We asked Xia more about his findings.

You studied four used car trading platforms – did all these platforms share similar technology or were there differences in the functionality and usability?

The essence of technology behind these digital platforms are similar. The core function of these platforms is to link used car buyers and sellers. This function can be achieved through a simple website or mobile app using existing mature technology.

The platforms facilitate these trades between used car sellers and buyers by providing an easily quantifiable inspection report, which certain level of transparency of the conditions of these vehicles. Within these reports, the damages from small scratches to structural deformation are all clearly identified. Some platforms chose more technologically advanced method such as standardized vehicle damage inspection systems with proprietary tools, and others relied on the experience of the platforms’ employees (inspectors).

My research shows that technologically more advanced solution does not necessarily give a platform a competitive edge. The core competitive advantage of a platform comes from one’s ability to attract and serve customers. The technology used to achieve these goals can be substituted by means such as rapid expansion of inspector network, financial guarantee of used car conditions, and most importantly, reaching a larger customer base.

You identified three orchestration strategies – was one found to be more successful than the others? How did you measure the relative success?

Each of these strategies is a success within their own time frame.

At the early stage, when customers are not yet familiar with the platform concept, strategy 1 Adherence is more applicable. Helping customers make sense of the platform’s business model is most critical.

Whereas strategy 2 Leverage works best at a growth stage of the platform market. Involving other important actors, who are not the direct participants of the platform transactions, which were previously ignored by the incumbent platform, can create opportunity to “dethrone” the dominant platform.

Finally, the third strategy Bypass,  works best when the market competition is fierce within the existing scope. This strategy suggests expanding the market to a larger and underserved customer base. In my research, the individual customers consist of this previously underserved market. However, this strategy requires exponentially more resources to succeed.

From a distance, strategy 3 looks like a competition of the size of a platform’s pocket size. Hence, the platform firm’s ability to raise capital is critical.

The industry usually looks at a few metrics to determine the “success” of a platform. These metrics include transaction volume, daily active user, and market share. But overall, the consensus is looking at the market size captured by a given platform. These metrics can provide a snapshot of a platform’s performance at a given point of time.

You say that the ‘first mover advantage’ did not result in long term success – what was the biggest factor in determining the long term success?

First mover advantage is highly regarded within the platform research community. Because a platform’s value is determined by the number of customers within the existing network. It is natural for a used car buyer to choose the platform with the largest variety of vehicles at a competitive price. And the larger number of available buyers would increase the likelihood of a used car seller to reach a deal quicker. Hence, more sellers would be attracted to this platform. Therefore, it makes sense that the first mover to be the one capturing the largest market first.

However, as my research shows, the first mover did not hold their dominant position for long. The latecomers managed to capture even larger market share.

The most important factor for a platform to succeed would be the ability to continuous harness its business ecosystem, or in a more academic term, the platform’s related “fields”. A platform should not only focus on its immediate participants, but also identify and deal with threats from external parties. For example, in my case studies, the automotive manufacturers, who do not participate the used car platforms directly, but control the used car policies of their dealerships, are one of such parties that diminished the value of the first mover advantage. The upcoming platform partnered with the major automotive manufacturers and severely damaged the supply channel of the incumbent used car platform.

About Xia Han

Xia Han is currently a Lecturer at Brunel Business School and a member of the Operations and Information System Management Research Group. He completed his PhD under the supervision of Dr Veronica Martinez and Prof. Andy Neely at the Cambridge Service Alliance.

His PhD research: The Dynamics of Digital Platform Orchestration: Unfolding the Institutional Logics Shifts and Fields Restructuring in the Chinese Used Car Market, was supported by RADMA.