The UTAUT Model Analysis in the Technology Use of Generation-Z Users in Cambodia during COVID-19 Situation

Abstract

Due to the widespread infection of the coronavirus (COVID-19) over the world, people were forced to stay at home, and technology has been increasingly used in communication, entertainment, and work. This research emphasized the study on the technology usage of Generation Z who are ready and highly skilled in using technology. The purpose of the study was to investigate the influence of key factors affecting the intended use and practical application of Generation Z technology in Cambodia during the COVID-19 pandemic. The researcher chose to use the UTAUT Model to test the research hypothesis. A questionnaire is a research tool used to collect data online. It was found that the sample size was 212 respondents. Descriptive analysis and the partial least square structural equation model (PLS-SEM) evaluation were performed. The results revealed that (1) most of the respondents were male, had under a bachelor’s degree, and monthly income was equal to or more than 312 US dollars, (2) the performance expectancy significantly influenced the behavioral intention, but effort expectancy, social influence, and facilitating conditions did not affect the behavioral intention of technology use, and (3) the behavioral intention to use technologies significantly influenced the actual use behavior during the covid-19 situation. This study suggests that technology organizations or businesses should pay attention to the potential benefits of technology for spurring the technology adoption and use of Generation Z people in Cambodia.

Paving the way for increased e-health record use: elaborating intentions of Gen-Z

“…The proposed effect of facilitating conditions on intentions emerged to be insignificant, supporting the findings of several studies on younger populations (Keen & Roberts, 2017 ; Suwannapusit, 2021 ; Tavares & Oliveira, 2016 ; Yuan et al, 2015 ). Conflicting findings observed in the literature also suggest differences in perceptions and intentions between generations.…”

“…(Almazroi et al, 2022 ) Performance Expectancy General (Alloghani et al, 2015 ; Alsahafi et al, 2022 ; El-Wajeeh et al, 2014 ; Kijsanayotin et al, 2009 ; Lee et al, 2020 ; Wei et al, 2020 ) (Ben et al, 2021 ) Older (Cimperman et al, 2016 ; Honein-Abouhaidar et al, 2020 ) Younger PE is positively related to intentions . (Almazroi et al, 2022 ; Cheung et al, 2020 ; Suwannapusit, 2021 ; Tavares & Oliveira, 2016 ; Yuan et al, 2015 ) Facilitating conditions NS General (Ben et al, 2021 ; Lee et al, 2020 ) Older (Cajita et al, 2018 ; Cimperman et al, 2016 ; Zibrik et al, 2015 ) Younger Facilitating conditions is not positively related to intentions . (Keen & Roberts, 2017 ; Suwannapusit, 2021 ; Tavares & Oliveira, 2016 ; Yuan et al, 2015 ) Social Influence General (Albar & Hoque, 2019 ; Alsahafi et al, 2022 ; Ben et al, 2021 ; El-Wajeeh et al, 2014 ; Kijsanayotin et al, 2009 ) ...…”

“…(Almazroi et al, 2022 ; Cheung et al, 2020 ; Suwannapusit, 2021 ; Tavares & Oliveira, 2016 ; Yuan et al, 2015 ) Facilitating conditions NS General (Ben et al, 2021 ; Lee et al, 2020 ) Older (Cajita et al, 2018 ; Cimperman et al, 2016 ; Zibrik et al, 2015 ) Younger Facilitating conditions is not positively related to intentions . (Keen & Roberts, 2017 ; Suwannapusit, 2021 ; Tavares & Oliveira, 2016 ; Yuan et al, 2015 ) Social Influence General (Albar & Hoque, 2019 ; Alsahafi et al, 2022 ; Ben et al, 2021 ; El-Wajeeh et al, 2014 ; Kijsanayotin et al, 2009 ) (Lee et al, 2020 ) Older (Zibrik et al, 2015 ) (Cimperman et al, 2016 ) Younger SI positively related to intentions and has the strongest influence on intentions . (Keen & Roberts, 2017 ) (Suwannapusit, 2021 ; Tavares & Oliveira, 2016 ; Yuan et al, 2015 ) Trust General (Alloghani et al, 2015 ; El-Wajeeh et al, 2014 ) …”

“…(Keen & Roberts, 2017 ; Suwannapusit, 2021 ; Tavares & Oliveira, 2016 ; Yuan et al, 2015 ) Social Influence General (Albar & Hoque, 2019 ; Alsahafi et al, 2022 ; Ben et al, 2021 ; El-Wajeeh et al, 2014 ; Kijsanayotin et al, 2009 ) (Lee et al, 2020 ) Older (Zibrik et al, 2015 ) (Cimperman et al, 2016 ) Younger SI positively related to intentions and has the strongest influence on intentions . (Keen & Roberts, 2017 ) (Suwannapusit, 2021 ; Tavares & Oliveira, 2016 ; Yuan et al, 2015 ) Trust General (Alloghani et al, 2015 ; El-Wajeeh et al, 2014 ) Older (Jung & Loria, 2010 ; Nymberg et al, 2019 ; Rasche et al, 2018 ) Younger Trust does not influence intentions directly . (Almazroi et al, 2022 ; Khan et al, 2019 ) Privacy Concerns/Risk General (Angst & Agarwal, 2009 ; Wei et al, 2020 ) Older (Dontje et al, 2014 ; Pywell et al, 2020 ; Vance Wilson et al, ...…”

“…Similar findings were observed in studies on medical staff where social influence had a strong effect on e-health adoption as well (Ben et al, 2021 ). Surprisingly literature on e-health adoption by younger populations has arrived at conflicting conclusions as several of them failed to detect this proposed relationship (Suwannapusit, 2021 ; Tavares & Oliveira, 2016 ; Yuan et al, 2015 ), while others did (Keen & Roberts, 2017 ). Moreover, there is evidence of the significance of age in moderating the social influence-intentions relationship in the e-health context (Ben et al, 2021 ).…”