Previous studies have identified trust as one of the key factors in the technology acceptance of autonomousvehicles. As these studies mostly investigated the population in general, little is known about segment-specif...Previous studies have identified trust as one of the key factors in the technology acceptance of autonomousvehicles. As these studies mostly investigated the population in general, little is known about segment-specific differences.Furthermore, the widely used survey methods are less able to capture the deeper forms of trust—which neuroscientificmethods are much better suited to capture. The main objective of our research is to study trust as one of the key factors oftechnology acceptance related to autonomous vehicles by using neuroscientific methods for specific consumer segments.Real-time eye-tracking tests were applied to a sample of 113 participants, combined with a posttest self-report. The testswere carried out under laboratory conditions during which our subjects watched videos recorded with the internal camerasof autonomous vehicles. Based on the fixation count, total fixation duration, and pupil dilation, we empirically verified thatthe trust level of all five identified segments is relatively low, while the trust level of the “traditional rejecting” segment is thelowest. An increase in trust level can be shown if the subjects receive extra information about the journey. Anotherimportant finding is that the self-reported trust level is not always congruent with the eye-tracking analysis results;therefore,combined approaches can lead to greater measurement validity.展开更多
基金the National Research,Development and Innovation Office–NKFIH,OTKA K137571.
文摘Previous studies have identified trust as one of the key factors in the technology acceptance of autonomousvehicles. As these studies mostly investigated the population in general, little is known about segment-specific differences.Furthermore, the widely used survey methods are less able to capture the deeper forms of trust—which neuroscientificmethods are much better suited to capture. The main objective of our research is to study trust as one of the key factors oftechnology acceptance related to autonomous vehicles by using neuroscientific methods for specific consumer segments.Real-time eye-tracking tests were applied to a sample of 113 participants, combined with a posttest self-report. The testswere carried out under laboratory conditions during which our subjects watched videos recorded with the internal camerasof autonomous vehicles. Based on the fixation count, total fixation duration, and pupil dilation, we empirically verified thatthe trust level of all five identified segments is relatively low, while the trust level of the “traditional rejecting” segment is thelowest. An increase in trust level can be shown if the subjects receive extra information about the journey. Anotherimportant finding is that the self-reported trust level is not always congruent with the eye-tracking analysis results;therefore,combined approaches can lead to greater measurement validity.
