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Factors affecting adoption of product virtualization technology for online consumer electronics shopping
Abstract
Purpose The purpose of this paper is to investigate the factors affecting the adoption of product virtualization technology (PVT) for online shopping small consumer electronics by applying a modified electronic technology acceptance model (e‐TAM) and tested model invariance male/female shoppers in the overall adoption process. Design/methodology/approach Online surveys are completed by a US national panel of online shoppers. The data are analyzed using single‐ and multiple‐group structural equation modelling. Findings The results provide empirical support for e‐TAM in the context of PVT acceptance for online small consumer electronics shopping. In addition, two external constructs – technology anxiety (TA) and innovativeness (INN) – show significant influences on the beliefs (perceived usefulness, ease‐of‐use and entertainment value). There is no significant gender difference in the overall adoption process of PVT. Research limitations/implications More specific consumer characteristics such as time‐consciousness, opinion leadership or age differences under different categories may be useful to investigate. Practical implications PVT may provide a valuable tool that online retailers can use to enhance their consumers' purchase behaviour, either by reducing the perceived risk through better online product evaluation or by enhancing consumers' enjoyment of the shopping process on their web site by increasing the number of unique and repeat traffic visitors to the site and ultimately establish an online competitive advantage. Originality/value Inclusion of TA and INN in e‐TAM for PVT acceptance and the equivalence test of the hypothesized model across gender make the research unique, adding to the explanatory and predictive power of the e‐TAM.
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“Lots of empirical research has found the negative linkage between perceived risk and user satisfaction [64,66,98].”
From Investigating the Impact of Critical Factors on Continuance Intention towards Cross-Border Shopping Websites (2019) · cites this paper as [64]
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“Di erent types of risks are involved in online transactions, which will impact consumers' purchase behavior [64].”
From Investigating the Impact of Critical Factors on Continuance Intention towards Cross-Border Shopping Websites (2019) · cites this paper as [64]
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Metadata
- Authors
- Kim, J., & Forsythe, S.
- Affiliations
- University of South Carolina (US)
- Auburn University (US)
- ORCID
- Kim, Jiyeon
- Venue
- International Journal of Retail & Distribution Management
- Publisher
- Emerald
- Published
- 2010-03-16
- Volume
- 38
- Issue
- 3
- Pages
- 190-204
- ISSN
- 0959-0552 (ISSN-L)
- OpenAlex
- W1972912785
- Cited by
- 150
- References
- 53
- Citations by year
- 2026: 2 · 2025: 3 · 2024: 5 · 2023: 13 · 2022: 13 · 2021: 16 · 2020: 13 · 2019: 14 · 2018: 10 · 2017: 10 · 2016: 13 · 2015: 5 · 2014: 13 · 2013: 5 · 2012: 11
- FWCI
- 14.20
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- International Journal of Retail & Distribution Management (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Social Sciences › Business, Management and Accounting › Marketing › Consumer Behavior and Marketing Influence
- Health Sciences › Health Professions › Health Information Management › Health, Technology, Consumer Behavior
- Keywords
- technology adoption, technology anxiety, consumer innovativeness, perceived usefulness, perceived ease of use, entertainment value, gender differences, online shopping, risk perception
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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