Factors Influencing People’s Intention to Adopt E-Banking: An Empirical Study of Consumers in Shandong Province, China

E-Banking is growing at an unprecedented rate and has become a truly worldwide phenomenon, offering convenience, flexibility and interactivity for those that can, and know how to access it. This is clearly evidence in China. However, despite such growth and popularity, some users still have reservations about using Information and communication technology (ICT) in their daily banking activities, perhaps due to deep routed cultural factors that cause consumers to question the efficacy of such changes. Through the application of a technology acceptance framework, and empirical evidence from 52 E-Banking user questionnaires and four key market segment interviews, the research explores the factors that influence consumers’ intention to adopt E-Banking in Shandong Province of China. The findings highlight that perceived usefulness and perceived credibility are significant factors which have a positive influence on consumers’ intention to utilise E-Banking, while perceived ease of use and perceived cost are less significant. Unpacking the reasons for resistance to the use of E-Banking highlighted that “difficult to operate”, “unnecessary to use it” and “worry about the security” are key drivers and therefore challenges for the service providers. Based on the results, recommendations are drawn for banks, involving focusing on the significant factors, avoiding weaknesses and optimising strengths of E-Banking and ultimately developing more accurate market positioning strategies to align and manage consumer expectations and maximise potential acceptance

The factors driving online shopping in Saudi Arabia: Regional and behavioral differences among women

This study proposes a revised technology acceptance model that integrates expectation confirmation theory to measure regional differences with regard to continuance online shopping intentions in Saudi Arabia. The sample consists of 650 female respondents. A structural equation model confirms model fit. Perceived usefulness, enjoyment, and subjective norms are determinants of online shopping continuance in Saudi Arabia. Women in the eastern, western, and central region groups are equivalent. The structural weights are also largely equivalent, but the regression path from perceived usefulness to enjoyment is not invariant between female shoppers in the eastern and western regions or in the eastern and central regions. This research moves beyond online shopping intentions and includes factors affecting online shopping continuance. The research model explains 60% of the intention to continue shopping online. Furthermore, this research suggests that online strategies cannot ignore the influence of either direct or indirect regional differences on continuance intentions; the model can be generalized across Saudi Arabia

The factors driving online shopping in Saudi Arabia: Gender differences and behavior

Purpose—This study proposes a revised technology acceptance model that integrates expectation confirmation theory to measure gender differences with regard to continuance online shopping intentions in Saudi Arabia. Design/Methodology—The 465-respondent sample consists of 68.8% women and 31.4% men. A structural equation model confirms model fit. Findings—Perceived usefulness, enjoyment, and subjective norms are determinants of online shopping continuance in Saudi Arabia. Both male and female groups are equivalent. The structural weights are also largely equivalent, but the regression paths from perceived usefulness to subjective norms and to continuous intention are not invariant between men and women. Originality—This research moves beyond online shopping intentions and includes factors affecting online shopping continuance. The research model explains 65% of the intention to continue shopping online. Research Implications—This research suggests that online strategies cannot ignore either the direct and indirect gender differences on continuance intentions in Saudi Arabia. The model can be generalized across Saudi Arabia