Research

  1. Home
  3. Research

At the IBT, we study behavior and technology from a human-centered perspective. We use latest methods to conduct fundamental research and to study technological applications and their implications for individuals, organizations, and society at large.

Technologies are becoming increasingly autonomous, from smart kitchen devices and robotic vacuum cleaners to self-driving cars and service robots. In fact, some voices argue that we are about to move from the age of automation to the age of autonomy. Autonomous technologies can make decisions and complete tasks on behalf of humans, promising unprecedented levels of convenience and efficiency. At the same time, this novel class of technology endangers some fundamental human motives. At the IBT, we examine how these changes affect the relationship between humans and technology, which barriers to consumer adoption exist, and what the societal consequences may be in the long run.

Exemplary Publications:

  • Whillans, A., de Bellis, E., Nindl, F., & Schlager, T. (2020). Robots Save Us Time—But Do They Make Us Happier?. Harvard Business Review. [Link]
  • De Bellis, E., & Johar, G. V. (2020). Autonomous shopping systems: Identifying and overcoming barriers to consumer adoption. Journal of Retailing, 96(1), 74-87. [Link]

The use of conversational AI ranges from text-based chatbots that automate service operations to voice-based interfaces such as Amazon Alexa or Google Home that take over every-day tasks in consumers’ homes. Building on prior work in human-to-human communication and interpersonal psychology, we examine the impact of conversational AI on consumer decision making, consumer trust, and how to design competent while empathic conversational AI. We further examine how the proliferation of AI-enabled technologies that appear increasingly more human-like impact mind perception, entire markets, and consumer self-expression.

Exemplary publications

  • Hildebrand, C., & Bergner, A. (2021). Conversational robo advisors as surrogates of trust: onboarding experience, firm perception, and consumer financial decision making. Journal of the Academy of Marketing Science, 49(4), 659-676. [Link]
  • Hartmann, J., Bergner, A., Hildebrand, C. (2023): MindMiner: Uncovering linguistic markers of mind perception as a new lens to understand consumer–smart object relationships, Journal of Consumer Psychology, Forthcoming. [Link]
  • Völkel, S. T., Schödel, R., Buschek, D., Stachl, C., Winterhalter, V., Bühner, M., & Hussmann, H. (2020). Developing a Personality Model for Speech-based Conversational Agents Using the Psycholexical Approach. Conference on Human Factors in Computing Systems – Proceedings, 1–14. [Link]

The combination of modern information technology and digital behavior offers new possibilities for tailor-made solutions in domains such as food, insurance, and ad targeting. On the one hand, an increasing number of firms allows individuals to self-customize their own products according to their specific preferences. On the other hand, websites are personalized to customers’ implicit wishes and needs by leveraging large amounts of customer profile data. At the IBT, we explore these two central one-to-one marketing concepts—customization and personalization—and examine both their benefits and risks for individuals and companies.

Exemplary publications: 

  • de Bellis, E., Hildebrand, C., Ito, K., Herrmann, A., & Schmitt, B. (2019). Personalizing the customization experience: a matching theory of mass customization interfaces and cultural information processing. Journal of Marketing Research, 56(6), 1050-1065. [Link]
  • Hildebrand, C., Häubl, G., Herrmann, A., & Landwehr, J. R. (2013). When social media can be bad for you: Community feedback stifles consumer creativity and reduces satisfaction with self-designed products. Information Systems Research, 24(1), 14-29. [Link]
  • Krause, F., Görgen, J., de Bellis, E., Franke, N., Burghartz, P., Klanner, I. M., & Häubl, G. (2023). One-of-a-kind products: Leveraging strict uniqueness in mass customization. International Journal of Research in Marketing. [Link]

Whenever we travel to a new city or country, we notice that different places carry their own distinctive vibe. At the IBT, we try to make these hidden differences between places visible. To do so, we collect large-scale psychological data to study the spatial distribution of psychological attributes at fine-grained scales (e.g., how are personality traits distributed across and within cities?). In interdisciplinary research teams, we seek to understand how such geo-psychological differences come about and how they relate to economic development (e.g., where innovations or new companies emerge and gain traction).

Exemplary Publications

  • Ebert, T., Gebauer, J. E., Brenner, T., Bleidorn, W., Gosling, S. D., Potter, J., & Rentfrow, P. J. (2022). Are regional differences in psychological characteristics and their correlates robust? Applying spatial-analysis techniques to examine regional variation in personality. Perspectives on Psychological Science, 17, 407–441. [Link]
  • Mewes, L., Ebert, T., Obschonka, M. Rentfrow, P. J., Potter, J., & Gosling, S. D. (2022). Psychological openness and the emergence of breakthrough vs. incremental innovations: A regional perspective. Economic Geography, 98, 379-410. [Link]

Many of both business and everyday decisions depend on where things happen. Questions like where to live, where to shop, or where to start a business, all revolve around space. At the IBT, we try to understand how areas differ considering factors like proximity, movement patterns, and the vibe or culture of a place. Using digital data sources, we are interested in how location insights can be used to foster human well-being and decision making.

Exemplary Publications

  • Ebert, T., Berkessel, J.B., Jonsson, T. (2023). Political person-culture match and longevity: The partisanship-mortality link depends on the cultural context. Psychological Science, 34, 1192-1205. [Link]
  • Ebert, T., Götz, F. M., Gladstone, J., Müller, S. R., & Matz, S. C. (2021). Spending reflects not only who we are but also who we are around: The joint effects of individual and geographic personality on consumption. Journal of Personality and Social Psychology, 121, 378-393. [Link]

Mobile phones are the most personal device in many people’s lives. While phones once were only used for communication, the technical sophistication of modern smartphones provides users with a wide range of functionalities. Many of these functionalities allow users to do things on their phone anytime and anywhere. These functionalities rely on an array of sensors and logging routines that can also be used to measure when and where people do certain things. Sensor-based behavioral metrics are increasingly being used to identify, describe, and characterize individuals and their activities. At the IBT, we investigate how mobile sensing can be used to study human behavior, decisions, as well as the environments and situations people spend time in.

Exemplary Publications:

  • Stachl, C., Au, Q., Schoedel, R., Gosling, S. D., Harari, G. M., Buschek, D., … & Bühner, M. (2020). Predicting personality from patterns of behavior collected with smartphones. Proceedings of the National Academy of Sciences, 117(30), 17680-17687. [Link]
  • Koch, T., Romero, P., & Stachl, C. (2022). Age and gender in language, emoji, and emoticon usage in instant messages. Computers in Human Behavior, 126, 106990. [Link]

In addition to situational aspects, the personality of a person is one of the most important characteristics to understand and anticipate behavior. Personality also plays a key role in peoples’ everyday decisions, preferences, and experiences. At the IBT, we study how personality is expressed in everyday behavior and how machine learning can be used to understand, assess, and conceptualize personality and individual differences.

Exemplary Publications:

  • Stachl, C., Au, Q., Schoedel, R., Gosling, S. D., Harari, G. M., Buschek, D., … & Bühner, M. (2020). Predicting personality from patterns of behavior collected with smartphones. Proceedings of the National Academy of Sciences, 117(30), 17680-17687. [Link]
  • Stachl, C., Pargent, F., Hilbert, S., Harari, G. M., Schoedel, R., Vaid, S., … & Bühner, M. (2020). Personality research and assessment in the era of machine learning. European Journal of Personality, 34(5), 613-631. [Link]

Oral communication extends beyond the mere words we utter to encompass the subtleties of our delivery. Often, the way we speak holds more significance than the words themselves. Elements such as tone, pitch, rhythm, and the subtle nuances in our voice serve as windows into our emotions, identity, and mental state. Analyzing the voice allows us to further understand what individuals convey, allowing us to further understand them.

Exemplary Publications

  • Busquet, F., Efthymiou, F., & Hildebrand, C. (2023). Voice analytics in the wild: Validity and predictive accuracy of common audio-recording devices. Behavior Research Methods, 1-21. [Link]
  • Hildebrand, C., Efthymiou, F., Busquet, F., Hampton, W. H., Hoffman, D. L., & Novak, T. P. (2020). Voice analytics in business research: Conceptual foundations, acoustic feature extraction, and applications. Journal of Business Research, 121, 364-374. [Link]

OPEN POSITIONS

Join the team!