Robot Helps When Robot Fits: Examining the Role of Baby Robots in Fertility Promotion.

Clicks: 401
ID: 65816
2019
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Steady

Ranked #6 of 25 articles by views in Healthcare (Basel, Switzerland)

Most read Least read

Bar heights use a square-root scale.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
Considering China is facing a precipitous decline in its population, there is an emerging trend of developing baby robots to encourage people's willingness to become "parents". Based on the decomposed theory of planned behavior and the theory of uncanny valley, this study empirically investigated whether a baby robot could perform as a prominent antecedent of fertility intention in China, and how this relates to its visual appearance. Consistent with prior research, the current study used a between-subjects design to show (1) a baby robot could significantly improve people's fertility attitude through temporal visual stimulation; (2) fertility attitude, subjective norms from peers, and perceived behavioral control of finance could significantly contribute to fertility intention. Theoretical contributions and implications are discussed in this study.
Reference Key
song2019robothealthcare Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Song, Yao;Qin, Zhenzhen;Kang, Tao;Jin, Yang;
Journal Healthcare (Basel, Switzerland)
Year 2019
DOI
E147
URL
Keywords
china perceived behavioral control subjective norms fertility intention social robot Machine learning blockchain anomaly detection digital identity management transactions

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.