NeuroIS—Alternative or Complement to Existing Methods? Illustrating the Holistic Effects of Neuroscience and Self-Reported Data in the Context of Technostress Research

Abstract

Recent research has made a strong case for the importance of NeuroIS methods for IS research. It has suggested that NeuroIS contributes to an improved explanation and prediction of IS phenomena. Yet, such research is unclear on the source of this improvement; while some studies indicate that NeuroIS constitutes an alternative to psychometrics, implying that the two methods assess the same dimension of an underlying IS construct, other studies indicate that NeuroIS constitutes a complement to psychometrics, implying that the two methods assess different dimensions of an IS construct. To clarify the role of NeuroIS in IS research and its contribution to IS research, in this study, we examine whether NeuroIS and psychometrics/psychological methods constitute alternatives or complements. We conduct this examination in the context of technostress, an emerging IS phenomenon to which both methods are relevant. We use the triangulation approach to explore the relationship between physiological and psychological/self-reported data. Using this approach, we argue that both kinds of data tap into different aspects of technostress and that, together, they can yield a more complete or holistic understanding of the impact of technostress on a theoretically-related outcome, rendering them complements. Then, we test this proposition empirically by probing the correlation between a psychological and a physiological measure of technostress in combination with an examination of their incremental validity in explaining performance on a computer-based task. The results show that the physiological stress measure (salivary alpha-amylase) explains and predicts variance in performance on the computer-based task over and above the prediction afforded by the self-reported stress measure. We conclude that NeuroIS is a critical complement to IS research.

The technostress trifecta ‐ techno eustress, techno distress and design: Theoretical directions and an agenda for research

“…Job-related outcomes include lack of job Barley et al, 2011Chen, Westman, & Eden, 2009Korunka & Vitouch, 1999Tarafdar, Tu, & Ragu-Nathan, 2010 Outcomes (also referred to as "strain") Barley et al, 2011Brown, Duck, & Jimmieson, 2014Chen et al, 2009Day et al, 2012Galluch et al, 2015Korunka & Vitouch, 1999Maier et al, 2015Reinke & Chamorro-Premuzic, 2014Srivastava, Chandra, & Shirish, 2015Sykes, 2015Zhang et al, 2016 Physiological outcomes, eg, stress hormones Galluch et al, 2015Tams, Hill, de Guinea, Thatcher, & Grover, 2014 satisfaction and organizational commitment, turnover intentions, role overload, role conflict (Ragu-Nathan et al, 2008;Tarafdar et al, 2007), job-related anxiety, and depression (Sprigg & Jackson, 2006). They have also been referred to as "strain."…”

The role of information systems research in shaping the future of information privacy

“…Neuro IS and neuroimaging techniques (e.g. Dimoka et al, 2011;Dimoka et al 2012;Gregor et al, 2014;Riedl et al, 2014;Tams et al, 2014) could be used to study why individuals actually behave the way they do when their information privacy is concerned. • Information privacy outcomes.…”

What Does the Skin Tell Us About Information Systems Usage? A Literature-Based Analysis of the Utilization of Electrodermal Measurement for IS Research

“…also indicate stress [19,20] Over the last years several investigations within IS research examine the antecedents and consequences of technology-related stress named technostress [21][22][23][24][25][26][27][28]. However, besides two examinations [8,9], most of these investigations only measure technostress perceptive rather than applying physiopychological methods such as EDA, although a current investigation reveals that physiological stress measurements and self-reported measurements measure two disjoint phenomena [29]. Hence, applying EDA in this context might enable us to obtain the following: 1.…”