Truck Alliance’s Fight to Build Complicated Network Effects (89)
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Jul 5, 2021
Explore the intricate world of logistics with insights into the Full Truck Alliance, where complex network effects shape the freight marketplace. Discover the challenges of matching supply and demand in less-than-full truckload shipping, driven by booming e-commerce. Delve into how digital solutions revolutionize the industry, enhancing connections between shippers and truckers. Learn about technological innovations that are streamlining long-haul operations, and the implications of IPOs in this rapidly evolving tech landscape.
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insights INSIGHT
Complex Network Effects in Trucking
Truck Alliance, like Uber Freight, connects truckers with shippers.
It faces more complex network effects than simple ride-hailing.
insights INSIGHT
China's Logistics Opportunity
Truck Alliance targets a large, inefficient market ripe for platform disruption.
The Chinese logistics market, worth trillions, suffers from high costs and fragmentation.
insights INSIGHT
Road Transport Dominance
Logistics spending in China is heavily reliant on road transport, unlike other developed economies.
Within road transport, Truck Alliance focuses on full truckload (FTL) and less than truckload (LTL) shipping.
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This week’s podcast is about Full Truck Alliance, a B2B marketplace platform for freight and cargo. There are a lot of lessons on the difficulties and complexities of matching, pricing and network effects for more complicated services.
Here are the pages from the F-1 filing I mentioned.
Questions for simple network effects:
Local vs. regional vs. international network effects?
Fast vs. slow network effects?
Directionality of interactions (Facebook vs. Twitter)?
Degree vs. value of connections?
Minimum viable scale vs. asymptotic scale?
What is congestion / saturation / degradation scale?
Linear vs. exponential growth at different scales? For each user group.
Questions for complicated network effects:
Less than truckload freight (LTL). This is about coordinating demand and locations for mobility. This is similar to carpooling in ride-sharing. The matching, pricing and network effects are more complicated.
On-demand vs. synchronous vs. asynchronous. Matching, pricing and network effects are more complicated. Pricing can follow spot demand vs. scheduled.
Cyclical and other fluctuations in both supply and demand. This impacts both prices and utilization.
Route specific network effects. Need to balance supply and demand (and critical mass) on each route.
Serial routes. Matching, pricing and arranging multiple routes in sequence. Much more complicated
How does this compare with economies of scale in geographic density.
I write and speak about digital China and Asia’s latest tech trends.
I also run Tech Strategy, a podcast and subscription newsletter on the strategies of China / Asia tech companies.
This content (articles, podcasts, website info) is not investment advice. The information and opinions from me and any guests may be incorrect. The numbers and information may be wrong. The views expressed may no longer be relevant or accurate. Investing is risky. Do your own research.