513. The impact of explainability and relationships on trust in AI for supplier compliance
Invited abstract in session TC-61: Behaviour in information systems, stream Behavioural OR.
Tuesday, 12:30-14:00Room: Maurice Keyworth G.31
Authors (first author is the speaker)
| 1. | Daniel Sanchez-Loor
|
| Department of International Business, Chung Yuan Christian University |
Abstract
AI technologies offer significant potential to enhance decision-making by augmenting human capacity and automating processes, such as evaluating supplier contract compliance. While these technologies promise efficiency, concerns about the opacity of AI reasoning and its impact on established human relationships remain unresolved. This study investigates how pre-existing supplier relationships and AI explainability influence user trust in AI decisions and empowerment. Using actor-network theory and agency theory, hypotheses are tested through a factorial survey experiment manipulating supplier relationship tenure and explainability. A pilot study of 105 professionals familiar with generative AI reveals that both relationship tenure and explainability positively affect trust and empowerment. Empowerment partially mediates the relationship between trust and intention to use AI, highlighting the need to translate trust into user confidence. However, longer supplier relationships negatively moderate the link between trust and empowerment, suggesting resistance in well-established supplier relationships. Practitioners could address these reservations by tailoring explanations to foster trust and promote the effective adoption of AI technologies in supplier compliance.
Keywords
- Behavioural OR
- Artificial Intelligence
- Supply Chain Management
Status: accepted
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