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(2020)
Ambush-Marketing löst meistens heftige Reaktionen aus - bei Befürwortern und Gegnern. Die Idee des Ambush-Marketings ist es, von den Erfolgen des Sponsorings zu profitieren, ohne die Pflichten eines offiziellen Sponsors einzugehen. Ambusher besitzen keine Vermarktungsrechte an einer Veranstaltung, bauen aber dennoch durch ihre Marketingmassnahmen eine Verbindung zu einem Event auf. Der Grat zwischen der Verletzung von Sponsoren-Rechten und kreativ-innovativer Kommunikationspolitik ist dabei oft sehr schmal.
YouTube fashion videos
(2020)
YouTube is the most widely adopted and successful video sharing platform. It works as a marketing instrument and money-making tool for companies while reaching the target group. After considering the significant literature based on YouTube, it is striking that there is lack of information about YouTube’s benefits as a video marketing instrument for fashion brands. To establish this subject further, the purpose of this study is to enrich the existing findings on social video marketing on YouTube in the apparel industry. The findings indicate the importance of YouTube as a social network for fashion marketers. The second part conducts an empirical study, which makes the YouTube channel performance of nine fashion brands the subject of discussion. Thereby, three brands per lifestyle, sports and luxury sector are analyzed through comparative aspects. Accordingly, the differences and similarities within and between the sectors are analyzed and evaluated.
”I have never seen one who loves virtue as much as he loves beauty,” Confucius once said. If beauty is more important as goodness, it becomes clear why people invest so much effort in their first impression. The aesthetic of faces has many aspects and there is a strong correlation to all characteristics of humans, like age and gender. Often, research on aesthetics by social and ethic scientists lacks sufficient labelled data and the support of machine vision tools. In this position paper we propose the Aesthetic-Faces dataset, containing training data which is labelled by Chinese and German annotators. As a combination of three image subsets, the AF-dataset consists of European, Asian and African people. The research communities in machine learning, aesthetics and social ethics can benefit from our dataset and our toolbox. The toolbox provides many functions for machine learning with state-of-the-art CNNs and an Extreme-Gradient-Boosting regressor, but also 3D Morphable Model technolo gies for face shape evaluation and we discuss how to train an aesthetic estimator considering culture and ethics.
Context: Organizations are increasingly challenged by dynamic and technical market environments. Traditional product roadmapping practices such as detailed and fixed long-term planning typically fail in such environments. Therefore, companies are actively seeking ways to improve their product roadmapping approach.
Goal: This paper aims at identifying problems and challenges with respect to product roadmapping. In addition, it aims at understanding how companies succeed in improving their roadmapping practices in their respective company contexts.
Method: We conducted semi-structured expert interviews with 15 experts from 13 German companies and conducted athematic data analysis.
Results: The analysis showed that a significant number of companies is still struggling with traditional feature-based product-roadmapping and opinion-based prioritization of features. The most promising areas for improvement are stating the outcomes a company is trying to achieve and making them part of the roadmap, sharing or co-developing the roadmap with stakeholders, and establishing discovery activities.
Regardless of company size or industry sector, a majority of project teams and companies use customized processes that combine different development methods-so-called hybrid development methods. Even though such hybrid development methods are highly individualized, a common understanding of how to systematically construct synergetic practices is missing. Based on 1,467 data points from a large-scale online survey among practitioners, we study the current state of practice in process use to answer the question: What are hybrid development methods made of? Our findings reveal that only eight methods and few practices build the core of modern software development. This small set allows for statistically constructing hybrid development methods.
This study investigates how integrated reporting (IR) creates value for investors. It examines how providers of financial capital benefit from an improved firm information environment provided by IR. Specifically, this study investigates the effect of voluntary IR disclosure on analyst earnings forecast accuracy as well as on firm value. To do so, we use an international sample of 167 listed companies that voluntarily publish an integrated report. Our analysis shows no significant effect of a voluntary IR publication on analyst earnings forecast accuracy and no significant effect on firm value. We thus do not find evidence for the fulfillment of IR's promises regarding improved information environment and value creation of voluntary adopters. We conclude that such companies might already have a relatively high level of transparency leading to an absent additional effect of IR disclosure. Positive effects of IR appear to be more relevant in environments where IR is mandatory.
In dieser Ausarbeitung wird auf Visualisierungsmöglichkeiten von neuronalen Netzen eingegangen. Ein neuronales Netz scheint zuerst nicht von außen einsehbar und ist somit für viele eine Blackbox. Häufig genutzte Python-Bibliotheken, zum Beispiel TensorFlow, werden vorgestellt und deren Stärken wie auch Schwächen präsentiert. Anhand dieser werden bereits bestehende Visualisierungen gezeigt und ihr derzeitiger Einsatz wird erläutert. Durch einen Vergleich soll ersichtlich werden, welche Bibliothek am meisten Daten während des Trainings liefert, damit diese Informationen weiter verarbeitet werden. Diese Daten sollen so visualisiert werden, dass sie bei der Entwicklung eines neuronalen Netzes unterstützend sind. Ziel ist es, auf die Möglichkeiten einzugehen, welche geboten werden können. Durch eine Vereinfachung des Debuggings neuronaler Netze sollen weiterführende Entwicklungen in diese Richtung unterstützt werden.