ESSEC METALAB

RESEARCH

DATA NETWORK EFFECTS: KEY CONDITIONS, SHARED DATA, AND THE DATA VALUE DUALITY

[ARTICLE] The authors propose a clarification on their theory of data network effects, in a response note to Clough and Wu (2022).

by Harris Kyriakou (ESSEC Business School), Robert Wayne Gregory, Ola Henfridsson and Evgeny Kaganer

Clough and Wu (2022) provide an interesting and thought-provoking response to their article (Gregory, Henfridsson, Kaganer, Kyriakou) on the role of artificial intelligence (AI) and data network effects for the creation of user value. In this response note, they build upon the points raised by Clough and Wu (2020) to outline three clarifications to their theory of data network effects concerning: 1) conditions when data network effects accrue; (2) the importance of theorizing shared data; and (3) the model's ability to explain the cumulative effect of data-driven learning on value creation and value capture.

[Please find the research paper here]

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