Data Network Effects

Data Network Effects is a type of network effect in which the value of a product or service increases for all users as additional users contribute data that enhance the system's performance, typically through improved algorithms, personalization, or predictive accuracy, thereby distinguishing it from other network effects that rely primarily on user count or direct interactions.

12

Publications

921

Citations

32

Authors

28

Institutions

Publications per year

2017–2026

10

Variants

Data-driven Network Effects

Authors

32

  1. DH
    Darek Haftor

    Uppsala University, Sweden

    3 publications · 138 citations

    3

    h-index

  2. RC
    Ricardo Costa Climent

    Uppsala University, Sweden

    3 publications · 138 citations

    3

    h-index

  3. RW
    Robert Wayne Gregory

    University of Miami, United States

    2 publications · 567 citations

    2

    h-index

  4. FR
    Frantz Rowe

    Nantes Université, France

    2 publications · 47 citations

    2

    h-index

  5. EK
    Evgeny Káganer

    IESE Business School, Spain

    2 publications · 567 citations

    2

    h-index

1–5 of 32

Venues

  1. Academy of Management Review

    AMR · 2 publications · 567 citations

    2

    h-index

  2. Journal of Business Research

    JBR · 2 publications · 78 citations

    2

    h-index

  3. SSRN Electronic Journal

    Repository · 1 publications · 12 citations

    1

    h-index

  4. Information Systems Research

    ISR · 1 publications · 32 citations

    1

    h-index

  5. Journal of Business Venturing

    JBV · 1 publications · 38 citations

    1

    h-index

1–5