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Purpose -This paper aims to examine the joint effect of power and gender on individuals' perceptions and evaluations of information systems (IS), and their behavioral intentions of technology acceptance. Design/methodology/approach -This study uses a 2 (powerful vs powerless) ϫ 2 (female vs male) between-subject experimental design. A total of 128 subjects participated in the experiment. Findings -The results suggest that there is a significant gender difference in terms of technology acceptance in the high-power condition. Further, such a gender difference is attenuated in the low-power condition. Specifically, when primed with the feeling of powerful, male users (vs female users) have higher computer self-efficacy and rate the IS as easier to use and more enjoyable. However, when the feeling of powerless was elicited, the effect of gender on technology acceptance disappeared. Originality/value -The gender effect on technology acceptance has been widely studied. The current research extends the literature by considering the moderating effect of power on such a gender effect.

Research shows aconsistent racial disparity in obesity between white and black adults in the United States. Accounting for the disparity is a challenge given the variety of the contributing factors, the nature of the association, and the multilevel relationships among the factors. We used the multivariable mediation analysis (MMA) method to explore the racial disparity in obesity considering not only the individual behavior but also geospatially derived environmental risk factors. Results from generalized linear models (GLM) were compared with those from multiple additive regression trees (MART) which allow for hierarchical data structure, and fitting of nonlinear and complex interactive relationships. As results, both individual and geographically defined factors contributed to the racial disparity in obesity. MART performed better than GLM models in that MART explained a larger proportion of the racial disparity in obesity. However, there remained disparities that cannot be explained by factors collected in this study.

Background and aimsNumerous studies have shown that people who have Internet addiction (IA) are more likely to experience poor sleep quality than people who do not. However, few studies have explored mechanisms underlying the relation between IA and poor sleep quality. As a first attempt to address this knowledge gap, a cross-sectional design was applied, and structural equation modeling was used to explore the direct relationship between IA and poor sleep quality, as well as the potential mediating roles of rumination and bedtime procrastination.MethodsA convenience sample, consisting of 1,104 Chinese University students (696 females or 63%), completed an online survey that included the following measures: Young’s 8-item Internet Addiction Diagnosis Questionnaire, the Pittsburgh Sleep Quality Index, the Ruminative Responses Scale, and the Bedtime Procrastination Scale.ResultsWhile the direct path between IA and poor sleep quality was not found to be significant, rumination and bedtime procrastination were each shown to separately mediate the predictive effect of IA on poor sleep quality. However, the greatest level of support was found for the sequential mediating effects of rumination and bedtime procrastination between IA and poor sleep quality.ConclusionWhile rumination and bedtime procrastination were both shown to be important independent mediators for the relation between IA and poor sleep quality, their combined effect was as great as either alone.

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