Sociotechnical Resilience: A Preliminary Concept

This article presents the concept of sociotechnical resilience by employing an interdisciplinary perspective derived from the fields of science and technology studies, human factors, safety science, organizational studies, and systems engineering. Highlighting the hybrid nature of sociotechnical systems, we identify three main constituents that characterize sociotechnical resilience: informational relations, sociomaterial structures, and anticipatory practices. Further, we frame sociotechnical resilience as undergirded by the notion of transformability with an emphasis on intentional activities, focusing on the ability of sociotechnical systems to shift from one form to another in the aftermath of shock and disturbance. We propose that the triad of relations, structures, and practices are fundamental aspects required to comprehend the resilience of sociotechnical systems during times of crisis.     

Toward an Epidemiology of Safety and Security Risks: An Organizational Vulnerability Assessment in International Airports

International airports are complex sociotechnical systems that have an intrinsic potential to develop safety and security disruptions. In the absence of appropriate defenses, and when the potential for disruption is neglected, organizational crises can occur and jeopardize aviation services. This investigation examines the ways in which modern international airports can be “authors of their own misfortune” by adopting practices, attitudes, and behaviors that could increase their overall level of vulnerability. A sociotechnical perspective, the macroergonomic approach, is applied in this research to detect the potential organizational determinants of vulnerability in airport operations. Qualitative data nurture the case study on international airports produced by the present research. Findings from this study highlight that systemic weaknesses frequently reside in areas at the intersection of physical, organizational, and social spaces. Specific pathways of vulnerability can be drawn across these areas, involving the following systemic layers: individual, task, tools and technology, environment, and organization. This investigation expands the existing literature on the dynamics that characterize crisis incubation in multiorganization, multistakeholder systems such as international airports and provides practical recommendations for airport managers to improve their capabilities to early detect symptoms of organizational vulnerability.     

Coordinability and Consistency in Accident Causation and Prevention: Formal System Theoretic Concepts for Safety in Multilevel Systems

Although a “system approach” to accidents in sociotechnical systems has been frequently advocated, formal system theoretic concepts remain absent in the literature on accident analysis and system safety. To address this gap, we introduce the notions of coordinability and consistency from the hierarchical and multilevel systems theory literature. We then investigate the applicability and the importance of these concepts to accident causation and safety. Using illustrative examples, including the worst disaster in aviation history, and recent incidents in the United States of aircraft clipping each other on the tarmac, we propose that the lack of coordinability is a fundamental failure mechanism causing or contributing to accidents in multilevel systems. We make a similar case for the lack of consistency. Coordinability and consistency become ingredients for accident prevention, and their absence fundamental failure mechanisms that can lead to system accidents. Finally, using the concepts introduced in this work, we identify several venues for further research, including the development of a theory of coordination in multilevel systems, the investigation of potential synergies between coordinability, consistency, and the high reliability organizations paradigm, and the possibility of reframing the view that “sloppy management is the root cause of many industrial accidents” as one of lack of coordinability and/or consistency between management and operations. By introducing and expanding on the concepts of coordinability and consistency, we hope to contribute to the thinking about, and the to language of, accident causation, and prevention and to add to the intellectual toolkit of safety professionals and academics.     

Enterprise risk management for automation in correctional facilities with pandemic and other stressors

Real-time tracking of tool and equipment inventories is a critical function of many organizations and sectors. For prisons and correctional facilities, tracking and monitoring of assets such as cookware, hardware, keys, janitorial equipment, vocational/technical specialty tools, etc., is essential for safety, security, trust, efficiency, education, etc. The performance of automated systems for this purpose can be diminished by a variety of emergent and future sociotechnical factors alone and in combination. This article introduces a methodology for contractor evaluation and selection in acquisition of innovative asset management systems, with an emphasis on evolving system requirements under uncertainty. The methodology features a scenario-based preferences analysis of emergent and future conditions that are disruptive to the performance of the asset-control system. The conditions are across technologies, operating environments, regulations, workforce behaviors, offender behaviors, prices and markets, organizations, cyber threats, etc. The methodology addresses the influence and interaction of the conditions to disrupt system priorities. Examples include: (i) infectious disease disrupting priorities among requirements and (ii)  radio-frequency identification (RFID) and wireless-technology innovations disrupting priorities among stakeholders. The combinations of conditions that most and least matter for the system acquisition are characterized. The methodology constitutes a risk register for monitoring sources of risk to project performance, schedule, and cost throughout the system lifecycle. The results will be of interest to both practitioners and scholars engaged in systems acquisition as the pandemic interacts with other factors to affect risk, uncertainty, and resilience of organizational missions and operations.     

System Dynamics Understanding in Projects: Information Sharing,Psychological Safety,and Performance Effects

Systems thinking has proven useful in project management planning activities and has been suggested as a critical driver of a range of beneficial organizational behaviors. Yet, empirical evidence on the myriad of ways in which systems thinking can impact internal project dynamics and performance remains limited. This study focuses on one aspect of systems thinking in particular: the ability to recognize and understand the dynamics of systems and their features (e.g., feedback and delay). It makes use of a unique, large‐scale interview data set along with objective and structured survey data drawn from multiple sources associated with supply chain system implementation projects. Analysis suggests that an individual's understanding of system dynamics as well as the similarity of such understanding to that typical of their team is, in fact, a strong predictor of both perceptions of psychological safety and information sharing quality in project work. These outcomes appear to mediate the relationship between system dynamics understanding and performance.     

A Hybrid Methodology for Modeling Risk of Adverse Events in Complex Health‐Care Settings

In spite of increased attention to quality and efforts to provide safe medical care, adverse events (AEs) are still frequent in clinical practice. Reports from various sources indicate that a substantial number of hospitalized patients suffer treatment‐caused injuries while in the hospital. While risk cannot be entirely eliminated from health‐care activities, an important goal is to develop effective and durable mitigation strategies to render the system “safer.” In order to do this, though, we must develop models that comprehensively and realistically characterize the risk. In the health‐care domain, this can be extremely challenging due to the wide variability in the way that health‐care processes and interventions are executed and also due to the dynamic nature of risk in this particular domain. In this study, we have developed a generic methodology for evaluating dynamic changes in AE risk in acute care hospitals as a function of organizational and nonorganizational factors, using a combination of modeling formalisms. First, a system dynamics (SD) framework is used to demonstrate how organizational‐level and policy‐level contributions to risk evolve over time, and how policies and decisions may affect the general system‐level contribution to AE risk. It also captures the feedback of organizational factors and decisions over time and the nonlinearities in these feedback effects. SD is a popular approach to understanding the behavior of complex social and economic systems. It is a simulation‐based, differential equation modeling tool that is widely used in situations where the formal model is complex and an analytical solution is very difficult to obtain. Second, a Bayesian belief network (BBN) framework is used to represent patient‐level factors and also physician‐level decisions and factors in the management of an individual patient, which contribute to the risk of hospital‐acquired AE. BBNs are networks of probabilities that can capture probabilistic relations between variables and contain historical information about their relationship, and are powerful tools for modeling causes and effects in many domains. The model is intended to support hospital decisions with regard to staffing, length of stay, and investments in safety, which evolve dynamically over time. The methodology has been applied in modeling the two types of common AEs: pressure ulcers and vascular‐catheter‐associated infection, and the models have been validated with eight years of clinical data and use of expert opinion.     

Interference Phenomena in Temporal Evolution of Accident Probability in Workplaces

The aim of this article is to investigate some implications of complexity in workplace risk assessment. Workplace is examined as a complex system, and some of its attributes and aspects of its behavior are investigated. Failure probability of various workplace elements is examined as a time variable and interference phenomena of these probabilities are presented. Potential inefficiencies of common perceptions in applying probabilistic risk assessment models are also discussed. This investigation is conducted through mathematical modeling and qualitative examples of workplace situations. A mathematical model for simulation of the evolution of workplace accident probability in time is developed. Its findings are then attempted to be translated in real-world terms and discussed through simple examples of workplace situations. The mathematical model indicates that workplace is more likely to exhibit an unpredictable behavior. Such a behavior raises issues about usual key assumptions for the workplace, such as aggregation. Chaotic phenomena (nonlinear feedback mechanisms) are also investigated for in simple workplace systems cases. The main conclusions are (1) that time is an important variable for risk assessment, since behavior patterns are complex and unpredictable in the long term and (2) that workplace risk identification should take place in a holistic view (not by work post).     

Risk assessment based on a STPA–FMEA method: A case study of a sweeping robot

Despite rapid developments in the quality and safety of consumer products, the rise of intelligent household appliances, such as sweeping robots, has introduced new safety concerns. Considering “person–product–environment” elements and the complex systems of emerging consumer products, this study presents a new method of risk assessment for consumer products: systems theoretic process analysis (STPA)–failure mode and effects analysis (FMEA). As a case study, this method is applied to the safety control of a sweeping robot. The results suggest that this method can identify all the possible failure modes and injury scenarios among the product components, and the safety constraints in the hierarchical control structure of the interactive system. Moreover, the STPA–FMEA method combines user and environmental factors with the value of product risk events, based on the risk priority number (RPN). This provides an accurate and orderly system to reduce or eliminate the root causes of accidents and injuries. Finally, analysis of unsafe control behavior and its causes can be used to suggest improved safety constraints, which can effectively reduce the risk of some injury scenarios. This paper presents a new method of risk assessment for consumer products and a general five-level complex index system.     

A Resilience-Based Approach to Risk Assessments—Building Resilient Organizations under Arctic Conditions

Reliability and higher levels of safety are thought to be achieved by using systematic approaches to managing risks. The assessment of risks has produced a range of different approaches to assessing these uncertainties, presenting models for how risks affect individuals or organizations. Contemporary risk assessment tools based on this approach have proven difficult for practitioners to use as tools for tactical and operational decision making. This article presents an alternative to these assessments by utilizing a resilience perspective, arguing that complex systems are inclined to variety and uncertainty regarding the results they produce and are therefore prone to systemic failures. A continuous improvement approach is a source of reliability when managing complex systems and is necessary to manage varieties and uncertainties. For an organization to understand how risk events occur, it is necessary to define what is believed to be the equilibrium of the system in time and space. By applying a resilience engineering (RE) perspective to risk assessment, it is possible to manage this complexity by assessing the ability to respond, monitor, learn, and anticipate risks, and in so doing to move away from the flawed frequency and consequences approach. Using a research station network in the Arctic as an example illustrates how an RE approach qualifies assessments by bridging risk assessments with value-creation processes. The article concludes by arguing that a resilience-based risk assessment can improve on current practice, including for organizations located outside the Arctic region.     

System of Systems Engineering and Risk Management of Extreme Events: Concepts and Case Study

The domain of risk analysis is expanded to consider strategic interactions among multiple participants in the management of extreme risk in a system of systems. These risks are fraught with complexity, ambiguity, and uncertainty, which pose challenges in how participants perceive, understand, and manage risk of extreme events. In the case of extreme events affecting a system of systems, cause‐and‐effect relationships among initiating events and losses may be difficult to ascertain due to interactions of multiple systems and participants (complexity). Moreover, selection of threats, hazards, and consequences on which to focus may be unclear or contentious to participants within multiple interacting systems (ambiguity). Finally, all types of risk, by definition, involve potential losses due to uncertain events (uncertainty). Therefore, risk analysis of extreme events affecting a system of systems should address complex, ambiguous, and uncertain aspects of extreme risk. To accomplish this, a system of systems engineering methodology for risk analysis is proposed as a general approach to address extreme risk in a system of systems. Our contribution is an integrative and adaptive systems methodology to analyze risk such that strategic interactions among multiple participants are considered. A practical application of the system of systems engineering methodology is demonstrated in part by a case study of a maritime infrastructure system of systems interface, namely, the Straits of Malacca and Singapore.     

Modelling and analysis of dynamic capacity complexity in multi-stage production

The uncertainty associated with managing dynamic capacity problem is the main source of its complexity. This article presents a system dynamics approach to model and analyse operational complexity of dynamic capacity in multi-stage production. The unique feature of this approach is that it captures the stochastic nature of three main sources of complexity associated with dynamic capacity. These are the demand, internal manufacturing delay and capacity scalability delay. The developed model was demonstrated by an industrial case study of multi-stage printed circuit board assembly line. The analysis of simulation experiments showed that ignoring complexity sources can lead to wrong decisions concerning both scaling levels and backlog management decisions. In addition, a general trade-off between the controllability and complexity of the dynamic capacity was illustrated. Finally, comparative analysis of the effect of each of these sources on the complexity level revealed that internal delay has the highest impact on dynamic capacity efficiency. Guidelines and recommendations for better capacity management and reduction of its complexity are presented.     

复杂信息度量的安全系统结构复杂性评价

作为复杂性研究和安全研究理论与方法的进一步扩展,建立复杂格空间,搭建了复杂性参量的立体化刻画的框架,确定熵的信息度量为复杂格空间的大小(维度)的测度的尺度,构造出复杂性测度的全方位的测度体系;将此理论与方法应用与工程系统的复杂性研究中,以煤矿工程系统的安全系统复杂性研究为例,从矿井开拓巷道系统联结关系、节点、环节、矿井安全子系统复合性、矿井安全监测系统网络、安全设施设置、监测系统、井下人员定位系统测定点分布等结构复杂性要素,进行复杂性评价与实证研究.     

Rethinking Risk Assessment for Public Utility Safety Regulation

To aid in their safety oversight of large‐scale, potentially dangerous energy and water infrastructure and transportation systems, public utility regulatory agencies increasingly seek to use formal risk assessment models. Yet some of the approaches to risk assessment used by utilities and their regulators may be less useful for this purpose than is supposed. These approaches often do not reflect the current state of the art in risk assessment strategy and methodology. This essay explores why utilities and regulatory agencies might embrace risk assessment techniques that do not sufficiently assess organizational and managerial factors as drivers of risk, nor that adequately represent important uncertainties surrounding risk calculations. Further, it describes why, in the special legal, political, and administrative world of the typical public utility regulator, strategies to identify and mitigate formally specified risks might actually diverge from the regulatory promotion of “safety.” Some improvements are suggested that can be made in risk assessment approaches to support more fully the safety oversight objectives of public regulatory agencies, with examples from “high‐reliability organizations” (HROs) that have successfully merged the management of safety with the management of risk. Finally, given the limitations of their current risk assessments and the lessons from HROs, four specific assurances are suggested that regulatory agencies should seek for themselves and the public as objectives in their safety oversight of public utilities.     

Fuzzy System Dynamics Risk Analysis (FuSDRA) of Autonomous Underwater Vehicle Operations in the Antarctic

With the maturing of autonomous technology and better accessibility, there has been a growing interest in the use of autonomous underwater vehicles (AUVs). The deployment of AUVs for under-ice marine science research in the Antarctic is one such example. However, a higher risk of AUV loss is present during such endeavors due to the extreme operating environment. To control the risk of loss, existing risk analyses approaches tend to focus more on the AUV's technical aspects and neglect the role of soft factors, such as organizational and human influences. In addition, the dynamic and complex interrelationships of risk variables are also often overlooked due to uncertainties and challenges in quantification. To overcome these shortfalls, a hybrid fuzzy system dynamics risk analysis (FuSDRA) is proposed. In the FuSDRA framework, system dynamics models the interrelationships between risk variables from different dimensions and considers the time-dependent nature of risk while fuzzy logic accounts for uncertainties. To demonstrate its application, an example based on an actual Antarctic AUV program is presented. Focusing on funding and experience of the AUV team, simulation of the FuSDRA risk model shows a declining risk of loss from 0.293 in the early years of the Antarctic AUV program, reaching a minimum of 0.206 before increasing again in later years. Risk control policy recommendations were then derived from the analysis. The example demonstrated how FuSDRA can be applied to inform funding and risk management strategies, or broader application both within the AUV domain and on other complex technological systems.     

Integrating Software into PRA: A Test-Based Approach

Probabilistic risk assessment (PRA) is a methodology to assess the probability of failure or success of a system's operation. PRA has been proved to be a systematic, logical, and comprehensive technique for risk assessment. Software plays an increasing role in modern safety critical systems. A significant number of failures can be attributed to software failures. Unfortunately, current probabilistic risk assessment concentrates on representing the behavior of hardware systems, humans, and their contributions (to a limited extent) to risk but neglects the contributions of software due to a lack of understanding of software failure phenomena. It is thus imperative to consider and model the impact of software to reflect the risk in current and future systems. The objective of our research is to develop a methodology to account for the impact of software on system failure that can be used in the classical PRA analysis process. A test-based approach for integrating software into PRA is discussed in this article. This approach includes identification of software functions to be modeled in the PRA, modeling of the software contributions in the ESD, and fault tree. The approach also introduces the concepts of input tree and output tree and proposes a quantification strategy that uses a software safety testing technique. The method is applied to an example system, PACS.     

The Crucial Role of Nomothetic and Idiographic Conceptions of Time: Interdisciplinary Collaboration in Nuclear Waste Management

The disposal of nuclear waste involves extensive time scales. Technical experts consider up to 1 million years for the disposal of spent fuel and high‐level waste in their safety assessment. Yet nuclear waste is not only a technical but also a so‐called sociotechnical problem and, therefore, requires interdisciplinary collaboration between technical, natural, social sciences, and the humanities in its management. Given that these disciplines differ in their language, epistemics, and interests, such collaboration might be problematic. Based on evidence from cognitive psychology, we suggest that, in particular, a concept like time is presumably critical and can be understood differently. This study explores how different scientific disciplines understand extensive time scales in general and then focuses on nuclear waste. Eighteen qualitative exploratory interviews were conducted with experts for time‐related phenomena of different disciplines, among them experts working in nuclear waste management. Analyses revealed two distinct conceptions of time corresponding to idiographic and nomothetic research approaches: scientists from the humanities and social sciences tend to have a more open, undetermined conception of time, whereas natural scientists tend to focus on a more determined conception that includes some undetermined aspects. Our analyses lead to reflections on potential difficulties for interdisciplinary teams in nuclear waste management. We focus on the understanding of the safety assessment, on potential implications for communication between experts from different disciplines (e.g., between experts from the humanities and engineering for risk assessment and risk communication), and we reflect on the roles of different disciplines in nuclear waste management.     

Sustaining the Benefits of a Quality Initiative through Cooperative Values: A Longitudinal Study

Although research has shown that organizational cultural values influence the success of quality initiatives, how and when cultural values are influential is unclear. This longitudinal study asserts that quality management should be viewed from a dynamic perspective to better understand the role of cooperative cultural values in a quality initiative. We use a multilevel model of quality management, and develop time‐oriented hypotheses using a sociotechnical systems perspective to examine the role of cooperative values. Our analysis uses longitudinal data from over 30 U.S. federal government agencies, collected during an enterprise‐wide quality initiative. We find that, over time, the influence of organization‐level quality practices diminishes, but the influence of cooperative values increases; workgroup‐level quality practices remain consistently important. Our findings reveal the unexplored influences of cooperative values to sustain the benefits of quality management.     

Risk Modeling of Interdependent Complex Systems of Systems: Theory and Practice

The emergence of the complexity characterizing our systems of systems (SoS) requires a reevaluation of the way we model, assess, manage, communicate, and analyze the risk thereto. Current models for risk analysis of emergent complex SoS are insufficient because too often they rely on the same risk functions and models used for single systems. These models commonly fail to incorporate the complexity derived from the networks of interdependencies and interconnectedness (I–I) characterizing SoS. There is a need to reevaluate currently practiced risk analysis to respond to this reality by examining, and thus comprehending, what makes emergent SoS complex. The key to evaluating the risk to SoS lies in understanding the genesis of characterizing I–I of systems manifested through shared states and other essential entities within and among the systems that constitute SoS. The term “essential entities” includes shared decisions, resources, functions, policies, decisionmakers, stakeholders, organizational setups, and others. This undertaking can be accomplished by building on state‐space theory, which is fundamental to systems engineering and process control. This article presents a theoretical and analytical framework for modeling the risk to SoS with two case studies performed with the MITRE Corporation and demonstrates the pivotal contributions made by shared states and other essential entities to modeling and analysis of the risk to complex SoS. A third case study highlights the multifarious representations of SoS, which require harmonizing the risk analysis process currently applied to single systems when applied to complex SoS.     

An Approach to Vulnerability Analysis of Complex Industrial Systems

The concept of vulnerability of complex industrial systems is defined and discussed in relation to risk and system survivability. The discussion is illustrated by referring to a number of previous industrial accidents. The various risk factors, or threats, influencing an industrial system's vulnerability are classified and discussed. Both internal and external threats are covered. The general scope of vulnerability analysis is compared to traditional risk analysis approaches and main differences are illustrated. A general procedure for vulnerability analysis in two steps, including building of scenarios and preparation of relevant worksheets, is described and discussed.     

Analysis of a two-echelon inventory system with returns

Product take-back and recovery activities have grown in recent times as a consequence of stringent government regulations and increased customer awareness of environmental pollution. Inventory management in the context of product returns has drawn the attention of many researchers. However, the inherent complexity of the system with uncertain returns makes the analysis of the system extremely difficult. So far, the literature on this type of system is mostly limited to single echelons. The few papers available in literature on multi-echelon systems with returns base their analyses on simplified assumptions such as non-existence or non-relevance of set-up and holding costs at different levels. In this paper, we relax these assumptions and consider a two-echelon system with returns under more generalized conditions. We develop a deterministic model as well as a stochastic model under continuous review for the system, and provide numerical examples for illustration.