IDEAS home Printed from https://ideas.repec.org/a/eee/teinso/v79y2024ics0160791x24002975.html
   My bibliography  Save this article

Decoding algorithm fatigue: The role of algorithmic literacy, information cocoons, and algorithmic opacity

Author

Listed:
  • Yang, Hui
  • Li, Dan
  • Hu, Peng

Abstract

Algorithmic technologies are dominating our online experiences, from content recommendations to personalized services. However, it also introduces a new challenge: algorithm fatigue. Algorithm fatigue describes the phenomenon where users experience mental and emotional exhaustion in prolonged interaction with algorithms. To decode this phenomenon, we explored personal and technical antecedents of algorithm fatigue and its impact on user behavior. Using data collected from 393 users of algorithm-driven applications, we identified three key drivers of algorithm fatigue: algorithmic literacy (understanding how algorithms work), information cocoons (being exposed to repetitive content), and algorithmic opacity (a lack of transparency in how algorithms make decisions). Interestingly, while greater algorithmic literacy is often thought to enhance user satisfaction, our findings suggest it actually exacerbates fatigue. Both information cocoons and algorithmic opacity also contribute to algorithm fatigue, highlighting the need for diverse content and transparent algorithm designs. Additionally, we found a strong link between algorithm fatigue and resistance behavior, with fatigued users more likely to resist algorithmic recommendations. Overall, this study suggests developers and policymakers design more user-centric algorithms that not only excel in personalization but also reduce potential fatigue and resistance in algorithmic interactions.

Suggested Citation

  • Yang, Hui & Li, Dan & Hu, Peng, 2024. "Decoding algorithm fatigue: The role of algorithmic literacy, information cocoons, and algorithmic opacity," Technology in Society, Elsevier, vol. 79(C).
    • Handle: RePEc:eee:teinso:v:79:y:2024:i:c:s0160791x24002975
    DOI: 10.1016/j.techsoc.2024.102749
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0160791X24002975
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.techsoc.2024.102749?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Benlian, Alexander & Klumpe, Johannes & Hinz, Oliver, 2020. "Mitigating the Intrusive Effects of Smart Home Assistants by using Anthropomorphic Design Features: A Multi-Method Investigation," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 112151, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    2. Nazir, Sajjad & Khadim, Sahar & Ali Asadullah, Muhammad & Syed, Nausheen, 2023. "Exploring the influence of artificial intelligence technology on consumer repurchase intention: The mediation and moderation approach," Technology in Society, Elsevier, vol. 72(C).
    3. Ron Berman & Zsolt Katona, 2020. "Curation Algorithms and Filter Bubbles in Social Networks," Marketing Science, INFORMS, vol. 39(2), pages 296-316, March.
    4. Hema Yoganarasimhan, 2020. "Search Personalization Using Machine Learning," Management Science, INFORMS, vol. 66(3), pages 1045-1070, March.
    5. Li, Yunjian & Song, Yixiao & Sun, Yanming & Zeng, Mingzhuo, 2024. "When do employees learn from artificial intelligence? The moderating effects of perceived enjoyment and task-related complexity," Technology in Society, Elsevier, vol. 77(C).
    6. Schiavo, Gianluca & Businaro, Stefano & Zancanaro, Massimo, 2024. "Comprehension, apprehension, and acceptance: Understanding the influence of literacy and anxiety on acceptance of artificial Intelligence," Technology in Society, Elsevier, vol. 77(C).
    7. Pal, Debajyoti & Zhang, Xiangmin & Siyal, Saeed, 2021. "Prohibitive factors to the acceptance of Internet of Things (IoT) technology in society: A smart-home context using a resistive modelling approach," Technology in Society, Elsevier, vol. 66(C).
    8. Yuanyou Ou & Baoning Niu, 2023. "Dual-Channel Feature Enhanced Collaborative Filtering Recommendation Algorithm," Future Internet, MDPI, vol. 15(6), pages 1-19, June.
    9. Gokhan Ertug & Martin Gargiulo & Charles Galunic & Tengjian Zou, 2018. "Homophily and Individual Performance," Organization Science, INFORMS, vol. 29(5), pages 912-930, October.
    10. Ren, Gaofei & Chen, Yaoyao & Yang, Maobao, 2024. "Customer perception, integration behavior, and loyalty of internet of things enterprises," Technology in Society, Elsevier, vol. 78(C).
    11. Alexander Buhmann & Johannes Paßmann & Christian Fieseler, 2020. "Managing Algorithmic Accountability: Balancing Reputational Concerns, Engagement Strategies, and the Potential of Rational Discourse," Journal of Business Ethics, Springer, vol. 163(2), pages 265-280, May.
    12. Burton, Joe, 2023. "Algorithmic extremism? The securitization of artificial intelligence (AI) and its impact on radicalism, polarization and political violence," Technology in Society, Elsevier, vol. 75(C).
    13. Maude Lavanchy & Patrick Reichert & Jayanth Narayanan & Krishna Savani, 2023. "Applicants’ Fairness Perceptions of Algorithm-Driven Hiring Procedures," Journal of Business Ethics, Springer, vol. 188(1), pages 125-150, November.
    14. Nima Kordzadeh & Maryam Ghasemaghaei, 2022. "Algorithmic bias: review, synthesis, and future research directions," European Journal of Information Systems, Taylor & Francis Journals, vol. 31(3), pages 388-409, May.
    15. Xiumei Ma & Yongqiang Sun & Xitong Guo & Kee-hung Lai & Doug Vogel, 2022. "Understanding users’ negative responses to recommendation algorithms in short-video platforms: a perspective based on the Stressor-Strain-Outcome (SSO) framework," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(1), pages 41-58, March.
    16. Wang, Juite & Liu, Y.-L., 2023. "Deep learning-based social media mining for user experience analysis: A case study of smart home products," Technology in Society, Elsevier, vol. 73(C).
    17. Paas, Leonard J. & Dolnicar, Sara & Karlsson, Logi, 2018. "Instructional Manipulation Checks: A longitudinal analysis with implications for MTurk," International Journal of Research in Marketing, Elsevier, vol. 35(2), pages 258-269.
    18. Einav, Gali & Allen, Ofir & Gur, Tamar & Maaravi, Yossi & Ravner, Daniel, 2022. "Bursting filter bubbles in a digital age: Opening minds and reducing opinion polarization through digital platforms," Technology in Society, Elsevier, vol. 71(C).
    19. Claudia Wagner & Markus Strohmaier & Alexandra Olteanu & Emre Kıcıman & Noshir Contractor & Tina Eliassi-Rad, 2021. "Measuring algorithmically infused societies," Nature, Nature, vol. 595(7866), pages 197-204, July.
    20. Robinson, Stephen Cory, 2020. "Trust, transparency, and openness: How inclusion of cultural values shapes Nordic national public policy strategies for artificial intelligence (AI)," Technology in Society, Elsevier, vol. 63(C).
    21. Büchel, Hendrik & Spinler, Stefan, 2024. "The impact of the metaverse on e-commerce business models – A delphi-based scenario study," Technology in Society, Elsevier, vol. 76(C).
    22. Yao Li & Eugenia Ha Rim Rho & Alfred Kobsa, 2022. "Cultural differences in the effects of contextual factors and privacy concerns on users’ privacy decision on social networking sites," Behaviour and Information Technology, Taylor & Francis Journals, vol. 41(3), pages 655-677, February.
    23. Ali, Mahmood & Zhou, Li & Miller, Lloyd & Ieromonachou, Petros, 2016. "User resistance in IT: A literature review," International Journal of Information Management, Elsevier, vol. 36(1), pages 35-43.
    24. Shin, Donghee & Zhong, Bu & Biocca, Frank A., 2020. "Beyond user experience: What constitutes algorithmic experiences?," International Journal of Information Management, Elsevier, vol. 52(C).
    25. Yang, Hongjun & Zhang, Shengtai, 2022. "Social media affordances and fatigue: The role of privacy concerns, impression management concerns, and self-esteem," Technology in Society, Elsevier, vol. 71(C).
    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. David Horneber & Sven Laumer, 2023. "Algorithmic Accountability," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 65(6), pages 723-730, December.
    2. Monica Lestari Paramita & Maria Kasinidou & Styliani Kleanthous & Paolo Rosso & Tsvi Kuflik & Frank Hopfgartner, 2024. "Towards improving user awareness of search engine biases: A participatory design approach," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 75(5), pages 581-599, May.
    3. Syahrulanuar Ngah & Samar Rahi & Fei Long & Cecile Gabarre & Aamir Rashid & Abdul Hafaz Ngah, 2024. "Future behavioural of console gamers and mobile gamers: are they differ?," Quality & Quantity: International Journal of Methodology, Springer, vol. 58(6), pages 5531-5557, December.
    4. Rehman, Anisur & Behera, Rajat Kumar & Islam, Md Saiful & Elahi, Yasir Arafat & Abbasi, Faraz Ahmad & Imtiaz, Asma, 2024. "Drivers of metaverse adoption for enhancing marketing capabilities of retail SMEs," Technology in Society, Elsevier, vol. 79(C).
    5. Tino Werner, 2023. "Quantitative robustness of instance ranking problems," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 75(2), pages 335-368, April.
    6. Zhang, Weidong & Zuo, Na & He, Wu & Li, Songtao & Yu, Lu, 2021. "Factors influencing the use of artificial intelligence in government: Evidence from China," Technology in Society, Elsevier, vol. 66(C).
    7. König, Pascal D. & Wenzelburger, Georg, 2021. "The legitimacy gap of algorithmic decision-making in the public sector: Why it arises and how to address it," Technology in Society, Elsevier, vol. 67(C).
    8. Yao, Xintong & Xi, Yipeng, 2024. "Pathways linking expectations for AI chatbots to loyalty: A moderated mediation analysis," Technology in Society, Elsevier, vol. 78(C).
    9. Radtke, Jörg, 2025. "E-participation in energy transitions: What does it mean? Chances and challenges within Germany's Energiewende," Technological Forecasting and Social Change, Elsevier, vol. 210(C).
    10. Arroyabe, Marta F. & Arranz, Carlos F.A. & Fernandez De Arroyabe, Ignacio & Fernandez de Arroyabe, Juan Carlos, 2024. "Analyzing AI adoption in European SMEs: A study of digital capabilities, innovation, and external environment," Technology in Society, Elsevier, vol. 79(C).
    11. Song-yi Youn & Joohye Hwang & Li Zhao & Jong-Bum Kim, 2023. "Privacy paradox in 3D body scanning technology: the effect of 3D virtual try-on experience in the relationship between privacy concerns and mobile app adoption intention," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-13, December.
    12. Fosch-Villaronga, Eduard & Calleja, Carlos José & Drukarch, Hadassah & Torricelli, Diego, 2023. "How can ISO 13482:2014 account for the ethical and social considerations of robotic exoskeletons?," Technology in Society, Elsevier, vol. 75(C).
    13. Zhang, Yi & Chen, Kaihua, 2022. "Network growth dynamics: The simultaneous interaction between network positions and research performance of collaborative organisations," Technovation, Elsevier, vol. 115(C).
    14. Ilya R. P. Cuypers & Gokhan Ertug & John Cantwell & Akbar Zaheer & Martin Kilduff, 2020. "Making connections: Social networks in international business," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 51(5), pages 714-736, July.
    15. Afshan Younas & Kabaly P Subramanian & Mohammed Al-Haziazi & Syed Sadullah Hussainy & Ahmed Nasser Salem Al Kindi, 2023. "A Review on Implementation of Artificial Intelligence in Education," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 7(8), pages 1092-1100, August.
    16. Xing, Yunfei & Zhang, Justin Zuopeng & Teng, Guangqing & Zhou, Xiaotang, 2024. "Voices in the digital storm: Unraveling online polarization with ChatGPT," Technology in Society, Elsevier, vol. 77(C).
    17. Lalit Jain & Zhaoqi Li & Erfan Loghmani & Blake Mason & Hema Yoganarasimhan, 2024. "Effective Adaptive Exploration of Prices and Promotions in Choice-Based Demand Models," Marketing Science, INFORMS, vol. 43(5), pages 1002-1030, September.
    18. DeMora, Stephanie L. & Granados Samayoa, Javier A. & Albarracín, Dolores, 2024. "Social media use and vaccination among Democrats and Republicans: Informational and normative influences," Social Science & Medicine, Elsevier, vol. 352(C).
    19. Jinjin Wang & Jiadi Yang, 2022. "Culture shaping and value realization of digital media art under Internet+," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(3), pages 1124-1133, December.
    20. Gao, Zhiyuan & Zhao, Ying & Li, Lianqing & Hao, Yu, 2024. "Echoes of dependency: The impact of resource reliance on green industry transformation in China," Resources Policy, Elsevier, vol. 96(C).

    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:eee:teinso:v:79:y:2024:i:c:s0160791x24002975. 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: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/technology-in-society .

    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.