The elaboration likelihood model, job ads, and application decisions

2004 ◽  
Author(s):  
Jonas William Shultz ◽  
David A. Jones ◽  
Derek S. Chapman
Keyword(s):  
Elaboration Likelihood Model ◽  
Elaboration Likelihood ◽  
Likelihood Model ◽  
Job Ads

English words and phrases in Dutch job advertisements

2015 ◽  
Vol 4 (1) ◽  
pp. 21-38 ◽  
Author(s):  
Frank van Meurs ◽  
Hubert Korzilius ◽  
Liset Bergevoet
Keyword(s):  
Language Use ◽  
Elaboration Likelihood Model ◽  
Elaboration Likelihood ◽  
Limited Evidence ◽  
Model Framework ◽  
Peripheral Cues ◽  
Job Advertisements ◽  
Likelihood Model ◽  
Central Route ◽  
Job Ads

It has been suggested that differences in mental processing affect the persuasiveness of language use. Within the Elaboration Likelihood Model framework, we examined if there were differences in the persuasiveness of English versus Dutch words in job ads depending on the way the job ads were processed, either by the central or the peripheral route. In an experiment, 144 participants evaluated ads for lower level jobs. Persuasiveness was measured in terms of text, job, and company evaluation, and application intention. There were no differences in persuasiveness for job ads containing English words depending on whether they were processed via the peripheral or the central route. However, under peripheral processing the jobs in the ads with English words were seen as being more attractive and as having a lower salary than the jobs in the all-Dutch ads, providing some limited evidence that English words may function as peripheral cues.

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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