Abstract English

This thesis provides an introduction to the design of two-sided digital platforms, especially of their worker-friendly, cooperative alternatives. Secondly, it offers background on the mobility market of Nairobi, Kenya, which is controlled by both cooperatives and international platforms. Building on that, I will share my experience and results of designing, prototyping and validating a niche „Platform Cooperative“ for personal drivers in Nairobi. The process is based on the „Lean Startup“ concept of Eric Ries, as well as user-centered design methods.

Introduction

Over the last decade, digital platforms have disrupted various industries through highly-efficient match-making and the increased productivity of existing assets (Evans, Garner 2016). However, dominating venture-capital funded platforms such as Uber and Airbnb have been facing ongoing regulatory challenges, growing competition and criticism for the socioeconomic effects they leverage for their investors‘ long-term interests.

Recognizing – but challenging – the success and impact of digital platforms, the “Platform Cooperativism Movement” has been promoting democratically controlled, member-owned digital businesses (Platform Cooperativism Consortium). Platform Cooperatives create worker-friendly ecosystems and ensure that the collaboratively created value of the platform is distributed or utilized in favor of the members.

Cooperative organizations have been a long-standing concept and exist in many parts of the world. In Kenya, where cooperatives traditionally play an important economic and societal role, many sectors are dominated or entangled with cooperatives (Otieno 2019). In the public transport sector, individual bus operators are required to be a member of a cooperative (Project 2015). The collected membership fees are then used within the local communities to provide basic social security and emergency loans for members, while surpluses are, for example, invested in the development of rental houses (Schneider, 2018).

The Kenyan urban market of individual mobility (e.g. Taxi), on the other hand, is controlled by the international platforms Uber and the Estonian competitor Bolt. These companies invest significant amounts of capital in Kenya, for example, to regularly subsidize rides. Although these measures lead to a growth of the ride-hailing industry in general, the customers‘ awareness of the value of provided services by the drivers is shrinking with the descending prices. On the other hand, drivers are required to work long shifts to pay off the car while trying to generate a sufficient income (Tanui 2019).

The first section of this thesis will provide an overview of the underlying principles and examples of (cooperative) digital platforms, as well as of the urban mobility landscape of the Kenyan capital Nairobi. Building on that, I will share my process and learnings of designing a cooperative mobility platform in Nairobi myself. By applying methods of user-centered design and Eric Ries‘ “Lean startup” approach (Ries 2011), I experimented in an iterative process, how design can contribute to the development of economically fair platform models in a highly competitive market environment such as Nairobi.

Digital platforms

“At the most general level, platforms are digital infrastructures that enable two or more groups to interact.” (Srnicek 2017)

Over the last decade, digital platform businesses have disrupted several industries through the digitalization of products, services, and business processes. This, in turn, has enabled highly-efficient matching of supply and demand and increased productivity and utilization of resources and assets (Evans & Gawer 2016).

According to a review of Kankanhalli, Faik, et. al. in 2018, available literature separates digital platforms in “technical” platforms for software development and production, and “non-technical” platforms for transactions between B2B & B2C, whereas the latter are subject to this thesis. Nevertheless, these “non-technical” platforms use digital technology, as they capture, transmit and monetize data, including personal data, over the Internet (Evans & Gawer 2016).

Inherent to the success of platforms is the effect of “network effects” since they “make a platform attractive by creating self-reinforcing feedback loops that grow the user base”. In a two-sided platform, where consumers and producers interact, a higher value creation by producers on the platform attracts more consumers, who, in turn, attract more producers and further value creation.” (Parker et. al. 2016).

Digital ride-hailing platforms connect passengers with nearby (taxi) drivers using a mobile app. They usually handle and harmonize pricing, payments, and safety. For many people, this has become a favorable alternative to conventional taxis due to advantages such as lower prices, convenient orders, integrated location services and reduced risk of fraud. Drivers, on the other hand, can join the taxi business without licenses or commitment to gatekeepers (Jalloh 2019).

Besides the benefits, ride-hailing platforms such as Uber have been facing various challenges. Most prominent are operation bans due to local regulatory conflicts with the taxi industry in many parts of the world (Dickinson 2018) and claims that the underlying “gig economy” philosophy is “unfair to on-demand workers” (Tansey 2015).

Platform Cooperative Movement

Platform cooperatives are digital platforms implemented and governed by a cooperative, which is, as per definition of the International Co-operative Association (ICA), “an autonomous association of persons united voluntarily to meet their common economic, social, and cultural needs and aspirations through a jointly-owned and democratically-controlled enterprise.” The most important underlying value framework for cooperatives was first set by the Rochdale Pioneers in 1844 and later revised by the ICA as follows (Schneider, p.22):

1. Voluntary and open membership
2. Democratic member control
3. Member economic participation
4. Autonomy and independence
5. Education, training, and information
6. Cooperation among cooperatives
7. Concern for community

Compared to cooperatives, privately-owned companies are not necessarily inferior: “Generally, the evidence indicates that worker cooperatives have higher productivity than conventional companies although this difference may be modest in size” (Doucouliagos 1995). Furthermore, they do “not differ in innovation or management capabilities from a conventional firm” (Basterretxea, Martínez 2012). In difficult economic periods, they are especially more likely to survive than traditional companies, which could be due to their workers (and hence owners) personal commitment and “willingness … to make adjustments [that] allow the firm to survive (Park et. al. 2004).

However, the movement is also facing skepticism: “Some have argued that we might fight these monopolistic trends by building up cooperative platforms. Yet all the traditional problems of [cooperatives] (e.g. the necessity of self-exploitation under capitalist social relations) are made even worse by the monopolistic nature of platforms, the dominance of network effects, and the vast resources behind these companies. Even if all its software were made open-source, a platform like Facebook would still have the weight of its existing data, network effects, and financial resources to fight off any coop rival.” (Srnicek 2017)

Design of Platform Cooperatives

Over the last few years, various worker-owned digital platforms have emerged. The platform “Up & Go” is a co-operative platform for house cleaning services in New York City. The cleaners are “trained professionals” and were already organized in existing, worker-run cooperatives, which facilitated the success of the “federal” platform cooperative.

Existing platform cooperatives have also experimented with approaches that differentiate them from for-profit platforms that are often driven by internal competition and rating systems. Hence the customers of “Up & Go” rate the their overall experience rather than individual member‘s performance, which would create a competitive environment within the organization (Thompson, 2019).

The design of the business model and user interfaces of “Up & Go” was done by the agency Colab – which is a cooperative itself. To gain practical insights on the design of platform cooperatives, I interviewed their member and strategist Ethan Winn, who talked me through the design process. According to him, “Up & Go was initially not a user-centered project”. Therefore, they conducted user interviews and a co-design workshop with customers, which allowed collaborative wireframing and rapid prototyping. Furthermore, they conducted working sessions with the workers of “Up & Go”, which led to the key learning that workers did not want to compete with each other, but instead value a supportive, collaborative environment. Winn said it was this kind of “the small decisions” that created the platform‘s unique integrity at large.

Cooperatives and mobility in Kenya

The first cooperative in Kenya was registered in 1908 by white settlers to develop and market their agricultural crops. Today, cooperatives are accountable for more than 50% of the country‘s GDP and “63 percent of the population derives a livelihood from them”.

The smallest type of cooperatives in Kenya are “Chamas”, which are groups of mostly females that collectively save money and distribute it equally over several months, or provide additional loans to trustworthy members who have unexpected needs for capital, for example, to pay their children‘s school fees. Some Chamas have grown into large, formalized organizations, and transformed into SACCOs (Savings and Credit Cooperatives Societies). For many Kenyans, membership in a SACCO “is their social-safety net, enabling them to cover medical expenses if they get ill and burial expenses when they die”. Therefore, SACCOs and cooperation as such, are considered rather as “a matter of necessity more than choice” (Schneider 2018).

Matatus in Nairobi

Means of public and private transport

Kenya‘s public transport is provided by “Matatus”, which are privately owned buses ranging from small vans to large buses. Every “Matatu” operator has to be organized in a company or become member of a SACCO (Project 2015). The collected money from the subscription to these companies and SACCOs is then used to support the operators, while surpluses are invested into additional wealth creation for the community such as real estate investments.

Apart from the public transport, Kenyans can opt to use “Boda boda” (motorcycle taxis), “Tuk Tuks”, metered Taxis or ride-hailing platforms for individual transport. The Kenyan government has been pushing for a similar organization as in the public transport sector: “Being members of SACCOs will help bring sanity as officials will know their members and punish errant members”, said Transport Principal Secretary, Paul Maringa (Business Daily).

International ride-hailing platforms

The biggest ride-hailing platforms in Kenya are Uber, Bolt and Little Cab, which dominate a market of around $30 million according to Statista. On each ride, Uber charges a commission of 25%, while Bolt and Little operate at 15% (Tanui 2019).

In the past, there have been numerous strikes of digital taxi drivers over high commission rates (Njanja 2019). These strikes have in fact changed the working conditions for drivers. For example, Uber implemented a reduction of the commission fee from 25 to 3%, if drivers complete the first 20 rides of a week already on Monday (based on driver statements). As strikes have an important role in Kenyan society, companies are aware of the potential physical risk of going too far. In the past, the founders of the former Dubai-funded competitor “Mondo ride” have left the country “after realizing that allied drivers had formed a WhatsApp cartel and prepared to storm their offices” due to outstanding payments (Wee 2019).

Local ride-hailing platforms

The fruitful startup scene of Kenya has given rise to various ride-hailing competitors. The most famous one is Little Cab, which is backed by the leading network provider Safaricom. Current news reports also mention MaraMoja among the active players. “Bebebeba” has previously started as a Kenyan ride-hailing platform developed by the Drivers and Partners Association of Kenya (DPAK) (Wambui 2018). Their app, however, is not functional anymore, as several other users reported to be not able to sign up. Another interesting project is “Nisa Taxi”, which is a platform that works with female drivers and is only available for women over safety concerns, given that more than 60 % of ride-hailing customers are female, while almost all drivers are male.

Case Study: Design of a cooperative mobility platform for Nairobi

The underlying hypothesis for this project is that cooperative platform models can compete with large-scale, highly capitalized digital platforms if they focus on niche customer segments, premium services and unique – or “cooperative” – user experience. Other than trying to imitate the competition, I‘m convinced that platform cooperatives should find unique pathways of doing and designing digital businesses.

As I was based in Nairobi throughout this project, I had the opportunity to research, interview, prototype and validate in a complex but inspiring environment. Being a regular customer of ride-hailing services such as Uber myself, I identified a high potential for social innovation. Also, as the ride-hailing market is fairly established, it allows me to focus on the actual differences of cooperative services and investor-driven platforms, without having to establish a generally viable scenario for a two-sided platform in the first place.

During my research on existing other ride-hailing startups in Kenya (see “Local ride-hailing platforms”), I was surprised about the reliability of local competitor‘s apps, as most of them had major bugs that prevented me from signing up and even test the service. Developing and maintaining digital infrastructure and especially apps in ever-changing mobile ecosystems comes at a high cost. Hence it is important to establish a product-market-fit and long-term strategy first, before venturing into the development (McCann, Yazici 2018) With regards to the digital infrastructure and user interface, my secondary research question was on how cooperative platforms can utilize either existing open source technologies or other platforms to prototype or even operate their service to a certain extent.

Methodology

Fundamental to the development and design of this project is the “Lean Startup” method of Eric Ries. Instead of working on complex projects that contain a lot of assumptions, it encourages entrepreneurs to establish a vision and approach it, while changing the strategy – or “to pivot” –  whenever it is required. Since products are constantly evolving during the “process of optimization”, setbacks should be proactively used to learn where to go next. In practice, the method suggests using a “Build-measure-learn feedback loop”, which is an iterative, learning-based design process. Startups should quickly conduct experiments that allow them to validate or invalidate their assumptions as fast as possible and with the minimum resources possible. Throughout this process, the product evolves to one or several Minimum Viable Products (MVP) until the product-market-fit is achieved and the startup is ready to scale. (Ries 2011)

The hypothesis and prototypes I created throughout the “Lean Process” were also subject to user-centered design methods, namely qualitative user interviews, usability testing, and rapid prototyping. Furthermore, I structured the project in consecutive “sprints” similar to the method of Knapp, Zeratsky, & Kowitz (2016). This allowed me to systematically monitor my learnings and decide on the next experiments or product decisions in an informed and data-driven manner.

Sprint 1: Understanding the driver's perspective

Various conversations with Uber drivers on the platform‘s business model, working conditions and typical earnings provided me with general insights on how ride-hailing platforms work from a driver‘s perspective. Also, I joined multiple Facebook groups related to the “Uber business” in Kenya and analyzed the topics and overall sentiment of posts and comments posted by drivers in the group. Most general posts were criticizing the pricing model of Uber, stating that it would calculate different prices for similar rides; others were complaining about the high commission rates Uber was earning from the ride‘s fare.

With regards to my vision of a driver-friendly platform, I decided to spin my first experiment directly around the drivers. For my initial hypothesis on how to make the driver‘s life easier, I was inspired by the daily membership fee of around 100 Kenyan shillings, that some Kenyan “Boda boda” drivers (motorcycle taxi) contribute to a Sacco on daily basis. This led me to the idea to take out the transaction-based platform commission and charge the driver a fixed daily usage fee. While the amount and payment frequency was surely random at this point, I was curious how a platform business model with revenue streams other than commission fees would be perceived by the driver community.

Hypothesis

Uber drivers in Nairobi are interested to sign up for a new platform that allows them to earn the full fare of their rides but comes at a fixed daily membership fee.

Experiment

Post an advertisement on the “Uber Drivers and Partners Kenya” Facebook group (102,276 members) and measure the sign-ups, comments, and engagement with a post promoting a commission-free but membership-based business model. Interested drivers could follow a sign-up link and provide their contact detail to receive a notification once it is available.

Results

15 people clicked the link, two drivers have signed up. One person commented that the post promoted “another armless thug” - referring to the reputation of existing platforms. A second commentator was reminded of the driver-founded platform “BebaBeba”.

Learning

Since the number of sign-ups generated from this post was fairly low, I concluded that the proposed conditions were an insufficient trigger to engage a considerable amount of drivers in the first place. To identify further approaches to tweak the prevalent business model of Uber and Bolt to become more driver-friendly, I dedicated my next sprint on the passenger‘s consumer perspective and gather insights for additional starting points.

Sprint 2: Experiments with Open Source Solutions

From a European perspective, the prices of Uber in Kenya are generally fairly low. For example, a 30 km ride with a distance of 11.49 km costs KES 500, which equivalents around 4.43 Euro. According to the Uber app, a similar trip in Berlin would cost around 30 Euro. In the example of Kenya, Uber deducts 25% of the KES 500, which gives 375 for the driver. Many Uber drivers have to pay KES 1,000 - 1,500 per day for the car, as they are usually not the owners. Based on my conversations with drivers, 12 rides per day at an average price of KES 500 are usual. Daily fuel costs are approximately 1,500 Euro KES (120 km). After deducting all of the driver‘s operational costs from an average daily revenue, the income of a usually 10-hour work shift is KES 1,500 (13.30 Euro). Without the commission of Uber, the daily income would be doubled to KES 3,000 (26.6 Euro). This sounds little too, but drivers who can earn this amount over a month, officially belong to the Kenyan middle class (Ndekei 2016).

But how can a low-commission or even commission-free ride-hailing platform work? When the monetary contribution to the platform per transaction is marginal or replaced by a fixed fee fee, how can a cooperative organization sustain itself? One approach would be to reduce the operational and initial investment costs to a minimum. For a digital platform, this could be done through open source technology or existing systems. A solution that combines both is “LibreTaxi”, a freely available ride-hailing platform that can be installed on any server. Instead of using a mobile app or web interface, both passengers and drivers interact with the platform through a chatbot connected to the messaging platform Telegram.

Hypothesis
Using the open-source software “LibreTaxi”, the implementation and operation of a ride-hailing platform could become so inexpensive that the commission fee could be dropped.

Experiment
I set up “LibreTaxi” and branded it as “Drivas Nairobi”. I assumed that the lack of network-effects (high availability of drivers and passengers) during the startup phase and the arguably less convenient chat-based interface could be compensated with lower prices for the passenger. My underlying vision was that this could become a less regulated, liberalized “open platform”. Payments between the passenger and driver would be done in cash, or via the popular mobile payment system M-Pesa. While this might not attract all costumers segments, I focused on a young and price-sensitive customer segment, which might comfortable to interact with a chatbot interface.

Results
A user test with Kenyans in their early twenties showed that the system fulfills the basic requirements of a ride-hailing platform. However, the target group noted unfavorable aspects in the conversational user flow, which would require additional adjustments. Although this could be improved through design and iteration, I realized a fundamental flaw in my initial hypothesis: Currently, customers can choose between several, extremely reliable and seamless ride-hailing hailing applications – at low fares. If the costs would be even lower, the original problem of insufficient driver payment would not be solved. Therefore I concluded that the specific outlined model needs to be fundamentally realigned.

Learning
Recognizing that my initial model effectively failed in differentiating itself from existing platforms with regards to driver-friendliness, I decided to rethink the general pricing model. Furthermore, I decided to stick at least to a chat-based approach of the platform for the next sprint, as it would allow me to directly interact with interested users while figuring out actual user needs and a viable business model.

Sprint 3: Design and validation of a 'social-ready' business model

From my other occupation in Nairobi, I knew Johnathan. He owns a “Toyota Belta” and works as a personal driver in Nairobi. Instead of Uber, his customers are business people and companies. While a typical ride-hailing driver aims to pick up and drop off passengers as quickly as possible to maximize productivity, Johnathan has personal relationships with his clients, brings them anywhere, waits for them during meetings or takes care of errands. Compared to an Uber driver, his work is less productive, as he can‘t accept more rides during the waiting periods.

However, he receives a higher payment for his work at the bottom line, as the customers also compensate for his waiting periods due to the flexibility and convenience it provides them with. On the other hand, although Uber drivers are quickly matched with a new customer during peak times, they don‘t receive compensation for their idle time throughout less busy periods of the day.

Hypothesis

A pricing model that is based on hourly rates would provide customers in an upper-middle-class segment with more flexibility, as it would allow them – at least for some trips – to have the driver waiting for them, do errands or choose a preferred route. I envisioned that this could democratize “personal driving experience”. On the other hand, the passenger would pay at least for a full hour, which ensures the driver is paid for longer periods of a working day. Additionally, the unpredictable travel times of Nairobi‘s rush hours would be addressed with a fairer pricing model.

Experiment

I designed a corporate identity and landing page for a personal driver service named “Drivas” and came up with a pricing model that was comprised of a hourly rate at KES 650 (5.78 Euro) and a daily rate at KES 3,000 (26.68 Euro), as well as a full day rate for personal drivers. I selected a stock photo that aimed to address a middle-aged urban middle class between 25-45. To generated traffic of potential local users for the website, I published an advertisement on Facebook. The posting promoted a service that allows users to “get a personal driver whenever they want” and a link to the landing page website. To sign up for the service, users could click a button of the website that opens a new WhatsApp chat with “Drivas”. For this purpose, I set up a WhatsApp business account, which enables additional features for commercial communication. Using Google Analytics for the website and Facebook‘s Analytics, I was able to track the performance of the campaign.

Results

Over a period of four days, the advertisement reached 18,776 people at a cost of 15.99 Euro. 291 users clicked on the advertisement. However, only around 10 people followed the signup procedure. Of those people, nobody has ordered a ride or requested more information, neither did they after my attempts of reengagement. However, some asked if they can join the platform as drivers.

Learning

The advertisement and landing page has not reached an audience that was interested in more personal ride-hailing services. I assert this might be both due to the broad target group of the Facebook campaign, as well as the assumption-based landing page that was mostly “vision-driven” and lacked sufficient insights from user research in the first place.

Sprint 4: Approaching 'product-market-fit' with personal driving for businesses

As I did not manage to gain considerable user traction with my previous attempt to offer personal driving services to a consumer target group, I decided to analyze the segment and needs of business customers in more detail, as this is the main source of work for personal drivers such as Jonathan. Hence I approached several business people in an upscale co-working space in Nairobi and conducted qualitative interviews. Three of them were foreign expatriates based in Kenya, while one was the owner of a local business consultancy:

Robert Executive in a Spanish company

• Does many meetings in Nairobi
• Used “Uber for Business” in the past
• Now uses the corporate service of “Little Cab”, the third-biggest and Kenyan ride-hailing platform
• Receives a monthly invoice for his team‘s rides, which can be paid via bank transfer from Europe
• A personal driver would give him more flexibility, but he doesn‘t want to commit to a full month (and employ one)

James Works for an NGO

• Uses “Little Cab” and Uber
• 1-6 rides per week
• Mostly distinct single trips from office to other parts of the city
• Does not need a monthly invoice,as rides are few
• Pays in cash or M-Pesa

Ann Director of a business consultancy

• Visits many clients at their offices
• Hired a full-time personal driver for 28,000 KSH per month (249.01 Euro)
• The driver drives her to meetings and waits for her during the meeting; also he does errands
• Trusts the driver and he knows her frequently visited locations, hence she is less involved in navigation
• Values the comfort and security of her car
• Her company also uses Uber, however, she finds it less convenient as the driver does not wait during meetings

Jack Head of Sales for an international company

• Visits clients in remote locations in Kenya
• Uses a personal driver who has been working for the company for a long time
• In Nairobi, he uses Uber daily to get around
• Does not own a car

From these interviews I deduced the following user needs:

1. Flexibility
2. The driver should know frequently visited locations (Many locations in Kenya are not as easy to find as in Europe, e.g. due to the lack of street names)
3. Money-saving
4. Trust in driver and car
5. Lower cost than hiring a driver and own a car
6. Aggregated billing of a team's ride

Hypothesis

Business customers in Nairobi need personal driving services for their meetings or trips out of town – without committing to an employed personal driver and any fix costs.

Experiment

I completely redesigned the landing page to directly address the identified needs of business customers in Nairobi. Also, I included additional value adds that would differentiate “Drivas” even more from regular ride-hailing platforms. For example, tiered discounts on the monthly bill and premium features such as “comfortable cars”. As in the previous sprint, interested visitors of the landing page would continue to WhatsApp, where they could “sign up” and request rides. To reach a more specific target group, I decided to not promote the platform using Facebook Ads, but instead simply post it in a dedicated group for expats in Nairobi. In case I would generate an interested customer, I engaged the personal driver Jonathan, who I could directly work and design the customer experience with. Also, he would provide the service, collect the payment and issue a receipt. In this way, I prototyped a fully operational service and achieved a first MVP that can be tested in the market.

Results

Of the 29 people who clicked on the link to learn more about “Drivas”, 12 people proceeded to WhatsApp and provided their names after being requested to do so by an automatic prompt. Accordingly, this landing page had a conversation rate of 41%, compared to the 2% scored with the previous sprint‘s approach. Moreover, several clients proactively engaged in the chat and requested prices for specific trips they were planning. One person requested specific information on the billing and order procedures for corporate clients.

Interestingly, three people requested an estimate for long-distance trips such as from Nairobi to the Western city of Kisumu, which takes approximately 6 hours by car. Two other people asked for return trips starting from places that were around 80 km away from Nairobi. Moreover, two people asked for the specific car types the platform uses. For the two requested trips involving long drives and returns to the passenger‘s location, the prices I could offer were too high according to the customers‘ feedback.

Learning

The performance of the MVP on personal driving for businesses customers created and tested during this sprint indicates a step in the right direction and provides valuable insights for exploration in further sprints beyond the scope of this thesis.

Interim conclusion on 'Drivas'

In my initial sprints, I built too much on the assumption that the mobility market has an established and simple user need. Also, I did not fully consider the market dominance of Uber and Bolt and the attraction of reliable infrastructure, network effects and low prices for a broad customer segment.

More importantly, I should have conducted at least one or two more rounds of qualitative user interviews prior to or at an early stage of the project, which probably would have provided me with more guidance on actual user needs from the beginning.

The sprint-based structure and underlying lean methodology allowed me to productively iterate from my invalid initial ideas to a platform concept, that converted qualitative user leads that I could learn from.

Fortunately, I pivoted to the business customer segment, which entailed a redesign of the pricing models towards long or full-day rides. I conclude that this led to a significantly more tangible and differentiated product.

With regards to the platform cooperative aspects, my main priority during the project was the design and validation of a business model, product and service that is suitable to enable “economic fairness”. Hence I assert that this is a pre-condition to attract actual “workers” and explore the democratic aspects of a (platform) cooperative in a participatory nature. Nevertheless, I found it important and helpful to regularly discuss my ideas, business models and especially prices with actual drivers in Nairobi throughout the project.

While the driver‘s feedback on my initial ideas and potential returns for them was commented as “little money” compared to potential returns from Uber, drivers were very keen on engaging with the personal driver service outlined in the fourth sprint, since the potential returns of this platform model are significantly higher than their average income from Uber.

(Sprint 5: Nation-wide driver platform)

My major learning of the last experiment was several people‘s interest in trips, either not starting from Nairobi, or going to remote destinations that do not allow the driver to return at the same day without the unpaid, unproductive time and fuel costs.

Considering that Kenya is a developing country, there are limited cross-country transport methods from and to non-urban destinations for people who expect safety and convenience – exept self-driving. Hence this market segment should be explored in an additional sprint. Other than Uber‘s focus on highly populated areas, a niche platform cooperative focusing on cross-country rides could also be inclusive to drivers based across the country.

(Sprint 6: Participatory design of a 'cooperative user experience')

Considering that “Drivas” aims to become a cooperative platform owned and democratically controlled by its member drivers, I‘m considering another sprint on a participatory design process within and among drivers interested in the project. For this purpose, an existing WhatsApp group of 24 drivers already interested in the project can be reengaged.

Subject to such a workshop could be a mapping and ideation of the drivers‘ experience with different types of customers, rapid prototyping of personal driving experience and development of internal processes of operating the platform.

The involvement of members in the creation of the platform could eventually lead to a unique “cooperative user experience” as a competitive advantage – which Winn of the Colab Cooperative described as “celebration of solidarity”.

Conclusion

The disruptive power of digital platforms discussed at the beginning of this thesis has had a significant impact on the mobility market in Kenya. Mainly with the growth of the platform Uber, more and more drivers entered the business and established relatively stable income sources. Those who did not have a suitable car, have been provided with cars and loans for the sake of rapid growth. From my conversations I learned, however, that Uber drivers in Nairobi work very hard – and as the market is becoming more and more competitive, the working conditions are getting even more challenging over time.

Uber‘s business is focused on urban areas where it can implement the same digital infrastructure and business models as in other parts around the world. This opens up a perfect opportunity for local, small or medium-scale platforms, that address the needs of specific customer segments. My project has shown that the traction of a fair platform idea significantly increased as soon as I focused on a niche market. Interestingly that aligns with the theories of experienced for-profit entrepreneurs such as Peter Thiel. He states that startups should start small instead of aiming to disrupt an industry early on, since it is easier “to dominate a niche market than a larger, pre-existing one”. Hence I conclude that this approach should be considered as fundamental to the design and prototyping of fair and worker-friendly platform models.

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