Socio-technical Research Research Articles

Laying the ground for future cross-organizational process mining research and application: a literature review

Purpose Process mining (PM) has emerged as a leading technology for gaining data-based insights into organizations’ business processes. As processes increasingly cross-organizational boundaries, firms need to conduct PM jointly with multiple organizations to optimize their operations. However, current knowledge on cross-organizational process mining (coPM) is widely dispersed. Therefore, we synthesize current knowledge on coPM, identify challenges and enablers of coPM, and build a socio-technical framework and agenda for future research.Design/methodology/approach We conducted a literature review of 66 articles and summarized the findings according to the framework for Information Technology (IT)-enabled inter-organizational coordination (IOC) and the refined PM framework. The former states that within inter-organizational relationships, uncertainty sources determine information processing needs and coordination mechanisms determine information processing capabilities, while the fit between needs and capabilities determines the relationships’ performance. The latter distinguishes three categories of PM activities: cartography, auditing and navigation.Findings Past literature focused on coPM techniques, for example, algorithms for ensuring privacy and PM for cartography. Future research should focus on socio-technical aspects and follow four steps: First, determine uncertainty sources within coPM. Second, design, develop and evaluate coordination mechanisms. Third, investigate how the mechanisms assist with handling uncertainty. Fourth, analyze the impact on coPM performance. In addition, we present 18 challenges (e.g. integrating distributed data) and 9 enablers (e.g. aligning different strategies) for coPM application.Originality/valueThis is the first article to systematically investigate the status quo of coPM research and lay out a socio-technical research agenda building upon the well-established framework for IT-enabled IOC.

Researching With Virtual Reality: Exploring the Methodological Affordances of VR for Sociotechnical Research and Implications for Technical and Professional Communication

Researching With Virtual Reality: Exploring the Methodological Affordances of VR for Sociotechnical Research and Implications for Technical and Professional Communication

Implementing artificial intelligence across task types: constraints of automation and affordances of augmentation

PurposeThis study aims to uncover the constraints of automation and the affordances of augmentation related to implementing artificial intelligence (AI)-powered systems across different task types: mechanical, thinking and feeling.Design/methodology/approachQualitative study involving 45 interviews with various stakeholders in artistic gymnastics, for which AI-powered systems for the judging process are currently developed and tested. Stakeholders include judges, gymnasts, coaches and a technology vendor.FindingsWe identify perceived constraints of automation, such as too much mechanization, preciseness and inability of the system to evaluate artistry or to provide human interaction. Moreover, we find that the complexity and impreciseness of the rules prevent automation. In addition, we identify affordances of augmentation such as speedier, fault-less, more accurate and objective evaluation. Moreover, augmentation affords to provide an explanation, which in turn may decrease the number of decision disputes.Research limitations/implicationsWhile the unique context of our study is revealing, the generalizability of our specific findings still needs to be established. However, the approach of considering task types is readily applicable in other contexts.Practical implicationsOur research provides useful insights for organizations that consider implementing AI for evaluation in terms of possible constraints, risks and implications of automation for the organizational practices and human agents while suggesting augmented AI-human work as a more beneficial approach in the long term.Originality/valueOur granular approach provides a novel point of view on AI implementation, as our findings challenge the notion of full automation of mechanical and partial automation of thinking tasks. Therefore, we put forward augmentation as the most viable AI implementation approach. In addition, we developed a rich understanding of the perception of various stakeholders with a similar institutional background, which responds to recent calls in socio-technical research.

City Information Models (CIMs) as precursors for Urban Digital Twins (UDTs): A case study of Lancaster

City Information Models (CIMs) present several research challenges and are arguably pre-cursors for a roadmap to the transition to Urban or City Digital Twins (UDTs/CDTs) and broader smart city drives. In a period of digital transformation in urban planning, CIMs are primarily designed to intersect and merge urban GIS/BIM in what is termed GeoBIM. CIMs are often cloud-based geospatial services and data repositories with one-way data connections, which differ from integrated and high-fidelity cyber-physical complex systems for digital twins (DTs). However, there is a lack of precision in terms of defining CIMs and UDTs, and this paper examines four broad sociotechnical research challenges regarding the progress of CIMs toward full UDTs/CDTs, including (1) technical training for adoption, (2) acquisition strategies for aerial data and remote sensing, (3) data licensing types and system management, and (4) stakeholder engagement with CIM platforms. These four research challenges and digital transformation are discussed by using back-casting futuring methods, establishing a framework for CIMs through co-designed workshops, and explored in the Lancaster City Information Model (LCIM) prototype. The LCIM, as a resulting case study, was developed for architects, planners, and stakeholders to engage with 3D urban models and urban analytics (view sheds, masterplan scenarios, and solar potentials of buildings) from 2019 to 2021 to address digital inequality in planning and data fragmentation. The framework and prototype results resulted in the most extensive 3D open urban dataset published in the UK, consisting of a baseline of 1″+/− buildings and infrastructure and 7.5 cm aerial imagery and a framework for developing transitions from CIMs to UDTs. The delivery of this case and the resulting published dataset highlights the essential research needed regarding definitions and precision around terminology and systems between CIMs and UDTs and four applied challenges in digital transformation and future socio-technical relationships.

Addressing Fragmentation of Health Services through Data-Driven Knowledge Co-Production within a Boundary Organization

Behavioral healthcare services involve multiple disconnected sectors and providers serving the same populations. Efforts to identify and address service delivery problems are hampered by fragmentation of datasets. We conducted an engaged research project in which we formed a boundary organization and developed a knowledge co-production process centered on collaborative data sharing and visualization. Multisector participants in [location] worked to access and share data and to collectively interpret the resulting integrated data through visualizations using four knowledge co-production practices: collective interaction with data, perspective taking, reflection & debrief, and iteration of visualizations. The knowledge co-production process was evaluated using qualitative methods. This research extends sociotechnical research on knowledge co-production by proffering collaborative data sharing and visualization as a knowledge co-production process that can extend across disconnected and disparate social groups and contributes to community informatics by highlighting the role boundary organizations can play in facilitating data sharing and data-driven problem solving between fragmented sectors.

Increasing System Reliability by Applying Conceptual Modeling and Data Analysis—A Case Study: An Automated Parking System

In complex sociotechnical research, companies aim to utilize data and digitalization to increase a system’s reliability and to minimize a system’s failures. This study exemplifies the use of conceptual modeling and data analysis to increase a system’s reliability by studying a case study for a medium-sized company. The company delivers an Automated Parking System (APS). We identified, collected, and analyzed internal and external data within this context. Internal data consist of failure data from maintenance, whereas external data include environmental data, mainly weather data. Data analyses transformed the collected data into information, where conceptual modeling facilitates the understanding of information by transforming it further into knowledge. We find that the combination of conceptual modeling and data analysis aids in exploring and understanding a system’s reliability. This understanding enables a company to enhance its product-development process. Conceptual modeling and data analyses guide and support each other in an iterative and recursive manner, and they both complement each other. Conceptual modeling also facilitates communication and understanding.

Rise of the Metaverse’s Immersive Virtual Reality Malware and the Man-in-the-Room Attack & Defenses

The allure of the metaverse along with Virtual Reality (VR) technologies and speed at which they are deployed may shift focus away from security and privacy fundamentals. In this work we employ classic exploitation techniques against cutting edge devices to obtain equally novel results. The unique features of the Virtual Reality landscape set the stage for our primary account of a new attack, the Man-in-the-Room (MitR). This attack, realized from a vulnerable social networking application led to both worming and botnet capabilities being adapted for VR with potential critical impacts affecting millions of users. Our work improves the state-of-the-art in Virtual Reality (VR) security and socio-technical research in VR. It shares several analytical and attacking tools, example exploits, evaluation dataset, and vulnerability signatures with the scientific and professional communities to ensure secure VR software development. The presented results demonstrate the detection and prevention of VR vulnerabilities, and raise questions in the law and policy domains pertaining to VR security and privacy.

Research methodology for industry‐academic collaboration – a case study

AbstractWhen industry and academia collaborate within an applied sociotechnical research project, it generates a complex context due to different means, goals, languages, and emergent practices. The industry is interested in developing projects, maximizing profit, and satisfying its clients and customers. Academia is oriented towards performing research to understand, explore, optimize, and verify meaningful statements. Different goals, timelines, ways of working, languages, and resources create too many emergent practices and friction in the research execution. In this paper, we perform a retrospective analysis on a research project conducted over a year that focused on the current and future state in nine companies and evaluated its use of research methodologies. A finding is the need to have well‐defined industry cases, and we suggest criteria for achieving this. Additionally, we see emergent practices and dynamic environments influencing the research process in industry and academic research context.

An overview of sociotechnical research on maritime energy efficiency

A qualitative synthesis is presented covering the literature on operational energy efficiency in shipping based on research from a sociotechnical perspective. Three themes were identified, using thematic analysis, as particularly significant for the management of energy: (i) cooperation, communication, and knowledge sharing between stakeholders; (ii) organizational information processing (cognitive bottlenecks and sense making practices); and (iii) professional education and training. We conclude that while previous research has uncovered many of the barriers to increasing energy efficiency, few studies have examined the interdependence of practices and technologies underlying organizational cognitive systems and change. The identified research gap calls for more longitudinal process-based case studies investigating the design, implementation, and use of information technologies supporting organizational planning and decision-making required for improving energy efficiency.

A paradigm shift to ethical decision-making—incorporating systemic epistemology into complex socio-technical decision support systems research

ABSTRACT Current decision support systems (DSS) research is overwhelmingly positivist and limits the adequate representation of relevant stakeholders. This crisis of relevance precludes the systemic inclusion of social and ethical issues in complex socio-technical DSS designs. For their unstable boundary conditions, such systems also require explicit coverage of their dynamics. Lending a novel perspective to DSS research, this paper proposes a framework with the new decision-making paradigm and the systemic inquiry of boundary critique to explore stakeholder perspectives for more ethically-aware DSS development. Using qualitative research, the developed framework is applied to unleash ethical issues for a dynamic and complex socio-technical university timetabling scenario implemented as a web-based group decision support system. Multiple stakeholder perspectives are recognised and analysed for boundary judgements, while a dynamic stakeholder network considers boundary liquidity and emergence. This work aims to couple systemic epistemology with the socio-technical lens to encourage the inclusion of ethical dimensions in dynamic and complex DSS designs.

Institutionalizing Outer Space: A sociotechnical explication of the Comsat-Intelsat actor-network

Humans once again stand poised to institutionally transcend possible harmful economic and social stagnation arising from earthbound limitations by becoming a space faring species. The resurgent public interest in the economic and cultural potential of outer space reflects the convergence of actants such as advancements in technology, deepening public interest in expanding human presence, and concern about the earth’s sustainability. Yet there exists limited institutional research about this important phenomenon. The aim of our sociotechnical research is to explicate critical institutionalizing effects of the historic Comsat actor-network since it was the first-ever attempt by humans to commercialize outer space. We use actor network theory (ANT) coupled with discourse analysis as our method. Our findings suggest that the Comsat-Intelsat network is a positive deviant case in that it is a unique public-private network which successfully initiates an institutional pathway to outer space. Our work provides a robust typology of institutions, syndicates, and actors involved in space commercialization. We highlight several Insights about various translation phases, actor relations, and assembling challenges. Moreover, we delineate and describe a framework of fourteen controversies then construct an anatomy of institutional work with five discourse topics and embedded narrative themes: Commercialization, stabilization, prognostication, systematization, and universalization. We theorize that successful space commercialization initiatives require all five discourses to be robustly and concurrently activated across multi-constituent heterogenous actor-networks.

Anticipation Next: System-Sensitive Technology Development and Integration in Work Contexts

When discussing future concerns within socio-technical systems in work contexts, we often find descriptions of missed technology development and integration. The experience of technology that fails whilst being integrated is often rooted in dysfunctional epistemological approaches within the research and development process. Thus, ultimately leading to sustainable technology-distrust in work contexts. This is true for organizations that integrate new technologies and for organizations that invent them. Organizations in which we find failed technology development and integrations are, in their very nature, social systems. Nowadays, those complex social systems act within an even more complex environment. This urges the development of new anticipation methods for technology development and integration. Gathering of and dealing with complex information in the described context is what we call Anticipation Next. This explorative work uses existing literature from the adjoining research fields of system theory, organizational theory, and socio-technical research to combine various concepts. We deliberately aim at a networked way of thinking in scientific contexts and thus combine multidisciplinary subject areas in one paper to present an innovative way to deal with multi-faceted problems in a human-centred way. We end with suggesting a conceptual framework that should be used in the very early stages of technology development and integration in work contexts.

Deep Learning for Enterprise Systems Implementation Lifecycle Challenges: Research Directions

Transforming the state-of-the-art definition and anatomy of enterprise systems (ESs) seems to some academics and practitioners as an unavoidable destiny. Value depletion lead by early retirement and/or replacement of ESs solutions has been a constant throughout the past decade. That did drive an enormous amount of research that works on addressing the problems leading to the resource drain. The resource waste had persisted throughout the ESs implementation lifecycle phases and dimensions especially post-live phases; leading to depleting the value of the social and technical dimensions of the lifecycle. Parallel to this research stream, the momentum gained by deep learning (DL) algorithms and platforms has been exponentially growing to fuel the advancements toward artificial intelligence and automated augmentation. Correspondingly, this paper is set out to present five key research directions through which DL would take part as a contributor towards the transformation of the ESs state-of-the-art. The paper reviews the ESs implementation lifecycle challenges and the intersection with DL research conducted on ESs by analyzing and synthesizing key basket journals (list of the Association of Information Systems). The paper also presents results from several experiments showcasing the effectiveness of DL in adding a level of augmentation to ESs by analyzing a large set of data extracted from the Atlassian Jira Software Issue Tracking System across different ecosystems. The paper then concludes by presenting the research directions and discussing socio-technical research courses that work on key frontiers identified within this scholarly work.

Medical History Taking Using Electronic Medical Records: A Systematic Review

Background: The relationship between digital tools and medical history taking (classically referred to as anamnesis) in clinical settings is problematic. We explored the medical history taking context, how data is managed by physicians and patients and which tools are used, particularly electronic health record, to gather, organize and record patient’s medical history and related health data. Materials and methods: Systematic review of the literature following PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analysis) guidelines, using published studies in English-language available from PubMed and Cochrane databases, using a combination of Medical Subject Headings and keywords. Our search yielded 162 citations of which 18 corresponded to our criteria and were included, regardless of study design, sample size or measurement type as a variety of perspectives and methodologies was deemed useful for an exploratory review and under a socio-technical research epistemology. The small number of publications related to the topic conditioned our analysis. Discussion: This review shows the paucity of relevant studies in the area of interest. Even thought it was possible to evaluate context changes in history taking that relate to EHR implementation and usage. Also, multiple challenges, benefits, risks and workflow adaptations have impacts on medical history taking. A potentially useful workflow adaptation is the access to the EHR previously or during the patient encounter with him or her. Conclusion:With the ever-increasing adoption of EHRs and its varying influence in clinical practice, physician’s adaptability was strained. Multiple workflow challenges and necessary changes regarding EHR use have been identified. Improving anamnesis practice is possible through better documentation, EHR templates and tools. Yet a new aspect of anamnesis – Digital anamnesis – benefits from better conceptualization and integration with classic anamnesis still taught in traditional medical schools. This study points to implications for medical schools and medical education in general. Highlights: Electronic Health Records implementation transformed clinical practice and redesigned workflows, improving patient safety and care within a multidisciplinary care setting. Some concerns surfaced concerning information privacy, quality of documentation and doctor-patient relationship, however many studies developed implemented and evaluated tools, templates and mnemonics to mitigate such distresses. “Digital anamnesis” is a proposed concept and refers to the process of medical history and information gathering using digital tools. This will be evermore important in the future, since technological development increasingly adds relevant features and functions to Electronic Health Record.

Designing Representative Model Worlds to Study Socio-Technical Phenomena: A Case Study of Communication Patterns in Engineering Systems Design

Abstract The engineering of complex systems, such as aircraft and spacecraft, involves large number of individuals within multiple organizations spanning multiple years. Since it is challenging to perform empirical studies directly on real organizations at scale, some researchers in systems engineering and design have begun relying on abstracted model worlds that aim to be representative of the reference socio-technical system, but only preserve some aspects of it. However, there is a lack of corresponding knowledge on how to design representative model worlds for socio-technical research. Our objective is to create such knowledge through a reflective case study of the development of a model world. This “inner” study examines how two factors influence interdisciplinary communication during a concurrent design process. The reference real world system is a mission design laboratory (MDL) at NASA, and the model world is a simplified engine design problem in an undergraduate classroom environment. Our analysis focuses on the thought process followed, the key model world design decisions made, and a critical assessment of the extent to which communication phenomena in the model world (engine experiment) are representative of the real world (NASA’s MDL). We find that the engine experiment preserves some but not all of the communication patterns of interest, and we present case-specific lessons learned for achieving and increasing representativeness in this type of study. More generally, we find that representativeness depends not on matching subjects, tasks, and context separately, but rather on the behavior that emerges from the interplay of these three dimensions.

The who, what, how of software engineering research: a socio-technical framework

Software engineering is a socio-technical endeavor, and while many of our contributions focus on technical aspects, human stakeholders such as software developers are directly affected by and can benefit from our research and tool innovations. In this paper, we question how much of our research addresses human and social issues, and explore how much we study human and social aspects in our research designs. To answer these questions, we developed a socio-technical research framework to capture the main beneficiary of a research study (the who), the main type of research contribution produced (the what), and the research strategies used in the study (how we methodologically approach delivering relevant results given the who and what of our studies). We used this Who-What-How framework to analyze 151 papers from two well-cited publishing venues---the main technical track at the International Conference on Software Engineering, and the Empirical Software Engineering Journal by Springer---to assess how much this published research explicitly considers human aspects. We find that although a majority of these papers claim the contained research should benefit human stakeholders, most focus on technical contributions without engaging humans in their studies. Although our analysis is scoped to two venues, our results suggest a need for more diversification and triangulation of research strategies. In particular, there is a need for strategies that aim at a deeper understanding of human and social aspects of software development practice to balance the design and evaluation of technical innovations. We recommend that the framework should be used in the design of future studies in order to nudge software engineering research towards explicitly including human and social concerns in their designs, and to improve the relevance of our research for human stakeholders.

A Socio-Technical Perspective on the Internet of Things: The Case of Advanced Services

The purpose of the study is to investigate how the Internet of Things (IoT) contributes to the manufacturers’ advanced service development and delivery. In order to better understand the creation of these IoT contributions, the study adopts a socio-technical research perspective which expands the scope of the investigation and integrates the technological, information and social factors that enable these IoT contributions. A multiple-case research method was employed to investigate the IoT contribution scenarios of 15 manufacturers offering advanced services, and to examine their dependence on other non-IoT factors using inductive and deductive thematic analysis. The analysis identified five advanced service value propositions which are enabled by ten ‘IoT-enabled IS artefacts’ which specify the distinct interactions between the technological, information and social subsystems that support the manufacturers’ advanced service value propositions. This study advances servitization research by showing that the IoT technology on its own is not sufficient for the creation of the IoT contributions. It shows instead the need for close interactions with a diverse range of other factors which are often not considered when developing the IoT strategy. The study further introduces the IS artefact notion as a unit of analysis that is an alternative to the commonly adopted techno-centric perspective used to conceptualise the IoT contributions. The study and its findings add to the development of a socio-technical perspective on the IoT in advanced services and generates a number of theoretical and practical implications.

Metahuman systems = humans + machines that learn

Metahuman systems are new, emergent, sociotechnical systems where machines that learn join human learning and create original systemic capabilities. Metahuman systems will change many facets of the way we think about organizations and work. They will push information systems research in new directions that may involve a revision of the field’s research goals, methods and theorizing. Information systems researchers can look beyond the capabilities and constraints of human learning toward hybrid human/machine learning systems that exhibit major differences in scale, scope and speed. We review how these changes influence organization design and goals. We identify four organizational level generic functions critical to organize metahuman systems properly: delegating, monitoring, cultivating, and reflecting. We show how each function raises new research questions for the field. We conclude by noting that improved understanding of metahuman systems will primarily come from learning-by-doing as information systems scholars try out new forms of hybrid learning in multiple settings to generate novel, generalizable, impactful designs. Such trials will result in improved understanding of metahuman systems. This need for large-scale experimentation will push many scholars out from their comfort zone, because it calls for the revitalization of action research programs that informed the first wave of socio-technical research at the dawn of automating work systems.

Generative Critique in Interdisciplinary Collaborations: From Critique in and of the Neurosciences to Socio-Technical Integration Research as a Practice of Critique in R(R)I

Discourses on Responsible Innovation and Responsible Research and Innovation, in short R(R)I, have revolved around but not elaborated on the notion of critique. In this article, generative critique is introduced to R(R)I as a practice that sits in-between adversarial armchair critique and co-opted, uncritical service. How to position oneself and be positioned on this spectrum has puzzled humanities scholars and social scientists who engage in interdisciplinary collaborations with scientists, engineers, and other professionals. Recently, generative critique has been presented as a solution to the puzzle in interdisciplinary collaborations on neuroscientific experiments. Generative critique seeks to create connections across disciplines that help remake seemingly stable objects in moments when taken-for-granted ways of seeing and approaching objects are unsettled. In order to translate generative critique from the neurosciences to R(R)I, socio-technical integration research (STIR) is proposed as a practice of generative critique in interdisciplinary R(R)I collaborations. These collaborations aim to account for societal aspects in research and technology development. For this purpose, a variety of approaches have been developed, including STIR and video-reflexive ethnography (VRE). STIR and VRE resemble each other but diverge on affective, collaborative, and temporal dimensions. Their juxtaposition serves to develop suggestions for how STIR could be modified on these dimensions to better enact generative critique in interdisciplinary R(R)I collaborations. In this way, the article contributes to ongoing discussions in R(R)I and in the engaged programme in science and technology studies more broadly on the dynamics of positioning in collaborative work.

Raising Awareness of Researchers-in-the-Making Toward Responsible Research and Innovation

Across the globe, research, development, and innovation (RDI) processes are operating at increasingly accelerated paces, promising rapid development and higher standards of living, but also increasing the likelihood of unintended, socially undesirable effects that inevitably attend progress. The notion of responsible research and innovation (RRI) has emerged in response to this dilemma, and the integration of RRI into daily RDI practices itself represents a considerable challenge. Integrating RRI concepts and practices at an early or even pre-career stage, before researchers fully develop their daily routines, could strengthen the assimilation of RRI into RDI more generally. Thus, in line with the emphasis of RRI on science education, how to integrate RRI aspects in the thinking of researchers-in-the-making before they start their active research carrier is an important but under-investigated question. In addition, the special features of Generation Z currently being in higher education suggest the use nontraditional tools in science education.Accordingly, this exploratory study asks how the RRI-awareness of researchers-in-the-making can be raised. We adapt the Socio-Technical Integration Research (STIR) method, which facilitates reflection on societal aspects during scientific research practices and decisions, to the context of science education. We test the introduction of STIR among researchers-in-the-making studying natural sciences at the University of Szeged (Hungary). Our findings suggest potential steps for science education on RRI with attention to the special needs Generation Z and facilitating their RRI awareness for their active researcher career.