Abstract
This study applied partial least squares (PLS) path modeling for quantifying and identifying the determinants of job seekers' acceptance and use of employment websites (EWs) by using an aggregate model that applied task-technology fit (TTF), consumer acceptance and use of information technology (UTAUT2). We propose that the most crucial constructs explaining EW adoption are habit, behavioral intention, performance expectancy, and facilitating conditions. This study verified that a job seeker's habits were a major predictor of intention and usage of EWs involving web-based technology and occasional usage. Thus, when job seekers perceive that their task is to fit the technology, they recognize the value of using the technology and use it habitually.
Highlights
Employment websites (EWs) are considered the most popular websites for online recruitment (Nikolaou, 2014)
partial least squares (PLS) path modeling was applied for confirmatory factor analysis because it is sufficient for a model with both reflective and formative constructs (Lu & Yang, 2014, p. 328)
Despite the fact that job searching on EWs is a relatively general concept in Taiwan and people are fully aware of the various job searching tasks that can be conducted through this service, industrious EWs have continuously developed friendly search interfaces with pooled, valued job postings in the past 20 years through third-party e-recruiting providers to improve their future when they are confronted with tough competition from social networking websites
Summary
Employment websites (EWs) are considered the most popular websites for online recruitment (Nikolaou, 2014). The extensiveness, efficacy, and employment rates (Kim, Chun, Kwak, & Nam, 2014) of EWs are substantially higher than the other e-recruiting websites. Prior studies that have identified a common key determinant: performance expectancy (PE) that influence the use of EWs are limited (Laumer, Eckhardt, & Trunk, 2010; Lin, 2010; Tong, 2009). The aim of the present study was to provide a comprehensive insight into the decision factors affecting the adoption of EWs. We established the direct effects of beliefs, affects, and technology characteristics (TECs) on EW adoption behavior by developing a research model that integrates the task-technology fit (TTF) model (Goodhue & Thompson, 1995), consumer acceptance and use of information technology (UTAUT2) (Venkatesh, Thong, & Xu, 2012). We propose the latest acceptance and use of technology model, the UTAUT2, to examine EWs in the consumer technology acceptance context
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