論文アブストラクト： Nomophobia, which refers to discomfort or anxiety caused by being unable to use one's smartphone, has become prevalent among smartphone users. However, the influence of nomophobia on employees' work-related outcomes remains unclear. Drawing on the job demands-resources theory, this study develops a model that explores the interplay between employees' nomophobia, work engagement, emotional exhaustion, work interruption, and job productivity. The proposed model was tested using data collected from 187 employees in one organization. The results demonstrate that some employees with high levels of nomophobia feel more engaged with their work and more productive, yet others tend to be emotionally exhausted and feel they are less productive. By illuminating the dual effects of nomophobia on employees' work-related outcomes, this study extends our understanding of how smartphone use positively and negatively affects employees in the workplace. The notion of nomophobia in the workplace is discussed, along with new directions for research.
スマホ依存症が仕事に与える影響について187人の従業員データを元に調査． 初めて，職場でのスマホ依存症の影響を探る包括的な理論モデルを開発し， スマホ依存症の考え方とそれらに対する研究の方向性を議論．
論文アブストラクト： Information workers are experiencing ever-increasing online distractions in the workplace, and software to block distractions is becoming more popular. We conducted an exploratory field study with 32 information workers in their workplace using software to block online distractions for one week. We discovered that with online distractions blocked, participants assessed their focus and productivity to be significantly higher. Those who benefited most were those who reported being less in control of their work, associated with personality traits of lower Conscientiousness and Lack of Perseverence. Unexpectedly, those reporting higher control of work experienced a cost of higher workload with online distractions blocked. Those who reported the greatest increase in focus with distractions blocked were those who were more susceptible to social media distractions. Without distractions, people with higher control of work worked longer stretches without physical breaks, with consequently higher stress. We present design recommendations to promote focus for our observed coping behaviors.
論文アブストラクト： Design recommendations for notifications are typically based on user performance and subjective feedback. In comparison, there has been surprisingly little research on how designed notifications might be processed by the brain for the information they convey. The current study uses EEG/ERP methods to evaluate auditory notifications that were designed to cue long-distance truck drivers for task-management and driving conditions, particularly for automated driving scenarios. Two experiments separately evaluated naive students and professional truck drivers for their behavioral and brain responses to auditory notifications, which were either auditory icons or verbal commands. Our EEG/ERP results suggest that verbal commands were more readily recognized by the brain as relevant targets, but that auditory icons were more likely to update contextual working memory. Both classes of notifications did not differ on behavioral measures. This suggests that auditory icons ought to be employed for communicating contextual information and verbal commands, for urgent requests.
論文アブストラクト： Knowledge workers experience many interruptions during their work day. Especially when they happen at inopportune moments, interruptions can incur high costs, cause time loss and frustration. Knowing a person's interruptibility allows optimizing the timing of interruptions and minimize disruption. Recent advances in technology provide the opportunity to collect a wide variety of data on knowledge workers to predict interruptibility. While prior work predominantly examined interruptibility based on a single data type and in short lab studies, we conducted a two-week field study with 13 professional software developers to investigate a variety of computer interaction, heart-, sleep-, and physical activity-related data. Our analysis shows that computer interaction data is more accurate in predicting interruptibility at the computer than biometric data (74.8% vs. 68.3% accuracy), and that combining both yields the best results (75.7% accuracy). We discuss our findings and their practical applicability also in light of collected qualitative data.