Impacts of Health and Safety Concerns on E-Commerce and Service Reconfiguration During the COVID-19 Pandemic: Insights from an Emerging Economy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The COVID-19 pandemic has brought unprecedented growth to the e-commerce industry, triggering widespread digital service transformation across various business segments in Vietnam. A pressing concern for both businesses and policymakers is whether the sudden peak in customer interest in e-commerce can be sustained in the future. This research seeks to address this concern by considering whether and how customers’ motivations to participate in e-commerce activities have changed. We collected primary data from a self-administered survey to empirically examine how health and safety concerns influence customers’ online shopping behavior during the pandemic, alongside other known determinants for e-commerce participation, namely technology readiness and connectedness. The results confirm that health and safety concerns have a positive influence on customers’ usage of e-commerce after controlling for technology readiness and connectedness. Furthermore, customers in age groups with higher risks of severe COVID-19 symptoms and mortality are more likely to increase e-commerce usage during the social distancing and isolation period. Our results support the idea that the customer base for e-commerce and digital services have expanded beyond the typical tech-savvy and young customers in their twenties. These are promising signs for postpandemic recovery and even expansion, as firms may leverage the momentum of change in customers’ motivations and start tailoring their public relation campaigns to address a wider age range of potential consumers.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it