Elderly Consumers' Online Grocery Shopping Continuance After COVID-19: A Combined Importance-Performance Map Analysis (cIPMA) Method.
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| Title: | Elderly Consumers' Online Grocery Shopping Continuance After COVID-19: A Combined Importance-Performance Map Analysis (cIPMA) Method. |
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| Authors: | Mohd-Any, Amrul Asraf (AUTHOR), Sarker, Moniruzzaman (AUTHOR), Bu, Zhenni (AUTHOR), Mahdzan, Nurul Shahnaz (AUTHOR) |
| Source: | International Journal of Human-Computer Interaction. Dec2025, Vol. 41 Issue 23, p15245-15261. 17p. |
| Subjects: | Older consumers, Online shopping, COVID-19, Expectancy-value theory, Customer loyalty, Consumer protection, Social network theory, Consumer behavior |
| Geographic Terms: | China |
| Abstract: | As the global population ages, China—home to the world's largest ageing population—experienced a notable surge in online grocery shopping (OGS) among the elderly during the COVID-19 pandemic. However, concerns remain about whether this trend will persist post-pandemic and what strategies could sustain this market. Based on 284 responses analysed using PLS-SEM, our findings reveal that consumer trust, return policy leniency, performance expectancy, imitating others, and effort expectancy positively influence the intention to continue purchasing groceries online. In contrast, facilitating conditions do not significantly impact continuance intention, while social influence is marginally insignificant. Fear of COVID-19 negatively affects the intention to continue. We propose that signalling theory offers stronger explanatory power than UTAUT and herding behaviour in predicting elderly consumers' OGS continuance intention. Building trust through user-friendly, straightforward platforms and flexible return policies may be an effective strategy to motivate and sustain elderly consumers' long-term engagement with OGS platforms. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Human-Computer Interaction is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Psychology and Behavioral Sciences Collection |
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| Header | DbId: pbh DbLabel: Psychology and Behavioral Sciences Collection An: 189570820 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Elderly Consumers' Online Grocery Shopping Continuance After COVID-19: A Combined Importance-Performance Map Analysis (cIPMA) Method. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Mohd-Any%2C+Amrul+Asraf%22">Mohd-Any, Amrul Asraf</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Sarker%2C+Moniruzzaman%22">Sarker, Moniruzzaman</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Bu%2C+Zhenni%22">Bu, Zhenni</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Mahdzan%2C+Nurul+Shahnaz%22">Mahdzan, Nurul Shahnaz</searchLink> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Human-Computer+Interaction%22">International Journal of Human-Computer Interaction</searchLink>. Dec2025, Vol. 41 Issue 23, p15245-15261. 17p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Older+consumers%22">Older consumers</searchLink><br /><searchLink fieldCode="DE" term="%22Online+shopping%22">Online shopping</searchLink><br /><searchLink fieldCode="DE" term="%22COVID-19%22">COVID-19</searchLink><br /><searchLink fieldCode="DE" term="%22Expectancy-value+theory%22">Expectancy-value theory</searchLink><br /><searchLink fieldCode="DE" term="%22Customer+loyalty%22">Customer loyalty</searchLink><br /><searchLink fieldCode="DE" term="%22Consumer+protection%22">Consumer protection</searchLink><br /><searchLink fieldCode="DE" term="%22Social+network+theory%22">Social network theory</searchLink><br /><searchLink fieldCode="DE" term="%22Consumer+behavior%22">Consumer behavior</searchLink> – Name: SubjectGeographic Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22China%22">China</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: As the global population ages, China—home to the world's largest ageing population—experienced a notable surge in online grocery shopping (OGS) among the elderly during the COVID-19 pandemic. However, concerns remain about whether this trend will persist post-pandemic and what strategies could sustain this market. Based on 284 responses analysed using PLS-SEM, our findings reveal that consumer trust, return policy leniency, performance expectancy, imitating others, and effort expectancy positively influence the intention to continue purchasing groceries online. In contrast, facilitating conditions do not significantly impact continuance intention, while social influence is marginally insignificant. Fear of COVID-19 negatively affects the intention to continue. We propose that signalling theory offers stronger explanatory power than UTAUT and herding behaviour in predicting elderly consumers' OGS continuance intention. Building trust through user-friendly, straightforward platforms and flexible return policies may be an effective strategy to motivate and sustain elderly consumers' long-term engagement with OGS platforms. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of International Journal of Human-Computer Interaction is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=pbh&AN=189570820 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1080/10447318.2025.2495835 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 17 StartPage: 15245 Subjects: – SubjectFull: Older consumers Type: general – SubjectFull: Online shopping Type: general – SubjectFull: COVID-19 Type: general – SubjectFull: Expectancy-value theory Type: general – SubjectFull: Customer loyalty Type: general – SubjectFull: Consumer protection Type: general – SubjectFull: Social network theory Type: general – SubjectFull: Consumer behavior Type: general – SubjectFull: China Type: general Titles: – TitleFull: Elderly Consumers' Online Grocery Shopping Continuance After COVID-19: A Combined Importance-Performance Map Analysis (cIPMA) Method. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Mohd-Any, Amrul Asraf – PersonEntity: Name: NameFull: Sarker, Moniruzzaman – PersonEntity: Name: NameFull: Bu, Zhenni – PersonEntity: Name: NameFull: Mahdzan, Nurul Shahnaz IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 12 Text: Dec2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 10447318 Numbering: – Type: volume Value: 41 – Type: issue Value: 23 Titles: – TitleFull: International Journal of Human-Computer Interaction Type: main |
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