An Examination of Home Internet and Mobile Device Use in the U.S.

Abstract

It is important to understand the determinants of the extent and types of activities performed by home Internet users and by mobile device users, as well as the interactions between these modes of usage. Few studies have looked at the interactions between these two channels of digital communication. While most prior research has been based upon surveys of attitudes toward and intentions to use a technology (and lack a final link to actual usage), in this study, the extent of actual home Internet use, mobile device use, and the simultaneity between these modes of usage are examined. We find that, overall, mobile device use is enhanced by home Internet use, while the two act as substitutes in the case of advanced and sensitive applications.

Facilitating mCommerce Growth in Nigeria through mMoney Usage: A Preliminary Analysis

“…Chauhan, 2015;Dass & Pal, 2011;Tobbin, 2010). In a similar fashion, Morgan and Ravindran (2014) in their work adopted a revised TAM, which the authors referred to as "A Reduced Form Technology Consumer Product Adoption Model" (p. 6) to study important factors impacting the interaction(s) between home Internet and mobile device use in the US context. The model incorporates perceived affordability, perceived risk, and user demographics among others to evaluate US consumers' use of home Internet as well as mobile devices (see Morgan & Ravindran, 2014).…”

“…In a similar fashion, Morgan and Ravindran (2014) in their work adopted a revised TAM, which the authors referred to as "A Reduced Form Technology Consumer Product Adoption Model" (p. 6) to study important factors impacting the interaction(s) between home Internet and mobile device use in the US context. The model incorporates perceived affordability, perceived risk, and user demographics among others to evaluate US consumers' use of home Internet as well as mobile devices (see Morgan & Ravindran, 2014). Also, from the perspective of the Kenyan consumers, Lule, Omwansa, and Waema (2012) applied the extended TAM model by adding three variables -transaction cost, perceived norm, and perceived self-efficacy -to study mBanking adoption in Kenya.…”

“…Simply put and in line with this study, perceived risk is the uncertainty about the outcome of the use of an innovation such as mMoney. Briefly, Riquelme and Rios (2010) assert that risk factor is a vital element in investigating technology adoption; while Morgan and Ravindran (2014) argue that consumers seem more concerned with risk when using mobile devices. In Nigeria, mobile phone theft and reuse issue is a major problem (see Boateng et al, 2014;Ebiye, 2015;Michael, Chinwokwu, & Arop, 2014).…”

The Effect of “Offline-to-Online” Trust Transfer on the Utilization of Online Medical Consultation Among Chinese Rural Residents: Experimental Study

“…Similarly, individuals in relatively good health may be more inclined to try online medical consultation, especially for the diagnosis and treatment of minor and common diseases, consequently experiencing “offline-to-online” trust transfer when engaging with such services. Home internet devices contribute to creating a supportive environment that facilitates individuals’ access to online medical services [ 68 ]. Furthermore, a positive experience with technology and services provided by offline health care institutions and physicians can significantly enhance an individual’s trust in offline physicians [ 8 ], thereby fostering their experience of “offline-to-online” trust transfer.…”

The Use, Impact, and Unintended Consequences of Mobile Web-Enabled Devices in University Classrooms

“…There is a fair bit written and spoken about the impact of mobile web-enabled devices on the lives and social behavior of people (Ley et al, 2014;Morgan & Ravindran, 2014). Gerpott and Thomas (2014, p.291) reviewed "175 scholarly empirical publications on mobile Internet (MI) usage intensity levels and potential determinants of respective usage behavior at the individual subscriber level."…”