Decision factors for the adoption of e-finance and other e-commerce activities.

详细信息   

• 作者：He ; Fang.
• 学历：Doctor
• 年：2009
• 导师：Mykytyn, Peter,eadvisorDiLalla, Lisabethecommittee memberKarau, Stevenecommittee memberNelson, Jimecommittee memberMathur, Ikeecommittee member
• 毕业院校：Southern Illinois University
• Department：Business Administration
• ISBN：9781109173888
• CBH：3358719
• Country：USA
• 语种：English
• FileSize：2473180
• Pages：245

文摘

The development of e-commerce relies upon consumer usage intentions, and Information Systems (IS) researchers have examined usage intentions toward various online e-commerce systems. However, these systems have been studied in prior works independently rather than comprehensively. In order to pursue better measures for predicting and explaining Business to Customer (B2C) e-finance and some other major e-commerce adoptions for consumers, a comparison analysis across three different online systems (online shopping, online banking and online payment) was conducted to advance the understanding of the adoption factors and their linkage to consumer behavior. Refining from Perceived Risk Theory and existing studies, specific risk facets, consumer characteristics and system characteristics were operationalized and integrated within the Technology Acceptance Model (TAM) resulting in a proposed e-finance and other e-commerce system adoption model. A survey instrument was developed based on exploratory qualitative inquiry and quantitative assessment and was used to assess the influence of different risk and utility facets on the attitude towards e-commerce adoption. Results of this empirical study showed that the relationships between perceived usefulness, perceived ease of use, and intention of use were positively and significant towards all three online systems, while perceived risk had a negative impact on the adoption of online shopping and online payment only, which could result from the relative high risk perception towards the two systems. The results provide support of extended TAM model which integrates perceived risk and additional system-specific features and user-specific demographic factors in predicting a consumer's intention of adoption of online systems. Implications for both the academic and practitioner communities were discussed.