ABSTRACT
Artificial intelligence (AI) has revolutionized the medical industry in the decade. It is critical to integrate human–computer interaction into daily clinic service and further increase the public acceptance of medical AI. Based on self-categorization theory, our research draws on speciesism as a vital cognitive factor to examine how patients' speciesism affects their acceptance of medical AI in different roles. The study adopted a positivist research paradigm by examining 249 samples of data collected during COVID-19 in China. The results indicate that patients with higher speciesism tend to have lower acceptance of medical AI in an independent role but higher acceptance in an assistive role. Furthermore, we verified the mediating effect of human–computer trust and the positive moderating role of human uniqueness perception. This article expands the practicality of speciesism from human–animal relationships into human–AI relationships and contributes to human–computer interaction from the perspective of medical AI acceptance. © 2023 Taylor & Francis Group, LLC.
ABSTRACT
After the COVID-19 pandemic began in 2020, Urumqi, a remote area in northwest China, experienced two lockdowns, in January and July 2020. Based on ground and satellite observations, this study assessed the impacts of these lockdowns on the air quality in Urumqi and the seasonal differences between them. The results showed that, during the wintertime lockdown, PM10, PM2.5, NO2, CO, and SO2 levels decreased by 38, 40, 45, 27, 8%, respectively, whereas O-3 concentrations increased by 113%. During the summer lockdown, PM10, PM2.5, NO2, CO, and SO2 levels decreased by 39, 24, 59, 2, and 13%, respectively, and the O-3 concentrations increased by 21%. During the lockdowns, the NO2 concentrations decreased by 53% in winter and 13% in summer in the urban areas, whereas they increased by 23% in winter and 9% in summer in the suburbs. Moreover, large seasonal differences were observed between winter and summer SO2, CO, and O-3. The lockdown played a vital role in the rapid decline of primary air pollutant concentrations, along with fewer meteorological impacts on air pollution changes in this area. The increase in O-3 concentrations during the COVID-19 lockdowns reflects the complexity of air quality changes during reductions in air pollutant emissions.
ABSTRACT
During the COVID-19 crisis, telecommuting has gradually attracted the public's attention. Past studies on the subject have produced inconsistent findings, suggesting that telecommuting can lead to simultaneous benefits and drawbacks. To discuss the deeper reasons for this finding, we divided telecommuting into two types-voluntary and involuntary telecommuting. Based on the job demands-resources model, we explored the impact of voluntary-involuntary telecommuting on employee innovative behaviour through co-worker emotional support, and we examined the cross-level moderating effect of organisational identification. Using the daily diary method, we collected 455 valid observations from 65 employees for eight consecutive days. The results show that compared with involuntary telecommuting, voluntary telecommuting leads to more co-worker emotional support, in a mediating role, and employee innovative behaviour. Furthermore, a high level of organisational identification enlarges the difference in co-worker emotional support for employees voluntarily or involuntarily telecommuting. Our results uncover those differences and fill the research gap on telecommuter motivation.