Psychological and Physiological Mechanisms in the Workplace: An ERP Study on Risky Decision-Making of Safety Behaviors Among Industrial Employees

DOI: https://doi.org/10.62517/jsse.202608303

Author(s)

Jingyuan Li*

Affiliation(s)

School of Economics and Business Administration, Heilongjiang University, Harbin, China *Corresponding Author

Abstract

Even with highly automated modern human-machine systems, safety accidents persist, largely stemming from operators’ unsafe behaviors. Heavy cognitive loads from multi-sensory information processing on human-machine interfaces impair workers’ judgment. From psychological and cognitive perspectives, employees can be divided into high-, moderate- and low-proactivity groups, whose safety performance varies markedly. It is practically valuable to develop targeted interventions to reduce unsafe behaviors based on proactivity traits. This research explores cognitive neural disparities in safety risk decision-making among workers with different proactivity levels. The study adapted the Iowa Gambling Task to simulate industrial safety decision scenarios and recorded participants’ event-related potential (ERP) signals throughout experiments. Feedback-related negativity (FRN) and P300, two core neural indicators for outcome evaluation and risk processing, served as electrophysiological markers. Drawing on existing theories of proactivity and safety cognition, testable hypotheses were proposed to uncover neural patterns behind safety risk judgments. ERP analyses confirmed all hypotheses. Under rewarding feedback, high-proactivity individuals produced larger P300 amplitudes. When facing loss-related negative feedback, low-proactivity participants showed the strongest FRN responses, with gaps widening under high-risk settings; all differences were statistically significant. In conclusion, proactivity drives notable cognitive neural divergences in safety risk decision-making and shapes neural reactions during risk evaluation. These results support enterprises in safeguarding staff wellbeing, improving person-job fit, refining incentive systems, and comprehensively boosting workplace safety management.

Keywords

Safety Management; ERP Experiment; Safety Behavior; Risky Decision-Making; Human-Machine Interaction

References

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