Do as your parents say?—Analyzing IT adoption influencing factors for full and under age applicants

Abstract

The article suggests a model for examining the adoption of e-recruiting by individuals. The model is empirically evaluated using survey data from 323 full and under age applicants. The results explain substantial parts of the individual adoption decision. Interestingly, the relative importance of the adoption drivers varies with age, social environment and the level of education. While, as expected, overall Performance Expectancy is the major force behind adopting e-recruiting, the relative importance of the other factors differs a lot. Whereas Facilitating Conditions came out as an important driver for under age pupils, full age students by contrast are highly driven by the influence of their peer groups and the communication of the respective company they apply for. A major outcome is that the Subjective Norm of family and friends, teachers and professors has a weaker influence for under age pupils who mostly live with their parents than for the group of students who already left home to study at college. Consequentially we assume that the social influence of peer groups on an individual's adoption differs with respect to age, social environment and level of education. This should be investigated more carefully in future adoption research as it might provide an answer for the varying significance of Subjective Norm in adoption research.

Research on information systems failures and successes: Status update and future directions

“…While software developers might evaluate an IS project as a success, other groups (such as users or top management) might attribute it as a failure. This shows the potential chasm between different groups, within or indeed outside an organization (Garrity 2001;Laumer et al 2010). In this context, we argue that it is only through crossing this chasm that a collective view of IS requirements and roles could emerge in order to avoid failures, and achieve greater success in implementing IS.…”

Older Consumers, Digital Marketing, and Public Policy: A Review and Research Agenda

“…In addition, even where age is a variable, this does not mean the studies focus on aging or older consumers. Some studies that focus on age consider differences between children and adults (e.g., Laumer, Eckhardt, and Trunk 2010) or samples of consumers with a relatively young mean age and few older consumers represented (e.g., Brown, Dennis, and Venkatesh 2010).…”

Drivers of mobile payment acceptance: The impact of network externalities

“…Effort expectancy indirectly impacts behavioral intentions through performance expectancy, This means that if a customer think that using a particular technology will need huge effort, their perception of that technology will be decreased (Zhou 2011). This construct is believed to have a significant influence on behavioral intentions towards technology acceptance in early stages, but its impact diminishes over long periods of continues usage (Venkatesh et al 2003), and some research failed to support its influence when testing for e-recruitment systems (Laumer et al 2010).…”