Assessing the acceptance of technological implants (the cyborg): Evidences and challenges

规范性 技术接受模型 心理学 结构方程建模 规范(哲学) 认知 社会心理学 规范的社会影响 技术变革 维数(图论) 可用性 计算机科学 人工智能 政治学 神经科学 机器学习 人机交互 法学 纯数学 数学
作者
Jorge Pelegrín Borondo,Eva Marina Reinares Lara,Cristina Olarte Pascual
出处
期刊:Computers in Human Behavior [Elsevier BV]
卷期号:70: 104-112 被引量:97
标识
DOI:10.1016/j.chb.2016.12.063
摘要

Society has already accepted the use of physical implants that increase an individual's seductive power as well as technological implants that correct physical disabilities. Various companies are currently developing technological implants to increase the innate capacity of the human body (insideables) (e.g., memory implants). Public acceptance of this new technology has not yet been investigated in academic research, where studies have instead focused on the ethical and evolutionary implications of insideables. The main aim of this study is the development of a model, namely the Cognitive-Affective-Normative (CAN) model, for assessing the acceptance of new types of technological products. The CAN model combines the cognitive variables perceived usefulness and perceived ease of use, as well as the normative variable subjective (or social) norm, from the TAM models with the affective variables positive emotions, negative emotions and anxiety. The CAN model was tested on a sample of 600 randomly selected individuals through structural equation modeling. Data were obtained from a self-administered, online survey. The proposed model explains 73.92% of the intention to use the technological product in the very early stages of its adoption, that is, its early acceptance. Affective and normative factors have the greatest influence on the acceptance of a new technology; within the affective dimension, positive emotions have the greatest impact. Any technology acceptance model should thus consider the emotions that the new technology produces, as well as the influence of the social norm.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
2秒前
2秒前
干净的琦发布了新的文献求助50
2秒前
jack关注了科研通微信公众号
3秒前
momo完成签到,获得积分10
3秒前
4秒前
科研通AI6.2应助Rachel_Man_Luo采纳,获得10
5秒前
5秒前
桐桐应助曼曼采纳,获得10
7秒前
7秒前
7秒前
zy发布了新的文献求助10
7秒前
无私尔风发布了新的文献求助10
7秒前
赘婿应助大聪明采纳,获得10
9秒前
DRX完成签到,获得积分10
9秒前
窦白梦完成签到,获得积分10
9秒前
岐堂发布了新的文献求助20
9秒前
是玥玥呀完成签到,获得积分20
10秒前
曼话发布了新的文献求助10
10秒前
10秒前
无极微光应助mxs采纳,获得20
11秒前
bkagyin应助KYTYYDS采纳,获得10
12秒前
科研通AI6.2应助白枫采纳,获得10
13秒前
安静从筠发布了新的文献求助10
13秒前
13秒前
老爷爷遨游世界完成签到,获得积分10
13秒前
跳跳妈妈完成签到,获得积分10
14秒前
14秒前
Tushar发布了新的文献求助10
14秒前
若猫完成签到 ,获得积分10
14秒前
14秒前
15秒前
16秒前
Li完成签到,获得积分10
16秒前
要减肥的之云完成签到 ,获得积分10
17秒前
17秒前
17秒前
打打应助张一九采纳,获得10
17秒前
18秒前
Hear发布了新的文献求助10
19秒前
高分求助中
Principles of Economics, 11th Edition 10000
Prescott's Microbiology: 2026 Release ISE 10000
University Physics with Modern Physics, 16th edition 10000
Cronologia da história de Macau 5000
Environmental Leverage in Times of Climate Crisis: Product Standards, Carbon Border Measures and Preferential Trade Agreements 1000
Interactions of Vowel Quality and Prosody in East Slavic 1000
Matrix Methods in Data Mining and Pattern Recognition 510
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7155877
求助须知:如何正确求助?哪些是违规求助? 8800630
关于积分的说明 18598640
捐赠科研通 6756597
什么是DOI,文献DOI怎么找? 3161349
关于科研通互助平台的介绍 2295880
邀请新用户注册赠送积分活动 2136042