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- Visualizing influenza A virus assembly by in situ cryo-electron tomographyPublication . Wachsmuth-Melm, Moritz; Peterl, Sarah; O’Riain, Aidan; Makroczyová, Jana; Fischer, Konstantin; Krischuns, Tim; Vale-Costa, Sílvia; Amorim, Maria João; Chlanda, PetrInfluenza A virus (IAV) forms pleomorphic particles that package eight ribonucleoprotein complexes (vRNPs), each carrying a distinct RNA genome segment. vRNPs assemble in the nucleus and undergo selective sorting during Rab11a-mediated trafficking to the plasma membrane. Virion assembly is orchestrated by matrix protein 1 (M1), which forms a layer beneath the viral envelope containing hemagglutinin (HA) and neuraminidase (NA). However, molecular details of vRNP distribution, cytosolic trafficking, and coordination of IAV assembly remains unclear. Using in situ cryo-ET, we reveal that HA-containing membranes provide Rab11a-dependent platforms for membrane-assisted vRNP clustering, reducing inter-vRNP distances. In the absence of HA, vRNPs cluster on NA-containing membranes and virus assembly remains intact, indicating that vRNP clustering and trafficking is membrane-assisted but HA independent. The characteristic 7 + 1 vRNP bundle forms concomitantly with budding and is orchestrated by M1 layer assembly that precedes plasma membrane attachment. We further reveal that intracellular M1 forms multilayered helical assemblies of antiparallel dimers, structurally distinct from the M1 layer in virions. These assemblies are compact in the nucleus but partially dissociate in the cytoplasm, likely serving as a reservoir for budding. Together, our findings uncover membrane-assisted vRNP clustering and molecular details of M1 coordinated influenza virus assembly.
- From 1D microbiological assays to 3D advanced skin models: enhancing preclinical strategies to unravel the impact of bioactive textiles on the human skin microbiomePublication . Negut, Irina; Mazzanti, Camilla; Laurano, Rossella; Ciardelli, Gianluca; Bronco, Simona; Oliveira, Cláudia S.Bioactive textiles have emerged as multifunctional materials to actively interact with the human skin and its microbiome. By embedding natural or synthetic bioactive compounds, such as chitosan, essential oils, plant extracts, and metallic nanoparticles, these materials aim to prevent and target infections, modulate inflammation, and promote skin homeostasis. Given the critical role of the skin microbiome in maintaining barrier integrity and immune balance, strategies that selectively inhibit pathogenic microorganisms (e.g., Staphylococcus aureus, Cutibacterium acnes) while preserving beneficial commensals like Staphylococcus epidermidis are essential to avoid dysbiosis and associated dermatological disorders. This review highlights current trends in the design and functionalization of bioactive textiles, emphasizing sustainable and biocompatible approaches that leverage natural antimicrobial compounds and green synthesis techniques. It also examines conventional evaluation pipelines primarily based on 1D microbiological assays and 2D skin models, highlighting their limitations in predicting real-world performance. Advanced in vitro models, particularly 3D reconstructed human skin platforms incorporating both pathogenic and commensal microbiota members, are presented as indispensable tools to study fabric–skin–microbe interactions under physiologically relevant conditions. These models enable accurate assessment of antimicrobial efficacy, biocompatibility, and microbiome impact, providing a bridge between in vitro and clinical outcomes. Furthermore, the potential of bioactive textiles in managing microbiome-related skin conditions, such as atopic dermatitis and acne, is discussed alongside the importance of developing microbiome-safe materials. Despite encouraging clinical evidence demonstrating pathogen reduction and symptomatic improvement, the successful translation of these materials to clinical practice needs interdisciplinary research and the adoption of advanced preclinical strategies to ensure innovative solutions for personalized skin health.
- Orchestrating strategic control points in layered AI ecosystems : insights from startup founders and investorsPublication . Cronjäger, Jannis; Bonhsack, RenéThe rapid rise of artificial intelligence (AI) has reshaped how digital businesses compete and collaborate. For startups, succeeding in this evolving landscape requires more than strong technology. It demands strategic defensibility within complex ecosystems. This thesis investigates how AI ventures can build and sustain competitive advantage by orchestrating control points as positions of influence over data, infrastructure, user access, and ecosystem relationships across the AI value chain. Drawing from theory on digital ecosystems, modularity, and dynamic capabilities, the study builds a four-step structured framework to understand control points across seven layers of the AI value chain: Hardware infrastructure, cloud compute, data, foundation models, machine learning operations, applications, and services. Using nine expert interviews with venture capitalists and AI founders, the thesis identifies which control points matter most at each layer, how different actors such as AI giants, enablers, creators, and integrators use them, and how startups can align their strategy accordingly. The result is a practical and intuitive framework that helps ventures assess where they can build defensibility not necessarily by owning the whole stack but by combining accessible control points in smart and adaptive ways. The study highlights that dynamic capabilities like agility, ecosystem integration, and technical know-how are key to sustaining relevance over time. It also shows that strategic control is less about ownership and more about orchestration and positioning within a layered and fast-moving AI environment.
- Case study : Casa del Constructor : adaptive strategies, inward internationalization, and resilience amid global disruptionsPublication . Rossell, Josue Alejandro Cordon; Reis, RicardoSmall and medium-sized enterprises (SMEs) represent the backbone of emerging economies; yet, they are highly vulnerable to systemic disruptions, such as the pandemic, geopolitical conflicts, and global supply chain volatility. This thesis examines how SMEs can enhance resilience, competitiveness, and long-term sustainability through strategizing inward internationalization. By using the case of Casa del Constructor, a family-owned construction materials retail store in Honduras, we can observe the strategies implemented to overcome these challenges. This thesis integrates key theoretical frameworks, including the Uppsala model, Dynamic Capabilities, the Resource-Based View, and the Global Value Chain framework, to explore adaptive strategies during times of disruption. This thesis takes on a qualitative case based on company data and market reports to analyze Casa del Constructor's strategic transformation from a domestic distributor to an import-driven GVC integrated business. This case study highlights how direct importing enabled the company to stabilize its inventory, improve margins, diversify its product offerings, and enhance its capabilities amid the COVID-19 pandemic and other disruptions in its local market. Moreover, it briefly highlights how market knowledge and experience gained through inward internationalization enabled the company to strategize a further vertical plan to establish a small manufacturing facility, which demonstrates the pathways for sustainable growth. This study contributes to theory by extending internationalization research into inward pathways in emerging markets and demonstrating how combining dynamic capabilities with GVC participation can enable SMEs to thrive during crises.
- To tip or not to tip : demographic, behavioral, and cultural drivers of tipping practices in RussiaPublication . Chistyakov, Vasilii; Fernandes, DanielTipping is a widespread yet complex practice that plays a central role in the hospitality industry. It is simultaneously an economic exchange, a social norm, and a signal of customer satisfaction. While tipping has been extensively researched in the United States and parts of Western Europe, there is a notable lack of empirical evidence from Russia and Eastern Europe, despite the cultural and economic differences that shape hospitality practices in these regions. This thesis addresses this gap by investigating tipping behavior in Russian restaurants. The study is guided by three research questions: What factors influence whether customers leave a tip in Russian restaurants? What factors determine the amount tipped by customers? How do demographic, behavioral, and perceptual variables interact in explaining tipping behavior? To answer these questions, a structured online survey was conducted among restaurant customers in Russia between February and March 2025, yielding 69 valid responses. The data were analyzed using descriptive statistics, logistic regression, and multiple linear regression. The findings indicate that behavioral and contextual factors - such as group size, bill payer, and dining frequency - play the most significant role in shaping tipping behavior. Demographic factors (age, gender, education) were not significant predictors of tip amounts, while perceptual factors showed mixed results: service quality had a positive effect, but food quality and cleanliness did not. By addressing an underexplored context, this study confirms some international findings while challenging others, thereby contributing to the broader literature on tipping behavior and offering practical insights for restaurant managers in Russia.
- A narrative review of AI in hospital-acquired infectionsPublication . Graça, Mariana Lopes Pereira da; Martins, HenriqueHospital-Acquired Infections (HAI) are a longstanding challenge in patient safety efforts and an important public health matter. The development of healthcare information technology has been improving the surveillance of hospital-acquired infections, making artificial intelligence technologies a promising approach to mitigate the burden of HAIs. This thesis constitutes a thorough narrative review of the existing literature on the use of Artificial Intelligence (AI) to combat hospital-acquired infections, as well as qualitative insights from professionals in the area. It aims to critically evaluate the challenges and goals of resorting to artificial intelligence for the early detection of HAIs, allowing the improvement of patient safety and healthcare outcomes. Findings from this review reveal significant results in HAI detection accuracy when AI is used. Demonstrating that, when compared to conventional methods, AI-based models are capable of greatly increasing the accuracy of hospital-acquired infection detection, which can result in earlier and more accurate identification of HAIs. The discussion reflects how AI can be a powerful support tool rather than a replacement for clinical judgment. It also addresses the importance of tailoring AI applications to specific hospital contexts to maximize their impact. The conclusion reinforces the promising potential of AI in reducing the burden of HAIs, while acknowledging that its success largely depends on overcoming technical, organizational and ethical challenges.
- Bridging the AI adoption gap with Microsoft Copilot : a comparative experiment of AI-generated SEO textPublication . Commentz, Daniel Friedrich; König, MichaelSmall and medium-sized enterprises (SMEs) face persistent challenges in adopting artificial intelligence (AI) due to limited resources, technical know-how, and data privacy concerns. On the contrary, especially within the intersect of AI and search engine optimization (SEO), while the literature is still in an embryonic phase, existing research has already acknowledged the potential of large language models (LLMs) for SEO purposes. While most studies focus on freely accessible tools like ChatGPT, other enterprise-grade solutions like MS Copilot are mostly overlooked. To address this gap, this study evaluates whether Copilot-generated search engine optimized product texts can enhance product page performance across three dimensions: Algorithmic relevance (H1), user engagement (H2), and commercial impact (H3). For this purpose, a controlled online field experiment was conducted within a German SME in the beauty and healthcare sector. From a sample of 20 product pages, half of the product texts were exchanged with Copilot-generated content, while the other half served as a control group and tracked eight weeks before and after the intervention. While statistical significance remained limited, descriptive patterns cautiously indicate that Copilot-generated content may improve search visibility and, in isolated cases, positively affect sales outcomes. Importantly, no evidence was found that such AI-generated content harms visibility or user experience. In doing so, this study contributes to the emerging embryonic research of applied AI in the field of SEO, offering an explorative foundation for future research. Furthermore, it offers first practical hints for SME practitioners evaluating the integration of AI-driven tools like MS Copilot.
- Analyzing the impact of artificial intelligence on the fan engagement in the sports industryPublication . Taub, Alexandra; Grohsjean, ThorstenThis thesis explores how artificial intelligence is impacting fan engagement in the sports industry. As digital transformation accelerates across sectors, sports organizations are increasingly adopting technologies such as chatbots, personalized content systems, data analytics, and virtual assistants to enhance the way they interact with fans. This research starts with reviewing the development of artificial intelligence and its role in marketing and consumer interaction. It then examines the concept of fan engagement, highlighting how emotional, behavioural, and social factors shape the relationship between fans and sports organizations. The analysis combines insights from an extensive literature review with real-world examples from major sporting events such as the Olympic Games, Wimbledon, and Formula 1 to understand how artificial intelligence is currently being used to improve fan experience. While the benefits of these technologies are clear, ranging from personalized content to more efficient communication, this research also considers the potential negative effects, including ethical concerns, data privacy issues, and the risk of losing the human touch in the relationship with fans. By an extensive literature review, the thesis offers a balanced view of how artificial intelligence is reshaping the landscape of fan engagement. It concludes with managerial recommendations for organizations aiming to integrate such tools in a way that supports authenticity, trust, and long-term connection with fans.
- The disclosure dilemma : understanding consumer responses to AI-generated brand communicationPublication . Kowarschik, Christine; Borges, MónicaThe rapid integration of generative artificial intelligence (GenAI) into marketing communication is changing how brands create advertising content. This study investigates how AI disclosure in advertising influences consumers’ attitudes toward the advertisement (Aad), perceived brand authenticity (BA), and purchase intention (PI). It explores the moderating effect of AI aversion and brand trust (BT). The growing integration of AI-generated content (AIGC) in marketing and regulatory requirements for disclosure under the EU AI act motivates this research. It addresses the lack of empirical evidence on consumer responses to AI transparency. A between-subject online experiment exposed female participants familiar with the fashion brand Mango to either an AI-disclosed or non-disclosed AI-generated advertisement. Established measurement scales captured Aad, BA, PI AI aversion, and BT. Data was analysed using regression analysis and moderation models. Results showed no significant direct effect of AI disclosure on Aad or BA, which contradicted the AI-authorship effect documented in prior studies. However, BA and Aad significantly predicted PI, BA showing a stronger influence. Neither AI aversion nor BT significantly moderated the relationship between disclosure and consumer responses, although BT strongly correlated with PI. It was revealed through exploratory qualitative insights that while most respondents remained indifferent to disclosure, a minority expressed concerns about authenticity, creativity, and ethics. Findings suggest that mandatory AI disclosure might not harm consumer perceptions, but authenticity remains critical for driving purchase intentions. To sustain trust and authenticity in AI campaigns, marketers should frame AI as a creative enhancer rather than a human replacement.
- Consumer responses to blockchain-based transparency : investigating the moderating role of product category and the mediating roles of trust in labels and greenwashing concernsPublication . Obermeier, Matilda Sara; Estarreja, MariaConsumers are increasingly interested in sustainability when it comes to supermarket purchases, but their attitudes do not always translate into actual buying behavior. Main reasons are mistrust in sustainability labels and greenwashing concerns. This thesis investigates blockchain-based transparency as an underexplored solution to increase perceived credibility and sustainable purchase intention. A mixed-methods approach was used, including a literature review, exploratory interviews, a pilot survey and an experimental online survey with a 2x2 between-subjects design (label type: blockchain versus traditional; product category: milk versus day cream). 206 valid responses were used for the analysis. The findings show that blockchain-based transparency can increase perceived credibility and purchase intention more than traditional sustainability labels. The moderation of product category and mediations of trust in sustainability labels and greenwashing concerns are not significant but reveal positive trends. These findings offer important insights for retailers, policy makers and technology developers who want to reduce greenwashing and improve sustainability communication.