The impact of the online and offline features on the user acceptance of Internet shopping malls

By Tony Ahn, Seewon Ryu, Ingoo Han. Electronic Commerce Research and Applications, 2004

668 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/5baf70907c0fb2cee0d40b486e5f909cc822dc70

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Citations in the corpus

Enhancing the online decision-making process by using augmented reality: A two country comparison of youth markets (2017, methodology): “Five items were used to measure quality of information (adapted from Ahn et al., 2004, Hausman and Siepke, 2009), four items to perceived ease of use (adapted from Davis, 1989; Gefen et al., 2003), four to perceived enjoyment (adapted from Rese et al., 2014), four to perceived usefulness (adapted…”
The influence of flow experience in the augmented reality context on psychological ownership (2021, methodology): “Perceived informativeness was measured with three items (Ahn, Ryu, and Han 2004; Hausman and Siekpe 2009).”
An empirical examination of the acceptance behaviour of hotel front office systems: An extended technology acceptance model (2008, methodology): “Ahn et al. (2004) classified the quality of online properties for an Internet shopping mall into system quality, information, system, and service quality.”
Factors influencing Internet shopping value and customer repurchase intention (2012, methodology): “H1a: Utilitarian shopping value is positively (+) associated with customer satisfaction.”
Investigating the impact of social media advertising features on customer purchase intention (2018, result): “Such results are similar to other studies’ results such as those proposed by Ahn et al. (2005), Chang et al.”
Personal values as underlying motives of shopping online (2008, methodology): “The three stages of this process are: product search; purchase services; and after-sales service (Ahn et al., 2004; Wolfinbarger and Gilly, 2003; Ranganathan and Ganapathy, 2002). During the search stage, intrinsic attributes (such as ‘‘well-organized web structure’’ and ‘‘visually attractive design”
E-learning success determinants: Brazilian empirical study (2017, unknown): “System quality of an e-learning system is critical to a good user experience of e-learning (Ahn, Ryu, & Han, 2004).”
Antecedents of Online Shopping Behavior in India: An Examination (2011, background): “Ahn, Ryu, and Han ( 2004 ) suggest that online and offline features of stores have an effect on the perceived usefulness, attitude, and intention to use the online shopping Web sites.”
Online stickiness: its antecedents and effect on purchasing intention (2007, background): “2004 ), since it is believed that web user's willingness to return is a strong indicator of website loyalty (Reichheld and Schefter 2000 ).”
An empirical investigation of employee portal success (2010, methodology): “System quality Navigation, searchability, structure, usability, functionality, accessibility 6 Items adapted from Ahn et al. (2004) and McKinney et al. (2002) Information quality Usefulness, understandability, interestingness, reliability, completeness, timeliness 6 Items adapted from Lin and Lee (2”
Understanding the MOOCs continuance: The role of openness and reputation (2015, background): “Access is a feature of perceived system quality (Ahn, Ryu, & Han, 2004, 2007) which is significantly related with satisfaction (Freeze, Alshare, Lane, & Wen, 2010; Roca, Chiu, &Martínez, 2006) as well as intrinsic and extrinsic motivation (Ahn et al., 2004, 2007).”
The interactional effects of atmospherics and perceptual curiosity on emotions and online shopping intention (2010, background): “Previous studies showed that increased benefits such as accumulated bonus points, responsive and reliable delivery, and others fringe benefits will please their customers (Ahn et al., 2004). Third, marketers should focus their attention on attracting people with high diversive and specific PC. With ”