Table 1 Key findings.
Author (s) | Research objectives | Literature approach | Methodology | Findings | Future research |
|---|---|---|---|---|---|
Venkatesh et al.31 | Proposed four main constructs of UTAUT model and four moderators | Review eight previous models to formulate Unified UTAUT | A questionnaire was created with items validated in prior research adapted to the technologies and organizations studied | UTAUT is a definitive model that synthesizes what is known and provides a foundation to guide future research in this area | 1. Identify and test additional boundary conditions of the model 2. study the degree to which systems perceived as successful from an IT adoption perspective (i.e., those that are liked and highly used by users) are considered a success from an organizational perspective |
Venkatesh et al.20 | Proposed UTAUT2 (Hedonic motivation, price value, and habit) | A review of the extant literature by Venkatesh et al. (2003) | The target population was the current users of mobile Internet technology in Hong Kong with two methods to assess CMV that is Using PLS and CFA | Hedonic motivation, price value and habit play important role with three moderators (age, gender and experience) | Extend our model and examine potential interventions to foster or break habits in the context of continued IT use |
Performance Expectancy, Effort Expectancy, Social Influence, Facilitating Condition, Hedonic Motivation, and Price Value Together but omitted habit | UTAUT 2 Approach | 500 were distributed using face-to-face method, a more convenient method to address a larger sample population in a cost-effective manner and data was analyzed using Smart-PLS | Behavioral Intention toward adopting DHS could be described by factors Performance Expectancy, Effort Expectancy, Social Influence, Facilitating Condition, Hedonic Motivation, and Price Value significantly | This research did not explore the “intention to use” but merely on the intention to adopt | |
Koenig-Lewis et al.35 | Perceived enjoyment, social influence, knowledge and perceived risk, and by identifying | The UTAUT 2 and Perceived price/value and habit were excluded as these are less applicable in the m-payments context | An online survey of 316 young people in France and the hypotheses were tested using structural equation modelling using AMOS 21 | Perceived enjoyment, social influence, knowledge and perceived risk, play significant relationship after exclude price value and habit | The need to consider perceived risk of m-payments can be decreased by providing customers with an engaged and enjoyable experience |
Mahfuz et al.37 | UTAUT2 model with cultural dimensions and website quality to know the influences on the m-banking services adoption without hedonic motivation in the model | UTAUT 2 | This paper analyzed by applied partial least squares (PLS) with 220 samples | Cultural dimension and web site quality to adoption of mobile banking in Bangladesh which is considered to be a vital consumer to adopt mobile banking services | Website quality and cultural dimension as a moderator variable like willingness to share on m-banking adoption |
Dwivedi et al.38 | Formalized an alternative theoretical model for explaining the acceptance and use of information system (IS) and information technology (IT) innovations | The acceptance and use of information system (IS) and information technology (IT) innovations | Combination of meta-analysis and structural equation modelling (MASEM) techniques. The meta-analysis was based on 1600 observations on 21 relationships coded from 162 prior studies on IS/ IT acceptance and use | The explanatory power of the theoretical model improved significantly when attitude is explicitly theorized | This research uncovered certain relationships that were not found in the original UTAUT model. Several of these paths identified in this research were due to the introduction of a new construct (attitude) not found in the original model |
Hoque et al.45 | Consumers’ health consciousness (HC), perceived knowledge (PK) and beliefs affecting the attitude and purchase intent (PI) of the consumers | Theory of Planned Behavior (TPB) | Survey conducted on a randomly selected sample of 712 households by using PLS-SEM | The results of the analyses corroborate that consumers’ health consciousness has a positive impact on perceived knowledge, belief, and attitude, but not on purchase intent | This study takes into account one dimension of health perception, namely physical health consciousness. Other dimensions such as mental, social, emotional, motivation and spiritual health have not been considered. The other important variables, such as the effect of emotion, specific belief, perceived risks, trust |
Cao et al.47 | UTAUT model to measure eight constructs: health consciousness, social influence, facilitation conditions, perceived risk, trust, performance expectancy, effort expectancy, and behavioral intention | UTAUT 2 | A questionnaire survey in a Japanese university and collected 233 valuable responses and data Structural equation modelling was used for hypothesis testing | Four constructs of UTAUT have significant effect on behavioral intention. Health consciousness and social influence indirectly behavioral intention through trust | Future study needs to explore those who have prior experience with m-Health use and those who have no experience with mHealth use |
Rasul et al.53 | The UTAUT model explain the technology continuance of adopting m-Health | Technology acceptance model (TAM) | 306 usable responses from a randomly crowdsource online survey of sugar-related mobile app users in Australia. Data were analyzed by structural equation modelling | Social influence was a significant predictor of continuance intention, but convenience was not, which could be attributed to increased app usage | The rich and refreshing insights revealed signal the potential fruitfulness of adding new factors, which future research can advocate or identify through critical |
Alsyouf et al.46 | Fills the literature gap regarding mediating effects of social influence and COVID-19 anxiety in the relationship between trust in government and exposure detection apps implementation, and between COVID-19 anxiety and exposure detection apps implementation, respectively | Technology acceptance model (TAM) | Quantitative study approach and a cross-section design targeted 586 participants from Saudi Arabia. The hypotheses were analyzed using the structural equation modelling–partial least squares (SEM-PLS3) approach | All constructs in this study found play significant impact on behavior except social media Awareness on app usage | Future research should consider different settings and include bigger samples representing a better result |
