Utilizing SEM-RFC to predict factors affecting online shopping cart abandonment during the COVID-19 pandemic
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...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-11-01
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| Series: | Heliyon |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844022025816 |
| _version_ | 1798014516576911360 |
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| author | Ardvin Kester S. Ong Marjorie Joy R. Dejucos Mary Anne F. Rivera John Vincent D.J. Muñoz Miguel S. Obed Kirstien Paola E. Robas |
| author_facet | Ardvin Kester S. Ong Marjorie Joy R. Dejucos Mary Anne F. Rivera John Vincent D.J. Muñoz Miguel S. Obed Kirstien Paola E. Robas |
| author_sort | Ardvin Kester S. Ong |
| collection | DOAJ |
| description | 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 conceptual 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 Ambivalence 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. |
| first_indexed | 2024-04-11T15:18:30Z |
| format | Article |
| id | doaj.art-ce40f32109c84114ad37bebd968ac8f1 |
| institution | Directory Open Access Journal |
| issn | 2405-8440 |
| language | English |
| last_indexed | 2024-04-11T15:18:30Z |
| publishDate | 2022-11-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj.art-ce40f32109c84114ad37bebd968ac8f12022-12-22T04:16:25ZengElsevierHeliyon2405-84402022-11-01811e11293Utilizing SEM-RFC to predict factors affecting online shopping cart abandonment during the COVID-19 pandemicArdvin Kester S. Ong0Marjorie Joy R. Dejucos1Mary Anne F. Rivera2John Vincent D.J. Muñoz3Miguel S. Obed4Kirstien Paola E. Robas5School of Industrial Engineering and Engineering Management, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines; Corresponding author.Department of Industrial Engineering, Faculty of Engineering, University of Santo Tomas, España Blvd, Manila 1015, PhilippinesDepartment of Industrial Engineering, Faculty of Engineering, University of Santo Tomas, España Blvd, Manila 1015, PhilippinesDepartment of Industrial Engineering, Faculty of Engineering, University of Santo Tomas, España Blvd, Manila 1015, PhilippinesDepartment of Industrial Engineering, Faculty of Engineering, University of Santo Tomas, España Blvd, Manila 1015, PhilippinesSchool of Industrial Engineering and Engineering Management, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, PhilippinesOnline 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 conceptual 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 Ambivalence 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.http://www.sciencedirect.com/science/article/pii/S2405844022025816Online shoppingRandom forest classifierStructural equation modelingShopping cart abandonment |
| spellingShingle | Ardvin Kester S. Ong Marjorie Joy R. Dejucos Mary Anne F. Rivera John Vincent D.J. Muñoz Miguel S. Obed Kirstien Paola E. Robas Utilizing SEM-RFC to predict factors affecting online shopping cart abandonment during the COVID-19 pandemic Heliyon Online shopping Random forest classifier Structural equation modeling Shopping cart abandonment |
| title | Utilizing SEM-RFC to predict factors affecting online shopping cart abandonment during the COVID-19 pandemic |
| title_full | Utilizing SEM-RFC to predict factors affecting online shopping cart abandonment during the COVID-19 pandemic |
| title_fullStr | Utilizing SEM-RFC to predict factors affecting online shopping cart abandonment during the COVID-19 pandemic |
| title_full_unstemmed | Utilizing SEM-RFC to predict factors affecting online shopping cart abandonment during the COVID-19 pandemic |
| title_short | Utilizing SEM-RFC to predict factors affecting online shopping cart abandonment during the COVID-19 pandemic |
| title_sort | utilizing sem rfc to predict factors affecting online shopping cart abandonment during the covid 19 pandemic |
| topic | Online shopping Random forest classifier Structural equation modeling Shopping cart abandonment |
| url | http://www.sciencedirect.com/science/article/pii/S2405844022025816 |
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