Early to Adopt and Early to Discontinue: The Impact of Self-Perceived and Actual IT Knowledge on Technology Use Behaviors of End Users

Author List: Aggarwal, Rohit; Kryscynski, David; Midha, Vishal; Singh, Harpreet;
Information Systems Research, 2015, Volume 26, Issue 1, Page 127-144.
For organizations to achieve the benefits of new information technology (IT) systems, their users must adopt and then actually use these new systems. Recent models help to articulate the potentially different explanations for why some users will adopt and then continue using new technologies, but these models have not explicitly incorporated IT knowledge. This is particularly important in contexts where the user base may be non-IT professionalsÑi.e., the users may vary substantially in their basic IT knowledge. We draw on psychology to argue that in situations where there is a wide variance in actual IT knowledge, there will often exist a U-shaped relationship between actual and self-perceived IT knowledge such that the least knowledgeable believe themselves to be highly knowledgeable. We then draw on individual-level adoption theories to argue that users with high self-perceived IT knowledge will be more likely to adopt new technologies and do so faster. We also draw on individual-level continuance theories to argue that users with low actual IT knowledge will be more likely to discontinue using new technologies and do so faster. We test our expectations using a proprietary data set of 225 sales professionals in a large Indian pharmaceutical company that is testing a new customer relationship management system. We find strong support for our hypotheses.
Keywords: IT knowledge ; non-IT professionals ; adoption ; continuance ; econometric analysis ; healthcare ; pharma ; CRM ; SaaS ; cloud computing ; self-assessment
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#284 0.168 users user new resistance likely benefits potential perspective status actual behavior recognition propose user's social associated existing base using acceptance
#53 0.151 knowledge application management domain processes kms systems study different use domains role comprehension effective types draw scope furthermore level levels
#49 0.122 adoption diffusion technology adopters innovation adopt process information potential innovations influence new characteristics early adopting set compatibility time initial current
#134 0.084 users end use professionals user organizations applications needs packages findings perform specialists technical computing direct future selection ability help software
#75 0.079 behavior behaviors behavioral study individuals affect model outcomes psychological individual responses negative influence explain hypotheses expected theories consequences impact theory
#179 0.065 technologies technology new findings efficiency deployed common implications engineers conversion change transformational opportunity deployment make making improve powerful choosing enhance
#132 0.060 likelihood multiple test survival promotion reputation increase actions run term likely legitimacy important rates findings long short higher argue prior
#148 0.054 productivity information technology data production investment output investments impact returns using labor value research results evidence spillovers industries analysis gains