The adaptation of the information system success model in recommender systems: the validation of dual-coding theory Article Swipe
Wen‐Yau Liang
,
Chun‐Che Huang
,
Bo-Ren Shih
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.47989/irpaper924
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.47989/irpaper924
Introduction. Recommender systems are extensively deployed to provide online users with advisory services, and the design of recommender systems' functional features has received substantial research attention. The social aspects of such system interactions, however, have been less explored. Furthermore, measuring user satisfaction, though natural in a business environment, is often challenging for recommender systems research. Method. This study provides the first empirical test of an adaptation of the information system success model in the context of recommender systems. Additionally, the dual-coding theory argument was introduced to examine the model. Analysis. Based on the proposed model, two presentation types are compared. An experimental design is used and a questionnaire is developed for analysis. Results. The experiment's results have shown that the recommender system designed on the basis of the dual-coding theory is better than the traditional recommender system in all aspects. Conclusions. Perceived usefulness and the user satisfaction have a significant positive relationship both with continued intention to use and continued intention to provide.
Related Topics
Concepts
Recommender system
Computer science
Adaptation (eye)
Coding (social sciences)
Empirical research
Context (archaeology)
Information system
Dual (grammatical number)
Information retrieval
Psychology
Literature
Mathematics
Paleontology
Neuroscience
Engineering
Biology
Art
Electrical engineering
Statistics
Epistemology
Philosophy
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.47989/irpaper924
- OA Status
- diamond
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4220678644
All OpenAlex metadata
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- OpenAlex ID
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https://openalex.org/W4220678644Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.47989/irpaper924Digital Object Identifier
- Title
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The adaptation of the information system success model in recommender systems: the validation of dual-coding theoryWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2022Year of publication
- Publication date
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2022-03-12Full publication date if available
- Authors
-
Wen‐Yau Liang, Chun‐Che Huang, Bo-Ren ShihList of authors in order
- Landing page
-
https://doi.org/10.47989/irpaper924Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
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diamondOpen access status per OpenAlex
- OA URL
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https://doi.org/10.47989/irpaper924Direct OA link when available
- Concepts
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Recommender system, Computer science, Adaptation (eye), Coding (social sciences), Empirical research, Context (archaeology), Information system, Dual (grammatical number), Information retrieval, Psychology, Literature, Mathematics, Paleontology, Neuroscience, Engineering, Biology, Art, Electrical engineering, Statistics, Epistemology, PhilosophyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| countries_distinct_count | 0 |
| institutions_distinct_count | 3 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/9 |
| sustainable_development_goals[0].score | 0.4399999976158142 |
| sustainable_development_goals[0].display_name | Industry, innovation and infrastructure |
| citation_normalized_percentile.value | 0.02741577 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |