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The effect of transparency and trust on intelligent system acceptance: Evidence from a user-based study

Author

Listed:
  • Jonas Wanner

    (Julius-Maximilians-Universität Würzburg)

  • Lukas-Valentin Herm

    (Julius-Maximilians-Universität Würzburg)

  • Kai Heinrich

    (Otto-von-Guericke-Universität Magdeburg)

  • Christian Janiesch

    (TU Dortmund University)

Abstract

Contemporary decision support systems are increasingly relying on artificial intelligence technology such as machine learning algorithms to form intelligent systems. These systems have human-like decision capacity for selected applications based on a decision rationale which cannot be looked-up conveniently and constitutes a black box. As a consequence, acceptance by end-users remains somewhat hesitant. While lacking transparency has been said to hinder trust and enforce aversion towards these systems, studies that connect user trust to transparency and subsequently acceptance are scarce. In response, our research is concerned with the development of a theoretical model that explains end-user acceptance of intelligent systems. We utilize the unified theory of acceptance and use in information technology as well as explanation theory and related theories on initial trust and user trust in information systems. The proposed model is tested in an industrial maintenance workplace scenario using maintenance experts as participants to represent the user group. Results show that acceptance is performance-driven at first sight. However, transparency plays an important indirect role in regulating trust and the perception of performance.

Suggested Citation

  • Jonas Wanner & Lukas-Valentin Herm & Kai Heinrich & Christian Janiesch, 2022. "The effect of transparency and trust on intelligent system acceptance: Evidence from a user-based study," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(4), pages 2079-2102, December.
    • Handle: RePEc:spr:elmark:v:32:y:2022:i:4:d:10.1007_s12525-022-00593-5
    DOI: 10.1007/s12525-022-00593-5
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    1. Nicolas Pfeuffer & Alexander Benlian & Henner Gimpel & Oliver Hinz, 2019. "Anthropomorphic Information Systems," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 61(4), pages 523-533, August.
    2. Nicolas Pfeuffer & Alexander Benlian & Henner Gimpel & Oliver Hinz, 2019. "Anthropomorphic Information Systems," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 61(4), pages 523-533, August.
    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. Kim, Yong Jin & Chun, Jae Uk & Song, Jaeki, 2009. "Investigating the role of attitude in technology acceptance from an attitude strength perspective," International Journal of Information Management, Elsevier, vol. 29(1), pages 67-77.
    5. Yogesh K. Dwivedi & Nripendra P. Rana & Anand Jeyaraj & Marc Clement & Michael D. Williams, 2019. "Re-examining the Unified Theory of Acceptance and Use of Technology (UTAUT): Towards a Revised Theoretical Model," Information Systems Frontiers, Springer, vol. 21(3), pages 719-734, June.
    6. Shahzad, Fakhar & Xiu, Guoyi & Shafique Khan, Muhammad Aamir & Shahbaz, Muhammad, 2020. "Predicting the adoption of a mobile government security response system from the user's perspective: An application of the artificial neural network approach," Technology in Society, Elsevier, vol. 62(C).
    7. Scott Thiebes & Sebastian Lins & Ali Sunyaev, 2021. "Trustworthy artificial intelligence," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(2), pages 447-464, June.
    8. Christian Janiesch & Patrick Zschech & Kai Heinrich, 2021. "Machine learning and deep learning," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(3), pages 685-695, September.
    9. Gary C. Moore & Izak Benbasat, 1991. "Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation," Information Systems Research, INFORMS, vol. 2(3), pages 192-222, September.
    10. Baishya, Kuldeep & Samalia, Harsh Vardhan, 2020. "Extending unified theory of acceptance and use of technology with perceived monetary value for smartphone adoption at the bottom of the pyramid," International Journal of Information Management, Elsevier, vol. 51(C).
    11. Viswanath Venkatesh, 2022. "Adoption and use of AI tools: a research agenda grounded in UTAUT," Annals of Operations Research, Springer, vol. 308(1), pages 641-652, January.
    12. Anders Persson & Mikael Laaksoharju & Hiroshi Koga, 2021. "We Mostly Think Alike: Individual Differences in Attitude Towards AI in Sweden and Japan," The Review of Socionetwork Strategies, Springer, vol. 15(1), pages 123-142, June.
    13. Oliveira, Tiago & Faria, Miguel & Thomas, Manoj Abraham & Popovič, Aleš, 2014. "Extending the understanding of mobile banking adoption: When UTAUT meets TTF and ITM," International Journal of Information Management, Elsevier, vol. 34(5), pages 689-703.
    14. D. Harrison McKnight & Vivek Choudhury & Charles Kacmar, 2002. "Developing and Validating Trust Measures for e-Commerce: An Integrative Typology," Information Systems Research, INFORMS, vol. 13(3), pages 334-359, September.
    15. Xinshu Zhao & John G. Lynch & Qimei Chen, 2010. "Reconsidering Baron and Kenny: Myths and Truths about Mediation Analysis," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 37(2), pages 197-206, August.
    16. Mahmud, Hasan & Islam, A.K.M. Najmul & Ahmed, Syed Ishtiaque & Smolander, Kari, 2022. "What influences algorithmic decision-making? A systematic literature review on algorithm aversion," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    17. David Silver & Aja Huang & Chris J. Maddison & Arthur Guez & Laurent Sifre & George van den Driessche & Julian Schrittwieser & Ioannis Antonoglou & Veda Panneershelvam & Marc Lanctot & Sander Dieleman, 2016. "Mastering the game of Go with deep neural networks and tree search," Nature, Nature, vol. 529(7587), pages 484-489, January.
    18. Joel Mokyr & Chris Vickers & Nicolas L. Ziebarth, 2015. "The History of Technological Anxiety and the Future of Economic Growth: Is This Time Different?," Journal of Economic Perspectives, American Economic Association, vol. 29(3), pages 31-50, Summer.
    19. Peters, Felix & Pumplun, Luisa & Buxmann, Peter, 2020. "Opening the Black Box: Consumer's Willingness to Pay for Transparency of Intelligent Systems," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 120853, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    20. Narasimha S. Paravastu & Sam S. Ramanujan, 2021. "Interpersonal Trust and Technology Trust in Information Systems Research: A Comprehensive Review and A Conceptual Model," International Journal of Information Systems and Social Change (IJISSC), IGI Global, vol. 12(4), pages 44-61, October.
    21. Shin, Donghee & Zhong, Bu & Biocca, Frank A., 2020. "Beyond user experience: What constitutes algorithmic experiences?," International Journal of Information Management, Elsevier, vol. 52(C).
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    Cited by:

    1. Lukas-Valentin Herm & Theresa Steinbach & Jonas Wanner & Christian Janiesch, 2022. "A nascent design theory for explainable intelligent systems," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(4), pages 2185-2205, December.
    2. Roman Lukyanenko & Wolfgang Maass & Veda C. Storey, 2022. "Trust in artificial intelligence: From a Foundational Trust Framework to emerging research opportunities," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(4), pages 1993-2020, December.

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    More about this item

    Keywords

    User acceptance; Intelligent system; Artificial intelligence; Trust; System transparency;
    All these keywords.

    JEL classification:

    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
    • M15 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - IT Management

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