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Data as capital and ethical implications in digital sport business models

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journal contribution
posted on 2023-10-16, 13:10 authored by Daniel ReadDaniel Read, Aaron SmithAaron Smith
Professional sport has entered the digital economy as organisations adopt data-driven business model innovations. The purpose of this article is to highlight the potential ethical vulnerabilities sport organisations and their leaders face when adopting digital sport business models. Here, we treat data as a species of capital that can be converted into economic capital once it undergoes a computational transformation via a data-driven business model innovation. We argue for two advantages in this approach. First, it helps make transparent the mechanisms through which digital sport business models work. Second, it reveals how the extraction and application of big data exacerbates inequitable power relationships between sport organisations and supporters – the big data divide – that leads to ethical vulnerabilities for sport organisations and their consumers. We suggest that sport consumers might be particularly vulnerable to digital data risk as a consequence of their high levels of brand loyalty and involvement, which tend to encourage trust in the sport properties soliciting, analysing, and monetising their data. Platform broadcasting partnerships, e-ticketing in smart stadiums, and cryptocurrency-based fan tokens are used as examples of data-driven business model innovations based on the conversion of data to capital, demonstrating how sport organisations risk violating the trust of supporters when using digital strategies. The article concludes with directions for future research to deliver an ethically informed data-driven sports industry.

History

School

  • Loughborough University London

Published in

Convergence: The International Journal of Research into New Media Technologies

Volume

29

Issue

5

Pages

1389-1408

Publisher

SAGE Publications

Version

  • VoR (Version of Record)

Rights holder

© The Authors

Publisher statement

This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).

Publication date

2023-05-19

Copyright date

2023

ISSN

1354-8565

eISSN

1748-7382

Language

  • en

Depositor

Dr Daniel Read. Deposit date: 13 July 2023

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