IDEAS home Printed from https://ideas.repec.org/a/wly/reggov/v16y2022i1p85-101.html
   My bibliography  Save this article

Same, same, but different! Qualitative evidence on how algorithmic selection applications govern different life domains

Author

Listed:
  • Noemi Festic

Abstract

The term algorithmic governance describes institutional steering effects of algorithmic‐selection applications that increasingly pervade all domains of everyday life. Empirical evidence on algorithmic governance is lacking and mostly limited to information services. This article compares the significance of algorithmic governance – measured by use, subjective significance, awareness, risk awareness, and coping practices – for four pivotal life domains (information, recreation, commercial transactions, and socializing). Drawing on qualitative, semi‐structured interviews with Internet users, this article reveals important nuances in how differently users engage with algorithmic‐selection applications across life domains and functional types like search or recommendation. While awareness of algorithmic selection and related risks is comparatively higher for information services, the findings reveal a significant lack of knowledge for algorithmic selection in other life domains and for specific algorithmic modes of operation. This article provides input for an evidence‐based development of suitable regulation of algorithmic‐selection applications, taking everyday practices of their users into account.

Suggested Citation

  • Noemi Festic, 2022. "Same, same, but different! Qualitative evidence on how algorithmic selection applications govern different life domains," Regulation & Governance, John Wiley & Sons, vol. 16(1), pages 85-101, January.
    • Handle: RePEc:wly:reggov:v:16:y:2022:i:1:p:85-101
    DOI: 10.1111/rego.12333
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/rego.12333
    Download Restriction: no
    File URL: https://libkey.io/10.1111/rego.12333?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Rajagopal, 2014. "The Human Factors," Palgrave Macmillan Books, in: Architecting Enterprise, chapter 9, pages 225-249, Palgrave Macmillan.
    2. Latzer, Michael & Festic, Noemi, 2019. "A guideline for understanding and measuring algorithmic governance in everyday life," Internet Policy Review: Journal on Internet Regulation, Alexander von Humboldt Institute for Internet and Society (HIIG), Berlin, vol. 8(2), pages 1-19.
    3. Logg, Jennifer M. & Minson, Julia A. & Moore, Don A., 2019. "Algorithm appreciation: People prefer algorithmic to human judgment," Organizational Behavior and Human Decision Processes, Elsevier, vol. 151(C), pages 90-103.
    4. Gunter J. Hitsch & Ali Hortaçsu & Dan Ariely, 2010. "Matching and Sorting in Online Dating," American Economic Review, American Economic Association, vol. 100(1), pages 130-163, March.
    5. Eyert, Florian & Irgmaier, Florian & Ulbricht, Lena, 2022. "Extending the framework of algorithmic regulation. The Uber case," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 16(1), pages 23-44.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Letizia Mencarini & Delia Irazú Hernández Farías & Mirko Lai & Viviana Patti & Emilio Sulis & Daniele Vignoli, 2019. "Happy parents’ tweets: An exploration of Italian Twitter data using sentiment analysis," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 40(25), pages 693-724.
    2. Letizia Mencarini & Delia Irazú Hernández-Farías & Mirko Lai & Viviana Patti & Emilio Sulis & Daniele Vignoli, 2018. "Italian happy parents In Twitter," Working Papers 117, "Carlo F. Dondena" Centre for Research on Social Dynamics (DONDENA), Università Commerciale Luigi Bocconi.
    3. Rahman, Shaikh Moksadur, 2020. "Relationship between Job Satisfaction and Turnover Intention: Evidence from Bangladesh," Asian Business Review, Asian Business Consortium, vol. 10(2), pages 99-108.
    4. Naveena Prakasam & Louisa Huxtable-Thomas, 2021. "Reddit: Affordances as an Enabler for Shifting Loyalties," Information Systems Frontiers, Springer, vol. 23(3), pages 723-751, June.
    5. Valeriy Makarov & Albert Bakhtizin, 2014. "The Estimation Of The Regions’ Efficiency Of The Russian Federation Including The Intellectual Capital, The Characteristics Of Readiness For Innovation, Level Of Well-Being, And Quality Of Life," Economy of region, Centre for Economic Security, Institute of Economics of Ural Branch of Russian Academy of Sciences, vol. 1(4), pages 9-30.
    6. Kristine Edgar Danielyan & Samvel Grigoriy Chailyan, 2019. "Delineation of Effectors Impact on The Human Brain Derived Phosphoribosylpyrophosphate Synthetase-1 Activity," Biomedical Journal of Scientific & Technical Research, Biomedical Research Network+, LLC, vol. 24(1), pages 17918-17926, December.
    7. Chuan Wang & Yupeng Liu & Wen Hou & Chao Yu & Guorong Wang & Yuyan Zheng, 2021. "Reliability and availability modeling of Subsea Autonomous High Integrity Pressure Protection System with partial stroke test by Dynamic Bayesian," Journal of Risk and Reliability, , vol. 235(2), pages 268-281, April.
    8. Yongping Bao & Ludwig Danwitz & Fabian Dvorak & Sebastian Fehrler & Lars Hornuf & Hsuan Yu Lin & Bettina von Helversen, 2022. "Similarity and Consistency in Algorithm-Guided Exploration," CESifo Working Paper Series 10188, CESifo.
    9. Sana Sadiq & Khadija Anasse & Najib Slimani, 2022. "The impact of mobile phones on high school students: connecting the research dots," Technium Social Sciences Journal, Technium Science, vol. 30(1), pages 252-270, April.
    10. Jascha-Alexander Koch & Michael Siering, 2019. "The recipe of successful crowdfunding campaigns," Electronic Markets, Springer;IIM University of St. Gallen, vol. 29(4), pages 661-679, December.
    11. Martins, José & Costa, Catarina & Oliveira, Tiago & Gonçalves, Ramiro & Branco, Frederico, 2019. "How smartphone advertising influences consumers' purchase intention," Journal of Business Research, Elsevier, vol. 94(C), pages 378-387.
    12. Wu, Bing & Yip, Tsz Leung & Yan, Xinping & Guedes Soares, C., 2022. "Review of techniques and challenges of human and organizational factors analysis in maritime transportation," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    13. Herings, P. Jean-Jacques & Mauleon, Ana & Vannetelbosch, Vincent, 2020. "Matching with myopic and farsighted players," Journal of Economic Theory, Elsevier, vol. 190(C).
    14. Daniel Woods & Mustafa Abdallah & Saurabh Bagchi & Shreyas Sundaram & Timothy Cason, 2022. "Network defense and behavioral biases: an experimental study," Experimental Economics, Springer;Economic Science Association, vol. 25(1), pages 254-286, February.
    15. Zarei, Esmaeil & Khan, Faisal & Abbassi, Rouzbeh, 2021. "Importance of human reliability in process operation: A critical analysis," Reliability Engineering and System Safety, Elsevier, vol. 211(C).
    16. Bilgihan, Anil & Barreda, Albert & Okumus, Fevzi & Nusair, Khaldoon, 2016. "Consumer perception of knowledge-sharing in travel-related Online Social Networks," Tourism Management, Elsevier, vol. 52(C), pages 287-296.
    17. Siliang Tong & Nan Jia & Xueming Luo & Zheng Fang, 2021. "The Janus face of artificial intelligence feedback: Deployment versus disclosure effects on employee performance," Strategic Management Journal, Wiley Blackwell, vol. 42(9), pages 1600-1631, September.
    18. Géraldine Boué & Enda Cummins & Sandrine Guillou & Jean‐Philippe Antignac & Bruno Le Bizec & Jeanne‐Marie Membré, 2017. "Development and Application of a Probabilistic Risk–Benefit Assessment Model for Infant Feeding Integrating Microbiological, Nutritional, and Chemical Components," Risk Analysis, John Wiley & Sons, vol. 37(12), pages 2360-2388, December.
    19. Leila Tavakoli & Hamed Zamani & Falk Scholer & William Bruce Croft & Mark Sanderson, 2022. "Analyzing clarification in asynchronous information‐seeking conversations," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 73(3), pages 449-471, March.
    20. Michael Bates & Michael Dinerstein & Andrew C. Johnston & Isaac Sorkin, 2022. "Teacher Labor Market Equilibrium and Student Achievement," CESifo Working Paper Series 9551, CESifo.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wly:reggov:v:16:y:2022:i:1:p:85-101. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1111/(ISSN)1748-5991 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.