Factors Influencing Gen Z Domestic Tourist Behavioral Intentions to Use MAE (Maybank) Mobile Payment in Kuala Lumpur: An UTAUT Perspective

Factors Influencing Gen Z Domestic Tourist Behavioral Intentions to Use MAE (Maybank) Mobile Payment in Kuala Lumpur: An UTAUT Perspective

Muhammad Asyraaf Zulkeffli, Muhammad Syazwan Yosri, Muhammad Afiq Mohd Shuhaili, Nadia Hanim Mohd Wasilan

University Technology Mara (UiTM), Kampus Alor Gajah Melaka

DOI: https://dx.doi.org/10.47772/IJRISS.2025.909000257

Received: 29 August 2025; Accepted: 02 September 2025; Published: 06 October 2025

ABSTRACT

This study investigates factors influencing Gen Z domestic tourists’ behavioural intention (BI) to use MAE (Maybank) mobile payment in Kuala Lumpur. Drawing on UTAUT, this study examine performance expectancy (PE), effort expectancy (EE), facilitating conditions (FC), perceived enjoyment (PEJ), and trust (TR). A quantitative survey (n=100) of Gen Z domestic tourists who use MAE employed validated multi-item measures on a five-point Likert scale. Reliability was satisfactory across constructs (α=.72–.96). Analyses (SPSS 29) comprised descriptive statistics, Pearson correlations, and multiple regression. Results show that EE (β=.341, p<.001), PEJ (β=.305, p=.003), and PE (β=.195, p=.024) significantly predict BI, whereas FC (p=.535) and TR (p=.371) are not significant. The model explains 71.3% of the variance in BI (R=.845, R²=.713, Adj. R²=.710). These findings suggest that ease of use, enjoyable user experience, and perceived efficiency are primary drivers of MAE usage among Gen Z domestic tourists, while infrastructural support perceptions and general trust do not add unique explanatory power once other factors are considered. The study extends UTAUT II to a tourism-payments setting and highlights the salience of hedonic motivation. Practical implications include prioritizing intuitive interfaces and engaging features; limitations include convenience sampling and a single-city context.

Keywords: UTAUT, e-wallet, MAE, Behavioral Intention, Generation Z, domestic tourism.

RESEARCH BACKGROUND / BACKGROUND OF STUDY

In recent years, globalization has evolved into an inescapable process, which enables the world flow of individuals, thoughts, technologies and capital (Milenkovic et al., 2022). This web of interconnectedness has markedly influenced technology development, essential for a contemporary advancement, (Milenkovic et al. 2022). More technology developments in Malaysia technology specifically in the tourism sector shifted the sector towards leading technology, from basic technology to advanced technology, with the advancement of mobile payment apps. Mobile payment apps revolutionized the payment experience during travels, providing cashless, secure, and convenient payment methods for accommodation, transportation, food, and attractions (Liu et al., 2019). According to Shanmugam et al. (2024), these applications were in harmony with the needs of technology-savvy travellers, allowing the national tourism sector to stay competitive and respond to contemporary requirements.

Domestic travel defined as travel within one’s own country constitutes approximately 80% of global arrivals and 73% of global tourism expenditure (Nyaupane et al., 2020). It has enormously favored the boost of the economy, wealth redistribution and social integration (Archer, 1978). The growth of the middle class and increased sources of income have resulted in robust growth in domestic tourism in developing countries (Nyaupane et al., 2020). As an example, based on the Department of Statistics Malaysia (DOSM, 2024) statistics, Kuala Lumpur recorded 64.8 million local tourists during the second quarter of 2024, an increase of 23.8 per cent from the same quarter last year. In addition, domestic travel has the potential to create an international tourism standard and the local tourism infrastructure support (Jafari, 1987; Canavan, 2013). The increasing interest in domestic travel opened prospects for innovation to enhance travel experiences, such as using digital instruments like mobile payment applications.

Mobile payment applications are digital tools that allow users to transact monetary funds with the use of mobile devices like cell phones (Kapoor et al., 2021. They enable payments for goods, services, and bills through wireless and telecommunication networks (Kapoor et al., 2021). Mobile payments are seen as an instrumental driver for mobile commerce (Kapoor et al., 2021) and as an emerging channel for financial transaction. Factors including security, ease of use, service availability, and perceived risk influence the adoption of mobile payment applications (Liu et al., 2020). Had the ability to convince people to use mobile payments despite the many advantages they have (convenience, time savings, etc.), they were a challenge in terms of adoption and implementation (Karnouskos, 2004). As technology continues to evolve, it is projected to have a meaningful impact on both e-commerce and m-commerce, especially among tech-savvy generations, including Generation Z (Gen Z), who have rapidly adopted new and emerging digital solutions.

Generation Z has a great deal of engagement on mobile devices as well, with over 90% of this cohort owning and using mobile devices (Ahmed et al., 2019). It is this persisting connectedness that incites their exploration and pursuit of trend with social media catering as the fuel. Yossi Mareta et al. (2023), the primary trend among Gen Z is increasing reliance on QR payment technology to make transactions easier, quicker, and more efficient. This has become an essential tech tool for this generation, especially in urban settings where they can quickly pay for services, locate new places and be more interactive. With the evolution of the digital payment systems by cities, such as MAE or Maybank2u App app to be widely used by Gen Z (Rahadi et al., 2022). Deployment of QR technology is essential to achieve the Gen Z’s minimum level of satisfaction (Aulia Tiara Imani et al.,2020).

MAE (Maybank2u App) is another popular mobile payment app in Malaysia that provides various financial services, from online banking and bill payments to digital wallet features (Kee et al., 2021). The Mobile payment application is easy to integrate into different services and has a user-friendly design to help users manage their finances on the go. MAE is the second-largest mobile payment app in Malaysia, just behind Touch ‘n Go (TNG), Amanda Siddharta (2024). Although TNG is the new standard that everybody uses in which high authorities do advocate cashless transactions which indirectly promises support of the government to TNG, however, MAE is said to be the trending choice for Gen Z others, as it provides plentiful features with more convenience (Ting, 2024). Ying & Mohamed (2020) explained that Government incentives could end up attracting users that are transient in usage and will not shift user behaviour to adopting the use of e-wallet. Though with the continued support of the Malaysian government for digital payments, the two apps have been well received among younger users (Istianah et al, 2021). Despite that statement, a few people would hear how well MAE is and in recent years, this has proven to be true as it proves that MAE’s effective and efficient solution has reached out to a more tech-savvy generation that prefer the dependability and versatility that mobile payment solutions can provide.

The Factors Influencing Gen Z Behavioural Intentions Towards Mobile Payment Apps (MAE) In Kuala Lumpur is an important investigation for many reasons. Firstly, having knowledge of these factors can ensure that mobile payment platforms, such as MAE, align with users’ expectations and deliver a seamless experience. Secondly, such apps have able to build a great trust of confidence amongst all users, due to a greater satisfaction of experience and invariably, it makes one long to have the second experience if not influence the second experience. Lastly, the insights from this study can help to improve mobile payment services, making them more appealing and practical for long-term use, which supports the growth of a cashless society.

Problem Statement

Despite the Malaysian government’s significant efforts to promote digital payment adoption, such as the E-Tunai Rakyat initiative, which allocated RM 450 million in the 2020 budget (Bernama, 2020; TheStar, 2020), there is limited understanding of the long- term effects of these incentives on Generation Z’s behavior toward mobile payment applications. Previous studies have highlighted an initial surge in mobile wallet adoption following these initiatives, but they mainly focus on short-term usage and overlook the factors that contribute to sustained satisfaction and continuous use, especially among domestic tourists (Ying & Mohamed, 2020).

This study addresses this gap by focusing on Generation Z domestic tourists using mobile payment applications (MAE) in Kuala Lumpur, a city with a high population of tech-savvy youth and significant digital payment adoption. By examining this demographic, the research aims to provide insights into the unique preferences, motivations, and satisfaction drivers that contribute to sustained use of mobile payment solutions (Triasesiarta Nur et al., 2021).

While previous research has explored issues such as convenience and technical difficulties (Alina Maharjan et al., 2024), there remains a lack of comprehensive analysis on the factors influencing the continued use of mobile payment solutions like Maybank e-Wallet. This study seeks to investigate how performance expectancy, effort expectancy, facilitating condition, perceived enjoyment and trust, and facilitating conditions impact Generation Z’s behavioral intentions toward sustained use of mobile payment applications. Understanding these dynamics will not only help mobile payment providers, such as Maybank, improve user satisfaction but also contribute to advancing Malaysia’s broader goal of creating a cashless society.

Research Questions

1. How do Performance Expectancy, Effort Expectancy, Facilitating Condition, Perceived Enjoyment and Trust influence Gen Z domestic tourist intention to use mobile payment applications in Kuala Lumpur.
2. What is the relationship between factors influencing domestic tourist (Gen Z) behavioral intention among Gen Z domestic tourists using mobile payment applications in Kuala Lumpur.

Research Objectives

The purpose of this study is to explore and comprehend the preferences of tourists regarding the Factors Influencing domestic tourist (Gen Z) Behavioral Intentions Towards Mobile Payment Apps (MAE) in Kuala Lumpur. The primary research objective in this study is:

1. To investigate Performance Expectancy, Effort Expectancy, Facilitating Condition, Perceived Enjoyment and Trust influence Gen Z domestic tourist intention to use mobile payment applications in Kuala Lumpur.
2. To identify the relationship between factors influencing domestic tourist (Gen Z) behavioral intention among Gen Z domestic tourists using mobile payment applications in Kuala Lumpur.

Significance of Study

The study on Factors Influencing domestic tourist (Gen Z) Behavioral Intention Towards Mobile Payment Apps (MAE) in Kuala Lumpur offers significant benefits from academic and practical. Below is the significance of this study:

Academic Perspective

The research on Factors Influencing determinant domestic tourist (Gen Z) Behavioral Intentions Towards Mobile Payment Apps (MAE) in Kuala Lumpur with important contributions to academics. It contributes to the existing literature by exploring the factors that find concerning Generation Z regarding mobile payment apps and addressing some of the gaps in the current literature (Triasesiarta Nur et al.,2021). This study further provides a framework to help studies to determine how satisfaction translates into users intention to continue to use these apps in future. The study of Generation Z provides an analysis of what separates this group with their own unique behaviors in relation to technology.

Practical

From a practical perspective, the results can help mobile payment service providers like MAE, to enhance their apps for Generation Z and become more user friendly. According to Emily Truman et al. (2019), a clear understanding of these insights can help businesses form marketing strategies targeting this age group and make it much easier for them to customize their services accordingly. The findings may also provide useful recommendations for other industry stakeholders including those initiating the MAE, whose intent had been to promote digital payment options that align to the needs and expectations of Generations Z.

LITERATURE REVIEW

Figure 1 : Conceptual framework adapted from Venkatesh et al., 2012.

The Unified Theory of Acceptance and Use of Technology (UTAUT) is a great choice for studying why Generation Z prefers mobile payment apps because it brings together important ideas from other models like the Technology Acceptance Model (TAM) and Diffusion of Innovations (DOI). UTAUT being used in this context to determine the intentions of domestic tourists, especially the Gen Z tourist who visit Kuala Lumpur and practice acceptance and usage of MAE and mobile payment applications. Based on UTAUT, those factors of perceived usefulness, perceived ease-of-use, subjective norms and behavior control, directly determine the intention of the individual towards using the technology. This makes it more effective than TAM in understanding how Generation Z thinks and behaves when using mobile payment apps.

1. H1: Performance Expectancy (PE) positively affects Behavioural Intention (BI).
2. H2: Effort Expectancy (EE) positively affects BI.
3. H3: Facilitating Conditions (FC) positively affect BI.
4. H4: Perceived Enjoyment (PEJ) positively affects BI.
5. H5: Trust (TR) positively affects BI

Dependent Variable (DV)

Domestic Tourist (Gen Z) Behavioral Intention Towards using MAE

Generation Z is quickly becoming one of the largest target markets in the tourism industry (Setiawan et al., 2018). This tech-savvy group depends on online platforms and mobile applications for most aspects of their travelling experience, including planning and research, booking accommodations, and booking activities (Lubis & Rahmiati, 2020; Nguyen et al., 2023). A significant driver of Gen Z travel intentions comes from social media, which frequently operates as an essential purity increase, with attributes such as entertainment, trends, and word-of-mouth sponsorship shaping their selection significantly (Liu et al., 2022). For this generation, destinations offering “Instagram able” experiences and focused on hands on direct contact to the local culture are attractive attractions, and virtually all aspects of travel purchasing choices are influenced by visual appeal and cultural immersion (Setiawan et al., 2018).

Aside from their proclivity for made-for-mobile qualities and engagement, Gen Z travellers are also more likely to want to use mobile payment systems while travelling things like perceived benefits, peer influence, and trust act as important motivators of Gen Z’s adoption of cashless payment solutions (Kerviler, et al., 2016). These preferences reflect their overall digital-first mindset, as they seek convenience, security, and the ability to incorporate technology into their travel experiences. As observed (Uysal, 2022), the experience of a pandemic has a direct influence on changes in consumer behavior, and the differences between Gen Z (and new generations) and older ones are even larger, because Gen Z and the younger generations show very different consumption behavior than previous generations. As a result, businesses within the tourism industry need to implement multi-generational marketing strategies that align with the generational standpoint of Gen Z as well as other generation.

Knowledge of the preferences and behaviors of Gen Z is vital for tourism stakeholders to strategically target this increasingly significant demographic cohort (Nguyen et al., 2021). This generation has a strong potential to shape the future of travelling so tourism providers need to adjust their services for Gen Z’s strong preference for personalized, tech driven and photogenic experiences. Stakeholder can appeal to gen z travellers who are looking for safety and comfort while travelling by utilising mobile payment options

Independent Variable (IV)

Performance expectancy of using MAE

Performance expectancy is one of the key concepts in organizational psychology that concerns individuals’ beliefs about the correlation between effort, performance and rewards. The nature of performance-based entitlement beliefs is essential to expectancy theory, which states that the effort performance link (Expectancy I) and the performance outcome link (Expectancy II) can determine levels of motivation (Arvey, 1972). Expectation performance studies have produced mixed results, with some concluding a significant relationship exists (Arvey, 1972) and others refuting these results (Kornreich, 1968). Performance expectancy is critical to the creation of high- performance organizations through the alignment of the individual and organizational goal (Blackman et al., 2017).

Next, performance expectancy is the most important factor in determining users satisfaction in adopting e-wallet because it measures users’ beliefs that the technology will improve their financial transactions and overall efficiency (Syifa, 2020). If e-wallets provide satisfactory results, whether in terms of speed, convenience, or ease of use, users will be able to provide it that satisfaction (Ayu, 2021). As a result, this congruence between expectations and actual performance builds confidence and loyalty of the user to the service. Studies of previous research have repeatedly stated that once performance expectancy is high, user satisfaction will be positively correlated with continued use and positive recommendations (Hsu, 2016). Therefore, optimizing the performance aspects of e-wallets is crucial for providers to enhance user satisfaction and retention. As e-wallet achieves customer performance expectancy, it will likely result in an increased of user adoption and satisfaction by providing a more efficient, reliable, and convenient transaction process (Esawe, 2022). This strengthens customer loyalty and gives MAE a competitive advantage in the e-wallet market.

Effort Expectancy of using MAE

Effort Expectancy refers to the degree of ease associated with the use of a system or technology. It is one of the key factors in technology acceptance models, particularly influencing a user’s decision to adopt and continue using new technologies (Khechine, 2016). In the context of digital platforms or tools, such as e-wallets or mobile apps, effort expectancy reflects how simple and intuitive users find the interface, navigation, and overall functionality (Limanan, 2023). A system with high effort expectancy is perceived as user-friendly, requiring minimal effort to learn and operate, which can lead to higher adoption rates and sustained usage, as users are more likely to engage with a system that does not require significant time or effort to use effectively (Khatri, 2018).

Effort Expectancy is closely associated with user satisfaction, as a system or technology that is easy to use directly impacts how satisfied users are with the overall experience (Syifa, 2020). When users find a platform intuitive, with minimal complexity or learning required, they are more likely to have a positive experience, leading to higher levels of satisfaction (Daragmeh, 2022).

MAE (Maybank’s e-wallet) can achieve the level of effort that customers expect, it will result in higher user satisfaction, as customers will find the platform easy to use and navigate (Nugroho, 2023). A seamless and intuitive interface encourages more frequent usage, leading to greater adoption rates among new users and increased retention of existing ones

Facilitating Condition of using MAE

Facilitating Conditions refers to the resources, infrastructure, and support systems that enable individuals to use a particular technology or system effectively. This concept forms an important proposition in technology acceptance models, which maintains that secondary influences can invariably affect an end users capabilities to adapt to and use a new/novel system (Hanif, 2018). The dimension of facilitating conditions encompasses the access to stable internet, technical support, sufficient training, and appropriate devices (Leong, 2021). With these conditions in place, users are encouraged to adopt and continue to use the technology, as they feel they are supported in overcoming any barriers to usage.

In the context of e-wallet, Facilitating Conditions are closely associated with users satisfaction, which indicates the degree in which external resources and support systems are provided (Daragmeh, 2022; Clarissa, 2022). Effective technical support and proper training can enable the users to use the e-wallet efficiently and make successful transactions when they have reliable internet access (Yang, 2021). These ideal situations allow for fewer frustrations and usage restrictions, thus a more seamless experience. This increases the chance that users will be satisfied with the e-wallet and will not encounter any troubles, and they will feel happy with the service that is benefit for the customers.

It can enable a positive customer facilitation condition regarding e-wallet, and the same will render various benefits. Improved access to resources like reliable internet, responsive technical support, and easy-to-follow tutorials will engage customers in using the e-wallet efficiently, minimizing frustrations and promoting use (Ajina, 2023). The enhanced user experience leads to increased satisfaction levels, creating customer loyalty and driving users.

Perceived Enjoyment of using MAE

Perceived Enjoyment refers to the degree to which using a particular technology or system is perceived as fun, enjoyable, or intrinsically satisfying by the user. This concept plays a crucial role in technology acceptance models, as it influences a user’s willingness to engage with and continue using the system (Venkatesh, 2000). When users find enjoyment in the experience of using an e-wallet, they are more likely to adopt it, as the positive emotions associated with its use can enhance motivation and overall satisfaction (Esawe, 2022). In the context of e-wallet applications, this enjoyment can stem from user-friendly interfaces, engaging features, and rewarding experiences, all of which can increase user engagement and loyalty.

Perceived enjoyment plays a crucial role in users’ satisfaction with e-wallets, as it encompasses the pleasure and satisfaction that the users derive from engaging with the application for financial transactions. When users find the e-wallet interface to be intuitive and user-friendly, experience the convenience of quick transactions, and encounter engaging features like rewards and promotions, their overall enjoyment increases, leading to higher satisfaction levels (Ariffin, 2021).

Achieving customer perceived enjoyment through the MAE (Malaysian e-wallet) has led to significant benefits, including increased user engagement and higher customer satisfaction, as users are more likely to frequently utilize an app, they find enjoyable (Esawe, 2022). This heightened enjoyment fosters emotional connections, encouraging user retention and reducing the likelihood of switching to competitors. By achieving higher satisfaction levels, MAE can encourage more people to recommend its e-wallet to friends and family, leading to a natural growth in its user base (Al-Okaily, 2023).

Trust of using MAE

Trust is one of the main factors in the acceptance and usage of e-wallets. The positive impact of trust on perceived usefulness, perceived ease of use, and intention to use e-wallets is supported in multiple studies (Hossain et al., 2022). Security also plays an important role as it is widely recognized that trust and behavioral intention are closely correlated with perceived security (Alaa S Jameel et al., 2022). The Technology Acceptance Model (TAM) has become a common framework for the study of e-wallet adoption, with many studies having added variables such as trust, security and social influence (Senali et al., 2022). Personal traits such as innovativeness and propensity to trust can have a moderating effect on the connections between the factors of TAM and intention to use e-wallets (Senali et al., 2022) Satisfaction and perceived risk are also found to be important in determining e-wallet continuance intention (Jakarta, 2019).

Trust and satisfaction are important determinant in e-wallets’ acceptance and usage. Studies find that there is a close link between satisfaction with mobile banking and e-wallet applications and trust (Geebren, 2021). In fact, trust depends upon security, transparency, and experience (Agarwal, 2024). Similarly, the e-service quality, perceived usefulness, and perceived ease of use also impact user satisfaction and intention to reuse e-wallet (Julia et al., 2024). Nevertheless, another challenge exists as customers seem to have different levels of satisfaction toward each e-wallet provider, wherein, security, efficiency and economic benefits, among the others, become the differentiators (Nurcahyo et al., 2023). In order to improve user satisfaction and trust, e-wallet providers must improve encryption techniques, communication transparency, easy to use interface and work with regulators (Agarwal, 2024).

Using the Technology Acceptance Model (TAM), it can be concluded that the components of perceived use in an easy and simple method sequentially affect e-wallet adoption (Mabkhot, 2023). E-loyalty includes digital customer experience, enjoyment, and trust (Harahap et al., 2023) The UTAUT2 model extended by adding trust found that e-wallet adoption intentions are influenced by effort expectancy, performance expectancy, price value, habit, and trust (Leong, 2021). That means that building trust and improving user experience to retain and attract new users is critical to e-wallet adoption and user loyalty.

Relationship between Independent Variable (IV) And Dependent Variable (DV

Relationship between performance expectation of MAE within Domestic tourist (Gen Z) behavioral Intention

MAE metrics can reflect the performance expectation of an e-wallet affecting the behavior of domestic tourists, especially among Gen Z travelers (Rosli, 2023). Having the ability to interweave various factors that define this generation’s habits, such as the preference for e-wallets, is paramount as this generation flourishes, more so as it has developed a high regard for the efficiency, reliability and convenience of digital payment systems. Gen Z tourists are more likely to trust the service if an e-wallet can live up to their performance expectation for a quick, seamless transaction with minimum errors (Rosli, 2023). The MAE acts as an indicator of how accurately the system meets its users’ expectations, a lower Mean Absolute Error (MAE) signifying better predictive alignment with their desired experience.

For Gen Z domestic tourists, behavioral intention to use an e-wallet often hinges on ease of use, convenience, and the overall user experience (Wardana, 2022; Halim, 2022). If the performance expectation is consistently met or exceeded, Gen Z tourists are likely to continue using the service, as it simplifies their travel-related transactions like paying for transport, or dining (Liberato, 2019). An e-wallet that delivers with minimal error (low MAE), reinforces positive behavior intention, motivating them to rely on the app during their travels within the country (Leong, 2021).

Relationship between Effort Expectancy of MAE within Domestic tourist (Gen Z) behavioral Intention

Effort expectancy, which refers to the perceived ease of use of an e-wallet, plays a crucial role in shaping Gen Z domestic tourists’ behavioral intention (Mulyati, 2023). For this tech-savvy generation, they expect digital solutions to be intuitive, simple, and efficient (Nair, 2021). In using an e-wallet, if the system requires minimal effort to navigate and complete transactions, it enhances the likelihood of continued use.

For Gen Z tourists, effort expectancy is a key determinant of whether they will adopt and continue using an e-wallet during travel. If the app simplifies tasks like booking tickets, paying for services, or splitting bills, with low friction and high reliability, it aligns with their expectation for convenience (Chelvarayan, 2022; Saputra, 2023). A small number of complain indicates that the MAE consistently meets this ease-of-use demand, reinforcing their intention to use it regularly. Gen Z, who often prefer hassle- free solutions, are more inclined to trust and adopt the app if it requires minimal learning or troubleshooting (Rosli, 2023).

Relationship between Facilitating Condition of MAE within Domestic tourist (Gen Z) behavioral Intention

The relationship between facilitating conditions and the behavioral intention to use MAE among Gen Z domestic tourists is significant. Facilitating conditions refer to the availability of resources, technology, and support that make it easier for users to adopt and utilize a system like an e-wallet (Widodo, 2019). For Gen Z tourists, who are generally tech-savvy and familiar with mobile applications, the presence of such conditions (e.g., reliable internet access, user-friendly apps, and widespread acceptance of e-wallet payments at tourist destinations) encourages their intention to use e-wallet (Rahmadhani, 2022).

In the context of tourism, Gen Z values convenience and speed, and they are inclined toward using mobile apps that streamline their travel experiences (Loan, 2023). E-wallets, like other digital tools, offers the convenience of making payments swiftly, eliminating the need to carry cash or worry about currency exchange when traveling domestically (Wardana,2022). However, with the presence of facilitating conditions such as app usability, seamless integration with other services, and a wide acceptance of e-wallets at tourist attractions plays a crucial role in shaping their behavioral intention to adopt such technology (Leong, 2021).

Facilitating conditions act as an enabler for the behavioral intention to adopt e- wallets among domestic Gen Z tourists (Ojo, 2022). Therefore, tourism service providers and e-wallet companies should work together to ensure that their platforms are reliable and widely accepted at various tourist hotspots. By doing so, they can meet the expectations of Gen Z travelers and encourage greater use of e-wallets, thereby enhancing the overall tourism experience for this demographic segment.

Relationship between Perceived Enjoyment of MAE (e-wallet) with tourist Gen Z behavioral Intention

The relationship between perceived enjoyment and the behavioral intention to use MAE among Gen Z tourists is important in shaping their attitudes toward adopting this technology (Esawe, 2022). Perceived enjoyment refers to the degree of pleasure or fun users experience when using an app or service (Esawe, 2022). For Gen Z tourists, who are often drawn to engaging and interactive digital experiences, the enjoyment factor plays a significant role in their intention to use an e-wallet (Maulita, 2022). If the process of making payments through an e-wallet is seamless, aesthetically pleasing, and offers a positive user experience, Gen Z tourists are more likely to use it during their travels (Nor Azureen Rozekhi, 2023).

Perceived enjoyment goes beyond mere functionality, it ties into the overall experience users have with the e-wallet’s interface and the additional features it offers, such as rewards, gamification, or personalized promotions (Esawe, 2022). For a tech- savvy generation like Gen Z, an e-wallet that makes transactions feel enjoyable and user- friendly can drive higher usage (Rosli, 2023). They often appreciate apps that are intuitive, visually appealing, and easy to navigate, and this increases their likelihood of using such services regularly (Lim, 2022). When users feel a sense of enjoyment and satisfaction from using an app, it fosters positive attitudes and strengthens their behavioral intention to keep using the e-wallet, especially in travel scenarios where convenience is key.

Relationship between Trust of MAE within Domestic tourist (Gen Z) behavioral Intention

The relationship between trust and the behavioral intention to use MAE among Gen Z domestic tourists is a crucial factor in determining their willingness to adopt this technology. Trust, in this context, refers to the belief that the e-wallet system is reliable, secure, and capable of protecting users’ financial and personal data (Kim, 2010). Trust in the safety and integrity of an e-wallet platform is a dominant aspect that determines the intention to utilize one among Gen Z tourists, who are generally worried by online security and privacy (Nor Azureen Rozekhi, 2023). They will then feel comfortable making transactions via the app, knowing their information is secure if trust is established.

Trust in e-wallet (MAE) systems is determined by several factors, such as how data is processed, the reliability of the e-wallet provider, and the effectiveness of fraud protection measures (Chandran, 2023). Thus, this group will be more inclined to trust an e-wallet that is highly secured with strong security features like an encryption method and secure authentication methods (Rabbani, 2023).

The level of trust the appointed representative, a local domestic Gen Z tourist, has will be greatly associated with the biophysical intention of using an e-wallet tool while on the go (Hasan, 2020). Data shown until October 2023 This increases the likelihood of increased engagement with the technology by Gen Z tourists, as they may feel more assured that their personal and financial details are protected (2015).

Studies show behavioral factors that influence e-wallet adoptions and customers’ trust. In some contexts, customers’ trust strongly influences e-wallet reuse intentions (Hikmah Julia et al., 2024; Khusnul Khotimah et al., 2022). Trust and e-service quality play an essential role in customer satisfaction and loyalty (Dewi & Abdul Haeba Ramli, 2023). Attitudes and behavioral intention have a relationship with e-wallet based on lifestyle compatibility and trust (Yang, 2021).

METHODOLOGY

Research Design

Research design represents an important step in any research project, as it creates a guideline on how to collect and analyze data (Mackey et al.,2021). Based on previous formulation, the researchers have chosen a quantitative research design which allows for a systematic examination and quantification of characteristics and functions of the market. This was a quantitative-based paper exploring associations between the dependent and independent variables as per the theoretical framework.

Population and Sample

Gen Z are described as those born between 1995 and 2010, as a group they have lived in the age of technology and social media, having a large impact on their interests and lifestyle choices (Jayathilake & Annuar, 2020). A salient characteristic of this generation is that they prefer experiences over material goods and have made active contributions to domestic tourism (Shiwei Shen et al., 2023). Gen Z is in Kuala Lumpur is often discovered to visit local attractions, cultural events, or unique activities that portray the richness of the city. Their increasing familiarity with technology has made it possible for them to access information, book trips using mobile applications, and share their experiences online, fundamentally influencing their travel choice.

Gen Z travellers in Kuala Lumpur for domestic tourism are the population of this study. Such young travellers form an important segment of the tourism contingent, and their motivations, behaviors and satisfaction levels are important for businesses and stakeholders in the tourism industry. Investigating the factors influencing their travel decisions will allow researchers to understand these activities and to develop better services and marketing approaches targeting this specific demographic group.

The Importance of Sample Size Determination in Studies of Tourism Satisfaction among Young Travelers An appropriate selection of the sample size increases a study statistical power and its ability to identify meaningful effects in different settings (Beck et al., 2013). According to Olejnik et al. (1984), determining an appropriate sample size involves considering four key factors: significance level, statistical power, analysis procedure, and effect size.

The sample size for this research was determined using the Krejcie and Morgan table (1970), which helped decide how many people to survey based on the population size. According to the table, a population of (8,691,172) required a sample of (384) to ensure reliable and statistically significant results. However, only 100 respondents were validated in the study because some participants did not complete the questionnaire, and others chose not to participate. The sample size for this research was determined using the Hair et al. (2018), which is exploratory factor analysis cannot be done if the sample has less than 50 observations (which is still subject to other factors), whereas simple regression analysis needs at least 50 samples and generally 100 samples for most research situations. From the academic perspective of Mastrangelo (2020), recommends a sample of 385 for optimal accuracy, with a minimum of 100 for meaningful use.

Questionnaire Design and Development

The literature has extensively support the efficacy of the fundamental UTAUT dimensions: performance expectancy and effort expectancy, as predictors of users’ attitudes toward and intentions to accept new technologies (Venkatesh, Morris, Davis, & Davis, 2003). This study focuses on these two UTAUT dimensions. Nevertheless, the universal validity of UTAUT has been scrutinized, with findings suggesting its applicability might vary across different cultural contexts (McCoy, 2007). Hence, while UTAUT can provide valuable insights into technology acceptance in Malaysia, its application should be approached carefully, considering cultural nuances and contextual factors.

The questionnaire was divided into 3 sections. The questions used were adapted from UTAUT as a survey sample to investigate users’ acceptance towards “Factors Influencing the Adoption of Mobile Payment Method among Gen Z: the Extended UTAUT Approach” (Triasesiarta Nur et al.,2021). All sections have used a five-point Likert scale, ranging from (1) “strongly disagree” to (5) “strongly agree”. At the end of the questionnaire, respondents were asked for their demographic profile, including gender, age, occupation, income and usage of mobile payment.

Pilot Test

SPSS will be used in this study for the data collection because it is useful for quantitative research and effective data analysis. The table below shows the data that researcher got from the software of SPSS version 29.

 Table 2: Pilot Test

The purpose of a pilot test is to determine whether the questions asked in an interview are understandable and reliable. A pilot test assesses the study’s validity and reliability. In this study, 30 respondents participated in a pilot test to evaluate the reliability of the questionnaire. The table above displays the pilot test results generated by SPSS, which was used to test the reliability of the survey items measuring Performance Expectancy, Effort Expectancy, Facilitating Conditions, Perceived Enjoyment, Trust, and Behavioral Intention.

Table 1 shows the summary and results of the reliability test for the research constructs. According to Taber (2017), Cronbach’s alpha is commonly used to demonstrate that the tests and scales constructed or adopted for research are fit for purpose. Alpha values are described as excellent (0.93–0.94), strong (0.91–0.93), reliable (0.84–0.90), robust (0.81), fairly high (0.76–0.95), high (0.73–0.95), good (0.71–0.91), relatively high (0.70–0.77), reasonable (0.67–0.87), adequate (0.64–0.85),moderate (0.61–0.65), satisfactory (0.58–0.97), acceptable (0.45–0.98), sufficient (0.45–0.96), not satisfactory (0.4–0.55), and low (0.11) (Taber, 2017).

However, in this study, the Cronbach’s Alpha for each set of items scored as follows: Performance Expectancy (0.962), Effort Expectancy (0.941), Facilitating Conditions (0.722), Perceived Enjoyment (0.845), Trust (0.922), and Behavioral Intention (0.849). All measurement items in this study are considered trustworthy based on these results, which align with Taber (2017).

Data Collection

For the study on the factors influencing domestic tourist (Gen Z) behavioral intentions towards mobile payment apps (MAE) in Kuala Lumpur, a quantitative approach will be employed to gain a comprehensive understanding of the factors impacting satisfaction and behavioral intention. Initially, a literature review was conducted to identify existing research and gaps regarding mobile payment application among Genration Z. This will guide the design and pre-testing of a survey questionnaire to ensure clarity, relevance, and appropriateness for the demographic (Creswell & Creswell, 2018). Following this, ethical approval has been sought from institutional review boards to meet ethical standards, including informed consent and data confidentiality (American Psychological Association, 2020).

The data collection phase involves distributing structured questionnaires to Gen Z users of the MAE application. The sample was selected by using convenience sampling, where researchers select easily accessible participants (Benites et al., 2023). Based on Tourism Malaysia statistics, this study focused on 8,691,172 hotel guests from domestic tourism for the first half of 2024 (January — June). Before respondents answer the survey, there are three screening questions they must answer to determine whether their characteristics align with the researcher’s requirements for the study:

1. Domestic tourist
2. Age ranges from 18 – 28-year-old (2006– 1996)
3. Use MAE for payment solution

If the respondents met these criteria, they proceeded to answer the survey by scanning the QR code provided by the researcher. Surveys were administered in online platforms (Google Form) and distributed through face-to-face interactions with clear instructions to ensure accurate responses (Kumar, 2011). For Kuala Lumpur, the top destinations were the malls: Pavilion Kuala Lumpur, Pasar Seni, Sogo, Berjaya Times Square and the Kuala Lumpur Convention Centre (Ayamany, 2021). Snowfall at Pavilion Bukit Bintang (Wahab, 2024) and Viva Batik Malaysia 2024 in Pasar Seni Kuala Lumpur (Azaman, 2024) held on December 2024 which successfully attract a lot of tourists. Therefore,researchers have decided to collect respondent data at Pavilion Bukit Bintang and Pasar Seni.

The final phase consists of preparing a detailed research report covering methodology, findings, discussions, and recommendations. The findings are shared with relevant stakeholders, including mobile payment providers, industry practitioners, and academic audiences through presentations and publications (Creswell & Creswell, 2018). The entire research process, from data collection to reporting, were planned to span approximately across four months, contributing valuable insights for improved mobile payment strategies tailored to Gen Z.

Data Analysis

In this study, all data gathered through the questionnaire underwent thorough processing and analysis using SPSS version 29, a widely recognized software package for statistical analysis in social sciences research. The researcher has employed a variety of statistical tests to conduct a comprehensive analysis of the dataset. Initially, descriptive statistics including means, standard deviations, frequencies, and percentages were utilized to systematically examine and outline the distribution of data. These statistical measures provided a clear overview of the sample characteristics and responses, aiding in the initial understanding of the dataset profile.

The minimum sample size required was 50, and 100 respondents data was successfully collected. This study focused on factors such as Performance Expectancy, Effort Expectancy, Facilitating Conditions, Perceived Enjoyment, and Trust and the behavioral intention in using these applications particularly in context of domestic tourist in Kuala Lumpur.

FINDINGS

Respondent Profile

Table 3 : Respondent profile

Demographic of the respondent profile is included in part A in total of 7 questions. There were 100 Domestic tourist (Gent Z) that has been interviewed by face to face method. Based on the gender data collected, respondent (n=100) there were 51% male and 49% female. Most respondents are between 22-25 years old (45%), followed by the 18-21 age group (32%) and 26-28 age group (23%). More than half of the respondents are currently employed (56%) and the rest is students (42%). In terms of income, almost half of the respondents earn between RM1,500-RM3,500 (48%), followed by those earning below RM1,500 (41%). Mobile payment usage is even, with most respondents having used it for 1-2 years or 3-4 years (34% each). Majority of the respondents are Malay (84%), followed by Indian (10%) and Chinese (6%). Respondents are predominantly from Selangor (40%), followed by Johor (19%) and others (28%), with smaller representations from Pahang (4%) and Penang (9%).

Descriptive Analysis

Perceived Enjoyment towards Mobile Payment (MAE) Applications

Table 4 : Descriptive Analysis

A descriptive analysis of Performance Expectancy towards Mobile Payment (MAE) Applications in a study on the factors influencing domestic tourist (Gen Z) behavioral intentions towards mobile payment apps (MAE) in Kuala Lumpur shows that Gen Z domestic tourists have high expectations for MAE’s performance. The statement “The mobile payment service allows me to complete online transactions faster” received the highest mean score of 4.60, indicating that Gen Z strongly agrees that MAE speeds up and simplifies their online transaction process. Meanwhile, the statement “Using a mobile payment service will increase my productivity in online transactions” had the lowest mean score of 4.46. Nevertheless, this score still demonstrates a high level of agreement. The difference between the highest and lowest scores indicates that Gen Z domestic tourists in Kuala Lumpur strongly agreed that transaction speed and convenience are the most important factors in measuring performance expectancy for MAE, compared to overall productivity gains.

Furthermore, the data collected highlights users’ Effort Expectancy towards Mobile Payment (MAE) Applications” focusing on ease of use and accessibility. The statement “Learning how to operate transactions through the mobile payment service was easy for me” recorded the highest mean score of 4.53, indicating that Gen Z domestic tourists find it easy to learn and use MAE’s features. Meanwhile, the statement “Using a mobile payment service makes it easier for me to do online transactions” had the lowest mean score, at 4.51. The difference between the highest and lowest scores is relatively small, indicating that all aspects of MAE’s ease of use are rated highly by Gen Z domestic tourists.

Moreover, the attribute of Facilitating Conditions towards Mobile Payment (MAE) Applications shows that the item “I have sufficient knowledge to use the mobile payment service” received the highest mean score of 4.35, indicating that Gen Z domestic tourists are confident in their ability to use MAE. Conversely, the statement “I will easily get help from other people when I find it difficult to use the mobile payment service” had the lowest mean score of 4.15. However, this score still indicates a reasonably high level of agreement, suggesting that Gen Z domestic tourists are confident in receiving support if needed. The difference between the highest and lowest scores shows that personal knowledge of MAE usage is more emphasized by Gen Z compared to reliance on help from others.

Next, the attribute of Perceived Enjoyment toward Mobile Payment (MAE) Application shows that the item “I enjoy using the mobile payment service for online transactions” received the highest mean score of 4.38, indicating that Gen Z domestic tourists generally find using MAE enjoyable. In contrast, the statement “For me, using the mobile payment service for online transactions is very entertaining” had the lowest mean score of 4.20. While this is the lowest score in this category, it still represents a positive sentiment. The small difference between the highest and lowest mean scores suggests a consistent level of positive perception related to the enjoyable aspects of using MAE among this demographic.

After that, under the attribute of Trust towards Mobile Payment (MAE) Applications shows that the item “I am sure that online transactions using mobile payment services are reliable” received the highest mean score of 4.33, indicating a strong belief among Gen Z domestic tourists in the reliability of MAE for online transactions. In contrast, the statement “I feel safe transacting online using the mobile payment service” received the lowest mean score of 4.13. While still indicating a positive sentiment, this lower score suggests that feelings of safety during online transactions using MAE could be an area for potential improvement or further investigation. The difference between the highest and lowest mean scores highlights that while reliability is a strong point for MAE, building a stronger sense of safety might further enhance user trust.

In drawing things to a close, the attribute “behavioral Intention using e-wallet (MAE)” shows that the statement “I will continue to use the mobile payment service MAE” and “I will often use the mobile payment service when transacting online,” both achieved the highest mean score of 4.48. This indicates a very strong likelihood that Gen Z domestic tourists intend to keep using MAE and frequently utilize it for online transactions. The statement “I will recommend my friends to use the mobile payment service” received the lowest mean score of 4.37. Although this score is still high and signifies a positive intention to recommend MAE, it is slightly lower than the other statements related to personal use. The small difference between the highest and lowest mean scores suggests a generally consistent and high level of behavioral intention across all measured aspects.

In the conclusion, with a mean score above 4.0 for every statement within the attribute, the descriptive statistics indicate that most respondents showed a strong positive intention to use MAE during domestic tourist visits to Kuala Lumpur.

Relationship Analysis

Correlation

Table 5 : Correlation

The table below shows how the researcher used several multiple regression analysis to look at the factors influencing domestic tourist (Gen Z) behavioral intentions towards mobile payment apps (MAE) in Kuala Lumpur. Regression analysis use R-value to quantify the proportion of variability from independent variable that contributes to dependent variable. The study framework’s variables were analysed using a regression sequence to determine the correlations between them and the mediating role of overall satisfaction. The purpose of the correlation analysis was to look at the connections between different variables. The direction and intensity of linear correlations between pairs of variables are shown by the Pearson correlation coefficients.

The correlation table 5 shows a significant relationship between the mobile payment application use behavior (MAE) of gen z domestic tourists in Kuala Lumpur and performance, effort, facilitating conditions, perceived usefulness, or trust. As the data indicates, all these metrics have positive correlations with behavioral intention, with effort and behavior having the strongest correlation (r=0.845, p<0.001), followed closely by perceived usefulness (r=0.831, p<0.001). That is if MAE application easy to use and meets user expectations, increasing trust in applications thus encourage usage behavior in a longer time.

At its core, the data show that effort, facilitating conditions and trust are the driving forces behind the behavioral intention of MAE application users, which in turn, reflect the satisfaction of existing users. This means that when the application is reliable, accessible, and able to fulfil their transaction needs seamlessly, domestic tourists are more likely to utilize MAE. The results in this study can help tourism organizations and application developers to enhance their customer experience which consequently increases tourists’ use of mobile payment

Model Summary

Table 6 : Model Summary

Based on the Model Summary, the high R value (0.845ª) indicates the highest strong relationship between effort expectancy and behavioural intention. This strong relationship confirms that when effort expectancy are prioritized, MAE user increases, subsequently motivating them to continue using it. Followed by the R value of perceived enjoyment relationship with behavioural intention which is (0.831 ª). This data show that MAE user enjoyed using MAE as their transaction platform and will be continue using it.

Moreover, the R value of performance expectancy and facilitating condition is strong in relationship with behavioural intention which is (0.792 ª) and (0.784 ª). The R value of both factors indicates that MAE user considers smooth transaction and compatible devices are crucial in determining their decision on continuing usage.

Lastly, the lowest R value would be trust (0.730 ª) that indicate moderate relationship with behavioural intention. The R value show that security and reliability

are essential considerations for users. By improving security of MAE, Maybank should be able to increase their new user also retaining their existing user.

H1: Performance Expectancy has a significant strong positive effect on Behavioral Intention

H2: Effort Expectancy has a significant strong positive effect on Behavioral Intention

H3: Facilitating Condition has a significant strong positive effect on Behavioral Intention H4: Perceived enjoyment has a significant strong positive effect on Behavioral Intention H5: Trust has a significant moderate positive effect on Behavioral Intention

Coefficients.

Table 7 : Results of Regression Analysis

The regression analysis in this table provides insights into the relationship between various independent variables (Performance, Effort, Facilitating, Perceived, Trust) and satisfaction with mobile payment applications (MAE) as well as behavioral intention among domestic tourists from Generation Z in Kuala Lumpur. The coefficients in this table demonstrate the extent to which each independent factor influences user satisfaction with the mobile payment application.

Effort (B = 0.309, Beta = 0.341, Sig. < 0.001) has the most significant impact on user satisfaction, as evidenced by its very low significance value. This suggests that elements related to Effort, potentially ease of use or the reliability of the MAE application, play a crucial role in influencing user satisfaction and, subsequently, their behavioral intention to continue using the application. Perceived is also significant (B = 0.248, Beta = 0.305, Sig. = 0.003), indicating that it is the second most important factor in influencing satisfaction.

On the other hand, Performance shows a moderate but significant effect (B = 0.189, Beta = 0.195, Sig. = 0.024). While it is significant, its impact is lower compared to Effort and Perceived. However, Facilitating and Trust do not show a significant relationship with user satisfaction (Sig. values of 0.535 and 0.371, respectively), suggesting that these factors may be less relevant or not influential enough in affecting tourist satisfaction in the context of MAE applications.

DISCUSSION & CONCLUSION

This research investigated the factors influencing Generation Z’s behavioral intentions towards mobile payment applications (MAE) in Kuala Lumpur, providing a comprehensive analysis across four chapters.

Established the context of the study, emphasizing the rapid transformation of the tourism industry through mobile payment technologies. It highlighted the significance of understanding Gen Z’s preferences, as this demographic is increasingly shaping the landscape of domestic tourism. The chapter underscored the importance of mobile payment applications in enhancing the travel experience, offering convenience and security, which are critical for tech-savvy travelers. Research questions were crafted to investigate the effect of performance expectancy, effort expectancy, facilitating conditions, perceived enjoyment, and trust on Gen Z adoption of these technologies.

A framework was provided based on a theoretical approach called the Unified Theory of Acceptance and Use of Technology (UTAUT). Using this framework, it helped find the relevant factors that affect Gen Z’s behavioral intentions towards mobile payment apps. Socioeconomic factors played a big role in the chapter explored the concept of performance expectancy in relation to mobile payment utilization, while effort expectancy addressed ease of use. The most important thing is to develop conditions that would provide users with the resources and assistance they need to work with these applications. User enjoyment in using mobile payment application play a vital role in determining their behavioral intention, thus perceived enjoyment was also discussed. Lastly, trust was discussed whether the security in using mobile payment application is reliable in user perspective. The chapter concluded that understanding these factors is crucial for developing strategies that resonate with Gen Z’s expectations.

The research methodology, include the design of the structured questionnaire and the sampling method. The use of convenience sampling where researchers select easily accessible participants. The chapter emphasized the importance of ethical considerations and the reliability of the data collection instruments, which were validated through a pilot study. This methodological rigor ensured that the subsequent analysis would yield meaningful insights into the factors influencing domestic tourist Gen Z behavioral intentions.

Results showed that the identified factors significantly affected Gen Z’s intention of using mobile payment applications. Specifically, Effort Expectancy, Perceive Enjoyment and Performance Expectancy were the important factors affecting mobile payment intention for Gen Z, indicating that they are influenced by the ease of use, enjoyment and efficiency of these solutions. However, facilitating conditions and trust was found to be not significant in this regard, suggesting the importance of sufficient and stable resources also adding an extra layer of protection to ensure user privacy.

Thus, this study was able to successfully meet its main objectives, ascertain the factors that affect domestic tourist Generation Z behavioral intentions to adopt MAE applications and establish a theoretical framework that highlights the link between These factors and behavioral intention, based on the qualitative research methodology, which yields in-depth insights into the significance of continuous upgrades on mobile payment applications following user needs, specifically Generation Z.

RECOMMENDATIONS

In future research, it is also suggested taking a more heterogeneous sample from other areas and conditions. In turn, this will enhance the findings and impact the understanding of domestic tourist (Gen Z) behavioral intention to utilizing mobile payment applications (MAE). Additionally, qualitative methods, such as interview or focus group methods, have the potential to enhance quantitative analysis by providing a deeper understanding of this demographic’s concerns and preferences, as well as the nuances of their interactions with mobile payment (MAE) technology.

Future researcher are recommended to conduct the research that assess the evolution of domestic tourist Generation Z attitudes and behavioral tendencies towards mobile payment (MAE) applications over time. Data guiding technology and user experiences are moving at fast pace, making it essential for stakeholders to constantly improve their services. In example, the analysis of domestic tourist (Gen Z) characteristics can serve as a building block for Maybank marketing purpose for this specific group. The comparative analyses between domestic tourist (Gen Z) and other age groups may reveal distinct characteristics and preferences for new marketing strategies.

Limitations of Study

One of the limitations of this study is that it focusses on a certain client profile and obtained only 100 respondents out of 384, which may not accurately represent the population’s variety. As a result, the findings may not apply to other generations also weak to represent generation Z as general because of their behaviours, preferences, or levels of access to mobile payment technologies may be differ. This proven by the huge gap in the number of respondents data collected. Future study should consider to include broader and more diverse selection of participants to acquire more comprehensive result of mobile payment acceptance across different generations.

This study used convenience sampling at two Kuala Lumpur sites with a modest sample size (n=100). Results may not generalise beyond Gen Z domestic tourists or to other e-wallet brands. Future work should employ probability sampling, larger multi-city samples, and test UTAUT2 moderators (age, gender, experience); comparative studies across e-wallets and destinations are also warranted.

Additionally, the geographical focus on Kuala Lumpur may restrict the applicability of the findings to other regions or countries. As such, the insights gained from this study may not be relevant to Generation Z users in different contexts as example Gen Z that live in rural area. Therefore, by highlighting the need for further research in varied geographical settings it can enhance the understanding about user of mobile payment application and the behavioral intention across diverse geographical area.

REFERENCES

1. Abas, A. (2020, January 12). Overwhelming response towards e-Tunai initiative. New Straits Times, p. online. Retrieved from https://www.nst.com.my/news/nation/2020/01/556779/overwhelming-response- towards-e-tunai-initiative
2. Abdullah, N.A., Redzuan, F., & Daud, N.A. (2020). E-wallet: factors influencing user acceptance towards cashless society in Malaysia among public universities. Indonesian Journal of Electrical Engineering and Computer Science, 20, 67-74.
3. Agarwal, P. (2024). Evaluating the Impact of Security Measures on Customer Trust in E-Wallet Transactions. International Journal of Science and Research (IJSR).
4. Ahmad, S.Z. (2013). Slow Growth or Rapid Internationalization in Emerging Markets: The Case of Maybank Berhad. Global Business and Organizational Excellence, 33, 19-39.
5. Ahmed, N. (2019). Generation Z’s Smartphone and Social Media Usage: Survey. Journalism and Mass Communication.
6. Ajina, A., Joudeh, J., Ali, N., Zamil, A., & Hashem, P. (2023). The effect of mobile-wallet service dimensions on customer satisfaction and loyalty: An empirical study. Cogent Business & Management, 10.
7. Alaeddin, O., & Altounjy, R. (2018). Trust, Technology Awareness and Satisfaction Effect into the Intention to Use Cryptocurrency among Generation Z in Malaysia.
8. Al-Okaily, M. (2023). The influence of e-satisfaction on users’ e-loyalty toward e-wallet payment apps: a mediated-moderated model. International Journal of Emerging Markets.
9. American Psychological Association. (2020). Publication manual of the American approaches (4th ed.). Sage Publications.
10. Archer, B.H. (1978). Domestic tourism as a development factor. Annals of Tourism Research, 5, 126-141.
11. Ariffin, S., Rahman, M., Muhammad, A., & Zhang, Q. (2021). Understanding the consumer’s intention to use the e-wallet services. Spanish Journal of Marketing – ESIC.
12. Arvey, R.D. (1972). Task performance as a function of perceived effort performance and performance-reward contingencies☆. Organizational Behavior and Human Performance, 8, 423-433.
13. ARZIANA MOHMAD AZAMAN. (2024, November 15). Syoknya dapat belajar banyak ilmu di Pasar Seni Kuala Lumpur, ini 4 activity menarik beli jiwa tersayang | SinarPlus. SinarPlus. https://sinarplus.sinarharian.com.my/jom-jalan-makan/jom-jalan/syoknya-dapat-belajar- banyak-ilmu-di-pasar-seni-kuala-lumpur-ini-4-aktiviti-menarik-beli-jiwa-tersayang
14. Augustin, S. (2020). Nearly 3 mil sign up for e-Tunai initiative , says Guan Eng. Free Malaysia Today, p. online. Retrieved from https://www.freemalaysiatoday.com/category/nation/2020/01/20/nearly-3-mil-sign-up-for-e-tunai-initiative-says-guan-eng/
15. Ayamany, K. (2021, September 30). The most visited places in Malaysia in pandemic year 2020: Zoo Negara, Sibu Central Market, Melaka River Cruise. Malay Mail. https://www.malaymail.com/news/malaysia/2021/09/30/the-most-visited-places-in-malaysia-in-pandemic-year-2020-zoo-negara-sibu-c/2009659
16. Ayu, I., Jayantari, A.U., Wardana, M., Ayu, G., Giantari, K., & Setiawan, P.Y. (2021). Perceived Usefulness, Perceived Ease of Use, and Consumer Satisfaction on Repurchase Intention of Digital Wallet Service (e-wallet).
17. Beck, T. W. (2013). The importance of a priori sample size estimation in strength and conditioning research. The Journal of Strength and Conditioning Research, 27(8), 2323– 2337.
18. Benites, O. G. C., Benítez, J. M. C., Del Rocio Ortiz Guevara, D., & Arenas, D. C. P. (2023). Production Order Costing system: Coconut food producing and processing industry. Centro Sur, 7(2).
19. Blackman, D.A., Buick, F., O’Flynn, J., O’Donnell, M.E., & West, D. (2017). Managing Expectations to Create High Performance Government. Review of Public Personnel Administration, 39, 185 – 208.
20. Canavan, B. (2013). The Extent and Role of Domestic Tourism in a Small Island. Journal of Travel Research, 52, 340 – 352.
21. Chandran, L., Lundin, L., & Padayatti, G. (2023). Transforming Personal Data Transactions with Auditable, Privacy-Preserving Data Exchange Agreements: Fostering Transparency and Trust in Digital Wallet Ecosystems. 2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation (ETFA), 1-9.
22. Chelvarayan, A., Yeo, S., Yi, H., & Hashim, H. (2022). E-Wallet: A Study on Cashless Transactions Among University Students. F1000Research, 11.
23. Cinar, K. (2020). Role of Mobile Technology for Tourism Development.
24. Clarissa, & Keni (2022). Effort Expectancy, Facilitating Condition, dan Trust untuk Memprediksi Behavior Intention Penggunaan e-Wallet. Journal Manajemen Bisnis dan Kewirausahaan.
25. Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and Daragmeh, A., Saleem, A., Bárczi, J., & Sági, J. (2022). Drivers of post-adoption of e-wallet
26. among academics in Palestine: An extension of the expectation confirmation model. Frontiers in Psychology, 13.
27. Daragmeh, A., Saleem, A., Bárczi, J., & Sági, J. (2022). Drivers of post-adoption of e-wallet among academics in Palestine: An extension of the expectation confirmation model. Frontiers in Psychology, 13.
28. Esawe, A. (2022). Understanding mobile e-wallet consumers’ intentions and user behavior. Spanish Journal of Marketing – ESIC.
29. Geebren, A., Jabbar, A., & Luo, M. (2021). Examining the role of consumer satisfaction within mobile eco-systems: Evidence from mobile banking services. Comput. Hum. Behav., 114, 106584.
30. Ghani, N., Mansor, M., & Zakariya, K. (2018). Gen Z’s Activities And Needs For Urban Recreational Parks. Planning Malaysia Journal.
31. Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2018). Multivariate Data Analysis (8th ed.). United Kingdom: Cengage Learning.
32. Halim, F., Efendi, E., Butarbutar, M., Malau, A.R., & Sudirman, A. (2020). Constituents Driving Interest in Using E-Wallets in Generation Z. Proceeding on International Conference of Science Management Art Research Technology.
33. Hanif, A., Jamal, F., & Imran, M. (2018). Extending the Technology Acceptance Model for Use of e-Learning Systems by Digital Learners. IEEE Access, 6, 73395-73404.
34. Harahap, F.Y., Fauzi, A., & Situmorang, S.H. (2023). The Influence Of Digital Customer Experience And Enjoyment On Flip E-Wallet E-Loyalty Through E-Trust In
35. Medan City Millenial Generations. International Journal of Economic, Business, Accounting, Agriculture Management and Sharia Administration (IJEBAS).
36. Hasan, A., & Gupta, S. (2020). Exploring Tourists’ Behavioural Intentions Towards Use of SelectMobile Wallets for Digital Payments. Paradigm, 24, 177 – 194.
37. Hsu, H., Hsu, J., Wang, S., & Chang, I. (2016). Exploring the Effects of Unexpected Outcome on Satisfaction and Continuance Intention. Journal of Electronic Commerce Research, 17, 239.
38. Imani, A.T., & Anggono, A.H. (2020). Factors Influencing Customers Acceptance of Using the QR Code Feature in Offline Merchants for Generation Z in Bandung (Extended UTAUT2). KnE Social Sciences.
39. Istianah (2021). Analisis Kendala Implementasi Marketplace Pemerintah dan Digital Payment Dalam Pemberdayaan UMKM. ILTIZAM Journal of Shariah Economics Research.
40. Jafari, J.Y. (1987). On Domestic Tourism. Journal of Travel Research, 25, 36 – 38.
41. Jameel, A.S., Rahman Ahmad, A., & Alheety, A.S. (2022). Behavioural Intention to Use e-Wallet: The Perspective of Security and Trust. 2022 2nd International Conference on Emerging Smart Technologies and Applications (eSmarTA), 1-5
42. Jayathilake, H., & Annuar, N. (2020). Exploring HRM practices to retain Generation-Z in the information technology sector: A systematic literature review. International Journal of Business and Technopreneurship, 10(1), 79–100.
43. Johnston, W.J., & Kim, K. (1994). Performance, Attribution, and Expectancy Linkages in Personal Selling. Journal of Marketing, 58, 68 – 81.
44. Julia, H., Sauf, A., & Buana Sakt, D.P. (2024). The Effect of Customer Trust and E-Service Quality on E-Wallet Application Reuse Intentions Mediated by Customer Satisfaction: A Comparative Study on Master of Management Students in Indonesia and Malaysia. Journal of Economics, Finance and Management Studies.
45. Kapoor, A.R., Dalmia, A., & Rajkumar (2021). Identifying Determinants That Influence the Customer’s Choice Of Using Payment Applications. Journal of emerging technologies and innovative research, 8.
46. Kar, M.H., Faizal, S., & Chinnasamy, S. (2019). The Perception and Engagement of Digital Natives and Digital Immigrants toward A Banking Institution Communications and Promotional Tools on Social. International Journal of Recent Technology and Engineering.
47. Karnouskos, S. (2004). Mobile payment: A journey through existing procedures and standardization initiatives. IEEE Communications Surveys & Tutorials, 6.
48. Kaushik, A., Agrawal, A., & Rahman, Z. (2015). Tourist behaviour towards self-service hotel technology adoption: Trust and subjective norm as key antecedents. Tourism Management Perspectives, 16, 278-289.
49. Kee, D.M., Hisam, N.A., Rashid, N.H., Aziz, N.S., Mazlan, N.A., & Mahadi, N.A. (2021). The Impact of Using Cashless Payment during the Covid-19 Pandemic: A Case Study of Maybank. International Journal of Accounting & Finance in Asia Pasific.
50. Kerviler, G., Demoulin, N., & Zidda, P. (2016). Adoption of in-store mobile payment: Are perceived risk and convenience the only drivers?. Journal of Retailing and Consumer Services, 31, 334-344. https://doi.org/10.1016/J.JRETCONSER.2016.04.011.
51. Khatri, V., Samuel, B.M., & Dennis, A.R. (2018). System 1 and System 2 cognition in the decision to adopt and use a new technology. Inf. Manag., 55, 709-724.
52. Khechine, H., Lakhal, S., & Ndjambou, P. (2016). A meta‐analysis of the UTAUT model: Eleven years later. Canadian Journal of Administrative Sciences-revue Canadienne Des Sciences De L Administration, 33, 138-152.
53. Khotimah, K., Lina, R.N., Yendra, & Yunus, M. (2022). Customer Interest Dalam Menggunakan E-Wallet Ovo Yang Di Pengaruhi Oleh Trust, Benefit and Risk Di Mall Jayapura Papua. Journal of Economics Review (JOER).
54. Kim, C., Tao, W., Shin, N., & Kim, K. (2010). An empirical study of customers’ perceptions of security and trust in e-payment systems. Electron. Commer. Res. Appl., 9, 84-95.
55. Kornreich, L.B. (1968). Performance Expectancy as a Determinant of Actual Performance: Failure to Replicate. Psychological Reports, 22, 535 – 543.
56. Krejcie, R.V., & Morgan, D.W., (1970). Determining Sample Size for Research Activities. Educational and Psychological Measurement.
57. Kumar, R. (2011). Research methodology: A step-by-step guide for beginners (3rd ed.).
58. Lacap, J.P. (2022). Exploring Mobile Wallet Adoption in the Philippines: A Partial Least Squares Path Modelling Approach. Proceedings of The International Halal Science and Technology Conference.
59. Leong, M., Kwan, J., & Lai, M. (2021). Technology readiness and UTAUT2 in e-wallet adoption in a developing country. F1000 Research, 10.
60. Levania, M. K. (2022, July 28). Translation, validity and reliability of decision style Liberato, P., Aires, C., Liberato, D., & Rocha, Á. (2019). Generation Z and the Technology Use During a Trip., 77-90.
61. Lim, X., Ngew, P., Cheah, J., Cham, T., & Liu, Y. (2022). Go digital: can the money-gift function promote the use of e-wallet apps?. Internet Res., 32, 1806-1831.
62. Limanan, C.C., & Keni, K. (2023). BEHAVIORAL INTENTION TO USE DIGITAL WALLETS IN INDONESIA. International Journal of Application on Economics and Business.
63. Liu, J.C., Wang, C., Zhang, T.C., & Qiao, H. (2022). Delineating the Effects of Social Media Marketing Activities on Generation Z Travel Behaviors. Journal of Travel Research, 62, 1140 – 1158.
64. Liu, W., Wang, X., & Peng, W. (2020). State of the Art: Secure Mobile Payment. IEEE Access, 8, 13898-13914.
65. Loan, N.T., Huy, D.T., Trang, L.H., & Hoang, N.V. (2023). Intention to Use Mobile Applications in Tourism among Gen Z in Vietnam. International Journal of Scientific Research in Science and Technology.
66. Loan, P., & Hoang, M. (2023). Generation Z’s Travel Trend and Behavior: A Systematic Literature Review. JOURNAL OF ECONOMICS, FINANCE AND MANAGEMENT STUDIES.
67. Mabkhot, H., Alsughayir, A., Ghaleb, M., & Albarq, A. (2023). Understanding the factors of mobile payment continuance intention: empirical test in Saudi Arabia. Journal of Law and Sustainable Development.
68. Mackey, A., & Gass, S. (2021). Second language research: Methodology and design.
69. Maharjan, A., Danuwar, R. K., Kayestha, M., Maharjan, M., Baral, D. K., Koirala, A., & Timalsina, D. P. (2024). Analysing Customers’ Perception on QR Payment in Kathmandu Valley: An Empirical Study using UTAUT and PLS-SEM. Quest Journal of Management and Social Sciences, 6(1), 57–73.
70. Mainul Hossain, M., Akter, S., & Adnan, H.B. (2022). Does the trust issue impact the intention to use e-wallet technology among students? Journal of Entrepreneurship and Business.
71. Makwana, D., Engineer, P., Dabhi, A., & Chudasama, H. (2023). Sampling methods in research: A review. International Journal of Trend in Scientific Research and Development, 7(3), 762–768.
72. Mareta, Y., & Meiryani, M. (2023). Determinants of Interest Using QRIS as a Payment Technology For E-Wallet by Z Generation in Indonesia. Syntax Literate ; Journal Ilmiah Indonesia.
73. Mastrangelo, P. (2020). Improving the Design and Interpretation of Sample Surveys in the Workplace.
74. Maulita, M., Amalia, P., & Luturnas, F. (2022). Factors That Influence Generation Z in Using E- Wallet During COVID-19 Pandemic. Proceedings of the International Conference on
75. Applied Science and Technology on Social Science 2021 (iCAST-SS 2021). mixed methods approaches (5th ed.). Sage Publications.
76. Milenković, D., Petković, J., & Marinković, S. (2022). Globalization and Its Impact on Technological Development. 41st International Conference on Organizational Science Development.
77. Mondol, E., Salman, N.A., Rahid, A.O., & Karim, A.M. (2021). Determinants of Consumer’s Willingness to Purchase Online in Malaysia: The Role of GEN Z’s Attitude. International Journal of Academic Research in Business and Social Sciences.
78. Mulyati, Y., Elsandra, Y., & Alfian, A. (2023). Determining Factors of E-Wallet Use Behavioral Intention: Application and Extension of The UTAUT Model. JOURNAL OF ECONOMICS, FINANCE AND MANAGEMENT STUDIES.
79. Nair, C. (2021). A Study on Millennials and Generation Z’s Attitude and Usage of E-Transaction and Mobile wallets in Mumbai. International Journal for Research in Applied Science and Engineering Technology.
80. Ngah, R., Putit, L., Mat, A., Abdullah, J., & Majid, R.A. (2020). MODERATING EFFECT OF SERVICE QUALITY ON PUBLIC TRANSPORT TRAVEL BEHAVIOUR AND ANTECEDENTS. PLANNING MALAYSIA JOURNAL, 18.
81. Nguyen, V.H., Truong, T., Pham, H.T., Tran, D.T., & Nguyen, P.H. (2021). Travel Intention to Visit Tourism Destinations: A Perspective of Generation Z in Vietnam. Journal of Asian Finance, Economics and Business, 8, 1043-1053.
82. Nor Azureen Rozekhi (2023). Factors Affecting Generation Z’s E-Wallet Use and Behavioral Intentions in Shah Alam, Selangor. International Journal of Business and Technology Management.
83. Nugroho, A., Siagian, H., Oktavio, A., & Tarigan, Z. (2023). The effect of e-WOM on customer satisfaction through ease of use, perceived usefulness and e-wallet payment. International Journal of Data and Network Science.
84. Nur, T., & Panggabean, R. R. (2021). Factors Influencing the Adoption of Mobile Payment Method among Generation Z: the Extended UTAUT Approach. Journal of Accounting Research, Organization and Economics, 4(1), 14–28.
85. Nurcahyo, R., Prabuwono, A.S., Fainusa, A.F., Wibowo, N., Habiburrahman, M., & Hindriyandhito, K. (2023). Enhancing User Satisfaction in Indonesia’s e-wallet Market: A Comprehensive Analysis of Factors and Priorities. Human Behavior and Emerging Technologies.
86. Nyaupane, G.P., Paris, C.M., & Li, X.(. (2020). Introduction: Special Issue on Domestic Tourism in Asia. Tourism Review International.
87. Ojo, A., Fawehinmi, O., Ojo, O., Arasanmi, C., & Tan, C. (2022). Consumer usage intention of electronic wallets during the COVID-19 pandemic in Malaysia. Cogent Business & Management, 9.
88. Olejnik, S. (1984). Planning Educational Research: Determining the Necessary Sample Size.. Journal of Experimental Education, 53, 40-48.
89. Psychological Association (7th ed.). American Psychological Association.
90. Puspitasari, I., Wiambodo, A.N., & Soeparman, P. (2021). The impact of expectation confirmation, technology compatibility, and customer’s acceptance on e-wallet continuance intention.
91. Uwamariya, M., Cremer, S., & Loebbecke, C. (2021). Mobile Payment Enhancing Tourism in Emerging Markets: A Qualitative Study among Small and Medium-Sized Enterprises (SMEs) in Rwanda’s Tourism Sector. Journal of African Business, 23, 480 – 496.
92. Rabbani, M., Wijaya, J., Kusuma, R., Purba, W., & Tajib, R. (2023). Digital Payments in Indonesia: Understanding the Effect of Application Security on User Trust. Indonesian Journal of Computer Science.
93. Rahadi, R.A., Nainggolan, Y.A., Afgani, K.F., Yusliza, M.Y., Faezah, J.N., Ramayah, T., Saputra, J., Muhammad, Z., Farooq, K., & Angelina, C. (2022). Towards a cashless society: Use of electronic payment devices among generation Z. International Journal of Data and Network Science.
94. Rahmadhani, S., Buchdadi, A., Fawaiq, M., & Prasetya, B. (2022). Determinants of intention to use e-wallet in Generation Z. BISMA (Bisnis dan Manajemen).
95. Rosli, M., Saleh, N., Ali, A., & Bakar, S. (2023). Factors Determining the Acceptance of E-Wallet among Gen Z from the Lens of the Extended Technology Acceptance Model. Sustainability. SAGE Publications.
96. Saputra, I., Yusuf, A., Hakim, L., & Rohayati, S. (2023). Determination Of Generation Z’s Intention In Using E-Wallet For Payment Transactions. E-Journal Akuntansi. scale in forensic psychiatric setting in Indonesia. Heliyon, 8(7).
97. Selvanathan, M., Tan, P.J., Bow, T.F., & Supramaniam, M. (2016). The Impact of Cost, Customer Experience, Ease of Use, and Trust towards Adoption of Online Banking. International Business Research, 9, 235-241.
98. Senali, M.G., Iranmanesh, M., Ismail, F.N., Rahim, N.F., Khoshkam, M., & Mirzaei, M.S. (2022). Determinants of Intention to Use e-Wallet: Personal Innovativeness and Propensity to Trust as Moderators. International Journal of Human–Computer Interaction, 39, 2361 – 2373.
99. Setiawan, B.I., Trisdyani, N.L., Adnyana, P.P., Adnyana, I.N., Wiweka, K., & Wulandani, H. (2018). The Profile and Behaviour of ‘Digital Tourists’ When Making Decisions Concerning Travelling Case Study: Generation Z in South Jakarta. Advances in Research.
100. Shanmugam, K., Rana, M.E., & Kong, Z.Y. (2024). A Comprehensive Analysis of Technological Advancements and Smart Tourism Strategies in Malaysia’s Post-Pandemic Tourism Industry. 2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS), 909-916.
101. Shen, S., Yang, F., & Sotiriadis, M. (2023). Experiential consumption dimensions and pro- environment behaviour by Gen Z in nature-based tourism: a Chinese perspective. Tourism Review.
102. Statista [Amanda Siddharta]. (2024, June 25). Recent e-wallets usage in Malaysia 2023, by brand. Statista. https://www.statista.com/statistics/1460205/malaysia-recent-e-wallets-used-by- brand/#:~:text=According%20to%20a%20survey%20in,used%20the%20e%2Dwallet%20rec ently.
103. Statistics, M. T. (n.d.). Malaysia Tourism Statistics. https://data.tourism.gov.my/
104. Syifa, N., & Tohang, V. (2020). The Use Of E-Wallet System. 2020 International Conference on Information Management and Technology (ICIMTech), 342-347.
105. Taber, K. S. (2017, June 7). The Use of Cronbach’s Alpha When Developing and Reporting Research Instruments in Science Education. Res Sci Educ. 10.1007/s11165-016-9602-2.
106. TING, L. S. T. (2024). Factors Influencing The Adoption of Touching Go (Tng) Ewallet Among Consumers In Malaysia. In Faculty of Accountancy and Management Department Of International Business.
107. Truman, E., & Elliott, C. (2019). Identifying food marketing to teenagers: a scoping review. The International Journal of Behavioral Nutrition and Physical Activity, 16.
108. Venkatesh, V., & Davis, F. (2000). A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies. Management Science, 46, 186-204.
109. Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157–178.
110. WAHAB, F. (2024, November 21). “Snowfall” lifts festive spirits at popular KL mall. The Star. https://www.thestar.com.my/metro/metro-news/2024/11/21/festive-spirits-lifted-as- 039snow039-falls-in-popular-kl-mall
111. Wardana, A., Saputro, E., Wahyuddin, M., & Abas, N. (2022). The Effect of Convenience, Perceived Ease of Use, and Perceived Usefulness on Intention to Use E-Wallet. Proceedings of the International Conference on Economics and Business Studies (ICOEBS 2022).
112. Wardana, A., Saputro, E., Wahyuddin, M., & Abas, N. (2022). The Effect of Convenience, Perceived Ease of Use, and Perceived Usefulness on Intention to Use E-Wallet. Proceedings of the International Conference on Economics and Business Studies (ICOEBS 2022).
113. Widodo, M., Irawan, M., & Sukmono, R. (2019). Extending UTAUT2 to Explore Digital Wallet Adoption in Indonesia. 2019 International Conference on Information and Communications Technology (ICOIACT), 878-883.
114. Yang, M., Mamun, A., Mohiuddin, M., Nawi, N., & Zainol, N. (2021). Cashless Transactions: A Study on Intention and Adoption of e-Wallets. Sustainability, 13, 831.
115. Ying, W. C., & Mohamed, M. I. K. P. (2020). Understanding the factors influences users continuous intention towards E-Wallet in Malaysia: Identifying the gap. Research in Management of Technology and Business, 1(1), 312–325.