| Abstract |
The COVID-19 pandemic has influenced many movements of rapid digitization in several sectors/areas used by the public. The three primary sectors/areas affected by such digitization process are identified as healthcare, transportation, and public domain registration. There are only a few studies investigating the impacts of the COVID-19 pandemic on the digital divide for the expatriate population. To fill this research gap, this study investigates these three primary sectors/areas while highlighting the growing digital divide in the expatriate population, using Chinese cities as case studies. The study finds that the emerging barrier is beyond language barriers related to digital access and utilization issues. The study finds that the ongoing digital inequality is related to the autonomy of use, suggesting the urgency for technological upgrades, inclusive digital platforms, and reversing digital design marginalization. This study is sample-based research, using limited samples of expatriate populations in nine major cities in three primary economic clusters in China. The user perspective is assessed against five digital inequalities, namely “technical means,” “autonomy of use,” “social support networks,” “experience,” and “skills.” The analysis is followed by further research on digital divide barriers, addressing how the newly installed digital devices/facilities/services affect the expatriate population beyond the traditional language barriers. The analysis evaluates challenges based on four DDB pillars (i.e., availability, access, renovation, and utilization) and language barrier. The findings show the high correlation between the autonomy of use and digital utilization has led to further disparities and disconnection of the expatriate population from the smart city movements, such as digitized healthcare, transportation, and public domain registration. This study contributes to digital divide research, enhancing awareness of such research related to technological/digital changes and the expatriate populations. © The Author(s) 2024. |
