An integrated model of the younger generation's online shopping behavior based on empirical evidence gathered from an emerging economy
| Autor: | Jianming Wang, Thinh Truong Vu, Van Thac Dang |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Male
Information Theory Social Sciences Cohort Studies Geographical Locations Habits Cognition Learning and Memory Psychology Ethnicities Computer Networks Empirical evidence Multidisciplinary 05 social sciences Advertising Models Economic Medicine Female The Internet Research Article Adult Computer and Information Sciences China Asia Science Decision Making Structural equation modeling Young Adult Human Learning 0502 economics and business Humans Learning Social media Emerging markets Consumer behaviour Service (business) Internet Behavior business.industry Cognitive Psychology Biology and Life Sciences Consumer Behavior People and Places Cognitive Science Survey data collection Population Groupings 050211 marketing business Chinese People 050203 business & management Neuroscience |
| Zdroj: | PLoS ONE, Vol 15, Iss 5, p e0232213 (2020) PLoS ONE |
| ISSN: | 1932-6203 |
| Popis: | The younger generation is the largest Internet user group in China. They are the first generation to grow up with computers, the Internet, smartphones, online social media, and online shopping. The individuals that belong to this generational cohort have one thing in common—their online shopping behavior. To understand the shopping behavior of the younger Chinese generation, this study draws on the theoretical foundation of generational cohort theory. This study proposes an integrated model that examines the effects of information adoption, personalized service, perceived switching risk, and habitual behavior on purchase intention in the online shopping environment. Survey data have been collected from 407 Chinese people that belong to the post-90s generation. Structural equation modeling is used to analyze the data. Empirical findings show that information adoption, personalized service, and perceived switching risk are the most important predictors of online purchase intention. However, habitual behavior is negatively related to online purchase intention. |
| Databáze: | OpenAIRE |
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