Understanding human performance in sociotechnical systems – steps towards a generic framework

Humans, their performance, actions and decisions play a significant role in a vast range of operations in complex sociotechnical systems. Numerous studies have therefore endeavoured to understand people's actions and/or inactions within their working environment and to identify those factors, a...

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Bibliographic Details
Main Authors: Kyriakidis, Miltos, Kant, Vivek, Amir, Sulfikar, Dang, Vinh N.
Other Authors: School of Social Sciences
Format: Journal Article
Language:English
Published: 2020
Subjects:
Online Access:https://hdl.handle.net/10356/138357
Description
Summary:Humans, their performance, actions and decisions play a significant role in a vast range of operations in complex sociotechnical systems. Numerous studies have therefore endeavoured to understand people's actions and/or inactions within their working environment and to identify those factors, also known as Performance Shaping Factors (PSFs), that contribute either positively or negatively to sociotechnical system performance. However, the majority of those studies are often created based on data and research derived from a specific domain, and therefore are difficult to apply beyond the domain of interest. Thus, this paper presents a generic framework to develop a standardised list of PSFs, referred to as (Cross-Sectoral Performance Shaping Factors, C-PSFs), to be used across sectors to describe the immediate and latent factors that affect human performance in a structured and consistent manner. Building upon the existing Railway-Performance Shaping Factors taxonomy and the fundamental concepts of Cognitive and Behavioral Science, the new C-PSFs taxonomy illustrates the numerous possible interdependencies between the human operator and a system's constraints. The former provides the empirical evidence for the C-PSFs taxonomy's generic factors, while the latter justifies the transferability and applicability of the taxonomy to a broad range of sociotechnical sectors. The analysis of two accidents, from the railway and energy sectors, support such evidence. The proposed taxonomy provides a common baseline set of PSFs across sectors and its usage can greatly improve safety management systems of cross-sectoral organisations.