| Title |
Utilizing SEM-RFC to predict factors affecting online shopping cart abandonment during the COVID-19 pandemic |
| ID_Doc |
74146 |
| Authors |
Ong, AKS; Dejucos, MJR; Rivera, MAF; Muñoz, JVDJ; Obed, MS; Robas, KPE |
| Title |
Utilizing SEM-RFC to predict factors affecting online shopping cart abandonment during the COVID-19 pandemic |
| Year |
2022 |
| Published |
Heliyon, 8, 11 |
| DOI |
10.1016/j.heliyon.2022.e11293 |
| Abstract |
Online shopping has accelerated during to the pandemic and an increase in online shopping cart abandonment (SCA) was also evident. The growth of online shopping is contributed by the rising middle class, high consumer spending, millennials, and a tech-savvy population which is valuable to the growth of e-commerce. This study aimed to predict the factors that affect SCA during the COVID-19 Pandemic utilizing the SEM-RFC hybrid. Several factors such as self-efficacy, attribute conflicts, hesitation at checkout, emotional ambivalence, choice process satisfaction, attitude, subjective norms, and perceived behavioral control were analyzed simultaneously. This study integrated the cognition-affect-behavior paradigm with the Theory of Planned Behavior to provide a con-ceptual framework measured through an online survey questionnaire answered by 1015 valid responses collected by convenience sampling. Results showed that Attitude, Attribute Conflict, Self-Efficacy, and Emotional Ambiv-alence are the primary significant factors affecting SCA. Amidst the pandemic, consumers still value the ease of use, convenience and safety of the mobile online shopping applications that they have, which they do not positively experience at this time. The findings of this study may be applied and extended by researchers, online retailers, and businesses to understand consumer's abandonment intentions. Moreover, the results and framework of this study may be capitalized on by the business sector to create marketing strategies and develop business models for a sustainable online shopping business worldwide. |
| Author Keywords |
Online shopping; Random forest classi fier; Structural equation modeling; Shopping cart abandonment |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:000883109400011 |
| WoS Category |
Multidisciplinary Sciences |
| Research Area |
Science & Technology - Other Topics |
| PDF |
https://doi.org/10.1016/j.heliyon.2022.e11293
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