Why people in China don’t need to carry wallet anymore – cascading behavior caused by development of fintech
Wechat pay and Alipay, products under Tencent and Alibaba, are now trending in China for their convenience in online transactions. Since their launch, more and more people have started to rely on this new technology instead of the old traditional way of carrying a purse and wallet anywhere they go. To explain why people are no longer carrying actual credit cards and cash but switching to only carrying phones, this blog post will be using the cascading behavior to explain the phenomenon.
Taking both Wechat pay and Alipay the new technology A.
HOW DOES A SPREAD OUT?
First, we will discuss the clusters and cascading behavior
To build a simple model for this discussion:
Suppose in a neighborhood that has 100 people living in in Shanghai, we divide the population into three clusters (according to yearly income). we also assume that the threshold is q=1/3.
We have demographic distributions as follows:
Lows income: 30 people
Middle class: 50 people
Upper class: 20 people
We define the following connections:
Everyone in the low-income cluster has 8 friends within the same cluster, 5 friends in the middle-class group, and only 1 friend in the upper-class cluster.
Everyone in the middle-class cluster has 20 friends within the same cluster, 10 friends in the low-income cluster, and 5 friends in the upper class.
Everyone in the upper-class cluster has 10 friends within the same cluster, 10 friends in the low-income cluster, and 1 friend in the low-income cluster.
In order for technology A to become popular and for everyone in these three groups to use it, we need to calculate how many initial users should exist, namely, how much effort the sales and marketing team needs to put in in order for the “snowball” to become bigger and bigger.
As for the product’s target users, this model will also aim to consider the first several users to be in the middle-class cluster. This is due to the fact that the middle-class cluster is generally more attracted by consumer-efficient products and technologies.
We know that for people in the middle-class cluster, all have 20+5+10 connections in total.
For p>= q which is the threshold = 1/3. We need 12 friends to also adopt technology A first so that the person who’s friends with the 18 people will also adopt the technology. We first assume that this is a possible scenario and that everyone in the middle-class cluster now adopts the technology. Now taking a look into the low-income cluster, 5/14 connections are within the mid-income group that has already adopted the technology. Thus the person in the low-income group will also adopt the technology. Now, this would lead to a cascading effect in the low-income group. Now we take a look at the upper-class cluster. 11/21 of the connections are already using the new technology and 11/21 > 1/3. Thus, the new technology will also spread into the upper-class cluster. And we have successfully had a single threshold cascading effect.
This shows that if this new technology is spread in the middle-class cluster then it can also spread to the other two.
Combining this with what Alipay and WeChat pay’s strategies, they first targeted white collars, who are in the middle-class cluster and seeking for convince in the products they use due to their large workloads. They are also the group of people that have a higher consumption level monetarily. Our simple model thus corresponds well with the strategies.
WHY PEOPLE USE THEM?
In the matrix below, we assume the following two choices, actual credit-card, and online payment. The payoffs are as followings
| Credit-card (actual) | Online payment transactions | |
| Credit-card (actual) |
(a,a) |
(b,c) |
| Online payment transactions |
(c,b) |
(d,d) |
Since online payment transactions provide more convenience due to the fact the most people wouldn’t forget to carry their phone with them all the time, this largely increases the payoffs of c and d. both Alipay and WeChat pay has also cooperated with credit card companies so you can use credit cards from these two platforms which also leads to an increase in the payoff.
We can write the calculations as ap+b(1-p) <= cp + d(1-p) Thus this will also decrease the value of threshold q. and leads to the fact that it’s even easier for those platforms to attract more new customers and maintain the old loyal customers.