Data (r)evolution: the economics of algorithmic search and recommender services

Oliver Budzinski, Sophia Gaenssle, Nadine Lindstädt-Dreusicke

Research output: Chapter/Conference proceedingChapterAcademic

2 Citations (Scopus)

Abstract

This chapter analyzes the economics behind algorithmic search and recommender services (SRS), which are based on personalized user data. Such services play a paramount role in digital business ecosystems (DBE), such as marketplaces (e.g. Amazon), audio streaming (e.g. Spotify), video streaming (e.g. Netflix, YouTube), app stores, social networks (e.g. Instagram, TikTok, Facebook, Twitter) and many more. We start with a systematic analysis of SRS as a commercial good, highlighting the changes because of digitization. Then we discuss benefits and risk for welfare that arise from the widespread employment of algorithmic search and recommendation systems. In doing so, we summarize the existing economics literature and go beyond its insights, highlighting further research agendas. Eventually, we explain the role of SRS within the DBE and managerial implications.

Original languageEnglish
Title of host publicationHandbook on Digital Business Ecosystems
Subtitle of host publicationStrategies, Platforms, Technologies, Governance and Societal Challenges
PublisherEdward Elgar Publishing
Pages348-366
Number of pages19
ISBN (Electronic)9781839107191
ISBN (Print)9781839107184
DOIs
Publication statusPublished - 19 Apr 2022
Externally publishedYes

Bibliographical note

Publisher Copyright:
© Sabine Baumann 2022. All rights reserved.

Research programs

  • ESHCC A&CS

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