User and Stakeholder Acceptance Analysis of Automated Road Transport Logistics Systems

Abstract

Role of humans in industry is changing due to novel automated vehicles [1]. Technology acceptance (TA) refers to the user’s motivation to use a technological solution. Technology Acceptance Model [2] proposed perceived usefulness and ease of use as important factors in TA. Expanding on that, the latest model ARTLAM [3] was constructed. It will be the foundation of our work, with slight adjustments made by my colleagues. As it has not yet been used in a study where participants would be exposed to a technological solution, this will be one of the contributions of this thesis. Perceived usefulness, ease of operation, supporting conditions, safety, security, reliability, and public acceptance are proposed as factors of TA. I will explore underlying factors of TA based on data from employees who were faced with a technological solution (experiences of usage) and compare it with underlying factors based on data from employees who were not (expectations before usage).

Method

I will conduct a survey measuring factors of TA in two groups of participants. The target population will be various employees in the logistics industry. Data for the first group (expectation) was already gathered and analyzed. Second group (experience) will be exposed to a Fleet Management System (FMS), which is a software for remote operation (scheduling tasks and resolving issues) of logistics vehicle fleets. Interviews will be carried out. I will perform multiple regression analysis on the data, thus identifying underlying factors of TA based on experiences and compare them with expectations. Interdisciplinarity will be ensured by researching a psychological construct (TA) and embedding the results in predictive processing framework.

Expected Results

I expect to identify usefulness and ease of use as significant antecedents of experience as they have already turned out to be important factors of TA [2]. I expect that reliability and supporting conditions will not be significant antecedents of experience as they refer to aspects of TA that will not be brought to participants’ attention. I hope that this framework will have implications in introduction of novel technologies.

References

[1] C. Cimini, A. Lagorio, D. Romero, S. Cavalieri, and J. Stahre, “Smart Logistics and the logistics operator 4.0,” IFAC-PapersOnLine, vol. 53, no. 2, pp. 10615–10620, 2020.

[2] F. D. Davis, “A technology acceptance model for empirically testing new end-user information systems: Theory and results,” dissertation, Massachusetts Institute of Technology, 1985.

[3] P. Fröhlich, M. Gafert, L. Diamond, M. Reinthaler, M. Neubauer, F. Hammer, and S. Koskinen, “Towards a Comprehensive Understanding of Stakeholder Requirements for Automated Road Transport Logistics,” In Proceedings of the Workshop on Automation Experience at the Workplace co-located with the ACM Conference on Human Factors in Computing Systems (CHI 2021), 2021.