کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
350994 618461 2011 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Understanding social networking sites adoption in China: A comparison of pre-adoption and post-adoption
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
پیش نمایش صفحه اول مقاله
Understanding social networking sites adoption in China: A comparison of pre-adoption and post-adoption
چکیده انگلیسی

Prior experience is an important determinant factor of individual behavior. This paper developed a theoretical model to predict the adoption intention of pre-adopters and post-adopters on social networking sites based on the theory of planned behavior. Using data from online surveys of netizens in China, the proposed model was tested in the context of pre-adoption and post-adoption by using the Partial Least Squares (PLS) technique. Then, multi-groups analysis was explored to compare the difference between the two groups. The results show that attitude, subjective norm and perceived behavior control have significant effect on the adoption intention of pre-adopters and post-adopters, and there is no significant difference between the two groups. In addition, information, meeting new people, and conformity motivations have the same significant effect on both groups. However, entertainment motivation has a significant effect on pre-adopters but connecting with old friends has none; in contrast, connecting with old friends has significant effect on post-adopters while entertainment motivation has no significant effect.


► We develop a model to understand social networking sites adoption.
► We examine differences in pre-adoption and post-adoption intention models.
► Entertainment motivation has effect on pre-adopters but none on post-adopters.
► Connecting with old friends has effect on post-adopters but none on pre-adopters.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers in Human Behavior - Volume 27, Issue 5, September 2011, Pages 1840–1848
نویسندگان
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