Enhancing data governance through transparency

An empirical study of the data trust model

Dados Bibliográficos

ID21404358
AutoresYei Jin Kim (Korea Research Institute for Construction Policy), Young Soo Park (0000-0002-6315-3309, Kookmin University), Sung-Pil Park (Korea Research Institute for Construction Policy, autor correspondente)
Ano2026
Volume225
Páginas124551
Data de publicação2026-04-01
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoTechnological Forecasting and Social Change (JOURNAL)
Identificadores do periódicoISSN: 0040-1625 • E-ISSN: 1873-5509
EditoraElsevier BV (PUBLISHER)
DOI10.1016/j.techfore.2026.124551
OpenAlexW7125903864
IdiomaEN
Citações recebidas1
Referências citadas212

As data-driven ecosystems expand, the Data Trust Model (DTM) has gained attention as a governance framework for secure transactions, yet adoption remains uncertain due to high information asymmetry and the dual burden of evaluating asset quality and transactional risk. Prior research has largely emphasized supply-side institutional design, treating transparency as a monolithic construct and overlooking user heterogeneity. To address these limitations, this study develops a context-specific model integrating the Technology Acceptance Model (TAM) and Theory of Planned Behavior (TPB). Transparency is bifurcated into Perceived Data Transparency (adverse selection) and Perceived Transaction Transparency (moral hazard) within an Agency Theory framework. The model is tested using Partial Least Squares Structural Equation Modeling (PLS-SEM) and Multi-Group Analysis (MGA) based on data from 400 potential users. Results show that transparency operates as a conditional enabler mediated by attitude rather than a direct driver. MGA further reveals systematic heterogeneity: experienced users rely more heavily on institutional signals—reputation, security, and warranty—when forming perceptions. Theoretically, this study integrates Agency and Signaling Theories to explain adoption under uncertainty. Practically, findings highlight the need for differentiated transparency mechanisms tailored to user experience. • This study examines the factors that shape user acceptance of the DTM. • Integrating TPB and TAM, the authors analyzed survey responses on data provider preferences. • Transparency in data transactions is crucial for enabling the use of DTM. • Findings highlight the need to distinguish between the perceptions of data providers and licensees. • Research emphasizes the trustee's reputation in shaping perceptions of data transparency

Corporate governance · Credence · Data quality · Database transaction · Empirical research · Reputation · Structural equation modeling · Survey data collection · Theory of planned behavior · Transparency (behavior) · Big Data and Business Intelligence · Privacy, Security, and Data Protection · Technology Adoption and User Behaviour