Author List: Yu, Jongtae; Hu, Paul Jen-Hwa; Cheng, Tsang-Hsiang;
Journal of Management Information Systems, 2015, Volume 32, Issue 2, Page 239-277.
This study examines how affect influences self-disclosure on social network (SN) websites. We test two competing models that build on direct causation theory and affect heuristic theory, respectively. In a direct effect model, affect steers self-disclosure, independent of cognitive costÐbenefit appraisals. The indirect effect model instead suggests that affect influences self-disclosure by adjusting perceptions of benefits and costs. The empirical comparison of the models relies on survey data from more than 500 university students. Overall, affect influences self-disclosure indirectly by adjusting the benefits people perceive. In particular, affect toward self-disclosure and toward SN websites relate positively to self-disclosure motivators; their perceived values appear amplified in the presence of positive affect. We also offer a plausible, alternative explanation of the observed positive relationship between privacy risk and self-disclosure according to an indirect effect model, in which self-disclosure is driven mainly by motivators, whereas the effects of inhibitors depend a posteriori on self-disclosure. These findings call for a reconsideration of any exclusive focus on the direct impacts of affect on technology use, as is common in previous research, and suggest the importance of affective factors for understanding social technology uses and managing customer relationships. > >
Keywords: affect dual processing approach; online privacy; online self-disclosure ;social network sites
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#173 0.345 effect impact affect results positive effects direct findings influence important positively model data suggest test factors negative affects significant relationship
#234 0.190 social networks influence presence interactions network media networking diffusion implications individuals people results exchange paper sites evidence self-disclosure important examine
#140 0.135 model use theory technology intention information attitude acceptance behavioral behavior intentions research understanding systems continuance models planned percent attitudes predict
#275 0.089 perceptions attitudes research study impacts importance perceived theory results perceptual perceive perception impact relationships basis significant positive reported common individuals
#278 0.066 website users websites technostress stress time online wait delay aesthetics user model image elements longer waiting appeal attract utility internet