10 Fakultät Wirtschafts- und Sozialwissenschaften
Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/11
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Item Open Access Innovationstrends bei Cloud-Services : Analyse der internationalen Patentaktivitäten(2023) Fritz, Theresa; Saiger, Daniel; Burr, WolfgangDer Einsatz von Cloud-Computing bietet Unternehmen durch die Virtualisierung von Rechenressourcen in Verbindung mit dem Zugriff über das Internet eine Vielzahl neuer Möglichkeiten. Innovative digitale Dienstleistungen können in Form von Cloud-Services genutzt und angeboten werden. Infolge wurden die Entwicklung von Cloud-Diensten in den letzten Jahren stark vorangetrieben und eine Vielzahl von Patenten angemeldet. Neben dem Schutz vor Nachahmung dienen Patente auch als Informationsquelle für technisches Wissen sowie zur Identifikation und Früherkennung von Trends. Für die Analyse der geografischen Innovationstrends im Bereich Cloud-Services werden demzufolge Patentdaten herangezogen und die Patentaktivitäten der Länder näher untersucht. Die Verwendung von Patentdaten als Indikator für Innovationsaktivitäten zeigt, dass auf geografischer Ebene neben den USA die asiatischen Länder, hier insbesondere China, als Innovationstreiber einzustufen sind. China weist dabei aufgrund staatlicher Anreize die höchste Patentaktivität auf. Die asiatischen Länder, insbesondere China, sind somit neben den USA als Innovationstreiber im Bereich Cloud-Services zu identifizieren.Item Open Access Who captures value from hackathons? : innovation contests with collective intelligence tools bridging creativity and coupled open innovation(2023) Attalah, Issam; Nylund, Petra A.; Brem, AlexanderBalancing value creation and value capture is a fundamental strategic issue for the management of open innovation. Insufficient compensation for created value may hinder the participation of a firm or individual in open innovation. It can thus provide an obstacle to the open innovation process as a whole. Hackathons provide an attractive setting for studying value appropriation in open innovation by actors of different types and with varying bargaining power. We define hackathons as idea competitions on specific topics in the form of a time‐limited event. These competitions have gained more popularity throughout the years and have recently become more prominent. Therefore, an abductive empirical study was carried out in an international set‐up with multiple embedded cases of hackathons. Results indicate that hackathons offer coupled open innovation processes. The value captured by the initiator of a hackathon in the form of inbound open innovation is balanced by outbound knowledge flows towards participants as well as with sideways knowledge flows between participants, which are a result of the generation of collective intelligence. Collective intelligence is thus identified as an alternative mechanism for value capture from open innovation.Item Open Access Evaluation of conversational agents: understanding culture, context and environment in emotion detection(2022) Teye, Martha T.; Missah, Yaw Marfo; Ahene, Emmanuel; Frimpong, TwumValuable decisions and highly prioritized analysis now depend on applications such as facial biometrics, social media photo tagging, and human robots interactions. However, the ability to successfully deploy such applications is based on their efficiencies on tested use cases taking into consideration possible edge cases. Over the years, lots of generalized solutions have been implemented to mimic human emotions including sarcasm. However, factors such as geographical location or cultural difference have not been explored fully amidst its relevance in resolving ethical issues and improving conversational AI (Artificial Intelligence). In this paper, we seek to address the potential challenges in the usage of conversational AI within Black African society. We develop an emotion prediction model with accuracies ranging between 85% and 96%. Our model combines both speech and image data to detect the seven basic emotions with a focus on also identifying sarcasm. It uses 3-layers of the Convolutional Neural Network in addition to a new Audio-Frame Mean Expression (AFME) algorithm and focuses on model pre-processing and post-processing stages. In the end, our proposed solution contributes to maintaining the credibility of an emotion recognition system in conversational AIs.Item Open Access BeeLife : a mobile application to foster environmental awareness in classroom settings(2024) Stock, Adrian; Stock, Oliver; Mönch, Julia; Suren, Markus; Koch, Nadine Nicole; Rey, Günter Daniel; Wirzberger, MariaIntroduction: Significant threats to our environment tremendously affect biodiversity and related gains. Particularly wild bees actively contribute by pollinating plants and trees. Their increasing extinction comes with devastating consequences for nutrition and stability of our ecosystem. However, most people lack awareness about those species and their living conditions, preventing them to take on responsibility. Methods: We introduce an intervention consisting of a mobile app and related project workshops that foster responsibility already at an early stage in life. Drawing on principles from multimedia learning and child-centered design, six gamified levels and accompanying nature-based activities sensitize for the importance of wild bees and their role for a stable and diverse ecosystem. A pilot evaluation across three schools, involving 44 children aged between 9 and 12, included a pre-, post-, and delayed post-test to inspect app usability and learning gains. Results: Most children perceived the app as intuitive, engaging, and visually appealing, and sustainably benefited from our intervention in terms of retention performance. Teacher interviews following the intervention support the fit with the envisioned target group and the classroom setting. Discussion: Taken together, the obtained evidence emphasizes the benefits of our intervention, even though our sample size was limited due to dropouts. Future extensions might include adaptive instructional design elements to increase observable learning gains.Item Open Access Decoding mental effort in a quasi-realistic scenario : a feasibility study on multimodal data fusion and classification(2023) Gado, Sabrina; Lingelbach, Katharina; Wirzberger, Maria; Vukelić, MathiasHumans’ performance varies due to the mental resources that are available to successfully pursue a task. To monitor users’ current cognitive resources in naturalistic scenarios, it is essential to not only measure demands induced by the task itself but also consider situational and environmental influences. We conducted a multimodal study with 18 participants (nine female, M = 25.9 with SD = 3.8 years). In this study, we recorded respiratory, ocular, cardiac, and brain activity using functional near-infrared spectroscopy (fNIRS) while participants performed an adapted version of the warship commander task with concurrent emotional speech distraction. We tested the feasibility of decoding the experienced mental effort with a multimodal machine learning architecture. The architecture comprised feature engineering, model optimisation, and model selection to combine multimodal measurements in a cross-subject classification. Our approach reduces possible overfitting and reliably distinguishes two different levels of mental effort. These findings contribute to the prediction of different states of mental effort and pave the way toward generalised state monitoring across individuals in realistic applications.Item Open Access Cooperative approaches to data sharing and analysis for industrial internet of things ecosystems(2021) Baars, Henning; Tank, Ann; Weber, Patrick; Kemper, Hans-Georg; Lasi, Heiner; Pedell, BurkhardThe collection and analysis of industrial Internet of Things (IIoT) data offer numerous opportunities for value creation, particularly in manufacturing industries. For small and medium-sized enterprises (SMEs), many of those opportunities are inaccessible without cooperation across enterprise borders and the sharing of data, personnel, finances, and IT resources. In this study, we suggest so-called data cooperatives as a novel approach to such settings. A data cooperative is understood as a legal unit owned by an ecosystem of cooperating SMEs and founded for supporting the members of the cooperative. In a series of 22 interviews, we developed a concept for cooperative IIoT ecosystems that we evaluated in four workshops, and we are currently implementing an IIoT ecosystem for the coolant management of a manufacturing environment. We discuss our findings and compare our approach with alternatives and its suitability for the manufacturing domain.Item Open Access Internet of Things (IoT) technology research in business and management literature : results from a co-citation analysis(2021) Korte, Andreas; Tiberius, Victor; Brem, AlexanderIn coherence with the progressive digitalization of all areas of life, the Internet of Things (IoT) is a flourishing concept in both research and practice. Due to the increasing scholarly attention, the literature landscape has become scattered and fragmented. With a focus on the commercial application of the IoT and corresponding research, we employ a co-citation analysis and literature review to structure the field. We find and describe 19 research themes. To consolidate the extant research, we propose a research framework, which is based on a theoretical implementation process of IoT as a concept, specific IoT applications, or architectures integrated in an adapted input-process-output model. The main variables of the model are an initial definition and conceptualization of an IoT concept (input), which goes through an evaluation process (process), before it is implemented and can have an impact in practice (output). The paper contributes to interdisciplinary research relating to a business and management perspective on IoT by providing a holistic overview of predominant research themes and an integrative research framework.Item Open Access Constructing platform capitalism : inspecting the political techno-economy of Building Information Modelling(2022) Braun, Kathrin; Kropp, Cordula; Boeva, YanaItem Open Access CIEMER in action : from development to application of a co-creative, interdisciplinary exergame design process in XR(2024) Retz, Celina; Klotzbier, Thomas J.; Ghellal, Sabiha; Schott, NadjaIntroduction: Motor-cognitive learning is crucial for achieving and maintaining wellbeing. Exergames can effectively facilitate this type of learning due to their inherent qualities of exertion and game-related disciplines. These qualities can create effectiveness, enjoyment, and meaning in the lives of individuals. To address these aspects equally, the design process for exergame interventions needs to be interdisciplinary from the beginning. Objective: This paper aims to (1) enhance an exergame design process model for interdisciplinary co-creation (CIEM) by an Extended Reflection part (CIEMER). Furthermore, it aims to (2) show a formal process for making the abstract model applicable. In doing so, (3) this paper will also derive methods for conducting the process in an academic seminar. Methods: The study employed the CIEMER to conduct a 2-month academic seminar with 20 students. The seminar consisted of a 3-day intensive workshop, a 6-week work phase, and a 1-week testing phase, creating four Extended Reality prototypes. We used a mixed methods approach to evaluate the model, including feedback interviews with external experts, internal surveys, and written reflections from student designers. Results: Four motor-cognitive learning prototypes in Extended Reality were created using the CIEMER. External expert evaluations highlighted the prototypes’ alignment with effective, enjoyable, and meaningful objectives and potential efficacy while noting shortcomings in discipline-specific theoretical application. Internal feedback from students, collected via surveys and reflections, consistently showed positive outcomes in interdisciplinary collaboration and learning, underscoring the importance of an integrated approach in achieving project goals. Conclusion: The formal process within CIEMER effectively yielded four promising prototypes, demonstrating its sufficiency. Students positively acknowledged the benefits of interdisciplinary collaboration, finding it supportive and competence-enhancing. Additionally, the Extended Reflections enabled rapid and targeted iterations, streamlining the reflection of the current state and Creation process.Item Open Access Camera-based mobile applications for movement screening in healthy adults : a systematic review(2025) El-Rajab, Inaam; Klotzbier, Thomas J.; Korbus, Heide; Schott, NadjaBackground: In recent years, the proliferation of mobile applications in the health and fitness sector has been rapid. Despite the enhanced accessibility of these systems, concerns regarding their validation persist, and their accuracy remains to be thoroughly evaluated compared to conventional motion analysis methodologies. Furthermore, there is a paucity of evidence regarding real-time feedback and movement quality assessment. Consequently, this systematic review aims to evaluate the current state of camera-based mobile applications for movement screening in healthy adults, focusing on specific types of movement.
Methods: A systematic literature search was conducted in four databases - PubMed, ScienceDirect, Web of Science, and IEEE Xplore - covering the period from 2000 to 2024. The search strategy was based on key terms related to four main concepts: screening, mobile applications, cameras, and physical activity. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. The study was registered a priori on PROSPERO (Registration ID: CRD42023444355) to ensure transparency and prevent selective reporting of outcomes.
Results: Of the 2,716 records initially identified, eight studies met the specified inclusion criteria. The studies were primarily concerned with fitness exercises, gait analysis, and sport-specific movements. Some studies demonstrated high reliability compared to gold standard systems, while others reported technical limitations such as camera positioning and data interpretation issues. Feedback mechanisms varied, with many applications lacking personalized real-time correction.
Conclusion: Despite the potential of smartphone-based movement screening applications, particularly their accessibility and affordability, challenges remain regarding accuracy and user feedback. Precise measurements comparable to established methods are crucial for application-oriented camera-based movement screening. Equally important are improving real-time feedback, expanding the types of movement that can be assessed, and ensuring broad applicability across different populations and environments to ensure sustainable use of application-based movement screening.