Abstract
Ride-hailing platforms are expanding globally, making inroads into developing markets. However, the technological affordances of many ride-hailing platforms were built in response to conditions in developed markets. Unlike developed markets, developing markets are characterized by infrastructural deficiencies, informality, and regulatory voids, which influence how consumers in these markets experience and use ride-hailing platforms. How do the affordances of ride-hailing platforms from developed markets shape the platforms' performance in developing markets? The authors explore this question using a qualitative ethnographic approach to examine Uber's operation in Ghana, engaging with drivers, riders, investors, Uber executives, and government officials. The findings show that Uber's platform performance in Ghana is shaped by three platform–market interaction outcomes: platform infrastructural deficiencies, (in)formalization, and affordance-based regulation. These interaction outcomes affect the platform's performance and manifest platform–market tensions. Market actors respond to the resulting platform performance with acceptance, avoidance, adaptation, substitution, resistance, brand responsibilization, and subversion. These insights contribute to research on the sharing economy, marketing in developing markets, and affordance theory. They also help ride-hailing managers understand how their platforms’ affordances work in other developing markets with similar characteristics and how they can manage the resulting platform performance and tensions to succeed in these markets.
I picked [up] a customer and asked her if she knew a better route, and she said, “Just follow your map [Uber navigation].” We ask because sometimes the map can take you on a very bad road. In Ghana, most of our roads are in bad shape. … Where she was going, the road was very bad. I even ended up getting a tire puncture. At the end of the trip, I realized she had a discount. They give riders huge discounts, so once the rider has a discount, they do not pay any amount to the driver. Imagine going through this bad road to drop off your rider, and then she ends up not giving you any money. It's really painful. We, Ghanaian drivers, love to have cash with us. (Razak, male, driver)
This narrative details Uber driver Razak’s experience with a rider in Accra, Ghana. It captures an unpleasant service delivery experience that manifests tensions—conflicts arising from misaligned goals and capabilities—when a global ride-hailing (RH) service encounters the unique circumstances of a developing economy like Ghana's. Uber's navigation system—initially developed in the United States and based on its infrastructure—does not account for the poor urban roads in developing countries with infrastructural deficiencies. As Razak feared, Uber's map sent him down a bad road, which resulted in a punctured tire and unwanted repair costs.
In addition, Uber's app, which determines ride prices, had, unbeknownst to Razak, given the customer a full “discount” on her ride, meaning she did not have to pay him directly when the ride ended. Ghana, like many other developing countries, has a cash-based economy, but Uber introduced a credit system in which the value of customers’ discounted rides is credited against the service fee that the driver pays weekly to Uber. This may be desirable in developed markets with cashless credit systems, but in Ghana drivers like Razak prefer cash payments, which allow them to pay their operating costs.
This opening quotation illustrates the tensions that can manifest when the affordances—defined as capabilities that enable or constrain user actions and outcomes—of global RH platforms built for developed markets interact with the distinct characteristics of developing markets. For simplicity, we conceptualize this phenomenon as platform–market tensions, or simply tensions. As we show, these tensions manifest as conflicts between what the platform's affordances offer and the developing market’s characteristics and participants’ goals.
RH platforms came into prominence as part of the rise of the sharing economy (SE) circa 2010, with firm-mediated, platform-based, peer-to-peer business models that have disrupted traditional markets (see Eckhardt et al. [2019] for a detailed review). Uber is the most prominent global RH platform, often competing with other global, regional, and local platforms in a market with more than one billion global users in 2023, more than 60% of whom are in developing or emerging markets (Statista 2024). A fundamental aspect of SE platforms is the technological affordances that enable their operationalization (Daramola and Etim 2022). Uber's success is based not only on its matching affordance that connects drivers and riders but also on its navigation and pricing affordances. We see in the opening scenario that both the driver and the rider complied with these affordances, even against their individual best interests. This is why it is important to understand the platform's affordances: They determine how the platform performs, which affects the user experience.
Affordances manifest between the product feature and the user's goals based on their environment and capabilities (Evans et al. 2017). RH platforms originating from developed markets were built for and in response to the characteristics of those markets (Eckhardt et al. 2019). However, developing markets are characterized by infrastructural deficiencies, informality, and regulatory voids, which influence how consumers in these markets experience and use sharing platforms (Hira 2017; Parente, Geleilate, and Rong 2018). Research suggests that developing market characteristics can enable or derail adoption of global RH platforms (Basukie, Wang, and Li 2020; Daramola and Etim 2022; Hira and Reilly 2017). Yet, research has not focused on how these outcomes may be shaped by the interaction of specific developing market characteristics (e.g., poor roads) with specific platform affordances (e.g., navigation), or how various market actors experience and respond to the resulting platform performance (e.g., avoiding navigation affordance). Thus, what remains unexplored is how the affordances of RH platforms from developed markets shape platform performance when utilized in developing markets.
We ask: How do the affordances of ride-hailing platforms from developed markets shape the platform's performance when utilized in developing markets? We address this question through an ethnographic study of the operations of Uber and other RH platforms (i.e., Bolt and Yango) in Ghana. Using an ecosystem approach, we engage key market actors in the local taxi and RH ecosystems, including riders, RH drivers, taxi drivers, car owners, Uber's country manager, and government officials. Rather than examining platform performance metrics (e.g., adoption rate), our analysis focuses on how well various market actors perceive that the platform delivers value or helps them achieve their goals.
In addressing this question, we contribute to research on the globalization of the SE by explaining how RH platform performance is shaped when its affordances interact with developing market characteristics. We explain how Uber's platform performance in Ghana is shaped by three types of platform–market interaction outcomes: platform infrastructural deficiencies, (in)formalization, and affordance-based regulation. These interactions can lead to positive assessments of the platform's performance but may also manifest platform–market tensions. We explain how various market actors respond to the resulting platform performance through acceptance, avoidance, adaptation, substitution, resistance, brand responsibilization, and subversion, and show how these responses may resolve or escalate tensions. We also discuss how these insights contribute to affordance theory and marketing in developing markets.
Although our research is based on data from Ghana, our findings are also applicable to RH platforms entering or operating in developing markets in Africa, Asia, and South America that share characteristics with Ghana, including poor roads and internet infrastructure, strong informal supply and exchange norms, and historical regulatory voids (Hira 2017), as we discuss in the next section. Our findings help managers of RH and other relevant SE platforms understand how their affordances may work differently in these developing markets with infrastructural deficiencies, informality, and regulatory voids. This is critical because the success of RH firms depends on their platform's affordances working as intended, which gives them control of the performance they deliver for users. Thus, we provide recommendations to help RH managers understand how they can succeed when their platforms’ affordances are utilized in such developing markets. We also discuss implications for governments and other stakeholders, such as drivers/service providers.
Theoretical Foundations
Marketing in Developing Economies
Developing economies are variously referred to as emerging, bottom-of-the-pyramid, low-to-mid-income, less industrialized, or third-world economies (Jakobi 2021; Prahalad 2005; Sheth 2011). Ghana is captured in all these categories. Disambiguating these different categorizations is beyond the scope of this article. For simplicity, we use “developing economy,” with “developed economy” as the comparison base. We also use “developing economies” and “developing markets” interchangeably because most markets in developing economies are characterized and shaped by the prevailing “developing” conditions in the macro economy (Jakobi 2021), as in our context in Ghana. However, we acknowledge that there are also developed markets in developing economies, such as the mobile money market in sub-Saharan Africa (Jack and Suri 2014).
Marketing research has identified three main characteristics of developing markets that are most salient and consequential for marketing managers and businesses operating in these markets: informality, regulatory voids, and infrastructural deficiencies. The first of these is that developing markets are informal, with large numbers of heterogeneous individual producers selling unbranded products and services through limited and closed-loop seller–buyer relationships (Sheth 2011; Viswanathan, Rosa, and Ruth 2010). According to the International Labour Organization (2024), in 2024, up to 88% of employment in developing countries was informal (86.3% in sub-Saharan Africa), compared with 12.9% in developed countries.
Second, as a reason for and outcome of their informality, developing markets have weak formal regulatory labor and market institutions (Barbour and Luiz 2019). Many developing markets lack formal government regulations that set standards; where regulations exist, they are poorly enforced (Barbour and Luiz 2019). Due to these regulatory (or institutional) voids, developing markets are largely dependent on informal labor arrangements, unstructured market systems, and cultural norms and social systems to guide relationships and exchanges (Jakobi 2021; Sheth 2011).
Finally, developing markets are characterized by inadequate and poor quality technological and physical infrastructure (e.g., internet, roads, and electricity) (Sheth 2011). For example, internet usage in low-income countries was estimated to be 27% of the population compared with 93% in high-income countries (International Telecommunication Union 2024). The International Monetary Fund developed a road quality infrastructure score for 144 countries on a scale of 1 to 7, with many developing countries scoring below 3.5 and many developed countries above 5.0 (e.g., Nigeria: 2.4; United States: 5.87) (Moszoro and Soto 2022).
To successfully serve these developing markets, marketing scholars have provided recommendations to nonlocal marketing practitioners to adjust their marketing mix (e.g., selling products in smaller quantities) (Prahalad 2005; Sheth 2011), leverage cultural norms and existing local partnerships and relationships (e.g., through local vendors) (Viswanathan, Rosa, and Ruth 2010), and develop formal systems to onboard informal actors (e.g., merchandising systems to manage store inventory) (Pels, Araujo, and Kidd 2022; Sutter et al. 2017).
However, marketing research has only recently started exploring how these developing market characteristics shape and are shaped by the advent of global SE platforms, like RH platforms, that are making inroads in these markets (Kozlenkova et al. 2021). Understanding how these developing market characteristics interact with SE platforms is important because SE platforms’ operations do not conform to many prior marketing and international business theories on managing the internationalization of global firms in developing markets (Parente, Geleilate, and Rong 2018). For example, unlike nonplatform firms that sell directly to customers, SE platforms use digital technology to mediate exchange between and among business and individual customers. Thus, their capabilities and affordances tend to differ from those of nonsharing/nonplatform incumbents (Eckhardt et al. 2019). Thus, Parente, Geleilate, and Rong (2018, p. 52) call for “further research on sharing economy firms and their interactions with different national ecosystem configurations [that] can provide important insights to theory as well as relevant information to managers and policymakers.” Our research advances this agenda.
RH Platforms in Developing Markets
Research that has examined the operations of RH firms in developing markets focuses on the motivation for adoption, transaction costs, and user experiences (Kozlenkova et al. 2021; Valente, Patrus, and Guimarães 2019). Here, we summarize key insights about how RH platforms interact with the three developing market characteristics and the gaps in the literature that we address (see Table 1). An extended paper-by-paper review is in Web Appendix A. We searched Google Scholar for papers that focused on the operation of RH and SE platforms in developing markets. As the SE literature is vast, we focused on review and conceptual articles that examine the operations of RH platforms in developing markets. We used search phrases such as “ride-hailing in developing countries,” “Uber in developing economies,” and “sharing economy in developing markets.” We selected articles from major journals to illustrate key insights representative of the findings from the papers we reviewed.
Review of Ride-Hailing Platform Interaction with Developing Market Characteristics.
Infrastructural deficiencies
RH platforms rely heavily on digital infrastructure—smartphone penetration, internet connectivity, payment systems—and although these enablers are improving rapidly in many developing markets, the growth is limited to urban areas (Hira 2017; Retamal and Dominish 2017). Physical infrastructure remains a persistent constraint. Poor road conditions, unreliable electricity, and weak public transit systems complicate service delivery, particularly in sub-Saharan Africa and parts of South Asia. However, these deficiencies also account for existing market demands, such as the need for efficient urban transportation, which RH platforms like Uber address (Boateng, Appau, and Baako 2022; Daramola and Etim 2022).
These infrastructural deficiencies are consequential. For example, in Ghana and India, internet and mobile access support RH adoption, but poor urban planning, road infrastructure, and traffic congestion reduce driver earnings and increase their stress (Agyemang 2020; Kashyap and Bhatia 2018). Although these deficiencies influence user experience (Basukie, Wang, and Li 2020), it is not clear how they shape specific platform affordances that drive platform performance, which may manifest tensions.
Informality
Many RH platforms thrive in developing markets precisely because they align with existing informal practices of work, exchange, and entrepreneurship (Hira 2017; Hira and Reilly 2017). Cultural acceptance of gig work, flexible income generation, and nonstandard employment arrangements facilitate the normalization of RH labor models in various developing markets (Basukie, Wang, and Li 2020; Kashyap and Bhatia 2018; Pasquali, Commenges, and Louail 2022).
In some markets, people aspire to work on RH platforms because they are more formal than traditional taxi systems (Boateng, Appau, and Baako 2022; Pasquali, Commenges, and Louail 2022). However, informality also results in precarious labor conditions (Daramola and Etim 2022). Additionally, although informal cultural norms enable trust in peer-to-peer models that support platform legitimacy, RH platforms introduce hierarchies, such as rent-seeking “taxidars” (taxi owners) in India or owner–driver dynamics in Ghana, which reproduce existing inequalities under the guise of flexibility (Agyemang 2020; Kashyap and Bhatia 2018). Digital exclusion, driven by literacy gaps and unequal smartphone access, also undermines participation among lower-income and low-literacy consumers (Retamal and Dominish 2017). Research has yet to fully examine how the interaction of the formal systems of RH platform affordances and these informal characteristics shapes the platform's performance in these markets, and how this may manifest platform–market tensions.
Regulatory voids
Regulatory voids are a persistent issue in developing market contexts. RH platforms often operate ahead of regulation, exploiting legal ambiguity to scale quickly while avoiding traditional oversight mechanisms (Chen and Wang 2019; Hira and Reilly 2017). Where regulations exist, they are frequently outdated or poorly enforced, as seen in India's partial reform attempts (Kashyap and Bhatia 2018) and Africa's fragmented approach to RH services (Boateng, Appau, and Baako 2022). While regulatory flexibility can facilitate market entry (Kozlenkova et al. 2021), over time the absence of coherent legal frameworks has significant consequences, such as a lack of labor protection, data privacy concerns, absence of environmental regulation, limited taxation, and ambiguous consumer safeguards (Hira and Reilly 2017; Parente, Geleilate, and Rong 2018).
Some governments, such as China’s, selectively maintain strategic regulatory oversight (Chen and Wang 2019). In comparison, in many developing markets, regulatory responses remain slow and reactive, particularly in sub-Saharan Africa, where platforms fill institutional voids not by design but by necessity (Barbour and Luiz 2019). However, the effects of RH platform affordances on the regulatory void in these markets and the implications for RH platforms and users remain unclear, despite research in legal studies suggesting that RH algorithms can act as regulators of drivers’ actions (Eyert, Irgmaier, and Ulbricht 2022).
In summary, prior research suggests that when RH firms encounter infrastructural deficiencies, informality, and regulatory voids in developing markets, the interaction can enable adoption but also create problems for platforms and market actors. What is not clear is how the interactions between the platform's affordances and the market characteristics shape the platform's performance, which, in turn, manifests platform–market tensions. We address these tensions and examine how different market actors respond to the resulting platform performance. Next, we explain affordance theory and how Uber's platform affordances work.
Affordances
As a broad sociotechnical concept, affordances have been used to examine how places, physical and digital objects, rules, practices, and ideas enable or constrain what people can and cannot do (Borghini, Sherry, and Joy 2021; Mardon, Denegri-Knott, and Molesworth 2023; Norman 1999; Pavlyuchenko and Dion 2025). As a relational concept, affordances describe perceived and actual “action possibilities” that exist between the intentions and actions of a goal-oriented actor and the characteristics of spaces, time, and objects in their environment (Gibson 1979). Thus, affordances are not features; they are what relate features (characteristics of a thing or environment that are present/absent) to outcomes (the result of an action) (Evans et al. 2017). For instance, while an object feature may be present or absent (e.g., a doorknob), its affordance manifests in how a goal-oriented actor perceives or uses it (e.g., opening the door). This can lead to actors using a specific object feature for diverse, and sometimes contradictory, behaviors and outcomes (Evans et al. 2017).
The concept of affordances has also been applied to explain how technologies and platforms constrain what users can and cannot do with their features (Gaver 1991; Kozinets, Ferreira, and Chimenti 2021). It is important to note that Uber's platform has standard affordances that largely operate the same way globally, with minor localization. As our goal is to explain how the affordances of the Uber platform interact with Ghana's developing market ecosystem characteristics, we focus here on what Davis and Chouinard (2016) call affordance mechanisms, which explain how affordances work or how “artifacts afford” (p. 241). Davis and Chouinard (2016) propose six affordance mechanisms: allow, request, demand, encourage, discourage, and refuse. We augment and apply these mechanisms to explain how the affordances of Uber's platform features shape user action possibilities. We summarize this in Table 2.
Uber's Affordance Mechanisms.
Affordance mechanism added by the authors, which extends Davis and Chouinard (2016).
The allow mechanism explains what users can do with the platform's features and what users’ actions enable the platform algorithms to do. For example, the Uber platform allows users to request rides by entering their pick-up and drop-off locations, which then allows the Uber algorithm to connect the rider to the nearest available driver. Requests and demands are ways that the platform specifies user actions. Requests enable flexibility in these actions (e.g., complete user profile), but demands are rigid (e.g., upload ID to verify identity), and noncompliance with demands leads to the platform closing action pathways (refuse).
Encourage, discourage, and refuse are feedback systems that the platform provides by rewarding, punishing, and failing, respectively, to respond to certain user actions. For example, the two-way ratings and review feature encourages drivers and riders to be polite to each other, or discourages them from being rude. As noted, the platform algorithms can refuse a user access if the demanded actions are not fulfilled.
We also extend Davis and Chouinard's (2016) typology of affordance mechanisms by including dictate as an affordance mechanism that is more instructive and less flexible than request but less instructive and more flexible than demand. Dictate sits between request and demand. For example, during the trip, the platform's navigation dictates directions, but the driver can use a different route or turn.
These affordance mechanisms are neither exhaustive nor mutually exclusive but can be understood as a continuum of how the Uber platform “affords” (Davis and Chouinard 2016). In the “Findings” section, we explain platform–market interaction outcomes and tensions that arise when Uber's platform affordances interact with infrastructural deficiencies, informality, and regulatory voids in Ghana's taxi and RH ecosystem.
Research Context: The Taxi and RH Ecosystem in Ghana
Like many market ecosystems in developing economies, Ghana's commercial transportation market is informal, with many actors playing various roles in a complex network of services provided by buses (trotro), taxis, rental cars, and motorbikes (Hart 2019). Research has also noted the infrastructural deficiencies and regulatory voids that characterize this market (Agyemang 2020; Boateng, Appau, and Baako 2022; Pasquali, Commenges, and Louail 2022), which we will examine in our “Findings” section. Here, we describe the informality of the market and its evolution with the advent of RH platforms, particularly with the arrival of Uber in 2016.
We consider taxis and RH services to be part of the commercial transportation market in Ghana but distinguish them by their distinct market ecosystems. Figure 1 provides a simple illustration of the two ecosystems based on our data. As illustrated on the left side of Figure 1, the traditional taxi ecosystem often begins with entrepreneurial individuals (known as the “car owners”) who invest in a taxi for additional income and find their drivers through their social networks. Drivers find passengers at vehicle stations where customers share a ride to specific destinations or pick up on-demand passengers who hail them from the roadside.
The Taxi and Ride-Hailing Market in Ghana.
Some car owners informally lease the taxi to the driver, who must pay a fixed weekly rent (called “sales”). The driver pays for fuel and other running costs, such as car registrations, while the car owner pays for repair and maintenance. Other car owners use an informal loan arrangement (called “work and pay”), offering the car as a loan to the driver over a two- or three-year period. The loan repayment amount is typically double the car purchase price. The driver makes weekly repayments and acquires full ownership after fully amortizing the agreed loan amount. Under this informal loan arrangement, all operating costs, including repair and maintenance, are the driver's responsibility.
When Uber began operating in Ghana in 2016, it created a RH ecosystem that is both similar to and different from the traditional taxi system. Like the traditional taxi system, the Uber RH ecosystem begins with the investor buying a car and leasing/loaning it to a driver. There are, however, notable differences: who can become a driver, how drivers find customers, and how customers pay drivers. Cash payments for Uber rides go directly to the driver, who then pays a service fee to Uber at the end of each week. By contrast, cashless (e.g., debit card) payments are made directly to Uber, which deducts its service fee and then transfers the remainder to the driver. These characteristics of this market made it an interesting context to examine our research question.
Ecosystem Research Methodology
Data Collection
We adopted an ethnographic ecosystem approach (Phillips and Ritala 2019) by engaging with all the key market actors, institutions, and data sources in the ecosystem described in the research context. Our primary data collection occurred in two waves, between November 2019 and July 2022, in Accra, as Ghana's capital and most populous city is the main location in which RH brands operate. We adopted ethnographic methods, which are most appropriate for answering our research question (Hill, Canniford, and Eckhardt 2022). Data collected include personal interviews, field observations and photographs, government reports, and media data (see Web Appendix B).
Interviews
The first phase of data collection began with in-depth interviews with 29 key actors in the RH ecosystem: drivers (10), riders (15), and car owners (4). Two of the drivers owned their cars; the rest were renting. We recruited some of these initial informants through personal networks and used a snowball sampling technique to recruit subsequent informants. We began with an initial interview guide that we adapted as the fieldwork progressed (McCracken 1988); the interview guide is included in Web Appendix C. All the interviews were conducted in person at locations chosen by informants. This first round of interviews (November 2019–January 2020) helped us develop initial themes about the ecosystem and identify themes for further investigation.
We returned to the field in February–July 2022, during which we interviewed 15 additional informants. This round of interviews—conducted to augment and extend our findings from the initial stage—was more purposive, and our interview guide was amended to reflect this (McCracken 1988). For example, we reinterviewed four informants from the first round of interviews in 2020 to examine any shifts in perception over time. We interviewed three new drivers—two had switched from driving on Uber to Bolt, and one only drove for Bolt. (Bolt and Yango are Uber's main competitors in Ghana.) We also interviewed taxi drivers to understand their experience and response to RH firms’ operations.
We interviewed deputy directors at the Ministry of Transport and the Driver and Vehicle Licensing Authority (DVLA). The DVLA registers cars and issues licenses, and the Ministry of Transport is the government department that signed the memorandum of understanding with RH firms to enable them to operate in Ghana. We also conducted three interviews with the then–Uber country manager for Ghana and the Ivory Coast. These three informants gave consent to use their actual names in the research; all other names are pseudonyms. All interviews, which lasted 30–180 minutes, were conducted in English and the local Twi language and were audio-recorded with the informants’ consent. Recorded interviews were professionally translated and transcribed, then later checked for accuracy by the first author, who is fluent in both languages. Table 3 provides a summary of the interview participants’ profiles.
Informant Profiles.
Denotes an informant interviewed more than once.
Denotes a car owner who has multiple cars.
Denotes a driver who owns their car.
Notes: M = male; F = female. Some informants preferred to give an age range instead of their specific age.
Observation, media, and government data
Our fieldwork also involved observation of key aspects of the market (Hill, Canniford, and Eckhardt 2022). This involved informal participant observations and visits to the Uber offices to understand how drivers are trained and how Uber manages its operations in Ghana. We documented these observations through photographs and field notes. Additionally, we collected data on media coverage of RH brands in Ghana for the period 2016–2022 to understand media representations of the brands. We focused on the online archives of Ghana’s three main news media outlets, using search terms like “Uber,” “Bolt,” “ride-hailing,” and “online taxis.” Although the search generated over 200 results, we focused our analysis on 103 articles that covered local news. We then collected official data and reports from various government bodies—such as car registrations and road crash data—to help deepen our understanding of RH brands’ impact in Ghana (Humphreys and Latour 2013).
Data Analysis
We analyzed the data using qualitative thematic and content analysis (Hill, Canniford, and Eckhardt 2022; Siebert et al. 2020) in two main phases that mirrored our fieldwork. The first phase of open and axial coding (Spiggle 1994) was conducted after the initial round of interviews in 2020. We used the informant groups (riders, drivers, and car owners) as the unit of analysis during open coding. During the axial coding phase, we generated intergroup themes that drew on all the themes developed in the open coding. Thematic analysis was carried out using a hermeneutical analysis of the transcribed interview data text (Thompson 1997).
The second round of data analysis used axial coding to deepen emerging themes from the first round of data analysis and to develop additional themes using the same hermeneutical interpretation of interviews, media, photos, field notes, and government textual data. We discussed and refined emerging themes through an iterative exploration of existing literature on the SE (e.g., Eckhardt et al. 2019) and the sociocultural context of the taxi and RH market in Ghana (e.g., Hart 2019).
Findings
As illustrated in Figure 2, when Uber's platform affordances interact with the infrastructural deficiencies, informality, and regulatory voids that characterize Ghana's taxi and RH market, they lead to three interaction outcomes that shape the platform's performance. This effect on platform performance can be positive but also manifests specific platform–market tensions. We explain how different market actors—drivers, riders, car owners, the government, and Uber—respond to the platform's performance resulting from these interaction outcomes and related tensions. We find that they respond to the effects of platform infrastructural deficiencies with acceptance or avoidance; to the effects of (in)formalization with adaptation, substitution, or resistance; and to the effects of affordance-based regulation with brand responsibilization and subversion. We explain how these responses may resolve or escalate the tensions.
Platform–Market Interaction Outcomes, Tensions, and Responses.
Platform Infrastructural Deficiencies
When Uber's platform affordances interact with the relevant infrastructural deficiencies in Ghana, the affordances also become deficient, which affects the platform's performance. Tensions manifest because these infrastructural deficiencies lead to the platform not functioning as intended or desired by users, who respond to the resulting platform performance with acceptance or avoidance (see Figure 2).
Infrastructural deficiencies shape platform affordances
As noted, Uber's platform affordances were initially built in response to, and for, the U.S. market's infrastructure (i.e., the quality of the urban road network and internet accessibility), which is more developed than Ghana's. Only 27% of Ghana's road network is paved, and just 44% of the paved roads are in good condition (Ministry of Roads and Highways 2023). The opening quotation provides one example of how Ghana's poor roads can affect the perceived effectiveness and reliability of Uber's navigation affordance. Dominic, an Uber driver, explains how the poor roads also negatively affect drivers’ perception of the fairness and accuracy of Uber's pricing affordances. The roads are very bad, I mean here [in Accra], and I will have to pass through all these gutters, bumps, and things and go and pick the person … and drop the person at exactly their location, and the price is that! I mean, why? Why! After picking and dropping a rider, through such a road, and if I happen to break my shock absorber, what money am I going to use to repair [the car]? (Dominic, male, driver)
Similarly, the Uber platform relies on mobile phones and the internet to function optimally. However, the quality of internet coverage and infrastructure in Ghana is inferior to that of developed markets and may not always work as well as needed. This infrastructural deficiency can further render the platform's matching and pricing affordances deficient, which similarly affects its performance in fulfilling ride requests and fair driver payments. If you have a poor signal, there is no way you will have trips coming through. You will go looking for trips for a long time, and they will never come if your internet is weak. And let's say, you finally get a trip and the internet goes off, that means it is not going to read, and when you finally get to the destination and you end the trip, the price is going to reduce because it was not reading. (Akomeah, male, driver)
Acceptance and avoidance
Despite their complaints, some riders and drivers respond to the platform's suboptimal performance by accepting it as being the result of the country's infrastructural deficiencies, because it is not Uber's fault that “the internet service in Ghana is not really like out there [developed countries]” (Akomeah, male, driver). They therefore make do. However, others responded by avoiding the use of these compromised affordances when they could. For example, Esinam prefers to give drivers directions because she does not trust Uber's navigation affordances to offer the best route to her destination. She says, The moment I pick you, I tell you to put off that person talking [navigation]. I want to show you where to pass. That's what I do. Unless I don't know where I am going. (Esinam, female, rider)
As noted in the opening vignette, Ghana has a cash-based economy that lacks the level of infrastructure support for cashless payments found in developed markets. In 2016 (the year Uber launched), 99% of transactions in the country were undertaken via cash (Amoah et al. 2017). Strategically, Uber adapted its platform to enable cash payments for rides, as it had in other developing markets such as Mexico and Panama (Alvarez and Argente 2022). Electronic payments via debit/credit cards, which are more prevalent and popular in developed markets, remain part of the platform's affordances. However, as many riders discovered, drivers in Ghana dislike and avoid card-based transactions. The Uber drivers do not want to accept card trips. I don't know why … I requested an Uber, but the driver realized it was a card trip, so he cancelled. I re-requested, he accepted, realized it was a card trip, and he cancelled [again]. (Adwoa, female, rider) I will say most Uber drivers prefer cash. Me included. Because you are buying fuel, you are servicing your car, and you need the cash, you understand. … With the experiences that I have had [with card payments], you don't get your cash [from Uber] immediately. So, what happens if I don't have money to fuel or service the car until then? (Abeeku, male, driver-owner)
In short, the infrastructural deficiencies in Ghana render Uber's platform affordances deficient, leading to unsatisfactory platform performance, which manifests tensions. The affected market actors—drivers and riders—respond to the compromised platform performance with acceptance or avoidance.
(In)formalization
Uber's platform affordances are built and operationalized within its formal systems. When this formal platform and its affordances interact with the informality of Ghana's RH and taxi market, they mutually transform each other. On one hand, the platform's affordances formalize transactions and market actors who use it. On the other hand, the market imposes some of its informal structures and practices on the platform's affordances. This (in)formalization interaction outcome affects the platform's performance as it supplants many cultural and exchange norms that hitherto defined a market that was informal. Despite some positive assessments of this performance, it also manifests tensions that influence how some market actors respond to the platform's performance.
Formalization
One illustration of how Uber's platform's affordances formalize the market is through its matching and pricing affordances. In the informal market, to find a driver and determine ride prices, consumers would normally stop a taxi by the roadside, tell the driver their destination, and haggle over the driver’s proposed fee until they agree on a price. Uber's matching and pricing affordances have replaced these informal cultural norms and practices by using its algorithms to match riders and drivers and dictating ride prices without any influence from drivers or riders. Both riders and drivers comply with the platform's dictated matching and pricing. Consequently, the informal matching and pricing norms, which remain offline and undocumented, are supplanted by Uber's formal matching and pricing systems, which document every transaction and Uber ride.
For many riders, Uber's formalization of the ride transactions is a better alternative to the taxi ecosystem's haggling and its associated drivers’ moral hazard (Liu, Brynjolfsson, and Dowlatabadi 2021), such as overcharging unsuspecting passengers. Bertha says: With Uber, it's not the usual standing by the roadside, stopping several taxis and bargaining prices. Because there are times that you have to bargain with so many taxi drivers … but in the end, they still charge whatever they want to charge. But with Uber, you know it's per distance, the journey, so it's not like you are being cheated. (Bertha, female, rider) It's not like your typical Ghana taxi business, where there are no records of anything. With Uber, I look on the [driver's] app, and I see records of transactions. And I like the fact that, because it keeps records, you could see your margins in there, as an investor. (Atsu, male, car owner)
Owing to the hitherto offline and informal nature of the taxi and RH market, another prevailing norm involves high levels of rider–driver interactions before the ride (determining location and price), during the ride (giving verbal directions to the location and having casual conversations), and after the ride (cash payment and renegotiation of price, if needed). Through its matching affordance, Uber’s platform has transformed these interactions by introducing a higher level of formality and impersonalization that discourages driver–customer interaction when booking/accepting rides. This supplanting of informal market norms can manifest tensions that lead to different responses by market actors, which we discuss subsequently.
Informalization
An illustration of how the market's informality has also led to the informalization of Uber's platform and its affordances is the informal lease/loan arrangement between car owners and drivers, which influences the supply of cars and drivers signing up to use Uber's platform (Pasquali, Commenges, and Louail 2022). Although we do not have data on how many Uber drivers own their cars in Ghana, 10 of the 13 drivers we interviewed did not own their cars and instead accessed them through a lease/loan arrangement. Thus, although they may be formalized as Uber drivers in Uber's platforms, car owners and drivers see Uber's platform performance as an extension of their informal lease/loan arrangements, thus transposing their informal arrangement into Uber's formal platforms. Albert's comment is illustrative: You must get your car owner's money [usually 400 or 500 cedis weekly] and then get the maintenance money too. Assuming the whole week, you make sales [revenue] of 700 cedis. From that, you have to pay Uber 25%. You will be left with somewhere around 550 or 600. You take away your car maintenance, which will be more than 130 cedis. So, at the end of the day, you are just working all the time, but you get nothing. (Albert, male, driver-owner)
Adaptation
Some market actors respond to the (in)formalized platform performance by adapting their normative practices to the formalization and vice versa. For example, drivers and riders adapted differently to the formalization effects of the platform's matching affordances. At the time of fieldwork, Uber did not reveal the drop-off location or the ride price to the driver before the driver accepted a ride. This creates a platform–market tension for drivers because the platform's impersonal matching affordance is inconsistent with the informal norms that allow drivers to know these details before agreeing to a trip request. Some drivers adapt to this formal impersonalization by first accepting the ride request, then using the app's calling affordance to call customers to inquire about the trip details before committing to the ride. Razak explains why this is important: When I get a ride request, the first thing I do is call the person and just confirm the pick-up and drop-off location. If you just accept the trip and drive to the given pick-up location, you will get there, and the person will not be there. (Razak, male, driver)
Some riders have fully adapted to this formalization and the impersonality it brings, so they resist driver attempts at informal interactions before or during the ride. As we have shown, the infrastructural deficiencies sometimes render Uber's navigation affordances deficient, which discourages drivers from using it; they instead ask riders for directions, as seen in the opening vignette. Although this is a cultural norm, some riders who have fully adapted to the impersonality of the platform's formalized matching and navigation affordances resist such driver interactions. For example, Aku finds such driver requests annoying: The annoying ones are those who do not follow the map. … They [Uber] have given you directions. Just follow the directions and go, and you are coming to ask me, “Do I know the place?” (Aku, female, rider)
Like Razak's passenger in the opening vignette, Aku demands that drivers follow the platform's navigation, even when she knows the (better) route to the drop-off location, because she likes the reduced interaction the platform affords.
To deal with the tensions of (in)formalization stemming from the lease/loan arrangement and Uber's pricing affordances, RH drivers and car owners have adapted by adopting smaller cars—such as the Daewoo Matiz and Hyundai i10—that have smaller engine capacities and consume less fuel to reduce their operational costs, since they cannot control ride prices. David says, We use these small, small cars [emphasis in original] because of the fuel consumption: 1.0L engines, the one that I was using was 0.8L. So just imagine! The fuel consumption was very good for me. (David, male, driver)
With these “small, small” cars, drivers “can do many more trips than the typical taxi cars before you need to fill up [on fuel] again” (Ernest, male, driver). Car owners prefer these cars because they are “moderately priced, so it gives you a better return on investment” (Tetteh, male, car owner), and “you can maximize profit within the shortest possible time” (Asamoah, male, driver-owner).
In other countries, the makes and models of cars used for Uber are varied. In Ghana, however, the RH ecosystem is unmistakably defined by these “small, small” cars (see Web Appendix D). Owing to Uber's first-mover status, this market adaptation has been associated with their brand, and the small cars are popularly known as “Uber cars.” Uber's then–country manager for Ghana, Marjorie, admitted that the tensions between Uber's dictated low pricing and the operational costs drivers in this market face motivated this adaptation: Of course, we know how [this occurred]. We drove down the prices. It becomes an equation of earnings and costs to operate the vehicles. Prices that low, what kind of vehicle could make the earnings work? Simple math! I don't think these small Uber cars have had a positive impact on our brand. … We’ve created some distance between our global brand and how we live it locally.
Substitution
Another way some market actors respond to the platform's performance due to the tensions from (in)formalization is by temporarily or permanently replacing their use of the Uber platform with market substitutes. For example, some drivers (like David) temporarily substitute their usual dependence on Uber by offering offline trips to customers they have built a rapport with or to people in their neighborhood. Many of the RH drivers we interviewed use multiple platforms, switching between the platforms depending on which dictates a more favorable price or lower service fee.
For some drivers like John, who used to drive on the Uber platform, the platform's matching and pricing affordance, which removes drivers’ haggling capabilities along with the service fee they must pay to Uber, forced him to permanently switch to the taxi ecosystem. I did Uber for a while, and I changed back to a taxi. I realized Uber wasn't worth it because the car I was using had 2.4L engine capacity, so my car consumed a lot of fuel. And if you consider the amount Uber gives me for a ride, when I find my own passengers, I charge about 3 or 4 times more than Uber's price, and when Uber gives me that low pricing, I will have to pay 25% of the amount to Uber as well. They are ripping me off my sweat, just like that … no way. (John, male, taxi driver)
This same tension also manifests in riders’ negative experience of the platform's performance when the platform dictates higher prices during peak demand periods (price surges). In such instances, RH prices can be more expensive than taxis, and some riders find this infuriating, especially because they cannot haggle with the platform's pricing affordance as they could in the informal taxi ecosystem. When it's raining and you order an Uber, you will be shocked by the prices you will see. I do not know how the app's algorithm is structured. … I feel they are taking advantage of me. … Something that is probably 20 cedis, you go to Uber now, and it's raining, and it's 100 cedis. … So, we would rather go back to our trotro, go back to our buses, go back to our local taxis because we know that at least we will have bargaining power. … I do not pick Uber when there are surges. (Akosua, female, rider)
Surge pricing creates higher value for both drivers and Uber but imposes higher costs on riders, which forces riders like Akosua to temporarily switch to informal market substitutes, where she can exert some control through her “bargaining power.”
Resistance
Another way drivers respond is through overt resistance, such as demonstrations, which escalates tensions between the platform and these market actors. Mawuli (male, driver) says, “We’ve been staging a lot of protests against Uber and Bolt concerning their prices.” In a local news article, drivers who were demonstrating against the RH platforms referred to their condition as modern-day slavery, with one driver commenting: “We are demonstrating against the fares. The fare is very low. We gain nothing from this job. … We, the drivers, are just slaves” (Armah 2019). Although driver demonstrations in Ghana are infrequent due to the absence of strong unions, these acts of resistance manifest and escalate the tensions that occur when RH platforms’ affordances formalize pricing in a market where pricing for rides is informally negotiated.
Affordance-Based Regulation
In formally regulated taxi markets, regulators often set rules and guidelines on quality (entry and operational requirements such as vehicle and driver registration), quantity (number of cars allowed), and economics (pricing) (Aarhaug and Skollerud 2014). In Ghana, although there are some formal entry and operational quality regulations (e.g., vehicle painting, driver's license, and car insurance), these tend to be poorly enforced due to administrative inefficiencies (Poku-Boansi 2020). There is no formal body regulating this market, and there are no formal economic or quantity regulations.
Thus, when Uber entered Ghana, there was little formal regulation for the firm to disrupt (Kazeem 2016). It is in this context that we examine the interaction outcomes between Uber's platform's affordances and the regulatory voids in Ghana's RH and taxi market, and how that impacts the platform's performance. We find that the platform's affordances have had an unintended regulatory impact on the ecosystem due to the regulatory void—this is what we describe as affordance-based regulation. The impact on the platform's performance is that it has become the unofficial regulator of the ecosystem. Although this has led to positive assessments of the platform's performance by some market actors, it has also generated platform–market tensions.
Economic and quantity regulatory affordances
Uber's pricing affordance exploits the absence of economic regulations to dictate prices and service fees as the firm finds expedient. Thus, part of formalizing the market also involves this economic regulation of the ecosystem. The platform's registration affordances also allow it to exploit the absence of quantity regulations to regulate the number of cars and drivers who can enter the ecosystem. As is also the case in other developing markets, this increases supply and choice for riders and has some positive labor outcomes for drivers (Sundararajan 2017). In Ghana, Uber also provides investor car owners with opportunities to maximize investment returns from leasing/loaning cars to drivers, which is similar to India's informal taxidar system (Kashyap and Bhatia 2018). However, this could reduce drivers’ revenue due to increased competition among drivers (Schor 2021).
Entry and operational quality regulatory affordances
We also see a strong regulatory effect of the platforms’ affordances on existing formal entry and operational quality regulations that are poorly enforced in the market. For example, although formal regulations require all commercial drivers to hold an appropriate license and keep their vehicles in roadworthy condition, many drivers fail to comply (Boateng 2020). Uber's registration affordances, however, demand that drivers meet these requirements in order to use the platform. Uber has made a lot of drivers now take care of their cars. Because they know that Uber checks they’re roadworthy, safety checks, there is a first aid box in the car, fire extinguishers and all that. You did not have these things in the traditional [taxi] system. Dirty vehicles and all sorts of things, no, no. The regulators who are supposed to regulate the traditional system do not ensure such standards. The Uber system has brought world-class standards into a developing country, so in terms of transportation, the ride-hailing service has increased the standards of commercial transportation to any standards you will meet in developed countries. (Akosua, female, rider)
Data gathering, oversight, and sanctioning affordances
Besides setting rules and standards, formal regulation also involves gathering information, oversight monitoring, and sanctioning actors who do not comply with set standards and rules (Yeung 2018). Although the government lacks these regulatory capabilities, Uber's platform has these affordances. For example, Uber's platform has affordances that gather information about riders, drivers, cars, and the details of every transaction and ride, which is impossible to achieve in the offline taxi ecosystem. This allows the brand to have monitoring oversight of rides, which also gives law enforcement access to the necessary data to investigate crimes occurring during RH rides. Abraham, deputy director at the DVLA, explains: If you pick a taxi and there is a rape, where are you going to get the data from? Investigating such issues that happen in taxis will take months. … But if after your ride with Uber, Bolt, or Yango, you report a rape, we know exactly when you requested the service and with whom, and that information helps law enforcement take action.
Finally, these data-gathering and oversight regulatory affordances also allow Uber to sanction drivers who do not comply with operational standards. This affordance is nonexistent in Ghana's taxi ecosystem, in which drivers determine their service delivery standards and face no formal sanctions if they are rude to a customer they are unlikely to see again. Uber's postride review affordance encourages riders to report drivers who do not comply with operational standards, such as those who are rude or drive recklessly. Despite many positive assessments of the platform's performance as a regulator in this market (e.g., by riders and the government), it also manifests tensions with a market lacking an official regulator to determine and sanction driver deviance. Drivers complained that Uber's sanctions, compared with competitors’, are unfair and biased toward rider complaints, creating disaffection among drivers. Asamoah explains: The only problem I have is sometimes when a rider reports a driver for an offense or something, sometimes the Uber app just blocks the driver just because a rider just makes a report. They don't take their time to listen to the driver's side. I think with Yango and Bolt, they listen to the drivers, too. They take their time to know exactly what happened before they take action. Uber tries to please the riders more than the drivers. That's their problem. When that happens, most drivers leave Uber. (Asamoah, male, driver-owner)
Brand responsibilization
The government’s response to the platforms’ performance as the unofficial regulator of the market is to responsibilize the platforms to build even more regulatory affordances. Dan, the deputy director at the Ministry of Transportation, explains: We’ve engaged them to come up with some form of safety features on their app for customers and riders to guarantee their safety. One of the key things we discussed was the identification of the drivers and riders. As it is now, there is no verification system they use to register on the app, particularly for the riders. If I’m a rider, I can just use any ID, whether it's genuine or fake, I can just use it. … For the traditional taxis, these are individual drivers. There is absolutely no control over what they do. So, it's quite difficult to introduce some measures of this nature to them. If we are going to be held accountable, let us all be accountable … let us also pinpoint where the government also has to be accountable. I find it inadmissible for Ghana … where one driver can have five driver's licenses, different numbers, different names, even if they’re all legit. How am I supposed to be accountable for the system if we’re not all playing our roles, so it's a tough situation. … There are certainly dysfunctions in the ecosystem, yet we remain accountable for the last man's safety.
Subversion
A more extreme reaction to the tensions stemming from Uber's sanctioning affordance as the unofficial regulator is the use of subversive tactics by some drivers to diminish Uber's brand, escalating tensions. Albert told us about a plot by some drivers to sabotage Uber's brand in retaliation for their harsher sanctions: To tell you the truth, there is an agenda by us drivers to sabotage Uber and then destroy the Uber company in Ghana for them to go. … Some of the drivers, when you make a request and it's Uber, and they come and pick you up, they act rude to you, the rider. It's a planned thing. It's an agenda to spoil the Uber [brand]. Because if you are a rider and I pick you up on an Uber trip and I act rude to you, next time, I am not sure you will want to use Uber again. That's the whole agenda, and we have succeeded. Some of the riders have moved from Uber. … Sometimes, too, we will recommend the other apps, and tell a rider, Oh, this one is better, try it. (Albert, male, driver-owner)
Discussion
This research examines how a global RH platform's performance is shaped by the interaction between its platform affordances and the infrastructural deficiencies, informality, and regulatory voids that characterize a developing market. We explain three types of interaction outcomes that impact the platform's performance and how they manifest platform–market tensions. We also explain how various market actors respond to the resulting platform performance. Our findings from a Ghanaian context provide an exemplary lens for understanding how global RH platform performance can shape and be shaped by the particular characteristics of other African and developing markets with similar characteristics. These insights thus enable us to provide several theoretical contributions and relevant managerial recommendations. We also discuss practical implications for other relevant market actors.
Theoretical Contributions
Our findings contribute to the SE literature by unpacking specific platform–market tensions that ensue when a global RH platform's affordances interact with developing market characteristics. We show that these tensions affect platform performance and emanate from (1) infrastructural deficiencies that render platform performance undesirable, (2) platform performance that transforms informal exchange norms, and (3) the platform acting like an unofficial market regulator with oversight and sanction capabilities. We explain seven different responses by various market actors to the resulting platform performance and how these responses may (temporarily) resolve tensions (e.g., acceptance and avoidance) or escalate them (e.g., resistance and subversion).
Our findings also show how market actors’ adaptation response may lead them to develop new affordances from existing platform features (e.g., using the app's calling feature to investigate and cancel card-based trips) and to create new market characteristics (e.g., driver mass adoption of “small, small” cars). Together, these insights extend prior research by showing how the performance of archetypal sharing platforms (Eckhardt et al. 2019) shapes and is shaped by developing markets they enter when their affordances interact with the infrastructural deficiencies, informality, and regulatory voids that characterize these markets.
While our research brings more nuance to prior research by paying attention to platform affordances, we also introduce three new insights that extend the SE literature. First, contrary to suggestions that physical infrastructure only plays a secondary role to digital infrastructure in platform success (Chen and Wang 2019; Parente, Geleilate, and Rong 2018), our research shows that not only are both equally important, but poor physical infrastructure can actually shape how consumers experience the digital infrastructure (e.g., bad roads make drivers and riders distrust Uber's navigation affordance even if there is sufficient digital infrastructure to make it work). Second, in addition to research findings that informality shapes platform adoption (Hira 2017; Pasquali, Commenges, and Louail 2022), we show that platforms also lead to the increased formalization of the informal market, and the informal market introduces informality into the formal affordances of the platform. Third, our theorization of affordance-based regulation shows that sharing platforms’ affordances can have a regulatory effect on informal markets with regulatory voids, which has not previously been shown in the literature.
Additionally, our research responds to recent calls to extend marketing research insight to understudied consumers and contexts (Eckhardt and Kopalle 2025; Uduehi, Saint Clair, and Crabbe 2025) by examining what happens when a global RH platform operates in an African market. The insights from this research show the theoretical value and contextualized boundary conditions that marketing scholarship stands to benefit from, including research that examines the globalizing effects of sharing platforms in a non-Western and developing market.
Finally, our research contributes to affordance theory in marketing by going beyond prior theorization on the affordances of store environments, physical and digital objects, and product features (Borghini, Sherry, and Joy 2021; Pavlyuchenko and Dion 2025). We examine the influence of developing market characteristics and market actors and how they shape and are shaped by platform affordances. We extend Mardon, Denegri-Knott, and Molesworth's (2023) theorization of affordance misalignment in (micro) consumer-object relationships by theorizing the macro-meso misalignments in platform–market tensions, which affect consumers, the brand, and the market. We also extend Davis and Chouinard's (2016) typology of affordance mechanisms by introducing dictate as a new affordance mechanism.
Managerial Implications and Recommendations
Our findings offer important lessons for RH platforms on how they can succeed in developing (and other) markets characterized by infrastructural deficiencies, informality, and regulatory voids. Here, we discuss key managerial implications and offer recommendations to managers of RH platforms—a market expected to reach over US$212 billion by 2029, with developing markets offering the best growth opportunities (Statista 2024). These insights will not apply to all RH platforms entering any developing market, but they are relevant for many. Thus, we identify specific market characteristics a manager can look out for when entering or operating in a developing market, especially in Africa, to determine how the findings may apply to them. We also explain when these implications and recommendations may be salient for other sharing platforms (e.g., Airbnb) that have archetypal SE characteristics (e.g., access-oriented, crowdsourced supply, enhanced customer role, and reliance on reputation system) (Eckhardt et al. 2019) as well as for relevant nonsharing platforms (e.g., Amazon). These implications and recommendations are summarized in Table 4.
Practical and Managerial Implications and Recommendations.
Managing platform infrastructural deficiencies
A key lesson for RH managers is that infrastructural deficiencies can cause their platforms’ affordances not to work as intended, which compromises the platform's performance. While this outcome may not apply to all RH platforms and all infrastructural deficiencies (e.g., electricity is less salient here), our findings show that it is important for managers of RH platforms that rely on road and internet quality (for real-time matching, pricing, and oversight affordance) to investigate how poor road and internet quality may affect their platform's performance. This may be more salient for RH platform managers entering developing countries in sub-Saharan Africa (e.g., Mali and Burkina Faso, where Uber does not operate yet), where the road quality score is below 3.5 and internet quality is poor (Daramola and Etim 2022) but less salient in emerging markets with better urban infrastructure, such as China and South Africa (Hira 2017). It is noteworthy, though, that the same problems impact rural locations in some developed countries, such as Australia (Park 2017). Thus, although RH platforms tend to operate in urban locations, managers can consider these platform-infrastructural deficiencies as they expand into rural areas, even in developed countries.
For RH platforms entering developing markets, prior research has recommended investing in relevant physical and digital infrastructure in collaboration with governments, where possible, and developing offline capabilities (Parente, Geleilate, and Rong 2018; Retamal and Dominish 2017). These recommendations are useful but can be difficult to implement since, for example, infrastructural development can be expensive and out of scope, and developing country governments may have different priorities. While offline capabilities may work for some affordances (e.g., navigation), they may not work for others (e.g., pricing) that require real-time internet data for optimal performance.
Instead, we recommend that RH platforms adapt to infrastructural weaknesses and strengths. For example, they can factor road quality into their pricing affordances, using geolocation data to segment routes based on road quality and charge higher prices for trips where the route may be faster but has many bad roads. These can become pricing category options for customers to choose from. They can also leverage local infrastructural strengths that are not a platform affordance. For example, they can address the avoidance of card-based transactions by adopting mobile money payments, which are popular in many developing countries with large unbanked populations (e.g., MoMo in Ghana, M-Pesa in Kenya, and bKash in Bangladesh) (Hira 2017). This may not work in countries like Nigeria and Indonesia, which do not have these capabilities but may have other infrastructural strengths. This recommendation is salient for other SE platforms, such as food delivery (e.g., DoorDash) and courier services (e.g., DHL), whose platform affordances provide real-time navigation and pricing based on route distance and time, which can be affected by road and internet quality.
Managing (in)formalization
RH platforms can transform relevant cultural norms, and platform performance can be affected by cultural norms. This outcome of (in)formalization is most salient when entering markets that have entrenched informal exchange and cultural norms that guide pricing, matching, and service supply. The taxi and RH markets in many countries in sub-Saharan Africa (e.g., Mozambique and Uganda), South Asia (e.g., India and Indonesia), and Latin America (e.g., Peru) have this informality (Durant et al. 2023; Hira 2017; Kashyap and Bhatia 2018). When RH managers enter such markets, they can monitor how their platform's affordances transform the informal market norms and manage the resulting tensions.
Some research suggests that RH managers should adopt existing matching and pricing norms, such as haggling (Chen and Wang 2019; Pasquali, Commenges, and Louail 2022). However, our research suggests that riders tend to prefer the formalized platform matching and pricing. Instead, we recommend that RH managers develop strategies that support better revenue outcomes for drivers and consider their costs of (in)formal asset amortization in pricing affordances. As we saw in Ghana, the platform performance becomes an extension of the informal lease/loan arrangements, which affects how drivers perceive Uber's pricing affordances. For example, RH platforms can cap service fees at certain revenue points to enable drivers to meet their other operational costs, like paying for car lease/loan costs. Although developed markets without such informality will not face the same implications, the recommendations can be applicable in these markets, like the United States, where many RH drivers buy their cars with loans and make monthly loan repayments with interest (Buchak 2024).
These recommendations can apply to other sharing platforms whose operation may lead to (in)formalization. For example, sharing platforms with matching affordances that connect people to freelance labor, like Taskrabbit, may encounter similar experiences in developing markets where people typically use informal networks and norms to find and price services for handymen and tradespeople. These recommendations also apply to managers of non-SE platforms that connect heterogeneous sellers and buyers, such as Amazon, when they enter developing markets with several informal, heterogeneous, and closed-loop seller–buyer relationships guided by relational trust. Examples of such markets include the dairy market in Kenya (Blackmore et al. 2022) and retail in rural India (Viswanathan, Rosa, and Ruth 2010). Entering these markets can lead to (in)formalization, but the algorithms behind global platforms are often not sensitive to these informal structures and norms; managers may need to retool the platform accordingly as they enter these markets.
Managing affordance-based regulation
A final key managerial implication from our findings is that RH platforms can unintentionally play the role of regulator in developing markets with regulatory voids. We do not expect affordance-based regulation to be automatic when RH platforms enter markets with some regulatory voids, such as South Africa, which has a quasi-regulated taxi market (Daramola and Etim 2022). However, we expect it to be consequential when they enter markets where the RH platform affordance can enforce standards that are higher than any existing formal regulations or informal norms, as was the case in Nigeria and Tanzania (Barbour and Luiz 2019; Daramola and Etim 2022), and where the affordances enable the firm to sanction noncompliance more effectively than incumbents and formal regulators.
Although major SE brands such as Uber and Airbnb are known to resist or avoid formal regulations (Schor 2021), our key recommendation is that RH managers whose platforms have such affordance-based regulation in these markets embrace and even lead on issues of formal regulation. Taking this approach would help establish standard regulatory benchmarks, eliminating uneven regulatory enforcement that can create competitive disadvantages, since competing sharing platforms operate under the same standards (e.g., requiring all drivers to have comprehensive car insurance).
Our advice also applies to other sharing platforms, such as peer-to-peer, short-term rental sharing platforms that set and enforce standards on identification, safety, and cleanliness, like Airbnb. The short-term rental market in many developing markets has significant regulatory voids (Schor 2021), and Airbnb's platform affordances may have similar regulatory effects on certain markets by setting and enforcing high service standards that nonplatform incumbents lack. Thus, these relevant sharing platforms can benefit from leading conversations on affordance-based regulation with governments, which can help build more trust and legitimacy with customers in markets with regulatory voids (Uzunca, Rigtering, and Ozcan 2018). These recommendations also apply to nonsharing platforms with similar affordance-based regulation, such as professional services platforms like Zocdoc (a platform for finding and rating physicians and dentists) that set, monitor, and enforce standards such as proof of qualification, practice quality, and insurance.
Implications for Nonfirm Market Actors
The findings have implications for the main nonfirm market actors—riders (consumers), drivers (service providers), and governments (formal regulators)—in similar developing markets. For riders, platform infrastructural deficiencies directly affect their service experience. Regardless, it may be more optimal for them to accept compromised platform performance than resort to avoidance because the benefits outweigh the limitations. These deficiencies may improve with development, and the alternative nonplatform incumbents are often no better. Riders benefit the most from the formalization of the market as the platform's pricing and matching affordances have resulted in fairer, smoother, and cheaper service and protection from driver moral hazards. Switching between platform firms and taxis to take advantage of lower fares can be beneficial, but taxis do not offer the brand trust benefits that platform brands provide. Affordance-based regulation also provides riders with a safer and better customer experience and guarantees of recovery if things go wrong. For this reason, they stand to benefit from choosing platforms with higher standards and enforcement.
For drivers, negotiating platform-infrastructural deficiencies, such as explaining reasons for not following navigation to the rider, can be more optimal than avoidance. (In)formalization is a double-edged sword for drivers. It has introduced smoother, more efficient matching and pricing but has also made drivers’ work precarious due to low, dictated prices. Affordance-based regulation has similar mixed outcomes for drivers: It has increased driver service costs and firm surveillance and control. However, it has also made drivers more professional and accountable, which influences rider satisfaction and demand. Our findings suggest that while resistance and subversion only escalate related tensions without resolution, a mix of resource adaptation and platform substitution (temporarily switching between offline and sharing competitors) can be effective in managing these tensions.
For formal regulators at national, regional, and local levels of government, improving digital and physical infrastructure is critical to addressing platform infrastructural deficiencies, not just for RH platform firms but for many others that depend on such infrastructure. Research suggests that developing country governments can allow platforms to self-regulate, adopt coregulation with platforms, or appropriate the resources of platforms to build their own regulatory capabilities (Hira and Reilly 2017; Kozlenkova et al. 2021; Retamal and Dominish 2017). Learning from how the government in Ghana is responsibilizing firms to undertake more affordance-based regulation, we recommend that governments can regulate informal markets indirectly through platforms. Through this approach, governments can encourage firms to embrace their regulatory role. They can more easily impose penalties for noncompliance on platforms and exact appropriate taxes, which can be invested in improving infrastructure. Governments can also indirectly use the platforms’ regulatory affordances to address persistent and emerging market problems, such as regulating pricing and the number of RH cars operating in the market. They can mandate taxis to enroll on platforms and compel platforms to train them over a period, as was done in the Ivory Coast. This is more achievable than recommendations for taxis to develop apps (Mohammed 2015), which may be more difficult in an informal market with heterogeneous taxi drivers. To reduce tensions from the burden of responsibilization, governments can take responsibility to provide the necessary frameworks (e.g., unique IDs) and policies that platforms can rely on to deliver such affordance-based regulation.
Conclusion and Directions for Future Research
Most of the marketing literature's understanding of RH and SE platforms is informed by research on developed markets (Eckhardt et al. 2019), despite the significant growth of sharing platforms in developing markets (Statista 2024). Our research thus provides an empirical response to calls for an ecosystem analysis of the operations of sharing platforms in developing markets (Parente, Geleilate, and Rong 2018). However, we focus here on RH platforms, and although our context shares similarities with many other developing markets, these ecosystems differ, as do different SE platforms and their affordances. Thus, we add to the call for further research into the operations and affordances of different sharing platforms in other developing market ecosystems with varying infrastructural capabilities, (in)formality, and regulatory intensity.
Supplemental Material
sj-pdf-1-jmx-10.1177_00222429261452137 - Supplemental material for Global Ride-Hailing Platform Affordances and Developing Market Characteristics
Supplemental material, sj-pdf-1-jmx-10.1177_00222429261452137 for Global Ride-Hailing Platform Affordances and Developing Market Characteristics by Samuelson Appau, Giana M. Eckhardt and Kingsley Tetteh Baako in Journal of Marketing
Footnotes
Acknowledgments
The authors would like to thank Daiane Scaraboto, Marian Makkar, Sefa Awaworyi Churchill, and Matthew Mabefam for providing helpful comments on an earlier draft of the article.
Author Contributions
Giana M. Eckhardt passed away after this article was accepted, during the publication process. Giana’s contribution to this project and our academic community are irreplaceable. This article is dedicated to the memory of Giana, and her generosity, warmth, and efficient intelligence.
Funding
The authors received no financial support for the research, authorship, and/or publication of this article.
Declaration of Conflicting Interests
The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Data Availability
Supplemental Material
Supplemental material for this article is available online.
Author Biographies
Samuelson Appau is Associate Professor of Marketing, Melbourne Business School, University of Melbourne, Australia (email: s.appau@mbs.edu). Giana M. Eckhardt was Professor of Marketing, King’s Business School, King’s College London, UK. Kingsley Tetteh Baako is Senior Lecturer, School of Property, Construction and Project Management, RMIT University, Australia (email: kingsley.baako@rmit.edu.au).
References
Supplementary Material
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
