Skip to main content
SpringerLink
Log in

The Role of Algorithm and Task Familiarity in Algorithm Aversion: An Empirical Study

  • Conference paper
  • First Online:
New Sustainable Horizons in Artificial Intelligence and Digital Solutions (I3E 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14316))

Included in the following conference series:

  • 426 Accesses

Abstract

Algorithm aversion, characterized by the tendency to distrust algorithmic advice despite its demonstrated superior or identical performance, has become an increasingly concerning issue as it reduces the practical utility of algorithms. To gain insights into this phenomenon, our research centers on individual traits, specifically focusing on familiarity with algorithms and familiarity with the task at hand, and their connections with attitudes toward algorithms. We construct a causal model to delve into these relationships and assess how attitudes, in turn, impact algorithm aversion. Our analysis draws upon data collected through an online survey involving 160 participants, and we employ PLS-SEM for our analysis. The results underscore a noteworthy positive correlation between familiarity with algorithms and attitudes toward algorithms. Interestingly, our findings indicate that familiarity with the task or domain knowledge does not significantly influence attitudes. Moreover, attitudes are demonstrated to have a negative impact on algorithm aversion. These discoveries hold significant implications for comprehending and addressing the issue of algorithm aversion. They shed light on the roles of individual traits and attitudes in shaping people's acceptance of algorithms, ultimately offering valuable insights for mitigating this phenomenon.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 79.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 99.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Bailey, D., Faraj, S., Hinds, P., von Krogh, G., Leonardi, P.: Special issue of organization science: emerging technologies and organizing. Organ. Sci. 30(3), 642–646 (2019). https://doi.org/10.1287/orsc.2019.1299

    Article  Google Scholar 

  2. Vrontis, D., Christofi, M., Pereira, V., Tarba, S., Makrides, A., Trichina, E.: Artificial intelligence, robotics, advanced technologies and human resource management: a systematic review. Int. J. Hum. Resour. Manag. 33, 1237–1266 (2022). https://doi.org/10.1080/09585192.2020.1871398

    Article  Google Scholar 

  3. Dietvorst, B.J., Simmons, J.P., Massey, C.: Algorithm aversion: people erroneously avoid algorithms after seeing them err. J. Exp. Psychol. Gen. 144, 114–126 (2015). https://doi.org/10.1037/xge0000033

    Article  Google Scholar 

  4. Mahmud, H., Islam, A.K.M.N., Ahmed, S.I., Smolander, K.: What influences algorithmic decision-making? A systematic literature review on algorithm aversion. Technol. Forecast. Soc. Change. 175, 121390 (2022). https://doi.org/10.1016/j.techfore.2021.121390

    Article  Google Scholar 

  5. Filiz, I., René Judek, J., Lorenz, M., Spiwoks, M.: The Tragedy of Algorithm Aversion. Ostfalia Hochschule für Angewandte Wissenschaften, Fakultät Wirtschaft (2021)

    Google Scholar 

  6. Fenneman, A., Sickmann, J., Pitz, T., Sanfey, A.G.: Two distinct and separable processes underlie individual differences in algorithm adherence: differences in predictions and differences in trust thresholds. PLOS ONE 16, e0247084 (2021). https://doi.org/10.1371/journal.pone.0247084

    Article  Google Scholar 

  7. Kawaguchi, K.: When will workers follow an algorithm? a field experiment with a retail business. Manag. Sci. 67, 1670–1695 (2021). https://doi.org/10.1287/mnsc.2020.3599

    Article  Google Scholar 

  8. Whitecotton, S.M.: The effects of experience and a decision aid on the slope, scatter, and bias of earnings forecasts. Organ. Behav. Hum. Decis. Process. 66, 111–121 (1996). https://doi.org/10.1006/OBHD.1996.0042

    Article  Google Scholar 

  9. Allen, R.T., Choudhury, P.: Algorithm-augmented work and domain experience: the countervailing forces of ability and aversion. Organ. Sci. 33, 149–169 (2022). https://doi.org/10.1287/orsc.2021.1554

    Article  Google Scholar 

  10. Logg, J.M., Minson, J.A., Moore, D.A.: Algorithm appreciation: people prefer algorithmic to human judgment. Organ. Behav. Hum. Decis. Process. 151, 90–103 (2019). https://doi.org/10.1016/j.obhdp.2018.12.005

    Article  Google Scholar 

  11. Ajzen, I.: The theory of planned behavior. Organ. Behav. Hum. Decis. Process. 50, 179–211 (1991). https://doi.org/10.1016/0749-5978(91)90020-T

    Article  Google Scholar 

  12. Fishbein, M., Ajzen, I.: Belief, attitude, intention, and behavior: an introduction to theory and research. Hilosophy Rhetor. 10, 130–132 (1977)

    Google Scholar 

  13. Wesche, J.S., Langer, M., Sonderegger, A., Landers, R.N.: Editorial to the virtual special issue: human-automation interaction in the workplace: a broadened scope of paradigms. Comput. Human Behav. 134, 107335 (2022). https://doi.org/10.1016/j.chb.2022.107335

    Article  Google Scholar 

  14. Mahmud, H., Islam, A.K.M.N., Mitra, R.K., Hasan, A.R.: The impact of functional and psychological barriers on algorithm aversion – an IRT perspective. In: Papagiannidis, S., Alamanos, E., Gupta, S., Dwivedi, Y.K., Mäntymäki, M., Pappas, I.O. (eds.) The Role of Digital Technologies in Shaping the Post-Pandemic World: 21st IFIP WG 6.11 Conference on e-Business, e-Services and e-Society, I3E 2022, Newcastle upon Tyne, UK, September 13–14, 2022, Proceedings, pp. 95–108. Springer International Publishing, Cham (2022). https://doi.org/10.1007/978-3-031-15342-6_8

    Chapter  Google Scholar 

  15. Mahmud, H., Islam, A.K.M.N., Mitra, R.K.: What drives managers towards algorithm aversion and how to overcome it? Mitigating the impact of innovation resistance through technology readiness. Technol. Forecast. Soc. Change. 193, 122641 (2023). https://doi.org/10.1016/j.techfore.2023.122641

    Article  Google Scholar 

  16. Gefen, D.: E-commerce: the role of familiarity and trust. Omega 28, 725–737 (2000). https://doi.org/10.1016/S0305-0483(00)00021-9

    Article  Google Scholar 

  17. Komiak, S.Y.X., Benbasat, I.: The effects of personalization and familiarity on trust and adoption of recommendation agents. MIS Q. Manag. Inf. Syst. 30, 941–960 (2006). https://doi.org/10.2307/25148760

    Article  Google Scholar 

  18. Sun, S., Wang, Y.: Familiarity, beliefs, attitudes, and consumer responses toward online advertising in China and the United States. J. Glob. Mark. 23, 127–138 (2010). https://doi.org/10.1080/08911761003673454

    Article  Google Scholar 

  19. Chen, J., Dibb, S.: Consumer trust in the online retail context: exploring the antecedents and consequences. Psychol. Mark. 27, 323–346 (2010). https://doi.org/10.1002/MAR.20334

    Article  Google Scholar 

  20. Husin, M.M., Aziz, S., Bhatti, T.: The impact of brand familiarity, perceived trust and attitude on investors’ decision-making in Islamic stock market. J. Islam. Mark. (2022). https://doi.org/10.1108/JIMA-04-2020-0093/FULL/HTML

    Article  Google Scholar 

  21. Dawar, N., Lei, J.: Brand crises: The roles of brand familiarity and crisis relevance in determining the impact on brand evaluations. J. Bus. Res. 62, 509–516 (2009). https://doi.org/10.1016/J.JBUSRES.2008.02.001

    Article  Google Scholar 

  22. Sharan, N.N., Romano, D.M.: The effects of personality and locus of control on trust in humans versus artificial intelligence. Heliyon. 6, e04572 (2020). https://doi.org/10.1016/J.HELIYON.2020.E04572

    Article  Google Scholar 

  23. Cao, G., Duan, Y., Edwards, J.S., Dwivedi, Y.K.: Understanding managers’ attitudes and behavioral intentions towards using artificial intelligence for organizational decision-making. Technovation 106, 102312 (2021). https://doi.org/10.1016/J.TECHNOVATION.2021.102312

    Article  Google Scholar 

  24. Berger, B., Adam, M., Rühr, A., Benlian, A.: Watch me improve—algorithm aversion and demonstrating the ability to learn. Bus. Inf. Syst. Eng. 63, 55–68 (2021). https://doi.org/10.1007/s12599-020-00678-5

    Article  Google Scholar 

  25. Luo, X., Tong, S., Fang, Z., Qu, Z.: Frontiers: machines vs. humans: the impact of artificial intelligence chatbot disclosure on customer purchases. Mark. Sci. 38, 913–1084, ii–ii (2019). https://doi.org/10.1287/mksc.2019.1192

  26. Gogoll, J., Uhl, M.: Rage against the machine: automation in the moral domain. J. Behav. Exp. Econ. 74, 97–103 (2018). https://doi.org/10.1016/J.SOCEC.2018.04.003

    Article  Google Scholar 

  27. Prahl, A., Swol, L.V.: Out with the humans, in with the machines?: investigating the behavioral and psychological effects of replacing human advisors with a machine. Hum.-Mach. Commun. 2, 209–234 (2021). https://doi.org/10.30658/hmc.2.11

    Article  Google Scholar 

  28. Duan, Y., Edwards, J.S., Dwivedi, Y.K.: Artificial intelligence for decision making in the era of Big Data – evolution, challenges and research agenda. Int. J. Inf. Manag. 48, 63–71 (2019). https://doi.org/10.1016/J.IJINFOMGT.2019.01.021

    Article  Google Scholar 

  29. Breward, M., Hassanein, K., Head, M.: Understanding consumers’ attitudes toward controversial information technologies: a contextualization approach. Inf. Syst. Res. 28, 760–774 (2017). https://doi.org/10.1287/isre.2017.0706

    Article  Google Scholar 

  30. Chau, P.Y.K., Lai, V.S.K.: An empirical investigation of the determinants of user acceptance of Internet banking An Empirical Investigation of the Determinants of User Acceptance of Internet Banking. J. Organ. Comput. Electron. Commer. 13, 123–145 (2003)

    Article  Google Scholar 

  31. Morris, M.G., Venkatesh, V.: Age differences in technology adoption decisions: implications for a changing work force. Pers. Psychol. 53, 375–403 (2000). https://doi.org/10.1111/J.1744-6570.2000.TB00206.X

    Article  Google Scholar 

  32. Whelan, E., Islam, A.K.M.N., Brooks, S.: Applying the SOBC paradigm to explain how social media overload affects academic performance. Comput. Educ. 143, 103692 (2020). https://doi.org/10.1016/J.COMPEDU.2019.103692

    Article  Google Scholar 

  33. Barclay, D., Higgins, C., Thompson, R.: The partial least squares (PLS) approach to causal modelling: personal computer adoption and use as an illustration. Technol. Stud. 2, 285–309 (1995)

    Google Scholar 

  34. Hair, J.F., Ringle, C.M., Sarstedt, M.: PLS-SEM: indeed a silver bullet. J. Mark. Theory Pract. 19, 139–152 (2011). https://doi.org/10.2753/MTP1069-6679190202

    Article  Google Scholar 

  35. Hair, J.F., Hult, G.T.M., Ringle, C.M., Sarstedt, M.: A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). Sage, Thousand Oaks (2017)

    Google Scholar 

  36. Kock, N.: One-tailed or two-tailed P values in PLS-SEM? Int. J. E-Collab. 11, 1–7 (2015). https://doi.org/10.4018/IJEC.2015040101

    Article  Google Scholar 

  37. Gefen, D., Straub, D., Gefen, D., Straub, D.: A practical guide to factorial validity using PLS-Graph: tutorial and annotated example. Commun. Assoc. Inf. Syst. 16, 91–109 (2005). https://doi.org/10.17705/1CAIS.01605

    Article  Google Scholar 

  38. Fornell, C., Larcker, D.F.: Evaluating structural equation models with unobservable variables and measurement error. J. Mark. Res. 18, 39–50 (1981). https://doi.org/10.1177/002224378101800104

    Article  Google Scholar 

  39. Gefen, D., Straub, D.W.: Consumer trust in B2C e-Commerce and the importance of social presence: Experiments in e-Products and e-Services. Omega 32, 407–424 (2004). https://doi.org/10.1016/J.OMEGA.2004.01.006

    Article  Google Scholar 

  40. Copeland, L., Bhaduri, G.: Consumer relationship with pro-environmental apparel brands: effect of knowledge, skepticism and brand familiarity. J. Prod. Brand. Manag. 29, 1–14 (2020). https://doi.org/10.1108/JPBM-03-2018-1794/FULL/HTML

    Article  Google Scholar 

  41. Sieck, W.R., Arkes, H.R.: The recalcitrance of overconfidence and its contribution to decision aid neglect. J. Behav. Decis. Mak. 18, 29–53 (2005). https://doi.org/10.1002/BDM.486

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. LUT University, Lappeenranta, Finland

    Hasan Mahmud & Najmul Islam

Authors
  1. Hasan Mahmud
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Najmul Islam
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hasan Mahmud .

Editor information

Editors and Affiliations

  1. Delft University of Technology, Delft, The Netherlands

    Marijn Janssen

  2. Positivo University, Curitiba, Paraná, Brazil

    Luiz Pinheiro

  3. Delft University of Technology, Delft, The Netherlands

    Ricardo Matheus

  4. Positivo University, Curitiba, Paraná, Brazil

    Fernanda Frankenberger

  5. Swansea University, Swansea, UK

    Yogesh K. Dwivedi

  6. University of Agder, Kristiansand, Norway

    Ilias O. Pappas

  7. University of Turku, Turku, Finland

    Matti Mäntymäki

Rights and permissions

Reprints and permissions

Copyright information

© 2023 IFIP International Federation for Information Processing

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Mahmud, H., Islam, N. (2023). The Role of Algorithm and Task Familiarity in Algorithm Aversion: An Empirical Study. In: Janssen, M., et al. New Sustainable Horizons in Artificial Intelligence and Digital Solutions. I3E 2023. Lecture Notes in Computer Science, vol 14316. Springer, Cham. https://doi.org/10.1007/978-3-031-50040-4_1

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-50040-4_1

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-50039-8

  • Online ISBN: 978-3-031-50040-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Societies and partnerships

Search

Navigation