Testing the Elaboration Likelihood Model of Persuasion on the Acceptance of Health Regulations in a Video Human-Robot Interaction Study

2021 ◽  
Author(s):  
Lena Langholf ◽  
Dominik Battefeld ◽  
Kristina Henning ◽  
Robin Zatrib ◽  
André Groß ◽  
...  
Keyword(s):  
Elaboration Likelihood Model ◽  
Human Robot Interaction ◽  
Elaboration Likelihood ◽  
Interaction Study ◽  
Robot Interaction ◽  
Likelihood Model ◽  
Health Regulations

scholarly journals Neuro-cognitive mechanisms of decision making in joint action: A human–robot interaction study

2011 ◽  
Vol 30 (5) ◽  
pp. 846-868 ◽  
Author(s):  
Estela Bicho ◽  
Wolfram Erlhagen ◽  
Luis Louro ◽  
Eliana Costa e Silva
Keyword(s):  
Decision Making ◽  
Joint Action ◽  
Human Robot Interaction ◽  
Interaction Study ◽  
Cognitive Mechanisms ◽  
Robot Interaction

Understanding online health community users' information adoption intention: an elaboration likelihood model perspective

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Tao Zhou
Keyword(s):  
User Behavior ◽  
Source Credibility ◽  
Elaboration Likelihood Model ◽  
Elaboration Likelihood ◽  
Content Type ◽  
Peripheral Cues ◽  
Likelihood Model ◽  
Adoption Intention ◽  
Information Adoption ◽  
Central Cues

PurposeThe purpose of this research is to draw on the elaboration likelihood model (ELM) to examine users' information adoption intention in online health communities (OHC).Design/methodology/approachThe authors collected 350 valid responses using a survey and conducted the moderated regression analysis to examine the research model.FindingsThe results indicated that users' information adoption intention is influenced by both central cues (argument quality) and peripheral cues (source credibility and emotional support). In addition, self-efficacy moderates the effect of both central cues and peripheral cues on information adoption intention.Originality/valuePrevious research has focused on the effect of individual motivations such as reciprocity and benefits on user behavior, and has seldom disclosed the influencing process of external factors on OHC users' behavioral decision. This research tries to fill the gap by adopting ELM to uncover the mechanism underlying OHC users' information adoption.

Privacy concerns for mobile app download: An elaboration likelihood model perspective

2017 ◽  
Vol 94 ◽  
pp. 19-28 ◽  
Author(s):  
Jie Gu ◽  
Yunjie (Calvin) Xu ◽  
Heng Xu ◽  
Cheng Zhang ◽  
Hong Ling
Keyword(s):  
Elaboration Likelihood Model ◽  
Mobile App ◽  
Elaboration Likelihood ◽  
Privacy Concerns ◽  
Likelihood Model
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