Editing Diffusion of innovations (section)

===Characteristics of individual adopters===
Like innovations, adopters have been determined to have traits that affect their likelihood to adopt an innovation. A bevy of individual personality traits have been explored for their impacts on adoption, but with little agreement.<ref>{{cite journal |last1=Greenhalgh |first1=T. |last2=Robert |first2=G. |last3=Macfarlane |first3=F. |last4=Bate |first4=P. |last5=Kyriakidou |first5=O. |year=2004 |title=Diffusion of Innovations in Service Organizations: Systematic Review and Recommendations |journal=The Milbank Quarterly |volume=82 |issue=4 |pages=599–600 |doi=10.1111/j.0887-378x.2004.00325.x|pmid=15595944 |pmc=2690184 }}</ref> Ability and motivation, which vary on situation unlike personality traits, have a large impact on a potential adopter's likelihood to adopt an innovation. Unsurprisingly, potential adopters who are motivated to adopt an innovation are likely to make the adjustments needed to adopt it.<ref>{{cite book|last1=Ferlie|first1=E|last2=Gabbay|first2=L|last3=Fitzgerald|first3=L|last4=Locock|first4=L|last5=Dopson|first5=S|chapter=Organisational Behaviour and Organisational Studies in Health Care: Reflections on the Future|editor1-last=Ashburner|editor1-first=L|title=Evidence-Based Medicine and Organisational Change: An Overview of Some Recent Qualitiative Research|date=2001|publisher=Palgrave|location=Basingstoke}}</ref> Motivation can be impacted by the meaning that an innovation holds; innovations can have symbolic value that encourage (or discourage) adoption.<ref>{{cite journal|last1=Eveland|first1=JD|title=Diffusion, Technology Transfer and Implementation|journal=Knowledge: Creation, Diffusion, Utilization|date=1986|volume=8|issue=2|pages=303–322|doi=10.1177/107554708600800214|s2cid=143645140}}</ref> First proposed by Ryan and Gross (1943), the overall connectedness of a potential adopter to the broad community represented by a city.<ref name="chla.library.cornell.edu"/> Potential adopters who frequent metropolitan areas are more likely to adopt an innovation. Finally, potential adopters who have the power or agency to create change, particularly in organizations, are more likely to adopt an innovation than someone with less power over his choices.<ref>{{cite book|last1=Rogers|first1=EM|title=Diffusion of Innovations|date=1995|publisher=Free Press|location=New York}}</ref>

Complementary to the diffusion framework, behavioral models such as [[Technology acceptance model]] (TAM) and [[Unified theory of acceptance and use of technology]] (UTAUT) are frequently used to understand individual technology adoption decisions in greater details.