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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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    Cited by:

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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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