Author List: Wang, Yinglei; Meister, Darren B.; Gray, Peter H.;
MIS Quarterly, 2013, Volume 37, Issue 1, Page 299-313.
Theory suggests that coworkers may influence individuals' technology use behaviors, but there is limited research in the technology diffusion literature that explicates how such social influence processes operate after initial adoption. We investigate how two key social influence mechanisms (identification and internalization) may explain the growth over time in individuals' use of knowledge management systems (KMS)-a technology that because of its publicly visible use provides a rich context for investigating social influence. We test our hypotheses using longitudinal KMS usage data on over 80,000 employees of a management consulting firm. Our approach infers the presence of identification and internalization from associations between actual system use behaviors by a focal individual and prior system use by a range of reference groups. Evidence of these kinds of associations between system use behaviors helps construct a more complete picture of social influence mechanisms, and is to our knowledge novel to the technology diffusion literature. Our results confirm the utility of this approach for understanding social influence effects and reveal a fine-grained pattern of influence across different social groups: we found strong support for bottom-up social influence across hierarchical levels, limited support for peer-level influence within levels, and no support for top-down influence.
Keywords: information technology diffusion; knowledge management; knowledge management systems; longitudinal research; social influence
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#153 0.228 usage use self-efficacy social factors individual findings influence organizations beliefs individuals support anxiety technology workplace key outcome behavior contextual longitudinal
#116 0.192 research study influence effects literature theoretical use understanding theory using impact behavior insights examine influences mechanisms specifically context perspective findings
#53 0.158 knowledge application management domain processes kms systems study different use domains role comprehension effective types draw scope furthermore level levels
#234 0.110 social networks influence presence interactions network media networking diffusion implications individuals people results exchange paper sites evidence self-disclosure important examine
#75 0.082 behavior behaviors behavioral study individuals affect model outcomes psychological individual responses negative influence explain hypotheses expected theories consequences impact theory
#49 0.077 adoption diffusion technology adopters innovation adopt process information potential innovations influence new characteristics early adopting set compatibility time initial current
#107 0.062 app brand mobile apps paid utility facebook use consumption users brands effects activities categories patterns controls extension store positive factor