Anna Yu. Akimova

Background. The spatial aspect of professionals’ trust and distrust in socio-technical systems has not been sufficiently explored. The study of its structure, criteria for spatial distribution, and interrelationships of elements is of both scientific and practical interest.

Objective. To perform a comparative analysis of the trust and distrust experienced by professional operators in a socio-technical system of subject–subject and subject–object interactions.

Design. This work is based on A.B. Kupreychenko’s methodological approach to studying trust and distrust in socio-technical systems, adapted by the authors to the railway transport system in Russia. The subjects were 86 locomotive crew members. The main focus was on their trust/distrust in the operation of the socio-technical (railway transport) system, including their workmates, managers, and themselves, as well as the technical objects they operate (locomotives), manufacturers of railway equipment, and conditions of its operation.

Results. The authors identified two relatively independent groups of indicators of trust/distrust in subject–subject and subject–object interactions. Trust in the elements of subject–subject interactions (involving workmates, managers, and the study participants themselves as specialists) was reliably higher than their trust in the elements of subject–object interactions (technical objects, manufacturers of railway equipment, and conditions of its operation). The correlations between trust and distrust in the elements of the socio-technical system were positive.

Conclusions. Trust and distrust perform the functions of integrating/differentiating elements of a socio-technical system according to their predictability in various operating conditions. The degree of trust/distrust in the system elements and their “location” in the space of trust/distrust are important when professionals make decisions in the course of performing professional actions. The results of the study can be used for designing socio-technical systems to increase the predictability of their operation in unstable conditions.