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Paths to social licence for tracking-data analytics in university research and services

Author

Listed:
  • Joshua P White
  • Simon Dennis
  • Martin Tomko
  • Jessica Bell
  • Stephan Winter

Abstract

While tracking-data analytics can be a goldmine for institutions and companies, the inherent privacy concerns also form a legal, ethical and social minefield. We present a study that seeks to understand the extent and circumstances under which tracking-data analytics is undertaken with social licence—that is, with broad community acceptance beyond formal compliance with legal requirements. Taking a University campus environment as a case, we enquire about the social licence for Wi-Fi-based tracking-data analytics. Staff and student participants answered a questionnaire presenting hypothetical scenarios involving Wi-Fi tracking for university research and services. Our results present a Bayesian logistic mixed-effects regression of acceptability judgements as a function of participant ratings on 11 privacy dimensions. Results show widespread acceptance of tracking-data analytics on campus and suggest that trust, individual benefit, data sensitivity, risk of harm and institutional respect for privacy are the most predictive factors determining this acceptance judgement.

Suggested Citation

  • Joshua P White & Simon Dennis & Martin Tomko & Jessica Bell & Stephan Winter, 2021. "Paths to social licence for tracking-data analytics in university research and services," PLOS ONE, Public Library of Science, vol. 16(5), pages 1-19, May.
  • Handle: RePEc:plo:pone00:0251964
    DOI: 10.1371/journal.pone.0251964
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    1. Carpenter, Bob & Gelman, Andrew & Hoffman, Matthew D. & Lee, Daniel & Goodrich, Ben & Betancourt, Michael & Brubaker, Marcus & Guo, Jiqiang & Li, Peter & Riddell, Allen, 2017. "Stan: A Probabilistic Programming Language," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 76(i01).
    2. Kuhn, Max, 2008. "Building Predictive Models in R Using the caret Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 28(i05).
    3. Moffat, Kieren & Zhang, Airong, 2014. "The paths to social licence to operate: An integrative model explaining community acceptance of mining," Resources Policy, Elsevier, vol. 39(C), pages 61-70.
    4. Bürkner, Paul-Christian, 2017. "brms: An R Package for Bayesian Multilevel Models Using Stan," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 80(i01).
    5. Bates, Douglas & Mächler, Martin & Bolker, Ben & Walker, Steve, 2015. "Fitting Linear Mixed-Effects Models Using lme4," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 67(i01).
    6. Friedman, Jerome H. & Hastie, Trevor & Tibshirani, Rob, 2010. "Regularization Paths for Generalized Linear Models via Coordinate Descent," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 33(i01).
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