Analysis Of Socio-technical Systems Research Articles

Logical interdependencies in infrastructure: What are they, how to identify them, and what do they mean for infrastructure risk analysis?

A useful theoretical lens that has emerged for understanding urban resilience is the four basic types of interdependencies in critical infrastructures: the physical, geographic, cyber, and logical types. This paper is motivated by a conceptual and methodological limitation-although logical interdependencies (where two infrastructures affect the state of each other via human decisions) are regarded as one of the basic types of interdependencies, the question of how to apply the notion and how to quantify logical relations remains under-explored. To overcome this limitation, this study focuses on institutions (rules), for example, rules and planned tasks guiding human interactions with one another and infrastructure. Such rule-mediated interactions, when linguistically expressed, have a syntactic form that can be translated into a network form. We provide a foundation to delineate these two forms to detect logical interdependence. Specifically, we propose an approach to quantify logical interdependence based on the idea that (1) there are certain network motifs indicating logical relations, (2) such network motifs can be discerned from the network form of rules, and that (3) the higher the frequency of these motifs between two infrastructures, the greater the extent of logical interdependency. We develop a set of such motifs and illustrate their usage using an example. We conclude by suggesting a revision to the original definition of logical interdependence. This rule-focused approach is relevant to understanding human error in risk analysis of socio-technical systems, as human error can be seen as deviations from constraints that lead to accidents.

Conceptualization of a functional random walker for the analysis of socio-technical systems

The Functional Resonance Analysis Method (FRAM) has been pointed out by several prior studies as an effective approach for modeling socio-technical systems. Despite previous contributions, FRAM still suffers from limited tractability in case of large models such as a difficulty of carrying out reliable and insightful analysis. This paper addresses this gap by proposing an approach inspired by network theory to enhance traditional FRAM analyses, namely the functional random walker (FRW). The definition of FRW complements the notion of random walks accounting for the variability being transferred inside the system from one function to another, offering a cost-effective means of exploring FRAM instantiations. Five design criteria are presented to reproduce such analysis with any FRAM model, along with two indicators, namely the probability of visiting nodes and the mean passage time. These two metrics permit to study the FRAM model both at function level (how a single function behaves within the model) and at system level (how multiple functions interact with each other). A walk-through application of FRW is presented for a healthcare setting. This application revealed how the FRW sheds light on systems’ strengths and vulnerabilities, and highlighted underlying knowledge, otherwise hidden in cluttered visual representations of FRAM instantiations.

Unpacking the Complex Socio-Technical Systems Assemblages in Cybersecurity

The ensuing digital transformation means that cybersecurity solutioning increasingly occurs in the context of complex intractable socio-technical systems comprising non-technical elements, including human, social, and societal factors. These evolving cybersecurity ecosystem dynamics, at the confluence of cyber-physical-social spaces, present several challenges to techno-centric cybersecurity solutions including for risk assessment, threat modelling, and incident analysis. This paper unpacks the complexity of the cybersecurity domain and illustrates the associated socio-technical systems assemblages through a case study and situational analysis of a cybersecurity incident. It then reviews socio-technical systems analysis approaches from the safety management domain and discusses the alignment with and relevance for cybersecurity. The utility of these approaches is demonstrated by applying the functional resonance analysis method to the said cybersecurity incident. The situational analysis surfaces the diverse set of factors, including human, non-human, cultural, economic, institutional, and global, that directly played a role in the unfolding of the incident, and which need to be considered in risk assessment and incident analysis. Further, analysing the incident through the functional resonance analysis method shows the functional dependencies and cascade of performance variability between the different elements in this situation, which goes beyond simple, root-cause, linear causality, and purely technical explanations. Overall, the paper explicates the need for cybersecurity risk assessment and incident analysis that is commensurate with the complexity of underlying socio-technical cyber systems.

Designing Inclusive AI Certifications

For decades, the route to familiarity in AI was through technical studies such as computer science. Yet AI has infiltrated many areas of our society. Many fields are rightfully now demanding at least a passing familiarity with machine learning: understanding the standard architectures, knowledge on how to use them, and addressing common concerns. A few such fields look at the standard ethical issues such as fairness, accountability, and transparency. Very few fields situate AI technologies in sociotechnical system analysis, nor give a rigorous foundation in ethical analysis applied to the design, development, and use of the technologies. We have proposed an undergraduate certificate in AI that gives equal weight to social and ethical issues and to technical matters of AI system design and use, aimed at students outside of the traditional AI-related disciplines. By including social and ethical issues in our AI certificate requirements, we expect to attract a broader population of students. By creating an accessible AI certification, we create an opportunity for individuals from diverse experiences to contribute to the discussion of what AI is, what its impact is, and where it should go in the future.

Linking farmers' perceptions and management decision toward sustainable agroecological transition: evidence from rural Tunisia.

Global food systems face sustainability challenges like undernourishment, inequity, resource degradation, and pollution. Food production and consumption drive environmental change with greenhouse gas emissions, biodiversity loss, and land-system shifts. The climate change crisis has intensified concerns about the ecological impact of these systems. Sustainable food networks, such as community-supported agriculture, are promoting sustainable production and consumption through short supply chains. International bodies like the Food and Agriculture Organization (FAO) and the Consultative Group for International Agricultural Research (CGIAR) are also spearheading initiatives for more equitable and sustainable food systems. In Tunisia, where dryland areas predominate, the ongoing implementation of the Agroecology Initiative provides the context for this study, which explores the drivers and barriers of agroecological transformation in this challenging environment. The research focuses on stakeholder engagement, with a gender perspective to explore farmer perceptions. The study, conducted in the northwest of Tunisia in 2022-2023, involved focus groups, workshops, surveys, and questionnaires with various stakeholders. Findings highlight farmer organizations' potential in promoting sustainable farming, with clear goals, diversified systems, and collaborations. However, challenges such as input scarcity, water shortage, low income, and marketing must be addressed. Results also indicate that over 90% of farmers who received assistance with agroecological practices reported a change in their ideas and practices. Fifty seven percent of the workshops participants identified the olive oil value chain as having the greatest potential for agroecological transformation, but it faces constraints such as climate, lack of policy incentives, training, funding, and difficulty in adopting technical innovations. Women's inclusion in agriculture, environmental, social, and economic challenges were also highlighted. Despite these obstacles, key drivers for agroecological transition were identified. These include the compatibility of many agroecological practices with existing farmer capabilities, their cultural and economic benefits, and the positive outcomes for environmental sustainability and health. The study advocates for a socio-technical systems analysis to address the root causes hindering Tunisia's agroecological transformation. A participatory approach is crucial to understanding priorities and developing a sustainable and resilient food system. Furthermore, the research underscores the importance of considering diverse farmer perspectives and tailoring strategies to support this critical transition effectively.

Strategic Pathways to Alternative Marine Fuels: Empirical Evidence from Shipping Practices in South Korea

This study investigates the transition to a sustainable shipping industry within the framework of the IMO’s 2050 carbon neutrality objective, focusing on sociotechnical systems analysis. This research delves into the sustainable paradigm shift towards alternative marine fuels, such as LNG, methanol, ammonia, and hydrogen, from a sociotechnical transition perspective, analyzing the multilevel perspective challenges and opportunities. Specifically, it scrutinizes the implications of adopting these alternative fuels for global shipping, identifying technical uncertainties, financial constraints, and infrastructure needs. Through a comprehensive review of the existing literature on ship emissions and alternative fuels, coupled with sociotechnical transition theory, this study addresses the multifaceted challenges and opportunities in meeting the IMO’s environmental objectives. It emphasizes the necessity of collaborative governance, innovative niche strategies, and a holistic approach to leverage the current window of opportunity in facilitating the maritime industry’s transition to sustainable fuel options. Finally, this research enhances our understanding of the intricate interplay between technological, social, industrial, and cultural dynamics in the greening of shipping, and offers insights into the strategic adoption of environmentally friendly marine fuels for a sustainable future.

The construction of self-sovereign identity: Extending the interpretive flexibility of technology towards institutions

Ever-growing concerns over ‘Big Brother’ continue driving individuals towards user-centric identity management systems. Nascent innovations are framed as offering Self-Sovereign Identity (SSI). Because of the association with value-laden ideals and technical components like blockchain, SSI is caught up with both hype and idiosyncrasy. Competing interpretations of SSI damage the public discourse and risk misrepresenting affordances these systems might offer. Based on a qualitative inductive interview study and document analysis, this article extrapolates a constructivist theoretical frame – the Extended Model of Interpretive Flexibility – which combines insights from the Social Construction of Technology and the Structurational Model of Technology. The Extended Model of Interpretive Flexibility highlights malleability in the technical implementations and social representations, which in turn is affected by and influences institutional properties around SSI. This research further offers implications for practice around the implementation of SSI, in particular regarding policy, management, and design. For theory on public sector information systems, the proposed model has generalizable potential for the analysis of socio-technical systems and offers future research directions.

A sociotechnical systems analysis of aircraft aerodynamic stall events

AbstractIn 2009, Colgan Air Flight 3407 had a fatal crash in New York due to an aircraft aerodynamic stall. Previous reports had placed the actions of the crew as the cause of the incident; however, this work provides a sociotechnical systems analysis of the events that led up to the fatal accident. An Accimap analysis provides a top‐down systemic analysis of Flight 3407, considering the high‐level governmental and regulatory agencies involvement. An online survey with 47 airline pilots provides a bottom‐up review of pilots’ perceptions and decision‐making in response to aerodynamic stall events. Combining the two approaches generates a holistic approach to managing aerodynamic stall events. Analysis of Flight 3407 identified contributory factors within the higher regulatory and company levels. Furthermore, questions of appropriate training were raised by the pilots within the survey results regarding the immediate response to a stall event which commonly affords a startle and/or surprise response. The impact of “startle and surprise” on the pilots’ response to this situation was identified as a key area to focus on, with design and training recommendations provided. We consider these within the context of recent training recommendations in the industry.

Analysis of airport design for introducing infrastructure for autonomous drones

PurposeConnecting autonomous drones to ground operations and services is a prerequisite for the adoption of scalable and sustainable drone services in the built environment. Despite the rapid advance in the field of autonomous drones, the development of ground infrastructure has received less attention. Contemporary airport design offers potential solutions for the infrastructure serving autonomous drone services. To that end, this paper aims to construct a framework for connecting air and ground operations for autonomous drone services. Furthermore, the paper defines the minimum facilities needed to support unmanned aerial vehicles for autonomous logistics and the collection of aerial data.Design/methodology/approachThe paper reviews the state-of-the-art in airport design literature as the basis for analysing the guidelines of manned aviation applicable to the development of ground infrastructure for autonomous drone services. Socio-technical system analysis was used for identifying the service needs of drones.FindingsThe key findings are functional modularity based on the principles of airport design applies to micro-airports and modular service functions can be connected efficiently with an autonomous ground handling system in a sustainable manner addressing the concerns on maintenance, reliability and lifecycle.Research limitations/implicationsAs the study was limited to the airport design literature findings, the evolution of solutions may provide features supporting deviating approaches. The role of autonomy and cloud-based service processes are quintessentially different from the conventional airport design and are likely to impact real-life solutions as the area of future research.Practical implicationsThe findings of this study provided a framework for establishing the connection between the airside and the landside for the operations of autonomous aerial services. The lack of such framework and ground infrastructure has hindered the large-scale adoption and easy-to-use solutions for sustainable logistics and aerial data collection for decision-making in the built environment.Social implicationsThe evolution of future autonomous aerial services should be accessible to all users, “democratising” the use of drones. The data collected by drones should comply with the privacy-preserving use of the data. The proposed ground infrastructure can contribute to offloading, storing and handling aerial data to support drone services’ acceptability.Originality/valueTo the best of the authors’ knowledge, the paper describes the first design framework for creating a design concept for a modular and autonomous micro-airport system for unmanned aviation based on the applied functions of full-size conventional airports.

Enterprise Digital Transformation using a Sociotechnical System Approach

AbstractDigital transformation is gaining increased attention due to its potential to change the way companies operate and unveil new business strategies. In consideration of the fact that digital transformations occur under specific sociotechnical environments and with particular intentions, success highly depends on the ability of companies to explicitly characterize their sociotechnical context and intended transformation. This paper sheds some light on how companies might approach digital transformation efforts through an enterprise‐level sociotechnical system approach that centers on digital twins and model‐based methods. Research findings and intervention strategies are derived from observations and interviews on ongoing projects, supplemented by findings from the literature. Core systems engineering analysis methods such as Concept of Operations analyses are part of such strategies given their potential to accelerate the sociotechnical system redesign cycle and generate actionable decisions toward digital transformation. A sociotechnical system analysis framework intended to guide organizations in developing their strategic approaches for adopting digital twins as transformation strategy is also shared. This framework and the entire paper assert the importance of taking a sociotechnical system perspective in defining, designing, and implementing a digital transformation.

Socio-technical system analysis of responsible data sharing in water systems as critical infrastructure.

Attention is increasingly focused on the protection of water systems as critical infrastructure, including subsystems of supply, sanitation, hygiene, and management. Similarly increasing consideration is paid to the growing role and impact of data on water systems and management. We explore key challenges associated with data-driven water systems as critical infrastructure. First, we describe the status of water infrastructure as a part of national critical infrastructure. Second, as this infrastructure increasingly relies on the constant flow of data from a huge variety, quality, and complexity of sensors, we provide a descriptive framework to map in detail the particular expertise needed across data-driven water management, applied to the UK water infrastructure as our use case. Third, through the framework of Capabilities Approach (CA) we analyze the specific challenges of data-driven water management, and argue that the current predominant narratives in the water infrastructure discourse have difficulties to effectively convey existing and emerging challenges. Fourth, we further demonstrate the widening gap between infrastructure services and consumer goods, arguing for increased convergence of the utilization of consumer data, and developing open data ecosystems.

Unleashing the Potential of AcciMap in Identifying and Anticipating Systemic Failures: A Case Study of Child Abuse Prevention through Design

This study proposes a new application of AcciMap, a tool initially created within safety science. AcciMap assists designers by identifying and anticipating systemic conditions that have contributed to prior failures and may influence the implementation of new design interventions. For validation, we applied AcciMap to analyze factors contributing to child abuse cases in South Korea. This process identified potential facilitators and barriers related to the implementation of a child abuse assessment checklist developed by the research team. We found that AcciMap enables designers to apply systems thinking to complex problems. It allows the consideration of potential implementation issues for new design interventions across multiple levels, helping designers understand and anticipate the complex systemic structures affecting their intervention. By exploring how AcciMap can be used for in-depth sociotechnical system analysis, this study contributes to advancing our understanding of systemic design.

Open Source Software Sustainability: Combining Institutional Analysis and Socio-Technical Networks

Sustainable Open Source Software (OSS) forms much of the fabric of our digital society, especially successful and sustainable ones. But many OSS projects do not become sustainable, resulting in abandonment and even risks for the world's digital infrastructure. Prior work has looked at the reasons for this mainly from two very different perspectives. In software engineering, the focus has been on understanding success and sustainability from the socio-technical perspective: the OSS programmers' day-to-day activities and the artifacts they create. In institutional analysis, on the other hand, emphasis has been on institutional designs (e.g., policies, rules, and norms) that structure project governance. Even though each is necessary for a comprehensive understanding of OSS projects, the connection and interaction between the two approaches have been barely explored. In this paper, we make the first effort toward understanding OSS project sustainability using a dual-view analysis, by combining institutional analysis with socio-technical systems analysis. In particular, we (i) use linguistic approaches to extract institutional rules and norms from OSS contributors' communications to represent the evolution of their governance systems, and (ii) construct socio-technical networks based on longitudinal collaboration records to represent each project's organizational structure. We combined the two methods and applied them to a dataset of developer digital traces from 253 nascent OSS projects within the Apache Software Foundation (ASF) incubator. We find that the socio-technical and institutional features relate to each other, and provide complimentary views into the progress of the ASF's OSS projects. Refining these combined analyses can help provide a more precise understanding of the synchronization between the evolution of institutional governance and organizational structure.

Healthcare Information Technology’s Relativity Challenges: Distortions Created by Patients’ Physical Reality versus Clinicians’ Mental Models and Healthcare Electronic Records

This paper examines the inconsistencies or distortions among three medical realities: patients’ physical reality (as reflected in clinical observations, lab reports, and other “objective” measures); clinicians’ mental models of patients’ conditions; and how that information is represented in the patient’s electronic chart—the electronic health record (EHR). We created a typology based on the semiotic triangle of “symbol,” “thought or reference,” and “referent.”
 Differing perspectives (or realities) are illustrated with examples from our observations in hospitals and medical facilities, interviews with clinicians, IT personnel and IT vendors, computer logs, and error reports.
 Scenarios/models enumerate how the differing perspectives can misalign to produce distortions in comprehension and treatment. These are categorized according to an emergent typology derived from the cases themselves and refined based on insights gained from the literature on interactive sociotechnical systems analysis, decision support science, and human-computer interaction.
 The scenarios reflect the misalignment between patients’ physical realities, clinicians’ mental models, and EHRs, identifying five types of misrepresentation: IT data too narrowly focused; IT data too broadly focused; EHRs miss critical reality; data multiplicities—perhaps contradictory or confusing; distortions from data reflected back and forth across users, sensors, and others.
 Conclusion: With humans, there is a physical reality and actors’ mental models of that reality. In healthcare, there is another player: the EHR/healthcare IT, which implicitly and explicitly reflects many mental models, facets of reality, and measures thereof that vary in reliability and consistency. EHRs are both microcosms and shapers of medical care.

Technologically mediated practices in sustainability transitions: Environmental monitoring and the ocean data buoy

The discourses of sustainability are inextricably linked to the influence of technology in shaping the future. Information and Communication Technology (ICT) in particular plays a crucial role in our understanding of the environment and human impacts as well as our search for future solutions to mitigate climate change. However advances in technology need to be accompanied by social innovation in order to meaningfully address the Sustainable Development Goals (SDGs). Sustainability transitions research extends the well-established field of socio-technical systems analysis by paying closer attention to environmental, economical, social, political and technical factors that can stimulate change. Yet in order to offer guidance towards future socio-technical solutions, a deeper understanding of the relations between humanity and technology is necessary. To fulfill this requirement we explore the the concept of technological mediation and identify four ICT mediated practices in sustainability transitions: information gathering, communicating, decision-making, and self-reflection. These practices are described in the context of Sustainable Development Goal 14 Life Below Water, then elaborated through a specific example: the development and use of remote sensing ocean data buoys. In discussion we demonstrate the utility of technological mediation perspective to shed light on the interdependence of society, technology and the environment, and open critical discourses on sustainability transitions that can help shape equitable future alternatives.

A socio-technical systems analysis of the application of RFID-enabled technology to the transport of precious laboratory samples in a large acute teaching hospital

The scale and pace of improvement in patient safety in healthcare has been unacceptably slow. A paucity of research into the application of systems-thinking concepts and a failure to appreciate health systems complexity are cited as barriers to sustainable health systems improvement. This study reports on a socio-technical systems analysis, called the CUBE, of the characteristics of a large acute teaching hospital's system for the transport of precious specimens, a system enabled by radio-frequency identification tracking technology. The CUBE proved itself to be an effective analytic tool. The analysis provided a constructive framework to link diverse data and documentation; explicitly inviting consideration of the roles and understandings of different stakeholders; as well as broader cultural factors that could influence current or future activity. The analysis also supported recommendations to improve and extend operations. This study supports the argument for systems understanding and systems thinking being at the core of new approaches to patient safety.

Численный метод определения вероятностных характеристик индивидуальных многокомпонентных рисков

Introduction. As a rule, the quantitative assessment of the probabilistic characteristics of multicomponent risks involves the analysis of a large amount of statistical data, but quite often the available sample datasets are not representative or do not meet the requirements for the organization of systematic statistical accounting. Therefore, the scientific substantiation of the admissibility of using expert methods for quantitative assessments of the probabilistic parameters of rare events and phenomena is one of the urgent problems in the field of risk analysis and safety modeling of sociotechnical systems. The purpose of the study is to construct a numerical method for determining the probabilistic parameters of a stochastic model of multicomponent risks based on the procedure of paired comparisons by experts of the possibilities of various outcomes when a threat is realized and accepting a hypothesis about a functional relationship between the results of subjective assessment and objective measurement of probabilities. Methods. When constructing a numerical method, the procedure of pairwise comparisons is performed by experts for particular conditional probabilities of the occurrence of various consequences of the impact of hazardous factors on protected objects related to the given options for performing a set of protection functions. Determining a specific type of functional relationship between the results of a subjective assessment and an objective measurement of probabilities is possible on the basis of a retrospective forecast with the selection of a parameter that achieves the best correspondence between the simulated damage and real statistical data. Results and discussion. A numerical method is proposed for determining the probabilistic characteristics of multicomponent risks, based on the objectification of expert estimates of the probabilities of possible outcomes when exposed to hazardous factors on protected objects. The method of calculating subjective probabilities and their representation in a rank scale with further conversion into numerical values of the scale of ratios of the corresponding objective probabilities is substantiated. Findings. The application of the proposed numerical method for determining the probabilistic characteristics of multicomponent risks based on expert assessments is possible provided that a functional relationship is set between the results of a subjective assessment of the possibility of outcomes and an objective measurement of their probabilities in accordance with Stevens' psychophysical law. Keywords: expert assessments, multicomponent risks, psychophysical law, measurement theory.

Forgotten children: a socio-technical systems analysis of the 2004 and 2015 forced child labour reports from Indian cottonseed farms.

Using a systems analysis approach, the authors analyse forced child labour incidents in Indian cottonseed farms in the years 2003/04 and 2014/15, and explore the role played by human factors in contributing to the illegal use of child labour in the Indian agri-food sector. National policies on labour welfare and rights are reviewed through the case studies used as a lens to explore wider issues associated with forced child labour in supply chains. The study highlights the evolution of organised crime in India with regards to the reliance on forced child labour, using the four conceptual dimensions of modern slavery established by the UK Home Office in 2017. The study does identify limitations and flaws associated with designing policies based on a “work-as-imagined” philosophy and demonstrates how the use of maturity modelling can explore how exploitation, corruption and organised crime is framed and can become more formalised over time.

Using a sociotechnical systems analysis to evaluate an intervention to improve opioid prescribing in emergency medicine

The United States is facing an unprecedented epidemic of opioid addiction and death due to opioid overdose. In an effort to improve patient knowledge and safe use about opioids, an Electronic Medication Complete Communication (EMC2) opioid strategy was developed targeting opioid naïve patients in the Emergency Department (ED). We conducted pre and post sociotechnical systems analyses to evaluate the variance between the process before the intervention and whether or not the process changed as expected with the new intervention. Results were analyzed using thematic qualitative analysis. Sociotechnical systems modeling illustrates the complexity of designing interventions for emergency medicine that affect multiple patients, providers, work systems, technologies, and processes. The post work systems model illustrates that several elements in the external ED environment can affect the effectiveness of the intervention. Sociotechnical systems analysis is an effective tool to illustrate the opportunities for designing health system interventions and evaluating the fidelity of such interventions.

A Sociotechnical Systems Analysis of Knowledge Management for Cybersecurity

Knowledge management (KM) is a tool to tackle cybersecurity issues, provided it emphasizes on the interrelated social, organizational, and technological factors involved in cybersecurity. This paper proposes a sociotechnical systems analysis framework of KM systems for cybersecurity. Specifically, it applies a sociotechnical systems approach to investigation of constructs of KM systems for cybersecurity and identifies five major constructs of KM systems for cybersecurity: roles of KM in cybersecurity, organizational framework of KM for cybersecurity, cybersecurity analytics process, tools of KM for cybersecurity, and system architecture of KM for cybersecurity. The five constructs in the proposed sociotechnical systems analysis framework are analyzed. The paper makes contribution to the growing information systems literature by presenting a special case of sociotechnical systems analysis. The sociotechnical systems analysis framework provides guidelines for the development of KM systems for cybersecurity in organizations.