Consumer adoption of the Internet: The case of apparel shopping
By E. Yoh, Mary Lynn Damhorst, S. Sapp, R. Laczniak. 2003
284 citations recorded by the source corpus.
Subfields: Information Systems and Management, Marketing
View Paper: https://www.semanticscholar.org/paper/0fca9e8ed0089fd1b528efe4a349427c09cc89e3
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Information Systems and Management
- Yogesh Kumar Dwivedi
- Mahmud Akhter Shareef
- Banita Lal
- Bhasker Mukerji
- Nripendra P. Rana
- Dov Te’eni
- Limor Arman Russo
- Vishanth Weerakkody
In Marketing
- Jihyun Kim
- Ann Marie Fiore
- Hyun-Hwa Lee
- S. Heidenreich
- Yogesh Kumar Dwivedi
- Katrin Talke
- Marta Blázquez
- Vinod Kumar
Citations in the corpus
- How to overcome pro-change Bias: : Incorporating passive and active innovation resistance in innovation decision models (2014, background): “At this stage, behavioral components join the intentional outcomes, so that actual behavior, such as active innovation adoption or active innovation rejection, results (Rogers, 2003; Yoh et al., 2003).”
- Past Purchase and Intention to Purchase in E-Commerce: the Mediation of Social Presence and Trust (2011, background): “Empirical research (Yoh et al., 2003) shows that customers’ prior internet experience is a strong determinant of their online shopping behavior.”
- A generalised adoption model for services: A cross-country comparison of mobile health (m-health) (2016, background): “Yoh et al. (2003) identified that social acceptance of any behaviour for a specific product could be a dominating reason to pursue a purchase which is also acknowledged in the theory of prospective gratification (LaRose et al., 2001).”
- Fashion Shopping in Multichannel Retail: The Role of Technology in Enhancing the Customer Experience (2014, background): “In the case of fashion clothing, prior experience with the Internet is the main variable that influences the intention to purchase online [75].”
- The role of the technology acceptance model in explaining effects of image interactivity technology on consumer responses (2006, background): “These behavioral intentions include intention to buy, purchase intention, intention to return to the online store, and intention to recommend online products (Balabanis and Vassileiou, 1999; Jarvenpaa and Todd, 1997; Korzaan, 2003; Shim and Drake, 1990; Yoh et al., 2003).”
- Applying the technology acceptance model to the online retailing of financial services (2006, background): “), the Theory of Reasoned Action (TRA) for apparel shopping ( Yoh et al. , 2003”
- Factors for Successful e‑Government Adoption: a Conceptual Framework (2007, methodology): “Yoh et al. (2003) integrated the theories of reasoned action and innovation adoption into one model to explain consumer adoption of the Internet for apparel shopping. Psychological factors, defined as beliefs and attitude, and social factors such as social support and social acceptance were the majo”