Information Systems (IS) research is a scientific field that focuses on the development, use, and impact of information technologies (Benbasat and Zmud, 2003). A current stream of research has been established under the name ‘Neuro-Information-Systems (NeuroIS). Through the application of neuroscientific methods and theories, NeuroIS seeks to contribute, on the one hand, to the development of new theories that make possible accurate predictions of IT-related behaviors, and, on the other hand, to the design of IT artifacts that positively affect economic and non-economic variables, such as productivity, satisfaction, adoption, and well being (Riedl et al., 2010). Several reference disciplines are connected to NeuroIS, such as neuropsychology and cognitive neuroscience, neuroeconomics, decision and social neuroscience, consumer neuroscience, neuroergonomics, affective computing, and Brain-Computer Interaction (Riedl and Léger, 2016). In the state of the art before this doctoral thesis, methods typically applied in Neuro-IS research included neurophysiological measurements (e.g. heart rate variability, skin conductance, and facial-electromyography), electroencephalography (EEG), and functional magnetic resonance imaging (fMRI). In order to contribute to the methodological development of NeuroIS, several different approaches have been conducted resulting in four publications in peer-reviewed scientific journals that represent the core of this cumulative doctoral thesis. In a didactic approach to incrementally improve scientific skills and rigor, this thesis comprises two projects where I was involved as co-author and two publications in the leading role as first author. While all publications focused on methodology, a close thematic link exists between the first two and the second two publications.
The first project investigated technostress, defined as any negative impact on attitudes, thoughts, behaviors, or body physiology that is caused either directly or indirectly by technology (Weil and Rosen, 1997), through an experimental design in which a computer system breakdown was simulated. In order to operationalize technostress, we used measurements of cortisol in saliva, a hormone known to be released in a physiologic stress response for the first time in NeuroIS research. Indeed, it was possible to objectively prove a stress reaction due to the computer system breakdown (Riedl et al., 2012). In a second project, we returned to technostress using an established NeuroIS method to measure the stress response (skin conductance), but focused on another methodological avenue by investigating a possible gender aspect. In fact, we could show that there are gender differences in the physiological stress response to a computer system breakdown (Riedl et al., 2013). As I will argue later on, the outcome of these two studies does not only have implications for technostress research, but also on IS research in general, as they contribute significantly to the methodological evolution of NeuroIS.
In another two separate, but connected, research projects, this doctoral thesis tried to implement a non-technological method derived from clinical neuroscience and neurology to NeuroIS by shifting the focus of research from single group investigations on healthy subjects to studying group differences between patients suffering from neurological diseases and healthy control subjects. This approach is routed in the historically earliest neuroscientific studies that investigated motor, cognitive, and/or behavioral functions of patients with cerebral lesions (so called ‘lesion studies, Rorden and Karnath, 2004). One published study of this thesis discussed the theoretical aspects of studying neurological patients in economically-oriented neurosciences in general (Javor et al., 2013), while a second one applied this approach to NeuroIS. More precisely, trust behavior towards avatars (artificially generated faces), an important research subject in NeuroIS, was investigated through an economic trust game that was played by a group of patients suffering from a neurological disease (Parkinsons disease) and another group of healthy controls. Indeed, we were able to show that a behavioral difference between patients and healthy controls exist and we argued that this difference has major impact on IS theory and practice (Javor et al., 2016). In conclusion, the methodological development of NeuroIS prior to and during this doctoral thesis was characterized by an excitement and search for new technological and non-technological methods. This has led to significant contributions to IS theory. Following this steep evolution, there are several scholars in the field arguing that a period of consolidation, in the sense of a refinement of and gaining experience with existing methods, should be pursued by future research.