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Varying Definitions of Online Platform and
Their effects on customers’ behaviors Research
Meichen Qian
University of California, Irvine
HWID# 361

Author note Meichen Qian is now at Department of Social Science, University of California, Irvine. This researcher is a final paper for the Social Science 3A courses. Contact: Meichenq@uci.edu
Abstract
This paper explores five published articles that report on results from research conducted on online platform and the changes they made to the customers’ behaviors. The articles, however, vary in the online platform and physical retail stores. Clemes, M. D., Gan, C., & Zhang, J. (2014) suggest that Beijing, China has significant increasing users in B2C online shopping. Other …show more content…

Almost all merchants are already or trying to have their own website to sell their products or services. However, many stores have not clear how they institute the amount of their sales through the online cubes. In my research paper, I focus on to what extend the online platform compete with the retail shopping. There are theoretical research model and practical cases to identify the determine factores of cumers behaviors. Then analyzing how can the side of sell compete the physical stores, and how to occupied the market shares in a short time. Therefore, I will from the possible factors, perceived risk, consumer resources, service quality, subjective norms, product variety, convenience and website factors are the main possible factors, to figure out to what degree they affect consumers’ adoption of online shopping.
Literature interview
In Clemes et al.’s (2014) article covering the empirical analysis of online shopping adoption in Beijing. “At the end of 2010, Internet users in China reached 420 million. the investing in B2C online shopping is not widely practiced and organised. There is a questionnaire gathering information from 435 respondents in Beijing, China (Clemes et al., 2014).
According to this questionnaire, there are ten more times generate indicators for interaction terms. “Self-Identity (β¼.236, po.001) had significant positive influences on Purchase
Intentions, whereas Perceived Deterrents (β¼ .261, po.001) significantly and

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