Narrow Results

This study proposes a research framework that integrates personal innovativeness, perceived risk, cost and enjoyment with the technology acceptance model (TAM). We used the proposed model to explore the antecedents of consumer behavioural intention (BI) to adopt mobile commerce (m-commerce). Excluding missing answers and invalid questionnaires, 477 valid responses were collected. In addition to confirmatory factor analysis (CFA), we used structural equation modelling (SEM) to examine the relationships among the constructs in the proposed model. Our findings indicated that the younger group (under 30) had lower stickiness to m-commerce. Among the constructs, perceived enjoyment (PE) had the most significant influence on BI, followed by attitude, perceived ease of use (PEOU), perceived usefulness (PU) and perceived risk. Our research results could be used as a guide and reference for m-commerce service providers to improve and operate their services.

Although technology acceptance and adoption have been intensively investigated using well-established theories called the Technology Acceptance Model (TAM) and Innovation Diffusion Theory (IDT), this paper claims that Emerging Technology (ET) has particular characteristics that differentiate it from the adoption of traditional technology that has been used for a long time. Therefore, it argues that TAM and IDT are not sufficient to investigate the adoption of ET. Investigating the adoption of ET requires additional, unique, non-traditional factors (constructs). Therefore, this paper aims first to conceptually develop a model of ETs adoption (META). To achieve this objective, TAM and IDT will be reviewed. Then, this paper will use the characteristics of ET as the basis for developing the factors that influence the adoption of ET. Secondly, to validate the model, a case study of an ET (i.e. Virtual Reality) will be analysed in-depth to reveal the factors that influence on its adoption by applying META. A discussion of META applications and implications for future research are also provided.

This study aims to adapt the Expectation Disconfirmation Theory and Technology Adoption Model to unveil provocative roles in patients’ satisfaction cognitions and subsequent continuity behaviors pertaining to telemedicine services in rural Bangladesh. A quantitative research model is developed and validated using a two-staged deep neural network and partial least squares structural equation modeling approach. The findings of this study provide evidence that five salient determinants; expectations, disconfirmation, performance, usefulness, and ease of use dominantly contribute to predicting patients’ satisfaction concerning continuity with telemedicine. This contributes to health informatics and behavioral literature by clarifying the complex interplay between patients’ satisfaction and determinants of continuity behavior in telemedicine’s domain. The findings provide novel insights into predictions of complex patients’ attitudes toward telemedicine continuity, and dynamic changes in adoption trends thereby assisting health professionals, global health experts, policymakers, and IS community in making higher quality informed decisions for people-centered future models of care.