A Longitudinal Investigation of Personal Computers in Homes: Adoption Determinants and Emerging Challenges

By V. Venkatesh, Susan A. Brown. MIS Q., 2001

1,546 citations recorded by the source corpus.

Subfields: Information Systems and Management, Marketing, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/c3736d31ea5e0bd8bd71b06d6e921f4ae59ac558

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Citations in the corpus

Protection motivation and deterrence: a framework for security policy compliance in organisations (2009, background): “Social influence is the extent to which social networks influence members’ behaviour through messages and signals that help form perceptions of an activity’s value (Venkatesh & Brown, 2001).”
A longitudinal investigation of continued online shopping behavior: An extension of the theory of planned behavior (2006, background): “For example, Venkatesh and Brown (2001) conducted a two-phase investigation for validating factors driving personal computer (PC) adoption in American homes.”
What drives consumers' continuance intention to e-shopping?: Conceptual framework and managerial implications in the case of Saudi Arabia (2011, background): “…of studies (Chen and Wellman, 2004; Laukkanen and Pasanen, 2008; MacGregor and Vrazalic, 2006; Slyke et al., 2002; Venkatesh and Morris, 2000; Venkatesh and Brown, 2001) conducted in “Western cultures” show that males are more likely than females to adopt e-service, the same may not hold in…”
Extending the two‐stage information systems continuance model: incorporating UTAUT predictors and the role of context (2011, background): “Prior research suggests that the more complex an innovation, the lower its rate of adoption, especially among consumers (Venkatesh & Brown, 2001; Brown & Venkatesh, 2005).”
The Role of Augmented Reality for Experience-Influenced Environments: The Case of Cultural Heritage Tourism in Korea (2018, background): “Theoretical and empirical research has validated the idea that perceived enjoyment is an important factor for successful IT usage (e.g., Carroll and Thomas 1988; Igbaria, Parasuraman, and Baroudi 1996; Venkatesh and Brown 2001).”
Exploring the influential factors in continuance usage of mobile social Apps: Satisfaction, habit, and customer value perspectives (2016, background): “Social influence is defined as the degree of impact on the interaction among people in the social network (Rice and Aydin, 1991), and as the perceived pressure gained to perform a specific behavior (Venkatesh and Brown, 2001).”
Guidelines for Conducting Mixed-methods Research: An Extension and Illustration (2016, methodology): “Utility for children “The extent to which using a PC enhances the effectiveness of household activities” (Venkatesh & Brown, 2001, p. 82).”
Who influences whom? Analyzing workplace referents' social influence on IT adoption and non-adoption (2009, methodology): “The brief outcome so far primarily provides insights into factors which influence non-adopters in the household context (Venkatesh and Brown, 2001).”
To Justify or Not to Justify: The Role of Anticipated Regret on Consumers’ Decisions to Upgrade Technological Innovations (2011, background): “The rate of such changes has been cited as one of the primary reasons why consumers are slow to adopt computers in the home (Venkatesh and Brown 2001).”
Determinants of end-user acceptance of biometrics: Integrating the "Big 3" of technology acceptance with privacy context (2013, background): “If consumers are usually swayed by word-of-mouth when judging the quality of an innovation [85], they are also capable of contributing their own opinions to the discourse.”
Avoidance of Information Technology Threats: A Theoretical Perspective (2009, background): “…evidence shows that these theories provide a convincing account of individual users’ acceptance of a wide range of IT in various settings (Adams et al. 1992; Karahanna et al. 1999; Moore and Benbasat 1991; Taylor and Todd 1995; van der Heijden 2004; Venkatesh and Brown 2001; Venkatesh et al. 2003).”
The importance of perceived trust, security and privacy in online trading systems (2009, background): “Many studies of user acceptance have validated the model empirically (Mathieson, 1991; Taylor and Todd, 1995; Venkatesh, 2000; Venkatesh, Davis, 1996, 2000; Venkatesh and Brown, 2001; Venkatesh et al., 2003).”
Exploring the influential factors of continuance intention to use mobile Apps: Extending the expectation confirmation model (2018, background): “Earlier research has indicated that the more complex an innovation is, the lower is its rate of adoption or intention to use it again, especially among consumers (e.g. Venkatesh and Brown (2001), Brown and Venkatesh (2005)).”