Browsing by Author "Jiang, Mengtian"

Now showing 1 - 2 of 2

Generational differences in online safety perceptions, knowledge, and practices
(2016-09)
Jiang, Mengtian
;
Tsai, Hsin-yi Sandy
;
Cotten, Shelia R.
;
Rifon, Nora J.
;
LaRose, Robert
As Internet usage has proliferated in recent years so have online security threats. Internet users are increasingly susceptible to online security threats. Using a qualitative approach, this study conducted 18 focus groups to examine how three different generations perceive online safety, use coping strategies, and protect themselves online: Silent and GI generation (SGI) (born 1945 or earlier), older Baby Boomers (1946-1954), and Millennials (1977-1992). Results show that although each generation shares a variety of online safety concerns, SGIs and Boomers are more suspicious about online security, have less confidence in their abilities, are uncertain about the effectiveness of protection resources, perform fewer protection behaviors, and are more likely to rely on others\' assistance compared to the Millennial group. Our findings indicate online safety training is needed for all three generations, but especially for older adults. Tailored approaches are suggested to reach different generations.
Understanding online safety behaviors: A protection motivation theory perspective
(2016-06)
Tsai, Hsin-yi Sandy
;
Jiang, Mengtian
;
Alhabash, Saleem
;
LaRose, Robert
;
Rifon, Nora J.
Internet users experience a variety of online security threats that require them to enact safety precautions. Protection motivation theory (PMT) provides a theoretical framework for understanding Internet users\' security protection that has informed past research. Ongoing research on online safety recommends new motivational factors that are integrated here in a PMT framework for the first time. Using PMT, a cross-sectional survey (N = 988) of Amazon Mechanical Turk (MTurk) users was conducted to examine how classical and new PMT factors predicted security intentions. Coping appraisal variables were the strongest predictors of online safety intentions, especially habit strength, response efficacy, and personal responsibility. Threat severity was also a significant predictor. Incorporating additional factors (i.e., prior experiences, subjective norms, habit strength, perceived security support, and personal responsibility) into the conventional PMT model increased the model\'s explanatory power by 15%. Findings are discussed in relation to advancing PMT within the context of online security for home computer users. (C) 2016 Elsevier Ltd. All rights reserved.