TY - GEN A1 - Ritterbusch, Georg David A1 - Teichmann, Malte Rolf T1 - Defining the metaverse BT - A systematic literature review T2 - Zweitveröffentlichungen der Universität Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe N2 - The term Metaverse is emerging as a result of the late push by multinational technology conglomerates and a recent surge of interest in Web 3.0, Blockchain, NFT, and Cryptocurrencies. From a scientific point of view, there is no definite consensus on what the Metaverse will be like. This paper collects, analyzes, and synthesizes scientific definitions and the accompanying major characteristics of the Metaverse using the methodology of a Systematic Literature Review (SLR). Two revised definitions for the Metaverse are presented, both condensing the key attributes, where the first one is rather simplistic holistic describing “a three-dimensional online environment in which users represented by avatars interact with each other in virtual spaces decoupled from the real physical world”. In contrast, the second definition is specified in a more detailed manner in the paper and further discussed. These comprehensive definitions offer specialized and general scholars an application within and beyond the scientific context of the system science, information system science, computer science, and business informatics, by also introducing open research challenges. Furthermore, an outlook on the social, economic, and technical implications is given, and the preconditions that are necessary for a successful implementation are discussed. T3 - Zweitveröffentlichungen der Universität Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe - 159 KW - Metaverse KW - Systematics KW - Bibliometrics KW - Augmented reality KW - Taxonomy KW - Semantic Web KW - Second Life KW - Blockchains KW - Economics Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-588799 SN - 1867-5808 IS - 159 SP - 12368 EP - 12377 ER - TY - JOUR A1 - Ritterbusch, Georg David A1 - Teichmann, Malte Rolf T1 - Defining the metaverse BT - A systematic literature review JF - IEEE Access N2 - The term Metaverse is emerging as a result of the late push by multinational technology conglomerates and a recent surge of interest in Web 3.0, Blockchain, NFT, and Cryptocurrencies. From a scientific point of view, there is no definite consensus on what the Metaverse will be like. This paper collects, analyzes, and synthesizes scientific definitions and the accompanying major characteristics of the Metaverse using the methodology of a Systematic Literature Review (SLR). Two revised definitions for the Metaverse are presented, both condensing the key attributes, where the first one is rather simplistic holistic describing “a three-dimensional online environment in which users represented by avatars interact with each other in virtual spaces decoupled from the real physical world”. In contrast, the second definition is specified in a more detailed manner in the paper and further discussed. These comprehensive definitions offer specialized and general scholars an application within and beyond the scientific context of the system science, information system science, computer science, and business informatics, by also introducing open research challenges. Furthermore, an outlook on the social, economic, and technical implications is given, and the preconditions that are necessary for a successful implementation are discussed. KW - Metaverse KW - Systematics KW - Bibliometrics KW - Augmented reality KW - Taxonomy KW - Semantic Web KW - Second Life KW - Blockchains KW - Economics Y1 - 2023 U6 - https://doi.org/10.1109/ACCESS.2023.3241809 SN - 2169-3536 VL - 11 SP - 12368 EP - 12377 PB - Institute of Electrical and Electronics Engineers CY - New York, NY ER - TY - THES A1 - Böken, Björn T1 - Improving prediction accuracy using dynamic information N2 - Accurately solving classification problems nowadays is likely to be the most relevant machine learning task. Binary classification separating two classes only is algorithmically simpler but has fewer potential applications as many real-world problems are multi-class. On the reverse, separating only a subset of classes simplifies the classification task. Even though existing multi-class machine learning algorithms are very flexible regarding the number of classes, they assume that the target set Y is fixed and cannot be restricted once the training is finished. On the other hand, existing state-of-the-art production environments are becoming increasingly interconnected with the advance of Industry 4.0 and related technologies such that additional information can simplify the respective classification problems. In light of this, the main aim of this thesis is to introduce dynamic classification that generalizes multi-class classification such that the target class set can be restricted arbitrarily to a non-empty class subset M of Y at any time between two consecutive predictions. This task is solved by a combination of two algorithmic approaches. First, classifier calibration, which transforms predictions into posterior probability estimates that are intended to be well calibrated. The analysis provided focuses on monotonic calibration and in particular corrects wrong statements that appeared in the literature. It also reveals that bin-based evaluation metrics, which became popular in recent years, are unjustified and should not be used at all. Next, the validity of Platt scaling, which is the most relevant parametric calibration approach, is analyzed in depth. In particular, its optimality for classifier predictions distributed according to four different families of probability distributions as well its equivalence with Beta calibration up to a sigmoidal preprocessing are proven. For non-monotonic calibration, extended variants on kernel density estimation and the ensemble method EKDE are introduced. Finally, the calibration techniques are evaluated using a simulation study with complete information as well as on a selection of 46 real-world data sets. Building on this, classifier calibration is applied as part of decomposition-based classification that aims to reduce multi-class problems to simpler (usually binary) prediction tasks. For the involved fusing step performed at prediction time, a new approach based on evidence theory is presented that uses classifier calibration to model mass functions. This allows the analysis of decomposition-based classification against a strictly formal background and to prove closed-form equations for the overall combinations. Furthermore, the same formalism leads to a consistent integration of dynamic class information, yielding a theoretically justified and computationally tractable dynamic classification model. The insights gained from this modeling are combined with pairwise coupling, which is one of the most relevant reduction-based classification approaches, such that all individual predictions are combined with a weight. This not only generalizes existing works on pairwise coupling but also enables the integration of dynamic class information. Lastly, a thorough empirical study is performed that compares all newly introduced approaches to existing state-of-the-art techniques. For this, evaluation metrics for dynamic classification are introduced that depend on corresponding sampling strategies. Thereafter, these are applied during a three-part evaluation. First, support vector machines and random forests are applied on 26 data sets from the UCI Machine Learning Repository. Second, two state-of-the-art deep neural networks are evaluated on five benchmark data sets from a relatively recent reference work. Here, computationally feasible strategies to apply the presented algorithms in combination with large-scale models are particularly relevant because a naive application is computationally intractable. Finally, reference data from a real-world process allowing the inclusion of dynamic class information are collected and evaluated. The results show that in combination with support vector machines and random forests, pairwise coupling approaches yield the best results, while in combination with deep neural networks, differences between the different approaches are mostly small to negligible. Most importantly, all results empirically confirm that dynamic classification succeeds in improving the respective prediction accuracies. Therefore, it is crucial to pass dynamic class information in respective applications, which requires an appropriate digital infrastructure. N2 - Klassifikationsprobleme akkurat zu lösen ist heutzutage wahrscheinlich die relevanteste Machine-Learning-Aufgabe. Binäre Klassifikation zur Unterscheidung von nur zwei Klassen ist algorithmisch einfacher, hat aber weniger potenzielle Anwendungen, da in der Praxis oft Mehrklassenprobleme auftreten. Demgegenüber vereinfacht die Unterscheidung nur innerhalb einer Untermenge von Klassen die Problemstellung. Obwohl viele existierende Machine-Learning-Algorithmen sehr flexibel mit Blick auf die Anzahl der Klassen sind, setzen sie voraus, dass die Zielmenge Y fest ist und nicht mehr eingeschränkt werden kann, sobald das Training abgeschlossen ist. Allerdings sind moderne Produktionsumgebungen mit dem Voranschreiten von Industrie 4.0 und entsprechenden Technologien zunehmend digital verbunden, sodass zusätzliche Informationen die entsprechenden Klassifikationsprobleme vereinfachen können. Vor diesem Hintergrund ist das Hauptziel dieser Arbeit, dynamische Klassifikation als Verallgemeinerung von Mehrklassen-Klassifikation einzuführen, bei der die Zielmenge jederzeit zwischen zwei aufeinanderfolgenden Vorhersagen zu einer beliebigen, nicht leeren Teilmenge eingeschränkt werden kann. Diese Aufgabe wird durch die Kombination von zwei algorithmischen Ansätzen gelöst. Zunächst wird Klassifikator-Kalibrierung eingesetzt, mittels der Vorhersagen in Schätzungen der A-Posteriori-Wahrscheinlichkeiten transformiert werden, die gut kalibriert sein sollen. Die durchgeführte Analyse zielt auf monotone Kalibrierung ab und korrigiert insbesondere Falschaussagen, die in Referenzarbeiten veröffentlicht wurden. Außerdem zeigt sie, dass Bin-basierte Fehlermaße, die in den letzten Jahren populär geworden sind, ungerechtfertigt sind und nicht verwendet werden sollten. Weiterhin wird die Validität von Platt Scaling, dem relevantesten, parametrischen Kalibrierungsverfahren, genau analysiert. Insbesondere wird seine Optimalität für Klassifikatorvorhersagen, die gemäß vier Familien von Verteilungsfunktionen verteilt sind, sowie die Äquivalenz zu Beta-Kalibrierung bis auf eine sigmoidale Vorverarbeitung gezeigt. Für nicht monotone Kalibrierung werden erweiterte Varianten der Kerndichteschätzung und die Ensemblemethode EKDE eingeführt. Schließlich werden die Kalibrierungsverfahren im Rahmen einer Simulationsstudie mit vollständiger Information sowie auf 46 Referenzdatensätzen ausgewertet. Hierauf aufbauend wird Klassifikator-Kalibrierung als Teil von reduktionsbasierter Klassifikation eingesetzt, die zum Ziel hat, Mehrklassenprobleme auf einfachere (üblicherweise binäre) Entscheidungsprobleme zu reduzieren. Für den zugehörigen, während der Vorhersage notwendigen Fusionsschritt wird ein neuer, auf Evidenztheorie basierender Ansatz eingeführt, der Klassifikator-Kalibrierung zur Modellierung von Massefunktionen nutzt. Dies ermöglicht die Analyse von reduktionsbasierter Klassifikation in einem formalen Kontext sowie geschlossene Ausdrücke für die entsprechenden Gesamtkombinationen zu beweisen. Zusätzlich führt derselbe Formalismus zu einer konsistenten Integration von dynamischen Klasseninformationen, sodass sich ein theoretisch fundiertes und effizient zu berechnendes, dynamisches Klassifikationsmodell ergibt. Die hierbei gewonnenen Einsichten werden mit Pairwise Coupling, einem der relevantesten Verfahren für reduktionsbasierte Klassifikation, verbunden, wobei alle individuellen Vorhersagen mit einer Gewichtung kombiniert werden. Dies verallgemeinert nicht nur existierende Ansätze für Pairwise Coupling, sondern führt darüber hinaus auch zu einer Integration von dynamischen Klasseninformationen. Abschließend wird eine umfangreiche empirische Studie durchgeführt, die alle neu eingeführten Verfahren mit denen aus dem Stand der Forschung vergleicht. Hierfür werden Bewertungsfunktionen für dynamische Klassifikation eingeführt, die auf Sampling-Strategien basieren. Anschließend werden diese im Rahmen einer dreiteiligen Studie angewendet. Zunächst werden Support Vector Machines und Random Forests auf 26 Referenzdatensätzen aus dem UCI Machine Learning Repository angewendet. Im zweiten Teil werden zwei moderne, tiefe neuronale Netze auf fünf Referenzdatensätzen aus einer relativ aktuellen Referenzarbeit ausgewertet. Hierbei sind insbesondere Strategien relevant, die die Anwendung der eingeführten Verfahren in Verbindung mit großen Modellen ermöglicht, da eine naive Vorgehensweise nicht durchführbar ist. Schließlich wird ein Referenzdatensatz aus einem Produktionsprozess gewonnen, der die Integration von dynamischen Klasseninformationen ermöglicht, und ausgewertet. Die Ergebnisse zeigen, dass Pairwise-Coupling-Verfahren in Verbindung mit Support Vector Machines und Random Forests die besten Ergebnisse liefern, während in Verbindung mit tiefen neuronalen Netzen die Unterschiede zwischen den Verfahren oft klein bis vernachlässigbar sind. Am wichtigsten ist, dass alle Ergebnisse zeigen, dass dynamische Klassifikation die entsprechenden Erkennungsgenauigkeiten verbessert. Daher ist es entscheidend, dynamische Klasseninformationen in den entsprechenden Anwendungen zur Verfügung zu stellen, was eine entsprechende digitale Infrastruktur erfordert. KW - dynamic classification KW - multi-class classification KW - classifier calibration KW - evidence theory KW - Dempster–Shafer theory KW - Deep Learning KW - Deep Learning KW - Dempster-Shafer-Theorie KW - Klassifikator-Kalibrierung KW - dynamische Klassifikation KW - Evidenztheorie KW - Mehrklassen-Klassifikation Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-585125 ER - TY - JOUR A1 - Krause, Hannes-Vincent A1 - Große Deters, Fenne A1 - Baumann, Annika A1 - Krasnova, Hanna T1 - Active social media use and its impact on well-being BT - an experimental study on the effects of posting pictures on Instagram JF - Journal of computer-mediated communication : a journal of the International Communication Association N2 - Active use of social networking sites (SNSs) has long been assumed to benefit users' well-being. However, this established hypothesis is increasingly being challenged, with scholars criticizing its lack of empirical support and the imprecise conceptualization of active use. Nevertheless, with considerable heterogeneity among existing studies on the hypothesis and causal evidence still limited, a final verdict on its robustness is still pending. To contribute to this ongoing debate, we conducted a week-long randomized control trial with N = 381 adult Instagram users recruited via Prolific. Specifically, we tested how active SNS use, operationalized as picture postings on Instagram, affects different dimensions of well-being. The results depicted a positive effect on users' positive affect but null findings for other well-being outcomes. The findings broadly align with the recent criticism against the active use hypothesis and support the call for a more nuanced view on the impact of SNSs.
Lay Summary Active use of social networking sites (SNSs) has long been assumed to benefit users' well-being. However, this established assumption is increasingly being challenged, with scholars criticizing its lack of empirical support and the imprecise conceptualization of active use. Nevertheless, with great diversity among conducted studies on the hypothesis and a lack of causal evidence, a final verdict on its viability is still pending. To contribute to this ongoing debate, we conducted a week-long experimental investigation with 381 adult Instagram users. Specifically, we tested how posting pictures on Instagram affects different aspects of well-being. The results of this study depicted a positive effect of posting Instagram pictures on users' experienced positive emotions but no effects on other aspects of well-being. The findings broadly align with the recent criticism against the active use hypothesis and support the call for a more nuanced view on the impact of SNSs on users. KW - social networking sites KW - social media KW - Instagram KW - well-being KW - experiment KW - randomized control trial Y1 - 2022 U6 - https://doi.org/10.1093/jcmc/zmac037 SN - 1083-6101 VL - 28 IS - 1 PB - Oxford Univ. Press CY - Oxford ER - TY - GEN A1 - Ullrich, André A1 - Vladova, Gergana A1 - Eigelshoven, Felix A1 - Renz, André T1 - Data mining of scientific research on artificial intelligence in teaching and administration in higher education institutions BT - a bibliometrics analysis and recommendation for future research T2 - Zweitveröffentlichungen der Universität Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe N2 - Teaching and learning as well as administrative processes are still experiencing intensive changes with the rise of artificial intelligence (AI) technologies and its diverse application opportunities in the context of higher education. Therewith, the scientific interest in the topic in general, but also specific focal points rose as well. However, there is no structured overview on AI in teaching and administration processes in higher education institutions that allows to identify major research topics and trends, and concretizing peculiarities and develops recommendations for further action. To overcome this gap, this study seeks to systematize the current scientific discourse on AI in teaching and administration in higher education institutions. This study identified an (1) imbalance in research on AI in educational and administrative contexts, (2) an imbalance in disciplines and lack of interdisciplinary research, (3) inequalities in cross-national research activities, as well as (4) neglected research topics and paths. In this way, a comparative analysis between AI usage in administration and teaching and learning processes, a systematization of the state of research, an identification of research gaps as well as further research path on AI in higher education institutions are contributed to research. T3 - Zweitveröffentlichungen der Universität Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe - 160 Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-589077 SN - 1867-5808 IS - 160 ER - TY - JOUR A1 - Ullrich, André A1 - Vladova, Gergana A1 - Eigelshoven, Felix A1 - Renz, André T1 - Data mining of scientific research on artificial intelligence in teaching and administration in higher education institutions BT - a bibliometrics analysis and recommendation for future research JF - Discover artificial intelligence N2 - Teaching and learning as well as administrative processes are still experiencing intensive changes with the rise of artificial intelligence (AI) technologies and its diverse application opportunities in the context of higher education. Therewith, the scientific interest in the topic in general, but also specific focal points rose as well. However, there is no structured overview on AI in teaching and administration processes in higher education institutions that allows to identify major research topics and trends, and concretizing peculiarities and develops recommendations for further action. To overcome this gap, this study seeks to systematize the current scientific discourse on AI in teaching and administration in higher education institutions. This study identified an (1) imbalance in research on AI in educational and administrative contexts, (2) an imbalance in disciplines and lack of interdisciplinary research, (3) inequalities in cross-national research activities, as well as (4) neglected research topics and paths. In this way, a comparative analysis between AI usage in administration and teaching and learning processes, a systematization of the state of research, an identification of research gaps as well as further research path on AI in higher education institutions are contributed to research. Y1 - 2022 U6 - https://doi.org/10.1007/s44163-022-00031-7 SN - 2731-0809 VL - 2 PB - Springer CY - Cham ER - TY - THES A1 - Dehnert, Maik T1 - Studies on the Digital Transformation of Incumbent Organizations T1 - Studien zur Digitalen Transformation traditioneller Organisationen BT - Causes, Effects and Solutions for Banking BT - Ursachen, Wirkungen und Lösungen für das Bankwesen N2 - Traditional organizations are strongly encouraged by emerging digital customer behavior and digital competition to transform their businesses for the digital age. Incumbents are particularly exposed to the field of tension between maintaining and renewing their business model. Banking is one of the industries most affected by digitalization, with a large stream of digital innovations around Fintech. Most research contributions focus on digital innovations, such as Fintech, but there are only a few studies on the related challenges and perspectives of incumbent organizations, such as traditional banks. Against this background, this dissertation examines the specific causes, effects and solutions for traditional banks in digital transformation − an underrepresented research area so far. The first part of the thesis examines how digitalization has changed the latent customer expectations in banking and studies the underlying technological drivers of evolving business-to-consumer (B2C) business models. Online consumer reviews are systematized to identify latent concepts of customer behavior and future decision paths as strategic digitalization effects. Furthermore, the service attribute preferences, the impact of influencing factors and the underlying customer segments are uncovered for checking accounts in a discrete choice experiment. The dissertation contributes here to customer behavior research in digital transformation, moving beyond the technology acceptance model. In addition, the dissertation systematizes value proposition types in the evolving discourse around smart products and services as key drivers of business models and market power in the platform economy. The second part of the thesis focuses on the effects of digital transformation on the strategy development of financial service providers, which are classified along with their firm performance levels. Standard types are derived based on fuzzy-set qualitative comparative analysis (fsQCA), with facade digitalization as one typical standard type for low performing incumbent banks that lack a holistic strategic response to digital transformation. Based on this, the contradictory impact of digitalization measures on key business figures is examined for German savings banks, confirming that the shift towards digital customer interaction was not accompanied by new revenue models diminishing bank profitability. The dissertation further contributes to the discourse on digitalized work designs and the consequences for job perceptions in banking customer advisory. The threefold impact of the IT support perceived in customer interaction on the job satisfaction of customer advisors is disentangled. In the third part of the dissertation, solutions are developed design-oriented for core action areas of digitalized business models, i.e., data and platforms. A consolidated taxonomy for data-driven business models and a future reference model for digital banking have been developed. The impact of the platform economy is demonstrated here using the example of the market entry by Bigtech. The role-based e3-value modeling is extended by meta-roles and role segments and linked to value co-creation mapping in VDML. In this way, the dissertation extends enterprise modeling research on platform ecosystems and value co-creation using the example of banking. N2 - Traditionelle Unternehmen sehen sich angesichts des zunehmend digitalen Kundenverhaltens und gesteigerten digitalen Wettbewerbs damit konfrontiert, ihr Geschäftsmodell adäquat für das digitale Zeitalter weiterzuentwickeln. Insbesondere etablierte Unternehmen befinden sich dabei in einem Spannungsfeld aus Bewahrung und Erneuerung. Der Großteil jüngerer Forschungsbeiträge zum Bankwesen fokussiert sich auf digitale Fintech-Innovationen, nur wenige Studien befassen sich mit Herausforderungen und Perspektiven traditioneller Banken. Vor diesem Hintergrund untersucht die Dissertation die Ursachen und Wirkungen der Digitalen Transformation im Bankwesen und zeigt Lösungswege für traditionelle Banken auf. Der erste Teil der Dissertation untersucht die Ursachen der Digitalen Transformation im Banking. Neuartige Einflussfaktoren und Entscheidungspfade im Kundenverhalten werden als strategische Digitalisierungstreiber für Banken identifiziert. Darauf aufbauend werden in einem Discrete-Choice-Experiment die Präferenzen deutscher Bankkunden hinsichtlich digitaler und nicht-digitaler Dienstleistungsattribute am Beispiel von Girokonten untersucht. Die Arbeit leistet einen über das Technologieakzeptanzmodell hinausgehenden Beitrag zur Erforschung des Kundenverhaltens in der Digitalen Transformation. Ein weiterer Forschungsbeitrag systematisiert anschließend wesentliche Charakteristika smarter Produkte und Dienstleistungen als Treiber von Geschäftsmodellen und Marktmacht in der Plattformökonomie. Der zweite Teil der Arbeit befasst sich zunächst mit den Auswirkungen der Digitalen Transformation auf die Strategieentwicklung von traditionellen Finanzdienstleistern, die mittels Fallstudien entlang ihres Finanzerfolgs typologisiert werden. Die Fassadendigitalisierung wird als Standardtyp traditioneller Anbieter systematisiert, die zwar zunehmend auf digitale Kundeninteraktion setzen, aber die Geschäftsmodelldimension der Digitalen Transformation vernachlässigen. Darauf aufbauend werden in Panelregressionsanalysen die Auswirkungen der Digitalisierung auf deutsche Sparkassen auf betriebswirtschaftliche Kennzahlen untersucht. Eine weitere quantitative Studie untersucht die Wirkungen neuartiger IT-Beratungswerkzeuge auf die Arbeitszufriedenheit von Bankkundenberatern. Die Dissertation leistet hiermit einen Beitrag zur Transformationsforschung in den Bereichen Bankstrategie und Arbeitsprozesse. Im dritten Teil der Dissertation werden gestaltungsorientiert Lösungsartefakte für die zentralen Handlungsfelder digitalisierter Geschäftsmodelle - Daten und Plattformen - entwickelt. Dies schließt einerseits eine konsolidierte Taxonomie für datengetriebene Geschäftsmodelle und andererseits ein Referenzmodell für zukünftige plattformbasierte Bankenökosysteme ein. Die rollenbasierte Referenzmodellierungsmethodik e3-value wird um Meta-Rollen und Rollensegmente erweitert, um die die strategischen Auswirkungen plattformbasierter Geschäftsmodelle aufzuzeigen. Hiermit erweitert die Dissertation die Unternehmensmodellierungsforschung im Bereich digitaler Plattform-Ökosysteme am Beispiel des Bankwesens. KW - digital transformation KW - digitalization KW - digital strategy KW - consumer behavior KW - platform ecosystems KW - value co-creation KW - Fintech KW - incumbent KW - bank KW - Digitale Transformation KW - Digitalisierung KW - Digitalstrategie KW - Kundenverhalten KW - Plattform-Ökosysteme KW - Wertschöpfungskooperation KW - Fintech KW - traditionelle Unternehmen KW - Bank Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-548324 ER - TY - CHAP A1 - Krasnova, Hanna A1 - Gundlach, Jana A1 - Baumann, Annika T1 - Coming back for more BT - the effect of news feed serendipity on social networking site sage T2 - PACIS 2022 proceedings N2 - Recent spikes in social networking site (SNS) usage times have launched investigations into reasons for excessive SNS usage. Extending research on social factors (i.e., fear of missing out), this study considers the News Feed setup. More specifically, we suggest that the order of the News Feed (chronological vs. algorithmically assembled posts) affects usage behaviors. Against the background of the variable reward schedule, this study hypothesizes that the different orders exert serendipity differently. Serendipity, termed as unexpected lucky encounters with information, resembles variable rewards. Studies have evidenced a relation between variable rewards and excessive behaviors. Similarly, we hypothesize that order-induced serendipitous encounters affect SNS usage times and explore this link in a two-wave survey with an experimental setup (users using either chronological or algorithmic News Feeds). While theoretically extending explanations for increased SNS usage times by considering the News Feed order, practically the study will offer recommendations for relevant stakeholders. Y1 - 2022 UR - https://aisel.aisnet.org/pacis2022/271 SN - 9781958200018 PB - AIS Electronic Library (AISeL) CY - [Erscheinungsort nicht ermittelbar] ER - TY - JOUR A1 - Spiekermann, Sarah A1 - Krasnova, Hanna A1 - Hinz, Oliver A1 - Baumann, Annika A1 - Benlian, Alexander A1 - Gimpel, Henner A1 - Heimbach, Irina A1 - Koester, Antonia A1 - Maedche, Alexander A1 - Niehaves, Bjoern A1 - Risius, Marten A1 - Trenz, Manuel T1 - Values and ethics in information systems BT - a state-of-the-art analysis and avenues for future research JF - Business & information systems engineering Y1 - 2022 U6 - https://doi.org/10.1007/s12599-021-00734-8 SN - 2363-7005 SN - 1867-0202 VL - 64 IS - 2 SP - 247 EP - 264 PB - Springer Gabler CY - Wiesbaden ER - TY - GEN A1 - Benlian, Alexander A1 - Wiener, Martin A1 - Cram, W. Alec A1 - Krasnova, Hanna A1 - Maedche, Alexander A1 - Mohlmann, Mareike A1 - Recker, Jan A1 - Remus, Ulrich T1 - Algorithmic management BT - Bright and dark sides, practical implications, and research opportunities T2 - Zweitveröffentlichungen der Universität Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe T3 - Zweitveröffentlichungen der Universität Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe - 174 Y1 - 0202 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-607112 SN - 2363-7005 SN - 1867-0202 SN - 1867-5808 IS - 6 ER - TY - JOUR A1 - Benlian, Alexander A1 - Wiener, Martin A1 - Cram, W. Alec A1 - Krasnova, Hanna A1 - Maedche, Alexander A1 - Mohlmann, Mareike A1 - Recker, Jan A1 - Remus, Ulrich T1 - Algorithmic management BT - bright and dark sides, practical implications, and research opportunities JF - Business and information systems engineering Y1 - 2022 U6 - https://doi.org/10.1007/s12599-022-00764-w SN - 2363-7005 SN - 1867-0202 VL - 64 IS - 6 SP - 825 EP - 839 PB - Springer Gabler CY - Wiesbaden ER - TY - JOUR A1 - Pawassar, Christian Matthias A1 - Tiberius, Victor T1 - Virtual reality in health care BT - Bibliometric analysis JF - JMIR Serious Games N2 - Background: Research into the application of virtual reality technology in the health care sector has rapidly increased, resulting in a large body of research that is difficult to keep up with. Objective: We will provide an overview of the annual publication numbers in this field and the most productive and influential countries, journals, and authors, as well as the most used, most co-occurring, and most recent keywords. Methods: Based on a data set of 356 publications and 20,363 citations derived from Web of Science, we conducted a bibliometric analysis using BibExcel, HistCite, and VOSviewer. Results: The strongest growth in publications occurred in 2020, accounting for 29.49% of all publications so far. The most productive countries are the United States, the United Kingdom, and Spain; the most influential countries are the United States, Canada, and the United Kingdom. The most productive journals are the Journal of Medical Internet Research (JMIR), JMIR Serious Games, and the Games for Health Journal; the most influential journals are Patient Education and Counselling, Medical Education, and Quality of Life Research. The most productive authors are Riva, del Piccolo, and Schwebel; the most influential authors are Finset, del Piccolo, and Eide. The most frequently occurring keywords other than “virtual” and “reality” are “training,” “trial,” and “patients.” The most relevant research themes are communication, education, and novel treatments; the most recent research trends are fitness and exergames. Conclusions: The analysis shows that the field has left its infant state and its specialization is advancing, with a clear focus on patient usability. KW - virtual reality KW - healthcare KW - bibliometric analysis KW - literature review KW - citation analysis KW - VR KW - usability KW - review KW - health care Y1 - 2021 U6 - https://doi.org/10.2196/32721 SN - 2291-9279 VL - 9 SP - 1 EP - 19 PB - JMIR Publications CY - Toronto, Kanada ET - 4 ER - TY - CHAP A1 - Abramova, Olga A1 - Gladkaya, Margarita A1 - Krasnova, Hanna T1 - An unusual encounter with oneself BT - exploring the impact of self-view on online meeting outcomes T2 - ICIS 2021: IS and the future of work N2 - Helping overcome distance, the use of videoconferencing tools has surged during the pandemic. To shed light on the consequences of videoconferencing at work, this study takes a granular look at the implications of the self-view feature for meeting outcomes. Building on self-awareness research and self-regulation theory, we argue that by heightening the state of self-awareness, self-view engagement depletes participants’ mental resources and thereby can undermine online meeting outcomes. Evaluation of our theoretical model on a sample of 179 employees reveals a nuanced picture. Self-view engagement while speaking and while listening is positively associated with self-awareness, which, in turn, is negatively associated with satisfaction with meeting process, perceived productivity, and meeting enjoyment. The criticality of the communication role is put forward: looking at self while listening to other attendees has a negative direct and indirect effect on meeting outcomes; however, looking at self while speaking produces equivocal effects. Y1 - 2021 UR - https://aisel.aisnet.org/icis2021/is_future_work/is_future_work/16 PB - AIS Electronic Library (AISeL) CY - [Erscheinungsort nicht ermittelbar] ER - TY - GEN A1 - Studen, Laura A1 - Tiberius, Victor T1 - Social Media, Quo Vadis? BT - Prospective Development and Implications T2 - Postprints der Universität Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe N2 - Over the past two decades, social media have become a crucial and omnipresent cultural and economic phenomenon, which has seen platforms come and go and advance technologically. In this study, we explore the further development of social media regarding interactive technologies, platform development, relationships to news media, the activities of institutional and organizational users, and effects of social media on the individual and the society over the next five to ten years by conducting an international, two-stage Delphi study. Our results show that enhanced interaction on platforms, including virtual and augmented reality, somatosensory sense, and touch- and movement-based navigation are expected. AIs will interact with other social media users. Inactive user profiles will outnumber active ones. Platform providers will diversify into the WWW, e-commerce, edu-tech, fintechs, the automobile industry, and HR. They will change to a freemium business model and put more effort into combating cybercrime. Social media will become the predominant news distributor, but fake news will still be problematic. Firms will spend greater amounts of their budgets on social media advertising, and schools, politicians, and the medical sector will increase their social media engagement. Social media use will increasingly lead to individuals’ psychic issues. Society will benefit from economic growth and new jobs, increased political interest, democratic progress, and education due to social media. However, censorship and the energy consumption of platform operators might rise. T3 - Zweitveröffentlichungen der Universität Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe - 131 KW - Delphi study KW - individual effects KW - interactive technologies KW - news media KW - social media KW - societal effects Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-482934 SN - 1867-5808 IS - 131 ER - TY - JOUR A1 - Studen, Laura A1 - Tiberius, Victor T1 - Social Media, Quo Vadis? BT - Prospective Development and Implications JF - Future Internet N2 - Over the past two decades, social media have become a crucial and omnipresent cultural and economic phenomenon, which has seen platforms come and go and advance technologically. In this study, we explore the further development of social media regarding interactive technologies, platform development, relationships to news media, the activities of institutional and organizational users, and effects of social media on the individual and the society over the next five to ten years by conducting an international, two-stage Delphi study. Our results show that enhanced interaction on platforms, including virtual and augmented reality, somatosensory sense, and touch- and movement-based navigation are expected. AIs will interact with other social media users. Inactive user profiles will outnumber active ones. Platform providers will diversify into the WWW, e-commerce, edu-tech, fintechs, the automobile industry, and HR. They will change to a freemium business model and put more effort into combating cybercrime. Social media will become the predominant news distributor, but fake news will still be problematic. Firms will spend greater amounts of their budgets on social media advertising, and schools, politicians, and the medical sector will increase their social media engagement. Social media use will increasingly lead to individuals’ psychic issues. Society will benefit from economic growth and new jobs, increased political interest, democratic progress, and education due to social media. However, censorship and the energy consumption of platform operators might rise. KW - Delphi study KW - individual effects KW - interactive technologies KW - news media KW - social media KW - societal effects Y1 - 2020 U6 - https://doi.org/10.3390/fi12090146 SN - 1999-5903 VL - 12 IS - 9 PB - MDPI CY - Basel ER - TY - GEN A1 - Weber, Edzard A1 - Tiefenbacher, Anselm A1 - Gronau, Norbert T1 - Need for standardization and systematization of test data for job-shop scheduling T2 - Postprints der Universität Potsdam Wirtschafts- und Sozialwissenschaftliche Reihe N2 - The development of new and better optimization and approximation methods for Job Shop Scheduling Problems (JSP) uses simulations to compare their performance. The test data required for this has an uncertain influence on the simulation results, because the feasable search space can be changed drastically by small variations of the initial problem model. Methods could benefit from this to varying degrees. This speaks in favor of defining standardized and reusable test data for JSP problem classes, which in turn requires a systematic describability of the test data in order to be able to compile problem adequate data sets. This article looks at the test data used for comparing methods by literature review. It also shows how and why the differences in test data have to be taken into account. From this, corresponding challenges are derived which the management of test data must face in the context of JSP research. Keywords T3 - Zweitveröffentlichungen der Universität Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe - 134 KW - job shop scheduling KW - JSP KW - social network analysis KW - method comparision Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-472229 SN - 1867-5808 IS - 134 ER - TY - JOUR A1 - Weber, Edzard A1 - Tiefenbacher, Anselm A1 - Gronau, Norbert T1 - Need for Standardization and Systematization of Test Data for Job-Shop Scheduling JF - Data N2 - The development of new and better optimization and approximation methods for Job Shop Scheduling Problems (JSP) uses simulations to compare their performance. The test data required for this has an uncertain influence on the simulation results, because the feasable search space can be changed drastically by small variations of the initial problem model. Methods could benefit from this to varying degrees. This speaks in favor of defining standardized and reusable test data for JSP problem classes, which in turn requires a systematic describability of the test data in order to be able to compile problem adequate data sets. This article looks at the test data used for comparing methods by literature review. It also shows how and why the differences in test data have to be taken into account. From this, corresponding challenges are derived which the management of test data must face in the context of JSP research. KW - job shop scheduling KW - JSP KW - social network analysis KW - method comparision Y1 - 2019 U6 - https://doi.org/10.3390/data4010032 SN - 2306-5729 VL - 4 IS - 1 PB - MDPI CY - Basel ER - TY - THES A1 - Weber, Edzard T1 - Erarbeitung einer Methodik der Wandlungsfähigkeit Y1 - 2015 ER - TY - GEN A1 - Stieglitz, Stefan A1 - Fuchß, Christoph A1 - Hillmann, Oliver A1 - Lattemann, Christoph T1 - Mobile learning by using ad hoc messaging network N2 - The requirements of modern e-learning techniques change. Aspects such as community interaction, flexibility, pervasive learning and increasing mobility in communication habits become more important. To meet these challenges e-learning platforms must provide support on mobile learning. Most approaches try to adopt centralised and static e-learning mechanisms to mobile devices. However, often technically it is not possible for all kinds of devices to be connected to a central server. Therefore we introduce an application of a mobile e-learning network which operates totally decentralised with the help of an underlying ad hoc network architecture. Furthermore the concept of ad hoc messaging network (AMNET) is used as basis system architecture for our approach to implement a platform for pervasive mobile e-learning. T3 - Zweitveröffentlichungen der Universität Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe - paper 015 KW - Mobile learning KW - ad hoc learning KW - community KW - e-learning platform KW - AMNET KW - ad hoc messaging network KW - pervasive learning Y1 - 2007 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-19960 SN - 1867-5808 ER -