Univ. Prof. Christina Schamp
All her research projects share the notion of addressing a relevant trend in consumer decision-making with a broad range of different, cutting-edge research methods. Trained as social psychologist, at the core of her research are behavioral experiments. However, she also employs meta-analytical studies, secondary data research, and machine learning methods. Given her prior work experience for a top-management consulting company, her research projects are practice driven, often in cooperation with both startups and multinational companies.
In the following, you will find more details about her research:
Ethnic consumer buying behaviour
One stream of research addresses ethical consumer decision-making in purchase settings that has gained strong momentum in both offline and online purchase behavior in recent years. There is rising discussion about purchasing and using products and resources not only according to the egoistic benefits they provide, but also to do justice in a moral sense. However, from a marketing perspective, it is still unclear if marketing success is compatible with ethicality, or if both can even be achieved in unison. On the one hand, a vast majority of consumers indicate in consumer surveys that they are willing to switch to ethical brands. On the other hand, market shares for ethical products are still low, in the 5-10% range, and consumers are often not living up to their own ethical standards, e.g., by having high product return rates in online shopping. Together with her co-authors, Dr. Schamp addresses this contradiction in several research projects, using hierarchical meta-analytical modelling, hierarchical Bayes modelling, as well as behavioral and field experiments.
Moral consumerism in the digital sphere
In recent projects, Dr. Schamp aims to extend these research findings beyond consumers’ purchase decisions to moral consumer behavior in a digital environment. By employing lab and field experiments, she evaluates how companies can incentive ethical or norm-compliant behavior by offering pre-commitment pricing schemes (in cooperation with a language learning app). Likewise, she studies how by different moral interventions can reduce consumers’ product returns in an online shopping context (in cooperation with a big fashion online retailer), and evaluates measures to reduce consumer thefts at self-checkouts (in cooperation with a retail stor
Virality of texts and images in social media
Another stream of research evaluates consumer-decision making in the social media context. Smartphones have made commenting on posts and sharing texts and images of (branded) experiences on social media nearly effortless. Dr. Schamp is interested in analyzing the consequences of this technological development both from a marketing and consumer behavior perspective, employing a mix of machine learning methods to analyze the vast amount of text and image data on social media and experimental studies to isolate the mechanism behind effects. Despite their ubiquity, marketing scholars have only just begun to explore the rich insights text and image data on social media can provide. Machine learning applications can play a central role in unlocking this potential for marketing practice. Together with her co-authors, she therefore also researchs the methodological foundations to harvest this potential by comparing the performance of different text classification methods, making recent developments in natural language processing applicable for management research.
Especially the intersection between technological trends and questions of ethicality and morality seems of increasing relevance in the future. A multi-method approach to triangulate the effects and understand the psychological mechanisms seems most fruitful to study these phenomena and provide implications for both marketing research and practice.
Dr. Melanie Clegg
Melanie Clegg‘s research projects primarily investigate consumer perceptions of algorithms and artificial intelligence. Specifically, she looks into whether, why, and under which circumstances consumers are willing to co-operate with and rely on algorithms and artificial intelligence. One aspect of this research focuses on creative co-work, innovation processes, and personalization enabled by artificial intelligence, and how consumers react to artificial intelligence in these domains. Another aspect deals with ethical pitfalls for businesses and society that are caused by the increasing impact of algorithms on professional and private aspects of our lives, and how can firms deal with such ethical compromises.
A second research focus of her lies in social interactions in the digital space such as social media platforms. Here, she primarily examines facettes of user-generated content that drive proliferation and motives that increase content creation and sharing.
To tackle these questions, Melanie Clegg uses a mixture of behavioral experiments, secondary data analysis, qualitative and quantitative analyses of text data as well as machine learning approaches.