Networking down: Networks, innovation, and relational labor in digital book publishing

Author:

Larson Christine1ORCID,Ready Elspeth2

Affiliation:

1. University of Colorado, USA

2. Max Planck Institute for Evolutionary Anthropology, Germany

Abstract

While management and network scholars have long asked why some groups adapt to innovation more readily than others, such questions have been surprisingly absent in studies of new media production. We offer a network analytical framework which relates producers’ informal networks to their capacity to adopt digital innovations. Through a network ethnography of 4264 romance writers, we find that established authors who reversed traditional advice patterns, by seeking advice from inexperienced newcomers rather than experienced peers, were more likely to adopt digital self-publishing. By linking the concept of relational labor to network structures, we demonstrate the value of “networking down” in a digitally disrupted cultural industry—a surprising finding in a business where networking up, to powerful actors, has seemed critical for success. We argue that strategic relational labor by established content creators facilitates adaptation to digital conditions and provides some measure of protection against precarity in a changing landscape.

Publisher

SAGE Publications

Subject

Sociology and Political Science,Communication

Reference83 articles.

1. Association of American Publishers, The Authors Guild and Association of American Booksellers (2020) Joint publishing industry letter to chairman Cicilline, 17 August. Available at: https://publishers.org/wp-content/uploads/2020/08/Joint-Letter-to-Rep-Cicilline-081720.pdf (accessed 22 January 2022).

2. Authors Guild (2020) The Profession of Author in the 21st Century. The Authors Guild, January. Available at: https://www.authorsguild.org/industry-advocacy/authors-guild-issues-report-exploring-the-factors-leading-to-the-decline-of-the-writing-profession/ (accessed 20 January 2022).

3. Exploring the Relationship Between Interdisciplinary Ties and Linguistic Familiarity Using Multilevel Network Analysis

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