Effects of Data Exchange Methods on Perceived Risk and Trust in Digital Engineering

Abstract

Data exchange is a critical part of collaborative design and digital engineering. Design teams need effective communication to exchange vital information and achieve desired outcomes. Literature shows high data quality is matched with higher levels of trust and lower levels of perceived risk which influence design decisions. This paper conducts a survey of industry professionals as a preliminary investigation of how data exchange methods implemented in digital engineering affect perceived trust and risk levels of engineers. The survey adopts questions from the Technology Acceptance Model (TAM) and Unified Theory of Acceptance and Use of Technology (UTAUT2) questionnaires to measure risk and trust perception in digital engineering environments for three data exchange methods and interfaces: direct data integration, air-gapped import and export, and semantic data exchange. Survey results show engineers have different trust and perceived risk levels towards different data exchange methods. Engineers behavioral intentions towards using a data exchange method depend on perceiving the method as less risky and trustworthy. Understanding how data exchange methods and interfaces impact engineers' trust and risk perception can inform effective implementation of digital engineering and lead to more successful collaborative engineering design projects.