Complex Socio-technical Systems Research Articles

Saving resources without sacrificing results: an empirical investigation of the dishwashing reality of British consumers in an international comparison

Abstract Routine household tasks, such as laundry or dishwashing, are complex socio-technical systems in which a variety of factors and actors interact, including manufacturers, technologies, regulators, consumer practices, cultural norms and infrastructures. A deep understanding of these socio-technical systems is necessary to find the right recommendations on how to optimise this system in order to achieve relevant savings in resource consumption without requiring a complete renewal of the infrastructure installed. In our case, we focus on automatic dishwashing in the United Kingdom and try to find out what an optimised consumer use of the dishwashers installed can look like and how many savings can be achieved. Accordingly, we modelled the base of dishwashers installed and conducted a consumer survey on dishwasher usage behaviour in sufficient detail to understand the interplay between the various factors. By simulating a change in usage behaviour, we find a potential energy saving of 21.3 % simply by following basic rules for selecting the appropriate programmes without the risk of a loss of performance.

Using a digital data analytic tool to capture dynamic change in coordination patterns: An exploratory study of the Apollo 13 mission

The operational environment of complex sociotechnical systems is inherently uncertain, demanding constant coordination restructuring to adapt to dynamic situational demands. However, coordination changes in the Human Factors and Ergonomics Field have primarily been studied using static methods, overlooking moment-by-moment adjustments. In the current study, we address coordination restructuring by using THEME, a digital analytical tool capable of visualising and exploring coordination restructuring from a multi-layered perspective. We examine restructuring in coordination patterns during NASA's Apollo 13 Mission, revealing significant shifts from stable, long-duration ‘coordination hubs' in routine operations to shorter-duration patterns during a crisis situation. Additionally, the results highlight the importance of flexible switching between reciprocal and one-directed coordination, along with enhanced role distribution. This study underscores how exploring temporality-sensitive phenomena like coordination through digital technologies such as THEME, advances our understanding of incident analysis and resilient performance within complex systems.

Inequalities in the production and use of cement and concrete, and their consequences for decarbonisation and sustainable development

Concrete is vital for constructing infrastructure and housing, and cement is the key binding material within concrete. Concrete is an enabler of development, as concrete structures are key to delivering societal services in many sectors. Much recent research on cement and concrete has focussed on technical solutions to decarbonisation; however, there is a knowledge gap around how cement and concrete intersect with other facets of sustainable development. This study explores the intersection of cement and concrete with inequalities, both through their production as commodities and through their use in built assets. An exploratory analysis of this issue was carried out, comprising an evaluation of industry associations’ conceptions of sustainable development and inequalities, an analysis of underlying power dynamics for several inequality issues using Lukes’ three dimensional framework of power, and a reflection on how certain inequalities may pose risks to achieving decarbonisation and sustainable development aims. Our study shows that industry associations’ narratives around sustainable development generally lack a detailed vision for addressing inequalities, in comparison to their focus on decarbonisation. We find that inequalities are a systemic issue for cement and concrete, spanning intra- and inter-national scales, and all three dimensions of power. These findings highlight that several inequalities are consequential from structural, underlying inequalities, whilst other inequalities are specific to the sectors themselves. The cement and concrete sectors are recommended to develop their conception of inequalities in relation to sustainable development: this can help reduce inequalities within their own workforces more effectively, and also reduce the risks of missing their decarbonisation targets. For large, complex socio-technical systems, such as cement and concrete, it is vital for consideration of inequalities to inform strategic planning with regards to decarbonisation and sustainable development.

A taxonomy of factors that contribute to organizational Cybersecurity Awareness (CSA)

Purpose Developing cybersecurity awareness (CSA) is becoming a more and more important goal for modern organizations. CSA is a complex sociotechnical system where social, technical and organizational aspects affect each other in an intertwined way. With the goal of providing a holistic representation of CSA, this paper aims to develop a taxonomy of factors that contribute to organizational CSA. Design/methodology/approach The research used a design science approach including a literature review and practitioner interviews. A taxonomy was drafted based on 71 previous research publications. It was then updated and refined in two iterations of interviews with domain experts. Findings The result of this research is a taxonomy which outline six domains for importance for organization CSA. Each domain includes several activities which can be undertaken to increase CSA within an organization. As such, it provides a holistic overview of the CSA field. Practical implications Organizations can adopt the taxonomy to create a roadmap for internal CSA practices. For example, an organization could assess how well it performs in the six main themes and use the subthemes as inspiration when deciding on CSA activities. Originality/value The output of this research provides an overview of CSA based on information extracted from existing literature and then reviewed by practitioners. It also outlines how different aspects of CSA are interdependent on each other.

A conceptual model for measuring the maturity of an Intelligent Construction Environment

ABSTRACT Construction projects can be regarded as complex sociotechnical systems composed of diverse and dynamically interacting elements. Digital Transformation advancements can support construction companies in creating an environment to cope with complexity and improve performance. Nevertheless, reaching these advantages involves understanding how transformed processes should be managed and measured, such as using maturity assessment tools. The construction industry lacks maturity models encompassing the sector’s main characteristics and focusing on its production context. Therefore, this work proposes a conceptual model for measuring the maturity of an Intelligent Construction Environment from a sociotechnical perspective. Thus, first, the concept of an Intelligent Construction Environment is introduced. Then, based on two empirical studies consisting of 17 interviews and 11 days of on-site data collection, as well as an extensive literature review, 19 measurement dimensions associated with 13 principles and five maturity levels are proposed. This work’s theoretical contributions encompass an in-depth understanding of how the construction industry can be positioned in the digital transformation path from a sociotechnical perspective. Main practical contributions include the proposition of maturity measurement dimensions for an Intelligent Construction Environment, which indicates the aspects construction managers should focus on throughout the digital transformation process of the production environment.

A conceptual model for measuring the maturity of an Intelligent Construction Environment

ABSTRACT Construction projects can be regarded as complex sociotechnical systems composed of diverse and dynamically interacting elements. Digital Transformation advancements can support construction companies in creating an environment to cope with complexity and improve performance. Nevertheless, reaching these advantages involves understanding how transformed processes should be managed and measured, such as using maturity assessment tools. The construction industry lacks maturity models encompassing the sector’s main characteristics and focusing on its production context. Therefore, this work proposes a conceptual model for measuring the maturity of an Intelligent Construction Environment from a sociotechnical perspective. Thus, first, the concept of an Intelligent Construction Environment is introduced. Then, based on two empirical studies consisting of 17 interviews and 11 days of on-site data collection, as well as an extensive literature review, 19 measurement dimensions associated with 13 principles and five maturity levels are proposed. This work’s theoretical contributions encompass an in-depth understanding of how the construction industry can be positioned in the digital transformation path from a sociotechnical perspective. Main practical contributions include the proposition of maturity measurement dimensions for an Intelligent Construction Environment, which indicates the aspects construction managers should focus on throughout the digital transformation process of the production environment.

Examining Ethical and Social Implications of Digital Mental Health Technologies Through Expert Interviews and Sociotechnical Systems Theory

This paper aims to understand how science and technology experts working in the digital mental health field interpret the ethical and social implications of its technologies, combining an ‘expert interview’ methodology with insights from sociotechnical systems theory. Following recruitment of experts in science and technology fields who had experience of supporting the development of DMH interventions, 11 semi-structured interviews were conducted and analyzed in accordance with the Framework Method. A single theme of ‘complexity of implications’ is presented here and divided into the categories of ‘implications for users’, ‘implications for healthcare professionals and systems’, and ‘implications for society’. Participants identified a range of ethical and social implications of digital mental health technologies at the three different levels, which this discussion relates to three key aspects of complex sociotechnical systems identified in existing theoretical work. These are ‘heterogeneity’, ‘interdependence’ and ‘distribution’, each of which raises important questions for future research about how complex values, relationships and responsibilities should be negotiated in digital mental health. The paper concludes that this study’s approach provides a model for understanding the implications of digital health more broadly, with participants’ combined experience and knowledge shedding light on key interventions at the forefront of digitalization in healthcare.

Managing Complexity in Socio-Technical Systems by Mimicking Emergent Simplicities in Nature: A Brief Communication.

In the context of socio-technical systems, traditional engineering approaches are inadequate, calling for a fundamental change in perspective. A different approach encourages viewing socio-technical systems as complex living entities rather than through a simplistic lens, which enhances our understanding of their dynamics. However, these systems are designed to facilitate human activities, and the goal is not only to comprehend how they operate but also to guide their function. Currently, we lack the appropriate terminology. Hence, we introduce two principal concepts, simplexity and complixity, drawing inspiration from how nature conceals intricate mechanisms beneath straightforward, user-friendly interfaces.

A novel approach to runway overrun risk assessment using FRAM and flight data monitoring

Abstract Runway overruns (ROs) are the result of an aircraft rolling beyond the end of a runway, which is one of the accident’s types that most frequently occurs on aviation. The risk of an RO arises from the synergistic effect among its precursors, such as unstable approaches, long touchdowns and inadequate use of deceleration devices. To analyse this complex socio-technical system, the current work proposes a customised functional resonance analysis method, called FRAM-FDM, as traditional techniques of risk and safety assessment do not identify the interactions and couplings between the various functional aspects of the system itself, especially regarding human and organisational components. Basically, FRAM-FDM is the coupling of a traditional FRAM with flight data monitoring (FDM) techniques, used here to quantify the variabilities of the flight crew performance while executing the required activity (i.e. the landing). In this proposal, these variabilities (i.e. the FRAM functions aspects) are aggregated by the addend of a logistic regression, resulting in a model to evaluate the flare operations and the brake application profile effect on the remaining distance to the end of the runway, used as a reference to classify the landing as acceptable or not. The present application of the FRAM-FDM assesses the operational risk of a sample fleet in overrunning the runway during landing, highlighting the brake pedal application profile as the most relevant contributor. The model improves the knowledge about the system behaviour, being useful to direct flight crew training.

Towards decision-making support for complex socio-technical system safety assessment: A hybrid model combining FRAM and dynamic Bayesian networks

Effectively managing system safety and resilience in critical infrastructures requires addressing emergent risks and critical resonances. This study introduces a quantitative model that merges Monte Carlo Simulation (MCS) of the Functional Resonance Analysis Method (FRAM) and Dynamic Bayesian Network (DBN) to assess technological, organizational, and human performance variability in complex social-technical systems. FRAM identifies system taxonomy and functional variability, while MCS pinpoints critical coupling, supplying prior probabilities for functional resonance. This information feeds into the DBN, facilitating the modeling of causal relationships and probabilistic inferences regarding risk uncertainties and system resonances. The model underwent rigorous testing and validation on a preheater cyclone system within the cement industry. This process involved the utilization of historical field data gathered from six prominent cement industries and input from thirty subject matter experts. The integrated approach deeply analyzes emerging risk indicators, unveiling interactions within organizational, human, and technical subsets, alongside performance variability. Furthermore, the model incorporates system learning parameters, aiding decision-making under uncertainty. These findings advance system safety and resilience management, offering insights for risk assessment and accident prevention across diverse scenarios in complex socio-technical systems.

Abstract PO5-10-09: Capturing Experiences: Navigating Breast Cancer Treatment of Nigerian Patients and Healthcare Providers Using Qualitative Interviews

Abstract Introduction A notable shift has occurred in medical relationships, placing greater emphasis on the role of patients within the healthcare system. A nascent body of literature in the US captures the experiences of patients following a diagnosis, but this is lacking in Nigeria. We used Systems Engineering Initiative for Patient Safety (SEIPS 2.0) as a theoretical framework from the discipline of human factors that serves as a guide for characterizing complex sociotechnical systems comprised of factors, work processes, and outcomes - with the patient and clinicians at the center. We specifically focused on the patient work network, which refers to individuals and communities that play role in supporting patient work. The objective of this study was to elicit the experiences of Nigerian breast cancer patients and healthcare providers by qualitative interviews and characterize productive and counterproductive activities of the patient work network. Methods The study was approved by the IRB. We used snowball sampling and social media to recruit Nigerian breast cancer patients and health care providers with experience treating breast cancer. One researcher conducted interviews that lasted 30–60 min using teleconferencing technology and an interview guide developed for this study. Questions for both patients and healthcare providers covered topics such as patient response to diagnosis, barriers and facilitators to care including people and communities within the patient’s network. We calculated descriptive statistics for demographics. Using thematic analysis, we carried out the analysis in the following stages: data review, category coding and data extraction, and synthesis and integration of findings. Results We interviewed 18 female patients (29-67 yrs old) and 6 healthcare providers (31-42 yrs old; 3 males). Twelve patients received treatment in urban areas and 6 in rural. Four patients had a bachelor's degree. Healthcare providers included primary, specialty, palliative, treatment, diagnostic care. We highlight a subset of the dataset with focus on productive versus unproductive work conducted by family and by religious community, with unproductive defined as potentially having negative impact on the patient and their experience (Table 1). Providers stated that patients who receive family support exhibit better health outcomes compared to those who do not. Providers shared that religious community can perpetuate patient denial in their diagnosis. Both patients and providers discussed an inclination towards seeking traditional care. Despite recognizing the challenges and pressures faced by patients, providers lacked in-depth understanding of the specific experiences patients encountered. Conclusion Our findings highlight the role of family and religious community in conducting activities that are both productive and unproductive facilitating productive activities and its influence on the decision-making process of patients. Alternatively, both family and religious community engage in activities counterproductive to the patient and their illness. Findings emphasize the importance of comprehensive support systems, education, and targeted interventions to improve the experiences and outcomes of Nigerian breast cancer patients. Effective strategies should address cultural beliefs, empower patients to make informed decisions, and enhance provider knowledge regarding the unique challenges faced by patients within the identified barriers. Table. Productive versus unproductive work conducted by family and by religious community Citation Format: Blessing Nwachukwu, Elizabeth Papautsky. Capturing Experiences: Navigating Breast Cancer Treatment of Nigerian Patients and Healthcare Providers Using Qualitative Interviews [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO5-10-09.

El factor humano y la ergonomía en la «seguridad del paciente»

The human condition is linked to error in any activity that is performed, and the healthcare world is no exception. The origin of human error does not lie within the perversity of human nature, instead, it has its origins in latent failures in the healthcare environment and is a consequence of the processes and procedures applied. The science of the Human Factor deals with the application of knowledge to people (capabilities, characteristics and limitations), with the design and the management of the equipment they use and with the environments in which they work and the activities they carry out.Part of the Human Factor are the non-technical skills. These skills greatly influence people's behavior and, therefore, their performance and the quality of healthcare in a very complex socio-technical system.

Integrated methodology for safety analysis based on a system-theoretic approach and numerical simulation

The System-Theoretic Process Analysis (STPA) method is a recognized approach to system safety analysis. However, it still has inadequate capabilities for quantitative safety analysis. To overcome this limitation, an integrated methodology was investigated for quantitative safety analysis of the complex socio-technical system that combines a system-theoretic approach and numerical simulation. In the proposed methodology, STPA method is utilized to reveal potential unsafe control actions (UCAs) and corresponding causes based on the operational principle of the target system from systemic perspective. Moreover, the consequences of identified UCAs can be quantified and safety constraints also can be improved to prevent UCAs using numerical simulations. As a complex system, the blind shear ram preventers (BSRPs) in deepwater drilling activities, with tightly interacting diverse subsystems or components, is employed to illustrate the applicability of the methodology. The results verified that the proposed methodology could evaluate potential hazards and quantify the analysis results. These results will be helpful for the design and safe operations of the BSRP system. The developed methodology has the potential to be used for safety analyses in other process industries.

Characterizing Developers' Linguistic Behaviors in Open Source Development across Their Social Statuses

Open Source Software (OSS) development has attracted numerous developers. As a typical complex sociotechnical system, an OSS project often forms a hierarchical social structure where a few developers are elite while the rest are non-elite. Differences in social status may result in distinct language use behaviors in interpersonal communication. Characterizing such behaviors is critical for supporting efficient and effective communication among developers with different social statuses. This study empirically compared elite and non-elite developers' language behaviors in their communication. We compiled a corpus of - 216,000 discourses collected from 20 large projects on GitHub. We investigated the linguistic differences in three aspects, namely, linguistic styles and characters, main concerns, and sentence patterns. Our findings reveal that elite and non-elite developers showed different linguistic patterns and had different concerns in their discourses. Their discourses also reflect the variation of the main focuses in the development process. Furthermore, elite and non-elite developers exhibited noticeable patterns in their linguistic behaviors in accordance with their roles and corresponding divisions of labor in the production process, no matter which semantic contexts. These findings provide implications for supporting communication that crosses social statuses in OSS development.

Measuring team situation awareness through team communication: A study on nuclear main control room crews.

Situation awareness (SA) in complex socio-technical systems is considered a key cognitive activity, as control crews are often engaged in simultaneous task processes and are required to monitor and evaluate system parameters, making decisions and projections for the future accordingly. However, measuring SA at the team level is still a challenging area of research within the topic. In our research, we applied verbal protocol analysis as an alternative method to assess nuclear power plant control room crews' team SA. We conducted a study of 10 control room crews, examining their intrateam communication and its relatedness to team performance. We have found that communication categories related to the second and third levels of team SA increased significantly after the onset of an emergency event. Furthermore, while none of the team communication categories was related to team performance before the emergency event, all of them showed a strong positive correlation with team performance after the emergency situation occurred. Our results underline the importance of adequate verbalization of key information within the team, so as to support the rapid and accurate development of team SA during emergency situations.

Evaluating health information systems-related errors using the human, organization, process, technology-fit (HOPT-fit) framework.

Complex socio-technical health information systems (HIS) issues can create new error risks. Therefore, we evaluated the management of HIS-related errors using the proposed human, organization, process, and technology-fit framework to identify the lessons learned. Qualitative case study methodology through observation, interview, and document analysis was conducted at a 1000-bed Japanese specialist teaching hospital. Effective management of HIS-related errors was attributable to many socio-technical factors including continuous improvement, safety culture, strong management and leadership, effective communication, preventive and corrective mechanisms, an incident reporting system, and closed feedback loops. Enablers of medication errors include system sophistication and process factors like workarounds, variance, clinical workload, slips and mistakes, and miscommunication. The case management effectiveness in handling the HIS-related errors can guide other clinical settings. The potential of HIS to minimize errors can be achieved through continual, systematic, and structured evaluation. The case study validated the applicability of the proposed evaluation framework that can be applied flexibly according to study contexts to inform HIS stakeholders in decision-making. The comprehensive and specific measures of the proposed framework and approach can be a useful guide for evaluating complex HIS-related errors. Leaner and fitter socio-technical components of HIS can yield safer system use.

Building back better: Modeling decentralized recovery in sociotechnical systems using strategic network dynamics

The ability of sociotechnical systems to recover from disruptions through decentralized, bottom-up processes is a crucial element of their overall resilience, but it is also among the most overlooked in resilience research. This paper proposes a computational framework leveraging dynamic multi-agent networks to conceptualize, model, and quantify multi-agent, decentralized recovery process building upon strategic network formation methods. This innovative approach addresses limitations in conventional strategic network formation models by accounting for the fluidity of structural shifts induced by the strategic behaviors of individual agents, and by acknowledging the inherent heterogeneity within agent populations. The central objective of this study is to highlight the critical role of bottom-up recovery and present a systematic, adaptable framework for modeling these processes in diverse real-world scenarios. We achieve this through four key elements: modeling post-disruption responses, exploring their interdependencies, accommodating multiple equilibria, and generating metrics for scenario comparison and forecasting. Our dynamic strategic network formation model offers valuable insights into crucial trade-offs in decentralized recovery processes and facilitates the integration of both bottom-up and top-down resilience strategies. Furthermore, it could serve as a predictive tool informing initial network architectural decisions by estimating likely post-disruption equilibrium states based on the initial network structure. Ultimately, this study provides a robust platform for analyzing network efficiency and resilience trade-offs, setting the stage for more informed decision-making in complex sociotechnical systems.

Using a Metadata Approach to Extend the Functional Resonance Analysis Method to Model Quantitatively, Emergent Behaviours in Complex Systems

In an increasingly complex world there is a real, urgent need for methodologies to enable engineers to model complex sociotechnical systems, as these now seem to describe the majority of systems in use today. This is, of course, exacerbated by the increasing involvement and augmentation with “black box” AI contributions. Hollnagel produced a methodology (FRAM) which did allow the analyst insights into these systems’ behaviour, but the model-based system engineering applications demand numbers and a quantitative approach. In the last 10 years, this original approach, developed to model systems as sets of interactive, interdependent “functions” (abstracted from agent or component details), has been further developed to the point where it can take the basic data and structures from the current component-focussed system engineering “models”, and can pull them all together into dynamic models (as opposed to the static, fixed System Theoretic Process Accimaps) from which analysts can discern how they really work in practice, and predict the emergent behaviours characteristic of complex systems. This paper describes how the FRAM methodology has now been extended to provide these extra, essential attributes. It also describes its implementation using an open-source software, freely available for use and verification on the GitHub site.

The impact of detergent performance on sustainable consumer laundry behavior: a socio-technical challenge

Abstract The laundry process is energy-intensive and an important target for reducing residential environmental impacts. Category life-cycle analysis (LCA) studies show the primary environmental impact is due to the energy consumed during the use phase, mainly for heating water. However, doing the laundry is a complex socio-technical system, where addressing sustainability requires not only technical levers but also an understanding of users’ habits, practices, and belief systems. This study investigates if and how consumers change their laundry habits and product satisfaction when using a technically lower-performing eco-brand detergent compared to a heavy duty high-performance detergent. These represent two distinct sustainable innovation strategies within the detergent industry, i) high-performance detergents formulated to provide excellent cleaning performance at lower wash temperatures and ii) eco-brand detergents optimized for a lower ingredient footprint but reducing cleaning performance. It is hypothesized that consumers may compensate in ways detrimental to the overall sustainability of the laundry lifecycle. The results showed significantly lower consumer satisfaction with the eco-brand performance which led to compensatory behavior including increased detergent dosing and higher wash temperatures. This study confirms the importance of detergent cleaning performance for sustainable consumer habit changes regarding lower wash temperatures.

Understanding complex processes better-A case study on increasing patient safety and efficiency in a central operating room

Various professional groups are involved in the daily work of the central operating room with the aim of providing the best possible treatment for each individual using modern medical technology (sociotechnical system) in acost-effective manner. Ensuring perioperative patient safety is of particular importance. At the same time, the efficient use of the central operating room is essential for the economic success of ahospital. Preoperative preparation is acomplex process with many substeps that are often difficult to manage. Historically, the focus has been on retrospective learning from errors and incidents. More recent approaches take asystemic view. Acentral idea is to consider the mostly positive course of treatment and the adjustments to daily work that are currently required by the people involved (Safety-II). By taking greater account of how the many components of the system interact, processes can be better understood and specific measures derived. This strengthens the system's ability to adapt to changes and disturbances, thus ensuring that goals are achieved. The functional resonance analysis method (FRAM) is an internationally recognized method for modelling work as done compared to work as imagined. This paper presents the application of FRAM to preoperative preparation in a major regional hospital. Is FRAM suitable for improving process understanding in preoperative preparation? An interdisciplinary project team identified relevant functions of preoperative preparation through document analysis and walkthroughs. Based on this, more than 30guided interviews were conducted with functionaries. The results were presented graphically and specific information, such as safety-related statements or reasons for the variability of functions, were also presented textually. In the next phase, statements were evaluated and compared with the target model and the job descriptions. The FRAM revealed the process as acomplex network of relationships. During the modelling process, avarying degree of centrality and variability of certain functions became apparent. From the observations, the project team selected those with high relevance for patient safety and for the efficiency of the overall process in order to prioritize starting points for deriving measures to increase resilience. These starting points relate either to single functions, such as surgical site marking or to multiple functions that are variable in their execution, such as delays due to nonsynchronized duty times. The FRAM conducted provides valuable new insights into the functioning of complex sociotechnical systems that go far beyond classical linear methods. The awareness of operational processes gained and the resulting dynamic view of interactions within the system enable specific measures to be derived that promote resilient behavior and reduce critical variability, thus contributing to increased patient safety and efficiency.