Cross-Group Research Fields
At IISM we emphasize the importance and relevance of cross-group research covering both, disciplinary as well as interdisciplinary contributions in information systems and marketing. Currently, we are emphasizing two cross-group research fields:
- Conversational Interfaces (Klarmann, Mädche)
- Flow Computing (Mädche, Weinhardt)
Since the 1960’s the crew of Star Trek is able to communicate with their ship-computer in a natural and speech-based way. Through voice commands, crew members can, for instance, easily obtain information about artifacts or learn the results of medical scans. In contrast, in this world, until recently conversational human-computer interfaces have worked pretty poorly. The most infamous example: The chatbot “Clippy” that Microsoft introduced for Microsoft Office ’97. It was removed from the software a few years later, because its only effect had been angry users.
Technological capabilities have grown enormously over the last few years. Nowadays conversational interfaces that are much more helpful are implemented on websites (e.g. Mildred for Lufthansa or TOBi for Vodafone UK). Conversational interfaces can be found on mobile devices as well as smart speakers like Amazon’s Echo series.
The basic idea of conversational agents is that users can communicate with systems in a natural way without adapting their speech pattern. Conversational interfaces can be text- or speech-based. Both types rely on natural language processing but differ in their input/output modality.
Designing and understanding the influences of conversational interfaces requires knowledge from the fields of Information Systems and Marketing. Coming from two distinct methodological traditions, both disciplines are interested in understanding how users, especially customers, can benefit most from the technological advances in the domain. The IISM follows an interdisciplinary approach to systematically build up this knowledge following a behavioral and design research oriented approach.
- Jasper Feine
- Ingo Halbauer
- Ulrich Gnewuch
- Martin Klarmann
- Alexander Mädche
- Stefan Morana
- Designing Social Cues for Customer Service Chatbots
- Consumer Decision Making Between Voice and Online Shopping
- Influence of PRoduct Order on Consumer's Decisions
- How Social Cues Change Consumer's Decision at Voice Shopping
- A Taxonomy of Social Cues
- Gnewuch, Ulrich, Stefan Morana, Marc T.P. Adam, and Alexander Maedche (2018), “Faster Is Not Always Better: Understanding the Effect of Dynamic Response Delays in Human-Chatbot Interaction”, in Proceedings of the 26th European Conference on Information Systems (ECIS), Portsmouth, United Kingdom, June 23-28.
- Halbauer, Ingo and Martin Klarmann (2018), “Testing Differences in Consumer Decision Making Between Voice and Online Shopping”, accepted for presentation at the 47th EMAC Conference Glasgow, United Kingdom, May 30-June 1.
- Gnewuch, Ulrich, Stefan Morana, and Alexander Maedche (2017), "Towards Designing Cooperative and Social Conversational Agents for Customer Service", ShortPaper, to appear in: Proceedings of the International Conference on Information Systems (ICIS) 2017.
As information technologies (IT) are both, drivers of highly engaging experiences and sources of disruptions at work, the phenomenon of flow - defined as the holistic sensation that people feel when they act with total involvement - has been suggested as promising vehicle to understand and enhance user behavior.
Despite the growing relevance of flow at work, contemporary measurement approaches of flow are of subjective and retrospective nature, limiting our possibilities to investigate and support flow in a reliable and timely manner. Therefore, in this cross-research field we investigate new concepts for the measurement and prediction of flow using objective data (e.g. physiological data). Based on this information, we design flow-aware computing systems that are able to adapt to the individual flow states of users.
- Alexander Mädche
- Mario Nadj
- Jasper Feine
- Christof Weinhardt
- Measurement and Prediction of Flow using Physiological Data
- Flow-Aware Notification Systems
- Team Flow Management & Feedback Systems