AN EMPIRICAL EXAMINATION OF INDIVIDUAL TRAITS AS ANTECEDENTS TO COMPUTER ANXIETY AND COMPUTER SELF-EFFICACY.

Author List: Thatcher, Jason Bennett; Perrewe, Pamela L.;
MIS Quarterly, 2002, Volume 26, Issue 4, Page 381-396.
To better understand how individual differences influence the use of information technology (IT), this study models and tests relationships among dynamic, IT-specific individual differences (i.e., computer self-efficacy and computer anxiety), stable, situation-specific traits (i.e., personal innovativeness in IT) and stable, broad traits (i.e., trait anxiety and negative affectivity). When compared to broad traits, the model suggests that situation-specific traits exert a more pervasive influence on IT situation-specific individual differences. Further, the model suggests that computer anxiety mediates the influence of situation-specific traits (i.e., personal innovativeness) on computer self-efficacy. Results provide support for many of the hypothesized relationships. From a theoretical perspective, the findings help to further our understanding of the nomological network among individual differences that lead to computer self-efficacy. From a practical perspective, the findings may help IT managers design training programs that more effectively increase the computer self-efficacy of users with different dispositional characteristics.
Keywords: Negative Affectivity; Personal Innovativeness; PERSONALITY; Self-Efficacy; Anxiety; Language of Keywords: English; Spanish
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#153 0.277 usage use self-efficacy social factors individual findings influence organizations beliefs individuals support anxiety technology workplace key outcome behavior contextual longitudinal
#155 0.176 technology research information individual context acceptance use technologies suggests need better personality factors new traits telemedicine adoption examined does management
#83 0.167 personal computers use lead order using users pcs innovativeness understanding professional help forces gained usage increase trends parallel introduced expressed
#145 0.107 differences analysis different similar study findings based significant highly groups popular samples comparison similarities non-is variety reveals imitation versus suggests
#17 0.089 empirical model relationships causal framework theoretical construct results models terms paper relationship based argue proposed literature issues assumptions provide suggest
#220 0.086 research study different context findings types prior results focused studies empirical examine work previous little knowledge sources implications specifically provide
#173 0.051 effect impact affect results positive effects direct findings influence important positively model data suggest test factors negative affects significant relationship