Exploring mobility characteristics in rural Sub-Saharan Africa: a case study of the Yamoussoukro Region, Côte d’Ivoire

Rosner, Philipp et al. Article — Published Version Exploring mobility characteristics in rural Sub-Saharan Africa: a case study of the Yamoussoukro Region, Côte d’Ivoire Transportation Suggested Citation: Rosner, Philipp et al. (2025) : Exploring mobility characteristics in rural SubSaharan Africa: a case study of the Yamoussoukro Region, Côte d’Ivoire, Transportation, ISSN 1572-9435, Springer US, New York, Vol. 52, Iss. 6, pp. 2511-2570, https://doi.org/10.1007/s11116-025-10671-0 This Version is available at: https://hdl.handle.net/10419/333378 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. http://creativecommons.org/licenses/by/4.0/ Accepted: 10 August 2025 / Published online: 24 September 2025 © The Author(s) 2025 Extended author information available on the last page of the article Exploring mobility characteristics in rural Sub-Saharan Africa: a case study of the Yamoussoukro Region, Côte d’Ivoire DavidZiegler1· PhilippRosner1· ClemensPizzinini1· MathisKremer1· SaraGrambs1· VictorRommel1· MarkusLienkamp1 Transportation (2025) 52:2511–2570 https://doi.org/10.1007/s11116-025-10671-0 Abstract Access to transportation is a key enabler of economic and sustainable development in rural emerging economies. Implementing effective improvements requires a deep understanding of the current mobility landscape. Despite its significance, recent research on transportation and mobility characteristics in rural Sub-Saharan Africa remains limited. This study addresses this gap by analyzing mobility patterns and motivations in central Côte d’Ivoire, based on a series of quantitative and qualitative field surveys and a twoelectric-vehicle pilot study, conducted between 2021 and 2023. We comprehensively assess rural transportation by situating our empirical findings within the context of existing transportation models and prior studies while evaluating their implications for the Sustainable Development Goals, and offering an outlook on electric vehicle usage patterns in rural areas. The findings provide important guidance for policymakers and industry stakeholders, helping to develop sustainable interventions and business models that improve local access to goods, services, and economic opportunities. Keywords Transportation · Rural mobility patterns · Sub-Saharan Africa · GPS logging · Surveys · Interviews · Electric Mobility · Sustainable Development Goals Introduction Access to transportation is a key enabler of economic and sustainable development in rural emerging economies, enabling rural populations to access goods, services, and opportunities, which is vital for mitigating poverty and fostering economic growth (Porter 2014), as proposed by the United Nations (2015) (UN) within their Sustainable Development Goal (SDG) agenda. Africa lags behind Asia in the availability of intermediate means of transport (IMT), lowcost options frequently utilized for short-distance travel and transporting goods (Starkey 2001). This disparity is evident in transportation access, the efficiency of transport services, etal.[full author details at the end of the article] 1 3 Transportation (2025) 52:2511–2570 the supply of agricultural transport, and transportation costs, indicating a significant potential for improvements in the region (Hine 2014). Governments, supported by development banks and agencies, heavily invested in rural road infrastructure in the late 20th century (Bryceson et al. 2008). However, there has been minimal investment in rural transportation services (RTSs) in recent decades, making it challenging to utilize the still-existing infrastructure. According to Starkey et al. (2002), the lack of investment, which has been primarily left to the private sector, hampers poverty reduction efforts, particularly in isolated and marginalized communities. These socioeconomic disparities between underdeveloped and more developed regions underscore the urgent need for transportation improvements for Sub-Saharan Africa (SSA) tailored to the local population’s specific needs and realities. However, despite its crucial role, many rural areas of SSA continue to face significant transportation challenges, limiting their potential for development. Poor transportation access limits essential services and economic opportunities, perpetuating the cycle of poverty and limited mobility. Therefore, improving access to essential services and markets is crucial for eradicating poverty and enhancing livelihoods (Hine et al. 2015; Acheampong et al. 2022). Rural transportation is complex and encompasses several factors, including the quality of roads, transport fares, and the availability of regional adapted transportation services. Infrequent and costly transport services limit transportation, further entrenching poverty. Women, in particular, bear a substantial transport burden, impacting their health and education outcomes (Hine 2014). Yet, in many parts of SSA, limited infrastructure, traditional agricultural practices, and climate change vulnerability contribute to a mobility landscape that remains poorly understood. Despite its critical importance, recent research on transportation and mobility in rural SSA remains scarce (Porter 2014; Pizzinini et al. 2023; Collett and Hirmer 2021). With this study, we focus on rural mobility between 2021 and 2023, drawing on extensive fieldwork conducted around the village of Zatta in Côte d’Ivoire. By integrating quantitative methods–such as on-field GPS tracking–with qualitative approaches, including workshops and surveys, we identify the intentions, scales, motivations, and constraints that underlie human movement and transportation demand in these communities. Furthermore, recognizing that insufficient transportation access hampers economic opportunities and the attainment of the Sustainable Development Goals, we evaluate the potential of on-site electric vehicles to enhance transportation and electricity access within the region. Our findings offer valuable insights for policymakers and industry stakeholders, providing a robust foundation for sustainable interventions, business models, and future research tailored to rural SSA’s specific challenges and opportunities. Literature review This section briefly overviews existing transportation assessments in SSA including the potential influence on progress towards the SDGs as well as possible electrification solutions for the problems identified. 1 3 2512 Transportation (2025) 52:2511–2570 Transportation Although human mobility intentions and behavior differ vastly between urban and rural Africa, informal paratransit services (minibus, shared, and motorcycle taxis) are vastly more common than private vehicles in both settings (Ehebrecht et al. 2018; Falchetta et al. 2021). In urban contexts, paratransit fills the gap left by inadequate formal public transport, providing flexible and affordable transportation (Godard 2013), but is often poorly integrated into urban planning, contributes to congestion and is plagued by safety concerns (Behrens et al. 2016; Salon and Gulyani 2019). In contrast, rural mobility remains constrained by limited road infrastructure, high transport costs, low vehicle availability, and therefore fewer vehicle services (Bryceson et al. 2008; Porter 2014). In consequence, multiple studies have emphasized heavy dependence on non-motorized transport (i. e. walking and cycling) for daily activities such as accessing markets, education, and healthcare (Porter 2002; Bryceson et al. 2003; Munyaka et al. 2022) and Intermediate Means of Transport (IMT) such as twoand three-wheelers, as they provide critical last-mile connectivity where road conditions limit conventional vehicle access (Starkey 2016; Dennis and Pullen 2017). Furthermore, the mobility transformation potential of digital communication technologies is more pronounced in rural areas (Porter 2016). In addition to personal transport, rural mobility patterns are shaped by a combination of agricultural activity, trade, and seasonal variations (Bryceson et al. 2003). Previous research has also explored the social dimensions of mobility, particularly gender disparities in transport access and the impacts of mobility constraints on economic opportunities (Porter 2011). While Starkey (2007) provides methodologies for quickly assessing local rural transport services, and a direct influence of transportation accessibilities on sustainable development (i. e. the UN SDGs) has been shown (Cook et al. 2017; Yiu et al. 2019; Ipingbemi et al. 2021), scarcity and missing generality of quantitative transportation studies with a focus on rural SSA leave a gap in current literature (Zuidgeest 2019). This is especially true considering the significant regional differences in typical modes and behaviors (Diaz Olvera et al. 2013) In the context of field data acquisition for assessing mobility within a defined target region, Table 1 summarizes the principal approaches most commonly reported in the literature. Methodology Publications GPS logging Booysen et al. (2013); Engelbrecht et al. (2015); Kemajou et al. (2019); Joseph et al. (2020); Hull et al. (2023); Pretorius et al. (2024) CDR logging Meredith et al. (2021) Interviews Dennis (1998); Del Mistro and Arenze (20002); Behrens et al. (2006) Travel diaries Golob and Meurs (1986); Schlich and Axhausen (2003) Group workshops incl. design thinking methods Dennis (1998); Starkey (2007); Soltes et al. (2017); Sigauke (2021); Wolcott et al. (2021) Cognitive maps Vajjhala and Walker (2010) Table 1 Existing methodologies for assessing local mobility patterns. 1 3 2513 Transportation (2025) 52:2511–2570 Electrification Electrification of transport service vehicles offers a range of benefits to operators, such as cheaper local energy supply, robust drivetrains, and vehicle concepts tailored to the local context and use cases (Collett et al. 2021). However, significant barriers stand in the way of electric vehicle (EV) adoption (Gicha et al. 2024), mainly among which are the higher purchase price in comparison to internal combustion engine vehicles (ICEVs) and reliable charging infrastructure (Moeletsi 2021). Nevertheless, a research group at Stellenbosch specifically analyzes the energy requirements, scheduling, and ensuing electrification potentials for minibusses in (inter)urban paratransit (Ndibatya and Booysen 2021; Rix et al. 2022; Wust et al. 2025), comprising the majority of publications in the field. Electric motorcycle taxis, primarily localized in East Africa and employing battery swapping in service models, are another strand of recent publications (Wahab et al. 2019; Sheehan et al. 2021; Vanatta et al. 2022; Martin et al. 2023). These two are the most prevalent forms of transportation in urban areas and, therefore, the first to be electrified. Once again, however, fewer publications cover periurban or rural EVs adoption, where the mentioned challenges are exacerbated further. Nevertheless, with motorcycles (Allee et al. 2022; Pawlak et al. 2023) and taxis (Gammon and Sallah 2021), the same vehicle types prevail, complemented by agricultural machinery (Götz et al. 2024) and fishing vessels (Lukuyu et al. 2020), all of which are typically researched in conjunction with electrification systems. For both domains in general, however, real-world movement data is required to quantify electrification’s potentials but is still lacking in literature (Collett and Hirmer 2021). Research gap The previous sections show that mobility and transportation in African regions, particularly in urban areas, have been studied with a rather limited focus over the past three decades. There is a noticeable gap in recent studies addressing the current mobility state, especially for rural regions in SSA. Therefore, a more comprehensive approach that not only deepens the understanding of mobility patterns but also evaluates the sustainable impact of transportation on the daily lives of people in rural SSA is needed. Our study aims to reduce this gap by providing a holistic assessment of mobility, integrating insights and methods from various methodologies, and aligning our findings with sustainable development to estimate the potential to enhance the quality of life in these communities. Research design This publication encompasses six mobility surveys in the region of Zatta, a rural village in the subprefecture of Kossou, Côte d’Ivoire. According to the hubs-and-spokes model of Starkey et al. (2002), primarily focused on emerging regions and sharing similarities with the industrial nation-related Central Place Theory of Christaller (1933), Zatta serves as the Market Town Hub for the region. Having a catchment area (further: market hub catchment area) up to a distance of 10 km, smaller villages rely on Zatta’s marketplace for trade and their inhabitants commute there frequently. An additional detailed regional map, providing 1 3 2514 Transportation (2025) 52:2511–2570 a geographical overview, can be found in Fig. 1. For comparison of the regional demographics to our surveys’ demographics, Zatta’s demographic profile is presented in the study by Essé et al. (2008), which is based on a survey of 168 respondents conducted in 2002. Additionally, national demographic data (Institut National de la Statistique, République de Côte d’ Ivoire 2014) provides insights into the gender distribution in the survey area, indicating to be nearly equal. To investigate the mobility needs, patterns, and behaviors, we conducted six studies within the market hub catchment area across eight villages of varying population sizes, including Zatta, as summarized in Table 2. Our research was part of a development cooperation project that aimed to implement electric mobility services in the Zatta region within three years. The surveys were conducted during the Design Thinking (DT) process's emphasize, define, and ideate phases (Munyai 2016). DT empowered the local community to discover new mobility solutions, as further detailed by Pizzinini et al. (2024). A timeline of the surveys conducted for this publication is outlined in Fig. 12. To ensure a comprehensive understanding of mobility mechanisms together with the communities, we employed a dual-perspective approach: Fig. 1 Zatta and its surrounding villages. The blue circle shows Zatta’s market hub catchment area. Grey circles show the catchment areas of other market towns. Green villages correspond to the surveyed villages listed in Table 2 1 3 2515 Transportation (2025) 52:2511–2570 1. Movement-Centered (predominantly quantitative results): We collected data on people’s vehicle movements to analyze movement patterns, metrics, and modal usage ( Sect. Movement-centered surveys). 2. Human-Centered (predominantly qualitative results): We conducted workshops, surveys, and interviews to explore individual motivations, travel needs, and perceived mobility barriers (Sect. Human-centered surveys). We conducted an in-depth analysis of Zatta as a Market Town Hub while examining the surrounding villages to understand their interdependencies, differences, and commonalities within the broader catchment area (we further call this area market-spoke catchment area). Unlike existing studies, our research integrates both perspectives across a 2.5-year study period, considering the region as a hubs-and-spokes system. This approach allows us to understand village-level mobility and how these rural communities interact with their market hub. Figure 2 illustrates the study area and the road network quality within the hubsand-spokes model. This study provides a holistic analysis of the rural mobility by synthesizing data from individual, community, and transportation system perspectives. The results focus on mobility needs, behaviors, and transportation dynamics, contributing to the broader understanding of the mobility ecosystem. Some visual impressions of the different surveys held for this publication can be found in Fig. 3. Movement-centered surveys To understand mobility in the investigated region, we first focused on the central market hub, Zatta. As the largest settlement in the area, Zatta plays a crucial role in regional mobility, serving as the primary center for services, trade, and transportation. Due to its high volume of travel activity and vehicle presence compared to smaller villages, the movement-centered surveys were concentrated on this hub. The findings from Zatta serve as a firm reference Table 2 List of the villages where our mobility surveys took place and whether they were movementor human-centered. Surveys Village name Inhabitants† GPS logging Roadside interviews Zatta workshop Individual travel motifs Community travel motifs Personal interviews Zatta* 8391 ✓ ✓ ✓ – ✓ ✓ Gogokro 2091 – – – – ✓ – Zougounou 1694 – – – – ✓ ✓ Ténikro 867 – – – ✓ – – Koffikro 273 – – – ✓ ✓ ✓ Djé N’gorankro 232 – – – – – ✓ Akossé 127 – – – – – ✓ Antoinekro 101 – – – – ✓ – Movement centered ✓ ✓ – ✓ – – Human centered – ✓ ✓ – ✓ ✓ * Market Hub, †Population derived from WorldPop Tatem (2017); The geographical placement of the villages and orientations to Zatta are shown in Fig. 1. 1 3 2516 Transportation (2025) 52:2511–2570 for understanding mobility in the surrounding villages. Since travel patterns in smaller villages are oriented mainly toward the market hub–primarily for trade and essential services–the insights gained from Zatta provide a valuable foundation for modeling regional mobility. The following sections detail the methods applied at the market hub, including GPS logging to track motorized travel between Zatta and smaller villages, roadside surveys to capture inbound and outbound trips, and workshops to identify key locations, visit frequencies, and travel distances of residents. GPS logging Survey area Zatta Participants (considered) 29 (16) Survey period 2021–2022 Focus Motorized travel Investigated travel characteristics Frequency Distance Mean of transport Start/stop Intention Freight ✓ ✓ ✓ ✓ – – We mounted Global Positioning System (GPS) loggers (Wittmann et al. 2017; Balke and Adenaw 2023) to track movements of 27 local ICEVs in Zatta. The loggers were activated by the vibrations when vehicles moved, tracked at a sample rate of 1Hz and powered directly by the vehicles’ 12V batteries. Fig. 3a shows an exemplary logger installation. The tracked vehicles were primarily used in on-demand paratransit and/or agricultural goods transport and stem from one of the four classes listed in Table 3 . The vehicle drivers’ primary occupations are shown in Figure 13. We did not record the types of goods and/or number of passengers transported as part of the logging survey. The selection of vehicles Fig. 2 Schematic overview of the villages participating in the surveys and their hub-and-spoke dependencies. 1 3 2517 Transportation (2025) 52:2511–2570 Class Stated occupations* Number Total distance (km) Motorcycle Farmer, Pisteur†, Plumber, Cooperative President, Cooperative Representative 12 15730 Taxi Driver 1 10002 aCar Driver 2 3901 Tricycle Owner /O perator 1 742 Table 3 Overview of GPS logged vehicle classes. Further details are shown in Table 14. * One occupation can account for multiple participants and vice versa; † Middlemen between the farmers and produce exporters. Fig. 3 Impressions on the different surveys held in the target region. 1 3 2518 Transportation (2025) 52:2511–2570 Table 9 Quantification of the results from the community cardboard survey taken place in Zatta and surrounding smaller villages. Distance in km* Importance ranked from highest (10) Frequency in days per 30 days to have at least 1 trip† School Electricity Water Agriculture Market Mobile Reception Social Healthcare Construction Material Machines School Electricity Water Agriculture Market Mobile Reception Social Healthcare Construction Material Machines School Electricity Water Agriculture Market Mobile Reception Social Healthcare‡ Construction Material† Machines Zatta 0 0 0 10 0 0 − 0 0 0 9 5 6 8 8 4 − 10 7 3 20 30 30 24 30 30 − 4 1 0 Gogokro 0 0 0 3 0 0 15 10 15 15 10 710 9 8 9 7 10 9 8 20 30 30 24 430 424 4 0 Zougounou 0 0 0 5 7 0 15 715 15 9 8 10 9 9 8 8 9 7 7 20 30 30 24 430 424 30 0 Koffikro 0 6 0 4 6 6 15 6 6 15 10 10 10 9 9 10 710 9 8 20 30 30 24 430 2 4 1 0 Antoinekro 3 3 0 2 5 0 15 5 5 15 9 8 10 9 9 8 8 9 7 7 20 30 30 24 430 424 1 0 Ø § 0.6 1.8 04.8 3.6 1.2 15 5.6 8.2 12 9.4 7.6 9.2 8.8 8.6 7.8 7.5 9.6 7.8 6.6 20 30 30 24 9.2 30 3.5 16 7.4 0 * A distance of zero means that category is available inside the village; † the answer "every day" is counted as every usual day for the occupation would take place and is therefore interpreted based on known frequencies of travel determined in the Zatta workshop, Sect. Zatta workshop; ‡ the frequency accounts for the whole village community in these cases; § average of the values above. 1 3 2525 Transportation (2025) 52:2511–2570 to rate their importance as lower. This suggests that people perceive these resources as more vital when they are not readily available in their local areas. ●Machinery is preferred in the villages surrounding Zatta, but it is minimally available and, therefore, not commonly used. This limited availability is likely due to the significant distance from these villages–averaging 15 km–and the logistical challenges of transporting the machinery. As a result, people are unfamiliar with using this equipment, leading to a lower demand for it. ●Construction material importance is influenced by ongoing house-building activities within villages. Therefore, some villages consider them very important and needed, others less important. Still, the distance to access the materials is relatively high on average, with about 8.2 km. The evaluation and comparison show that healthcare, agriculture, and construction materials are far apart, making it difficult to travel on foot daily. Machine usage and social events exceed a usual foot distance significantly, rendering them to be facilitated much less than the other categories. The local market hub, Zatta, already incorporates many categories, allowing them to be used much more often but being prioritized lower than in the surrounding villages lacking these resources. Individual travel motifs Based on the previous section, we have already analyzed a variety of villages in the marketspoken catchment area regarding their collective motifs for travel. Further, we want to detail our travel motif analysis by evaluating individual responses from Zatta (Sect. Zatta workshop), Koffikro (Sect. Individual travel motifs), a comparable small village with only about 250 inhabitants, and Ténikro, a village with roughly the same distance to Zatta but around 3 times more inhabitants than Koffikro. In the first step, we analyze the cognitive maps from the Zatta Workshop (Sect. Zatta workshop), shown in Figs. 16, 17 and 18. A qualitative synthesis across the maps of all three workshop groups reveals similarities in travel destinations, aligning with people’s intentions to meet equal needs. Predominantly identified motifs from the workshop encompassed education (schools, college), food-related places (market, bakery), social spaces (church, mosque), healthcare facilities (hospital), and work (fields). Further quantitatively condensing the cognitive maps to Table 10 leads to the following conclusions: ●People walk up to 1 kilometer within the market hub to access the bakery, hospital, market, and other amenities. ●Individuals often opt for motorcycles if possessed for substantial social events, such as attending church. ●Interpreting the frequency numbers for hospital visits for the whole community, people tend to visit them less than once a week per person but needed once a day by at least one person in the village, a statistic that underscored their importance. ●The agricultural fields, primarily located in the northwest, northeast, and south of Zatta, average 4.4 kilometers from the community. For trips to these fields, motorcycles and 1 3 2526 Transportation (2025) 52:2511–2570 Table 10 Frequencies of destination maps drawn during the Zatta workshop (Sect. Zatta workshop). Max. distance in km Mode of transport* Frequency in days per week Destination 1 3 5 ≥ 7 Ø in km W B M 1 2 3 4 5 6 7 Ø in days Inside Zatta College 1 − − − 1.0 2 − 1 − − − − 2 1 − 5.3 School 3 − − − 1.0 1 − − − − − − 6 − − 5.0 Market 2 − − − 1.0 16 1 − 4 − 1 1 2 1 1 3.4 Church/ Mosque 3 − − − 1.0 6 − 4 5 2 2 − 1 − 2 2.8 Bakery 1 − − − 1.0 − − 1 − 2 2 − − − − 2.5 Hospital 1 − − − 1.0 2 1 2 2 − − − − − − 0.8† Field 1 1 4 1 4.4 9 8 12 − 1 2 3 3 6 − 4.7 * W: walk, B: bicycle, M: motorbike; †one additional answer with once−a−month frequency included. 1 3 2527 Transportation (2025) 52:2511–2570 bicycles are the preferred modes of transportation, particularly among those who can afford or own them. As a counterpart to the workshop held with Zatta locals, we made a travel diary survey involving the participation of 35 individuals from two local villages, Koffikro and Ténikro (localization: Fig. 1), partly relying on Zattas’ market. Similar to the Zatta workshop, we identified with the travel diary important locations, distances, means of transport, and travel frequencies of village locals. Similar to the preceding workshop evaluation in Table 10, the results are condensed quantitatively in Table 11. The analysis of the two villages highlights that the market hub Zatta and the next town Yamoussoukro serve as essential remote hubs for the residents. Villagers visit these hubs frequently, averaging at least once a week, which supports the hubs− and− spokes model described by Starkey et al. (2002). Although Zatta is geographically closer to the villagers, Yamoussoukro is more attractive to them, likely because it offers a broader variety of goods and services. It unveiled several intriguing observations about the local customs and lifestyle patterns. Religious sites, such as churches and mosques, are a central part of life in Zatta and surrounding towns, with people attending services at least once a week. Fieldwork is a predominant occupation, drawing individuals into the fields about five times a week on average, mainly for subsistence farming. This vital work ethic is also evident in other subsistence activities, which occupy their time around six days a week. The analysis also highlighted that the distance to these fields varies, typically 2.5 to 5 kilometers, depending on the proximity of each village. In Zatta, motorized transport is standard for reaching these fields, unlike in smaller villages where walking remains the primary mode of transportation. Moreover, the emergence of cell phones and other electrical devices has created new motivations for travel among the population. People visit places within walking distance that provide electricity and cell phone reception, illustrating a mix of traditional and contemporary reasons for traveling within the community. Movement—centered surveys In this section, we discuss the results of the movement—centered surveys directly observed via traffic counting, roadside interviews, or the GPS logging of locals’ vehicles. Roadside interviews To directly gather information about traffic flows in and out of Zatta, we conducted roadside interviews and counted traffic as described in Sect. Roadside interviews. The content of the roadside interviews and the counts are shown in Tables 16 and 17. Their results are discussed next. The evaluation of the roadside interviews unveils that people from Zatta travel outside on average, with 82 % to fields, 8 % to construction sites, and 2.5 % visiting the forest, garden, or farms. The primary goods collected predominantly from fields were firewood (19 %), banana and yam (16.7 %), manioc (12 %), cacao (9.5 %), tomatoes (4.75 %), and other 1 3 2528 Transportation (2025) 52:2511–2570 Table 11 Frequencies of destination maps drawn from the individual motifs survey (Sect. Individual travel motifs). Koffikro Destination Max. distance in km Mode of transport* Frequency in days per week 1 3 5 ≥ 7Ø in km W B M T C 1234567Ø in days Church/ Mosque† 4 − − 1 1.64 4 − 1 − − 5 − − − − − − 1.0 Zatta − − − 2 7.0 1 − 1 − − 2 − − − − − − 1.0 Yamoussoukro − − − 5 22.6 − − − 1 4 4 1 − − − − − 1.2 Field 2 6 − 1 2.7 8 − − 1 − − − − − 9 − − 5.0 Ténikro Max. distance in km Mode of Transport* Frequency in days per week Destination 1 3 5 ≥ 7Ø in km W B M T C 1234567Ø in days Church/ Mosque† 20 − 1 − 0.8 20 − 1 − − 18 3 − − − − − 2.8 Work† 1 − − − 1.0 − 1 − − − − − − − − 1 − 6.0 Cellphone c harging − 1 − − 4.0 1 − − − − 1 − − − − − − 1.0 Neighbor villages 2 − 1 2 10.5 1 1 1 2 − 4 − − − − 1 − 1.8 Zatta − − − 2 10.5 1 1 − − − 2 − − − − − − 1.0 Yamoussoukro − − − 11 21.3 3 2 − − 6 10 1 − − − − − 1.1 Field − 8 8 10 4.7 21 2 3 − − − 3 2 3 9 9 − 4.7 * W: walk, B: bicycle, M: motorbike, T: tricycle, C: car & taxi; † inside the village. 1 3 2529 Transportation (2025) 52:2511–2570 goods like leaves, dried grass, aubergine, mushroom, fish or chicken from animal enclosures facilitated nearby to the fields (2.38 %). The analysis, shown in Fig. 4a, revealed that people mainly walked for distances up to 5 km outside the village, used bicycles for distances up to 10 km, and used motorcycles for longer distances up to 30 km. Additionally, tricycles were frequently used to transport goods to and from the fields, particularly for short distances within the village. We also examined how different modes of transportation are used based on gender, as depicted in Fig. 4b. Our analysis revealed that women mainly walked or rode as passengers in a tricycle as their primary mode of transport. In contrast, it was uncommon for women to ride motorcycles or bicycles themselves, likely due to limited ownership of motorized vehicles and cultural usage norms favoring men. Vehicle GPS logging This section details the quantitative GPS logging results of 16 local vehicles around Zatta, described in Sect. GPS logging. The loggings cover a total of 1362h and 30439km. Table 12 summarizes the tracked fleet’s total (left) and daily (right) distance and duration distribution. On average, the vehicles covered 1902km (85h) in total and recorded respectively 27km (1.2h) per day. The medians are lower than the average due to skewed distributions towards lower distances. Outliers stemming from the taxis taking significantly more and longer trips than other classes. Figure 5 shows the number of daily recorded trips for each vehicle type. The electric aCars commenced operations in October 2022. We consider a trip a vehicle’s movement between two stationary intervals of more than 10min each. During the survey, trip counts fluctuated due to logging issues described in Table 4. Maintenance and data synchronization were performed at the start of each research visit, leading to high recorded trip counts and flatting out due to error reasons, mentioned in Sect. GPS logging. The geographical reach for each vehicle type is mapped in Fig. 6. Motorcycles seem to be used in both the immediate market hub and its catchment area. While shorter distances are more common, they are also employed for a few extended journeys outside the market hub catchment area. In contrast, tricycles are (within the very limited data for this vehicle type) exclusively used within the market hub catchment area, often for short—distance trips to and from fields (for agriculture) or forests (for firewood). This indicates their predominant application in agricultural transport. Electric cars (aCars) were operated using a transportation service model similar to tricycles but free of charge during the project phase. As a result, they also serve similar destinations within the market hub area, with the notable addition of occasional trips to Yamoussoukro, likely due to their comfort and suitability to drive longer distances on wellmaintained roads too. Lastly, taxis exhibit high and regular usage connecting villages on mostly these regional spoke roads with few long-distance trips as well. To understand the distances driven in rural uninhabited areas (UHAs) and residential areas (REAs), we conduct an analysis focusing on trip intersections with residential areas defined in Open Street Maps (OSM) and the WorldPop dataset. The findings in Fig. 7 illustrate the distance distribution of the different vehicle types in UHAs and REAs. The deeper evaluation shows: ●aCars’ are driven inside REAs in median just around 0.6km but within the UHAs 3.5km. 1 3 2530 Transportation (2025) 52:2511–2570 ●Taxis cover considerably higher UHA distances, in median around 10km, while their REA distances varies between 1km to 7km. Taxis are driven much more in REAs than the other vehicle types. Occasionally, a one-time ride of almost 100km was recorded. ●Tricycles’ are mostly utilized in UHA, for distances of 1.5km in the median, while only 0.6km in REA. ●Motorcycles cover UHA distances up to 5km, with occasional longer one-time rides up to 100km. 2021−09 2021−11 2022−01 2022−03 2022−05 2022−07 2022−09 2022−11 2023−01 2023−0 3 Date 0 20 40 60 80 100 Trips aCars Taxis Tric y cles Motorc y cles Weekends Fig. 5 Daily number of trips recorded for the different means of transport with the GPS loggers. q25 ¯x ˜x q75 σ Total distance in km 821 1562 1902 1913 2187 Daily distance in km 5 15 27 27 51 Total duration in hours 47 72 85 106 60 Daily duration in hours 0.4 0.8 1.2 1.4 1.5 Table 12 Total and daily recorded distances and durations of the participants. Fig. 4 Analysis of the roadside interviews and simultaneous traffic counting. 1 3 2531 Transportation (2025) 52:2511–2570 The analysis underscores that taxis are more frequently utilized in residential areas. Motorcycles are used for longer travel to towns and other regions, but not predominantly. In contrast, aCars, tricycles, and motorcycles usually cover distances of 2km to 10km through UHAs to travel between villages or to access fields. REA UHA REA UHA 0 1 2 5 10 20 Distance in km aCars REA UHA REA UHA 0 1 2 5 10 20 50 100 Taxis REA UHA REA UHA 0 1 2 5 10 Tricycles REA UHA REA UHA 0 1 2 5 10 20 50 100 Motorcycles Fig. 7 Distances covered in residential (REA) and uninhabited areas (UHA). Fig. 6 GPS traces by mode focused on the region nearby Zatta. The inset includes all trips, also the less frequent trips exceeding the Zatta area. 1 3 2532 Transportation (2025) 52:2511–2570 We further delve into the cross−combinations between UHA and REA origin/destination combination, as depicted in Fig. 8, encompassing both the recorded number of trips and their distances. We recognize that: ●The aCars show a lower number of trips from REAs to UHAs than from UHAs to REAs. The discrepancy suggests there may be occasional data logging gaps. The median distances involving UHAs are nearly the same, within 5km, reflecting the car’s agricultural service-oriented usage, which aligns with the typical distances to fields and forests discussed in previous sections. In contrast, trips within REAs are relatively short, indicating many intra-village travels. Longer outliers stem from traffic between different villages. ●Taxis make about ten times more trips within or between REAs than for other combinations. Trips solely connecting two UHAs are nearly negligible in count, constituting only 3 out of every 1,000 trips, even though their distances are significant. Analysis of Fig. 8 Cross combinatory analysis differentiating residential (REA) and uninhabited area (UHA) originsdestination pairs. 1 3 2533 Transportation (2025) 52:2511–2570 trip records indicates that the primary purpose for these longer trips is likely private leisure. Trips that include REAs tend to be more consistent, with an average distance of around 10km. This suggests that taxis are more commonly used for longer rides to and from residential areas. ●Tricycles feature twice as many trips within or between REAs than trips involving UHAs. Trips only involving REAs are relatively small, indicating a majority of travels inside REAs. UHA to REA trips are shorter than REA to UHA trips, suggesting that they are often combined with short trips within the UHAs within one journey. ●Motorcycles’ have four times more trips within or between REAs than for combinations including UHAs. Still, solely UHA trips significantly increase compared to taxis or tricycles. Motorcycles cover short distances within REAs, with outliers indicating longer trips up to 100 km for journeys between residential areas. Trips between REAs and UHAs are approximately 3 to 5 km long, reflecting agricultural transport purposes around Zatta. Solely UHA trips average 1.8 km, indicating they are combined within one journey. Transport electrification modeling considerations Since the intention of the aCars’ field test is evaluating the general suitability of EVs in RTSs within or outside of electrified areas, Fig. 9 further details the essential parameters for modeling local EV operations for each of the four vehicle classes in the GPS dataset. One of the main operational challenges is recharging, which we assume to be possible only at the vehicle’s home base as public (fast) charging infrastructure is not available yet in rural African settings. We, therefore, combine trips to tours starting and ending in Zatta, as their length determines the necessary range for EVs. Their departure time is crucial if the energy is to be provided locally through renewable sources only available at certain times of day and especially if the vehicles shall be intelligently managed to minimize charging cost. Total energy throughput and tour duration (i. e. return time) depend on the average speed within the driving portions and the idle time during the tour. Therefore, the parameters’ distributions are plotted in Fig. 9. As the diversity in data quality and tour behavior between the vehicle classes would make histograms quite confusing, we choose to present most of the data in cumulative form. We exclusively use a Gaussian kernel density estimation of the probability density for the departure time to ease the plausibility check of daily patterns. Notably, due to the non-representative composition and selection of the tracked fleet, no findings concerning absolute probabilities of demand levels for different vehicle classes in the target region can be drawn, limiting the analysis to relative demand characteristics. Nevertheless, to our knowledge, this is still the first quantitative dataset on transport electrification in rural SSA. Starting with the top left subfigure, the findings from the geographical analysis are confirmed as motorcycles and tricycles generally cover very short tours, the median being below 2km. While both the aCars and taxis based in Zatta also conduct about 30% of their tours similarly, the majority cover longer distances marked by distinctly right-shifted distributions. The marked accumulation (ca. 40%) of taxi tours at 35 km to 45 km and 70 km to 90 km signifies their frequent usage shuttling between the regional hub of Yamoussoukro and Zatta, which are about 18km apart. The aCars experience similar accumulations -albeit 1 3 2534 Transportation (2025) 52:2511–2570 seen in Sect. Human-centered surveys, primarily due to the scarcity of transport vehicles. Walking as a mode of transport poses substantial risks and dangers, especially for women, due to external factors as noted in Sect. Impact on sustainable development. The mentioned insights, along with evidence from Sect. Impact on sustainable development, highlight that regional development and progress in various areas are substantially promoted by mobility, positively impacting SDG achievements. Moreover, the reciprocal relationship between mobility access and sustainable development underscores the necessity to prioritize transportation understanding and progression, which seems equally crucial to existing SDG indicators. By integrating transportation considerations into broader sustainable development agendas, policymakers can catalyze positive socio-economic impacts and foster inclusive growth of rural communities in emerging economies. Outlook Moving forward, there are several possibilities for further research and exploration. Firstly, to gain an even more extended understanding of the topics covered in this study, conducting additional on-field studies with a larger sample size of gender-diverse participants would be beneficial. This would allow for a deeper investigation into various aspects of mobility dynamics in rural areas, providing more an even more detailed picture of transportation behavior and motifs. Additionally, extending the study scope to more villages surrounding the local market hub can offer a more holistic perspective on local disparities in the region. Furthermore, exploring whether mobility mechanisms similar to those observed in our study apply to other rural regions in Côte d’Ivoire or SSA can provide valuable comparative insights. While this paper primarily focuses on understanding mobility and its impacts on rural society in SSA regions, future research endeavors could delve into sustainable strategies for improving existing mobility systems based on the insights gained. By exploring options for enhancing mobility sustainably, future publications can contribute to developing targeted interventions and policy recommendations to address transportation challenges and foster socio-economic development in rural communities. Overall, the insights of this study contribute to the basis for future research efforts to advance our understanding of mobility dynamics and drive positive progress in SSA regions. Supplementary information We provide a supplementary dataset that includes all trip information of the recorded tracks, described in Sect. GPS logging. Raw GPS coordinates are excluded, and dates, tracking IDs, origins, and destinations are anonymized in this dataset to protect the participants’ privacy. 1 3 2541 Transportation (2025) 52:2511–2570 Appendix 1: Research design See Figs. 12 13, 14, 15 and Tables 14, 15. Fig. 14 Representative cards for the collective survey. Fig. 13 Short impression of all vehicle types we tracked during the research project in Zatta and its surrounding region. Fig. 12 Timeline and mobility-focused surveys of the project. 1 3 2542 Transportation (2025) 52:2511–2570 Fig. 15 Board design of the collective survey, including exemplary the results of Zatta. 1 3 2543 Transportation (2025) 52:2511–2570 Table 14 Full overview of the participants’ tracking, including the participants’ occupations and problems that came up during the recording process. Participant Occupation Vehicle Distance recorded in km Considered Problems 1Carrier aCar 2016 ✓ – 2Carrier aCar 1884 ✓ – 3Carrier Tricycle 742 ✓ – 4Carrier Tricycle 0xSD-Card missing 5Carrier Tricycle 0x Energy installation broken 6Carrier Tricycle 0xSD-Card missing 7Carrier Tricycle 0xLogger missing 8 Construction manager & worker Car 0xLogger missing 9Cooperative representative Motorbike 840 ✓ – 10 Farmer Motorbike 2655 ✓ – 11 Farmer Motorbike 1858 ✓ – 12 Farmer Motorbike 1781 ✓ – 13 Farmer Motorbike 1722 ✓ – 14 Farmer Motorbike 883 ✓ – 15 Farmer Motorbike 772 ✓ – 16 Farmer Motorbike 674 ✓ – 17 Farmer Motorbike 97 x Antenna cable broken 18 Farmer Motorbike 0 x Data corruption 19 Farmer Motorbike 0 xSD-Card missing 20 Farmer Motorbike 0 x Data corruption 21 Farmer Motorbike 0 x Data corruption 22 Farmer Tricycle 116 ✓ SD-Card missing once 23 Farmer Tricycle 0xLogger missing 24 Farmer Tricycle 0xLogger missing 25 Pisteur Motorbike 1072 ✓ – 26 Pisteur Tricycle 0xSD-Card missing 27 Plumber Motorbike 2064 ✓ – 28 President of rice cooperative Motorbike 1410 ✓ – 29 Taxidriver Car 10002 ✓ – 1 3 2544 Transportation (2025) 52:2511–2570 Semi-structured interview guideline Information The guideline was developed during a Bachelor’s Thesis of Grambs (2022) in the context of the research project connected with this publication. The guideline language is French, the predominant language in the survey region around the village of Zatta. 1. Demande de données personnelles Nous vous remercions d’avoir accepté de participer à cette interview. Tout d’abord, quelques questions sur votre personne : ●Nom, Âge, sexe, (ancienne) profession, situation/état civil. 2. Pour commencer, nous aimerions savoir à quoi ressemble votre vie quotidienne. ●à quelle heure commence votre journée ? No. Interviewees’ occupation Gender Age Village Date of interview 1Carpenter Male 42 Zatta 04.05.2022 2Doctor Male 55 Zatta 04.05.2022 3President of youth Male 35 Zatta 07.05.2022 4Representative of youth Male 25 Zatta 07.05.2022 5Representative of agricultural cooperative Male 56 Zatta 29.04.2022 6Representative of women Female 55 Zatta 05.05.2022 7School director Male 60 Zougonou 05.05.2022 8Teacher Male 45 Zougonou 05.05.2022 9Farmer Male 60 Koussé 05.05.2022 10 Farmer Male 30 Koussé 05.05.2022 11 Farmer Male 30 Koussé 05.05.2022 12 Farmer Male 42 Koussé 05.05.2022 13 Housewife Female 40 Koussé 05.05.2022 14 Moto -taxi driver Male 32 Koffikro 02.05.2022 15 Farmer Male 40 Koffikro 28.04.2022 16 Merchant Female 40 Koffikro 28.04.2022 17 Tailor Female 25 Koffikro 28.04.2022 18 Village Chief Male 60 Bokabo 02.05.2022 19 Advisor to the village chief Male 50 Bokabo 02.05.2022 20 Moto -taxi driver Male 19 Bokabo 02.05.2022 Table 15 List of all personally interviewed locals, including their occupation, age, and living place. 1 3 2545 Transportation (2025) 52:2511–2570 ●Quelles sont les activités de votre travail ? ●Combien d’heures dure votre travail ? ●Combien d’heures après/en dehors du travail sont travaillées dans la journée sans être rémunérées ? Par exemple, l’éducation des enfants, l’administration, les fonctions attribuées, les tâches ménagères ? ●Avez-vous des activités de loisirs spécifiques ? ●Y a-t-il des cycles hebdomadaires ? Par ex. le jour du marché. ●Questions spécifiques à la profession, par ex. jour de marché : ●Comment se déroule un jour de marché typique ? ●Différentes personnes ont-elles des rôles différents ? ●Oú apportez-vous la marchandise ? ●Quelle part de la marchandise gardez-vous au village et quelle part est vendue ? ●Qui achète la marchandise ? ●Oú vont les marchandises à la fin ? ●La marchandise est-elle perdue, par exemple si elle n’est pas vendue ou si elle est endommagée pendant le transport ? ●Qu’achetez-vous au marché ? 3. Questions sur les habitudes de mobilité ●3.1 Nous souhaitons maintenant savoir comment vous vous déplacez dans votre vie quotidienne.Oú vous déplacez-vous ? ●A quelle fréquence vous déplacez-vous ? ●Quand vous déplacez-vous ? ●Y a-t-il des périodes précises pendant lesquelles la mobilité est accrue ? A quels intervalles ? ●Pendant combien de temps vous déplacez-vous ? ●Avec quels moyens de transport vous déplacez-vous ? ●Avec quelles personnes vous déplacez-vous habituellement ? ●Combien d’argent consacrez-vous à la mobilité dans votre vie quotidienne ?3.2 Opinions sur les différents moyens de transportSe déplacer à pied : avantages et inconvénients, activités, personnes adaptées. ●Effectuer des trajets à vélo : avantages et inconvénients, activités, personnes adaptées. ●Effectuer des trajets en moto/mobylette : avantages et inconvénients, activités, personnes adaptées. ●Parcourir des trajets en tricycle : avantages et inconvénients, activités, personnes adaptées. ●Effectuer des trajets en voiture : avantages et inconvénients, activités, personnes adaptées. ●Auriez-vous volontiers recours à d’autres moyens de transport si cela vous était possible ? 1 3 2546 Transportation (2025) 52:2511–2570 4. Décrivez les problèmes/besoins que vous percevez dans votre localité. ●4.1 Approvisionnement et utilisation de l’énergieUtilisez-vous actuellement de l’électricité ? ●De quelle source ? ●Dans quel but ? ●Combien vous coûte l’électricité ? ●Quels sont les problèmes que vous rencontrez dans votre utilisation quotidienne de l’électricité ?4.2 Soins médicauxQuel est le lien avec les soins de santé ? ●Comment réagissez-vous en cas d’urgence médicale ? ●Quel est le coût du transport en termes d’urgence médicale ?4.3 Disponibilité de l’eau potableQuelle eau buvez-vous ? ●Combien de temps faut-il pour se procurer de l’eau potable ? ●Combien payez-vous pour l’eau potable ?4.4 écoleOú se trouvent les écoles les plus proches ? ●Combien de temps faut-il pour se rendre dans ces écoles ? ●Comment les écoliers se rendent-ils à l’école ? 5. Questions dans le cadre d’un atelier du futur ●Quelle utilisation de la mobilité pensez-vous pouvoir être envisagée à l’avenir ? ●Comment pensez-vous que la mobilité évoluera à l’avenir ? ●Qui profiterait particulièrement des différents changements en matière de mobilité ? ●Pensez-vous que la mobilité peut conduire à une amélioration de la qualité de vie générale ? 6. Projet aCar (en rapport avec le rooting) ●Présentation du projet. ●Y a-t-il des trajets que vous empruntez particulièrement souvent ? ●Pourriez-vous envisager d’utiliser l’aCar comme service ? ●Pensez-vous que la voiture offre une valeur ajoutée que les autres voitures ne peuvent pas avoir ? ●Si vous pensez à l’équipement de la voiture, y a-t-il des caractéristiques particulières à prendre en compte ? ●Qui, selon vous, profiterait le plus d’un tel moyen de transport ? 1 3 2547 Transportation (2025) 52:2511–2570 Appendix 2: Research results See Figs. 16, 17 and 18. Tables 19 and 18. Fig. 16 Important locations identified during the Zatta workshop by the first group of locals. 1 3 2548 Transportation (2025) 52:2511–2570 Fig. 17 Important locations identified during the Zatta workshop by the second group of locals. 1 3 2549 Transportation (2025) 52:2511–2570 Fig. 18 Important locations identified during the Zatta workshop by the third group of locals. 1 3 2550 Transportation (2025) 52:2511–2570 Location* Date† Time Age Gender‡ No. of people Direction†† Mode‡‡ Origin Destination Purpose Detail Frequency Distance Cost** Interviewers S14.2 13:48 35, 40 m(2x) 2 Out T Field Zatta, tomato field Work, construction, transport palm leaves They go to their father’s tomato field to build a shed out of palm leaves. Yes, exceptional purpose 100 m Tricycle owned by the owner of the farm 3,4 S14.2 14:00 38 m1In WFields (cacao) Zatta Firewood (Fago), transport of two chicken Additional work, actually works as a mechanic Daily 1 km Wheel– barrow: 5000 3,4 S14.2 12:24 12 f1Out W Zatta – Take firewood and water – Daily 20 min –3,4 NE 15.2 12:00 30, 35 m(2x) 2 Out W Zatta Constru–ction site House on construction site Carried with him: cement, water for drinking Daily 500 m –3,4 Table 16 (continued) 1 3 2557 Transportation (2025) 52:2511–2570 Location* Date† Time Age Gender‡ No. of people Direction†† Mode‡‡ Origin Destination Purpose Detail Frequency Distance Cost** Interviewers NE 15.2 12:00 – m 1In MField at Tenikro Zatta Worked (caco champ), now. take a rest at home – Daily 17 km –2,3 NE 15.2 12:00 55 f1In WField Zatta Firewood, yam –Daily, multiple times 3 km –2,3 NE 15.2 12:00 52 m1In BField Zatta Work Maniok, gombo, aubergine Not regulary 7km B: 30000 2,3 NE 15.2 12:00 48 m1In BField Zatta Banana harvest Bananas are sold on market on Wednesday 5–6 times per week 4km B: 30000 2,3 NE 15.2 12:30 50 m(2x) 2 In WAero– port Zatta Bush rats 2 men with dogs were chasing rats and wanted to sell them later in Zatta Daily 5km –2,3 Table 16 (continued) 1 3 2558 Transportation (2025) 52:2511–2570 Location* Date† Time Age Gender‡ No. of people Direction†† Mode‡‡ Origin Destination Purpose Detail Frequency Distance Cost** Interviewers NE 15.2 12:30 – m 1In BField Zatta Return to Zatta for rest Champignon, fish Daily 3 km –2,3 NE 15.2 13:00 58 m1In WCon– stru– ction site Zatta Getting sth. from the construction site – Daily 50m –2,3 NE 15.2 13:00 40 m1In MField Zatta – – Daily 3km 40000 2,3 NE 15.2 13:00 35 m1In BField Zatta Collecting Firewood, ignam Daily 7 km B: 30000 2,3 NE 15.2 13:00 30 f1Out B Zatta Cons–truction site Getting food Tomates – – – 2,3 * NW: northwest entrance of Zatta, NE: northeast entrance of Zatta, S: south entrance of Zatta; † in the year 2022;‡ f: female, m: male; †† In: to, Out: out of Zatta;‡‡ B: bicycle, M: motorbike, T: tricycle, W: walk; ** costs in CFA, ‡‡ applies. Table 16 (continued) 1 3 2559 Transportation (2025) 52:2511–2570 Table 17 Locals that were just counted during the roadside interview phase. Location* Date† Gender‡ No. of people Direction†† Mode‡‡ Cargo NW 14.2 m7In B– NW 14.2 m1Out B– NW 14.2 m(c) 1 In B– NW 14.2 m3In M– NW 14.2 m(c) 1 Out M– NW 14.2 f9In W– NW 14.2 f(c) 3 In W– NW 14.2 m – In W– NW 14.2 m – Out W– S15.2 m1Out MGenerator S15.2 m3In T Wood S15.2 m1Out T – S15.2 f1In W Wood S15.2 f4In T People S15.2 m1In B– S15.2 m1In B– S15.2 m1Out M– S15.2 m3Out T People S15.2 m1In BProduce S15.2 m1Out M– S15.2 m1In BProduce * NW: northwest entrance of Zatta, S: south entrance of Zatta; † in the year 2022; ‡ f: female, m: male, c: child; †† In: to, Out: out of Zatta;‡‡ B: bicycle, M: motorbike, T: tricycle, W: walk 1 3 2560 Transportation (2025) 52:2511–2570 Destination Mean of transport Days per week No. of days per week Distance (one way) Person Village Church Walk Wed, Sun 2 0.5 1 1 Field Walk Mo, Tue, Thur, Fri, Sat 5 5 1 1 Church Moto Sun 1 1 2 1 Field Moto Mo, Tue, Thur, Fri, Sat 5 7 2 1 Yamoussoukro Car Wed, Sun 2 15 2 1 Church Walk Sun 1 0.3 3 1 Field Moto Mo, Tue, Wed, Thur, Fri, Sat 6 4 3 1 Church Walk Sun 1 0.5 4 1 Field Walk Mo, Tue, Wed, Thur, Fri, Sat 6 3 4 1 Church Walk Sun 1 0.3 5 1 Field Walk Mo, Tue, Wed, Thur, Fri, Sat 6 2 5 1 Church Walk Sun 1 1 6 1 Field Walk Mo, Tue, Wed, Thurs, Sat 5 6 6 1 Yamoussoukro Taxi Fri 1 21 6 1 Church Walk Sun 1 0.5 7 1 Field Walk Mo, Tue, Wed, Thurs, Fri, Sat 6 5 7 1 Church Walk Sun 1 0.1 8 1 Field Walk Mo, Tue, Wed, Thurs, Fri, Sat 6 5 8 1 Field Walk Mo, Tue, Wed, Thurs, Fri, Sat 6 2 9 1 Charging Phone Walk Wed 1 4 10 1 Church Walk Sun 1 4 10 1 Domicile Walk Thur 1 5 10 1 Field Walk Mo, Tue, Sat 3 8 10 1 Church Walk Sun 1 0.5 11 1 Field Walk Mo, Tue, Thurs, Fri, Sat 5 7 11 1 Zatta Walk Wed 1 10 11 1 Church Walk Sun 1 1 12 1 Field Bike Fri, Sat 2 3 12 1 Field Walk Mo, Tue 2 3 12 1 Yamoussoukro Taxi Wed 1 21 12 1 Zatta Bike Thur 111 12 1 Church Walk Wed, Sun 2 1 13 1 Field Walk Mo, Tue, Thurs, Fri 4 6 13 1 Yamoussoukro Bike Sat 1 24 13 1 Church Walk Wed, Sun 2 1 14 1 Field Walk Mo, Tue 2 4.5 14 1 Loblakro Bike Fri 1 36 14 1 Yamoussoukro Bike Thur 1 22 14 1 Church Walk Sun 1 1 15 1 Field Walk Mo, Tue, Wed, Thurs, Fri, Sat 6 3 15 1 Field Walk Mo, Tue, Wed, Thurs, Fri 5 4.5 16 1 Yamoussoukro Taxi Sat 1 22 16 1 Church Walk Sun 1 1 17 1 Field Walk Mo, Tue, Wed, Thurs, Sat 5 6 17 1 Table 18 Raw table of answers given during the travel diary survey explained in Section 3.1.3 and evaluated in Sect. 4.1.2. 1 3 2561 Transportation (2025) 52:2511–2570 Destination Mean of transport Days per week No. of days per week Distance (one way) Person Village Yamoussoukro Taxi Fri 1 21 17 1 Church Walk Sun 1 0.3 18 1 Field Walk Mo, Tue, Wed, Thur, Sat 5 2 18 1 Yamoussoukro Walk Fri 1 22 18 1 Church Walk Sun 1 0.5 19 1 Field Walk Mo, Tue, Wed, Thursdays, Fri, Sat 6 3 19 1 Church Walk Sun 1 0.3 20 1 Field Moto Mo, Tue, Wed, Thursdays, Fri, Sat 6 4 20 1 Church Walk Sun 1 0.3 21 1 Field Walk Mo, Tue, Thursdays, Fri, Sat 5 6 21 1 Yamoussoukro Walk Wed 1 22 21 1 Church Walk Sun 1 0.3 22 1 Field Walk Mo, Tue, Wed, Thursdays, Fri 5 6 22 1 Yamoussoukro Walk Sat 1 22 22 1 Different Villages Tricycle Fri 1 0 23 1 Ville Tricycle Wed 1 0 23 1 Work Tricycle Mo, Tue, Wed, Thursdays, Fri, Sat 6 0 23 1 Church Walk Sun 1 1 24 1 Field Bike Mo, Tue, Thursdays, Sat 4 4 24 1 Yamoussoukro Taxi Wed 1 22 24 1 Zougounou Moto Fri 1 18 24 1 Field Walk Mo, Tue, Thursdays, Sat 4 7 25 1 Field Walk Mo, Wed, Fri 3 6 26 1 Church Walk Sun 1 0.5 27 2 Field Walk Mo, Tue, Thursdays, Fri, Sat 5 2 27 2 Yamoussoukro Taxi Wed 1 22 27 2 Field Walk Mo, Tue, Thursdays, Fri, Sat 5 2.5 28 2 Yamoussoukro Taxi Wed, Sun 2 23 28 2 Church Walk Sun 1 0.2 29 2 Field Walk Mo, Tue, Thursdays, Fri, Sat 5 3 29 2 Yamoussoukro Taxi Wed 1 22 29 2 Field Walk Mo, Tue, Thursdays, Fri, Sat 5 1 30 2 Yamoussoukro Taxi Wed 1 23 30 2 Church Moto Sun 1 7 31 2 Field Walk Mo, Tue, Thursdays, Fri, Sat 5 3 31 2 Zatta Moto Wed 1 7 31 2 Church Walk Sun 1 0.2 32 2 Field Walk Mo, Tue, Thursdays, Fri, Sat 5 1.5 32 2 Church Walk Sun 1 0.3 33 2 Field Walk Mo, Tue, Thursdays, Fri, Sat 5 3 33 2 Field Tricycle Mo, Tue, Thursdays, Fri, Sat 5 1 34 2 Yamoussoukro Tricycle Wed 1 23 34 2 Field Walk Mo, Tue, Thursdays, Fri, Sat 5 8 35 2 Zatta Walk Wed 1 7 35 2 Table 18 (continued) 1 3 2562 Transportation (2025) 52:2511–2570 SDG Challenges potentials Detail 1 2345678910† Others‡ C Cost of Transportation – ––1–––––– – Mobility as a safety issue for women f1–––––––– – Mobility availability m ––3 1 –––2 1 – Mobility changes due to the rainy season m ––1––––1– – No driver’s license – – – – – – – 2– – – PEmpowerment through independent mobility m –––––––1– – Increase mobility between villages m ––2–––––– – Mobility to develop village 2m ––1–––1– – – 1 CPoverty* 2m –––––1– – – – P Democratize mobility access to strengthen the ecosystem – – – – – – – – – – x 2COrganization and completion of agricultural projects* 2m ––––––––– – Crop insecurity – – – 1–––––– – Food waste – ––2–––––1– Provide school meals m – – – – 1–––– – P Develop the agricultural sector by building infrastructure* 2m ––––––––– – Improve of goods transportation to allow a cheaper and better, decentralized goods exchange – ––––––––– x 3C Cost of health services f – – 2–––––– – Lack of medical equipment/staff m – 1– – 1–––– – Mistrust in the health care system* f – 11–––––– – Accessibility to health services m – 1– – 1–––– – Emergency mobility f – – 2–––––– – P Expand health care services m – 1––––––– – VbS services as proposed in Pizzinini et al. (2023) – ––––––––– x Table 19 Evaluation of SDG indicators intersecting with mobility within the survey described in Sect. 3.2.3. 1 3 2563 Transportation (2025) 52:2511–2570 SDG Challenges potentials Detail 1 2345678910† 4CCost of education* fm –––––1– – – – Bad school facilities fm – – – – 11– – – – Inadequate coverage of school access because of resources/staff f2m –––––1– – – – Long distances to school and unsafe routes m ––1–11– – – – PInvest school facilities* 3m ––––11– – – – Establish a school bus system m – – 1 1 –––1– – Better transportation system for teachers – ––––––––– x 5CWomen’s associations* f ––––––––– – Inequality between women and men f ––––––––– – Mobility as a safety issue for women f1–––––––– – PGiving means of mobility to women –1–2––––1– – Equal access to motorized transportation and self–driving for woman and men – ––––––––– x 6CMaintenance of drinking water facilities* m ––1–––––– – Drinking water availability/insecurity – ––311–––– – PDrinking water transportation beyond usual services – ––––––––– x 7C Access to energy m 1–2–11– – – – Cost of connection to the energy grid m – – – – 1–––– – P Usage of batteries – – – 1– – 1––1– Application and usages of synergies of BEVs for energy supply – ––––––––– x 8COrganization and completion of agricultural projects* 2m ––––––––– – Manual labor* m1–1–––––– – PDevelop the agricultural sector by building infrastructure* 2m ––––––––– – Improve working conditions* m1–1–––––– – Increase business productivity* 2m 1 –––––1– – – Transport service for agricultural machines – – – – – – – – – – x VbS services as proposed in Pizzinini et al. (2023) – ––––––––– x Table 19 (continued) 1 3 2564 Transportation (2025) 52:2511–2570 SDG Challenges potentials Detail 1 2345678910† 9CSubsidies by the Ivorian State* 2m –1––––––– – P Develop the agricultural sector by building infrastructure* 2m ––––––––– – Modern market* m ––––––1– – – Market goods transportation service – ––––––––– x 10 CInequality between youth and elders* f ––––––––– – Mode choice inequalities related to income and gender – ––––––––– x PSubsidies by Ivorian State* 2m –1––––––– – Fair transportation services that reach everyone – – – – – – – – – – x 11 C – PIncrease village decision–power on a structural level* 3m ––1–––1– – – Mobility to develop village 2m ––1–––1– – – 12 CFood waste* – ––2––––1– – P Improved goods inter–village goods transport via motorized transportation and infrastructure – – – – – – – – – – x 13 CClimate change* 2m –––1––––– – Crop security* – ––2–––––– – Transportation issues due to heavy rain – – – – – – – – – – x PMore flooding secured streets – ––––––––– x * not directly connected with mobility, but rather indirectly related; † additional content from on-site observations; ‡ general challenges and potentials mentioned within the interviews. Surveyee group numbers align with the entry positions of the groups in Table 8. For categories containing just one gender, only the number of individuals stating the information are listed. Mixed groups include gender information (male: m, female: f). Table 19 (continued) 1 3 2565 Transportation (2025) 52:2511–2570 Supplementary Information The online version contains supplementary material available at h t t p s : / / d o i . o r g / 1 0 . 1 0 0 7 / s 1 1 1 1 6 - 0 2 5 - 1 0 6 7 1 - 0 . Acknowledgements This research was conducted with funding from the German Federal Ministry for Economic Cooperation and Development (BMZ). The authors declare no conflict of interest between funding and the presented research approach. Author contributions The first author, D.Z., devised the idea for this publication and drafted the research proposal; D.Z. supervised and conducted the field research together with C.P. and P.R.; M.K., S.G., and V.R. conducted their theses during field research under the supervision of D.Z. and contributed with results to this paper; D.Z. analyzed the data, drafted the storyline, wrote the majority of the content, and illustrated the figures; M.K. contributed content to the Individual Travel Motifs, Roadside Interviews, and Community Travel Motifs section; S.G. and V.R. contributed content to the Personal Interviews and Impact on Sustainable Development section; P.R. contributed content to Vehicle GPS Logging and Transport Electrification Modeling Considerations section; C.P. and P.R. contributed valuable thoughts to the publication and reviewed the paper critically; D.Z. and P.R. revised the publication; M.L. made an essential contribution to the conception of the research project. He critically revised the paper for its important intellectual content; M.L. gave final approval of the version to be published and agreed to all aspects of the work. Funding Open Access funding enabled and organized by Projekt DEAL. This research was conducted with funding from the German Federal Ministry for Economic Cooperation and Development (BMZ). Data availability We provide a supplementary dataset that includes all trip information of the logged tracks, described in Section 3.1.1. Raw GPS coordinates are excluded, and dates, tracking IDs, origins, and destinations are anonymized in this dataset to protect the participants’ privacy. Declarations Conflict of interest The authors declare no conflict of interest between funding and the presented research approach. Ethical approval Not applicable. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. References Acheampong, R. A., Lucas,K., Poku-Boansi,M., Uzondu, C.: Transport and Mobility Futures in Urban Africa. 1st ed. 2022. The Urban Book Series. Cham: Springer International Publishing and Imprint Springer. (2022) https://doi.org/10.1007/978-3-031-17327-1 Allee, A., Schroeder, J., and Sherwood, J.: Powering Small-Format Electric Vehicles with Minigrids. Tech. rep. Rocky Mountain Institute.(2022) http://www.rmi.org/insight/minigrid-ev (visited on 10/16/2023) Balke, G., Adenaw, L.: Heavy commercial vehicles mobility: dataset of trucks anonymized recorded driving and operation (DT-CARGO). Data Brief 48, 109246 (2023). https://doi.org/10.1016/j.dib.2023.109246. Behrens, R., McCormick, D., Mfinanga, D.: Paratransit in African Cities: Operations, Regulation and Reform. Routledge, London (2016). https://doi.org/10.4324/9781315849515 1 3 2566