The effects that shape the value of data

Due to the heterogeneity of data, data valuation is very challenging in practice. Therefore, it is important to understand the basic characteristics of digital business models before making an assessment:

  • Direct network effects

In digital business models, the utility value of a digital good often depends on the number of other people or machines using a service. For example, social networks do not create value for users unless other participants interact with them. Economically, such networks generate positive externalities (spill-over effects). In these, the sum of all value added contributions of the individual network participants is smaller than the total value added generated by the network (so-called super additivity of value added contributions). From an economic point of view, a network is therefore extraordinary, since the marginal utility increases rather than decreases as usual as the volume increases.

  • Indirect network effects

It is also possible that the benefit is not directly dependent on a digital good. This is the case, for example, with a price comparison search engine for rental cars, which in turn refers to another digital platform for booking rental cars.

  • Scaling options

Digital goods have a high proportion of fixed costs and a low proportion of variable costs. The effective marginal costs of software or e-books, for example, are close to zero. Once created, they can be sold without a physical presence.

  • Change costs and lock-in effects

The accumulation of data by one supplier may inhibit customers of a digital good or prevent them from switching to another supplier. The costs can be both monetary and psychological.

  • Complementary goods

Digital goods and services complement each other. Several digital goods, such as apps that complement the operating system of a smartphone, create added value for the user.

https://dx.doi.org/10.1787/9789264293083-en

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