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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Main Authors: Kyriakidis, Miltos, Kant, Vivek, Amir, Sulfikar, Dang, Vinh N.
Other Authors: School of Social Sciences
Format: Article
Language:English
Published: 2020
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Online Access:https://hdl.handle.net/10356/138357
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1383572020-05-04T04:17:58Z Understanding human performance in sociotechnical systems – steps towards a generic framework Kyriakidis, Miltos Kant, Vivek Amir, Sulfikar Dang, Vinh N. School of Social Sciences Institute of Catastrophe Risk Management (ICRM) Social sciences::Sociology Human Factors & Human Performance Sociotechnical Systems 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. NRF (Natl Research Foundation, S’pore) 2020-05-04T04:17:52Z 2020-05-04T04:17:52Z 2017 Journal Article Kyriakidis, M., Kant, V., Amir, S., & Dang, V. N. (2018). Understanding human performance in sociotechnical systems – steps towards a generic framework. Safety Science, 107, 202-215. doi:10.1016/j.ssci.2017.07.008 0925-7535 https://hdl.handle.net/10356/138357 10.1016/j.ssci.2017.07.008 2-s2.0-85025169290 107 202 215 en Safety Science © 2017 Elsevier Ltd. All rights reserved.
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic Social sciences::Sociology
Human Factors & Human Performance
Sociotechnical Systems
spellingShingle Social sciences::Sociology
Human Factors & Human Performance
Sociotechnical Systems
Kyriakidis, Miltos
Kant, Vivek
Amir, Sulfikar
Dang, Vinh N.
Understanding human performance in sociotechnical systems – steps towards a generic framework
description 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.
author2 School of Social Sciences
author_facet School of Social Sciences
Kyriakidis, Miltos
Kant, Vivek
Amir, Sulfikar
Dang, Vinh N.
format Article
author Kyriakidis, Miltos
Kant, Vivek
Amir, Sulfikar
Dang, Vinh N.
author_sort Kyriakidis, Miltos
title Understanding human performance in sociotechnical systems – steps towards a generic framework
title_short Understanding human performance in sociotechnical systems – steps towards a generic framework
title_full Understanding human performance in sociotechnical systems – steps towards a generic framework
title_fullStr Understanding human performance in sociotechnical systems – steps towards a generic framework
title_full_unstemmed Understanding human performance in sociotechnical systems – steps towards a generic framework
title_sort understanding human performance in sociotechnical systems – steps towards a generic framework
publishDate 2020
url https://hdl.handle.net/10356/138357
_version_ 1681056307709214720