Cognition Technology and Work

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Situational risk has been postulated to be one of the most important contextual factors affecting operator’s trust in automation. However, experimentally, it has received only little attention and was directly manipulated even less. To close this gap, this study used a virtual reality multi-task environment where the main task entailed making a diagnosis by assessing different parameters. Risk was manipulated via the altitude, the task was set in including the possibility of virtually falling in case of a mistake. Participants were aided either by information or decision automation. Results revealed that trust attitude toward the automation was not affected by risk. While trust attitude was initially lower for the decision automation, it was equally high in both groups at the end of the experiment after experiencing reliable support. Trust behavior was significantly higher and increased during the experiment for the decision automation supported group in the form of less automation verification behavior. However, this detrimental effect was distinctly attenuated under high risk. This implies that negative consequences of decision automation in the real world might have been overestimated by studies not incorporating risk.
 
Deep learning and neural network
Human–AI interaction process and usefulness
In the global war for talent, traditional recruiting methods are failing to cope with the talent competition, so employers need the right recruiting tools to fill open positions. First, we explore how talent acquisition has transitioned from digital 1.0 to 3.0 (AI-enabled) as the digital tool redesigns business. The technology of artificial intelligence has facilitated the daily work of recruiters and improved recruitment efficiency. Further, the study analyzes that AI plays an important role in each stage of recruitment, such as recruitment promotion, job search, application, screening, assessment, and coordination. Next, after interviewing with AI recruitment stakeholders (recruiters, managers, and applicants), the study discusses their acceptance criteria for each recruitment stage; stakeholders also raised concerns about AI recruitment. Finally, we suggest that managers need to be concerned about the cost of AI recruitment, legal privacy, recruitment bias, and the possibility of replacing recruiters. Overall, the study answers the following questions: (1) How artificial intelligence is used in various stages of the recruitment process. (2) Stakeholder (applicants, recruiters, managers) perceptions of AI application in recruitment. (3) Suggestions for managers to adopt AI in recruitment. In general, the discussion will contribute to the study of the use of AI in recruitment, as well as providing recommendations for implementing AI recruitment in practice.
 
The present study examined how task priority influences operators’ scanning patterns and trust ratings toward imperfect automation. Previous research demonstrated that participants display lower trust and fixate less frequently toward a visual display for the secondary task assisted with imperfect automation when the primary task demanded more attention. One account for this phenomenon is that the increased primary task demand induced the participants to prioritize the primary task than the secondary task. The present study asked participants to perform a tracking task, system monitoring task, and resource management task simultaneously using the Multi-Attribute Task Battery (MATB) II. Automation assisted the system monitoring task with 70% reliability. Task load was manipulated via difficulty of the tracking task. Participants were explicitly instructed to either prioritize the tracking task over all other tasks (tracking priority condition) or reduce tracking performance (equal priority condition). The results demonstrate the effects of task load on attention distribution, task performance and trust ratings. Furthermore, participants under the equal priority condition reported lower performance-based trust when the tracking task required more frequent manual input (tracking condition), while no effect of task load was observed under the tracking priority condition. Task priority can modulate automation trust by eliminating the adverse effect of task load in a dynamic multitasking environment.
 
Efforts have always been deployed to surpass limitations in human cognitive abilities to enhance aspects such as task accuracy, work effectiveness, and error management. Cognitive enhancement is a field aiming at improving human cognition to overcome those limitations. It bears important interest from the human factors community given its potential for reducing errors in complex operational environments, but also for occupational psychology to improve work performance, mitigate risks, and improve job stress/well-being. Yet, cognitive enhancement strategies are still marginally used in practice. The current narrative review presents a brief summary of the literature on human cognitive enhancement and discusses key implications as well as operational applications of the main methods and technologies reported in this field. Using a human factors perspective, the paper also outlines how such techniques could be integrated into intelligent support systems to help operators facing cognitive challenges in complex operational domains, including those experiencing functional limitations preventing them to contribute to the workforce. We also discuss the implications of integrating such techniques into the workplace and the consequences this might incur for workers and stakeholders. Then, we briefly present a five-step guideline to discuss ways of optimally integrating cognitive enhancement methods into the workplace.
 
Mixed method flow
Results of qualitative phase
Conceptual model and hypothesis paths
Conceptual model and hypotheses
Contributing to the scarce literature on how companies can deal with their business model of digital transition, this work explores the digital transformation (DT) process in small and medium enterprises (SME), investigating how organizational culture, structure, and leadership influence it. While such three factors are deemed essential components to facilitate DT, how they operate and how they relate to each other are still not very well-defined issues in need of in-depth investigation. This study employed a mixed-methods approach, following an exploratory sequential design. First, a conceptual model was developed based on qualitative data collected from expert interviews and analyzed through grounded theory. This stage uncovered 25 first-order concepts about culture, structure, and leadership, further organized into 6 constructs and hypothesis paths. Then, with a sample of 192 SMEs, the structural model was measured and validated using exploratory factor analysis and PLS-SEM. As a result, our study offers robust and timely research, whose conceptual model condenses a knowledge corpus that future research can benefit from, and it provides statistical extrapolations about how and how much those factors relate to each other in SME context; moreover, given the traditional scarce resources and lack of flexibility in SMEs, it provides orientation and guidelines to managers facing DT and needing to understand the organizational factors they should be aware of, where to focus energy, and what to expect as results. From a large-scale perspective, this study carries an impactful contribution to the many countries where SMEs play a major economic and social role.
 
The main objective of the current contribution was to investigate human–machine cooperation over time. Participants were asked to choose repeatedly between four automation modes ranging from manual control to supervisory control. Three experiments were undertaken to assess the influence of previous exposure to automation and duration of automation use on automation mode selection and associated subjective assessments. In Experiment 1, automation mode selection was investigated for a short period of time and without previous exposure to automation. Short- and longer-term automation selections were investigated after brief exposure to all automation modes (Experiment 2) or more extensive exposure to a particular mode (Experiment 3). Results indicated that automation mode selection and subjective assessments are influenced by both previous automation exposure and duration of use. Automation mode selection is not primarily based on perceived performances, subjective workload or on trust and acceptance of the automation modes. In practice, the reported data support the idea that short-term studies are not necessarily well-suited to investigating human–machine cooperation issues.
 
The workplace is an important setting for health protection, health promotion and disease prevention. Currently, health and wellbeing approaches at an aviation organisational level are not addressing both human and safety needs. This issue has been intensified since the COVID 19 pandemic. This paper reports on the findings of a survey pertaining to aviation worker wellbeing and organisational approaches to managing wellbeing and mental health. The survey was administered at two different time periods during the COVID 19 pandemic (2020 and 2021). Collectively, feedback was obtained from over 3000 aviation workers. Survey feedback indicates that aviation workers are experiencing considerable challenges in relation to their health and wellbeing. These challenges are not being adequately addressed at an organisational level, which creates risk both from an individual and flight safety perspective. The descriptive findings of both surveys along with a regression analysis is used to make a principled case for augmenting the existing approach to managing aviation worker wellbeing (including mental health), at both an organisational and regulatory level. It is argued that aviation organisations, with the support of the regulator should implement a preventative, ethical and evidence-based strategy to managing wellbeing and mental health risk. Critically, aviation organisations need to advance and integrated health, wellbeing, and safety culture. This necessitates an alignment of human, business, and safety objectives, as articulated in concepts of corporate social responsibility (CSR) and responsible work. Critically, this approach depends on trust and the specification of appropriate protections, so that aviation workers feel safe to routinely report wellbeing levels and challenges, and their impact on operational safety.
 
PRISMA flowchart
Traditionally, automation was introduced to alleviate workload associated with tedious and repetitive tasks. Recently, automation is being used to augment knowledge work, which includes high-level cognitive activities. As automated systems are being extended to perform skill-based tasks, the work required of humans may be altered, potentially affecting their cognitive workloads. Researchers have investigated the influences of automation on cognitive workload across different domains and tasks by assessing changes in task performance, perceived (subjective) workload, and physiological states. A major challenge in comparing results and drawing inferences across studies is that a profusion of measures is often used to assess cognitive workload. The experimental tasks employed across many domains further complicates synthesizing findings. Thus, the aim of this review is to examine how cognitive workload is assessed when at least two different measures of cognitive workload are used in research focused on human-automated knowledge work. To accomplish this aim, the various approaches employed to measure cognitive workload were first summarized. Then, automated and cognitive experimental tasks were classified, utilizing existing frameworks, to identify associations, dissociations, and insensitivities across task types. Finally, recommendations were provided for aligning task types, study designs, and measurement selections, along with expanding the types of tasks and measures used when studying automation applications supporting knowledge work.
 
Professional learning design framework (PLD framework)
Continuing professional development recognises that changes in the contemporary world demand that engineering professionals continuously learn. Today’s professional landscape requires the provision for ongoing learning relevant to evolving workplace requirements. This is particularly the case for engineers working in hazardous industries who make decisions every day with significant consequences. Despite this, the safety literature has paid little attention to best practice in professional learning. There is a large literature regarding lessons to be learned from accidents. Other published studies focus on training methods such as simulation. Educator-focused approaches such as these separate learning from real day-to-day workplace contexts and the learning needs of professionals. It is increasingly recognised that professionals learn, in a way that shapes their practice, from a diverse range of activities. Learning must therefore be active, social, and situated within the sphere of professional responsibilities, contexts, and groups. This paper presents a learner-centred framework that can be used to develop professional learning for safety that is grounded in day-to-day work practices and professional context needs. The framework aims to move away from the limitations that have been found with the current professional development approaches to enhance learner-centred professional learning. The framework was developed and used in the context of engineering practices regarding safety, but, because the framework encourages learning to be designed based on workplace contexts, it is applicable across a range of training needs and professions.
 
Schematic illustration of the sequence of a take-over process, adapted from Gold et al. (2013) and corrected based on Gold et al. (2018) to better define “Automation inactive (real)”
Schematic illustration of the sequence of a take-over process, taken from SAE (2016a). SAE adapted this figure from Seppelt and Victor (2016)
Schematic illustration of the sequence of a take-over process. Image taken from BSI (2020)
Transfer of DDT function sequence from automated to manual driving (system-initiated). Highlights of discrepancies among Gold et al. (2013, 2018), Seppelt and Victor (2016), SAE (2016a) and Wintersberger et al. (2017). This figure is adapted from SAE (2016a)
Correspondence among Gold et al. (2013, 2018), Seppelt and Victor (2016), SAE (2016a), Wintersberger et al. (2017) and BSI (2020). Transfer of DDT function sequence from automated to manual driving (system- initiated). This figure is adapted from BSI (2020)
During the last 20 years, technological advancement and economic interests have motivated research on automated driving and its impact on drivers’ behaviour, especially after transitions of control. Indeed, once the Automated Driving System (ADS) reaches its operational limits, it is forced to request human intervention. However, the fast accumulation and massive quantity of produced studies and the gaps left behind by standards have led to an imprecise and colloquial use of terms which, as technology and research interest evolve, creates confusion. The goal of this survey is to compare how different taxonomies describe transitions of control, address the current use of widely adopted terms in the field of transitions of control and explain how their use should be standardized to enhance future research. The first outcome of this analysis is a schematic representation of the correspondence among the elements of the reviewed taxonomies. Then, the definitions of “takeover” and “handover” are clarified as two parallel processes occurring in every transition of control. A second set of qualifiers, which are necessary to unequivocally define a transition of control and identify the agent requesting the transition and the agent receiving the request (ADS or the driver), is provided. The “initiator” is defined as the agent requesting the transition to take place, and the “receiver” is defined as the agent receiving that request.
 
Modern organizations live in a context of political, economic, technological, social and environmental changes for which they need to be prepared to adapt and continue operating successfully. In this sense, a more resilient performance becomes a fundamental factor for an organization’s success. In this article, we present the ResiliFRAM method, a detailed description on how to use the Functional Resonance Analysis Method—FRAM to analyse resilient performance. The aim is to understand how the resilience abilities, monitoring, anticipating, responding and learning, are articulated producing a resilient performance. ResiliFRAM uses ergonomic analysis to understand Work-as-Done (WAD) and FRAM to identify routes for resilient performance. ResiliFRAM was applied in a case study in the construction industry of the building sector and the results indicated that it is possible to shed light on some organizational practices that afford a more resilient performance.
 
Over the past two decades, systemic-based risk assessment methods have garnered more attention, and their use and popularity are growing. In particular, the functional resonance analysis method (FRAM) is one of the most widely used systemic methods for risk assessment and accident analysis. FRAM has been progressively evolved since its starting point and is considered to be the most recent and promising step in understanding socio-technical systems. However, there is currently a lack of any formal testing of the reliability and validity of FRAM, something which applies to Human Factors and Ergonomics research as a whole, where validation is both a particularly challenging issue and an ongoing concern. Therefore, this paper aims to define a more formal approach to achieving and demonstrating the reliability and validity of an FRAM model, as well as to apply this formal approach partly to an existing FRAM model so as to prove its validity. At the same time, it hopes to evaluate the general applicability of this approach to potentially improve the performance and value of the FRAM method. Thus, a formal approach was derived by transferring both the general understanding and definitions of reliability and validity as well as concrete methods and techniques to the concept of FRAM. Consequently, predictive validity, which is the highest maxim of validation, was assessed for a specific FRAM model in a driving simulator study using the signal detection theory. The results showed that the predictive validity of the FRAM model is limited and a generalisation with changing system conditions is impossible without some adaptations of the model. The applicability of the approach is diminished because of several methodological limitations. Therefore, the reliability and validity framework can be utilised to calibrate rather than validate an FRAM model.
 
Phases of the study
Military and emergency response remain inherently dangerous occupations that require the ability to accurately assess threats and make critical decisions under significant time pressures. The cognitive processes associated with these abilities are complex and have been the subject of several significant, albeit service specific studies. Here, we present an attempt at finding the commonalities in threat assessment, sense making, and critical decision-making for emergency response across police, military, ambulance, and fire services. Relevant research is identified and critically appraised through a systematic literature review of English-language studies published from January 2000 through July 2020 on threat assessment and critical decision-making theory in dynamic emergency service and military environments. A total of 10,084 titles and abstracts were reviewed, with 94 identified as suitable for inclusion in the study. We then present our findings focused on six lines of enquiry: Bibliometrics, Language, Situation Awareness, Critical Decision Making, Actions, and Evaluation. We then thematically analyse these findings to reveal the commonalities between the four services. Despite existing single or dual service studies in the field, this research is significant in that it is the first examine decision making and threat assessment theory across all four contexts of military, police, fire and ambulance services, but it is also the first to assess the state of knowledge and explore the extent that commonality exists and models or practices can be applied across each discipline. The results demonstrate all military and emergency services personnel apply both intuitive and formal decision-making processes, depending on multiple situational and individual factors. Institutional restriction of decision-making to a single process at the expense of the consideration of others, or the inappropriate training and application of otherwise appropriate decision-making processes in certain circumstances is likely to increase the potential for adverse outcomes, or at the very least restrict peak performance being achieved. The applications of the findings of the study not only extend to facilitating improved practice in each of the individual services examined, but provide a basis to assist future research, and contribute to the literature exploring threat assessment and decision making in dynamic contexts.
 
Research model
Consequences of techno-stressors
Temporal effects of technostress
Results—consequences of techno-stressors
Results—temporal effects of technostress
This paper analyzes teleworkers’ technostress evolution over time, as well as its effects on these individuals’ work-related well-being over time. The proposed research model was tested using a survey-based longitudinal study with individuals that forcibly moved to teleworking in the context of a COVID-19 lockdown at two points in time (T0 and T1). Results indicate that two techno-stressors (work–home conflict and work overload) generated strain in teleworkers, which in turn decreased their satisfaction with telework and perceived job performance. In addition, teleworkers experienced two types of enduring technostress: synchronous effect (i.e., stressors generating strain at T1), and a cumulative reverse causation effect (i.e., strain at T0 has an effect on stressors at T1). These findings contribute to cognition, work, and technology literature by providing a more complete understanding of teleworkers’ technostress and its possible cumulative effects over time. Practical insights for managing technostress when moving to and remaining in teleworking are provided.
 
The exploitation of so-called insiders is increasingly recognised as a common vector for cyberattacks. Emerging work in this area has considered the phenomenon from various perspectives including the technological, the psychological and the sociotechnical. We extend this work by specifically examining unintentional forms of insider threat and report the outcomes of a series of detailed Critical Decision Method (CDM) led interviews with those who have experienced various forms of unwitting cybersecurity breaches. We also articulate factors likely to contribute firmly in the context of everyday work-as-done. CDM’s probing questions were used to elicit expert knowledge around how decision making occurred prior, during and post an unintentional cyber breach whilst participants were engaged in the delivery of cognitive tasks. Through the application of grounded theory to data, emerging results included themes of decision making, task factors, accidents and organisational factors. These results are utilised to inform an Epidemiological Triangle to represent the dynamic relationship between three vectors of exploit, user and the work environment that can in turn affect the resilience of cyber defences. We conclude by presenting a simple framework, which for the purposes of this work is a set of recommendations applicable in specific scenarios to reduce negative impact for understanding unintentional insider threats. We also suggest practical means to counteract such threats rooted in the lived experience of those who have fallen prey to them.
 
Some safety events do not stabilise in a coherent state, presenting with transient or intermittent features. Such dynamism may pose problems for human performance, especially if combined with non-typical stimuli that are rarely encountered in everyday work. This may explain undesirable pilot behaviour and could be an important cognitive factor in recent aircraft accidents. Sixty-five airline pilots tested a real-world typicality gradient, composed of two cockpit events, a typical event, and a non-typical event, across two different forms of dynamism, a stable, single system transition, and an unstable, intermittent system transition. We found that non-typical event stimuli elicited a greater number of response errors and incurred an increased response latency when compared to typical event stimuli, replicating the typicality effect. These performance deteriorations were amplified when a form of unstable system dynamism was introduced. Typical stimuli were unaffected by dynamism. This indicates that dynamic, non-typical events are problematic for pilots and may lead to poor event recognition and response. Typical is advantageous, even if dynamic. Manufacturers and airlines should evolve pilot training and crew procedures to take account of variety in event dynamics.
 
Wright map of the Cognitive Processing subscale. For the cognitive processing subscale, the average person ability was − 0.67 (see “M” to the left of the dividing line, on the ability side). This indicates participants found dashboard ergonomics associated with this subscale as assessed by the questionnaire to be less problematic, or difficult, compared to an ideal Rasch model. When examining the ranges, the map indicates mean item difficulty and person ability overlapped for about half of respondents. The least challenging item (Item 14: The dashboard is so cluttered with gauges, buttons and controls that it is overwhelming)—shown at the top of the figure, had a difficulty value of 0.68. The item presenting the greatest challenge (Item 28: I understand the meaning of all my car’s gauges) had a difficulty value of − 1.87. Item 28 was stated in a positive rather than negative way and therefore had to be reverse coded, had misfit, and was removed from the analysis
Wright map for Thurstone Rasch thresholds for the Cognitive Processing subscale. The bolded X in the column marked top P = 50% is the point on the latent continuum at which a person would have a 50% probability of being in the highest category and a 50% probability of being below that point. Similarly, the bolded X in the column marked bottom P = 50% is the point on the continuum at which a person would have a 50% probability of being in the lowest category and a 50% probability of being above that level. The difference in logits between those points provides one index of the operational range of the scale. For the cognitive scale, that range is approximately 5 logits. The range of difficulty levels for each item between the bottom 50% column and the top 50% column provides one index of the difficulty range for each item. That range is approximately 1.5 logits for most items
Item response category characteristic curves. Andrich thresholds (category probabilities) of item 39 with (a) and without (b) the neutral category. In 3a, the neutral category is non-modal and overlaps adjacent response categories whereas 3b indicates ordered response levels
Older drivers are a rapidly growing demographic group worldwide; many have visual processing impairments. Little is known about their preferences about vehicle instrument cluster design. We evaluated the psychometric properties of a questionnaire on “dashboard” design for a population-based sample of 1000 older drivers. Topics included gauges, knobs/switches, and interior lighting; items were statements about their visual design. Response options used a Likert-scale (“Definitely True” to “Definitely False”). Factor and Rasch analyses identified underlying subscales. Driver responses revealed four thematic subscales fitting the Rasch model: cognitive processing, lighting, pattern recognition, and obstructions. Internal consistency of subscales was acceptable (0.70–0.87); all possessed a sufficiently unidimensional structure. Opportunities for improvement were identified (item scope, category ordering, discrimination of respondents’ perception levels). Assessment of motor vehicle dashboard preferences indicated cognitive processing, lighting, pattern recognition, and obstructions are areas relevant to older drivers. Future work will examine the relationship between older drivers’ visual function (e.g., contrast sensitivity, visual processing speed) and their design preferences as revealed by the Dashboard Questionnaire, with the aim to optimize instrument cluster displays for older drivers.
 
External view of the JL-8 high-fidelity flight simulator
Simple line plot of the mean N value in the training group for the N-back task throughout the training sessions. Error bars indicate the SE
Performance on Raven’s advanced progressive matrices for each group on the pretest and posttest. Error bars indicate the SE
SA Performance of each group on the pretest and posttest. A Situational Understanding Subdimension Score of the 3D-SART. The graph depicts the Situational Understanding Scores. B SAGAT. The figure depicts Performance on the SAGAT
The close relationship between working memory and situation awareness (SA) has been confirmed and further empirical investigations are lacking. The main aim of this study was to demonstrate the feasibility of working memory training for improving SA. Thirty-eight participants completed a challenging flight scenario in a high-fidelity flight simulator and were randomized into a training group (n = 20) or a control group (n = 18). The training group engaged in an adaptive dual N-back task for 2 weeks, while the control group was given a negative control task. Three-dimensional situation awareness rating technique (3D-SART) scores and situation awareness global assessment technique (SAGAT) scores were recorded to evaluate pretest and posttest SA. The results showed that both situational understanding dimension scores in the 3D-SART and SAGAT scores were significantly increased from the pretest to the posttest in the training group, while the control group showed no significant differences. It was concluded that working memory training can effectively improve individuals’ SA, which has important implication for future research.
 
The automotive market today has seen the entry of Level-3 conditional automated driving vehicles equipped with an automated driving system that waits for the drivers to start it on the road. Before making a full assessment of the use of automated driving systems, drivers should be made to experience real-world conditional automated driving. A driver may have a mood change when driving a real-world automated vehicle. This emotion points to the mediation of motivation, which affects a driver’s cognition and intention to start an automated driving system on the road. In this study, the emotion of experiencing autonomous driving, cognition, and satisfaction of the driving performance were introduced to construct an intention model to start an automated driving system. Online and off-line questionnaires were adopted, and the emotional response, cognition of automated driving, and intention of 133 drivers who experienced real-world conditional automated driving were determined. Driver experience was assessed in four scenarios as part of emotional tests: during manual driving, during conditional automated driving, during takeover under the influence of the warning system, and during takeover driving. The results of the questionnaire showed a significant positive correlation between emotion and cognition, satisfaction of autonomous driving performance, and the intent to start the automated driving system. Emotions play a mediating role between cognition, satisfaction, and intention to start automated driving. Drivers who experienced conditional automated driving appeared to exhibit a moderately high level of emotional response in terms of joy, interest, and surprise, whereas medium-level negative emotions included fear and anger. Drivers experienced some intensity of emotional changes during conditional automated driving and takeover driving. The emotional changes were uneven but encouraging support was reported. In addition, specific hypotheses relating the driving performance of the automated vehicles (in terms of programmed design of takeover and warning system of takeover) to the emotional dimensions were tested. A cluster analysis of the emotional response measures revealed five different emotional patterns when experiencing the real-world automated vehicle, among which the happy/satisfied group had higher intention to start an automated driving system on the road, followed by the emotional group, whereas the disgust group showed the lowest intention. The cluster analysis was supported by demographic and driving cognitive characteristics (age, education, and self-evaluation of the driving level and driving experience) of the five groups of drivers. Finally, the theoretical and practical significance of this study was expounded. The research results may provide some suggestions and hints for the government and enterprises to promote the development of automated driving.
 
Swiss cheese model redrawn from Reason (1997). The layers of defence (illustrated by cheese slices) may be physical, technological, organizational, or human applications. The holes in the barriers are created by active failures or latent conditions (Reason 1997)
Example of adaptation of technology by seafarers. All the available alternatives for managing window wipers except the one they need (start/stop all wipers) has been covered
Navigating a ship is a complex task that requires close interaction between navigators and technology available on the ship’s bridge. The quality of this interaction depends on human and organisational factors, but also on technological design. This is recognized by the International Maritime Organization (IMO) through the SOLAS V/15 regulation that requires human factor considerations in bridge design. The objective of this paper is to investigate how tensions between the main stakeholders’ interests and perspectives in ship bridge design may influence the achievement of the goals set forth in the SOLAS V/15 regulation. This objective is explored through a qualitative study in the maritime industry, involving seafarers, shipowners, and equipment manufacturers. We find suboptimal ship bridge design usability to be connected to structural characteristics of the maritime sector, where different aims and perspectives between core stakeholders impairs alignment with respect to conception of work-as-done in the operative environment. We also find that profitability is a major driver for the blunt end stakeholders, for whom the relation between usability and profitability is perceived as a trade-off rather than of synergy. We conclude that there is a need to develop processes, enablers, and management tools to (1) update the understanding of the professional competence needed in the technology dense work environment on ship bridges today; (2) strengthen the maritime stakeholders’ awareness of the advantages of human-centred design (HCD) which are both operator well-being and system performance; (3) enable implementation of HCD into existing design and development processes; (4) provide metrics for business cases enabling informed ergonomic investment decisions.
 
Due to the argued benefits of passenger comfort, cost savings, and road safety, the bus sector is showing increasing interest in advanced driver-assistance systems (ADAS). Despite this growth of interest in ADAS and the fact that work tasks are sometimes complicated (especially docking at bus-stops which may occur several hundred times per shift), there has been little research into ADAS in buses. Therefore, the aim of this study was to develop further knowledge of how professional bus drivers experience and accept an ADAS which can help them dock at bus-stops. The study was conducted on a public route in an industrial area with five different bus-stops. Ten professional bus drivers got to use a narrow navigation system (NNS) that could dock automatically at bus-stops. The participants’ experience and acceptance were investigated using objective as well as subjective data (during and after the test-drive) and data were collected using interviews, questionnaires, and video recordings. The participants indicated high levels of trust in and acceptance of the NNS and felt that it had multiple benefits in terms of cognitive and physical ergonomics, safety, and comfort. However, the relatively slow docking process (which was deemed comfortable) was also expected to negatively affect, e.g., timetabling, possibly resulting in high stress levels. Therefore, when investigating users’ acceptance of ADAS in a work context, it is important to consider acceptance in terms of the operation, use, and work system levels and how those levels interact and affect each other.
 
Team stress is an emergent cognition in which members jointly appraise their current task situations. The sharedness of stress appraisals has been elaborately studied in social groups such as couples, families, friends, and small communities. However, insights into teams have been rather limited. Keeping in mind the effects of stress on teams, it is essential to understand how team stress will form in teams over time. Seven dyad teams were observed during a 13-min flight simulation task. Researchers used the course of action analysis to reconstruct and distinguish one top-down (i.e., the shared stress configuration) and three bottom-up configuration types (i.e., the mimic, interactive, and independent stress configurations). Our findings suggest that especially the bottom-up influence of social stressors plays an important role in the team stress, especially when members verbally interact with one another. This proposes that, in comparison to the influence of contextual factors, diverse empathic processes play a more distinct role in the formation of team stress than initially thought in teams. This article also intends to illustrate how team stress can be studied over time, and how this type of output can contribute to a more fine-grained theoretical understanding of how team stress forms over time in teams. Last, it also provides some basic practical insights into the design of stress feedback systems.
 
Lack of support for handling a reduction of autonomy in a highly autonomous automation may lead to a stressful situation for a human when forced to take over. We present a design approach, the Reduced Autonomy Workspace, to address this. The starting point is that the human and the automation work together in parallel control processes, but at different levels of autonomy cognitive control, such as setting goals or implementing plans, which is different from levels of automation. When autonomy is reduced, the automation should consult the human by providing information that has been aligned to the level at which the human is working, and the timing of the provision should be adapted to suit the human’s work situation. This is made possible by allowing the automation to monitor the human in a separate process. The combination of these processes, information level alignment and timing of the presentation, are the key characteristics of the Reduced Autonomy Workspace. The Reduced Autonomy Workspace consists of four phases: Identification of the need; evaluation of whether, and, if so, when, and how to present information; perception and response by the human; implementation of a solution by the automation. The timing of the information presentation should be adapted in real-time to provide flexibility, while the level of the information provided should be tuned offline and kept constant to provide predictability. Use of the Reduced Autonomy Workspace can reduce the risk for surprising, stressful hand-over situations, and the need to monitor the automation to avoid them.
 
The relevance of user experience in safety-critical domains has been questioned and lacks empirical investigation. Based on previous studies examining user experience in consumer technology, we conducted an online survey on positive experiences with interactive technology in acute care. Participants were anaesthesiologists, nurses, and paramedics (N = 55) from three German cities. We report qualitative and quantitative data examining (1) the relevance and notion of user experience, (2) motivational orientations and psychological need satisfaction, and (3) potential correlates of hedonic, eudaimonic, and extrinsic motivations such as affect or meaning. Our findings show that eudaimonia was the most salient aspect in these experiences, and that the relevance of psychological needs is differently ranked than in experiences with interactive consumer technology. We conclude that user experience should be considered in safety-critical domains, but research needs to develop further tools and methods to address the domain-specific requirements.
 
The car driving simulator used and an example, indicated by a red circle, of one of the cyclists to be detected by the participants (Color figure online)
Protocol summary
Average emotional assessment at before (a) and after (b) exposure to communication supports
Emotional assessments in three studies after exposure to communication supports (Rogé et al. 2015; this study) and short film clips (Lafont et al. 2018)
This study aimed to investigate the impact of the emotional and informational components of road safety communication on the motorists’ ability to detect cyclists in an urban environment. Different communication supports (audiovisual, auditory, visual) were used to present road safety messages to elicit different intensities of a same pattern of negative emotions before performing driving on a car driving simulator. Subjective results (intensities collected with a visual analog scale) showed that all the communication supports elicited the same set of emotions where sadness was salient. However, no evidence was found concerning a congruent physiological pattern (cardiac and pupillary response) either during exposure to communication supports or during a subsequent driving task. Better cyclist detections were observed after exposure to the safety messages, regardless of the communication support used. This result was confirmed by a better attention management for all participants, as shown by the analysis of the number of saccades per minute, the fixation durations and the speed of head movements and a safer speed management in areas where cyclists were present. The type of communication support is less important than the message itself to deliver some negative emotions. The combination of low-intensity negative emotions with safety messages appears to be an efficient strategy for a successful road safety communication when the aim is to improve motorists’ ability to detect cyclists. Perspectives in terms of on-board systems and guidelines for designing safety campaigns were also discusses, as well as limitations of this study.
 
The three-level model of SA (adapted from Endsley)
The framework of DEMATEL–ISM method
The cause-and-effect relationship diagram of influencing factors
The hierarchical model of the influencing factors
It is increasingly being recognized that the flight crew’s team situation awareness (TSA) is essential for flight safety. To explore the inherent correlation and hierarchical structure of the flight crew’s TSA, 21 influencing factors were extracted from individuals, flight crew, equipment, environment, management, and task perspectives based on the Delphi Method and flight accident investigation. By absorbing the advantages of Decision Making Trial and Evaluation (DEMATEL) and Interpretive Structure Modeling (ISM), the influencing degree, the influenced degree, the centrality, and the causality of each influencing factor were calculated to find out the key factors and the cause-and-effect relationship; a multi-level hierarchical model was established for analyzing the interaction mechanism of the flight crew’s TSA. The results show: (i) for the formation and maintenance of the flight crew’s TSA, among the 21 influencing factors, task property, safety consciousness, workload, communication, coordination, physiological, and mental state are the most important influencing factors; (ii) the multi-level hierarchical model is divided into five layers and reflects the function pathway. Attention, memory, and safety consciousness are the direct causes of the failure of the flight crew’s TSA. Regulatory policy, safety culture, and training can be considered upon as the deepest and fundamental influencing factors affecting the flight crew’s TSA; (iii) the mutual influencing degree of elements and the cause-and-effect relationship are quantificationally presented to better reveal the inherent correlation. This study provides a workable reference for analyzing the flight crew’s TSA and offers a novel decision-making approach to support better flight safety management by priority actions.
 
The procedure for study 1
Average UX score of different reply methods and genders
Average UX scores of different reply methods, genders and instruction types
Voice user interfaces (VUIs) have exploded in popularity over the past 3 years. However, there has been little research on the reply methods that VUIs can adopt to communicate with people. In this paper, we designed 2 studies with 20 participants to explore the influence of reply methods on user experience in 2 kinds of scenarios (applicational scenarios and giving a command) when using a VUI. We explored the performance of different reply methods (fact-only, rational, and emotional) at different times and in different scenarios. In addition, we examined whether there were gender differences when evaluating a reply and different preferences for different reply methods. A “Wizard of Oz” method was used in the experiments to simulate real scenarios for communication between the participants and the VUI. We divided a reply into three parts (fact + judgment + strategy) and constructed three kinds of reply methods. In the experiments, we used quantitative scoring (five aspects: affection, confidence, naturalness, social distance, and satisfaction), preference selection and an interview to measure the participants’ user experience. The results indicated that the participants were inclined to prefer the reply methods (rational and emotional) that offered judgments and strategies in our experiment script, and the emotional style received the highest evaluation. In addition, we found that male participants tended to have a higher evaluation of VUIs’ replies for all three reply methods in applicational scenarios and when giving a command than female participants in our studies. In general, these results may contribute to the design of VUI replies.
 
Technology acceptance model (TAM)
TAMUI (TAM and user involvement)
TAMUI with the estimated regression loads
The present article explores the concept of user involvement in the information system (IS) development context. It integrates situational involvement and intrinsic involvement constructs in the Technology Acceptance Model (TAM) and empirically tested a theoretical model with premises that were previously tested separately but not operationalized and tested together. From data collected from companies that have recently implemented an IS, Exploratory Factorial Analysis (EFA), Factorial Confirmatory Analysis (CFA), and Structural Equation Modeling (SEM) were used to assess the construct’s validity and the hypothesis test of the model, respectively. With a sample of 114 respondents, the main results indicate that situational involvement influences intrinsic involvement, perceived usefulness, and ease of use perception; it also indicates that intrinsic involvement influences usefulness perception, ease of use perception, and behavioral intention. Thus, this paper validated the assumptions about the importance of user involvement as an influence in adopting an IS, pointing out that situational involvement influences intrinsic involvement and that future users can become cognitively biased to better perceive a system as useful and easy to use, increasing its acceptance and adoption. It represents an original approach in this field with theoretical and empirical contributions.
 
Vessel traffic service (VTS) is important to protect the safety of maritime traffic. Along with the expansion of monitoring area per VTS operator in Tokyo Bay, Japan, inexperienced operators must acquire the ability to quickly and accurately detect conditions that requires attention (CRAs) from a monitoring screen. In our previous study (Song B, Itoh H, Kawamura Y, Fukuto J (2018) Analysis of Cognitive Processes of Operators of Vessel Traffic Service. In: Proceedings of the 2018 International Association of Institutes of Navigation. IAIN 2018, pp 529–534, Song et al., J Jpn Inst Navig 140:48–54, 2019), we established a task analysis method based on the assumption that the cognitive process model consists of three stages: “situational awareness”, “situation judgment”, and “decision making”. A simulation experiment was conducted for VTS operators with different levels of ability and their cognitive processes were compared based on the observation of eye movements. The results showed that the inexperienced operators’ abilities to predict situation changes were lower. And it was considered that oral transmission of the knowledge is difficult, thus new training methods are needed to help the inexperienced operators to understand the prediction methods of experienced operators. In this study, based on the cognitive process of an experienced operator, we analyzed the prediction procedures of situation changes and developed an educational tool called vessel traffic routine (VTR). The training method learning VTR aims to quickly improve inexperienced VTS operators’ abilities to predict situation changes. A simulation verification experiment of the VTR effect was conducted for four inexperienced operators, who were divided into two groups with and without prior explanation of VTR. By evaluating the cognitive processes of inexperienced operators, it was confirmed that those given prior explanations of VTR were better at detecting CRAs.
 
Focus areas of the HAIS-Q questionnaire
Direct, proportional and positive correlation for “Knowledge”, “Attitude” and “Behaviour” distribution across Focus Areas, for IT (blue dots) vs. Non-IT (yellow dots). The dot size represents the type of organisation: Hospitals (wider dots) vs. HC Software Provider (smaller dots)
Mean Overall Scores for Knowledge (K), Attitude (A) and Behaviours (B) for the FAs where IT personnel reported total mean scores higher than Non-IT personnel
Mean Overall Scores for Knowledge (K), Attitude (A) and Behaviours (B) for the Focus Areas where IT reported total mean scores equal or lower than Non-IT personnel
Mean Scores for the FAs for IT (blue lines, chart on the left) vs. Non-IT (yellow lines, chart on the right) personnel in different type of organisations: HC Software Provider organisations (lighter lines in both charts) vs. non-software-related organisations i.e., hospital organisations (darker lines in both charts)
Computer and Information Security (CIS) is usually approached adopting a technology-centric viewpoint, where the human components of sociotechnical systems are generally considered as their weakest part, with little consideration for the end users’ cognitive characteristics, needs and motivations. This paper presents a holistic/Human Factors (HF) approach, where the individual, organisational and technological factors are investigated in pilot healthcare organisations to show how HF vulnerabilities may impact on cybersecurity risks. An overview of current challenges in relation to cybersecurity is first provided, followed by the presentation of an integrated top–down and bottom–up methodology using qualitative and quantitative research methods to assess the level of maturity of the pilot organisations with respect to their capability to face and tackle cyber threats and attacks. This approach adopts a user-centred perspective, involving both the organisations’ management and employees, The results show that a better cyber-security culture does not always correspond with more rule compliant behaviour. In addition, conflicts among cybersecurity rules and procedures may trigger human vulnerabilities. In conclusion, the integration of traditional technical solutions with guidelines to enhance CIS systems by leveraging HF in cybersecurity may lead to the adoption of non-technical countermeasures (such as user awareness) for a comprehensive and holistic way to manage cyber security in organisations.
 
Design of appropriate interaction and human–machine interfaces for the handover of control between vehicle automation and human driver is critical to the success of automated vehicles. Problems in this interfacing between the vehicle and driver have led, in some cases, to collisions and fatalities. In this project, Operator Event Sequence Diagrams (OESDs) were used to design the handover activities to and from vehicle automation. Previous work undertaken in driving simulators has shown that the OESDs can be used to anticipate the likely activities of drivers during the handover of vehicle control. Three such studies showed that there was a strong correlation between the activities drivers represented in OESDs and those observed from videos of drivers in the handover process, in driving simulators. For the current study, OESDs were constructed during the design of the interaction and interfaces for the handover of control to and from vehicle automation. Videos of drivers during the handover were taken on motorways in the UK and compared with the predictions from the OESDs. As before, there were strong correlations between those activities anticipated in the OESDs and those observed during the handover of vehicle control from automation to the human driver. This means that OESDs can be used with some confidence as part of the vehicle automation design process, although validity generalisation remains an important goal for future research.
 
We provide evidence for a power law relationship between the subjective one-dimensional Instantaneous Self Assessment workload measure (five-level ISA-WL scale) and the radio communication of air traffic controllers (ATCOs) as an objective task load variable. It corresponds to Stevens’ classical psychophysics relationship between physical stimulus and subjective response, with characteristic power law exponent γ of the order of 1. The theoretical model was validated in a human-in-the loop air traffic control simulation experiment with traffic flow as environmental stimulus that correlates positively with ATCOs frequency and duration of radio calls (task load, RC-TL) and their reported ISA-WL. The theoretical predictions together with nonlinear regression-based model parameter estimates expand previously published results that quantified the formal logistic relationship between the subjective ISA measure and simulated air traffic flow (Fürstenau et al. in Theor Issues Ergon Sci 21(6): 684–708, 2020). The present analysis refers to a psychophysics approach to mental workload suggested by (Gopher and Braune in Hum Factors 26(5): 519–532, 1984) that was recently used by (Bachelder and Godfroy-Cooper in Pilot workload esimation: synthesis of spectral requirements analysis and Weber's law, SCL Tech, San Diego, 2019) for pilot workload estimation, with a corresponding power law exponent in the typical range of Stevens’ exponents. Based on the hypothesis of cognitive resource limitation, we derived the power law by combination of the two logistic models for ISA-WL and communication TL characteristics, respectively. Despite large inter-individual variance, the theoretically predicted logistic and power law parameter values exhibit surprisingly close agreement with the regression-based estimates (for averages across participants). Significant differences between logistic ISA-WL and RC-TL scaling parameters and the corresponding Stevens exponents as ratio of these parameters quantify the TL/WL dissociation with regard to traffic flow. The sensitivity with regard to work conditions of the logistic WL-scaling parameter as well as the power law exponent was revealed by traffic scenarios with a non-nominal event: WL sensitivity increased significantly for traffic flow larger than a critical value. Initial analysis of a simultaneously measured new neurophysiological (EEG) load index (dual frequency head maps, DFHM, (Radüntz in Front Physiol 8: 1–15, 2017)) provided evidence for the power law to be applicable to the DFHM load measure as well.
 
Since the start of industrialization, machine capabilities have increased in such a way that human control of processes has evolved from simple (with mechanization) to cognitive (with computerization), and even emotional (with semi/full automation). The processes have also evolved from simple to complicated, and now complex systems, in the emerging context of Industry 4.0. The objective of the special issue “Human and Industry 4.0” is to benefit from studies and results from current manufacturing projects to highlight clues and good practices to design intelligent manufacturing systems for Industry 4.0, then paying attention to human involvements in order to unsure what it looks like in practice and how to realize these systems, especially when it comes to maintenance and operations. This paper aims to summarize the scientific papers that contributed to the Special Issue “Human and Industry 4.0”.
 
Industrial cobotics is presented as a way of business competitiveness by combining human skills and decision making with robotic advantages. The place and safety of humans in cobotic (collaborative robotic) systems are the subjects of much discussion. This article provides a qualitative overview of the main multidisciplinary fields related to the place of human operators during the design process of humans–robots’ systems and discusses paths for effective consideration of the human challenge during this kind of design projects. The added value of this article is its multidisciplinary aspect. Readers will find in this article a technological overview of cobotics, different methodologies and design models focused on final users, interesting examples of evaluation indicators potentially adapted to an effective consideration of humans during the design process of cobotic systems (economic, technical, and human) and guidelines seeking to support cobotic system designers to succeed considering final users during the design process.
 
We build a system dynamics model based on a conceptual model originally proposed by safety scientist Jens Rasmussen to explore the dynamics of a safety system subject to pressures for performance improvement. Rasmussen described forces that generate a drift in the boundary of acceptable performance that can push the organization towards “flirting with the margin” and thus operate at very high risk of catastrophic safety failure. Simulations of the model faithfully replicate the behavior described by Rasmussen and others in a variety of scenarios. Simulation experiments further illuminate the potential for risky behavior and point towards some approaches to better system safety.
 
Photos from the control room of the studied power plants (operators’ images were removed due to ethical considerations)
Workload has long been considered as one of the important factors for personal functions and malfunctions, particularly in complex systems. Undertaking operations in workstations of such systems usually entails complex tasks and poor cognitive performance of their operators may contribute to human error and critical subsequent consequences. Although many studies have investigated the effects of workload on the cognitive performance, there is a gap for specific jobs and operations such as control room operation. This paper then aims to determine that what dimensions of the workload has more impact on cognitive performance of a combined cycle power plant (CCPP) Control room operators. Control room operators from two CCPPs participated (n = 95) in this study. Hierarchical task analysis (HTA) was employed to perform the job analysis. To assess the perceived workload, NASA Task Load Index (NASA-TLX) was performed at the end of the work shift. The participants were subjected to three cognitive performance tests including sustained attention, simple reaction and working memory at the beginning and end of the work shift. The values of mental demand on check and control tasks (92.17 ± 4.38), decisions about abnormal conditions (90.16 ± 5.71) and reporting (85.09 ± 3.25) were high. The task of communication and coordination in terms of temporal demand (71.66 ± 7.3) and performance (68.04 ± 4.92) had higher values compared to other tasks. The highest weighted workload (84.27 ± 6.48) was also attributed to the task of checking and controlling. Sustained attention and working memory were more susceptible to excessive workload among CCPP control room operators.
 
The advent of Industry 4.0 where humans and intelligent machines coexist, allows machines to assist humans on production lines. During such processes, humans work with other humans and/or machines to produce the required products, forming human-related collaborations. Therefore, Industry 4.0 goes beyond a digital ecosystem by being considered as a System of Information Systems which matches heterogeneous systems. This heterogeneity causes poor information interoperability, weakening the effectiveness of collaboration. This poses an issue: how to facilitate human-related collaborations on production lines into Industry 4.0? Addressing it requires better information interoperability and the definition of indicators that can be used to generate recommendations during collaborations. In this article, we focus on indicators of collaboration context and integrate them into a collaboration context ontology to enhance human-related collaborations into Industry 4.0. We then show how to use it in generating context-aware collaborator recommendations.
 
Graceful extensibility has been recently introduced and can be defined as the ability of a system to extend its capacity to adapt when surprise events challenge its boundaries. It provides basic rules that govern adaptive systems. Railway transportation systems can be considered cyber-physical systems that comprise interacting digital, analog, physical, and human components engineered for safe and reliable railway transport. This enables autonomous driving, new functionalities to achieve higher capacity, greater safety, and real-time health monitoring. New rolling stock introductions require continuous adaptations to meet the challenges of these complex railway systems as an introduction takes several years to complete and deals with changing stakeholder demands, new technologies, and technical constraints which cannot be fully predicted in advance. To sustain adaptability when introducing new rolling stock, the theory of graceful extensibility might be valuable but needs further empirical testing to be useful in the field. This study contributes by assessing the proto-theorems of graceful extensibility in a case study in the railway industry by means of adopting pattern-matching analysis. The results of this study indicate that the majority of theoretical patterns postulated by the theory are corroborated by the data. Guidelines are proposed for further operationalization of the theory in the field. Furthermore, case results indicate the need to adopt management approaches that accept indeterminism as a complement to the prevailing deterministic perspective, to sustain adaptability and deal effectively with surprise events. As such, this study may serve other critical asset introductions dealing with cyber-physical systems in their push for sustained adaptability.
 
Research framework
Results of research
As social media use continues to increase, consumers are beginning to experience social media fatigue leading to concern among marketers about the efficacy of the channel. This research examines social media fatigue through a stressor–strain–outcome model to better understand how consumers cope with this phenomenon and how it impacts adoption behaviors. Data were collected from 452 valid WeChat users through questionnaires and analyzed using SEM with PLS. The results show that information overload, social overload, and privacy concerns significantly affect social media fatigue; system function overload and social overload affect the user’s negative behavior through the mediation of fatigue, not anxiety. Social overload and private concern significantly affect anxiety and fatigue, and anxiety further significantly affect negative usage behavior.
 
This paper addresses the engineering of the ethical behaviors of autonomous industrial cyber-physical human systems in the context of Industry 4.0. An ethical controller is proposed to be embedded into these autonomous systems, to enable their successful integration in the society and its norms. This proposed controller that integrates machine ethics is realized through three main strategies that utilize two ethical paradigms, namely deontology, and consequentialism. These strategies are triggered according to the type of event sensed and the state of the autonomous industrial cyber-physical human systems, their combination being potentially unknown or posing ethical dilemmas. Two case studies are investigated, that deal with a fire emergency, and two different contexts i.e. one with an autonomous train, and one with an autonomous industrial plant, are discussed to illustrate the controller utilization. The case studies demonstrate the potential benefits and exemplify the need to integrate ethical behaviors in autonomous industrial cyber-physical human systems already at the design phase. The proposed approach, use cases, and discussions make evident the need to address ethical aspects in new efforts to engineer industrial systems in the context of Industry 4.0.
 
This paper presents a field workshop organised by the Healthcare Improvement Scotland (HIS) focusing on the evaluation of the formalised AcciMap approach by patient safety practitioners of the National Health Service (NHS). Participants who were experienced in incident analysis relating to patient safety and risk management across different NHS boards but had no prior knowledge using the AcciMap approach were recruited for a case study analysis (Wrong Patient) (Chassin and Becher in Ann Intern Med 136:826–833, 2002). They were subsequently divided into three teams after introduction and training, where each team performed an independent case analysis. AcciMap outcomes produced indicated both similar and varying contributing factors identified by each team. This was also reflected in their formulation of safety recommendations. Their findings were then compared with each other (reliability) and with external review (validity). Based on results obtained from the survey instrument distributed after the exercise and focus discussions, the AcciMap approach was generally perceived as intuitive and a potentially relevant toolkit for incident investigations. However, questions were raised particularly regarding the usability (ease of use) in conducting analyses compared RCA techniques.
 
Research model
This paper aims to develop a concept of incentive gamification for organizations in the digital era. Incentive gamification is an incentive-based policy using the game pattern. This policy aims to improve performance of employee who works in the marketing department of such e-commerce as an online marketer. This study involves 104 female employees. Data were collected using questionnaire and analysed using regression analysis. The results show that there was a significant positive effect between personal dexterity on learning experience and individual performance. Furthermore, incentive gamification was also proven to moderate the relationship between personal dexterity, learning experience and also employee performance. Theoretical and managerial implication, as well as future research directions are also discussed.
 
One objective of Industry 4.0 is to reach a better system performance as well as to have a better consideration of humans. This would be done by benefiting from knowledge and experience of humans, and balancing in a reactive way some complex or complicated tasks with intelligent systems. Several studies already dealt with such an objective, but few are done at a methodological level, which forbids, for example, the correct evaluation of design choices in terms of human awareness of the situation or mental workload when designing intelligent manufacturing systems integrating the human. Indeed, increasing the intelligence and autonomy of industrial systems and their composing entities (resources, products, robots…), as fostered by Industry 4.0, increases their overall complexity. This modification reduces the ability to understand the behaviors of these systems, and leads to the difficulty for humans not only to elaborate alternative decisions when required, but also to make effective decisions and understand their consequences. This paper evaluates such a design methodology, the Cognitive Work Analysis (CWA), and its applicability when designing an assistance system to support Human in the control of Intelligent Manufacturing System in Industry 4.0. Among several functions identified through the application of CWA, the assistant system might have to integrate a digital twin of the intelligent manufacturing system. The evaluation of the methodology through the one of the designed assistant systems is done using a micro-world, which is an intelligent manufacturing cell composed of intelligent mobile ground robots, products, and static production robots interacting together and with a human supervisor in charge of the reaching of several time-based and energy-based performances indicators. The assistant system embeds a digital twin of the intelligent manufacturing system. Twenty-three participants took part in experiments to evaluate the designed assistance system. First results show that the assistance system enables participants to have a correct awareness of the situation and a correct evaluation of their alternative decisions, while their mental workload is managed and expected production performances are reached. This paper contains an analysis of these experiments and points out some limits of the CWA method in the context of Industry 4.0, especially the lack of tool enabling to specify clearly the cooperation processes between the supervisor and the intelligent manufacturing system. This paper concludes with potential research avenues, the main one being the potential benefits of coupling CWA with human–machine cooperation principles to fine tune and adapt the cooperation between the human and the intelligent manufacturing system.
 
Structure of the online experiment
Presentation of the allocation result in the three experimental conditions. Note: The third part of the figure is a screenshot of the online questionnaire—the text on there is in German explaining the participants how to allocate the tasks and naming the different production steps
Independent and dependent variables and their assumed connections
New technologies are ever evolving and have the power to change human work for the better or the worse depending on the implementation. For human–robot interaction (HRI), it is decisive how humans and robots will share tasks and who will be in charge for decisions on task allocation. The aim of this online experiment was to examine the influence of different decision agents on the perception of a task allocation process in HRI. We assume that inclusion of the worker in the allocation will create more perceived work resources and will lead to more satisfaction with the allocation and the work results than a decision made by another agent. To test these hypotheses, we used a fictional production scenario where tasks were allocated to the participant and a robot. The allocation decision was either made by the robot, by an organizational unit, or by the participants themselves. We then looked for differences between those conditions. Our sample consisted of 151 people. In multiple ANOVAs, we could show that satisfaction with the allocation process, the solution, and with the result of the work process was higher in the condition where participants themselves were given agency in the allocation process compared to the other two. Those participants also experienced more task identity and autonomy. This has implications for the design of allocation processes: The inclusion of workers in task allocation can play a crucial role in leveraging the acceptance of HRI and in designing humane work systems in Industry 4.0.
 
An instantiation of state transition model
Illustration of areas with different density of coordination points
The re-coordination process of Flight LNI043 represented as the state transition model
ρ\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\rho$$\end{document} of areas where the working points representing Flights LNI043 and LNI610 are situated
State space models with characteristics of regular organizations and HROs: a a regular organization characterized by sparser coordination points; b a regular organization characterized by unevenly-distributed coordination points; c a regular organization characterized by biasedly-distributed coordination points; and d a typical HRO
Resilience is a topic widely discussed in the system safety community yet with various conceptualizations which have not been fully converged in principle. Characterization of resilience of socio-technical systems is then left open to be interpreted by alternative means. As one of the means, coordinated control theory (CCT) can explain a mechanism that enables the systems to achieve adaptations constantly in response to consecutive disturbances and changes. This article presents a theoretical viewpoint for depicting continuity of a system’s resilient performance, based on coordinated control, as understanding of safety degradation and accident incubation in socio-technical systems. The theoretical viewpoint was exemplified, via preliminary analysis of resilient processes in the practical context of combining air crash LNI610, Lion Air, Indonesia, 2018 and its pre-accident story. This article also demonstrates the potential that the CCT view of resilience supports the high reliability organization (HRO) theory, by conceptually visualizing the HROs’ characteristics that have been well grounded in empirical observations, and comparing the visualized state space models that describe HROs and regular organizations respectively. The CCT insights into resilient performance and processes of a system/organization make theoretical sense how to maintain system states aligned with coordinated control principles, thereby enhancing the system’s capacity for adapting to a dynamic and uncertain work environment. Future research will focus on refining the proposed framework for descriptions of input/output behaviors of the resilient systems, as well as addressing self-organization contributing to growth of the systems’ adaptive capacity.
 
Top-cited authors
Natasha Merat
  • University of Leeds
Anna Schieben
  • German Aerospace Center (DLR)
Tyron Louw
Ruth Madigan
  • University of Leeds
Makoto Itoh
  • University of Tsukuba