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

Oliver Budzinski; Sophia Gaenssle; Nadine Lindstädt-Dreusicke

doi:10.4337/9781839107191.00031

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

Oliver Budzinski, Sophia Gaenssle, Nadine Lindstädt-Dreusicke

Research output: Chapter/Conference proceeding › Chapter › Academic

4 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 language	English
Title of host publication	Handbook on Digital Business Ecosystems
Subtitle of host publication	Strategies, Platforms, Technologies, Governance and Societal Challenges
Publisher	Edward Elgar Publishing
Pages	348-366
Number of pages	19
ISBN (Electronic)	9781839107191
ISBN (Print)	9781839107184
DOIs	https://doi.org/10.4337/9781839107191.00031
Publication status	Published - 19 Apr 2022
Externally published	Yes

Bibliographical note

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© Sabine Baumann 2022. All rights reserved.

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10.4337/9781839107191.00031Licence: CC BY

Cite this

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Data (r)evolution: the economics of algorithmic search and recommender services. / Budzinski, Oliver; Gaenssle, Sophia; Lindstädt-Dreusicke, Nadine.
Handbook on Digital Business Ecosystems: Strategies, Platforms, Technologies, Governance and Societal Challenges. Edward Elgar Publishing, 2022. p. 348-366.

Research output: Chapter/Conference proceeding › Chapter › Academic

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

Abstract

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