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Research Projects 2017-07-04T11:54:54+00:00

Innovation Labs to Foster Idea and Product Development: Analysis of the Design Parameters by Example of the HYVE Innovation Labs

Innovation labs are a current trend in creating the next disruptive innovation. Facilities following the concept of innovation labs are spreading around the world and have become an increasingly important factor in corporate innovation strategies. Nevertheless a systematic and academic approach to analyze the design of current innovation labs and a common understanding of the concept is still missing. This master thesis (“Innovation Labs zur Förderung der Ideen- und Produktentwicklung: Beleuchtung der Gestaltungsparameter am Beispiel des HYVE Innovation Labs“) aims to take a first step towards closing this gap by examining related concepts such as incubators, accelerators, innovation centers and living labs. Academic publications and best practices on the topic of existing innovation labs are analyzed to create a current understanding of the concept of innovation labs. By developing an Innovation Lab Morphology the basic design parameters and the various specifications therein are described. This morphology can be used for academic purposes as a tool to analyze labs by providing a systematical way to characterize existing facilities. As a further application for practitioners HYVE has developed the INNOVATION LAB CANVAS to create a hands-on tool for the setup of new labs under CC-license.

Mirko Bahrenberg is a master’s candidate at the TU Darmstadt chair of Technology and Innovation Management and research fellow at the HYVE Science Labs

The Tawny Project – Emotional intelligence for the human IoT

Imagine a world with emotionally intelligent machines, a world where products and devices know how you feel. Our ambition is to build a living environment that responds to human emotion, cognition and motivation in order to improve and facilitate people’s life. We make things empathic.
We want to realize this vision by developing affective computing technology which allows to match human’s physiological data with psychophysiological inventories to create emotional intelligence for the Internet of Things (IoT). The TAWNY projects interlinks today’s major technological challenges such as artificial intelligence (AI), digitalization of products, IoT, big data, smart robots or autonomous systems.
Enormous growth rates are predicted for the IoT sector in the upcoming years. However, most of the current solutions are concentrating on M2M communication. We want to complement these developments by putting the user at the heart of the innovation process leading to a human-centered IoT.

A Longitudinal Study on Customer Perception of Autonomous Driving through data crawling and technology acceptance models.

Autonomous Driving has been said to be the next big disruptive innovation in the years to come. Considered as being purely technology driven, it is supposed to have massive societal impact in areas such as insurance companies, laws and regulations, logistics firms, automotive industry as well as all types of transportation methods, not only expected to have an enormous environmental effect but also the possibility of saving millions of lives worldwide.
Starting with a description of the technology, main benefits, challenges, players and state of the art technologies, followed by a literature review to demonstrate the research gap regarding customer perception on the topic, this research focuses on developing a longitudinal study to understand how customer perception has evolved and changes in the following years regarding Autonomous Driving and Autonomous Driving Technologies. Through the use of innovative data crawling technologies all user developed content in the internet related with Autonomous Driving will be analyzed and related to Technology Acceptance Models, developing an easy to understand approach for its future longitudinal development. The goal of this research is to get important customer Insights as well as to create the first research of its kind on the Topic.

Juan Rosenzweig is a master´s candidate for the dual program on Global Innovation Management at Strathclyde University and Hamburg Technical University as well as a research fellow at HYVE Science Labs

From Open Innovation to Open Government: A Multi-Level Analysis of Open Government Communities

Today, complex social challenges often question the very fabric of modern society with alienated citizens and create deep-seated tensions between them and their government. This research project shows how information and communication technologies in general and Open Government communities in particular may contribute to enable unprecedented opportunities for systematically fostering civic engagement in virtual and more collaborative system environments. In opposite to the private sector, where community-based approaches have already become popular strategies for systematically implementing distributed and participatory problem solving, the public sector hesitantly started with more open, citizen orientated, and collaborative service-offerings. As a consequence, also the related research contributions remain relatively silent. Structured in four different research perspectives and based on two empirical Open Government community projects the results enrich various existing streams of literature and provide, in addition, manifold implications for practitioners.

The research project was part of Giordano Koch’s PhD Thesis at the University of Hamburg

Online Research Methods for Customer Integration in the Example of the Insurance Industry

Insurances are complex intangible services that are very difficult to understand for consumers. Additionally insurances customarily evoke negative associations and subsequently consumers do not like to deal with them. Using the netnography method, deep consumer insights regarding the field of private health insurance were generated. Based on the identified consumer insights a Online Research Community (ORC) was set up enabling selected participants to discuss the topic of “Private Health Insurance”. The ORC validated the results of the netnography to a large extent. The thesis further resulted in preliminary approaches to improve need satisfaction in consumers.

Anja Öztas received her master’s degree in Economic Sciences from the Schumpeter School of Business and Economics, Bergische Universität Wuppertal and is a research fellow at the HYVE Science Labs

Why do beauty bloggers recommend and influence?

Subtitle: The “recent empties” phenomenon
What moves the predominantly young women to sacrifice a considerable amount of time and effort in order to write texts, take pictures and create videos for the purpose of discussing beauty and personal care products? The study investigates the motivational drivers of bloggers in the context of the unique interplay exemplified in the “recent empties” phenomenon. Here bloggers take on the role of recommenders who provide advice on beauty and personal care products at “eye-level” to their audience, while on the other hand inhibiting an influencer function for brands and companies. In this, the individuals behind the blogs follow their own idiosyncratic composition of motivational drivers, which are hitherto not investigated in existing literature.

The master’s thesis study provides an exploration of motivational drivers of beauty bloggers to act as influencers and recommenders online. In this a conceptual framework was developed from social-exchange theory and need based motivation theory, and tested qualitatively. The result is a useful and qualitatively tested instrument for assessing and analyzing bloggers’ motivations to partake in this interplay of interests of audience and companies. Possible application areas are influencer marketing, influencer recommender systems, and co-creation.

Kalle Kroll received his master’s degree from the Copenhagen Business School, Department of Management, Politics and Philosophy and is a research fellow at the HYVE Science Labs.

Consumer empowerment in crowdsourcing systems

Subtitle: Effects of perceived empowerment on consumers’ innovative behavior and change in brand passion
Crowdsourcing systems are increasingly used by companies to co-create new products with consumers. While consumer-brand interactions in conventional marketing campaigns are rather limited, consumers who participate in the ideation of products and intensively interact with the brand may experience strong feelings of empowerment. A sense of empowerment may arise when consumers feel they are capable of performing a meaningful task which serves a purpose they endorse and which has an impact on the brand’s innovation efforts. The research shows that this state of enhanced empowerment not only affects the innovative behavior of consumers, but also has an impact on emotive consumer-brand relationships. Specifically, the work provides empirical evidence that individual consumers’ empowerment experienced in a real-world crowdsourcing initiative has a positive effect on the quality of consumers’ submissions. Additionally, data reveals that perceived empowerment is positively associated with a change in brand passion increasing the level of passion consumers feel towards the host brand in the course of their participation. The results suggest that consumer empowerment is a favorable psychological state which is crucial in crowdsourcing systems as it offers brands new opportunities to co-create better ideas and build strong, passionate relationships with consumers.

Volker Bilgram is an external doctoral researcher at Prof. Frank Piller’s Chair of Technology and Innovation Management RWTH Aachen University and research fellow of the HYVE Science Labs

User Driven Innovation in the Health Care Sector

Subtitle: How Online Communities can be Utilized as Source for Digital Innovation
As the trend in the health care is going towards eHealth and quantified self, the health industry needs to rapidly develop new products to satisfy the quickly changing and growing needs of the user. To support this development, user innovations can be included to shorten and facilitate the innovation process. The research study consists of an empirical research with the method Netnography to identify digital user innovations for the health care sector in online communities.
The aim is to analyse the identified innovations regarding the type of innovation, the characteristics of the innovators and the online community where the innovation was figured out. Results of the study show that patients and relatives with the characteristics of lead user freely reveal their developments in online communities. Not only ideas, concepts or prototypes are revealed but also finalized products that can be further developed by user oriented companies.

Nina Bergsteiner, University of Applied Sciences Upper Austria and research fellow HYVE Science Labs

Netnography – Online Communities as Source of Innovation

Netnography enables researchers to access online community members’ knowledge in order to obtain deep insights into the world of consumers. It combines qualitative research with advantages of quantitative methods both applied on online consumer tribes. This research project introduces netnography as an innovative research approach to extract and use online community dialog for market research and new product development. Additionally, an increasing number of publications in recent times have reflected the scientific interest in this emerging technique. Considering the growing contributions in this research area, this study also aims to provide a comprehensive review and analysis of the existing body of academic literature on netnography. Next to this literature review the project includes a detailed case study how to apply netnography in the field of e-Mobility.

Hanna Stockinger is research fellow of the HYVE Science Labs and PhD candidate at the Ulm University

The Future of Augmented Reality – An Open Delphi and Web Monitoring Study

Augmented Reality is an emerging technology becoming state-of-the-art in a great variety of application scenarios. Although, the technology is at a point where it is mature enough to be used in publicly available consumer applications, the real commercial breakthrough of Augmented Reality is still lacking. This study remedies the prevailing lack of consumer research in this area through the conduction of a novel web monitoring method. The population of 48,560 consumer comments published until July 2013 on English speaking online community websites treating the topic Augmented Reality, were extracted and analyzed. Apart from the consumers’ perception of Augmented Reality the expert view has been investigated. Therefore, an innovative deviation of the Delphi technique has been employed by integrating an Online Research Community in the last round of a conventional Delphi procedure. Highly influential experts, being the drivers of Augmented Reality development, were consulted.

Hanna Stockinger is a research fellow of the HYVE Science Labs and PhD candidate at the Ulm University

Daily Happiness – The Analysis of Happiness Using Daily Mobile Panel Data

Research on happiness and life satisfaction have become commonly and regularly covered topics  in the field of sociology: Not only their development through the life span, but also the influence of subjective well-being on other areas of life (e.g. work performance, marriage or health) are subjects of great  research interest in sociology.Therefore, many researchers use panel data – like the Socio Economic Panel (SOEP) – to analyze life satisfaction and its influence by inspecting yearly changes of the respective variables. However, this method does not succeed in unveiling daily variations of happiness or life satisfaction that possibly occur during each year. Therefore, this paper aims to further investigate and analyze the variation of life satisfaction and happiness on a daily basis. For that purpose, a panel of mobile users was asked to indicate their currently perceived state of happiness once a day over a period of several months.Using both fixed and random effects, as well as hybrid models for time series and taking daily-within-variation into account, this paper aims to identify key drivers of daily happiness like personal activity rates, daily goals or nutrition. By analyzing happiness and life satisfaction by the variation of daily available data, we reach novel and relevant results in the field of happiness research.

Tobias Rüttenauer is a master’s candidate at the LMU Munich chair of sociology and research fellow at the HYVE Science Labs.

A Context Aware Recommender System Based on Mood Extraction

Todays electronic devices make it possible to track literally every second of our lives. This is from digital scales that draw nice graphs up to activity trackers that can show and analyze your sleep cycles, count the steps you walk during the day, and track your fitness activities. Nevertheless all the collected information is only shown to the user without any additional value except that it is saved somewhere. Besides tracking activities, it was never easier to track things like your mood or other factors that influence your quality of life. Mobile devices make this possible by the tap of a finger in an appropriate application. That’s a big step forward as compared with the old pen and paper method, but still there is some room for improvement. It would be even simpler if one could infer the mood without any user interaction. Imagine one could extract meta data, like a user’s mood or fitness which directly influences our quality of life, automatically from the data collected by the sensors we use day by day. Especially for applications in the health and fitness sectors this meta informations could lead to much more appealing data preparation and usage. This innovation would enable to give more accurate and personalized recommendations for a healthier and better life to the user without any additional interaction needed.

The thesis is three-fold. First we will conduct a study to collect movement data and measure the participants’ moods. Second we will create a mood extraction system which will be able to infer the mood by analyzing the activity data and third we will provide an example implementation of a context aware recommander system using a user’s mood to give personalized recommendations.

Daniel Richter is a master’s candidate at the TU Munich chair of software engineering and research fellow at the HYVE Science Labs.