INTRODUCTION
Background and Motivation
In recent years, the rapid advancement of the Internet and Information Technologies (IT) has transformed computers and mobile phones from luxuries into essential tools accessible to most people As a result of significant market demand and economic advantages, IT companies are actively competing to introduce a diverse range of innovative products and services.
The rapid evolution of IT products has provided customers with numerous opportunities to switch between alternatives, significantly impacting market dynamics Various studies have examined switching behaviors across different categories, including web browsers like Internet Explorer and Chrome, office software such as Microsoft Office and WPS, and social networking platforms like MySpace and Facebook, as well as IT services like broadband Internet access (Bhattacherjee et al., 2012) This switching behavior poses a considerable challenge to companies, as it can jeopardize long-term customer relationships, highlighting the importance of relationship marketing strategies (Ganesh et al.).
The phenomenon of IT switching presents both challenges and opportunities for IT providers, as exemplified by Kaixin.com, which has lost its market share to competitors like Weibo This significant impact of IT switching behaviors has garnered increasing attention from information systems scholars Previous research has explored user switching behaviors in various IT products, including blogs, social networking sites, and online marketplaces (Chang et al., 2014; Lin et al., 2012; Zhang, Cheung et al., 2008).
The rapid growth of Fintech services and IT systems has led to the emergence of numerous convenient payment solutions, particularly in mobile payments, which offer significant advantages recognized by both academics and industry professionals Mobile payment innovations have expanded beyond electronic transactions to include various payment types, such as commuter trains, flight tickets, hotel accommodations, and restaurant services As noted by Dahlberg and Oorni, commercial institutions, merchants, and financial organizations are striving to deliver more efficient and user-friendly payment methods.
Consumers benefit from a variety of smartphone features, including services and applications that enhance daily activities As a result, mobile services have become integral to everyday life, with mobile payments emerging as a valuable tool Defined as the use of a mobile device to initiate, authorize, and confirm financial transactions for goods and services, mobile payments are gaining traction due to the rapid expansion of the mobile phone industry These payment systems offer greater efficiency and convenience for users, allowing customers to conduct financial transactions swiftly and comfortably, regardless of the payment amount.
The rise of mobile devices has revolutionized payment transactions, allowing customers to conduct them anytime and anywhere without the need for multiple cards or cash This exponential growth in mobile payment tools is driven by the increasing demand for mobility in financial transactions The primary motivation for customers to embrace these technologies is the convenience they offer when integrated with smartphones.
Recent surveys indicate a growing trend in mobile payments, reflecting increased awareness and interest among smartphone users (Tavilla, 2012) A statistical report reveals a significant rise in the number of mobile payment users.
2009 to 2016 In particular, Asia/Pacific dominated the number of mobile payment users in all years and reached 163.3 million users in 2016
According to a report from The Statistics Portal, global smartphone subscriptions reached 2.32 billion in 2017, with projections estimating that this number will rise to 2.87 billion by 2020 In Vietnam, the number of smartphone users is expected to reach 42.66 million by 2022.
The Statistics Portal (2018) [Figure 1-2] Number of Smartphone Users Worldwide from 2014 to 2020 (in billions)
The rapid expansion of the mobile phone industry in Vietnam has spurred the development of mobile payment systems; however, cash remains the dominant payment method, with 90% of transactions conducted in cash Additionally, Cash on Delivery (COD) is the most widely accepted payment option in e-commerce, accounting for 90% of transactions, according to data from the Global Findex database and the Gallup World Poll (2017).
While numerous studies have explored the factors influencing the adoption of mobile payment systems, there is a notable lack of research examining the effects of transitioning from traditional payment methods to mobile payments In Vietnam, where cash remains the dominant payment method, this gap presents an opportunity for further investigation Consequently, this study aims to identify the factors that affect individuals' intentions to switch from cash payments to mobile payment solutions.
Research Objectives and Questions
This thesis aims to explore the factors that drive the transition from cash payments to mobile payments in Vietnam, while also examining how gender, age, income, and career influence this switching process The study will address key research questions related to these dynamics.
• What are the main factors affect switching intention from cash payment to mobile payment in Vietnam?
• What factors moderate the user’s intention to switch from cash payment to mobile payment in Vietnam?
This study develops a research model that integrates the push-pull-mooring (PPM) framework by Bansal et al (2005) with the technology acceptance model (TAM) proposed by Davis et al (1989) The PPM framework is utilized to analyze consumer switching behavior, while the TAM is widely favored for explaining information technology acceptance and adoption.
Relevance Significance
Technological advancements have revolutionized the payments industry, providing customers with faster, safer, and more convenient mobile payment options compared to traditional cash methods The rise of mobile payments, characterized by their flexibility in time and location, is becoming a significant trend (Carlsson et al., 2006; Jarvenpaa and Lang, 2005) This payment method not only reduces transaction costs but also promotes non-cash financial transactions while minimizing personal and financial risks (Nickerson, 2013) The Vietnamese government aims to enhance non-cash payment systems by 2020, with mobile payments playing a vital role Despite this progress, cash remains the most widely used payment method in Vietnam, according to The Global Findex Database 2017.
Research on mobile payment adoption in Vietnam has primarily focused on identifying factors influencing its acceptance, with limited studies examining the transition from traditional cash payments to mobile payment methods This gap underscores the need to investigate the factors driving the intention to switch from cash to mobile payment To address this, the study utilizes the Technology Acceptance Model (TAM) by Davis (1989) and the Push–Pull–Mooring (PPM) framework by Bansal et al (2005) Understanding these factors is essential for informing effective marketing and management strategies that can enhance consumer acceptance of mobile payment in Vietnam, benefiting both the government and businesses.
Structure of Study
The remain chapters are organized as follow:
Chapter One outlines the research background, beginning with the motivation and context that inspired the study It then reviews the research objectives and questions, highlighting their importance Additionally, the significance of the research is discussed, culminating in an overview of the study's structure.
Chapter Two provides a literature review that explores the global and Vietnamese landscape of mobile payment, highlighting its current developments It discusses key concepts and theories related to user IT/IS switching behavior to enhance understanding of switching intentions Additionally, the chapter introduces the original and modified Technology Acceptance Model (TAM) alongside the push-pull-mooring framework It also summarizes the main factors identified in previous studies on mobile payment.
Chapter Three introduces a foundational conceptual model for empirical testing, drawing on insights from switching literature and prior research on mobile payment adoption It culminates in the formulation of hypotheses derived from these discussions.
Chapter Four presents the construction of the questionnaire as well as the data collection procedure
Chapter Five presents the analysis of data and study results using SPSS 23 and AMOS 23 It details the findings derived from path analysis methods, encompassing descriptive statistics, reliability analysis, exploratory factor analysis (EFA), and structural model analysis.
Chapter Six contributes discussions and explanations of the results related to each hypothesis considering both conceptual and practical views in Vietnam.
LITERATURE REVIEW
An Overview of Mobile Payment
Mobile payment refers to financial transactions conducted via mobile devices, such as smartphones, mobile phones, or tablet PCs, to pay for products and services According to Au and Kauffman (2008), it involves initiating, authorizing, and confirming payment transactions through a mobile device Similarly, Karnouskos (2004) defines it as any payment utilizing mobile technology to activate or confirm payments for goods, services, and bills Mobile payments are applicable in both online m-commerce and e-commerce, as well as offline transactions at cash desks.
This study follows both the definitions that were given by Au and Kauffman
Mobile payment refers to any transaction where a mobile device is utilized to initiate, authorize, and confirm the exchange of financial value for goods and services This method of payment can be employed in both online and offline settings.
According to the Federal Reserve Bank of Boston, mobile payment includes two kinds: remote payment and proximity payment (Becker, 2007)
Remote mobile payment relies on telecommunication networks like GSM or the Internet to connect consumers to payment servers, enabling independent transaction processing (Zhou, 2012, p.1086) Despite its convenience, this payment method has significant drawbacks, as the absence of a signature or PIN can lead to fraudulent transactions when credit cards or mobile phones are stolen (Bingel and Massoth, 2009, p.2).
Proximity mobile payment allows consumers to make payments using their mobile devices at designated locations equipped with advanced technologies (Zhou, 2012, p.1086) This process involves the transmission of payment data from the mobile device to the merchant's Point of Sale (POS) system through various communication methods, including Quick Response (QR) codes, Near Field Communication (NFC), and Magnetic Secure Transmission.
(MST), Code, Bluetooth, Bluetooth Low Energy (BLE) (Anisa report, 2016)
• QR-Codes Payment: QR Codes are square barcodes QR, or “Quick Response” barcodes were designed to contain the meaningful information right in the barcode
NFC payment, or Near Field Communication payment, is a type of proximity mobile payment that allows customers to make contactless transactions at the point of sale (POS) using NFC-enabled devices This technology is compatible with both Android and iOS platforms, including popular services like Google Wallet, Samsung Pay, and Apple Pay, enabling seamless purchases through a contactless financial payment infrastructure.
Magnetic Secure Transmission (MST) is a proximity mobile payment technology that emulates a magnetic card strip, allowing users to make payments at nearly all card reader terminals Exclusively offered by Samsung through Samsung Pay, MST provides a convenient and widely accepted payment solution.
Proximity mobile payments are utilized in both face-to-face transactions between consumers and merchants, as well as in unattended point-of-sale locations From the consumer's perspective, these payments are deemed safer, as they provide the same level of security as credit or debit card transactions without the need to hand over the card to the merchant Additionally, the entire proximity mobile payment process occurs in the customer's presence, enhancing transparency and trust.
2.1.2 Advantages and Disadvantages of Mobile Payment
Mobile payment offers distinct advantages over both offline and online payment methods As noted by Zhou (2011), one key benefit is the ability for users to make payments easily and quickly through mobile devices, providing unparalleled mobility Additionally, research by Teo et al (2015) and Ding and Unnithan highlights the significant advantages of mobile payment, including enhanced speed and convenience, making it an increasingly popular choice for consumers.
Mobile payment services have revolutionized the way consumers transfer money, enabling transactions without the need for a bank, which saves time and reduces costs while minimizing personal risk (Nickerson, 2013) By integrating traditional payment methods with mobile technology, customers can conveniently eliminate the use of cash (Pham and Ho).
Mobile payment systems have transformed the way consumers conduct transactions by turning mobile phones into electronic wallets, eliminating the need for physical cards and reducing the risks associated with using plastic This innovative payment method is particularly advantageous in high-transaction environments such as restaurants and large retailers, making it suitable for both individual and bulk payments.
Despite the numerous advantages of mobile payment systems, their adoption remains relatively low, primarily due to concerns over personal and sensitive financial information security (Duane et al., 2014).
Insecurity and account risks in mobile payments often stem from poor mobile network quality, inadequate user support, and a lack of service awareness (Anthony and Mutalemwa, 2014; Chogo and Sedoyeka, 2014; Intermedia, 2011) Additional challenges include insufficient e-float or cash for transactions (Intermedia, 2013), high transaction costs, and a lack of procedural training (Chogo and Sedoyeka, 2014) Moreover, the usability of mobile devices—characterized by small screens, limited visual keyboards, and unfriendly interface designs—further hinders the adoption of mobile payment solutions (Ondrus and Pigneur, 2006c; Chogo and Sedoyeka, 2014).
Global Growth of Mobile Payments
The rapid global expansion of mobile payments is transforming how people engage in banking, trading, money transfers, and commerce directly from their smartphones According to a GSMA report, the number of users adopting mobile payment solutions is on the rise, reflecting a significant shift in consumer behavior towards digital financial transactions.
In 2017, the mobile money industry processed an impressive $1 billion daily, generating over $2.4 billion in direct revenues The global mobile payment market reached a total revenue of $780 billion that year, with projections indicating it would grow to $1.08 trillion by 2019.
The Statistics Portal (2018) [Figure 2-1] Total Revenue of Global Mobile Payment Market from 2015 to 2019
In 2017, the global number of registered mobile payment customers surged to 690 million mobile money accounts, marking an impressive increase of over 136 million new accounts and a 25 percent growth compared to 2016.
The growth of mobile payments varies significantly across different continents and countries, with China and the United States leading in user penetration rates According to a 2017 whitepaper report, the United States was projected to surpass China in 2019, achieving a user penetration rate of 28% Additionally, mobile money services have seen rapid expansion in regions such as Africa, Asia, and Latin America.
Mobile Payment in Vietnam
2.3.1 Current Status of Payment in Vietnam
Despite being one of the fastest-growing e-commerce markets in the region, Vietnam's online payment adoption remains low A 2017 World Bank report indicated that non-cash transactions in Vietnam accounted for only 5%, significantly trailing behind China (26.1%), Thailand (59.7%), and Malaysia (89%) The prevalence of cash payments continues to dominate consumer behavior in Vietnam.
In 2016, a significant 89% of respondents favored cash-on-delivery as their preferred payment method for online shopping, while 41% opted for Internet banking, and 23% used card payments.
Vietnam E-Commerce Report 2016 [Figure 2-2] Most Popular Payment Methods for Online Shopping
Vietnam Bank Card Association reported that, in 2017, a vast majority of ATM transaction was still cash withdrawals, with 86,81% of total domestic’s card transaction value
[Figure 2-3] Transaction through ATM/POS by Value
In 2016, smartphone ownership reached 72% in urban areas of Vietnam, while rural areas saw a lower rate of 53% Additionally, the same year, 49% of the Vietnamese population was reported to be using the Internet, as indicated by Appota Corporation.
The Vietnamese government aims to decrease cash transactions to below 10% of total market transactions by 2020, leveraging the country's young population and their rapid technological adaptation With over half of the population owning smartphones, Vietnam is well-positioned to transition from cash payments to mobile payment solutions, highlighting the significant potential for growth in this sector.
In 2017, Vietnam experienced a significant surge in mobile payment transactions, with nearly 110 million transactions recorded and an 81% increase in transaction value compared to the previous year The State Bank of Vietnam reported that during the first nine months of 2017, mobile phone transactions exceeded 90 million, with transaction values surpassing 423 trillion VND, marking achievements of 93% and 139% respectively.
In Vietnam, mobile payments have seen significant growth, with increases of 153% in 2015 and 316% in 2016 Currently, these payments are facilitated through both Remote and Proximity methods, utilizing QR codes and Point-of-Sale systems powered by Magnetic Secure Transmission (MST) technology, particularly through Samsung Pay.
In 2017, major Vietnamese banks, including Vietcombank, VietinBank, BIDV, and Agribank, along with 25 non-bank financial institutions like Moca and MoMo, adopted QR code payment solutions within their mobile banking applications Today, QR payment has emerged as the leading mobile payment service in Vietnam, offering significant advantages to both businesses and consumers.
In Vietnam, QR payment services are predominantly offered by leading financial companies such as VNpay, Momo, and Ononpay A report from VNpay indicates that by the end of 2017, the QR Pay payment gateway had facilitated 23,000 customer scans, with 8,000 payment points accepting this method Projections suggest that this number will rise to 15,000 by 2020, highlighting the growing adoption of QR payment solutions in the country.
Launched in September 2017, Samsung Pay is a mobile payment application for Samsung smartphones that has partnered with 15 banks and 3 card organizations Utilizing Magnetic Secure Transmission (MST) technology acquired from LoopPay, Samsung Pay supports both NFC and MST payments, allowing it to be accepted in a wide range of stores without the need for additional hardware This competitive edge positions Samsung Pay favorably against Apple Pay and Android Pay, particularly in Vietnam, where 98% of card terminals utilize magnetic MST technology.
User IT/IS Switching Behavior
Migration was defined as the movement of migrants from one geographic location to another for a certain period of time (Clark, 1986; Boyle and Halfacree,
Service switching involves the process of customers replacing their current service provider with another option available in the market This concept has been explored in various studies, highlighting its significance in understanding consumer behavior and market dynamics.
Customer switching is a key concept in relationship marketing, as highlighted by Keaveney (1995), who employed a critical incidents method to explore the reasons behind customers' decisions to switch service providers His study identifies the various factors influencing this switching behavior, providing valuable insights into customer service dynamics.
In their 1995 study, Bansal and Taylor (1999, p 202) developed a model to explain service provider switching by integrating the theory of planned behavior with additional factors Their research indicates that customers are likely to switch providers when their expectations are not met, highlighting that the decision to switch services is a multifaceted behavioral process.
Bansal et al (2005) utilized Lee’s migration theory (1996) to analyze brand and service switching in marketing With the rapid advancement of Internet technologies, consumers now have access to innovative IT products, such as computers and mobile phones, which have become essential due to their numerous features In the competitive landscape of technology, IT companies are consistently enhancing and innovating their offerings to introduce new products that provide greater convenience.
IT user switching shares similarities with physical migration between service providers, yet it has unique characteristics Due to rapid IT innovations, users now have a wide array of options with evolving functionalities, making it easy to switch between products or services With just a single click to download and install, users can effortlessly explore new IT choices from competing providers (Bhattacherjee et al., 2012).
Discontinuing the use of previous IT products or services is not necessary, as users can simultaneously utilize both old and new technologies for a transitional period This allows for effective evaluation of the new IT solutions while still relying on the familiar systems (Keaveney and Parthasarathy, 2001; Xu, Li, and Heikkila, 2013).
This research examines IT switching behavior, focusing on users' decisions or intentions to fully or partially transition from cash payments to mobile payments, along with the factors influencing this shift.
Theoretical Background for the Study
In the realm of IT and IS, the adoption of innovations is often analyzed through various models, with the Technology Acceptance Model (TAM), introduced by Davis in 1989, being the most prominent TAM significantly influences our understanding of technology acceptance and adoption behaviors (Lippert, 2007; Gefen and Karahanna, 2003b) Adapted from the Theory of Reasoned Action (TRA), TAM posits that consumer behavior is directly shaped by users' intentions to accept technological innovations (Davis, 1989).
The Technology Acceptance Model (TAM) is a valuable framework for predicting consumer behavior, as highlighted by Wang et al (2011) Its strengths include reliable instruments, excellent measurement properties, and empirical validity (Pavlou, 2003) Additionally, TAM effectively accounts for a significant portion of the variance in usage intentions, making it a powerful tool in understanding technology adoption (Venkatesh, 1999).
The Technology Acceptance Model (TAM) has been effectively utilized in numerous IT studies, accounting for 40 to 50 percent of technology acceptance research (Park, 2009) This includes significant research areas such as wireless LAN usage (Yoon and Kim, 2007), the adoption of internet banking (Gu and Lee, 2009), and attitudes towards self-service solutions (Dabholkar and Bagozzi).
The Technology Acceptance Model (TAM) has been widely utilized in the Internet system sector to explain and predict user acceptance of new information systems across various organizational contexts Key studies, including those by Davis and colleagues (1989) and Venkatesh (2000), demonstrate TAM's relevance in diverse fields such as information systems, marketing, and electronic commerce Central to the TAM model are two critical factors: perceived ease of use and perceived usefulness, which significantly influence users' behavioral intentions.
[Figure 2-4] Technology Acceptance Model (TAM) Davis (1989)
Perceived ease of use refers to the extent to which individuals believe that utilizing a specific system requires minimal effort (Davis, 1989) This concept plays a crucial role in shaping users' perceptions about the effort needed for the ongoing use of innovative technology Despite the challenges in objectively measuring and quantifying this factor due to its highly subjective nature, it remains a key determinant in the successful application of technology (Davis, 1989, p.320).
Perceived usefulness (PU) is defined as the extent to which an individual believes that utilizing a specific system will improve their job performance (Davis, 1989) In the realm of new technology adoption, implementing incentives such as bonuses and rewards can bolster this belief Davis et al (1989) assert that perceived usefulness is influenced by perceived ease of use, indicating that, all else being equal, a technology's ease of use enhances its perceived usefulness Furthermore, an individual's intention to use the new technology serves as a measure of their capability to adopt it, while actual system usage is ultimately determined by this behavioral intention (Venkatesh and others).
To achieve optimal outcomes, it is essential to consider external variables influenced by target technology, consumer behavior, and contextual factors (Moon and Kim, 2001; Kim et al., 2009; Van der Heijden, 2004; Venkatesh and Davis, 1996; Wang et al., 2003) The Technology Acceptance Model (TAM) has been utilized in various studies to forecast user acceptance, particularly in the realm of mobile payments (June et al., 2005; Zhou).
Numerous studies highlight the significance of perceived usefulness and perceived ease of use in the acceptance of mobile payments (Mallat, 2007; Chen, 2008) The Technology Acceptance Model (TAM) has been utilized to analyze behavioral intentions, particularly in the context of transitioning from offline to online banking (Lee et al., 2011) While TAM serves as a valuable framework for examining technological acceptance, it overlooks the influence of social factors (Venkatesh and Morris, 2000) and fails to adequately account for the variety of environmental factors and constraints that affect user behavior (Fu et al.).
In the context of mobile payments, users operate their devices in public settings where they can see and be influenced by the actions and reactions of others (Nysveen et al., 2005) Therefore, the existing model requires adjustments and extensions to comprehensively explain user intentions regarding the adoption of new technology Taylor and Todd (1995) suggest that the Technology Acceptance Model (TAM) should incorporate social, human, and additional factors to enhance its effectiveness.
The Technology Acceptance Model (TAM) has been widely utilized to understand technology acceptance across various research studies (Davis, 1989; Davis et al., 1989; Moore and Benbasat, 1991; Mathieson, 1991; Taylor and Todd, 1995; Venkatesh, 2000) and to predict user acceptance of new information systems in diverse organizational settings (Adams and Nelson, 1992; Chin and Todd, 1995; Doll and Hendrickson, 1998) Additionally, TAM has been effectively applied in fields such as information systems, marketing, electronic commerce, and user switching behavior (Chau and Lai, 2003; Chen et al., 2002; O'Cass and Fenech).
To achieve optimal results, it is essential to consider external variables influenced by target technology, consumer behavior, and contextual factors (Moon & Kim, 2001; Kim et al., 2009; Van der Heijden, 2004; Venkatesh & Davis, 1996; Wang et al., 2003) In the context of switching, the Technology Acceptance Model (TAM) has been adapted by Lee (2011), which will be further elaborated in Section Three.
2.5.2 The Push-Pull-Mooring (PPM) Framework
The Push–Pull–Mooring (PPM) framework, rooted in Ravenstein's "Law of Migration" (1885), explores human migration through the interplay of push and pull factors (Lee, 1966) This paradigm, identified by Jackson (1986) as pivotal for migration studies, categorizes push factors—such as lack of job opportunities, unemployment, resource depletion, air pollution, adverse climate, and natural disasters—as negative influences driving people away from their homes (Lewis, 1982; Bogue, 1969) Conversely, pull factors are the attractive elements of a new destination, including better job prospects, higher incomes, favorable climate, and quality education, which entice individuals to relocate (Lewis, 1982; Bogue).
The push-pull model fails to fully capture the complexities of migration, as it overlooks the significant impact of normative and psychosocial variables on migration decision-making (Germani, 1965) Individual migration choices are intricately linked to personal traits and social contexts (Lee, 1966; Longino, 1992; Moon, 1995) Longino (1992) introduced the concept of "mooring," which encompasses lifestyle, cultural, and spatial factors that can either hinder or promote migration decisions Moon (1995) further developed the push-pull model by integrating mooring effects, resulting in the enhanced PPM model.
Bansal et al (2005) highlighted the versatility of the PPM model, demonstrating its applicability in predicting not only national migration behaviors but also individual service provider switching behaviors The model's relevance in marketing stems from its parallels with geographical migration concepts, as both involve the movement of individuals According to Boyle et al., "migration" is defined as "the movement of a person (a migrant) between two places for a certain period of time," emphasizing the fluidity of consumer choices in various contexts.
1998), can be used to describe the behavior of consumers switching between from a physical retail channel to another mobile retail channel
The Pull-Push-Mooring (PPM) factors significantly influence customer switching intentions; however, the underlying latent variables can vary across different service industries To enhance contextual relevance and performance, it is crucial to adapt the PPM model for various fields (Bansal et al., 2005; Lui, 2005; Ye and Potter, 2007; Zhang et al., 2008; Cheng et al., 2009; Chiu et al., 2011; Hou et al., 2009, 2011) Individual perceptions, beliefs, and variations affect switching behaviors differently across services, including banking (Ganesh et al., 2000), Internet service providers (Keaveney and Parthasarathy, 2001), credit cards (Burnham et al., 2003), and mobile phones (Kim et al., 2004).
Empirical Studies on Mobile Payment
Mobile payment is a relatively new research area compared to e-commerce, internet banking, and mobile banking Various studies have examined the factors influencing user adoption of mobile payment, enhancing our understanding of its acceptance among both merchants and users The predominant theoretical frameworks utilized in this research include the Technology Acceptance Model (Davis, 1989), the Theory of Planned Behavior (Taylor and Todd, 1995), Innovation Diffusion Theory (Rogers, 1995), and the Unified Theory of Acceptance and Use of Technology (Venkatesh et al., 2012).
The complexity of mobile payment systems necessitates the adaptation of research constructs to include various factors These factors encompass mobility, convenience, compatibility, and mobile payment knowledge, alongside trust, perceived risk, and social influence Additionally, considerations such as privacy, personal innovativeness, relative advantage, perceived cost, and reputation play a crucial role Performance and effort expectations, subjective norms, perceived security, personal habits, and the attractiveness of alternatives are also significant in understanding mobile payment adoption (Kim, 2009; Schierz).
(2010), Lu (2011), Yang (2012), Tan (2014), Cabanillas (2014), Pham (2015), Daştan (2016), Ting (2016), Liu (2016), Oliveira (2016), Ooi (2016), Lwoga
Schierz's 2010 study highlights that consumer acceptance of mobile payment services is influenced by several key factors, including perceived compatibility, perceived security, perceived usefulness, perceived ease of use, individual mobility, and subjective norms These elements significantly shape users' attitudes toward mobile payment usage, ultimately impacting their intention to adopt these services.
Chandra (2010) highlighted that consumer trust in mobile payment systems can be influenced by the characteristics of mobile service providers and mobile technology This, in turn, impacts the perceived ease of use, perceived usefulness, and consumers' intention to adopt these payment systems.
According to Kim et al (2009), individual differences such as innovativeness and mobile payment knowledge, along with system characteristics like mobility, reachability, compatibility, and convenience, play a crucial role in influencing the intention to use mobile payment systems The study highlights that these factors impact users' perceptions of usefulness and ease of use, ultimately affecting their willingness to adopt mobile payment technologies.
Lu et al (2011) applied the IDT model to identify factors influencing the intention to use mobile payment, revealing that perceived costs and risks negatively impact this intention, while positive factors like relative advantage, compatibility, and image enhance it Additionally, the inclusion of initial consumer trust in the model provided empirical evidence for the trust transfer process from the Internet to mobile environments Various models have been developed to explore key factors affecting mobile payment adoption in public transport, including the study of mobile ticket usage across the Boston rail network (Brakewood et al., 2014).
Di Pietro et al (2015), Fontesa et al (2017)
Ricardo (2016) applied the UTAUT model to analyze how five factors—performance expectation, effort expectation, social influence, perceived risk, and perceived cost—impact behavioral intention towards mobile payment services The findings revealed that performance expectation significantly influences the intention to use mobile payments, while perceived cost and perceived risk do not positively affect this intention A summary of these factors affecting mobile payment acceptance is presented in [Table 2-4].
[Table 2-2] Factors Affecting Mobile Payment Proposed by Relevant Studies
A review of previous mobile payment research indicates that the Technology Acceptance Model (TAM) has been employed to understand the acceptance of new technology by incorporating variables that influence mobile payment systems While most consumer studies concentrate on factors affecting users' intentions to accept, adopt, and utilize mobile payments, there is a scarcity of research examining the transition from traditional payment methods to mobile payments This study aims to address this gap by investigating the factors influencing the intention to switch from cash payments to mobile payments in Vietnam.
RESEARCHER MODEL AND HYPOTHESIS
Research Model
The rapid advancement in technology offers users a vast array of IT product and service innovations, particularly in the financial sector where consumers now have multiple payment options such as cash, credit cards, debit cards, and mobile payments As new payment methods are introduced, they must achieve market acceptance to replace existing options With the rise of the Internet and smartphones, users can easily compare and experience these new payment methods through online reviews The emergence of mobile payments, which provide significant advantages like mobility, highlights the importance of researching users' intentions to switch from traditional payment methods Lee et al (2011) employed the Technology Acceptance Model (TAM) to analyze factors influencing the transition from offline to online banking While the TAM has been widely acknowledged for explaining intentions to use Internet banking, Lee et al (2011) contend that user acceptance in the virtual market cannot be fully captured by traditional behavioral intention constructs, as increased acceptance of online banking often leads to a decline in offline banking usage.
Lee et al (2011) highlight that in technology acceptance, "usage" and "switching" represent distinct concepts Usage pertains to the application of technology for specific tasks, as noted by Autzen (2007), while switching reflects the inclination to transition from one method to another Furthermore, Lee et al adapted the "intention to use" component within the Technology Acceptance Model (TAM).
‘‘intention to switch” to facilitate measuring the switching behavior, the precursor of usage behavior
[Figure 3-1] The Modified Technology Acceptance Model (TAM) model (Lee,
This study adapts the intention to switch concept from Lee et al (2011), which examines behavioral intentions to transition to online banking, incorporating it into the Technology Acceptance Model (TAM) to develop a comprehensive research model Additionally, the Push-Pull-Mooring (PPM) framework, a well-established model for understanding IT switching, is integrated into this analysis The combined use of the TAM model and the PPM framework aims to identify the key factors influencing the shift from cash payments to mobile payments in Vietnam.
Hypothesis
Push factors negatively impact the quality of life in a given location, motivating individuals to leave their origin (Lee, 1966; Moon, 1995; Bansal et al., 2005) In the context of service literature, these factors, derived from migration theory, encompass negative perceptions of service providers, including poor employee performance, service failures, and issues related to perceived quality, commitment, and pricing, which ultimately lead to low customer satisfaction and trust (Bansal et al., 2005; Jung et al., 2017) Consequently, push factors contribute to customers' decisions to abandon their current service providers This study highlights the push factors associated with cash payments, such as low satisfaction and inconvenience.
3.2.1.1 Low Satisfaction at Cash Payment
Customer satisfaction plays a crucial role in marketing, particularly in the context of consumer switching behavior It is defined as the overall psychological state that arises when emotions linked to unmet expectations are combined with a customer's previous feelings about their consumption experience.
In marketing, customer satisfaction significantly influences repurchase intentions, revisit rates, and recommendations, while low satisfaction levels lead to a higher likelihood of switching to alternative products Unsatisfied customers are more likely to abandon a product, as their intention to switch is greater compared to satisfied customers, indicating that a low satisfaction level can severely impact customer loyalty and the continuation of a relationship.
In both offline and online service contexts, customer satisfaction is crucial for understanding whether consumers will switch to alternative service providers or remain with their current choice Research indicates that low satisfaction acts as a push factor, leading customers to seek better options Specifically, when customers experience low satisfaction with cash payments, they perceive both the usefulness and ease of use of mobile payments as inadequate, prompting them to transition to mobile payment solutions.
H1a: Low Satisfaction at cash payment has a positive impact on the Perceived Usefulness
H1b: Low Satisfaction at cash payment has a positive impact on the Perceived Ease of Use
Cash remains one of the oldest payment methods, primarily favored for small transactions under $25, while credit and mobile payments dominate higher-value transactions in the West (Chen et al., 2017; Bagnall et al., 2016) Despite its long-standing use, cash presents inconveniences, such as the necessity of carrying coins and the limitation of spending only what is on hand In contrast, credit cards and mobile payments enhance purchasing power without the risks associated with carrying cash, appealing to those who prefer not to carry large amounts for safety or comfort reasons (Chen et al., 2017) Additionally, credit and mobile payments offer faster transaction speeds, eliminating the need to count cash and wait for change, while mobile payments allow users to transact anytime and anywhere via a wireless network (Au and Kauffman, 2008) The key advantage of mobile payment systems lies in their mobility, enabling seamless transactions without intermediaries (Kleinrock, 1996; Dahlberg, 2003) As the convenience of payment methods declines, so too does their perceived usefulness and ease of use (Keaveney).
(1995) and Lai (2012) found that inconvenience is a negative factor that motivates customers to switch from the incumbent service provider In view of these findings, we hypothesize the following:
H2a: Inconvenience of cash payment has a positive impact on the Perceived Usefulness
H2b: Inconvenience of cash payment has a positive impact on the Perceived Ease of Use
Migration decisions are influenced by factors from both the origin and destination locations Pull factors, defined as the appealing characteristics of a destination, attract potential migrants (Moon, 1995; Bansal et al., 2005) Similarly, in marketing, pull factors represent the advantages of alternatives that encourage consumers to switch from their current choices (Lin and Huang, 2014).
Pull factors are attractive forces that encourage consumers to adopt mobile payment systems Research has identified several key elements that positively influence the acceptance of mobile payments, such as mobility, compatibility, perceived usefulness, and perceived ease of use These factors create an appealing alternative, enhancing the pull forces that motivate consumers to transition to mobile payment solutions In the context of technology switching, the alternative attractiveness of these pull factors is recognized as the most effective driver for encouraging this shift.
Pull effects in migration and marketing refer to the appealing qualities of alternatives that positively impact individuals' intentions to switch This concept has been supported by various studies, highlighting the significance of attractiveness in influencing decision-making processes.
In 2014, alternative attractiveness refers to customer satisfaction with competing service providers they consider switching to, suggesting that users expect the alternative to offer superior products or services compared to their current provider (Park et al., 2010) Users are motivated to switch when they perceive the new provider as better, distinct, or offering fairer prices and greater enjoyment, influenced by their expectations or specific characteristics of the alternative service providers (Hou et al., 2011).
Keaveney (1995) suggested that consumers are likely to switch to a new service provider if they perceive it as superior, more trustworthy, or more appealing, even if the cost is higher This shift in preference can be influenced by positive perceptions of alternatives, which are often communicated through various channels such as advertisements, word of mouth, and media coverage.
In this study, various payment options such as cash, card, and mobile payments are explored, with mobile payment emerging as the most advantageous due to its speed, mobility, availability, and convenience Prominent mobile payment providers like Samsung Pay, VNpay, and Zalopay enhance consumer appeal through valuable promotions and discounts To achieve its electronic payment goals by 2020, the Vietnamese government promotes mobile payment through social media, increasing its attractiveness The rapid growth of smartphones and the availability of free mobile payment apps facilitate consumer adoption This study identifies the attractiveness of alternative mobile payment methods as a pull variable, influencing perceived usefulness and ease of use, while also impacting customers' switching intentions, as supported by existing literature.
H3a: Alternative Attractiveness has a positive impact on the Perceived Usefulness H3b: Alternative Attractiveness has a positive impact on the Perceived Ease of Use
The migration theory incorporates mooring effects, which are defined by Moon (1995) as cultural and spatial factors that contribute to an individual's psychological well-being These mooring effects, including perceived cultural values, significantly influence decisions regarding whether to remain in a current location or relocate to a new one (Bansal et al., 2005; Hou et al.).
Mooring effects encompass both social and personal factors that influence a consumer's decision to remain with their current service provider or to switch to a different one These elements play a crucial role in shaping consumer loyalty and behavior in the marketplace.
2017) In this study, mooring factors are shown through personal innovativeness, mobile payment knowledge, perceived risk, habit, and switching cost
Personal innovativeness toward information technology refers to an individual's willingness to experiment with new systems and technologies (Chang et al., 2005) Research consistently highlights personal innovativeness as a crucial predictor of technology acceptance (Lewis et al., 2003) Those with high levels of personal innovativeness significantly influence their intention to adopt new technology systems, as they are more inclined to discover novel uses and take risks in exploring new technologies (Agarwal and Prasad, 1998) For instance, personal innovativeness has a notable impact on online shopping decisions (Blake et al., 2003; Crespo and del Bosque, 2008).
In the context of switching behaviors, individual differences play a significant role in influencing migration behaviors, as highlighted by Han (2010) In particular, individuals in the IT sector who are inclined to experiment with new products or services tend to exhibit a higher acceptance of innovative technologies A key variable in research on IT usage is personal innovativeness, which significantly impacts how individuals engage with technology.