The Impact of Signals Transmission on Patients’ Choice through E-Consultation Websites
An Econometric Analysis of Secondary Datasets
Bibliographic Data
| ID | 15479243 |
|---|---|
| Authors | Adnan Muhammad Shah (0000-0002-9638-3514, Information Technology University, corresponding author), Rizwan Ali Naqvi (0000-0002-7473-8441, Sejong University), Ok-Ran Jeong (Gachon University, corresponding author) |
| Year | 2021 |
| Volume | 18 |
| Issue | 10 |
| Pages | 5192-5192 |
| Publication date | 2021-05-13 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | International Journal of Environmental Research and Public Health (JOURNAL) |
| Journal identifiers | ISSN: 1661-7827 • E-ISSN: 1660-4601 |
| Publisher | Multidisciplinary Digital Publishing Institute (PUBLISHER • CH) |
| DOI | 10.3390/ijerph18105192 |
| PMID | 34068291 |
| OpenAlex | W3160377831 |
| Language | EN |
| Citations received | 7 |
| References cited | 66 |
(1) Background: The COVID-19 pandemic has dramatically and rapidly changed the overall picture of healthcare in the way how doctors care for their patients. Due to the significant strain on hospitals and medical facilities, the popularity of web-based medical consultation has drawn the focus of researchers during the deadly coronavirus disease (COVID-19) in the United States. Healthcare organizations are now reacting to COVID-19 by rapidly adopting new tools and innovations such as e-consultation platforms, which refer to the delivery of healthcare services digitally or remotely using digital technology to treat patients. However, patients' utilization of different signal transmission mechanisms to seek medical advice through e-consultation websites has not been discussed during the pandemic. This paper examines the impact of different online signals (online reputation and online effort), offline signals (offline reputation) and disease risk on patients' physician selection choice for e-consultation during the COVID-19 crisis. (2) Methods: Drawing on signaling theory, a theoretical model was developed to explore the antecedents of patients' e-consultation choice toward a specific physician. The model was tested using 3-times panel data sets, covering 4231 physicians on Healthgrades and Vitals websites during the pandemic months of January, March and May 2020. (3) Results: The findings suggested that online reputation, online effort and disease risk were positively related to patients' online physician selection. The disease risk has also affected patients' e-consultation choice. A high-risk disease positively moderates the relationship between online reputation and patients' e-consultation choice, which means market signals (online reputation) are more influential than seller signals (offline reputation and online effort). Hence, market signals strengthened the effect in the case of high-risk disease. (4) Conclusions: The findings of this study provide practical suggestions for physicians, platform developers and policymakers in online environments to improve their service quality during the crisis. This article offers a practical guide on using emerging technology to provide virtual care during the pandemic. This study also provides implications for government officials and doctors on the potentials of consolidating virtual care solutions in the near future in order to contribute to the integration of emerging technology into healthcare
Econometric analysis · Econometric model · Econometrics · Economics · Telecommunications · Transmission (telecommunications · Computer Science · Customer Service Quality and Loyalty · Digital Marketing and Social Media · Medicine · Psychology · Technology Adoption and User Behaviour
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| Citations per year | 1.4 |
|---|---|
| Citation span | 2021 - 2026 (6) |
| Highly cited | No |