Reflective-Formative Hierarchical Component Model for Characteristic-Adoption Model
Bibliographic Data
| ID | 16911434 |
|---|---|
| Authors | Stany Wee Lian Fong (0000-0001-5421-1485, Multimedia University, corresponding author), Hishamuddin Ismail (0000-0001-8296-0125, Multimedia University), Hishamuddin bin Ismail, Tan Pei Kian (0000-0001-5945-7644, Multimedia University) |
| Year | 2023 |
| Volume | 13 |
| Issue | 2 |
| Publication date | 2023-04-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | SAGE Open (JOURNAL) |
| Journal identifiers | ISSN: 2158-2440 • E-ISSN: 2158-2440 |
| Publisher | SAGE Publications (PUBLISHER • US) |
| DOI | 10.1177/21582440231180669 |
| OpenAlex | W4380985669 |
| Language | EN |
| Citations received | 2 |
| References cited | 66 |
The innovation characteristic studies are deemed to be significant as consumers’ behavior are influenced by how they perceive these product characteristics. As the innovation characteristics continue to grow, these characteristics are observed to be cognitively centric in nature with significant overlapping in meanings and terms. To overcome this gap, this study intends to develop a cognitive-affective-balanced higher-order adoption model upon key constructs in the innovation adoption and diffusion literature. Five broad higher-order constructs namely information, compatibility, relative advantage, perceived risk, and brand trust are concluded and categorized into cognitive, affective, and conative components based on the “think-feel-do” process of Hierarchy-of-Effects model. Contrary to the diffusion literature, this study has empirically proven brand trust (β = .3638) to be the most influential characteristic to adoption intention compared to relative advantage (β = .2144), compatibility (β = .2142), and perceived risk (β = −.1669). The empirical support of brand trust as the affective-mediator contributes to justifying the significance of emotional-based characteristic to the adoption of innovation
Cognition · Formative assessment · Digital Marketing and Social Media · Innovation Diffusion and Forecasting · Psychology · Social Psychology · Technology Adoption and User Behaviour
Editor’s Comments
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| Citations per year | 1 |
|---|---|
| Citation span | 2024 - 2026 (3) |
| Highly cited | No |