1. Introduction
On 25 January 2020, Malaysia recorded its first three cases of coronavirus disease (COVID-19) [
1]. Cases have increased unexpectedly since the first detection of this epidemic. Government and health authorities have tried to mobilize all health and safety measures to alleviate the spread of the epidemic, including hand washing, wearing masks, social distancing, and lockdown [
2]. Traditional measures in the field of public health may not be enough to avoid the spread of the virus in a population, in the long term, which requires more effective preventive measures [
3].
As preparedness strategies were no longer adequate to control the disease, it has spread to several Malaysian states, and the government deliberately put in place a range of preventive initiatives to minimize the severity of the infection in the states [
4]. While researchers have found no effective treatment, an agile response is needed to tackle the virus. The lack of a rapid response disaster management strategy to a tragedy, such as an outbreak, can become a prime reason for failure to mitigate the impact of a disaster on society. Further, governments and health authorities have attempted to mobilize emerging technology to counter this new challenge [
5], including the use of tracker wristbands, mobile apps, thermal cameras, facial recognition, and drones [
6].
Digital contact tracing apps were introduced as tools to help minimize the spread of the infection. Contact tracing is a time-tested technique that has been implemented extensively to tackle outbreaks of infectious diseases, such as measles, HIV, syphilis, and Ebola [
7]. It includes finding infected people and warning them that they are at risk, through a careful method of retracing where and with whom an infected person is in the vicinity of [
8].
In the case of the COVID-19 epidemic, digital contact tracing provides many advantages over conventional contact tracing [
9]. First of all, it aims to automate a labor-intensive practice, in a circumstance where human communication tracers are scarce [
10]. In addition, it can give more precision, where human memories are forgettable and fallible [
11], particularly in the case of COVID-19, where the disease may be symptomless for up to two weeks [
12]. Finally, the speed of infection of the COVID-19 virus requires quick contact tracing to be functional [
13]. Digital contact tracing, by offering speed, scale, and precision, seeks to overcome these weaknesses.
There is a positive association between perceived vulnerabilities and privacy concerns, associated with the usage of DCT apps, because people are generally aware of the risks associated with the sharing of personal information [
14].
Various studies have been undertaken regarding user data privacy, in relation to the adoption of DCT apps. If people are fully unaware of their privacy, the exposure of personal information can lead to major privacy issues in the electronic communication environment in the future [
15].
This is supported by numerous research findings, demonstrating the favorable influence of privacy knowledge on privacy concerns about the use of health informatics as a service [
14].
Alternatively, [
5] discovered that a lack of understanding among users about their privacy protection hinders the adoption of appropriate DCT apps, which necessitates user education. As a result, this demonstrates that privacy concerns are somewhat related to user awareness in the adoption of such a system. This demonstrates that the privacy issue is typically related with the user’s awareness in the adoption of such a technology [
4].
In Malaysia, and many other affected countries, many challenges face policymakers, regarding the extent to which the population agrees to adopt and share personal information on tracking apps that exacerbate the situation [
16]. Citizens have a set of apprehensions about adopting such applications, especially in the shadow of the COVID-19 pandemic [
17], as the sharing of personal information of patients and their families by the authorities or third parties increases the risks of stigmatization, discrimination, and blame form the public [
18]. There is an augmented risk that the public can begin to openly blame patients with COVID-19 for initiating infection clusters. In fact, in some cases, these infected people had to react publicly to these accusations to defend themselves [
19]. Accordingly, these challenges were not limited to the concerns of disseminating personal information only, but also developing these applications locally, in record time, and making them suitable for users is part of these obstacles.
The chief industry regulator at the Malaysian Communications and Multimedia Commission (MCMC) confirmed that the improvement of the app in Malaysia was still lagging behind, due to a lack of understanding of the public sector requirements [
20]. This is likely to result in a lower acceptance rate for locally improved applications in Malaysia [
21]. Investigate digital contact tracing apps’ usage intention currently remains limited [
22]. Therefore, it is important to analyze the variables that would stimulate or slow down the adoption of a contact-tracing app and reduce the concerns of users of these applications, to incorporate it effectively into lockdown exit strategies, considering the current problems.
This research intends to extend the UTAUT model to understand users’ acceptance of COVID-19 Digital Contact Tracing Apps in Malaysia. This study aims to answer the following questions:
What are the factors that could influence the Adoption of MySejahtera?
Does age moderate the relationships between Performance Expectancy, Effort Expectancy, Social Influence, Facilities Condition, App-Related Privacy Concerns, and Adoption of the MySejahtera application?
How can an empirical evaluation of the proposed model be conducted, based on the Unified Theory of Acceptance and Use of Technology model?
This study is structured into the following sections. Firstly, the literature review and theoretical background are presented. Secondly, the conceptual framework and hypotheses development are laid out. Then, the research methodology, data analysis and results are presented. Finally, the discussion and conclusion are provided.
7. Discussion
The results of this study show four main hypotheses were significant; these hypotheses, Performance Expectancy, Effort Expectancy, Social Influence, Facilities Condition, had a significant and positive effect on the adoption of MySejahtera application in Malaysia, as shown in
Figure 6 and
Table 18. In Chapter four, the path coefficient and
p-value of UTAUT factors (PE, EE, SI, FC, APP), in predicting the adoption of the MySejahtera application were (β = 0.178,
p = 0.0028), (β = 0.168,
p = 0.028), (β = 0.126,
p = 0.027) and (β = 0.457,
p = 0.000) and (β = −0.053,
p = 0.432), respectively. In addition, the results indicate age was a moderating and positive influence between Performance Expectancy, Effort Expectancy, and MySejahtera application adoption, but age was a moderating and negative influence on Facilities Condition, Social Influence, and MySejahtera application adoption among people who adopted MySejahtera in Malaysia.
Furthermore, the t- and p-value of Performance Expectancy, Effort Expectancy, Social Influence and Facilities Condition were (β = 0.141, p = 0.038), (β = 0.146, p = 0.036), (β = −0.142, p = 0.022) and (β = −0.202, p = 0.021), respectively. On the other hand, App-related privacy concern did not have a significant influence on MySejahtera adoption and age also did not moderate the relationship between App-related privacy concern and MySejahtera application adoption in Malaysia (β = −0.006, p = 0.467).
The present study shows that UTAUT constructs consist of four factors: Performance Expectancy (H1), Effort Expectancy (H2), Social Influence (H3), Facilities Condition (H5), App-related privacy concern (H5). Three path coefficients were found to be significant and related to adopting the MySejahtera application, and these are H1, H1, H3, and H4, while one factor was found to be not significant, H5. The findings found that UTAUT factors had a significant and positive effect on MySejahtera application adoption among people in Malaysia. Therefore, H1 is supported, as shown in
Table 18, in Chapter four. Several past studies have reported findings, including a significant and positive relationship between UTAUT factors and the adoption of new technology (Wang and Shih, 2009; Wang and Shih, 2009; Venkatesh et al., 2003). This study has contributed to the understanding of the relationship between the core UTAUT factors and MySejahtera application adoption among people in Malaysia. There is a strong correlation between PE, EE, SI, FC, and MySejahtera application adoption.
7.1. Performance Expectancy That Could Influence MySejahtera Application Adoption (H1)
Empirical evidence generated from the present study indicates that the relationship between Performance Expectancy and MySejahtera application adoption, among people who adopted the MySejahtera application in Malaysia, was significantly and positively impacted. Therefore, hypothesis H1 is acceptable, as shown in
Table 18 and
Figure 6, in Chapter four (β = 0.178, t = 2.18;
p = 0.028 < 0.05). Several past studies have reported findings, including a significant and positive relationship between Performance Expectancy and COVID-19 applications adoption (Garousi et al., 2020; Sharma, et al., 2020). The more useful the MySejahtera application is perceived to be, the greater the attitude to adopt it. In light of such a finding, the benefits of MySejahtera adoption should be a factor to consider and emphasize when developing applications and implementing the technology, such as COVID-19 applications.
This result shows that people’s attitude seems to be a key predictor of the MySejahtera application’s adoption because they view MySejahtera adoption is a good and pleasant idea.
This result could imply that people in Malaysia who expect to gain benefits from the adopting of MySejahtera are more likely to have the intention to use MySejahtera, which provides benefits to them in technology adoption. Osatuyi (2013) found Performance Expectancy can play a significant role in affecting individuals’ MySejahtera adoption, when users expect higher levels of performance gains in terms of the MySejahtera application.
7.2. Effort Expectancy That Could Influence on MySejahtera Application Adoption (H2)
A significant positive relationship was found between Effort Expectancy and MySejahtera application adoption among people in Malaysia. Thus, H2 is accepted (β = 0.168, t = 2.214, p = 0.028). The result is consistent with the findings reported in previous studies (Abdullah et al., 2020; Chowdhury et al., 2020). In the current study, Effort Expectancy, one of the four direct determinants in the UTAUT model, is related to how individuals believe new technology will help them perform their job better. The results show that people in Malaysia agreed on the idea that Effort Expectancy will lift behavioral intention of MySejahtera application adoption.
7.3. Social That Influence Could Influence on MySejahtera Application Adoption (H3)
The results of this study indicate that Social Influence influenced MySejahtera application adoption Therefore, hypothesis H3 was supported (β = 0.126, t = 2.222; p = 0.027 < 0.05). This result was consistent with previous research, which suggested that Social Influence plays a significant role in innovation adoption decisions (Walrave et al., 2020; Kukuk, 2020; Wang et al., 2020). Therefore, through our research of new apps, we expect that if individuals believe that other VIPs will use the app and support it or recommend its use, they will see it necessary and will intend to download and use the COVID-19 app. In fact, the effect of Social Influence is very strong, especially in East Asian cultures contexts, such as Malaysia.
7.4. Facilities Conditions That Could Influence on MySejahtera Application Adoption (H4)
Empirical evidence generated from the present study indicates that the relationship between Facilities Condition and MySejahtera application adoption, among people in Malaysia, was significantly and positively impacted. Therefore, hypothesis H4 is accepted, as shown in
Table 18 and
Figure 6 (β = 0.457, t = 5.741;
p = 0.000). The results of this study show that within the UTAUT factors, Facilities Condition had a strongly significant and positive influence on MySejahtera application adoption among people in Malaysia. These results are consistent with what was revealed by some previous studies (Martin et al., 2020; Kukuk, 2020; Walrave et al., 2020). Facilitating conditions are factors in an environment that allows the use of COVID-19 applications on smartphones by individuals. The people in Malaysia believe the effective use of COVID-19 applications to contribute to curbing the spread of the epidemic depends on the availability of the organizational resources (materials and humans), and the appropriate technical infrastructure required to achieve optimum performance. This means that the degree to which individuals believe that the organizational resources and technical infrastructure are in place to support the effective use of COVID-19 applications, to reduce the spread of the epidemic, can determine whether or not they will actually use COVID-19 apps via mobile phone.
7.5. App-Related Privacy Concerns Did Not Influence MySejahtera Application Adoption (H5)
The relationship between App-Related Privacy Concerns and MySejahtera application adoption in Malaysia was insignificant. Therefore, hypothesis H2b was not supported (β = −0.053, t = 0.788;
p = 0.432). According to previous studies (Mat et al., 2020; Walrave et al., 2020b), it was determined that privacy concerns, related to health informatics, negatively affect the use of technology related to patients’ health. In the context of applying digital contact tracking apps for COVID-19, we expected privacy concerns to negatively affect the intent to accept the application, especially since some privacy organizations have indicated that there are some abuses by governments and support providers for these applications, and raised concerns about data protection issues related to the implementation of digital contact tracking applications. At the time of this research, there was little research available, regarding the adoption and acceptance of contact tracing applications by individuals, especially using existing technology adoption and acceptance theories. However, studies suggest that privacy plays a major role in the acceptance of contact tracing apps [
35]. The findings of the research show App-Related Privacy Concern was considered an unimportant factor that influences MySejahtera application adoption in Malaysia. However, the result may be explained from the cultural viewpoint of people who adopt the MySejahtera application in Malaysia. The probable reason for this finding could be that the people who adopt the MySejahtera application may feel that privacy concerns are not relevant to the specific context of the COVID-19 pandemic. Although hypothesized to have a significant effect on MySejahtera application adoption, the findings of this study are in line with some previous evidence that found App-Related Privacy Concerns to be not significantly, and in fact, negatively related, to MySejahtera application adoption by an individual in Malaysia. As noted from the findings, the citizens in Malaysia were not confident in the information of the MySejahtera application and their confidence in technology was weak, particularly the truth of information via MySejahtera.
Most contact tracing apps are widely supported by the government, so individual privacy concerns must be taken into consideration and privacy should be investigated as a possible impact on intent to use COVID-19 apps [
33]. Finally, respondents consider these factors as essential elements to adopting MySejahtera application in Malaysia: Performance Expectancy, Effort Expectancy, Social Influence, and Facilities Conditions factors. This is in contrast to other factors, such as App-Related Privacy Concerns, which may not be considered as important for the time being.
7.6. Moderating Effects of Users’ Age
As an objective, the moderating role of demographic variables, such as the age of respondents, was assessed using the interaction method by Smart-PLS 0.3. The results suggest that age was a significant interaction effect, based on the structural invariance model. The findings showed that age was a moderating effect between Performance Expectancy, Effort Expectancy, Social Influence, Facilities Condition, and MySejahtera adoption, but it was not moderating between App-Related Privacy Concerns and MySejahtera application adoption. The results indicate that age moderates the relationship between Performance Expectancy, Effort Expectancy, and MySejahtera adoption. This is because the path coefficient and t-value for PE and EE were (β = 0.141; t = 1.771; p ˂ 0.05) and (β = 0.146; t = 1.776; p ˂ 0.05), respectively. Therefore, the positive relationship between Performance Expectancy, Effort Expectancy, and MySejahtera application adoption will be higher with age. On the other hand, the negative relationship between Social Influence, Facilities Condition, and MySejahtera application adoption will be lower with age. The path coefficient and t-value for SI and FC were (β = −0.142; t = 2.008; p ˂ 0.05) and (β = −0.202; t = 2.023; p ˂ 0.05), respectively. This means the results show that Social Influence and Facilities Condition for MySejahtera Application adoption is lower in younger adults. Older adults are more concerned with Social Influence and Facilities Conditions that influenced on MySejahtera Application adoption among citizens in Malaysia. This is because young generations are more aware and familiar with the latest mobile phones and the functions of mobile phones to use the MySejahtera application. They are considered a technologically savvy group. This indicates that Performance Expectancy and Effort Expectancy with MySejahtera Application adoption are higher with older age, while younger adults are more concerned with Performance Expectancy and Effort Expectancy, influenced by MySejahtera Application adoption, indicating that Performance Expectancy and Effort Expectancy are the most important factors for them. Finally, age did not moderate the relationship between App-Related Privacy Concerns and MySejahtera Application adoption among citizens in Malaysia.
7.7. UTAUT Applicability Validation
The UTAUT framework was found to be a good fit for explaining MySejahtera application adoption among Malaysians in this study. As demonstrated in
Table 18, in Chapter Four, the internal consistency (Cronbach’s alpha and Composite Reliability) of each of the components exceeds 0.7, indicating that they are satisfactory (Hair et al., 2006). The SRMR of this study model was 0.073, as shown in
Table 14, indicating that it was a satisfactory fit (Chen, 2007).
Table 12 reveals that H1, H2, H3, H4, H6, H7, H8, and H9 had a substantial impact on the adoption of the MySejahtera application.
The items’ convergent validity is determined by the magnitude of the standardized factor loading exceeding 0.50, indicating that the items, per factor, have sufficient convergent validity (Fornell and Larcker, 1981) (see
Table 7).
Table 7 in Chapter Five shows that the average variance extracted (AVE) in each construct is greater than 0.50. We compared the square root of the average variance recovered with the correlations among the components to assess the factors’ discriminant validity (Fornell and Larcker 1981). The correlations between the components (off-diagonal elements) and the square root of the average variance retrieved are shown in
Table 8 (diagonal elements).
The square root of the average variance recovered in each example is greater than the correlations of the relevant components with the other factors in the model. As a result, each factor achieves discriminant validity. Furthermore, the UTAUT model’s squared multiple correlations (R2) explain 54.7 percent of the variance in MySejahtera adoption, indicating that it is a good fit. Moreover, the results suggest that the Facilities Condition had a medium-sized effect of the predictive variable on MySejahtera adoption, with a value of 0.173. Furthermore, the predictive variables of Performance Expectancy, Effort Expectancy, and Social Influence exhibited small-sized effects on MySejahtera adoption, with 0.043, 0.031, and 0.023, respectively.
Age was also found to be a moderator between Performance Expectations, Effort Expectations, Social Influence, Facilities Condition, and MySejahtera adoption, but not between MySejahtera Application and MySejahtera adoption. The findings show that the UTAUT model is a good fit, as seen in
Table 7,
Table 8,
Table 9,
Table 10,
Table 11,
Table 12,
Table 13,
Table 14 and
Table 15. As a result of these findings, the UTAUT framework may be utilized to describe the elements that influence the adoption of the MySejahtera Application. Performance Expectancy, Effort Expectancy, Social Influence, and Facility Condition are more significant predictors of MySejahtera Application adoption, according to the UTAUT model. Age was also found to be a moderator between Performance Expectancy, Effort Expectancy, Social Influence, Facility Condition, and MySejahtera application adoption, but not between App-Related Privacy Concerns and MySejahtera application adoption.
7.8. Research Implications
This research will contribute to the study and identification of the factors that would stimulate or slow down the adoption of a contact-tracing app. To be specific, a model that describes the adoption of Digital Contact Tracing Apps in Malaysia. Furthermore, this research proposes solutions to mitigate the impact of the factors affecting the users’ acceptance of COVID-19 Digital Contact Tracing Apps. These solutions will reflect the public benefit behind using this application to confront COVID-19 and recover from this crisis faster. Studying MySejahtera Application adoption for COVID-19 in developing countries, such as Malaysia, does not only serve the development of technology in Malaysia, but can contribute to the body of knowledge in the area of application acceptance for COVID-19 Digital Contact Tracing Apps. This research will be of significance in several areas and provide new knowledge, theoretical and practical. Therefore, the findings of the study have several valuable implications for academics, practices, and policy making.
7.9. Implications for Academic Research
The study’s findings have several implications for academic research. First, the extended UTAUT model of motivation is applicable to developing countries, with different degrees of explanatory power. Moreover, the results reveal the need for testing other variables that may provide more in explaining MySejahtera Application adoption for the COVID-19 pandemic, among individuals and organizations in developing countries in general and Malaysia in particular. Second, the model of UTAUT can be employed to explain other online behavior, such as e-government, e-health application, e-sign, and other electronic applications. Third, the current study indicates that the proposed model of UTAUT can be valid. The study also indicates that the aggregated model of technology acceptance theories (UTAUT) is moveable and can be used to examine the adoption of the MySejahtera Application in diverse cultures, such as Malaysia. The fourth contribution is met by the establishment and testing of the full structural model. This model can be used in its current form to test other social network applications, or modified to fit the MySejahtera application for the COVID-19 pandemic. According to the literature, there is very little research that uses the UTAUT framework model to discuss the adoption of the MySejahtera Application for the COVID-19 pandemic, from the viewpoint of people in the Asia region in general and in Malaysia in particular. Therefore, this research used the UTAUT model to account for the adoption to use the MySejahtera application. Thus, the model generated from this research may be a useful tool for academics to understand these factors in the future. Finally, the research applied a Smart-PLS technique that permits a concurrent assessment of all the factors in the conceptual framework. The current research used two types of group analysis, using the PLS-SEM technique: measurement and structure models, using the variance structure analysis to examine the impact of the research model, in the context of Malaysia. The application of PLS-SEM can be considered a methodological contribution because it promoted a better quality of research.
7.10. Implications for Practices
This is the first study to look at the UTAUT elements and App-Related Privacy Concerns that influence people’s adoption of the MySejahtera application for the COVID-19 pandemic in Malaysia. As a result, the findings of this study have various important implications for Malaysians, both young and elderly. To begin with, this study demonstrates that people’s attitudes have an impact on how they accept the MySejahtera application. As a result, people should focus on UTAUT aspects to improve the number of MySejahtera app users. Second, this study makes a significant contribution by statistically confirming the elements that influence people’s adoption of the MySejahtera application.
Thus, those with higher Performance Expectations, Effort Expectations, Social Influence, and Facility Conditions are more likely to use the MySejahtera application. On the other hand, App-Related Privacy Concerns highlighted that, as long as individuals believe that MySejahtera application adoption is not joyful, fun, or confident, their behavioral intention to use the MySejahtera application system will not be influenced. Individuals’ privacy worries will be reduced as a result of the findings of this study. Based on the findings of this study, it is possible to conclude that people’s performance will improve if motivators for the MySejahtera application are determined in terms of Performance Expectancy, Effort Expectancy, and Social Influence Facilities Condition.
The findings of this study will aid existing persons and those in charge of training, in adopting a pedagogical approach for strategically integrating MySejahtera application adoption in learning. The COVID-19 pandemic technologies used in the MySejahtera application can assist people in being successful and healthy in their lives. People who have a high level of self-efficacy may find it easier to adopt new technology.
This study assists all Malaysians and government institutions, in the sense that people will be more willing and able to learn new technology. The study’s findings will help to improve the quality of the MySejahtera application system among Malaysians. The suggestions could serve as a baseline for enhancing the usability of the MySejahtera COVID-19 pandemic application in Malaysia. In a time when the world is facing a global epidemic, the resultant model provides full knowledge of privacy problems. Finally, digital technologies have the potential to play a significant role in tackling current pandemic difficulties and slowing the virus’s spread.
However, the efficiency and accuracy of these systems are determined by the application architecture and user participation. If systems used mechanisms to assure user security and privacy, user engagement may be improved.
7.11. Policy Contribution
To deploy the MySejahtera application, policy makers must develop a priority factor list that includes Performance Expectations, Effort Expectations, Social Influence, Facility Conditions, and App-Related Privacy Concerns. As a result, the Malaysian government is in charge of developing IT infrastructure, as well as expanding IT education in high schools and universities. Furthermore, the government should help individuals overcome barriers to using the MySejahtera application by guaranteeing stronger internet infrastructure and encouraging non-users to use it.
Furthermore, the report recommends that the government raise awareness by educating children, adults, senior citizens, and women about the inventive potential of new technologies, such as the MySejahtera app. Finally, the paper recommends that policy makers focus on maximizing UTAUT elements that have been empirically demonstrated to influence and contribute to improving citizens’ intentions to adopt the MySejahtera application.
7.12. Limitations of the Study
There are various flaws in this study that can be addressed in future research. To obtain a more comprehensive understanding of the users’ acceptance of MySejahtera application adoption, this study discussed a few factors of MySejahtera application adoption and ignored other factors, such as perceived risk, perceived trust, perceived ease of use, or other moderating variables, such as gender, education, and experience. Second, this study was limited to Malaysian citizens. As a result, the findings of this study do not reflect the behavior of other institutions, secondary schools, or countries, in need of additional investigation. Third, the persons that were surveyed were all Malaysians.
The survey is insufficiently broad in terms of population coverage. As a result, generalizing the study’s findings should be done with caution. Fourth, a mixed-methods study should be conducted, to look into additional citizen characteristics. Citizens’ interviews could also help to clarify the nature of these features and how they interact.
7.13. Recommendation and Research Future
The contribution is made possible by the instrument’s use, as well as the evaluation of the items and latent structures for assessing features of MySejahtera application utilization. New versions of UTAUT for earlier concepts, produced expressly for this study, are the specific construct app-related privacy issue. All constructs were tested and refined in the pilot study and the primary research instrument, resulting in statistically valid assessments of the latent variables. Researchers working on the MySejahtera application for the COVID-19 pandemic should find value in the predicted links that have been documented and use them to build definitions for their own studies.
We advocate following the design choices that should be followed for the construction of contact tracing apps, to ensure privacy, security, and secure development.
To maintain the privacy and security of user data, contact tracing systems must use well-established and cutting-edge encryption systems for data storage, enable customizable access control mechanisms, and employ secure communication methods for data transmission between users and data centers. To reduce the risk of misuse, developers should also consider the semantics of safe software development, strong authentication mechanisms, and possibly two-factor authentication.
The media can help stimulate app adoption by informing citizens about the app’s features, benefits, and use cases, which increases self-efficacy and perceived benefits.
The app’s privacy policy should be stated clearly and understandably. When the epidemic is over, the developer should implement tools that allow them to simply remove user data.
While substantial technology advances have been made to facilitate COVID-19 response, contact tracing apps still need to be improved to reach desired goals in a privacy-conscious manner.
The design should be straightforward and offer a user interface for interaction and personal tracking to promote usability.
8. Conclusions
Finally, in light of the earlier discussion of the findings, the study’s research objectives have been met. Using PLS-SEM, this study investigated the UTAUT variables of the MySejahtera COVID-19 pandemic application in Malaysia. According to the findings of this study, UTAUT characteristics (Performance Expectancy, Effort Expectancy, Social Influence, and Facility Condition) were important predictors of MySejahtera app adoption among Malaysian citizens. App-Related Privacy Concerns, on the other hand, were determined to be minimal in the adoption of the MySejahtera application. As previously stated, the purpose of this research is to determine whether the UTAUT framework, which was designed in developed countries, can be applied to non-Western cultures or developing countries.
Most technology acceptance theories, established and produced in developed countries, are culturally biased in the service of those developed countries’ social and cultural systems, according to popular belief. Malaysians can use the MySejahtera application technology to assist in slowing down the epidemic. These methods can be replicated by other Southeast Asian countries, particularly those with low resources that are currently suffering from the fatal outbreak’s more severe consequences. There are several benefits to utilizing the app, but there are also some drawbacks. However, we believe that the policy of test, track, trace, and support will be critical in containing the present pandemic and preventing a second coronavirus outbreak. Finally, the study includes information on the state of MySejahtera application technology among Malaysian citizens, as well as sources of reference for academics, practitioners, and policy makers interested in using MySejahtera to combat the COVID-19 pandemic in Malaysia.