Investigating Performance Expectancy and Social Influence on Generation Y’s Behavioral Intention to Use Mobile Government Tax Filing Services in Malaysia

Investigating Performance Expectancy and Social Influence on Generation Y’s Behavioural Intention to Use Mobile Government Tax Filing Services in Malaysia

Nik Anis Sazwani Nik Abdullah¹, Nik Anis Idayu Nik Abdullah^2*, Mariaton Safrina Baharuddin³, Amir Faizal Hassan⁴

^1,3,4Faculty of Business, UNITAR University College Kuala Lumpur (UUCKL) 50450, Kuala Lumpur, Malaysia

²Faculty of Accountancy, University Technology MARA, Cawangan Selangor, Kampus Puncak Alam, Selangor, Malaysia

*Corresponding author

DOI: https://dx.doi.org/10.47772/IJRISS.2025.909000157

Received: 10 August 2025; Accepted: 18 August 2025; Published: 03 October 2025

ABSTRACT

The adoption of mobile government services (m-Government) is transforming public service delivery, particularly in areas such as tax filing among individual taxpayers in Malaysia. Understanding the factors that influence taxpayers’ acceptance is crucial for successful implementation and maximizing taxpayer engagement. This study aims to investigate the influence of performance expectancy, social influence and perceived trust on Generation Y’s behavioral intention to use m-Government for tax filing in Malaysia. The Unified Theory of Acceptance and Use of Technology (UTAUT) served as the theoretical framework for this study. A quantitative approach was employed, using an online questionnaire distributed via non-probability sampling. Data from 136 respondents in the Generation Y category were analyzed using the Statistical Package for the Social Sciences (SPSS). Multiple regression analysis was conducted to test the relationships between performance expectancy, social influence, perceived trust and the dependent variable, behavioral intention. The results revealed that both performance expectancy and social influence have a significant relationship with behavioral intention to use mobile tax services, while perceived trust did not show a statistically significant relationship. Although perceived trust was not a statistically significant predictor in this study, initiatives to strengthen citizens’ confidence in the services security and reliability remain important for long-term sustainability.

Keywords: UTAUT, Taxpayers, Generation Y, Behavioral Intention, m-Government

INTRODUCTION

Mobile government (m-Government) services are a major step in digital governance, bringing services closer to the citizen from. By leveraging mobile technology, governments can provide faster, more equitable, and citizen-centric services especially important in a world that increasingly relies on mobile connectivity. Through m-Government, citizens can access government services through mobile devices instead of traditional methods that demands a lot of effort and time (Chen et al., 2016). Governments the world over are picking on the momentum of electronic government (e-Government) to initiate m-Government (Mensah et al., 2024). Governments around the world are diverting towards the m-Government due to the higher penetration rate of mobile devices (Ding et al., 2019; Phonthanukitithaworn et al., 2016).

m-Government also can know as a form of government service delivered through smart device applications and interactive SMS services to reach the citizen flexibly and comfortably (Desmal st al., 2022).  m -Government can be defined as the process of delivering government information and services to citizens by utilizing mobile or wireless communication technology (Noor Dheyaa et al., 2019). Wang et al., (2020) defined m-Government as the deliberate government’s strategy of providing services to stakeholders through mobile technology systems without the constraints of space and time. Maw et al (2009), m-Government is the leveraging of mobile technology systems to enhance electronic government systems to better deliver public services. m-Government through enabling environment of mobile technology transforms e-government service systems such as government-to-government services (G2G), government to citizens (G2C), government to business (G2B), and government to employees (G2E) into mobile devices and systems (Mossey et al., 2019).

Despite the growing availability of m-Government services, adoption rates among citizens particularly taxpayers remain relatively low. m-Government can improve quality of services, the effectiveness and efficiency of public services, and increase profitability (Pedersen, 2017). Scholars have further indicated that m-Government is an extension, complementary, valued addition in terms of its technological advancement of e- Government (Kushchu et al, 2003; Shareef et al., 2016a). Notably, although Generation Y taxpayers are digitally literate and frequent users of mobile technology, their adoption of m-Government platforms remain inconsistent. This inconsistency needs to explore by the specific determinants that shape their adoption with m-Government services, mobile tax filing services. This raises important questions about the factors influencing their behavioral intention to use such services, as well as the potential barriers that hinder adoption.

M-Government supports to enhance the citizen’s accessibility to online services and facilitates the traditional ways of tasks performing by the government agencies (Almarashdesh, 2010:  Implementation of m-Government involving the utilization of all kinds of wireless and mobile technology, services, applications and devices for improving benefits to the parties involved in m-Government transactions. One of the most popular devices, smartphones, makes m-Government more convenient, efficient, and accessible for citizens at any time anywhere. Despite continuous government efforts, citizen behavior remains crucial to the success of m-Government initiatives. Citizens are the primary stakeholders in the m-Government framework. Therefore, understanding citizens’ behavioral traits is essential to identify the driving forces behind the adoption of m-Government services (Batubara et al., 2018; Almarashdeh et al., 2017; Wang et al., 2020b).

LITERATURE REVIEW, HYPOTHESES AND RESEARCH FRAMEWORK

Unified Theory of Acceptance and Use of Technology (UTAUT)

Unified Theory of Acceptance and Use of Technology (UTAUT) is a model that brings together the eight technology acceptance models in explaining how people adopt and use new technologies (Venkatesh et al., 2003). UTAUT is used to measure and understand the factors determining the user adoption behavior of information technology. Venkatesh et al. (2003) conducted an extensive study of eight commonly used models of technology acceptance to develop a unified model that integrate elements across all eight models to provide a comprehensive view of the behavior of users towards new technology. There are four key constructs in UTAUT model which are performance expectancy, effort expectancy, social influence and facilitating conditions.

UTAUT incorporates four key constructs that serve as the foundational pillars of the theory, explaining the social phenomena influencing user behavioral intention. This makes UTAUT particularly suitable for the present study, as it aims to predict and explain the factors that drive the adoption of m-Government services (Mensah et al., 2024; Venkatesh et al., 2003).

Different researchers extend and modify the UTAUT model to suit specific purposes and study context. Extension and modification of the UTAUT model have been encouraged as new mechanisms to include the measuring and the elucidation of the consequences of the technology adoption intention and usage behavior (Dwivedi et al., 2011).

This study modified the construct by adding perceived trust. This aligns with research practices, which is extensions and modification can help explain a significant portion of the variance in users’ intention to adopt m-Government (Saxena et al., 2017; Mensah et al., 2024). UTAUT is designed to be superior in performance to other theories since it can explain about 70% of the variance (higher predictive powers) in behavioral adoption (Venkatesh at al., 2003), thus accounting for the application in this research.

Performance Expectancy

Performance expectancy is defined as the degree to which a person believes that applying the technology would help them to achieve gains in job performance (Venkatesh et al., 2003). A study by Alalwan et al. (2017) stated that performance expectancy influences the decision to adopt mobile technology. Performance Expectancy signifies the degree to which a person believes that a system is beneficial in performing a specific duty and synonymous with perceived usefulness in Technology Acceptance Model (TAM), (Almaiah et al., 2020). Studies have indicated that performance expectancy is a major determinant of behavioral adoption of m-government including e-government (Chao, 2019; Mutaqin et al., 2020). Performance expectancy in the context of m-Government is the ability of users to have access to unimpeded access to quality public services the fast way possible 24/7 (Mensah et al., 2022). Past studies have demonstrated that the performance expectancy of m-Government services have a positive impact on the intention to use m-Government services (Sharma et al., 2018). Therefore, this study has proposed the hypothesis as follow:

H1: There is a significant relationship between performance expectancy and behavioral intention to use m-Government tax filing services among Generation Y taxpayers in Malaysia.

Social Influence

Social influence as the extent to which an individual perceives that others who are important to them, such as family and friends, consider that she or he should use the system (Venkatesh et al., 2003). Social influence is defined as the degree to which use of m -Government services is influenced by peers (Mansoori et al., 2018; Junnonyang 2021). The positive opinions of those members may encourage other citizens to contribute through their participation thus, increasing their intention to use the system (Naranjo et al., 2019). A study by Nysveen et al. (2005) indicate that social influence is a significant factor in term of the use mobile services. Social influences play an important role in determining the acceptance and usage behavior of new adopters of new information technologies (Malhotra et al., 1999).  Therefore, this study has proposed the hypothesis as follow:

H2: There is a significant relationship between social influence and behavioral intention to use m-Government tax filing services among Generation Y taxpayers in Malaysia.

Perceived Trust

Many citizens concern about data privacy, trust, and security when using m-Government services. These concerns may negatively impact their behavioral intention to use such services. Trust can be defined as the willingness of a party to be vulnerable to the actions of another party based on the expectation that the other will perform a particular action important to the trust or irrespective of the ability to monitor or control that other party (Mayer et al., 1995). Trust is a user`s confidence in the mobile government system’s ability to provide a reliable and efficient service (Wang et al., 2014). Trust plays a vital role in reducing perceived risks of using new technologies, especially for transactions involving uncertainty (Almrashdah, 2010). The citizens that trust the government are inclined to use and share government services if they think it is safe and secure (Carter et al., 2005). To earn taxpayer’s trust, they must have confidence in the technology provided to them. Therefore, this study has proposed the hypothesis as follow:

H3: There is a significant relationship between perceived trust and behavioral intention to use m-Government tax filing services among Generation Y taxpayers in Malaysia.

Behavioral Intention

Behavioral Intention is defined as the degree to which users intend to accept and use the system (Fishbein e al.,1979). Behavioral intention to use is the possibility of a user desire to embrace and engage the use of a new technology system (Mensah et al., 2022). Venkatesh et al., (2003) stated that behavioral intention will have a significant positive influence on technology usage. Behavioral intention encourages behaviors that drive an individual’s acceptance and adoption of technological innovations (Misra et al., 2022). A user’s intention to use the m-Government service is related to real usage of the services (Yu, 2012; Almrashdah, 2010).

Research Framework

The conceptual framework outlined in Figure 1 below will serve as a foundation for further investigation and exploration to show independent variables and dependent variable. The independent variables included within the conceptual framework are performance expectancy, effort expectancy and social influence.

Figure 1: Conceptual framework of the study

RESEARCH METHODOLOGY

Data Collection

This study utilized quantitative data analysis and was designed as a descriptive study. A sample size of this are 136 respondents. A set of questionnaires was distributed to individual taxpayers in Malaysia using a non-probability sampling technique, specifically purposive sampling. The questionnaires were administered via Google Forms, and to maximize the response rate, several follow-ups were conducted with the participants. The respondents consisted of individual taxpayers from various backgrounds. The data collected were analysed using the Statistical Package for the Social Sciences (SPSS), Version 30.

Results and Findings of the Study

Table 1.0 Descriptive Statistics of Respondents

Table 2.0 Hypotheses Testing Results

IBM SPSS Statistic was employed to analyse for the descriptive statistics that included the demographic of the respondents. The respondents of this study were the individual taxpayers in Malaysia. Among them, 65 were male and 71 were female. A total of 102 respondents had more than 10 years of work experience. In addition, 118 respondents had a university degree, which shows that most participants were well educated.

In this study, 3 hypotheses were developed. The direct relationships of performance expectancy, social influence, perceived trust towards behavioral intention to use m-Government tax filing services among Generation Y taxpayers in Malaysia were examined. The regression analysis revealed that perceived trust was not a statistically significant predictor, as its p-value (.107) exceeded the standard threshold of p < .05. Therefore, H3 was not supported. In contrast, both performance expectancy and social influence were found to be statistically significant predictors of behavioral intention, with p-values less than .001. These results indicate that users’ perceptions of the system’s usefulness and the influence of others play a substantial role in shaping their intention to adopt m-Government services. This indicates that both are strong and significant predictor of the outcome variable thus, H1 and H2 were accepted.

DISCUSSIONS, CONCLUSIONS AND CONTRIBUTIONS

The study found that perceived trust did not have a statistically significant effect on taxpayers’ behavioral intention to use m-Government services in the Malaysian context. Among Generation Y in Malaysia, the finding that perceived trust was not a significant predictor of behavioral intention to use m-Government services may reflect their higher digital literacy and familiarity with mobile technology platforms. This group, having grown up with technology, may already assume a basic level of security and reliability in digital services, including those provided by the government and agencies. As a result, perceived trust becomes less of a concern compared to other factors when it comes to the behavioral intention to adopt m-Government services. This non-significant relationship may because of the relatively high baseline trust in public digital infrastructure in Malaysia, where citizens may assume a certain level of data security and government accountability.

Performance expectancy suggests that Generation Y are practical and efficiency-oriented which they are more likely to adopt m-Government services if these platforms are perceived as useful, time saving, and easy to use. Social influence plays a significant role in this demographic. Generation Y are highly connected through social media and peer networks, where trends and digital behaviors often spread quickly. These insights suggest that m-Government services initiatives targeting Generation Y should prioritize enhancing service functionality and leveraging social networks to boost adoption. The significance of performance expectancy reinforces the concept that users are more likely to adopt m-Government services when they perceive them as useful and capable of enhancing the efficiency of government related tasks. This result aligns with the (UTAUT), which emphasize the role of expected benefits in driving adoption (Venkatesh et al., 2003).

The strong impact of social influence indicates that recommendations or behaviors of peers, family, or broader social networks significantly affect citizens’ decisions to engage with m-Government services. In Malaysia, public campaigns, endorsements from community leaders, and peer usage may play critical roles in legitimizing and encouraging m-Government use.

This study adopts a cross-sectional research design, which limits the ability to draw causal inferences between the variables. To obtain deeper insights and better understand changes over time, future research should consider employing longitudinal designs. Investigating the role of privacy concerns and security awareness in shaping perceived trust perceptions could also provide deeper understanding. Additionally, the current study utilizes a non-probability sampling technique, which restricts the generalizability of the findings. Therefore, it is recommended that future researchers use probability sampling methods and validate the results using data collected from randomized samples.

ACKNOWLEDGEMENT

The authors would like to thank the UNITAR University College Kuala Lumpur (UUCKL) and Universiti Teknologi MARA (UiTM) for providing the supports for this study.

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