Hariharan, Anuja, Adam, Marc T.P., Dorner, Verena, Lux, Ewa, Mueller, Marius B., Pfeiffer, Jella, Weinhardt, Christof. 2017. Brownie: A Platform for Conducting NeuroIS Experiments. Journal of Association of Information Systems. 18 (4), 264-296.

RIS

@ARTICLE{Hariharan2017,
title = {Brownie: A Platform for Conducting NeuroIS Experiments},
author = {Anuja Hariharan and Marc T.P. Adam and Verena Dorner and Ewa Lux and Marius B. Mueller and Jella Pfeiffer and Christof Weinhardt},
year = {2017},
doi = {http://dx.doi.org/10.17705/1jais.00457},
volume = {18},
number = {4},
language = {EN},
pages = {264-296},
journal = {Journal of the Association for Information Systems (JAIS)},
abstract = {In the NeuroISfield, experimental software needs to simultaneously present experimental stimuli to participants while recording, analyzing, or displaying neurophysiological measures. For example, a researchermight record a user’s heart beat (neurophysiological measure) asthe userinteracts with an e-commerce website (stimulus) to track changes in user arousalorshowa user’schanging arousal levels during an exciting game. In this paper, we identify requirements for a NeuroISexperimental platform that we call Brownie and present its architecture and functionality. We then evaluate Brownie viaa literature review and a case study that demonstrates Brownie’s capability to meet the requirements in a complex research context. We also verify Brownie’susabilityviaa quantitative study with prospective experimenters who implemented a test experiment in Brownie and an alternative software. We summarize the salient features of Brownie as follows: 1) it integrates neurophysiological measurements, 2) it incorporatesreal-time processing of neurophysiological data, 3i) it facilitates research on individual and group behavior in the lab, 4) it offers a large variety of options for presenting experimental stimuli, and 5) it is opensource and easily extensible with opensource libraries. In summary, we conclude that Brownie is innovativein its potential to reduce barriers for IS researchers by fostering replicability and research collaborationand to supportNeuroISand interdisciplinary research in cognate areas, such as management, economics, or human-computer interaction.},
}