CONCLUSION

This chapter offers an innovation-co-evolution-complexity perspective, that is, an evo­lutionary innovation economics approach, on algorithmic selection on the Internet, a rapidly growing phenomenon, characterized by automated selection of information elements and the assignment of relevance to them.

Applications are in different market phases.

Comparative business model analyses of algorithmic selection applications reveal similarities in services offered to end users, resulting in part from market characteristics (e.g., pricing in two- or multi-sided markets) or from imitation strategies. Services for business and public service customers, on the other hand, vary more widely, because they are frequently custom-made for specific purposes.

Algorithmic selection promises to reduce information asymmetries and various kinds of transaction costs (e.g., search and information costs) and as a result increases con­sumption and sales, and facilitates social orientation. Providers of algorithmic selection are mostly active as market makers (intermediaries) or layer players (specialists), and less as orchestrators or integrators. Revenue strategies in these markets depend on the fact that algorithmic selection applications often serve different, interdependent customer segments in two- or multi-sided markets, where prices have to be weighted accordingly and cross-financing is indispensible. As a result, indirect forms of revenue predominate.

The effects on traditional media incumbents’ profitability vary from industry to indus­try. Theoretical considerations indicate a tendency to decrease profitability for incum­bents of the news industry and a tendency towards a profitability increase in the music industry, as music-streaming services have been pushing revenues of the traditional music industry and have enhanced legal music consumption.

Products and services based on algorithmic selection have become vital and essential for the generation of economic wealth but are also compromised by the production of social risks, among other things, threats to basic rights and liberties as well as impacts on the mediation of realities and people’s future development. The emergence of social risks is coupled with discussions of whether and what governance approaches are appropriate to remedy such risks. Analyses indicate that there are no one-size-fits-all solutions, and that there is the need for a governance mix consistent with the respective risks and appli­cations in question. Adequate governance strategies often call for an interplay between the various levels and actors involved (e.g., self-help of consumers depends, among other things, on organizational or technical dispositions). Finally, governance measures are not only directed towards the algorithms (technical design) alone, but predominantly target organizational settings, for example, the business models and strategies, with far-reaching effects for the economics of the markets concerned.

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