The Paradox of Data Portability and Lock-In Effects

Abstract

There has been a rising clamor for legislation to expand data portability. In addition to the objective of enhancing platform users’ data autonomy, many argue that data portability would rejuvenate competition and innovation in digital markets by liberating users and their data from being locked into single systems. Based on this ambitious belief, there is a growing propensity to attempt to enlarge the scope of data subject to data portability.
However, as this Note has demonstrated, the market functions of data portability have been overestimated. Those who are adamant that the scope of data subject to data portability should be broadened to fulfill its market objective seemingly fail to realize that it is users, not legislators, who have the final say on the volume and the categories of data that are ported. If users do not have strong incentives to port data that are functionally essential to the digital market competition, the logical chain to invigorate the competitive environment in digital markets by enhancing users’ data autonomy will naturally break down. Therefore, this Note has put the academic dispute about data and platforms to one side and instead has sought to shed light on this issue from the perspective of users.
It is also important to recognize that users are not, in fact, locked in by all categories of data. Instead, there is a sliding scale — the less that users are locked in by data, the lower the likelihood they will port their data. Therefore, compared to inferred and derived data, users have stronger incentives to port provided data that will otherwise cause artificially raised switching costs (ARSCs). The paradox is that the data which are ported are relatively small in volume and are less essential to digital market competition. In contrast, the inferred and derived data that users are less likely to port are arguably more significant to realizing the market goals.
This Note has illustrated this paradox by analyzing three sources of user lock-in effects. First, data portability is incapable of solving lock-in effects by non-data-based features. Second, data portability is rarely suitable to mitigate the lock-in effects generated by market inherent switching costs (MISCs). Third, data portability has the potential to remove the data-based ARSCs. Thus, data portability can only solve highly limited data lock-in problems. This limited function can be achieved objectively by the individualistic goals of data portability. A broader scope of data portability is unnecessary and meaningless because relying on data portability to reinvigorate competition is merely the wishful thinking of legislators. In reality, it will not lead to any major changes.

Keywords: Data Portability, Lock-In Effects, Digital Market Competition, Switching Costs

JEL Classification: K00, K10, K19, K2, K20, K21, K29, K3, K30