Start Date
12-16-2013
Description
The core objective of this study is to understand individuals IS usage by going beyond the traditional subjective self-reported and objective system-log measures to unveil the delicate process through which users interact with IS. In this study, we conducted a laboratory experiment to capture users’ eye movement and, more importantly, applied a novel methodology that uses the Gaussian mixture model (GMM) to analyze the gathered physiological data. We also examine how performance pressure and prior usage experience of the investigative system affect IS usage patterns. Our results suggest that experienced and pressured users demonstrate more efficient and focused usage patterns than inexperienced and non-pressured ones, respectively. Our findings constitute an important advancement in the IS use literature. The proposed statistical approach for analyzing eye-movement data is a critical methodological contribution to the emerging research that uses eye-tracking technology for investigation.
Recommended Citation
Eckhardt, Andreas; Maier, Christian; HSIEH, JJ; Chuk, Tim; Chan, Antoni; Hsiao, Janet; and Buettner, Ricardo, "Objective measures of IS usage behavior under conditions of experience and pressure using eye fixation data" (2013). ICIS 2013 Proceedings. 26.
https://aisel.aisnet.org/icis2013/proceedings/HumanBehavior/26
Objective measures of IS usage behavior under conditions of experience and pressure using eye fixation data
The core objective of this study is to understand individuals IS usage by going beyond the traditional subjective self-reported and objective system-log measures to unveil the delicate process through which users interact with IS. In this study, we conducted a laboratory experiment to capture users’ eye movement and, more importantly, applied a novel methodology that uses the Gaussian mixture model (GMM) to analyze the gathered physiological data. We also examine how performance pressure and prior usage experience of the investigative system affect IS usage patterns. Our results suggest that experienced and pressured users demonstrate more efficient and focused usage patterns than inexperienced and non-pressured ones, respectively. Our findings constitute an important advancement in the IS use literature. The proposed statistical approach for analyzing eye-movement data is a critical methodological contribution to the emerging research that uses eye-tracking technology for investigation.