Paper Type
Complete
Abstract
As organizations transition from intuition-based to data-driven decision-making, building trust emerges as a critical yet complex sociotechnical challenge. While prior research recognizes the importance of trust for technology adoption and effective data use, it has not delineated the specific dimensions that underpin data-driven decision-making. To address this gap, we conduct an interpretive case study of a major South African insurance company to explore how trust is constructed across multiple levels. Our findings reveal five interrelated dimensions—institution-based trust, relational trust, trust in systems, trust in data, and trust in data-driven insights—that collectively shape decision-makers’ trust and influence the adoption of data-driven decision-making. We propose a multi-level trust framework that combines technological capabilities with social and institutional perspectives, highlighting the nested and dynamic nature of trust-building in this context. The framework offers actionable guidance for managers navigating data-driven transformations and contributes to the information systems literature by conceptualizing trust as a multidimensional, evolving construct within sociotechnical systems.
Paper Number
1413
Recommended Citation
Oosterwyk, Grant; Elo, Jenny; and Watkowski, Laura, "Building Trust in Data-Driven Decision-Making: A Multi-Level Framework" (2025). AMCIS 2025 Proceedings. 12.
https://aisel.aisnet.org/amcis2025/data_science/sig_dsa/12
Building Trust in Data-Driven Decision-Making: A Multi-Level Framework
As organizations transition from intuition-based to data-driven decision-making, building trust emerges as a critical yet complex sociotechnical challenge. While prior research recognizes the importance of trust for technology adoption and effective data use, it has not delineated the specific dimensions that underpin data-driven decision-making. To address this gap, we conduct an interpretive case study of a major South African insurance company to explore how trust is constructed across multiple levels. Our findings reveal five interrelated dimensions—institution-based trust, relational trust, trust in systems, trust in data, and trust in data-driven insights—that collectively shape decision-makers’ trust and influence the adoption of data-driven decision-making. We propose a multi-level trust framework that combines technological capabilities with social and institutional perspectives, highlighting the nested and dynamic nature of trust-building in this context. The framework offers actionable guidance for managers navigating data-driven transformations and contributes to the information systems literature by conceptualizing trust as a multidimensional, evolving construct within sociotechnical systems.
When commenting on articles, please be friendly, welcoming, respectful and abide by the AIS eLibrary Discussion Thread Code of Conduct posted here.
Comments
SIGDSA