A theoretical model of factors influencing online consumer purchasing behavior through electronic word of mouth data mining and analysis.

The coronavirus disease 2019 pandemic has impacted and changed consumer behavior because of a prolonged quarantine and lockdown. This study proposed a theoretical framework to explore and define the influencing factors of online consumer purchasing behavior (OCPB) based on electronic word-of-mouth (e-WOM) data mining and analysis. Data pertaining to e-WOM were crawled from smartphone product reviews from the two most popular online shopping platforms in China, Jingdong.com and Taobao.com. Data processing aimed to filter noise and translate unstructured data from complex text reviews into structured data. The machine learning based K-means clustering method was utilized to cluster the influencing factors of OCPB. Comparing the clustering results and Kotler's five products level, the influencing factors of OCPB were clustered around four categories: perceived emergency context, product, innovation, and function attributes. This study contributes to OCPB research by data mining and analysis that can adequately identify the influencing factors based on e-WOM. The definition and explanation of these categories may have important implications for both OCPB and e-commerce.

Impact of improved stroke green channel process on the delay of intravenous thrombolysis in patients with acute cerebral infarction during the COVID-19 pandemic: An observational study

Objective This study analyzed the impact of the improved stroke green channel process on the delay of intravenous thrombolysis in patients with acute cerebral infarction under coronavirus disease 2019 (COVID-19) prevention and control measures. Methods We included 57 patients from the stroke center of the Seventh People's Hospital of Shanghai University of Traditional Chinese Medicine before the improvement of the stroke green channel process (March–July 2019), as well as 94 patients during the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreak (March–July 2020) and 68 patients during the Omicron variant outbreak (March–July 2022) after the improvement of stroke green channel process. The door-to-needle time (DNT), door-to-imaging time (DIT), and door-to-test completion time were compared among the three groups. We analyzed the impact of this process improvement in the emergency green channel during the pandemic on the delay of intravenous thrombolysis. Results This study included a total of 229 patients with acute cerebral infarction who went through the green channel for intravenous thrombolysis (57 in the pre-pandemic group, 94 in the SARS-CoV-2 outbreak group, and 68 in the Omicron outbreak group). The percentages of patients undergoing intravenous thrombolysis in the pre-pandemic, SARS-CoV-2 outbreak, and Omicron outbreak groups differed significantly (19.32%, 22.27%, and 28.94%, respectively, P = 0.029). Compared to the pre-pandemic group, the National Institutes of Health Stroke Scale (NIHSS) score at admission was significantly higher in the Omicron outbreak group (7.71 ± 7.36 in the Omicron outbreak group vs. 5.00 ± 4.52 in the pre-pandemic group) (P = 0.026) but not in the SARS-CoV-2 outbreak group (4.79 ± 5.94 in the SARS-CoV-2 outbreak group vs. 5.00 ± 4.52 in the pre-pandemic group, P = 0.970). Significantly higher proportions of patients undergoing emergency intravenous thrombolysis came to the hospital by ambulance in the SARS-CoV-2 and Omicron outbreak groups compared to the pre-pandemic group (38.6% in the pre-pandemic group, 51.1% in the SARS-CoV-2 outbreak group, and 82.4% in the Omicron outbreak group, P < 0.001). Compared to the pre-pandemic group, the DIT was significantly higher in the SARS-CoV-2 outbreak group (22.42 ± 7.62 min in the SARS-CoV-2 outbreak group vs. 18.91 ± 8.23 min in the pre-pandemic group, P =0.031) but not the Omicron outbreak group (20.35 ± 10.38 min in the Omicron outbreak group vs. 18.91 ± 8.23 min in the pre-pandemic group, P = 0.543). The door-to-test completion time was significantly longer in the SARS-CoV-2 and Omicron outbreak groups compared to that in the pre-pandemic group (78.37 ± 25.17 min in the SARS-CoV-2 outbreak group, 92.60 ± 25.82 min in the Omicron outbreak group vs. 65.11 ± 22.35 min in the pre-pandemic group, P < 0.001);however, the DNT in the SARS-CoV-2 and Omicron outbreak groups did not differ significantly from those in the pre-pandemic group (both P > 0.05). Conclusion During the two periods of the COVID-19 outbreak (SARS-CoV-2 and Omicron), after the improvement of the green channel for intravenous thrombolysis, there might be some delay in in-hospital DIT during the SARS-CoV-2 outbreak, however, the in-hospital delay indicator DNT for intravenous thrombolysis were not affected.