“Stranger Danger,” E-commerce, and the Digital Transmission of Trust
The Hustle recently published a piece about the sharing economy that opened with the story of Zhao Shuping:
Last July, an idealistic young entrepreneur by the name of Zhao Shuping had an epiphany: “Everything on the street,” he proclaimed, “can now be shared.”
Capitalizing on China’s sharing economy fetish, Shuping raised 10m yuan (~$1.6m USD) from a cadre of drooling investors, purchased 300k umbrellas, and rented them out at train stations across 11 Chinese cities for a fee of $0.80 per half-hour.
Within 2 weeks, all 300k umbrellas had been stolen.
The sharing economy is poised to grow to $335B worldwide by 2025 — and, as these platforms become more common, so too do the tales of their utter failure. Yet, our trust in collaborative consumption remains astronomically high.
There are many possible answers to the why question. Zachary Crockett, the author of “How the Sharing Economy Makes Us Trust Complete Strangers,” thinks that technology platforms such as Lyft, Uber, and Airbnb, to mention only a few prominent examples, have deprogrammed our sense of “stranger danger.” It’s ironic, indeed, that we are more likely to trust strangers and get into their cars, sleep in their beds, and invite them into our homes to assemble our mail order furniture than to trust the press, banks, government officials, our immediate neighbors, or even our coworkers. According to Crockett, the reason for this abatement of inhibition is because technology has changed our mechanisms for trust.
In pre-industrial times, when we wanted to trade a goat for 50 pounds of wheat, we based our trust in close-knit circles of personal relationships. After the Industrial Revolution, we began to get most of our manufactured goods from corporations, which meant that transactions became less personal and trust was easily eroded. To gain trust back, companies created strong brand identities and submitted to government regulations that claimed to serve the public interest.
Today, companies seek to gain trust through technologies such as digital ranking systems and blockchain ledgers, which aim to reintroduce either a personal dimension into essentially anonymous transactions or a tamper-proof repository of data not owned by anyone. Blockchain, in particular, has been described as the “trust machine,” but critics contend that blockchain technology is unable to create data that has unassailable integrity.
That’s all well and good, but what happens when that “engineered trust” is absent from commercial digital transactions on the scale of an entire continent? Trust in Africa is always local and face-to-face, but noticeably absent in e-commerce transactions as the Nigerian companies Konga and Jumia have experienced.
Moja is a complete rethink of e-commerce for Africa — an enterprise engine designed to empower entrepreneurs through trade, training, network-building, and financial inclusion. To use Crockett’s language, Moja is an African technology company that converts the collaborative trust of face-to-face entrepreneurial networks into “transactional integrity credit” that can enable trade in wider, impersonal circles of exchange.
Designed for trust, Moja fosters local capacity within entrepreneurial networks and connects them with each other; expanding local, regional, and global trade circles. Moja provides the digital means to expand business opportunities and access to financial services — an entire ecosystem in the palm of one’s hands. The technology mechanism that Moja uses to accomplish this mission is its trust score algorithm.
The Moja trust score algorithm is a unique, proprietary formula based on a Moja user’s in-app activity that indicates a user is increasing in trustworthiness. The Moja trust score, the contributing data components of which are viewable by all users of the app, is a number correlated directly to the user’s Moja profile.
The higher the number, the higher the likelihood that the person or entity will fulfill its promises. This motivates people to increase their Moja score so that others, by viewing their user profile, will have a value neutral, external basis on which to decide whether they are trustworthy. What accrues here is portable transactional integrity credit that can be applied to new situations and relationships. Moja is designed to increase trust, and its trust score algorithm is built from gamified user activity data drawn from the diverse interfaces of the Moja app.
Moja’s gamification is a form of human-centered design that tugs on eight core drives within people that motivate them toward certain activities such as trust building — the principal missing ingredient in African e-commerce and economic development. Yu-Kai Chou, a global leader in the field of behavioral design, calls this Octalysis, in his book Actionable Gamification: Beyond Points, Badges, and Leaderboards.
The first core drive is epic meaning and calling. Epic meaning and calling is the core drive where a person believes that s/he is doing something greater than him/herself or s/he was “chosen” to do something.
The second core drive is development and accomplishment. Development and accomplishment is the internal drive of making progress, developing skills, and eventually overcoming challenges: points, badges, and leaderboards are most often used to depict progress in this core drive.
The third core drive is empowerment of creativity and feedback. Empowerment of creativity and feedback is when users are engaged in a creative process where they have to repeatedly figure things out and try different combinations.
The fourth core drive is ownership and possession. This is the drive where users are motivated because they feel like they own something. Besides being the major core drive for wanting to accumulate wealth, this deals with many virtual goods or virtual currencies within systems.
The fifth core drive is social influence and relatedness. This drive incorporates all of the social elements that drive people, including: mentorship, acceptance, social responses, companionship, as well as competition and envy.
The sixth core drive is scarcity and impatience. This is the drive of wanting something because you cannot have it: the fact that people cannot get something right now motivates them to think about it all day long.
The seventh core drive is unpredictability and curiosity. This is a harmless drive of wanting to find out what will happen next. If you do not know what is going to happen, your brain is engaged, and you think about it often.
The eighth core drive is loss and avoidance. This core drive is based upon the avoidance of something negative happening. Opportunities that are in jeopardy of fading away appeal to this core drive because people feel like if they do not act immediately, they will permanently lose the opportunity to act.
But what does the Moja trust score mean in practice? It means that a user is building a solid portfolio of trust through mutually beneficial selling/buying, learning new skills, participating as an active member of a trusted network, and utilizing Moja value added services: Pay, Money, and Mobile. User activity in each of these areas contribute points toward a user’s aggregate Moja trust score.
In addition to showing an increase in a user’s trustworthiness, the Moja trust score algorithm may also become a distinguishing feature of a person’s digital creditworthiness. The higher the Moja score, the more creditworthy the user will likely be. With digital credit, loan decisions are frequently determined based on the analysis of unconventional sources of digital data, rather than the traditional credit scores calculated by a conventional credit bureau. This is particularly relevant in developing countries, where most households don’t have credit scores, due both to the underdevelopment of credit bureaus and to the fact that many people don’t have a history of financial transactions that can be verified by a lender.
The information leveraged by digital credit lenders to determine creditworthiness is varied. Most lenders from (or associated with) the telecom industry use the applicant’s history of mobile phone usage, including phone calls, text messages, airtime purchases, data use, and mobile money transactions. When the applicant has an app (such as the Moja app) installed on their smartphone, this app collects all of that information as well as GPS data, information on social media use, contact lists, and the like. The Moja trust score algorithm will draw from a similar array of data streams as well as ones that are proprietary to Moja users to determine whether a person or business entity is creditworthy and thus able to access Moja’s financial products and services.