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Acceptance of Blockchain in Smart City Governance from the User Perspective
Published in Mohamed Lahby, Utku Kose, Akash Kumar Bhoi, Explainable Artificial Intelligence for Smart Cities, 2021
Emre Erturk, Dobrila Lopez, Weiyang Yu
There were also researchers studying blockchain from the technology acceptance perspective. A 2018 study investigated blockchain in the sharing-economy from a technology adoption perspective, to find the factors that influence adoption (Tumasjan & Beutel, 2018). The authors constructed a conceptual model using the unified theory of acceptance and use of technology (UTAUT) as a basis with several other factors that they believed to be important. Their final conceptual model introduced four main factors. Performance expectancy measures the usefulness and effectiveness of the technology, similar to perceived usefulness in TAM, which the authors believed to have the strongest influence on the adoption of blockchain. Effort expectancy is the second factor that measures the ease of use of the technology and the amount of training/education required for users. Attitude is the third factor, measuring the users’ intention to adopt the technology. This incorporates other factors such as social influence and facilitating conditions. The last factor proposed in their model is the pervasiveness and it measures how widely the technology is distributed across businesses.
Technology Acceptance, Adoption, and Usability: Arriving at Consistent Terminologies and Measurement Approaches
Published in Christopher M. Hayre, Dave J. Muller, Marcia J. Scherer, Everyday Technologies in Healthcare, 2019
Lili Liu, Antonio Miguel Cruz, Adriana Maria Rios Rincon
The most common theories used to explain acceptance and adoption of technologies are the Technology Acceptance Model (in its versions TAM and TAM2) (Davis, 1989), the Combined Technology Acceptance Model and Theory of Planned Behaviour models (C- TAM TPB) (Taylor & Todd, 1995), the Innovation Diffusion Theory (IDT) (Rogers, 1995), the Social Cognitive Theory (SCT) (Compeau & Higgins, 1995) and the Motivational Model (MM) (Davis, Bagozzi & Warshaw, 1992). Recently, the Unified Theory of Acceptance and Use of Technology, in its versions UTAUT (Venkatesh, Morris, Davis & Davis, 2003) and UTAU2 (Venkatesh, Thong & Xu, 2012) which integrates previous models with the behavioural intention perspectives and usage of technologies (i.e., TAM-TAM2, TPB, C- TAM TPB, IDT, SCT and MM) have emerged as dominant models to explain the behavioural intention to use technologies and the actual use of technologies.
Choices and Decisions of Computer Users
Published in Julie A. Jacko, The Human–Computer Interaction Handbook, 2012
One type of decision that a person can make with regard to computer use is that of whether to use a given system at all. The most extensive line of research that has looked into this question is research on technology acceptance. A good entry point to this literature is the influential article by Venkatesh et al. (2003), which presented the Unified Theory of Acceptance and Use of Technology (UTAUT), a model that integrates eight previously developed models, including the especially widely studied technology acceptance model (see, e.g., Venkatesh and Davis 2000). These models in turn drew their inspiration from more general theories from social psychology and sociology, such as the precursors of the recently formulated reasoned action approach of Fishbein and Ajzen (2010).
Autonomous Vehicles Acceptance: A Perceived Risk Extension of Unified Theory of Acceptance and Use of Technology and Diffusion of Innovation, Evidence from Tehran, Iran
Published in International Journal of Human–Computer Interaction, 2023
Iman Farzin, Amir Reza Mamdoohi, Francesco Ciari
An increasing number of researchers are interested in investigating the latent factors affecting the acceptance of AVs. The majority of studies have employed the Unified Theory of Acceptance and Use of Technology (UTAUT) theory (which is one of the most comprehensive technology acceptance models, to identify such factors). Although UTAUT has been formulated by combining eight other theories of acceptance, it does not include some of the variables incorporated by those theories. To gain a more profound understanding of the factors affecting acceptance, this study employs a combination of UTAUT and Diffusion of Innovation Theory (DOI) variables and perceived risk (PR). Therefore, the proposed model takes variables such as PE, EE, SI (from UTAUT), OB, TR (from DOI), and PR into account.
AI and emerging technology adoption: a research agenda for operations management
Published in International Journal of Production Research, 2023
Viswanath Venkatesh, Raji Raman, Frederico Cruz-Jesus
Prior literature can only aid in limited ways because of the nascent state of research in this domain. AI in general is expected to have a transformational effect on research because it challenges some of the most fundamental assumptions about research including those tied to technology adoption (Schuetz and Venkatesh 2020b). Nonetheless, several broad theories of technology adoption are available that can provide an effective starting point for such investigations and to help articulate a research agenda. Most widely cited among these theories is the unified theory of acceptance and use of technology (UTAUT) that was originally introduced about two decades ago (see Venkatesh et al. 2003). Although the theory itself is general and can be applied to a variety of technology adoption contexts, contextualised versions of this theory, including UTAUT 2 to the context of consumer adoption of technologies (e.g. Venkatesh, Thong, and Xu 2012), have been developed. Building on UTAUT, several papers have presented research agendas for technology adoption in general (e.g. Blut et al. 2022; Venkatesh, Thong, and Xu 2016) and specific technologies, such as AI, in particular (e.g. Venkatesh 2022). It is important to note that contextualisation of general theories is not only important from the standpoint of providing useful practical guidance, but also from the perspective of creating important new knowledge (e.g. Hong et al. 2013).
The role of usability, aesthetics, usefulness and primary task support in predicting the perceived credibility of academic social networking sites
Published in Behaviour & Information Technology, 2022
Felix Nti Koranteng, Jaap Ham, Isaac Wiafe, Uwe Matzat
Thus, usability, aesthetics, and usefulness remain key concepts that affect user experience and technology behaviour (Perry 2017). (Morville 2004)’s User Experience Honeycomb outlined usability, aesthetics (described as desirability), and usefulness as among seven factors that influence user experience. Also, the Unified Theory of Acceptance and Use of Technology (UTAUT) (Venkatesh, et al. 2003) - one of the popular technology acceptance theories–postulates usability and usefulness as direct predictors of users’ intentions to use an information system. That is, usability and usefulness closely relate to effort expectancy and performance expectancy respectfully, as operationalised in the UTAUT. Hence, (Venkatesh, et al. 2003) defined usability as the degree of ease of use of an information system and usefulness as the belief that the information system is effective for its purpose. Aesthetics symbolises beauty, creativity, and originality (Tractinsky, Katz, and Ikar 2000). Aesthetics is ‘the visual appeal of an information system’ (Oyibo and Vassileva 2020, 10). Despite not being direct persuasive principles, usability, aesthetics, and usefulness have been effective in influencing certain persuasive strategies. For instance, (Lehto, Oinas-Kukkonen, and Drozd 2012) established that design aesthetics influence users’ perception of dialogue support in behaviour change support systems. Another study (i.e. Oyibo and Vassileva 2020) confirmed a positive correlation between usefulness and the persuasiveness of a fitness application. Nevertheless, it remains unclear how usability, aesthetics, and usefulness play out in ASNSs.