Image of THE IMPACT OF ELECTRONIC WORD OF MOUTH ON JOBSEEKERS’ INTENTION TO CONTINUE USING LINKEDIN AS A METHOD OF JOB SEARCHING

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THE IMPACT OF ELECTRONIC WORD OF MOUTH ON JOBSEEKERS’ INTENTION TO CONTINUE USING LINKEDIN AS A METHOD OF JOB SEARCHING

LinkedIn is one of the most popular e-recruitment tools for job applicants. Although some studies explored the effectiveness and efficiencies of LinkedIn, little exploration has been conducted to discover the underlying cause of jobseekers' intention to use LinkedIn. This study considers the implication of Electronic Word of Mouth to the behavioural intention of jobseekers to use LinkedIn, using the Technology Acceptance Model (TAM) as its framework. The Partial Least Square Structural Equation Modelling (PLS-SEM) was applied to analyze 431 samples of ASEAN Jobseekers via SmartPLS 3. Findings show that Electronic Word of Mouth positively influences the perceived ease of use, Perceived Usefulness, and Attitude of jobseekers, which consequently positively impacts the jobseekers' behavioural intention to use LinkedIn. The mediating role of Perceived Ease of Use, Perceived Usefulness., and Attitude was also examined and shows that the three variables partially mediate the relationship between Electronic Word of Mouth and Behavioural Intention. Theoretically, this study can help academics to discover the significance of the Electronic Word of Mouth in new technology acceptance. Practically, managers can use this information to increase the positive Electronic Word of Mouth of their company’s LinkedIn profiles to attract more decent talents to the company. To The Author’s knowledge, this study is one of the first investigations into how external variables influence the TAM Model in e-recruitment which uses regional samples instead of country-wise samples.

Availability
300069126912RLC MM (Rak Tesis)Available
Detail Information
Series Title
Tesis
Statement of Responsibility
Call Number
6912
Publisher
Salemba, Jakarta : Magister Manajemen FEB UI.,
Collation
xv, 115 p. : ill. ; 30 cm.
Language
English
ISBN/ISSN
-
Classification
650
Content Type
text
Edition
-
Subject(s)
Tesis
Electronic Word Of Mouth
Manajemen Umum
ASEAN
Linkedin
Technology Acceptance Model (TAM)
2023
Specific Detail Info
-
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