Choice of transport in urban and periurban zones in metropolitan area

https://doi.org/10.1016/j.jtrangeo.2022.103331Get rights and content

Highlights

  • User income is a significant variable in motorized transport choice in urban and periurban zones.

  • In both zones, income and education are socioeconomic user characteristics that determine the choice of motorized transport.

  • For active mobility in the peripheral zone, age is a determining factor in the transport choice.

  • For active mobility in the conurbed zone, the gender is a factor; men choose a bicycle more often in the conurbation.

Abstract

The choice of transport is a user decision defined by transport attributes and user characteristics. In a sprawl area in an emerging economy, the determining factors can be analyzed by considering a metropolitan area, the user residence area, the conurbation, or a periurban area. To determine the main user characteristics affecting transport choice in urban and periurban zones, the transport choice was analyzed using discrete choice models considering user characteristics and transport attributes. A case study was conducted in the Queretaro metropolitan area (QMA). Four transport modes were analyzed: car and bus (motorized), and bicycle and walking (active). The peripheral and conurbed zones were compared, considering the four transport modes. The results show that user income is a determinant in motorized transport choice; age and gender are determinants in active transport choice.

Introduction

A metropolitan area is delimited by the local political structure. Each peripheral area has diverse socioeconomic characteristics with dissimilar gravitation characteristics (Obregón and Bueno, 2015). Metropolitan areas (MA) have great significance in a region or country because they have the greatest concentration of population, dynamics, and economy. Metropolitan areas have been created by the expansion of medium-sized cities (one hundred thousand to one million inhabitants) and irregular settlements in periurban areas where there are commercial and service activities (Bazant, 2010, 489). Expansion normally occurs in a radial direction around the city center, or in a linear direction following road infrastructure; in these areas, localities with urban and rural characteristics can coexist. According to Sudhira et al. (2004), the factors that influence urban sprawl are population, population growth rate, distance, and density. Squires (2002) defined the growth model as low-density, which was later confirmed by Sultana and Weber (2007, 193) and Heinrichs et al. (2009, 30).

The peri-urbanization process is characterized by settlements beyond urban areas (Zasada et al., 2011; Haller, 2014). According to Ravetz et al. (2013), the peri-urban region is often a zone of chaotic urbanization that results in sprawl. Friedmann (2011) stated that the peri-urban region is a “zone of encounter, conflict, and transformation surrounding large cities.” Liu and Bardaka (2021) stated that the decentralization of employment, combined with the availability of affordable housing in suburban areas, has encouraged low-income households previously concentrated in central cities to migrate to the suburbs. In emerging countries, peripheralization is twofold, as a function of infrastructure availability, public facilities, and basic services, and includes residential zones and illegal/improvised settlements (UN, 2008), partly resulting from economies with modest economic growth in which domestic migrants settle in shantytowns (Da Gama-Torres, 2008). In emerging countries such as Mexico, foreign manufacturing facility settlements have developed at the outskirts of urban centers. These include industrial parks, which create jobs but whose workers are directly connected to the central nuclei in the same municipality or a neighboring municipality (Webster and Muller, 2002). Guerra et al. (2018) reported that urban sprawl in Mexico is dense and spatially concentrated, and that even in single-use developments, residents quickly convert housing units into shops and local businesses. In the sense of the relationship between urban form, transportation supply, and individuals' mode choice, they reported that there is less driving in urban areas with better transit and fewer roadways, as well as in dense urban areas with concentrated job centers. They conclude that contemporary policies have contributed to increased motorization. Additionally, despite the rapid growth in vehicle fleets, Mexico's urban areas remain highly multimodal, with 49% of residents commuting to work by transit, 28% by car, and 23% commuting by foot or bicycle. Another factor that distinguishes cities in Mexico from cities in developed countries is the low accessibility by the urban poor because of uncoordinated land-use planning and a lack of transportation infrastructure and regular transit services.

On the one hand, dynamic exposure induces urbanized land demand, primarily residential, commercial, and industrial developments, mostly constructed in the peripheral area, induced by the manufacturing sector because it is the most productive per worker, demands more land area, and is often located in the urban periphery. Recently, to mitigate these impacts, the Secretariat for Urban, Territorial, and Agricultural Development (SEDATU) and the National Housing Commission (CONAVI) have advanced an agenda of urban containment by linking housing subsidies to urban growth boundaries set at the federal level (Montejano et al., 2019).

On the other hand, Harbering and Schlüter (2020) show that beyond factors directly related to public transport infrastructure, spatial development patterns are important determinants of mode choice. With this in mind, some studies have focused on understanding how geography moderates the impact of built environment attributes on mode choice behavior (Eldeeb et al., 2021). In this sense, a long travel distance is highly associated with the selection of motorized travel modes (Sun et al., 2017). In contrast, the probability of active travel modes (i.e., walking and biking) diminishes when the travel distance increases (Muñoz et al., 2016; Winters et al., 2017). The travel behavior of individuals plays a very significant role in travel demand management and transport planning, and according to Subbarao et al. (2020), travel behavior patterns and their interactions have many applications in the analysis of transportation policies. Scheiner and Holz-Rau (2007) reported that urban form and travel developed as a research field in spatial and transport sciences, based on the understanding that travel may be explained by urban form to a considerable degree. García (2008) suggested that in Latin America, increasing mobility in peri-urban areas should consider the number of trips and the travel times and distances involved, recognizing that long-distance trips are less frequent than short-distance trips.

Regarding the travel mode, the choice is exact (i.e., observed), but the trip attributes are uncertain (Lunke et al., 2021). The user must choose a transport mode; this decision is influenced by variables such as income, education degree, age, and gender, and by the attributes of the transport mode. Income and education are still unequally distributed in developing countries; for this reason, Harbering and Schlüter (2020) propose including these socioeconomic factors and spatial development patterns in the analysis of mode choice. How the spatial difference in travel behavior is unclear is determined, as is whether they result from individual decisions regarding residential locations (Scheiner and Holz-Rau, 2007). Bento et al. (2005) stated that commuter information, such as age and gender, vary at the individual level, whereas measures of urban spatial structure, such as population density and job-population balance, vary at the metropolitan level. Why do some people drive, others use transit, and others use active modes of transportation? This is a research question that has been addressed many times in the US and Europe (Boarnet, 2011; Stevens, 2016; Giuliano and Dargay, 2006; Buehler, 2011; Pucher and Buehler, 2006), but much less in developing countries or Latin America (Toro-González and Cantillo-García, 2020; Rudke et al., 2021; Tonini et al., 2021; Zegras, 2010) or middle-income countries such as Mexico (Guerra, 2014, Guerra, 2017; Guerra et al., 2018; Harbering and Schlüter, 2020), a country with a rapid urban development characteristic caused by cheaper peripheral land focused on workers in the manufacturing sector (Montejano et al., 2019). Rahul and Verma (2017) considered the inadequacy of the transportation solutions determined for a developed country in developing countries, making it imperative for researchers to develop separate models of travel behavior for the latter.

In this context, this study aims to analyze and compare the attributes and socioeconomic characteristics that influence transport choice among residents in urban and peri-urban zones, considering that user income is the most significant variable in user transport choice. The research is based on a case study, the Queretaro Metropolitan Zone (QMZ), the 8th largest metropolitan region in Mexico, and distinguished in recent years as one of the Mexican states with the greatest dynamics of economic growth and a high share of drivers (greater than 40%). The traditional logit model was applied to socioeconomic and transport attribute variables. Global models of travel behavior hinge on the choices of individual decision-makers who are seen as actors assessing the benefits and costs of their travel choices (Nkeki and Asikhia, 2019). This study utilized a dataset of 3,849 household travel surveys to obtain a representative sample of the population of the region. The analysis includes four main transportation modes: walking, biking, public transit (bus), and car. A geographical analytical approach considers the conurbated and peripheral areas of the QMZ, allowing us to obtain detailed spatial variations in the probability of selecting different modes of transportation. This study uses data reported in Obregón and Betanzo (2015), Obregón et al. (2015), Obregón et al. (2016), Obregón et al. (2018), and Obregón and Ángeles (2018).

Section snippets

Background

Mobility is a fundamental element in modern societal development. In a rapidly growing metropolitan area in Mexico, understanding the significant user characteristics and transport attributes affecting transport choices, and how they influence decisions in diverse territorial environments, contributes to understanding the relationship between urban form and travel behavior to improve quality of life. In this section, the factors that influence mode choice are discussed. Regarding mode choice,

Study area features, data and model

Guerra et al. (2018) states that, as in other low- and middle-income countries, nearly all of Mexico's recent and projected population and economic growth is occurring outside of its largest cities. As this phenomena occurs in the Queretaro Metropolitan Zone (QMZ), the process of the gradual spread of urbanization has given way to what is called “urban sprawl” (Bruckner and Fansler, 1983). In Mexico, the urban area of a large city is known as the metropolitan zone (MZ), which includes a central

Descriptive statistics

The principles of descriptive statistics were used to study the socioeconomic characteristics of the zones, trip motives, number, and number of users of each mode of transport, including their respective travel times. The Fig. 3 shows the modal split for trips in the conurbated and peripheral zones, revealing primarily less car use and more trips walking in the peripheral zone. In this sense, the mean travel time was less for walking in the peripheral (16.91 min) with respect to the conurbated

Results and discussion

The most robust logit models are considered for the conurbed and peripheral areas (Fig. 2), subdivided for motorized and active modes to compare the mode choice characteristics in each area.

Conclusion

This study clarifies how user characteristics in different zones change the user transport choice. Income is a determinant of motorized transport, while age and gender are determinants of active mobility. In emerging countries, higher income is associated with higher education grades and access to vehicles. In the QMZ, high car commuting rates with respect to other Latin American cities (greater than 40%) have led to high travel times in the transit system, a lack of a massive transport system,

Author contribution statement

Saúl Antonio, Obregón Biosca: Study conception and design, analysis and interpretation of results, writing - original draft.

Declaration of Competing Interest

None.

Acknowledgments

The author would like to thank the anonymous reviewers who have made valuable suggestions and comments on an earlier version of this paper. The National Council of Science and Technology of México for sponsoring this research under the contracts FOMIXQRO-2010-C01-146269 and CB-2015-257525-S

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