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The purpose of this paper is to characterize distracted driving by quantifying the response time and response intensity to an emergency stop using the driver’s physiological states.

Field tests with 17 participants were conducted in the connected and automated vehicle test field. All participants were required to prioritize their primary driving tasks while a secondary nondriving task was asked to be executed. Demographic data, vehicle trajectory data and various physiological data were recorded through a biosignalsplux signal data acquisition toolkit, such as electrocardiograph for heart rate, electromyography for muscle strength, electrodermal activity for skin conductance and force-sensing resistor for braking pressure.

This study quantified the psychophysiological responses of the driver who returns to the primary driving task from the secondary nondriving task when an emergency occurs. The results provided a prototype analysis of the time required for making a decision in the context of advanced driver assistance systems or for rebuilding the situational awareness in future automated vehicles when a driver’s take-over maneuver is needed.

The hypothesis is that the secondary task will result in a higher mental workload and a prolonged reaction time. Therefore, the driver states in distracted driving are significantly different than in regular driving, the physiological signal improves measuring the brake response time and distraction levels and brake intensity can be expressed as functions of driver demographics. To the best of the authors’ knowledge, this is the first study using psychophysiological measures to quantify a driver’s response to an emergency stop during distracted driving.

The purpose of the research is to investigate users’ adoption of blockchain-based games in China.

This research applied existing technology diffusion theories to develop a research model to examine users’ adoption of blockchain-based games. As a result, a research model with nine research hypotheses was developed. The developed research model was empirically tested using data collected from a survey of 210 blockchain-based games users. Structural equation modeling was applied to analyse the collected data.

The results indicated that seven of nine research hypotheses were supported. It was found that trust, perceived usefulness, perceived enjoyment and perceived ease of use were key determinants for users’ behavioural intention to use blockchain-based games. The most influential relationship in the research model appeared to be the effect of perceived usefulness on users’ behavioural intention to use blockchain-based games. However, subjective norms did not have significant positive impacts on users’ behavioural intention to use blockchain-based games.

The regulatory support from governmental authorities is essential to provide additional legal certainty to build users’ trust in playing blockchain-based games. Blockchain-based games providers should arrange the training program targeted to the general users to enhance their understanding of the key features associated with blockchain-based games. Blockchain-based games developers should come up with good design solutions to maximize user enjoyment with blockchain-based games by considering additional entertainment elements.

To the best of the authors’ knowledge, this study is first of its kind in investigating the adoption of blockchain-based games from users’ perspectives. This study contributes to the existing literature on the adoption of blockchain technology.