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Workplace friendships
(2023)
Workplace friendships, i.e., when work colleagues are also friends, are a widespread phenomenon in organizations which has attracted increasing research interest in recent decades. Numerous studies have investigated consequences of workplace friendships and found positive outcomes, such as increased employee job satisfaction or organizational performance, as well as negative outcomes, such as decreased knowledge-sharing between different friendship cliques. Other studies have examined what shapes workplace friendships, focusing on determinants such as personality or the spatial composition of organizations. Finally, an increasing number of studies focus on multiplex workplace friendships, where employees who are friends are also linked by a specific work-focused relationship. In this chapter, we first take stock of the literature on workplace friendships by providing an overview of their antecedents and consequences at the individual, the group, and the organizational level, and review the smaller body of research on multiplex workplace friendships. Second, we critically discuss practical implications of workplace friendships, focusing on their relevance to three current challenges for employees and organizations: the increase in virtual work, social inequalities in organizations, and the increased overlap of professional and private life. Finally, we provide recommendations for organizations on how to address these challenges and effectively manage workplace friendships.
Disinformation campaigns spread rapidly through social media and can cause serious harm, especially in crisis situations, ranging from confusion about how to act to a loss of trust in government institutions. Therefore, the prevention of digital disinformation campaigns represents an important research topic. However, previous research in the field of information systems focused on the technical possibilities to detect and combat disinformation, while ethical and legal perspectives have been neglected so far. In this article, we synthesize previous information systems literature on disinformation prevention measures and discuss these measures from an ethical and legal perspective. We conclude by proposing questions for future research on the prevention of disinformation campaigns from an IS, ethical, and legal perspective. In doing so, we contribute to a balanced discussion on the prevention of digital disinformation campaigns that equally considers technical, ethical, and legal issues, and encourage increased interdisciplinary collaboration in future research.
Between reality & fantasy
(2023)
Synthetische Medien ermöglichen die zunehmend automatisierte Erstellung virtueller Influencer, von denen bereits einige Millionen Follower in sozialen Medien gewonnen haben. Unter der Leitung von Professor Stefan Stieglitz und Sünje Clausen (Universität Potsdam) und in Kooperation mit Sanofi hat ein Forschungsprojekt untersucht, wie computergenerierten Charaktere für die Influencer-Kommunikation im Unternehmensumfeld genutzt werden können. Nähere Informationen zu den Forschungsergebnissen können in der Communication Insights nachgelesen werden: eine kurze Einführung in die Influencer-Kommunikation, potenziellen Vorteile als auch Herausforderungen von virtuellen Influencern, Tipps für den Prozess der Gestaltung und Nutzung eines virtuellen Influencers.
Gender at the crossroads
(2023)
Since the early 2000s, the United Nations (UN) global counterterrorism architecture has seen significant changes towards increased multilateralism, a focus on prevention, and inter-institutional coordination across the UN’s three pillars of work. Throughout this reform process, gender aspects have increasingly become presented as a “cross-cutting” theme. In this article, I investigate the role of gender in the UN’s counterterrorism reform process at the humanitarian-development-peace nexus, or “triple nexus”, from a feminist institutionalist perspective. I conduct a feminist discourse analysis of the counterterrorism discourses of three UN entities, which represent the different UN pillars of peace and security (DPO), development (UNDP), and humanitarianism and human rights (OHCHR). The article examines the role of gender in the inter-institutional reform process by focusing on the changes, overlaps and differences in the discursive production of gender in the entities’ counterterrorism agendas over time and in two recent UN counterterrorism conferences. I find that gendered dynamics of nested newness and institutional layering have played an essential role both as a justification for the involvement of individual entities in counterterrorism and as a vehicle for inter-institutional cooperation and struggle for discursive power.
This book brings together a variety of innovative perspectives on the inclusion of gender in the governance of (counter-)terrorism and violent extremism.
Several global governance initiatives launched in recent years have explicitly sought to integrate concern for gender equality and gendered harms into efforts to counter terrorism and violent extremism (CT/CVE). As a result, commitments to gender-sensitivity and gender equality in international and regional CT/CVE initiatives, in national action plans and at the level of civil society programming, ´have become a common aspect of the multilevel governance of terrorism and violent extremism. In light of these developments, there is a need for more systematic analysis of how concerns about gender are being incorporated in the governance of (counter-)terrorism and violent extremism and how it has affected (gendered) practices and power relations in counterterrorism policy-making and implementation.
Ranging from the processes of global and regional integration of gender into the governance of terrorism, via the impact of the shift on government responses to the return of foreign fighters, to state and civil society-led CVE programming and academic discussions, the essays engage with the origins and dynamics behind recent shifts which bring gender to the forefront of the governance of terrorism. This book will be of great value to researchers and scholars interested in gender, governance and terrorism.
The chapters in this book were originally published in Critical Studies on Terrorism.
Atwood (2022) analyzes the effects of the 1963 U.S. measles vaccination on longrun labor market outcomes, using a generalized difference-in-differences approach. We reproduce the results of this paper and perform a battery of robustness checks. Overall, we confirm that the measles vaccination had positive labor market effects. While the negative effect on the likelihood of living in poverty and the positive effect on the probability of being employed are very robust across the different specifications, the headline estimate-the effect on earnings-is more sensitive to the exclusion of certain regions and survey years.
The EU and its member countries have been laggards in using forest carbon to reduce EU emissions. The European Green Deal aims to change this. As part of its long-term emissions reductions, the EU aims to offset this by creating land-based carbon sinks, especially forest carbon sinks as well as carbon capture and storage. This chapter focuses on the role of forest carbon as part of the EU's climate policies towards achieving net-zero greenhouse gas emissions by 2050. It furthermore examines the European Commission's proposed forest strategy and its proposal for a revised LULUCF Regulation. The chapter shows that the logic of appropriateness dominates the European Commission's forest policies. Finally, the chapter makes policy recommendations on how the EU could credibly use long-term carbon sinks to achieve climate neutrality.
Long-term environmental policy remains a vexing puzzle of environmental policy. Following its definition, the author reviews the methods suitable for the study of long-term environmental policy and develops a typology of policy instruments to cope with these challenges. The concluding section offers five central research challenges to advance the study of long-term environmental policy.
The impact of civilian harm on strategic outcomes in war has been the subject of persistent debate. However, the literature has primarily focused on civilian casualties, thereby overlooking the targeting of civilian infrastructure, which is a recurrent phenomenon during war. This study fills this gap by examining the targeting of healthcare, one of the most indispensable infrastructures during war and peace time. We contend that attacks on medical facilities are distinct from direct violence against civilians. Because they are typically unrelated to military dynamics, the targeting of hospitals is a highly visible form and powerful signal of civilian victimization. To assess its effects, we analyze newly collected data on such attacks by pro-government forces and event data on combat activities in Northwest Syria (2017-2020). Applying a new approach for panel data analysis that combines matching methods with a difference-in-differences estimation, we examine the causal effect of counterinsurgent bombings on subsequent violent events. Distinguishing between regime-initiated and insurgent-initiated combat activities and their associated fatalities, we find that the targeting of hospitals increases insurgent violence. We supplement the quantitative analysis with unique qualitative evidence derived from interviews, which demonstrates that hospital bombings induce rebels to resist more fiercely through two mechanisms: intrinsic motivations and civilian pressure. The results have important implications for the effects of state-led violence and the strength of legal norms that protect noncombatants.
We conduct a laboratory experiment to study how locus of control operates through people's preferences and beliefs to influence their decisions. Using the principal-agent setting of the delegation game, we test four key channels that conceptually link locus of control to decision-making: (i) preference for agency; (ii) optimism and (iii) confidence regarding the return to effort; and (iv) illusion of control. Knowing the return and cost of stated effort, principals either retain or delegate the right to make an investment decision that generates payoffs for themselves and their agents. Extending the game to the context in which the return to stated effort is unknown allows us to explicitly study the relationship between locus of control and beliefs about the return to effort. We find that internal locus of control is linked to the preference for agency, an effect that is driven by women. We find no evidence that locus of control influences optimism and confidence about the return to stated effort, or that it operates through an illusion of control.
An increasing number of clinicians (i.e., nurses and physicians) suffer from mental health-related issues like depression and burnout. These, in turn, stress communication, collaboration, and decision- making—areas in which Conversational Agents (CAs) have shown to be useful. Thus, in this work, we followed a mixed-method approach and systematically analysed the literature on factors affecting the well-being of clinicians and CAs’ potential to improve said well-being by relieving support in communication, collaboration, and decision-making in hospitals. In this respect, we are guided by Brigham et al. (2018)’s model of factors influencing well-being. Based on an initial number of 840 articles, we further analysed 52 papers in more detail and identified the influences of CAs’ fields of application on external and individual factors affecting clinicians’ well-being. As our second method, we will conduct interviews with clinicians and experts on CAs to verify and extend these influencing factors.
Digital Platforms (DPs) has established themself in recent years as a central concept of the Information Technology Science. Due to the great diversity of digital platform concepts, clear definitions are still required. Furthermore, DPs are subject to dynamic changes from internal and external factors, which pose challenges for digital platform operators, developers and customers. Which current digital platform research directions should be taken to address these challenges remains open so far. The following paper aims to contribute to this by outlining a systematic literature review (SLR) on digital platform concepts in the context of the Industrial Internet of Things (IIoT) for manufacturing companies and provides a basis for (1) a selection of definitions of current digital platform and ecosystem concepts and (2) a selection of current digital platform research directions. These directions are diverted into (a) occurrence of digital platforms, (b) emergence of digital platforms, (c) evaluation of digital platforms, (d) development of digital platforms, and (e) selection of digital platforms.
Invention
(2023)
This entry addresses invention from five different perspectives: (i) definition of the term, (ii) mechanisms underlying invention processes, (iii) (pre-)history of human inventions, (iv) intellectual property protection vs open innovation, and (v) case studies of great inventors. Regarding the definition, an invention is the outcome of a creative process taking place within a technological milieu, which is recognized as successful in terms of its effectiveness as an original technology. In the process of invention, a technological possibility becomes realized. Inventions are distinct from either discovery or innovation. In human creative processes, seven mechanisms of invention can be observed, yielding characteristic outcomes: (1) basic inventions, (2) invention branches, (3) invention combinations, (4) invention toolkits, (5) invention exaptations, (6) invention values, and (7) game-changing inventions. The development of humanity has been strongly shaped by inventions ever since early stone tools and the conception of agriculture. An “explosion of creativity” has been associated with Homo sapiens, and inventions in all fields of human endeavor have followed suit, engendering an exponential growth of cumulative culture. This culture development emerges essentially through a reuse of previous inventions, their revision, amendment and rededication. In sociocultural terms, humans have increasingly regulated processes of invention and invention-reuse through concepts such as intellectual property, patents, open innovation and licensing methods. Finally, three case studies of great inventors are considered: Edison, Marconi, and Montessori, next to a discussion of human invention processes as collaborative endeavors.
Labor unions’ greatest potential for political influence likely arises from their direct connection to millions of individuals at the workplace. There, they may change the ideological positions of both unionizing workers and their non-unionizing management. In this paper, we analyze the workplace-level impact of unionization on workers’ and managers’ political campaign contributions over the 1980-2016 period in the United States. To do so, we link establishment-level union election data with transaction-level campaign contributions to federal and local candidates. In a difference-in-differences design that we validate with regression discontinuity tests and a novel instrumental variables approach, we find that unionization leads to a leftward shift of campaign contributions. Unionization increases the support for Democrats relative to Republicans not only among workers but also among managers, which speaks against an increase in political cleavages between the two groups. We provide evidence that our results are not driven by compositional changes of the workforce and are weaker in states with Right-to-Work laws where unions can invest fewer resources in political activities.
Although the literature on the determinants of training has considered individual and firm-related characteristics, it has generally neglected regional factors. This is surprising, given the fact that labour markets differ by regions. Regional factors are often ignored because (both in Germany and abroad) many data sets covering training information do not include detailed geographical identifiers that would allow a merging of information on the regional level. The regional identifiers of the National Educational Panel Study (Starting Cohort 6) offer opportunities to advance research on several regional factors. This article summarizes the results from two studies that exploit these unique opportunities to investigate the relationship between training participation and (a) the local level of firm competition for workers within specific sectors of the economy and (b) the regional supply of training measured as the number of firms offering courses or seminars for potential training participants.
The management of knowledge in organizations considers both established long-term
processes and cooperation in agile project teams. Since knowledge can be both tacit and explicit, its transfer from the individual to the organizational knowledge base poses a challenge in organizations. This challenge increases when the fluctuation of knowledge carriers is exceptionally high. Especially in large projects in which external consultants are involved, there is a risk that critical, company-relevant knowledge generated in the project will leave the company with the external knowledge carrier and thus be lost. In this paper, we show the advantages of an early warning system for knowledge management to avoid this loss. In particular, the potential of visual analytics in the context of knowledge management systems is presented and discussed. We present a project for the development of a business-critical software system and discuss the first implementations and results.
This study utilizes cross-country survey data to analyze differences in attitudes toward cryptocurrency as an alternative to traditional money issued by a central bank. Particularly, we investigate women’s general attitude toward cryptocurrency systems. Results suggest that women invest less into cryptocurrency, show less interest in the future cryptocurrency investment, and see less economic potential in these systems than men do. Further evidence shows that these attitudes are directly connected with lower literacy in cryptocurrency systems. These findings support theory on gender differences in investment behavior. We contribute to the existing literature by conducting a cross-country survey on cryptocurrency attitudes in Europe and Asia, and hence show that this gender effect is robust across these cultures.
Artificial intelligence (AI)-based technologies can increasingly perform knowledge work tasks, such as medical diagnosis. Thereby, it is expected that humans will not be replaced by AI but work closely with AI-based technology (“augmentation”). Augmentation has ethical implications for humans (e.g., impact on autonomy, opportunities to flourish through work), thus, developers and managers of AI-based technology have a responsibility to anticipate and mitigate risks to human workers. However, doing so can be difficult as AI encompasses a wide range of technologies, some of which enable fundamentally new forms of interaction. In this research-in-progress paper, we propose the development of a taxonomy to categorize unique characteristics of AI-based technology that influence the interaction and have ethical implications for human workers. The completed taxonomy will support researchers in forming cumulative knowledge on the ethical implications of augmentation and assist practitioners in the ethical design and management of AI-based technology in knowledge work.
With larger artificial neural networks (ANN) and deeper neural architectures, common methods for training ANN, such as backpropagation, are key to learning success. Their role becomes particularly important when interpreting and controlling structures that evolve through machine learning. This work aims to extend previous research on backpropagation-based methods by presenting a modified, full-gradient version of the backpropagation learning algorithm that preserves (or rather crystallizes) selected neural weights while leaving other weights adaptable (or rather fluid). In a design-science-oriented manner, a prototype of a feedforward ANN is demonstrated and refined using the new learning method. The results show that the so-called crystallizing backpropagation increases the control possibilities of neural structures and interpretation chances, while learning can be carried out as usual. Since neural hierarchies are established because of the algorithm, ANN compartments start to function in terms of cognitive levels. This study shows the importance of dealing with ANN in hierarchies through backpropagation and brings in learning methods as novel ways of interacting with ANN. Practitioners will benefit from this interactive process because they can restrict neural learning to specific architectural components of ANN and can focus further development on specific areas of higher cognitive levels without the risk of destroying valuable ANN structures.
Faced with the triad of time-cost-quality, the realization of production tasks under economic conditions is not trivial. Since the number of Artificial-Intelligence-(AI)-based applications in business processes is increasing more and more nowadays, the efficient design of AI cases for production processes as well as their target-oriented improvement is essential, so that production outcomes satisfy high quality criteria and economic requirements. Both challenge production management and data scientists, aiming to assign ideal manifestations of artificial neural networks (ANNs) to a certain task. Faced with new attempts of ANN-based production process improvements [8], this paper continues research about the optimal creation, provision and utilization of ANNs. Moreover, it presents a mechanism for AI case-based reasoning for ANNs. Experiments clarify continuously improving ANN knowledge bases by this mechanism empirically. Its proof-of-concept is demonstrated by the example of four production simulation scenarios, which cover the most relevant use cases and will be the basis for examining AI cases on a quantitative level.
Virtual reality can have advantages for education and learning. However, it must be adequately designed so that the learner benefits from the technological possibilities. Understanding the underlying effects of the virtual learning environment and the learner’s prior experience with virtual reality or prior knowledge of the content is necessary to design a proper virtual learning environment. This article presents a pre-study testing the design of a virtual learning environment for engineering vocational training courses. In the pre-study, 12 employees of two companies joined the training course in one of the two degrees of immersion (desktop VR and VR HMD). Quantitative results on learning success, cognitive load, usability, and motivation and qualitative learning process data were presented. The qualitative data assessment shows that overall, the employees were satisfied with the learning environment regardless of the level of immersion and that the participants asked for more guidance and structure accompanying the learning process. Further research is needed to test for solid group differences.
This chapter reviews the interplay of agglomeration and pollution as well as the effect of energy policies on pollution in an urban context. It starts by describing the effect of agglomeration on pollution. While this effect is theoretically ambiguous, empirical research tends to find that larger cities are more polluted, but per capita emissions fall with city size. The chapter discusses the implications for optimal city size. Conversely, urban pollution tends to discourage agglomeration if larger cities are more exposed to pollution. The chapter then considers various energy policies and their effect on urban pollution. Specifically, it looks at the effects of energy and transport policies as well as urban policies such as zoning.
Green recovery
(2023)
This chapter reviews how the European Union has fared in enabling a green recovery in the aftermath of the Covid-19 crisis, drawing comparisons to developments after the financial crisis. The chapter focuses on the European Commission and its evolving role in promoting decarbonisation efforts in its Member States, paying particular attention to its role in financing investments in low-carbon assets. It considers both the direct effects of green stimulus policies on decarbonisation in the EU and how these actions have shaped the capacities of the Commission as an actor in the field of climate and energy policy. The analysis reveals a significant expansion of the Commission’s role compared to the period following the financial crisis. EU-level measures have provided incentives for Member States to direct large volumes of financing towards investments in climate-friendly assets. Nevertheless, the ultimate impact will largely be shaped by implementation at the national level.
SNS Democracy Council 2023
(2023)
Transboundary problems such as climate change, military conflicts, trade barriers, and refugee flows require increased collaboration across borders. This is to a large extent possible using existing international organizations. In such a case, however, they need to be considerably strengthened – while current trends take us in the opposite direction, according to the researchers in the SNS Democracy Council 2023.
Conclusion
(2023)
Based on the previous findings in this book, Chapter 18 by Heike Krieger and Andrea Liese discusses the general dynamics of change or metamorphosis in the international legal order. They discern a mixed picture of an international order between metamorphosis—that is, a more fundamental transformation—of international law, norm change, turbulences, and robustness. They explain drivers of change and highlight factors such as national interests during the war on terror, changing long-term foreign policy beliefs, and the rise in populism and autocracy, before discussing the most common strategies the actors involved use. Other relevant factors include changes in the political environment, such as shocks and power shifts or the ambiguous role of fragmentation. Moreover, they identify factors that make legal norms robust, including the vital role of norm defenders and legal and institutional structures as stabilizing elements. Krieger and Liese conclude by cautioning that if the attacks on the international order continue at the current frequency and magnitude, a metamorphosis of international law will likely be unstoppable.
International law is constantly navigating the tension between preserving the status quo and adapting to new exigencies. But when and how do such adaptation processes give way to a more profound transformation, if not a crisis of international law? To address the question of how attacks on the international legal order are changing the value orientation of international law, this book brings together scholars of international law and international relations. By combining theoretical and methodological analyses with individual case studies, this book offers readers conceptualizations and tools to systematically examine value change and explore the drivers and mechanisms of these processes. These case studies scrutinize value change in the foundational norms of the post-1945 order and in norms representing the rise of the international legal order post-1990. They cover diverse issues: the prohibition of torture, the protection of women’s rights, the prohibition of the use of force, the non-proliferation of nuclear weapons, sustainability norms, and accountability for core international crimes. The challenges to each norm, the reactions by norm defenders, and the fate of each norm are also studied. Combined, the analyses show that while a few norms have remained surprisingly robust, several are changing, either in substance or in legal or social validity. The book concludes by integrating the conceptual and empirical insights from this interdisciplinary exchange to assess and explain the ambiguous nature of value change in international law beyond the extremes of mere progress or decline.
This chapter addresses the role of evaluation of and in public administration. We focus on two analytical key dimensions: a) the provider of the evaluation and b) the subject of the evaluation. Four major types of evaluation are distinguished: (1) external institutional evaluation, (2) internal institutional evaluation, (3) external evaluation of administrative action/results, (4) internal evaluation of administrative action/results. Type 1 and 2 refer to evaluation of administrative structures and processes as the subject of administrative reform. Type 3 and 4 represent different versions of evaluation in public administration, because the subject is administrative action and its outputs. The chapter highlights salient approaches and organizational settings of evaluation and provides insights into the institutionalization of an evaluation function in public administration. Finally, the chapter draws lessons regarding strengths and potentials but also remaining weaknesses and challenges of evaluation of and in public administration.
Fighting false information
(2023)
The digital transformation poses challenges for public sector organizations (PSOs) such as the dissemination of false information in social media which can cause uncertainty among citizens and decrease trust in the public sector. Some PSOs already successfully deploy conversational agents (CAs) to communicate with citizens and support digital service delivery. In this paper, we used design science research (DSR) to examine how CAs could be designed to assist PSOs in fighting false information online. We conducted a workshop with the municipality of Kristiansand, Norway to define objectives that a CA would have to meet for addressing the identified false information challenges. A prototypical CA was developed and evaluated in two iterations with the municipality and students from Norway. This research-in-progress paper presents findings and next steps of the DSR process. This research contributes to advancing the digital transformation of the public sector in combating false information problems.
This technical report presents the results of student projects which were prepared during the lecture “Operating Systems II” offered by the “Operating Systems and Middleware” group at HPI in the Summer term of 2020. The lecture covered ad- vanced aspects of operating system implementation and architecture on topics such as Virtualization, File Systems and Input/Output Systems. In addition to attending the lecture, the participating students were encouraged to gather practical experience by completing a project on a closely related topic over the course of the semester. The results of 10 selected exceptional projects are covered in this report.
The students have completed hands-on projects on the topics of Operating System Design Concepts and Implementation, Hardware/Software Co-Design, Reverse Engineering, Quantum Computing, Static Source-Code Analysis, Operating Systems History, Application Binary Formats and more. It should be recognized that over the course of the semester all of these projects have achieved outstanding results which went far beyond the scope and the expec- tations of the lecture, and we would like to thank all participating students for their commitment and their effort in completing their respective projects, as well as their work on compiling this report.
In the last two centuries BC, with the Republic limping towards its end, the cultivated ruling elite began to lose its moral and political authority.1 Its members not only held themselves responsible for the so-called crisis of tradition, but at the same time also conveyed the impression of a loss of memory, as if all Romans were suffering from some kind of amnesia or identity crisis.2 In particular, institutional figures such as pontiffs and augurs, who had preserved Rome’s memory throughout its history, were accused of neglecting their duties and, by extension, of allowing ancient practices and values to slowly disappear.3 Accordingly, Cicero and Varro, both perfect representatives of this elite, employed recurrent terms such as neglect (neglegentia/neglegere), involuntary abandon (amittere), oblivion (oblivio), vanishing of institutions (evanescere), and ignorance (ignoratio/ignorare) to describe this critical loss of information; they depicted the citizenry of Rome (civitas) as disoriented and estranged, incapable of sharing any common knowledge or values.
Digital technology offers significant political, economic, and societal opportunities. At the same time, the notion of digital sovereignty has become a leitmotif in German discourse: the state’s capacity to assume its responsibilities and safeguard society’s – and individuals’ – ability to shape the digital transformation in a self-determined way. The education sector is exemplary for the challenge faced by Germany, and indeed Europe, of harnessing the benefits of digital technology while navigating concerns around sovereignty. It encompasses education as a core public good, a rapidly growing field of business, and growing pools of highly sensitive personal data. The report describes pathways to mitigating the tension between digitalization and sovereignty at three different levels – state, economy, and individual – through the lens of concrete technical projects in the education sector: the HPI Schul-Cloud (state sovereignty), the MERLOT data spaces (economic sovereignty), and the openHPI platform (individual sovereignty).
How do social changes, new technologies or new management trends affect communication work? A team of researchers at Leipzig University and the University of Potsdam (Germany) observed new developments in related disciplines. As a result, the five most important trends for corporate communications are identified annually and published in the Communications Trend Radar. Thus, Communications managers can identify challenges and opportunities at an early stage, take a position, address issues and make decisions. For 2023, the Communications Trend Radar identifies five key trends for corporate communications: State Revival, Scarcity Management, Unimagination, Parallel Worlds, Augemented Workflows.
During the outbreak of the COVID-19 pandemic, many people shared their symptoms across Online Social Networks (OSNs) like Twitter, hoping for others’ advice or moral support. Prior studies have shown that those who disclose health-related information across OSNs often tend to regret it and delete their publications afterwards. Hence, deleted posts containing sensitive data can be seen as manifestations of online regrets. In this work, we present an analysis of deleted content on Twitter during the outbreak of the COVID-19 pandemic. For this, we collected more than 3.67 million tweets describing COVID-19 symptoms (e.g., fever, cough, and fatigue) posted between January and April 2020. We observed that around 24% of the tweets containing personal pronouns were deleted either by their authors or by the platform after one year.
As a practical application of the resulting dataset, we explored its suitability for the automatic classification of regrettable content on Twitter.
In this chapter, we conduct bibliometric performance analyses and a co-citation analysis on all articles relating to family firms indexed in Scopus and Web of Science and all articles published in the Family Business Review, Journal of Family Business Management, and the Journal of Family Business Strategy. Based on the literature sample of 4,056 articles published between 1960 and 2020 by 3,600 authors in 783 journals and their 175,163 references, we identify the most productive and most cited journals, the most cited authors, and the 25 most cited articles. Our science mapping reveals the agency theory, definitions, entrepreneurship, internationalization, ownership, resources, socioemotional wealth, and succession as the predominant research themes in family firm research. Whereas entrepreneurship explicitly appears in one of the clusters, innovation does not yet. Based on our findings, we propose a research framework and point to several research gaps to be addressed by future research.
Despite the merits of public and social media in private and professional spaces, citizens and professionals are increasingly exposed to cyberabuse, such as cyberbullying and hate speech. Thus, Law Enforcement Agencies (LEA) are deployed in many countries and organisations to enhance the preventive and reactive capabilities against cyberabuse. However, their tasks are getting more complex by the increasing amount and varying quality of information disseminated into public channels. Adopting the perspectives of Crisis Informatics and safety-critical Human-Computer Interaction (HCI) and based on both a narrative literature review and group discussions, this paper first outlines the research agenda of the CYLENCE project, which seeks to design strategies and tools for cross-media reporting, detection, and treatment of cyberbullying and hatespeech in investigative and law enforcement agencies. Second, it identifies and elaborates seven research challenges with regard to the monitoring, analysis and communication of cyberabuse in LEAs, which serve as a starting point for in-depth research within the project.
The authors propose that while tacit knowledge is a valuable resource for developing new business models, its externalization presents several challenges. One major challenge is that individuals often don’t recognize their tacit knowledge resources, while another is the reluctance to share one’s knowledge with others. Addressing these challenges, the authors present an application-oriented serious game-based haptic modeling approach for externalize tacit knowledge, which can be used to develop the first versions of business models based on tacit knowledge. Both conceptual and practical design fundamentals are presented based on elaborated theoretical approaches, which were developed with the help of a design science approach. The development of the research process is presented step by step, whereby we focused on the high accessibility of the presented research. Practitioners are presented with guidelines for implementing their serious game projects. Scientists benefit from starting points for their research topics of externalization, internalization, and socialization of tacit knowledge, development of business models, and serious games or gamification. The paper concludes with open research desiderata and questions from the presented research process.
Business processes are regularly modified either to capture requirements from the organization’s environment or due to internal optimization and restructuring. Implementing the changes into the individual work routines is aided by change management tools. These tools aim at the acceptance of the process by and empowerment of the process executor. They cover a wide range of general factors and seldom accurately address the changes in task execution and sequence. Furthermore, change is only framed as a learning activity, while most obstacles to change arise from the inability to unlearn or forget behavioural patterns one is acquainted with. Therefore, this paper aims to develop and demonstrate a notation to capture changes in business processes and identify elements that are likely to present obstacles during change. It connects existing research from changes in work routines and psychological insights from unlearning and intentional forgetting to the BPM domain. The results contribute to more transparency in business process models regarding knowledge changes. They provide better means to understand the dynamics and barriers of change processes.
Decubitus is one of the most relevant diseases in nursing and the most expensive to treat. It is caused by sustained pressure on tissue, so it particularly affects bed-bound patients. This work lays a foundation for pressure mattress-based decubitus prophylaxis by implementing a solution to the single-frame 2D Human Pose Estimation problem.
For this, methods of Deep Learning are employed. Two approaches are examined, a coarse-to-fine Convolutional Neural Network for direct regression of joint coordinates and a U-Net for the derivation of probability distribution heatmaps.
We conclude that training our models on a combined dataset of the publicly available Bodies at Rest and SLP data yields the best results. Furthermore, various preprocessing techniques are investigated, and a hyperparameter optimization is performed to discover an improved model architecture.
Another finding indicates that the heatmap-based approach outperforms direct regression.
This model achieves a mean per-joint position error of 9.11 cm for the Bodies at Rest data and 7.43 cm for the SLP data.
We find that it generalizes well on data from mattresses other than those seen during training but has difficulties detecting the arms correctly.
Additionally, we give a brief overview of the medical data annotation tool annoto we developed in the bachelor project and furthermore conclude that the Scrum framework and agile practices enhanced our development workflow.
RailChain
(2023)
The RailChain project designed, implemented, and experimentally evaluated a juridical recorder that is based on a distributed consensus protocol. That juridical blockchain recorder has been realized as distributed ledger on board the advanced TrainLab (ICE-TD 605 017) of Deutsche Bahn.
For the project, a consortium consisting of DB Systel, Siemens, Siemens Mobility, the Hasso Plattner Institute for Digital Engineering, Technische Universität Braunschweig, TÜV Rheinland InterTraffic, and Spherity has been formed. These partners not only concentrated competencies in railway operation, computer science, regulation, and approval, but also combined experiences from industry, research from academia, and enthusiasm from startups.
Distributed ledger technologies (DLTs) define distributed databases and express a digital protocol for transactions between business partners without the need for a trusted intermediary. The implementation of a blockchain with real-time requirements for the local network of a railway system (e.g., interlocking or train) allows to log data in the distributed system verifiably in real-time. For this, railway-specific assumptions can be leveraged to make modifications to standard blockchains protocols.
EULYNX and OCORA (Open CCS On-board Reference Architecture) are parts of a future European reference architecture for control command and signalling (CCS, Reference CCS Architecture – RCA). Both architectural concepts outline heterogeneous IT systems with components from multiple manufacturers. Such systems introduce novel challenges for the approved and safety-relevant CCS of railways which were considered neither for road-side nor for on-board systems so far. Logging implementations, such as the common juridical recorder on vehicles, can no longer be realized as a central component of a single manufacturer. All centralized approaches are in question.
The research project RailChain is funded by the mFUND program and gives practical evidence that distributed consensus protocols are a proper means to immutably (for legal purposes) store state information of many system components from multiple manufacturers. The results of RailChain have been published, prototypically implemented, and experimentally evaluated in large-scale field tests on the advanced TrainLab. At the same time, the project showed how RailChain can be integrated into the road-side and on-board architecture given by OCORA and EULYNX.
Logged data can now be analysed sooner and also their trustworthiness is being increased. This enables, e.g., auditable predictive maintenance, because it is ensured that data is authentic and unmodified at any point in time.
Like conventional software projects, projects in model-driven software engineering require adequate management of multiple versions of development artifacts, importantly allowing living with temporary inconsistencies. In the case of model-driven software engineering, employed versioning approaches also have to handle situations where different artifacts, that is, different models, are linked via automatic model transformations.
In this report, we propose a technique for jointly handling the transformation of multiple versions of a source model into corresponding versions of a target model, which enables the use of a more compact representation that may afford improved execution time of both the transformation and further analysis operations. Our approach is based on the well-known formalism of triple graph grammars and a previously introduced encoding of model version histories called multi-version models. In addition to showing the correctness of our approach with respect to the standard semantics of triple graph grammars, we conduct an empirical evaluation that demonstrates the potential benefit regarding execution time performance.
Modular and incremental global model management with extended generalized discrimination networks
(2023)
Complex projects developed under the model-driven engineering paradigm nowadays often involve several interrelated models, which are automatically processed via a multitude of model operations. Modular and incremental construction and execution of such networks of models and model operations are required to accommodate efficient development with potentially large-scale models. The underlying problem is also called Global Model Management.
In this report, we propose an approach to modular and incremental Global Model Management via an extension to the existing technique of Generalized Discrimination Networks (GDNs). In addition to further generalizing the notion of query operations employed in GDNs, we adapt the previously query-only mechanism to operations with side effects to integrate model transformation and model synchronization. We provide incremental algorithms for the execution of the resulting extended Generalized Discrimination Networks (eGDNs), as well as a prototypical implementation for a number of example eGDN operations.
Based on this prototypical implementation, we experiment with an application scenario from the software development domain to empirically evaluate our approach with respect to scalability and conceptually demonstrate its applicability in a typical scenario. Initial results confirm that the presented approach can indeed be employed to realize efficient Global Model Management in the considered scenario.