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Digital transformation (DT) has created a number of significant opportunities and related alterations in consumers' behaviours. However, consumers differ in adopting DT. There is still a need to investigate consumer's capabilities and his/her perception of other customers that supports or hinders the DT process. This study aims to investigate human thinking capabilities (critical thinking, holistic thinking and creative thinking) as drivers of two specific types of outcomes: DT barriers and/or DT nurture. In addition, this research also examines the linkage between human capabilities (three types of thinking) and other customers' perception. Finally, it postulates that other customers' perception drives DT barriers and/or DT nurture.

Applying to the public, private and international banking sectors, 273 questionnaires were collected. The collected data was analysed using AMOS as well as the PROCESS macro.

The results showed that human thinking capabilities have different effects on DT barriers and nurture. While critical thinking has a significant effect on DT barriers, both holistic thinking and creative thinking have a significant effect on DT nurture. Other customers' perception construct has a significant effect on both DT barriers and nurture. In addition, only holistic thinking has an effect on other customers' perception.

This study advances knowledge in three ways. Firstly, it examined DT barriers and nurture as variables from the customer's perspective. Secondly, it examined each human thinking capability on DT barriers and nurture, giving more insights. Thirdly, it studied human thinking capabilities as one of the main factors that might affect other customers' perception and DT barriers and nurture, while most previous studies focused only on other customers' perception's impact on DT barriers and nurture.

This study aims to examine how the theory of planned behaviour and technology acceptance theory can be used to understand the adoption of non-pharmaceutical interventions (NPIs). The relationships between attitudes, behavioural intentions towards using NPIs, actual use of NPIs and word-of-mouth (WOM) were examined and compared between early and late adopters.

A survey was conducted to test the hypotheses with partial least squares structural equation modelling (n = 278).

The results indicate that relationships between attitudes, intentions and behavioural intentions were positive and significant in the whole data set – and that there were differences between the early and late adopters. WOM had no substantial relationship with actual usage and early adopters’ behavioural intentions.

This research gives a better sense of how WOM impacts attitudes, behavioural intentions and actual usage among early and late adopters of NPIs and highlights the effectiveness of WOM, especially among late adopters of NPIs. Furthermore, using the TAM allows us to make specific recommendations regarding encouraging the use of NPIs. A new three-stage communications model is introduced that uses early adopters as influencers to reduce the NPI adoption time by late adopters.