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As followers are becoming more educated and better connected, empowering leadership has gained traction in recent times as an alternative to traditional top-down models of leadership. Several scholars have investigated the relationship between empowering leadership and other variables in different contexts. As most previous studies have focused on the positive aspects of empowering leadership, research on its potential dark side is scarce. Furthermore, no previous study has examined whether and how the transfer of workload from followers to leaders can occur over time, which I proposed can lead to emotional exhaustion and work-family conflict among leaders. Therefore, I proposed that despite the positive outcomes of empowering leadership for both followers and leaders, it may also trigger negative outcomes capable of affecting the well-being of leaders. Drawing on the Conservation of Resources (COR) theory, Job Demand-Resources (JD-R) theory, and Too-Much-of-a-Good-Thing (TMGT) effect model, I investigated this idea. Using follower workload as a moderator, I proposed that the relationship between empowering leadership and leader workload is positive when follower workload is high and negative when follower workload is low. In addition, I examined how empowering leadership interacts with follower workload to affect leader emotional exhaustion and work-family conflict, mediated by leader workload. I proposed that this interaction results in a negative relationship between empowering leadership and both outcomes when follower workload is low, and a positive relationship when it is high.
I tested these hypotheses using data from a three-wave time-lagged design field study with 65 leader-follower dyads consisting of civil servants from different administrative entities of India and Pakistan. The time lag between each study variable was four weeks. At Time 1 (T1), followers answered questions about demographic characteristics, virtual interaction with their leaders, their workload, and the extent to which their leaders practice empowering leadership. At the same time, leaders answered questions about demographic characteristics and their job satisfaction. At Time 2 (T2), leaders provided data on their own workload. Finally, at Time 3 (T3), leaders rated their emotional exhaustion and work-family conflict. A moderated mediation model was tested using PROCESS Model 7 in R. The findings of the study reveal that a significant increase in follower workload through empowering leadership will also increase the leader's workload. Consequently, this increased leader workload leads to a crossover of this interactive effect onto the level of emotional exhaustion and work-family conflict experienced by leaders.
This research offers various contributions to the leadership literature. While empowering leadership has been commonly associated with positive outcomes, my study reveals that it can also lead to negative outcomes. In addition, it shifts the focus of existing research from the effect of empowering leadership on followers to the consequences that it might have for leaders themselves. Overall, my research underscores the need for leaders to consider the potential counterproductive effects of empowering leadership and tailor their approach accordingly.
Quantified Self, die pro-aktive Selbstvermessung von Menschen, hat sich in den letzten Jahren von einer Nischenanwendung zu einem Massenphänomen entwickelt. Dabei stehen den Nutzern heute vielfältige technische Unterstützungsmöglichkeiten, beispielsweise in Form von Smartphones, Fitness-Trackern oder Gesundheitsapps zur Verfügung, welche eine annähernd lückenlose Überwachung unterschiedlicher Kontextfaktoren einer individuellen Lebenswirklichkeit erlauben.
In der Folge widmet sich diese Arbeit unter anderem der Fragestellung, inwieweit diese intensive und eigen-initiierte Beschäftigung, insbesondere mit gesundheitsbezogenen Daten, die weitgehend als objektiviert und damit belastbar gelten, die Gesundheitskompetenz derart aktiver Menschen erhöhen kann. Darüber hinaus werden Aspekte untersucht, inwieweit die neuen Technologien in der Lage sind, spezifische medizinische Erkenntnisse zu vertiefen und in der Konsequenz die daraus resultierenden Behandlungsprozesse zu verändern.
Während der Ursprung des Quantified Self im 2. Gesundheitsmarkt liegt, geht die vorliegende Arbeit der Frage nach, welche strukturellen, personellen und prozessualen Anknüpfungspunkte perspektivisch im 1. Gesundheitsmarkt existieren werden, wenn ein potentieller Patient in einer stärker emanzipierten Weise den Wunsch verspürt, oder eine entsprechende Forderung stellt, seine gesammelten Gesundheitsdaten in möglichst umfassender Form in eine medizinische Behandlung zu integrieren.
Dabei werden auf der einen Seite aktuelle Entwicklungen im 2. Gesundheitsmarkt untersucht, die gekennzeichnet sind von einer hohen Dynamik und einer großen Intransparenz. Auf der anderen Seite steht der als stark reguliert und wenig digitalisiert geltende 1. Gesundheitsmarkt mit seinen langen Entwicklungszyklen und ausgeprägten Partikularinteressen der verschiedenen Stakeholder.
In diesem Zuge werden aktuelle Entwicklungen des zugrunde liegenden Rechtsrahmens, speziell im Hinblick auf stärker patientenzentrierte und digitalisierte Normen untersucht, wobei insbesondere das Digitale Versorgung Gesetz eine wichtige Rolle einnimmt.
Ziel der Arbeit ist die stärkere Durchdringung von Wechselwirkungen an der Schnittstelle zwischen den beiden Gesundheitsmärkten in Bezug auf die Verwendung von Technologien der Selbstvermessung, um in der Folge zukünftige Geschäftspotentiale für existierende oder neu in den Markt drängende Dienstleister zu eruieren.
Als zentrale Methodik kommt hier eine Delphi-Studie zum Einsatz, die in einem interprofessionellen Ansatz versucht, ein Zukunftsbild dieser derzeit noch sehr jungen Entwicklungen für das Jahr 2030 aufzuzeigen. Eingebettet werden die Ergebnisse in die Untersuchung einer allgemeinen gesellschaftlichen Akzeptanz der skizzierten Veränderungen.
This study aims to bring together scattered research findings on user satisfaction with mobile government apps into a unified framework. The researchers analyzed 70 high-quality papers from leading journals and conferences and systematically integrated different frameworks and case studies to reflect the importance of the field over time while also highlighting methodological and geographical research gaps. The study achieved a significant methodological advance by developing codebooks for empirical analysis utilizing the App Store. This approach validated the framework’s dimensions on 8,524 reviews, demonstrating the framework’s applicability to platform-based apps and identifying critical areas for future research. Combining academic insights with practical findings, this research provides comprehensive guidance for developing and evaluating user-centered mobile government apps, facilitating improved service delivery and alignment with user expectations.
Traditionally, business models and software designs used to model the usage of artificial intelligence (AI) at a very specific point in the process or rather fix implemented application. Since applications can be based on AI, such as networked artificial neural networks (ANN) on top of which applications are installed, these on-top applications can be instructed directly from their underlying ANN compartments [1]. However, with the integration of several AI-based systems, their coordination is a highly relevant target factor for the operation and improvement of networked processes, such as they can be found in cross-organizational production contexts spanning multiple distributed locations. This work aims to extend prior research on managing artificial knowledge transfers among interlinked AIs as coordination instrument by examining effects of different activation types (respective activation rates and cycles) on by ANN-instructed production machines. In a design-science-oriented way, this paper conceptualizes rhythmic state descriptions for dynamic systems and associated 14 experiment designs. Two experiments have been realized, analyzed and evaluated thereafter in regard with their activities and processes induced. Findings show that the simulator [2] used and experiments designed and realized, here, (I) enable research on ANN activation types, (II) illustrate ANN-based production networks disrupted by activation types and clarify the need for harmonizing them. Further, (III) management interventions are derived for harmonizing interlinked ANNs. This study establishes the importance of site-specific coordination mechanisms and novel forms of management interventions as drivers of efficient artificial knowledge transfer.
With the further development of more and more production machines into cyber-physical systems, and their greater integration with artificial intelligence (AI) techniques, the coordination of intelligent systems is a highly relevant target factor for the operation and improvement of networked processes, such as they can be found in cross-organizational production contexts spanning multiple distributed locations. This work aims to extend prior research on managing their artificial knowledge transfers as coordination instrument by examining effects of different activation types (respective activation rates and cycles) on by Artificial Neural Network (ANN)-instructed production machines. For this, it provides a new integration type of ANN-based cyber-physical production system as a tool to research artificial knowledge transfers: In a design-science-oriented way, a prototype of a simulation system is constructed as Open Source information system which will be used in on-building research to (I) enable research on ANN activation types in production networks, (II) illustrate ANN-based production networks disrupted by activation types and clarify the need for harmonizing them, and (III) demonstrate conceptual management interventions. This simulator shall establish the importance of site-specific coordination mechanisms and novel forms of management interventions as drivers of efficient artificial knowledge transfer.
A remarkable peculiarity of videoconferencing (VC) applications – the self-view – a.k.a. digital mirror, is examined as a potential reason behind the voiced exhaustion among users. This work draws on technostress research and objective self-awareness theory and proposes the communication role (sender vs. receiver) as an interaction variable. We report the results of two studies among European employees (n1 = 176, n2 = 253) with a one-year time lag. A higher frequency of self-view in a VC when receiving a message, i.e., listening to others, indirectly increases negative affect (study 1 & 2) and exhaustion (study 2) via the increased state of public self-awareness. Self-viewing in the role of message sender, e.g., as an online presenter, also increases public self-awareness, but its overall effects are less harmful. As for individual differences, users predisposed to public self-consciousness were more concerned with how other VC participants perceived them. Gender effects were insignificant.
Technology for humanity
(2023)
The educational sector currently faces a massive digital transformation with various digital offerings entering the market. To provide some orientation in this transforming space, a national digital education platform (NDEP) is under development in Germany as part of a nationwide flagship project. On the one hand, in efficiently connecting the relevant stakeholders to each other and to value-adding education-related offerings, various benefits emerge. On the other hand, monopolising the educational sector and influencing the respective market through a state-controlled platform bears potential regulatory risks from misuse of power by the platform to malpractice by the users. Against this background, we aim to identify and systematise these potential drawbacks prior to the platform’s actual development and implementation. We pursue a qualitative, interpretivist approach for policy analysis, based on ten elite interviews and two workshops. Our results are threefold: (1) We capture the consolidated NDEP architecture; (2) We categorise the range of relevant functions and value propositions of the NDEP; (3) We derive 23 regulatory areas of conflict across the three building blocks that result from the potential ecosystem and function scope configurations of the NDEP. As a contribution to research, we shed new interdisciplinary light on the governance and infrastructure of public-private platforms that enable innovation and collaboration while integrating respective market segments. As a contribution to practice, we provide clear guidance for policy-makers in strategizing the development and governance of and through national digital platforms in education.
The increasing prevalence and ubiquity of digital technologies is changing the needs and expectations of patients towards healthcare services. As a result, a plethora of patient-centered services edges into the healthcare market. Since digital technologies bear the potential to surmount barriers in time and space, patients increasingly demand real-time or near-time healthcare services. Amongst a cloud of related concepts in the context of digital health, one term increasingly typifies this impulse: on-demand healthcare. While this term can be noticeably found in practice, there is hardly some theoretical foundation so far. Against this background, the aim of this paper is to address this research gap and to explore the phenomenon of on-demand healthcare. Based on a design-science approach including a literature review and analysis of in-depth interviews and empirical cases, the outcome of this paper is twofold: (1) a conceptual framework and (2) a proposal for a definition of on-demand healthcare.
The usage of data to improve or create business models has become vital for companies in the 21st century. However, to extract value from data it is important to understand the business model. Taxonomies for data-driven business models (DDBM) aim to provide guidance for the development and ideation of new business models relying on data. In IS research, however, different taxonomies have emerged in recent years, partly redundant, partly contradictory. Thus, there is a need to synthesize the common ground of these taxonomies within IS research. Based on 26 IS-related taxonomies and 30 cases, we derive and define 14 generic building blocks of DDBM to develop a consolidated taxonomy that represents the current state-of-the-art. Thus, we integrate existing research on DDBM and provide avenues for further exploration of data-induced potentials for business models as well as for the development and analysis of general or industry-specific DDBM.
Uncovering the digitalization impact on consumer decision-making for checking accounts in banking
(2022)
Checking account providers must understand the importance of digital and non-digital service attributes across different customer segments to achieve a product-market fit in digitalization. In particular, various latent personal characteristics influence customer choices in digital banking. However, there is only limited research on banking customer behavior beyond the technology acceptance model, and none that explores customer preferences for checking accounts experimentally. Against this background, we present the results of a discrete choice experiment on customer preferences towards checking accounts in Germany. The outcome of the paper is a detailed quantitative assessment of the relationships between checking account service attributes and a set of latent influencing factors on choice. While customer service experience, the scope of services, and professional expertise are identified as re-occurring critical aspects for customers when choosing their banking service provider, the type of provider and digital product innovation showed little impact on customer choice overall. In multigroup analyses, we reveal the moderating impact of influencing factors on the preference of checking account service attributes. Additional segmentation analyses point to six customer segments from which four still prefer a traditional operating model. The largest segment of traditional product-innovative customers prefers digitalized, i.e., data-driven checking accounts in a mixed-mode with human customer advisory and on-site branch services from a traditional bank. At the other end of the spectrum, a small innovative Fintech customer segment, influenced by non-pragmatism and social norms, prefers a purely digital operating model with data-driven applications in banking.
Due to changing customer behavior in digitalization, banks urge to change their traditional value creation in order to improve interaction with customers. New digital technologies such as core banking solutions change organizational structures to provide organizational and individual affordances in IT-supported personal advisory. Based on adaptive structuration theory and with qualitative data from 24 German banks, we identify first, second and third order issues of organizational change in value creation, which are connected with a set of affordances and constraints as the outcomes for customer interaction.
Learning in virtual, immersive environments must be well-designed to foster learning instead of overwhelming and distracting the learner. So far, learning instructions based on cognitive load theory recommend keeping the learning instructions clean and simple to reduce the extraneous cognitive load of the learner to foster learning performance. The advantages of immersive learning, such as multiple options for realistic simulation, movement and feedback, raise questions about the tension between an increase of excitement and flow with highly realistic environments on the one hand and a reduction of cognitive load by developing clean and simple surroundings on the other hand. This study aims to gain insights into learners' cognitive responses during the learning process by continuously assessing cognitive load through eye-tracking. The experiment compares two distinct immersive learning environments and varying methods of content presentation.
As a central functionality of SNSs, the newsfeed is responsible for the way, how content is presented. This paper investigates the implications of current content presentation on Facebook, which has appeared to be a matter of users’ criticism. Leaning on the communication theory, we conceptualize clutter on a newsfeed as noise that hinders the receiver’s adequate message decoding (i.e., sensemaking). We further operationalize newsfeed clutter via perceived disorder, information overload, and system feature overload. Our participants browsed their Facebook newsfeed for at least 5 minutes. The follow-up survey results provide partial support for our hypotheses, with only perceived disorder significantly associated with lower sensemaking. These findings shed new light on user experience and underpin the importance of SNSs as communication systems, adding to the existent literature on the dark sides of social media.
This systematic literature review highlights the gap in demand forecasting in the manufacturing sector, which is challenged by complex supply chains and rapid market change. Traditional methods fall short in this dynamic environment, highlighting the need for an approach that combines advanced forecasting techniques, high-quality data, and industry-specific insights. Our research contributes by evaluating advanced forecasting methods, the effectiveness of AI and data strategies to improve accuracy. Our analysis reveals a shift towards machine learning and deep learning to improve accuracy and highlights the untapped potential of external data sources. Key findings provide both researchers and practitioners with guidance on effective forecasting strategies and key data types and offer an integrated framework for improving forecasting accuracy and strategic decision-making in manufacturing. This work fills a critical research gap and provides stakeholders with actionable insights to manage the complexity of modern manufacturing, representing a significant advance in forecasting practice.
The field of healthcare is characterized by constant innovation, with gender-specific medicine emerging as a new subfield that addresses sex and gender disparities in clinical manifestations, outcomes, treatment, and prevention of disease. Despite its importance, the adoption of gender-specific medicine remains understudied, posing potential risks to patient outcomes due to a lack of awareness of the topic. Building on the Innovation Decision Process Theory, this study examines the spread of information about gender-specific medicine in online networks. The study applies social network analysis to a Twitter dataset reflecting online discussions about the topic to gain insights into its adoption by health professionals and patients online. Results show that the network has a community structure with limited information exchange between sub-communities and that mainly medical experts dominate the discussion. The findings suggest that the adoption of gender-specific medicine might be in its early stages, focused on knowledge exchange. Understanding the diffusion of gender-specific medicine among medical professionals and patients may facilitate its adoption and ultimately improve health outcomes.
Increasingly, research attention is being afforded to various forms of problematic media use. Despite ongoing conceptual, theoretical, and empirical debates, a large number of retrospective self-report scales have been produced to ostensibly measure various classes of such behaviour. These scales are typically based on a variety of theoretical and diagnostic frameworks. Given current conceptual ambiguities, building on previous studies, we evaluated the dimensional structure of 50 scales targeting the assessment of supposedly problematic behaviours in relation to four technologies: Internet, smartphones, video games, and social network sites. We find that two dimensions (‘compulsive use’ and ‘negative outcomes’) account for over 50% of all scale-items analysed. With a median of five dimensions, on average, scales have considered fewer dimensions than various proposed diagnostic criteria and models. No relationships were found between the number of items in a scale and the number of dimensions, or the technology category and the dimensional structure. The findings indicate, firstly, that a majority of scales place an inordinate emphasis on some dimensions over others and, secondly, that despite differences in the items presented, at a dimensional level, there exists a high degree of similarity between scales. These findings highlight shortcomings in existing scales and underscore the need to develop more sophisticated conceptions and empirical tools to understand possible problematic interactions with various digital technologies.
Consumer behaviour changes and strategic management decisions are driving adaptations in manufacturing routines. Based on the theory of situational strength, we investigated how contextual and person-related factors influence workers’ adaptation in a two-worker position routine. Contextual factors, like retrieval cues (Study 1), time pressure (Study 2), and convenience (Study 3), were varied. Person-related factors included retentivity, general and routine-specific self-efficacy, and perceived adaptation costs. Dependent variables included various error types and production time before and after adaptation. In each study, 148 participants were trained in a production routine at t1 and executed an adapted routine at t2, one week later. Repeated measures ANOVA for performance at t1 and t2, and MANOVA for performance at t2, revealed that time increased for all groups at t2. For participants in Studies 1 & 2, error rates remained consistent. Retentivity significantly impacted errors at both t1 and t2, emphasising that routine changes in a ‘running business’ take time, regardless of contextual factors. Workers with lower retentivity may require additional support.
The Circular Economy (CE) - based on five principles (reduce, reuse, refurbish, repair, and recycle) - has received increased attention in both academia and practice in recent years. The transition to CE by public and private organizations can be seen as an entrepreneurial act encompassing their strategic policies, business models, structures, and processes. Little is known about the involvement of employees of organizations making this transition. Therefore, this study investigates the influence of organizations’ commitment to the five CE principles on their employees’ perceptions of the usefulness, ease of implementation, and acceptability of the principles. The method used is exploratory, a mixed-method approach combining PLS-SEM and fsQCA. This research contributes to the field by developing a unified theoretical perspective on the entrepreneurial context. It also highlights the impact of CE principles on organizations that are transitioning to more sustainable development.