•We present a novel approach (HuPeROI) to quantify the impact of PSFs on human performance.•The HuPeROI can also be used to assess human performance in relation to the quality of the PSFs.•The methodology is developed and tested with subject matter experts and train operating personnel for three mainline railway scenarios.•Regulatory bodies can integrate the approach within their SMS to improve railway safety.•The HuPerOI approach is transferrable to any safety critical industry. Human error and degraded human performance are associated with more than 80% of all railway accidents worldwide. Research on human performance and human reliability has highlighted the importance of the contextual factors associated with human errors, known as performance shaping factors (PSFs). A major shortcomings of current Human Reliability Analysis techniques, which employ qualitative and quantitative methods for assessing the human contribution to risk, lies with their little capability to model the dependencies among PSFs and to quantify their impact on human performance. This paper presents a novel approach to assess human performance accounting for the dependencies among the relevant PSFs, referred to as Human Performance Railway Operational Index (HuPeROI). The HuPeROI is developed on the integration of the Analytic Network Process and Success Likelihood Index Methodology, using the insights of 52 front-line, managerial and human factors railway personnel, and was demonstrated in three different types of railway operations: regional, high-speed and underground. Findings show that the HuPeROI can be efficiently used to assess operators’ performance as function of the quality of the relevant R-PSFs. Regulatory bodies and other stakeholders can implement the framework within their safety management systems to improve safety of railway operations.
Purpose - Human resources have become a key issue in relation to the strong competition between service firms. Therefore, the purpose of this paper is to explore the relationship between high-performance human resource management (HRM) within this field to firm performance, making a useful attempt to explore the "black box" of enterprise human resources management effect on firm performance. Design/methodology/approach - In order to validate the relationship between high-performance HRM and firm performance, Chinese service industry samples were collected. Structural equation modeling and regression are adopted to estimate the direct effect of high-performance HRM on firm performance and the mediating role of innovation. Findings - The results show that the impacts of high-performance HRM on firm performance are significant. Moreover, innovation plays a partial mediating role between them. Training, work analysis and employee participation has a significantly positive impact on firm performance, while effects of profit sharing, employee development and performance evaluation on enterprise performance is not significant. The results strongly support the hypothesis that innovation holds intermediary variables between high-performance HRM and firm performance. Practical implications - Studying the relationship between high-performance HRM and firm performance can help Chinese enterprises more reasonable and effective learning foreign advanced management ideas and methods. And then can help Chinese enterprises to establish a high-performance HRM system that is suitable for Chinese enterprises; the research can help enterprises to identify meaningful practice of human resources management, outstanding keys, and perfect the HRM system of enterprises; research on innovation and innovative thinking is conducive to develop employees' innovation motive, promote employee' innovative behavior, and improve firm performance. Originality/value - This paper takes innovation as a mediating variable into the model and studies the intermediary role of innovation.
Red coloration is a sexually selected, testosterone-dependent signal of male quality in a variety of animals, and in some non-human species a male's dominance can be experimentally increased by attaching artificial red stimuli. Here we show that a similar effect can influence the outcome of physical contests in humans - across a range of sports, we find that wearing red is consistently associated with a higher probability of winning. These results indicate not only that sexual selection may have influenced the evolution of human response to colours, but also that the colour of sportswear needs to be taken into account to ensure a level playing field in sport.
•We present a generic framework to create a standardized cross-sectoral list of PSFs.•The C-PSFs taxonomy is grounded in cognitive and behavioural theory.•The relation between C-PSFs and the empirical R-PSFs is examined in case studies.•This demonstrates the coherence and compatibility of the C-PSFs and R-PSFs taxonomies. 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.
Millions of individuals routinely remain awake for more than 18 h daily, which causes performance decrements. It is unknown if these functional impairments are the result of that extended wakefulness or from the associated shortened sleep durations. We therefore examined changes in objective reaction time performance and subjective alertness in a 32-d inpatient protocol in which participants were scheduled to wakefulness durations below 16 h while on a 20-h "day," with randomization into standard sleep: wake ratio (1: 2) or chronic sleep restriction (CSR) ratio (1: 3.3) conditions. This protocol allowed determination of the contribution of sleep deficiency independent of extended wakefulness, since individual episodes of wakefulness in the CSR condition were only 15.33 h in duration (less than the usual 16 h of wakefulness in a 24-h day) and sleep episodes were 4.67 h in duration each cycle. We found that chronic short sleep duration, even without extended wakefulness, doubled neurobehavioral reaction time performance and increased lapses of attention fivefold, yet did not uniformly decrease self-reported alertness. Further, these impairments in neurobehavioral performance were worsened during the circadian night and were not recovered during the circadian day, indicating that the deleterious effect from the homeostatic buildup of CSR is expressed even during the circadian promotion of daytime arousal. These findings reveal a fundamental aspect of human biology: Chronic insufficient sleep duration equivalent to 5.6 h of sleep opportunity per 24 h impairs neurobehavioral performance and self-assessment of alertness, even without extended wakefulness.
Purpose - This paper aims to advance the current debates on the effect of performance measurement (PM) in the operations management domain. In order to accomplish that, it investigates the contribution of business PM and human resource management (HRM) practices to business performance. Design/methodology/approach - The paper is based on ten case studies conducted across both manufacturing and service organisations capturing evidence from both the human resource function and line management. Findings - In the PM and HRM literatures, there is a debate about the contribution these practices make to the overall performance of the organisation. In particular, the results from the PM literature are inconclusive. This paper argues that performance is a result of employee engagement and that the PM system is a communication and guiding mechanism, which if implemented well and used appropriately, can channel the efforts of employees striving to perform. Originality/value - This paper contradicts the performance drivers approach to PM by providing new insights into the roles PM and HRM practices play in delivering business performance. Additionally, the paper develops a set of propositions as a means of clearly stating the findings and for encouraging future research in this area.
This article responds to recent calls for research examining the mechanisms through which high‐performance human resource practices (HPHRPs) affect employee outcomes. Using the theoretical lens of social exchange and process theories, the authors examine one such mechanism, public service motivation, through which HPHRPs influence employees’ affective commitment and organizational citizenship behaviors in public sector organizations. A sample of professionals in the Egyptian health and higher education sectors was used to test a partial mediation model using structural equation modeling. Findings show that public service motivation partially mediated the relationship between HPHRPs and employees’ affective commitment and organizational citizenship behaviors. Similar results were achieved when the system of HPHRPs was disaggregated to consider the individual effects of five human resource practices.
75–96% of maritime accidents are caused by human and organizational factors. Seafarers' emotion may degrade the effectivity of human behavior when tasks in onboard environment are complex and demanding. This study was concerned with the relationship between seafarers' emotion and occurring events in navigation. The Electroencephalogram (EEG) and Self-Assessment Manikin (SAM) scale rating are used to investigate the occurrence and impact of seafarers' emotions on their performance using a bridge simulator. The study was conducted and described in two sections: emotion calibration and test recognition. In the first section, two types of emotions are induced by the sound clips of the International Affective Digitized Sounds (IADS), developed by the National Institute of Mental Health Center for the Study of Human Emotions. In the second section, emotion is recognized by the Support Vector Machine (SVM) classifier, as well as self-rated after the crew-qualified test in a bridge simulator. The results indicate that SVM can identify the emotions by EEG feature extraction, with an accuracy of 77.55%. The results concerning officers' emotion in a bridge simulator test reveal that seafarers’ emotion in maritime operations, relating to events exposure, affects their behavior and decision-making. In addition, negative emotion has a higher likelihood of contributing to human errors than positive emotion. Less negative emotion is the most dangerous emotion state during navigation, followed by extreme positive emotion. •Seafarers' emotion and their performance in operations in the bridge simulator revealed significant correlations.•The brain wave data of seafarers is calibrated with different types of emotions.•The effects of seafarers' emotion, relating to events exposure, on operational errors are identified and quantified.•The results from the experiment have potential application to seafarer training and qualification.
Performance monitoring is a critical process which allows us to both learn from our own errors, and also interact with other human beings. However, our increasingly automated world requires us to interact more and more with automated systems, especially in risky environments. The present EEG study aimed at investigating and comparing the neuro-functional correlates associated with performance monitoring of an automated system and a human agent using a vertically-oriented arrowhead version of the flanker task. Given the influence of task difficulty on performance monitoring, two levels of difficulty were considered in order to assess their impact on supervision activity. A large N2-P3 complex in fronto-central regions was observed for both human agent error detection and system error detection during supervision. Using a cluster-based permutation analysis, a significantly decreased P3-like component was found for system compared to human agent error detection. This variation is in line with various psychosocial behavioral studies showing a difference between human-human and human-machine interactions, even though it was not clearly anticipated. Finally, the activity observed during error detection was significantly reduced in the difficult condition compared to the easy one, for both system and human agent supervision. Overall, this study is a first step towards the characterization of the neurophysiological correlates underlying system supervision, and a better understanding of their evolution in more complex environments. To go further, these results need to be replicated in other experiments with various paradigms to assess the robustness of the pattern and decrease during system supervision. •Others’ errors detection triggers a broad fronto-central complex in brain activity.•The error monitoring activity is lower for system than human agent supervision.•Task difficulty reduces error-related potentials for human and artificial agents.•Non-parametric cluster-based permutation test better evidences supervision activity.