PARTICIPANT INFORMATION
About this study
Agentic AI Adoption and Perceived Workflow Productivity in Logistics: The Roles of Trust in AI and AI Governance
This doctoral research examines how agentic AI adoption is associated with perceived workflow productivity in logistics through trust in AI, and whether AI governance moderates the relationship between adoption and trust.
Who can participate?
Professionals with direct experience of an agentic AI-enabled logistics workflow in current operational use or an active pilot involving real users or operational cases. You will need sufficient knowledge of implementation, operational use, governance and workflow performance. Screening determines eligibility.
What does agentic AI mean here?
For this survey, agentic AI refers to an AI-enabled system or digital agent that can work toward a human-defined goal by interpreting context, planning or sequencing tasks, interacting with digital tools or data sources, coordinating multi-step workflows, and recommending or initiating task-related outputs or workflow steps with varying levels of task autonomy.
Governance arrangements, approval rules, accountability, monitoring and human oversight are assessed separately. They are not required for a system to qualify as agentic AI.
What will I be asked to do?
Complete a structured online questionnaire lasting approximately 8–12 minutes. Think about the same focal workflow throughout. There are no right or wrong answers. An optional final question invites a brief comment; please omit names, employer names and confidential information.
Complete the questionnaire online
Answer each step directly on this website using a phone, tablet or computer. No login or download is needed. When data collection is open, your answers are sent to the researcher only when you submit the form. Questionnaire previews do not save responses.
Participation and privacy
Participation is voluntary and has no effect on your employment or relationship with the researcher. You may stop at any time before submitting. Screening answers are saved only if you choose to submit them; no survey answers are sent while you are filling in the form.
The research dataset does not record your name, email address, exact employer, IP address or account identity. Answers are stored securely for academic research and reported in aggregate. Access to research data is restricted to the researcher and, where required, academic reviewers. Technical hosting and sign-in services may process connection or account information separately from the research dataset.
A temporary draft stays in this browser tab so you can move back and forth. Leaving through “Exit without submitting” removes it. As the research responses are anonymous, an individual response cannot reliably be identified for withdrawal after submission.
Ethics approval
Ethics approval dated 25 October 2026. Reference: JS19589/DBAODL/RES811/1026.
Research contact
Samdavid Jeyaraj — Doctoral researcher
JS19589@campus.globalnxt.edu.my