AI Design Competence for more customer experience through better conceptualized occasional commerce strategies
(AI for designing future malls).
Occasional Commerce – Customers shop online and offline.
So what is the relevance of stores in the marketing mix and how can AI (advanced analytics and metrics) be used to streamline and increase the efficiency with better conceptualized shops, malls and commercial real estate.
The following research provides answers to these questions.
Are Chatbots able to personalize the customer experience and furthermore interact with a user emotionally intelligent?
The Thesis defines the status quo of chatbots in the fashion industry, shows potential future use cases and design principles of an emotional intelligent chatbot.
Emotion Sensing Technologies that track/read, interpret and respond to emotions are about to be fully integrated into our daily lives. These systems have huge potentials but also pose difficult challenges, these are sketched in this thesis…
In a world of digitalization, globalization, connectivity and mobility, people long for something that makes sense. A mindset that is based on more mindfulness, deceleration and more focus. In this thesis main elements and practices of ‘mindful lifestyle and leadership’ are being scrutinized.
This paper deals with the question of whether “plastic-free” consumption can be achieved and fueled by smart pop-up stores…
Artificial Intelligence and Natural Language Processing as and Enabler for Future Fashion? This bachelor thesis scrutinizes the question of whether artificial intelligence or more precisely, language analysis is an enabler for the future fashion industry…
The bachelor thesis scrutinizes the disruptive dynamics of the technologies Smart Clothing and Artificial Intelligence (AI) for the area of Personal Fitness, with the intention to show the development of this field towards a technologically advanced field Personal Fitness 2.0, which is driven by the use of Smart Clothing and Artificial Intelligence.
The bachelor thesis deals with the discrimination potential of Machine Learning Algorithms within Decision – Support – Systems (DSS), which are increasingly used in German companies. The specialization is in the areas of recruiting and marketing. The concrete goal of the work was to find out whether AI-based systems reinforce gender discrimination or not.
