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For the last 20 years, enterprise architecture management (EAM) was primarily an instrument for harmonizing and consolidating IT landscapes and is lived as a transformation and governance discipline. It, however, is rather related to IT strategy than aligned to the actual corporate strategy and the work of the enterprise architect is characterized by tasks like prescribing, monitoring, documenting, and controlling. As digital transformation continues apace, companies are facing new challenges that lead to a volatile, uncertain, complex, and ambiguous (VUCA) world. To face these challenges, vision, understanding, clarity and agility allow to anticipative and implement necessary changes. This, of course, has implications for the role of the enterprise architect. S/he needs to start actively supporting innovation and taking more of an advisory role instead of just being driven by the current state of the enterprise architecture. This paper investigates the role of the enterprise architect in the VUCA world. Based on current literature and expert interviews, a survey was conducted among consultants who work as (or with) enterprise architects. Survey results include the evaluation of statements on current tasks of enterprise architects, their influence on projects and companies as well as future requirements on the roles of the enterprise architect. The results from the survey were synthesized with the findings from literature to derive the roles, tasks and skills of enterprise architect in the VUCA world.
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.
I need to move it, move It!
(2024)
Purpose
Student interest and learning success is an important component of teaching learning research. However, while the impact of emotions and psychological needs on students' achievements has been a focus of research, the impact of their physiological needs has been under studied. In this explorative study, I examine what impact the physiological and psychological needs of student teachers have on their feelings, motivation, and interest in different learning settings.
Approach
The research method used was the daily reconstruction method and included the Felix-App, a new digital research and feedback tool that allows the measurement of feelings, needs, motivation, and interest in real time.
Findings
The results suggest the importance of physiological needs for perceived emotions, motivation, and interest in the learning subject. The psychological needs, on the other hand, are of less importance.
Originality
The Felix-App is an innovative tool to learn more about learners' emotions and needs in real learning settings. The importance of physiological needs has been known since Maslow, but should be considered much more in the context of teaching and learning research in the future. There is a need for further research on the importance of physical aspects in learning.
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.
Observing inconsistent results in prior studies, this paper applies the elaboration likelihood model to investigate the impact of affective and cognitive cues embedded in social media messages on audience engagement during a political event. Leveraging a rich dataset in the context of the 2020 U.S. presidential elections containing more than 3 million tweets, we found the prominence of both cue types. For the overall sample, positivity and sentiment are negatively related to engagement. In contrast, the post-hoc sub-sample analysis of tweets from famous users shows that emotionally charged content is more engaging. The role of sentiment decreases when the number of followers grows and ultimately becomes insignificant for Twitter participants with a vast number of followers. Prosocial orientation (“we-talk”) is consistently associated with more likes, comments, and retweets in the overall sample and sub-samples.
During a crisis event, social media enables two-way communication and many-to-many information broadcasting, browsing others’ posts, publishing own content, and public commenting. These records can deliver valuable insights to approach problematic situations effectively. Our study explores how social media communication can be analyzed to understand the responses to health crises better. Results based on nearly 800 K tweets indicate that the coping and regulation foci framework holds good explanatory power, with four clusters salient in public reactions: 1) “Understanding” (problem-promotion); 2) “Action planning” (problem-prevention); 3) “Hope” (emotion-promotion) and 4) “Reassurance” (emotion-prevention). Second, the inter-temporal analysis shows high volatility of topic proportions and a shift from self-centered to community-centered topics during the course of the event. The insights are beneficial for research on crisis management and practicians who are interested in large-scale monitoring of their audience for well-informed decision-making.
Does a smile open all doors?
(2020)
Online photographs govern an individual’s choices across a variety of contexts. In sharing arrangements, facial appearance has been shown to affect the desire to collaborate, interest to explore a listing, and even willingness to pay for a stay. Because of the ubiquity of online images and their influence on social attitudes, it seems crucial to be able to control these aspects. The present study examines the effect of different photographic self-disclosures on the provider’s perceptions and willingness to accept a potential co-sharer. The findings from our experiment in the accommodation-sharing context suggest social attraction mediates the effect of photographic self-disclosures on willingness to host. Implications of the results for IS research and practitioners are discussed.
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.
Accelerating knowledge
(2019)
As knowledge-intensive processes are often carried out in teams and demand for knowledge transfers among various knowledge carriers, any optimization in regard to the acceleration of knowledge transfers obtains a great economic potential. Exemplified with product development projects, knowledge transfers focus on knowledge acquired in former situations and product generations. An adjustment in the manifestation of knowledge transfers in its concrete situation, here called intervention, therefore can directly be connected to the adequate speed optimization of knowledge-intensive process steps. This contribution presents the specification of seven concrete interventions following an intervention template. Further, it describes the design and results of a workshop with experts as a descriptive study. The workshop was used to assess the practical relevance of interventions designed as well as the identification of practical success factors and barriers of their implementation.
Context-aware, intelligent musical instruments for improving knowledge-intensive business processes
(2022)
With shorter song publication cycles in music industries and a reduced number of physical contact opportunities because of disruptions that may be an obstacle for musicians to cooperate, collaborative time consumption is a highly relevant target factor providing a chance for feedback in contemporary music production processes. This work aims to extend prior research on knowledge transfer velocity by augmenting traditional designs of musical instruments with (I) Digital Twins, (II) Internet of Things and (III) Cyber-Physical System capabilities and consider a new type of musical instrument as a tool to improve knowledge transfers at knowledge-intensive forms of business processes. In a design-science-oriented way, a prototype of a sensitive guitar is constructed as information and cyber-physical system. Findings show that this intelligent SensGuitar increases feedback opportunities. This study establishes the importance of conversion-specific music production processes and novel forms of interactions at guitar playing as drivers of high knowledge transfer velocities in teams and among individuals.
Although mothers and fathers in almost all rich democracies are entitled to some form of paid parenting leave, fathers in particular do not take all the leave available to them. As employers play an important role in the implementation of parenting leave policies, this chapter investigates which workplace characteristics influence mothers' and fathers' uptake of their statutory leave entitlements. In Part 1, we estimate the size of the gap between statutory leave entitlement and leave uptake across genders and countries by combining data from the OECD and the European Labor Force Survey. In Parts 2 and 3, we review the literature on structural, cultural, and normative explanations for the gap in parenting leave uptake. We conclude the chapter with suggestions for further research, including the need for reliable data on the size of the implementation gap and research on non-European countries.
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.
Modern browsers are digital software platforms, as they allow third parties to extend functionality by providing extensions. In a highly competitive environment, differentiation through provided functionality is a key factor for browser platforms. As the development of browsers progress, new functions are constantly being released. Browsers could thus enter complementary markets by adding functionality previously provided by third-party extensions, which is referred to as ‘platform coring’. Previous studies have missed the perspective of the parties involved. To address this gap, we conducted interviews with third-party and core developers in the security and privacy domain from Firefox and Chrome. This study provides three contributions. First, insights into stakeholder-specific issues concerning coring. Second, measures to prevent coring. Third, strategical guidance for developers and owners. Third-party vendors experienced and core developers confirmed that coring occurs on browser platforms. While developers with extrinsic motivations assess coring negatively, developers with intrinsic motivations perceive coring positively.
Software platforms regularly introduce new features to remain competitive. While platform innovation is considered to be a critical success factor, adding certain features could hurt the ecosystem. If platform owners provide functionality that was previously provided by a contributor, the owners enter complementary product spaces. Complementary market entry frequently occurs on software platforms and is a major concern for third-party developers.
Divergent findings on the impact of complementary market entry call for the consideration of additional factors. As prior research neglected the third-party perspective, this contribution aims to address this gap. We explore the use of measures to prevent complementary market entry using a survey approach on browser platforms. The research model is tested with 655 responses among developer from Mozilla Firefox and Google Chrome. To explain countermeasures employment, developer’s attitude and perceived likelihood are important. The results reveal that developers employ countermeasures if complementary market entry is assessed negatively and perceived as likely for their extension. Differences among browser platforms concerning complementary market entry are identified. Product spaces of extensions being available on multiple platforms are less likely to be entered and more heavily protected. Implications for research and stakeholders, i.e. platform owners and contributors are discussed.
Social institutions
(2024)
Social institutions are a system of behavioral and relationship patterns that are densely interwoven and enduring and function across an entire society. They order and structure the behavior of individuals in core areas of society and thus have a strong impact on the quality of life of individuals. Institutions regulate the following: (a) family and relationship networks carry out social reproduction and socialization; (b) institutions in the realm of education and training ensure the transmission and cultivation of knowledge, abilities, and specialized skills; (c) institutions in the labor market and economy provide for the production and distribution of goods and services; (d) institutions in the realm of law, governance, and politics provide for the maintenance of the social order; (e) while cultural, media, and religious institutions further the development of contexts of meaning, value orientations, and symbolic codes.
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.