and urban form has been published (Arabani and Amani, 2007; Soltani and Ivaki, 2011; Shahangian et al., 2012; Soltanzadeh and Masoumi, 2014); it concluded that travel behavior is strongly influenced by socio-economic factors compared to urban form. Subsequently only a few cities—Istanbul, Turkey (Özbil, 2013; Özbil et al., 2016) and Amman, Jordan (Shbeeb and Awad, 2013)—in the MENA region have provided limited additional literature in this arena.

From Saudi Arabia, in Riyadh, Alotaibi and Potoglou (2017) examined the influence of TDM measures on public transport usage and travel behavior. Within the Arabian Peninsula, Alkaabi (2014) assessed factors persuading public and private sector workers to choose the metro as their main commuting mode in Dubai, United Arab Emirates. Majority of the cities still follow a car-dominated mobility infrastructure but there are exceptions like Dubai, where a multi-modal mobility ecosystem is maturing and follows the Singapore example.

The use of private motorcycles or two-wheelers and shared rickshaw is more prominent in the SA region than the MENA region. The SA region has the most spatially dense population in the world and generally has low household income levels compared to the MENA region, which makes non-motorized transportation like walking and cycling the primary form of mobility; inhabitants are also often forced to live in peripheral settlements on the edge of their cities.

3.2. The determinants of mobility attitudes and mode choices

Travel behavior is influenced by various built environment variables. This is one of the most heavily researched subjects in travel studies (Handy, 1993; Cervero and Kockelman, 1997; Boarnet and Sarmiento, 1998; Boarnet and Crane, 2001; Ewing and Cervero, 2001, 2010; Cervero, 2002; Chatman, 2003, 2008; Ewing et al., 2003; Frank et al., 2008; Ewing and Handy, 2009; Lee et al., 2014). The concept of individuals' attitudes and their influence on travel behavior was introduced in the 1970s (Golob et al., 1977; Reichman, 1977; Tardiff, 1977; Dobson et al., 1978; Salomon and Ben-Akiva, 1983; Cooper et al., 2001; Hildebrand, 2003; Parkany et al., 2004; Thogersen, 2006). Attitude can be defined as positive or negative evaluations or beliefs held about something that in turn may affect one's behavior; attitudes are typically broken down into cognitive, affective, and behavioral components as per Nairne in 1997 (Nairne, 1997). Attitudes are considered a component of the decision-making process by social psychologists (Parkany et al., 2004) and are defined as part of the decision process by transportation researchers (Sunkanapalli et al., 2000). Additionally, Outwater et al., in 2003 established that attitudes along with intentions have significant impact in understanding travel mode choices (Outwater et al., 2003). Other researchers have also found attitude to be a more significant indicator than demographics and travel needs in choosing public transportation (Gärling et al., 1998; Fujii and Gärling, 2003; Parkany et al., 2004). Commuters' mobility attitudes are an important aspect in mode choices, and attitude refers to evaluation of a behavior, which disposes a person to behave in a certain way toward it based on attitude theory (Parkany et al., 2004). While abundant literature exists on cities in the Global North, limited empirical research has been conducted to examine and quantify the factors influencing the attitudes and travel behavior of users in the MENA and SA regions.

There are scant travel behavior studies for the MENA region which relate to attitudes and built environment. Etminani-Ghasrodashti and Ardeshiri in 2016 empirically studied the effect of individuals' mobility patterns on their non-working trips in Shiraz, Iran and found a strong influence of attitudes as compared to the built environment. In addition to the built environment, other key variables such as mobility attitudes are found to be key determinants of travel behavior (Etminani-Ghasrodashti and Ardeshiri, 2016). Other recent studies have explored mobility habits, influence on women commuters and their perceptions about public transport services in Algiers, Amman, Beirut, Casablanca, and Muscat (Delatte et al., 2018). Masoumi et al., in 2018 studied associations between urban mobility decisions, built environment, human perceptions, and infrastructure in Tehran, Cairo, and Istanbul. Similarly, some MENA researchers have focused on the impact of personal characteristics and built environment factors on an individual's travel choices (Al-Atawi and Saleh, 2014; Soltanzadeh and Masoumi, 2014; Soltani and Shams, 2017). Özbil in 2013 researched street connectivity and layout in neighborhoods in Istanbul and found that street features do impact the pedestrian demand. Similarly, Özbil et al. in 2014 assessed the walkability for students aged between 12 and 14 and concluded that street related features such as width, length, number of crossing, and traffic signals majorly impact the route choice of students. In Jordan, Shbeeb and Awad (2013) studied the impacts of the urban environment and the condition of sidewalks in providing safety for school students' walkability in Amman.

Similarly, the SA region also contains limited travel behavior (mode choices) research compared to Western literature but comparatively more than the MENA region. For example, a number of researchers have studied the urban sprawl impact on travel demand and choices in Dhaka (Nasrin et al., 2015), Chennai (Srinivasan et al., 2007a,b), Rajkot (Munshi, 2016), in all of India (Ahmad and de Oliveira, 2016), in Kathmandu (Bajracharya et al., 2020), Kabul (Kakar and Prasad, 2020), Lahore (Kamran et al., 2016; Shakeel and Jahanzaib, 2019) and Sri Lanka (Ranasinghe et al., 2015). Very few studies have evaluated the influence of people's attitudes (Javid, 2017a,b; Javid et al., 2021; Mehriar et al., 2021; Masoumi et al., 2022).

Besides the limited published research on the factors influencing urban mode choices at neighborhood level in the MENA and SA regions, a common deficit across most of the countries, when compared to Western counterparts, is the absence of in-depth modeling and simulation. Table 1 below groups the key determinants of mobility attitudes and mode choices as similar and dissimilar for the MENA and SA cities.

TABLE 1
www.frontiersin.org

Table 1. Key determinants of mobility attitudes and travel behaviors among MENA and SA cities.

3.3. Traditional public transport and emerging shared mobility modes

Revolution in mobility is undisputed—the only question is when the new disruptive technologies will be fully embedded into the existing mobility ecosystems. The traditional public transport systems remain the backbone of cities' urban mobility ecosystem. The traditional public transport sector had been innovating at its natural pace, but this pace was rapidly accelerated after the launch of the smartphone in 2007. These trends have given rise to emerging shared mobility modes (which includes sharing vehicles, bicycles, e-scooters, demand-responsive vans, ride-hailing) and studies have found that there are numerous fiscal, social, and environmental benefits of shared mobility (Shaheen et al., 2016; Xue et al., 2018). The smartphone application-based (app-based) ride-hailing services—also known as ride-hailing or e-hailing, or Transportation Network Company (TNC) services in the United States and VTC or Véhicule (or Voitures) de Transport avec Chauffeur in European countries—are intended to bridge the gap between private and public transport by offering reliable, comfortable, on-demand, end-to-end travel without the hassle of owning and driving a private vehicle. A substantial body of literature has acknowledged that younger, better-educated, and more affluent individuals are more likely to be ride-hailing users (McGrath, 2015; Rayle et al., 2016; Clewlow and Mishra, 2017). Industry has proven that disruptive innovations have the power to redefine the transportation industry and change users' behaviors (EBRD., 2019). Over the last decade, a variety of new mobility services and technologies have been developed, such as autonomous vehicles, drones, and mobility-as-a-service, and these innovations are critical to the development of a sustainable urban mobility ecosystem (Gössling, 2017).

Among MENA cities, a couple of major empirical studies were completed recently for Tehran and Cairo (Mehriar et al., 2020; Masoumi, 2021, 2022). Etminani-Ghasrodashti and Hamidi (2019) found in Tehran that individuals who prefer driving and semi-public transit also have a higher number of Snapp trips than other demographics. These findings support the effects of attitudes on the demand for app-based taxis in Iran. Trip security, cost-effectiveness, anti-shared mobility, and technology-oriented attitudes have a direct effect on the frequency of ride-hailing trips. Individuals with strong and positive preferences toward technology are more likely to use an app-based taxi (Alemi et al., 2018). Our findings align with the literature that suggests trip security is an essential element of public and semi-public transit mode choices. According to our findings, on-demand ride services could complement or compete with other modes of transport, especially in areas with limited access to public transit. However, the presence of ride-hailing services does not necessarily result in fewer car trips if the service operates as a private (single-person occupancy) vehicle and not as a shared mobility option.

Second, Mostofi et al. (2020), determined for Tehran and Cairo that the gender ratio of the regular ride-hailing users indicates that women are more frequent users than men in these two cities (60.6% in Tehran and 64% in Cairo). It showed that in Cairo and Tehran, the citizens who adopt ride-hailing as their regular motorized modes for their trips outside their neighborhood are less likely to use a vehicle instead of walking for near destinations than regular private car users. Therefore, these results indicate that car dependence of frequent ride-hailing users is significantly less than regular car users in both cities. However, in Cairo, they are more likely to replace walking by using a vehicle for trips inside the neighborhood than regular users of public bus and urban rail transits. Therefore, there is a concern that in Cairo, by shifting more regular public transport users to ride-hailing, the share of the walking mode decreases in the modal split of Cairo. In addition, the findings showed that frequent users of ride-hailing have remarkably higher household incomes and a higher car ownership rate in 2017 in both cities. However, the adoption of regular ride-hailing might be increased among lower-income households and non-household car owners by a decrease in the service fare through the competition of ride-hailing companies, and improvement of internet services in the coming years.

In the SA region, very limited literature was found that has empirically studied the emerging shared mobility modes and their impacts on travel behavior. Devaraj et al. (2020), found in Chennai, India that there is significant interaction between ride-hailing adoption and the consideration propensity of IPT modes. Second, ride hailing adoption and factors such as residential and work location, vehicle ownership, and availability of other modes affect ride hailing adoption, whereas activity characteristics (purpose, duration, and timing) and perception of conventional modes influence the intensity of use: usage intensity decreases with an increase in the number of cars in the households, whereas it increases with the number of two-wheelers owned in non-car households. Third, a significant role is played by work-related spatial and temporal characteristics in the adoption and usage intensity of ride hailing services of workers in the developing country context (Javid et al., 2021).

As it can be noted there is a lack of comprehensive research to understand motives behind the adoption of these shared mobility services and their impacts on the use of traditional public transport modes. This deficit poses a number of challenges for decision-makers and policymakers in terms of governance, planning, demand assessment, policy development, funding, security and enforcement.

4. Discussion

4.1. Data and methods

The findings of this paper complement the debate about the determinants of mobility attitudes and the impact of urban forms on travel choices in the MENA and SA cities. This section provides tabular comparison of previous studies undertaken for various cities in the MENA and SA regions. Supplementary Appendices 1, 2 provide a comparative summary of analysis based on the following attributes: correlations studies, travel modes reviewed, sample size, data collection method, data analysis approach; a summary of key findings is provided for each study.

A general observation noted in the reviewed studies for the MENA and SA cities is that they contain smaller sample sizes compared to their Western counterparts, which can be associated with lower literacy rates, less public participation and lower responsiveness in surveys. Most of the respondents in the surveys are male, and female participation in surveys is limited. The demographics of the survey participants are most of the time university students in the respective university where the research is being conducted, which can be linked to convenience in the data collection process.

Another reflection concerns the methodology followed in the MENA and SA regions' transportation research; it tends to be more descriptive and limited conclusions are found based on empirical modeling results apart from a few exceptions (Soltanzadeh and Masoumi, 2014; Etminani-Ghasrodashti and Ardeshiri, 2016; Soltani and Shams, 2017; Etminani-Ghasrodashti and Hamidi, 2019; Masoumi, 2020, 2021, 2022; Mehriar et al., 2020; Javid et al., 2021; Masoumi et al., 2021). The spatial data availability and analysis remains a challenge for most of the cities in the MENA and SA regions basically due to non-availability of updated information in a single repository and also hesitancy to share the information by the governing authorities.

4.2. Descriptive perspectives on contextual differences of MENA and South Asia with Western societies

Cities globally are experiencing rapid changes driven by technological advances, economic reforms, and behavioral shifts. The cities in the MENA and SA regions are not only facing an urban population challenge, which is predicted to double by 2050 (UN DESA, 2014), but also socio-cultural, demographic, and socio-economic dynamics there continue to challenge their urban mobility. These two important regions of the Global South differ from Western societies in travel behavior determinants in certain ways such as ethnic and faith values for women travelers, private transport mode dominance once available, and underdeveloped mobility governance systems.

The cities and provinces within the MENA and South Asia regions can range from highly developed (for instance Dubai) to very underdeveloped cities, even in the same country. Hence, it can be said that the findings for a city or a country cannot be generalized for the whole region. It is important to highlight that the cities of the GCC countries have a slightly different context compared to the other MENA cities, as the cities in the GCC countries have witnessed very rapid economic and population growth, which has been accompanied by major urban development and transportation system expansion. The dispersed urban developments and large highway-based transport systems have resulted in high car dependency. To be sure, a few cities like Dubai, Riyadh, and Doha have made major progress toward providing public transport systems by adding state-of-the-art driverless metro systems and enhanced public bus transport networks, but it remains a challenge to derive an attitudinal change from private cars to public transport.

A number of cities in the MENA and SA regions have started to aspire to being the happiest and safest places in order to attract intellectual talent and investment, but they will have to adopt a clearer roadmap for an effective governance framework to integrate the emerging digitalized shared mobility modes within the existing transportation systems. Agile governance that allows innovations is critical to the development of sustainable urban mobility. Hence, there is a need to better understand how these disruptive new mobility services and technologies influence mobility attitudes at a neighborhood level.

Most cities in the MENA region exhibit car-dominated travel behavior as the region faces hot climatic conditions, which makes the use of non-motorized mobility modes (walking and cycling) less convenient, and the transport infrastructure provided is mainly for cars. Megacities in the MENA region like Tehran, Cairo, and Istanbul possess a large informal transport sector contrary to Western societies. However, the GCC cities within the MENA region have more defined regulatory frameworks to govern the transportation services in their cities. Hence, there are exceptional examples like Dubai, which is a regional benchmark for having a state-of-the-art multi-modal urban mobility system and is aspiring to be a world leader in seamless and sustainable mobility.

The SA region has high proliferation and use of the private motorcycle (two-wheeler), which is not very common in the MENA region and Western cities. High ownership and usage of private motorcycles in the SA cities is increasing congestion levels as well as environmental and health issues. Additionally, unregulated paratransit services and the informal transport sector make up the majority of the mobility share in the SA cities. Commuters' socio-economic standing and residence area characteristics affect their mobility attitudes.

Women in both MENA and SA regions face safety and security challenges and are reluctant to use public transport. The rapid emergence of ride-hailing mobility service providers has provided a safe alternative for women travelers in both regions.

The review indicates high car ownership and bus transport dominance in most cities of the MENA region, which is verified by a recent categorization of cities based urban typologies (Oke et al., 2020). Most of the cities in the MENA region are categorized as “Auto Sprawl,” “Bus Transit Dense,” and “Bus Transit Sprawl” typologies except for Dubai, which is labeled as “Hybrid Moderate” due to its multi-modal mobility system, whereas most megacities in the SA region are grouped as “Congested Boomer” and “Congested Emerging.”

4.3. Knowledge gaps

Based on the literature from the MENA and SA regions, the knowledge gaps are summarized below:

• MENA contains limited research in terms of understanding the mode choices, attitudes toward urban mobility, and emerging digitalization influences, while the SA region has a greater quantity of research than the MENA region.

• There is limited diversity and participation of women in urban mobility research, decision-making, and consideration for their mobility requirements. This gap in understanding women commuters' attitudes limits the ability for inclusive policymaking for the regions.

• The influence of digitalized shared mobility services on travel mode choices in the MENA and SA cities is scarcely studied.

4.4. Study limitations

The research is based on the previous studies sourced from the three popular online platforms, but there may be a few studies that were missed as part of this literature review. However, the overall analysis of the determinants for travel choices in the MENA and SA regions might not alter significantly as a result. As it is obvious in this study that few megacities in the MENA and SA regions have limited empirical-based literature on mobility patterns, the mode choices of residents in suburban and rural parts of the MENA and SA regions is not fully represented in this paper. Mobility attitudes and their spatial influence are not well captured in this study.

5. Conclusions

Transport and mobility literature reviews are common in European and North American cities. However, limited literature and reviews thereof exist for the Global South. This review paper articulates the key variables of travel choices in the MENA and SA cities. Additionally, the manuscript attempts to synthesize the existing literature and add a new perspective to it by discussing the influence of emerging shared mobility modes due to rapid digitalization and the vital role of cities' mobility governance frameworks. The findings can assist planners, policymakers, decision-makers, and mobility service providers to guide their approach toward providing an equitable mobility ecosystem and place-based communities by considering the importance of mobility attitudes and urban form.

Findings based on the literature suggest that mobility attitudes and travel choices in the MENA and SA regions are influenced by some factors in common with Western cities (Scheiner and Holz-Rau, 2007; Buehler, 2011; Cheng et al., 2020), namely socio-demographics (varying by gender, age, household income, driving license availability, education level, private vehicle ownership, and household structure), spatial attributes (urban forms) and lifestyles (Etminani-Ghasrodashti and Ardeshiri, 2016; Soltani and Shams, 2017; Masoumi et al., 2018). Cultural and climatic conditions as well as socio-economic standing have key impacts on the mobility choices in the MENA and SA regions, which is different to Western literature. Class and income disparities are deeply embedded in the socio-spatial arrangements and mobility challenges of the MENA and SA cities.

Key findings for the MENA region reveal that the users' attitude is an important determinant of mode choices and the urban form is less significant. Public transport usage is mainly related to the inability to use a private car (Delatte et al., 2018) and the perceived service quality of public transport (Hamed and Olaywah, 2000).

The study finds that the urban mobility governance frameworks in the MENA and SA regions require reforms to integrate the emerging digitalized shared mobility modes within the existing transportation systems. A timely policy shift in urban mobility governance is critical for a sustainable mobility ecosystem through an effective governance framework.

The suggested avenues for future research are to explore mobility attitudes in the MENA and SA context for assessing the sensitivity of the determinants of various mode choices in light of emerging digitalized shared mobility services. Future research could examine the influence of digitalized shared mobility trends, and reforms in governance need to be explored so as to deploy the best urban mobility ecosystem in cities, one that is for people, is equitable, integrated, sustainable, seamless and promotes place-based communities. Future studies specifically in the MENA and SA regions can investigate the importance of stability in the cities' governance system as a pre-requisite for the delivery of a sustainable urban mobility ecosystem.

Data availability statement

The original contributions presented in the study are included in the article/Supplementary material, further inquiries can be directed to the corresponding author.

Author contributions

Conceptualization, methodology, analysis, and writing—original draft preparation: A-GC. Writing—review and editing: A-GC and HM. All authors have read and agreed to the published version of the manuscript.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/frsc.2022.1085784/full#supplementary-material

References

Ahmad, S., and de Oliveira, J. A. P. (2016). Determinants of urban mobility in India: lessons for promoting sustainable and inclusive urban transportation in developing countries. Transp. Policy 50, 106–114. doi: 10.1016/j.tranpol.2016.04.014

CrossRef Full Text | Google Scholar

Al-Atawi, A., and Saleh, W. (2014). Travel behaviour in Saudi Arabia and the role of social factors. Transport 29, 269–277. doi: 10.3846/16484142.2014.913199

CrossRef Full Text | Google Scholar

Alemi, F., Circella, G., Handy, S., and Mokhtarian, P. (2018). What influences travelers to use Uber? Exploring the factors affecting the adoption of on-demand ride services in California. Travel Behav. Soc. 13, 88–104. doi: 10.1016/j.tbs.2018.06.002

CrossRef Full Text | Google Scholar

Alkaabi, K. (2014). Analyzing the travel behaviour and travel preferences of employees and students commuting via the Dubai Metro. Arab World Geogr. 17, 42–65.

Google Scholar

Alotaibi, O., and Potoglou, D. (2017). Perspectives of travel strategies in light of the new metro and bus networks in Riyadh City, Saudi Arabia. Transp. Plann. Technol. 40, 4–27. doi: 10.1080/03081060.2016.1238572

CrossRef Full Text | Google Scholar

Arabani, M., and Amani, B. (2007). Evaluating the Parameters Affecting Urban Trip-generation. Shiraz: Iranian Journal of Science & Technology.

Google Scholar

Bagley, M. N., and Mokhtarian, P. L. (2002). The impact of residential neighborhood type on travel behavior: a structural equations modeling approach. Ann. Reg. Sci. 36, 279–297. doi: 10.1007/s001680200083

CrossRef Full Text | Google Scholar

Bajracharya, A. R., Shrestha, S., and Skotte, H. (2020). Linking travel behavior and urban form with travel energy consumption for Kathmandu Valley, Nepal. J. Urban Plann. Dev. 146, 05020008. doi: 10.1061/(ASCE)UP.1943-5444.0000590

CrossRef Full Text | Google Scholar

Boarnet, M. G., and Crane, R. (2001). Travel by Design: The Influence of Urban Form on Travel. Oxford: Oxford University Press on Demand. doi: 10.1093/oso/9780195123951.001.0001

CrossRef Full Text | Google Scholar

Boarnet, M. G., and Sarmiento, S. (1998). Can land-use policy really affect travel behaviour? A study of the link between non-work travel and land-use characteristics. Urban Stud. 35, 1155–1169. doi: 10.1080/0042098984538

CrossRef Full Text | Google Scholar

Buehler, R. (2011). Determinants of transport mode choice: a comparison of Germany and the USA. J. transp. Geogr. 19, 644–657. doi: 10.1016/j.jtrangeo.2010.07.005

CrossRef Full Text | Google Scholar

Cao, J., Mokhtarian, P. L., and Handy, S. (2007). Do changes in neighborhood characteristics lead to changes in travel behavior? A structural equations modeling approach. Transportation 34, 535–556. doi: 10.1007/s11116-007-9132-x

CrossRef Full Text | Google Scholar

Cervero, R. (2002). Built environments and mode choice: toward a normative framework. Transp. Res. D: Transp. Environ. 7, 265–284. doi: 10.1016/S1361-9209(01)00024-4

CrossRef Full Text | Google Scholar

Cervero, R., and Kockelman, K. (1997). Travel demand and the 3Ds: density, diversity, and design. Transp. Res. D: Transp. Environ. 2, 199–219. doi: 10.1016/S1361-9209(97)00009-6

CrossRef Full Text | Google Scholar

Chatman, D. G. (2003). How density and mixed uses at the workplace affect personal commercial travel and commute mode choice. Transp. Res. Rec. 1831, 193–201. doi: 10.3141/1831-22

CrossRef Full Text | Google Scholar

Chatman, D. G. (2008). Deconstructing development density: quality, quantity and price effects on household non-work travel. Transp. Res. A: Policy Pract. 42, 1008–1030. doi: 10.1016/j.tra.2008.02.003

CrossRef Full Text | Google Scholar

Cheng, L., De Vos, J., Zhao, P., Yang, M., and Witlox, F. (2020). Examining non-linear built environment effects on elderly's walking: A random forest approach. Transp. Res. Part D: Transp. Environ. 88, 102552. doi: 10.1016/j.trd.2020.102552

CrossRef Full Text | Google Scholar

Clewlow, R. R., and Mishra, G. S. (2017). Disruptive Transportation: The Adoption, Utilization, and Impacts of Ride-hailing in the United States. California: University of California.

Google Scholar

Cooper, J., Ryley, T., and Smyth, A. (2001). Contemporary lifestyles and the implications for sustainable development policy: lessons from the UK's most car dependent city, Belfast. Cities 18, 103–113. doi: 10.1016/S0264-2751(00)00062-7

CrossRef Full Text | Google Scholar

De Vos, J. (2022). The shifting role of attitudes in travel behaviour research. Transp. Rev. 42, 573–579. doi: 10.1080/01441647.2022.2078537

CrossRef Full Text | Google Scholar

De Vos, J., Cheng, L., and Witlox, F. (2021). Do changes in the residential location lead to changes in travel attitudes? A structural equation modeling approach. Transportation 48, 2011–2034. doi: 10.1007/s11116-020-10119-7

CrossRef Full Text | Google Scholar

De Vos, J., Ettema, D., and Witlox, F. (2018). Changing travel behaviour and attitudes following a residential relocation. J. Transp. Geogr. 73, 131–147. doi: 10.1016/j.jtrangeo.2018.10.013

CrossRef Full Text | Google Scholar

Delatte, A., Baouni, T., Belwal, R., Daou, L., Gourram, D., Imam, R., et al. (2018). Understanding the needs of mena public transport customers: culture of service and gender responsive recommendations. TeMA J. Land Use Mobil. Environ. 1, 7–30.

Google Scholar

Devaraj, A., Ramakrishnan, G. A., Nair, G. S., Srinivasan, K. K., Bhat, C. R., Pinjari, A. R., et al. (2020). Joint model of application-based ride hailing adoption, intensity of use, and intermediate public transport consideration among workers in Chennai City. Transp. Res. Record. 2674, 152–164. doi: 10.1177/0361198120912237

CrossRef Full Text | Google Scholar

Dobson, R., Dunbar, F., Smith, C. J., Reibstein, D., and Lovelock, C. (1978). Structural models for the analysis of traveler attitude-behavior relationships. Transportation 7, 351–363. doi: 10.1007/BF00168036

CrossRef Full Text | Google Scholar

EBRD. (2019). Disruptive Technology and Innovation in Transport. London: European Bank for Reconstruction and Development.

Google Scholar

Etminani-Ghasrodashti, R., and Ardeshiri, M. (2016). The impacts of built environment on home-based work and non-work trips: an empirical study from Iran. Transp. Res. A 85, 85. 196–207. doi: 10.1016/j.tra.2016.01.013

CrossRef Full Text | Google Scholar

Etminani-Ghasrodashti, R., and Hamidi, S. (2019). Individuals' demand for ride-hailing services: investigating the combined effects of attitudinal factors, land use, and travel attributes on demand for app-based taxis in Tehran, Iran. Sustainability 11, 5755. doi: 10.3390/su11205755

CrossRef Full Text | Google Scholar

Ettema, D., and Nieuwenhuis, R. (2017). Residential self-selection and travel behaviour: what are the effects of attitudes, reasons for location choice and the built environment? J. Transp. Geogr. 59, 146–155. doi: 10.1016/j.jtrangeo.2017.01.009

CrossRef Full Text | Google Scholar

Ewing, R., and Cervero, R. (2001). Travel and the built environment: a synthesis. Transp. Res. Rec. 1, 87–114. doi: 10.3141/1780-10

CrossRef Full Text | Google Scholar

Ewing, R., and Cervero, R. (2010). Travel and the built environment. J. Am. Plann. Assoc. 76, 265–294. doi: 10.1080/01944361003766766

CrossRef Full Text | Google Scholar

Ewing, R., and Handy, S. (2009). Measuring the unmeasurable: urban design qualities related to walkability. J. Urban Design 14, 65–84. doi: 10.1080/13574800802451155

CrossRef Full Text | Google Scholar

Ewing, R., Pendall, R., and Chen, D. (2003). Measuring sprawl and its transportation impacts. Transp. Res. Rec. 1831, 175–183. doi: 10.3141/1831-20

CrossRef Full Text | Google Scholar

Frank, L., Bradley, M., Kavage, S., and Chapman, J. (2008). Urban form, travel time, and cost relationships with tour complexity and mode choice. Transportation 35, 37–54. doi: 10.1007/s11116-007-9136-6

CrossRef Full Text | Google Scholar

Fujii, S., and Gärling, T. (2003). Development of script-based travel mode choice after forced change. Transp. Res. F: Traffic Psychol. Behav. 6, 117–124. doi: 10.1016/S1369-8478(03)00019-6

CrossRef Full Text | Google Scholar

Gärling, T., Gillholm, R., and Gärling, A. (1998). Reintroducing attitude theory in travel behavior research: the validity of an interactive interview procedure to predict car use. Transportation 25, 129–146. doi: 10.1023/A:1005004311776

CrossRef Full Text | Google Scholar

Golledge, R. G., Brown, L. A., and Williamson, F. (1972). Behavioural approaches in geography: an overview. Aust. Geogr. 12, 59–79. doi: 10.1080/00049187208702613

CrossRef Full Text | Google Scholar

Golob, T. F. (2003). Structural equation modeling for travel behavior research. Transp. Res. B: Methodol. 37, 1–25. doi: 10.1016/S0191-2615(01)00046-7

CrossRef Full Text | Google Scholar

Golob, T. F., Horowitz, A. D., and Wachs, M. (1977). Attitude-behavior Relationships in Travel Demand Modelling. London: Croom Helm.

Google Scholar

Gössling, S. (2017). Tourism, information technologies and sustainability: an exploratory review. J. Sustain. Tour. 25, 1024–1041. doi: 10.1080/09669582.2015.1122017

CrossRef Full Text | Google Scholar

Hamed, M. M., and Olaywah, H. H. (2000). Travel-related decisions by bus, servis taxi, and private car commuters in the city of Amman, Jordan. Cities 17, 63–71. doi: 10.1016/S0264-2751(99)00052-9

CrossRef Full Text | Google Scholar

Handy, S. (1993). Regional versus Local Accessibility: Implications for Nonwork Travel. Berkeley, CA: The University of California Transportation Center.

Google Scholar

Handy, S., Cao, X., and Mokhtarian, P. (2005). Correlation or causality between the built environment and travel behavior? Evidence from Northern California. Transp. Res. D: Transp. Environ. 10, 427–444. doi: 10.1016/j.trd.2005.05.002

CrossRef Full Text | Google Scholar

Hickman, R., and Banister, D. (2005). Towards a 60% Reduction in UK Transport Carbon Dioxide Emissions: A Scenario Building and Backcasting Approach. London: ECEEE, 717–730.

Google Scholar

Hildebrand, E. D. (2003). Dimensions in elderly travel behaviour: a simplified activity-based model using lifestyle clusters. Transportation 30, 285–306. doi: 10.1023/A:1023949330747

CrossRef Full Text | Google Scholar

Javid, M. A. (2017a). Influence of travelers' attitudes, status and auto consciousness on car use reduction measures. Jordan J. Civil Eng. 11.

Google Scholar

Javid, M. A. (2017b). Intentions of car and motorcycle oriented groups towards public transport in Lahore. Tech. J. Univ. Eng. Technol. 22, 9–16.

Google Scholar

Javid, M. A., Ali, N., Shah, S. A. H., and Abdullah, M. (2021). Travelers' attitudes toward mobile application–based public transport services in Lahore. SAGE Open 11, 1–15. doi: 10.1177/2158244020988709

CrossRef Full Text | Google Scholar

Kakar, K. A., and Prasad, C. (2020). Impact of urban sprawl on travel demand for public transport, private transport and walking. Transp. Res. Procedia 48, 1881–1892. doi: 10.1016/j.trpro.2020.08.221

CrossRef Full Text | Google Scholar

Kamran, M., Batool, Z., and Rehman, Z. (2016). Comparison of urban form parameters of Lahore with its neighboring cities. Pak. J. Sci. 68, 203–232.

Google Scholar

Kitamura, R., Mokhtarian, P. L., and Laidet, L. (1997). A micro-analysis of land use and travel in five neighborhoods in the San Francisco Bay Area. Transportation 24, 125–158. doi: 10.1023/A:1017959825565

CrossRef Full Text | Google Scholar

Lee, J.-S., Nam, J., and Lee, S.-S. (2014). Built environment impacts on individual mode choice: an empirical study of the Houston-Galveston metropolitan area. Int. J. Sustain. Transp. 8, 447–470. doi: 10.1080/15568318.2012.716142

CrossRef Full Text | Google Scholar

Lyons, G., and Goodwin, P. (2014). Grow, Peak or Plateau - The Outlook for Car Travel. London: University College London.

Google Scholar

Lyons, G., Mokhtarian, P., Dijst, M., and Böcker, L. (2018). The dynamics of urban metabolism in the face of digitalization and changing lifestyles: understanding and influencing our cities. Resour. Conserv. Recycl. 132, 246–257. doi: 10.1016/j.resconrec.2017.07.032

CrossRef Full Text | Google Scholar

Maldonado-Hinarejos, R., Sivakumar, A., and Polak, J. W. (2014). Exploring the role of individual attitudes and perceptions in predicting the demand for cycling: a hybrid choice modelling approach. Transportation 41, 1287–1304. doi: 10.1007/s11116-014-9551-4

CrossRef Full Text | Google Scholar

Masoumi, H. (2020). Urban commute travel distances in Tehran, Istanbul, and Cairo: weighted least square models. Urban Sci. 4, 39–63. doi: 10.3390/urbansci4030039

CrossRef Full Text | Google Scholar

Masoumi, H. (2021). Residential location choice in Istanbul, Tehran, and Cairo: the importance of commuting to work. Sustainability 13, 5757. doi: 10.3390/su13105757

CrossRef Full Text | Google Scholar

Masoumi, H. (2022). Home-based urban commute and non-commute trip generation in less-studied contexts: evidence from Cairo, Istanbul, and Tehran. Case Stud. Transp. Policy 10, 130–144. doi: 10.1016/j.cstp.2021.11.011

CrossRef Full Text | Google Scholar

Masoumi, H., Aslam, S. A. B., Rana, I. R., Ahmad, M., and | Naeem, N. (2022). Relationship of residential location choice with commute travels and socioeconomics in the small towns of South Asia: the case of Hafizabad, Pakistan. Sustainability 14, 3163. doi: 10.3390/su14063163

CrossRef Full Text | Google Scholar

Masoumi, H., Gouda, A. A., Layritz, L., and Stendera, P. (2018). Urban Travel Behavior in Large Cities of MENA Region: Survey Results of Cairo, Istanbul, and Tehran. Berlin: Technische Universität Berlin.

Google Scholar

Masoumi, H., Ibrahim, M. R., and Aslam, A. B. (2021). The relation between residential self-selection and urban mobility in middle eastern cities: the case of Alexandria, Egypt. Urban Forum 32, 261–287. doi: 10.1007/s12132-020-09414-4

CrossRef Full Text | Google Scholar

McGrath, F. (2015). The Demographics of Uber's U.S. Users. Available online at: https://www.globalwebindex.net/blog/the-demographics-of-Ubers-us-users (accessed November 19, 2020).

Google Scholar

Mehriar, M., Masoumi, H., Aslam, A. B., and Gillani, S. M. (2021). The neighborhood effect on keeping non-commuting journeys within compact and sprawled districts. Land 10, 9620. doi: 10.3390/land10111245

CrossRef Full Text | Google Scholar

Mehriar, M., Masoumi, H., and Mohino, I. (2020). Urban sprawl, socioeconomic features, and travel patterns in middle east countries: a case study in Iran. Sustainability 12, 9620. doi: 10.3390/su12229620

CrossRef Full Text | Google Scholar

Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., and Group, P. (2009). Reprint—preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Phys. Ther. 89, 873–880. doi: 10.1093/ptj/89.9.873

CrossRef Full Text | Google Scholar

Mostofi, H., Masoumi, H., and Dienel, H.-L. (2020). The relationship between regular use of ridesourcing and frequency of public transport use in the MENA region (Tehran and Cairo). Sustainability 12, 8134. doi: 10.3390/su12198134

CrossRef Full Text | Google Scholar

Munshi, T. (2016). Built environment and mode choice relationship for commute travel in the city of Rajkot, India. Transp. Res. D: Transp. Environ. 44, 239–253. doi: 10.1016/j.trd.2015.12.005

CrossRef Full Text | Google Scholar

Nairne, J. S. (1997). Psychology: The Adaptive Mind. Monterey, CA: Thomson Brooks/Cole Publishing Co.

Google Scholar

Nasrin, S., Bunker, J., and Zheng, Z. (2015). Worker attitude toward bus rapid transit: considering Dhaka, Bangladesh. Transp. Res. Rec. 2533, 8–16. doi: 10.3141/2533-02

CrossRef Full Text | Google Scholar

NEOM. (2020). NEOM - About. Available online at: https://www.neom.com/en-us/about/ (accessed November 20, 2020).

Google Scholar

Oke, J. B., Aboutaleb, Y. M., Akkinepall, A., Azevedo, C. L., Han, Y., Zegras, P. C., et al. (2020). A novel global urban typology framework for sustainable mobility futures. Environ. Res. Lett. 15, 095006. doi: 10.1088/1748-9326/aba65d

CrossRef Full Text | Google Scholar

Outwater, M. L., Castleberry, S., Shiftan, Y., Ben-Akiva, M., Shuang Zhou, Y., Kuppam, A., et al. (2003). Attitudinal market segmentation approach to mode choice and ridership forecasting: structural equation modeling. Transp. Res. Rec. 1854, 32–42. doi: 10.3141/1854-04

CrossRef Full Text | Google Scholar

Özbil, A. (2013). Modeling walking behavior in cities based on street network and land-use characteristics: the case of Istanbul. METU J. Fac. Archit. 30, 17–33. doi: 10.4305/METU.JFA.2013.2.2

CrossRef Full Text | Google Scholar

Özbil, A., Argin, G., and Yeşiltepe, D. (2016). Pedestrian Route Choice by Elementary School Students: The Role of Street Network Configuration and Pedestrian Quality Attributes in Walking to School. Istanbul: International Journal of Architectural Research.

Google Scholar

Park, Y., and Akar, G. (2019). Understanding the effects of individual attitudes, perceptions, and residential neighborhood types on university commuters' bicycling decisions. J. Transp. Land Use 12, 419–441. doi: 10.5198/jtlu.2019.1259

CrossRef Full Text | Google Scholar

Parkany, E., Gallagher, R., and Viveiros, P. (2004). Are attitudes important in travel choice? Transp. Res. Rec. 1894, 127–139. doi: 10.3141/1894-14

CrossRef Full Text | Google Scholar

Ranasinghe, G., Amarawickrama, S., Ranasinghe, G., and Ratnayake, R. (2015). A model for assessing the level of walkability in urban neighborhoods in Sri Lanka. Int. J. Built Environ. Sustain. 2, 292–300. doi: 10.11113/ijbes.v2.n4.97

CrossRef Full Text | Google Scholar

Rayle, L., Dai, D., Chan, N. R., and Shaheen, S. (2016). Just a better taxi? A survey-based comparison of taxis, transit, and ridesourcing services in San Francisco. Transp. Policy 45, 168–178. doi: 10.1016/j.tranpol.2015.10.004

CrossRef Full Text | Google Scholar

Reichman, S. (1977). Instrumental and life-style aspects of urban travel behavior. Transp. Res. Rec. 649, 38–42.

Google Scholar

Salomon, I. (1980). Life Style as a Factor in explaining Travel Behavior [Doctoral dissertation]. Cambridge, MA: Massachusetts Institute of Technology.

Google Scholar

Salomon, I., and Ben-Akiva, M. (1983). The use of the life-style concept in travel demand models. Environ. Plann. A 15, 623–638. doi: 10.1068/a150623

CrossRef Full Text | Google Scholar

Scheiner, J., and Holz-Rau, C. (2007). Travel mode choice: affected by objective or subjective determinants? Transportation 34, 487–511. doi: 10.1007/s11116-007-9112-1

CrossRef Full Text | Google Scholar

Shahangian, R., Kermanshah, M., and Mokhtarian, P. L. (2012). Gender differences in response to policies targeting commute to automobile-restricted central business district: stated preference study of mode choice in Tehran, Iran. Transp. Res. Rec. 2320, 80–89. doi: 10.3141/2320-10

CrossRef Full Text | Google Scholar

Shaheen, S., Cohen, A., and Zohdy, I. (2016). Shared Mobility: Current Practices and Guiding Principle. Philadelphia, PA: United States, Federal Highway Administration.

Google Scholar

Shakeel, N., and Jahanzaib, M. (2019). Influence of land use, socio-demographic and travel attributes on travel behaviour in city of Lahore. Arch. Urban Plann. 15, 67–74. doi: 10.2478/aup-2019-0009

CrossRef Full Text | Google Scholar

Shbeeb, L., and Awad, W. (2013). Walkability of school surroundings and its impact on pedestrian behaviour. TeMA J. Transp. Land Use Mobil. Environ. 6, 171–188.

PubMed Abstract | Google Scholar

Soltani, A., and Ivaki, Y. E. (2011). The influence of urban physical form on trip generation, evidence from metropolitan Shiraz, Iran. Indian J. Sci. Technol. 4. doi: 10.17485/ijst/2011/v4i9.24

CrossRef Full Text | Google Scholar

Soltani, A., and Shams, A. (2017). Analyzing the influence of neighborhood development pattern on modal choice. J. Adv. Transport. 2017. doi: 10.1155/2017/4060348

CrossRef Full Text | Google Scholar

Soltanzadeh, H., and Masoumi, H. E. (2014). The determinants of transportation mode choice in the middle eastern cities: the Kerman Case, Iran. TeMA J. Land Use Mobil. Environ. 7, 199–222.

Google Scholar

Srinivasan, K. K., Lakshmi Bhargav, P. V., Ramadurai, G., Muthuram, V., and Srinivasan, S. (2007a). Determinants of changes in mobility and travel patterns in developing countries: case study of Chennai, India. Transp. Res. Rec. 2038, 42–52. doi: 10.3141/2038-06

CrossRef Full Text | Google Scholar

Srinivasan, K. K., Pradhan, G. N., and Naidu, G. M. (2007b). Commute mode choice in a developing country: role of subjective factors and variations in responsiveness across captive, semicaptive, and choice segments. Transp. Res. Rec. 2038, 53–61. doi: 10.3141/2038-07

CrossRef Full Text | Google Scholar

Sunkanapalli, S., Pendyala, R. M., and Kuppam, A. R. (2000). Dynamic analysis of traveler attitudes and perceptions using panel data. Transp. Res. Rec. 1718, 52–60. doi: 10.3141/1718-07

CrossRef Full Text | Google Scholar

Tardiff, T. J. (1977). Causal inferences involving transportation attitudes and behavior. Transp. Res. 11, 397–404. doi: 10.1016/0041-1647(77)90004-1

CrossRef Full Text | Google Scholar

Thogersen, J. (2006). Understanding repetitive travel mode choices in a stable context: a panel study approach. Transp. Res. A: Policy Pract. 40, 621–638. doi: 10.1016/j.tra.2005.11.004

CrossRef Full Text | Google Scholar

Timmermans, H. (2003). “The saga of integrated land sse - transport modeling: how many more dreams before we wake up?” in Proceedings of the International Association of Traveler Behavior Conference (Sevilla).

Google Scholar

UN DESA (2014). World Urbanization Prospects, the 2011 Revision. New York, NY: Population Division, Department of Economic and Social Affairs, United Nations Secretariat.

Google Scholar

World Economic Forum (2015). Visualising the World Economy and Population. Available online at: https://www.weforum.org/agenda/2015/02/visualising-the-world-economy-and-population-in-one-chart/ (accessed November 18, 2020).

Google Scholar

Xue, M., Yu, B., Du, Y., Wang, B., Tang, B., Wei, Y.-M., et al. (2018). Possible emission reductions from ride-sourcing travel in a global megacity: the case of Beijing. J. Environ. Dev. 27, 156–185. doi: 10.1177/1070496518774102

CrossRef Full Text | Google Scholar

Keywords: mobility attitudes, urban form, public transport, shared mobility, mode choices, urban governance

Citation: Chaudhry A-G, Masoumi H and Dienel H-L (2023) A systematic literature review of mobility attitudes and mode choices: MENA and South Asian cities. Front. Sustain. Cities 4:1085784. doi: 10.3389/frsc.2022.1085784

Received: 31 October 2022; Accepted: 28 December 2022;
Published: 25 January 2023.

Edited by:

Silvia Siri, University of Genoa, Italy

Reviewed by:

Juheon Lee, Midwestern State University, United States
Edmund Zolnik, George Mason University Arlington Campus, United States

Copyright © 2023 Chaudhry, Masoumi and Dienel. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Houshmand Masoumi, yes masoumi@ztg.tu-berlin.de

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.