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DIGITAL WALLET DYNAMICS: UNDERSTANDING THE POTENTIAL
ADOPTION FACTORS OF WORLDCOIN IN THAILAND'S FINTECH SECTOR
ASSOC. PROF. TANPAT KRAIWANIT, PH.D.
PONGSAKORN LIMNA
PEERAPAT WATTANASIN
DOCTOR OF PHILOSOPHY (PH.D.) PROGRAM IN DIGITAL ECONOMY,
FACULTY OF ECONOMICS, RANGSIT UNIVERSITY
ACADEMIC YEAR 2023
A
ACKNOWLEDGEMENT
The authors would like to express our deepest gratitude to all those who contributed to
the completion of this research project. We appreciate the resources and facilities provided by
Rangsit University, which were essential for conducting this research. Our thanks are extended
to all the participants who generously shared their time and insights, thereby significantly
contributing to the success of this study. Financial support for this research was received from
the Research Institute of Rangsit University, under grant number 38/2566. We are grateful for
their assistance in facilitating this project. We also acknowledge the support and constructive
discussions from our colleagues and friends. Lastly, we express our gratitude to our families
for their unwavering support throughout this endeavor. We sincerely thank all individuals and
entities involved for their invaluable contributions to this research endeavor.
Assoc. Prof. Tanpat Kraiwanit, Ph.D.
Pongsakorn Limna
Peerapat Wattanasin
B
ABSTRACT
This research delves into the factors influencing the adoption of digital wallet
technology, focusing specifically on the Worldcoin digital wallets among Thai individuals over
18 years old. Utilizing a convenience sampling method, the study analyzes responses from
1,430 participants, employing binary regression through statistical analysis software to
examine the influence of various factors—demographic, social, motivational, technological,
and economic—on the adoption of Worldcoin. The findings underscore the significance of
gender, age, education level, occupation, monthly income, savings, existing digital wallet
ownership, frequency of use, and social media engagement in shaping an individual’s intention
to adopt Worldcoin. Moreover, it identifies social support, social presence, trust, perceived
risk, service reliability, perceived usefulness, ease of use, time savings, consumption,
discounts, and promotions as significant determinants affecting Worldcoin adoption. The
implications of these findings are significant for stakeholders in the FinTech sector, suggesting
that a deeper understanding of these determinants can guide more effective strategies for
promoting digital wallet adoption. By addressing the specific needs and concerns reflected in
these factors, developers, marketers, policymakers, as well as other stakeholders, can enhance
user engagement, improve service offerings, and ultimately drive wider acceptance and use of
digital wallet technologies.
Keywords: Digital Wallet, Adoption, Worldcoin, Financial Technology (FinTech)
C
LIST OF CONTENTS
Acknowledgement A
Abstract B
List of Contents C
List of Tables E
List of Figures F
Chapter 1 Introduction 1
1.1. Background of the Study 1
1.2. Research Objective 4
1.3. Research Question 4
1.4. Scope of the Study 4
1.5. Conceptual Framework 4
1.6. Significance of the Study 6
Chapter 2 Literature Review 8
2.1. Financial Technology and Digital Wallet 8
2.2. World coin 11
2.3. Demographic Factors 12
2.4. Social Factors 13
2.5. Motivation Factors 15
2.6. Technological Factors 16
2.7. Economic Factors 17
Chapter 3 Methodology 18
3.1. Research Strategy 18
3.2. Sample and Sampling Technique 18
3.3. Research Instrument 19
3.4. Data Collection 20
3.5. Data Analysis 21
D
Chapter 4 Results 28
4.1. General Data Characteristics of the Respondents 28
4.2. The Potential Factors Influencing the Adoption of World coin 30
Chapter 5 Discussions and Conclusions 38
5.1. Discussions 38
5.2. Conclusions 41
5.3. Research Implications 42
5.4. Policy Recommendations 42
5.5. Limitations and Recommendations for Future Studies 43
References 45
Appendix
Appendix A Ethical Clearance Certificate 57
Appendix B Questionnaire 58
Appendix C Publication 61
Researcher Biography 71
E
LIST OF TABLES
Table 4.1. General Data Characteristics of the Respondents 28
Table 4.2. Omnibus Test of the Model's Performance 30
Table 4.3. The Model Summary 31
Table 4.4. Classification Table for Back-Testing 31
Table 4.5. Variables in the Model 32
Table 4.6. Omnibus Test of the Model's Performance 34
Table 4.7. The Model Summary 34
Table 4.8. Classification Table for Back-Testing 35
Table 4.9. Variables in the Model 35
F
LIST OF FIGURES
Figure 1.1. Global Fintech Market 2023-2027 3
Figure 1.2. Conceptual Framework 6
Figure 2.1. Thai FinTech Ecosystem 9
Figure 2.2. Worldcoin’s Logo 11
Figure 3.1. Binary Logistic Regression Analysis Model 23
1
CHAPTER 1
INTRODUCTION
1.1. Background of the Study
The COVID-19 virus outbreak has resulted in a significant economic slowdown due to
restrictions on economic activities, including travel, face-to-face interactions, and the
implementation of measures like lockdowns and work-from-home policies. These
circumstances have forced the world to accelerate its economic revival through digital
technology and various digital innovations. This new economic paradigm is referred to as the
Digital Economy, which promotes efficiency in economic activities by utilizing various digital
technologies. In this digital economy, businesses and economic activities can operate more
efficiently and adapt to contemporary needs by offering services over the internet. For instance,
products and services in the digital economy are often bought and sold online, known as
electronic commerce (e-commerce), enabling people to make purchases from anywhere with
internet access. Furthermore, the Digital Economy necessitates the adoption of financial
innovations, such as digital financial systems, for transactions, transfers, and withdrawals.
Additionally, the Digital Economy has led to changes in consumer behavior, business practices,
and government policies, resulting in transformations in how businesses are conducted and
managed. Companies that employ digital technology in their operations enhance their ability
to meet customer demands, reduce production costs, and open up new revenue opportunities.
This transformation in the digital economy has also had a significant impact on social and
communication sciences, fostering continuous data creation and sharing, allowing nearly
unrestricted access to information and knowledge for everyone (Asanprakit & Kraiwanit, 2023;
Banga & te Velde, 2020; Xu et al., 2022).
Financial Technology, or FinTech, refers to the application of digital systems in various
financial processes to make financial transactions more convenient, efficient, and
systematically organized. In the current landscape of FinTech, it has significantly influenced
consumer behavior as businesses have integrated online payment systems and various FinTech
solutions into the buying and selling of products and services. These systems are accessible
through websites, applications, and various digital devices such as smartphones, computers,
and laptops. Particularly noteworthy is the fact that the COVID-19 pandemic has accelerated
2
Digital Disruption, driving the adoption of a new economic model, the Digital Economy. This
has led to substantial growth in various forms of FinTech during this period (Barroso &
Laborda, 2022; Subramanian, 2022). The ongoing technological innovations in various
dimensions are reshaping society. The interconnectedness of the internet and the prevalence of
smartphones have made advanced technology easily accessible to everyone. Industry 4.0
signifies a major transformation in the global economy and society, driven by technological
advancements that revolutionize both internal and external organizational operations,
enhancing digital interactions (Limna & Kraiwanit, 2022; Mourzis et al., 2022).
In recent years, Thailand has witnessed a remarkable surge in financial technology,
commonly known as FinTech, transforming the traditional landscape of banking and finance.
Spearheaded by government initiatives such as Thailand 4.0, the nation is swiftly embracing
digitalization to propel its economy into the digital age. Supported by the Bank of Thailand's
regulatory sandboxes, innovative FinTech startups are flourishing, catering to the evolving
needs of consumers and businesses alike. With a burgeoning middle class and increasing
smartphone penetration, digital payments and e-wallets have emerged as a cornerstone of
Thailand's FinTech ecosystem. Platforms like PromptPay, TrueMoney, and Rabbit Line Pay
have gained widespread acceptance, facilitated seamless transactions and reduced reliance on
cash. Moreover, Thailand's FinTech scene extends beyond payments, encompassing diverse
sectors such as peer-to-peer (P2P) lending, blockchain technology, insurance technology
(InsurTech), and robo-advisory services. P2P lending platforms are empowering small and
medium-sized enterprises (SMEs) with alternative financing options, fostering economic
growth and financial inclusion. Meanwhile, the adoption of blockchain and cryptocurrency is
gaining momentum, supported by regulatory frameworks governing digital asset businesses. In
the insurance sector, InsurTech startups are leveraging technology to streamline insurance
processes, enhance customer experience, and offer tailored insurance solutions. Additionally,
the rise of robo-advisors is democratizing wealth management, making investment
opportunities more accessible to retail investors through automated advisory services and
personalized investment strategies. As Thailand embraces the digital revolution, its FinTech
landscape continues to evolve, promising further innovation and disruption in the financial
services industry (Bank of Thailand, n.d.; Moenjak et al., 2020; Karim et al., 2022; Kraiwanit,
2022; Kraiwanit et al., 2022; Sosa & Montes, 2022; Zheng, 2022).
3
Technavio (2023) has announced its latest market research report titled "Global Fintech
Market 2023-2027," illustrated in Figure 1.1. The report projects that the global financial
technology (fintech) market will expand by USD 277.22 billion from 2022 to 2027. This
expansion reflects an expected compound annual growth rate of 20.5% during the forecast
period. In 2022, the Asia-Pacific region held the largest share of the global market, and it is
anticipated to experience an incremental growth of 39% over the projection period.
Figure 1.1. Global Fintech Market 2023-2027
Source: https://www.prnewswire.com/news-releases/fintech-market-2023-2027-a-
descriptive-analysis-of-the-five-forces-model-market-dynamics-and-segmentation---
technavio-301723159.html
Simultaneously, the economy is evolving towards new consumer behaviors, a change
catalyzed by the convergence of economic, technological, and sociocultural factors in the era
of the Digital Economy. Digital wallets have emerged as a technology that enables individuals
to store, manage, and conduct transactions using digital currency. These digital wallets offer
convenience, security, and accessibility, making them an appealing alternative to traditional
payment methods. The growing popularity of digital wallets has emphasized the significance
of understanding the factors that influence their acceptance and usage (Agarwal et al., 2020;
Ilieva et al., 2023). In the realm of digital wallets, Worldcoin stands out as an innovative
potential game-changer in the FinTech industry. Worldcoin aims to redefine the relationship
between individuals and digital currency, creating a future of financial transactions with unique
4
products (Guo & Renaldi, 2022; Torpey, 2023). This study focuses on Worldcoin and explores
the potential factors that impact individual decision-making regarding the acceptance of this
technology in the Thai context.
1.2. Research Objective
The research explored the determinants that may influence the adoption of digital wallet
technology, with a particular emphasis on assessing the potential effects and advantages of this
technology within the FinTech sector. The study narrowed its scope to concentrate on the
specific case of Worldcoin digital wallets.
1.3. Research Question
What are the potential factors influencing the adoption of Worldcoin digital wallets and
how do these factors highlight the technology's potential impacts and advantages within the
FinTech sector in the context of Thailand?
1.4. Scope of the Study
The scope of the study encompasses a comprehensive investigation into the factors that
can impact the adoption of digital wallet technology, with a specific focus on evaluating the
prospective implications and benefits of this technology within the burgeoning FinTech sector.
The research will refine its focus to concentrate exclusively on the particular case of Worldcoin
digital wallets. This research will employ a quantitative research method, utilizing online
surveys as the data collection tool. The collected data will be analyzed to draw conclusions
based on a study conducted with a sample group. The researchers conducted this study by
distributing questionnaires to the sample group through Google Form.
1.5. Conceptual Framework
Demographic factors include characteristics such as age, gender, income, education,
occupation, and marital status. These factors are often used to understand consumer behavior
and preferences. In this context, they may be used to predict how different demographic groups
are likely to adopt Worldcoin and digital wallet technology. For example, younger individuals
5
might be more inclined to embrace new technologies, while income levels can influence the
ease of adoption. Social factors encompass elements related to an individual's social
environment, including their social network, family, peers, and cultural background. Social
influence plays a significant role in technology adoption. For example, if an individual's friends
and family are early adopters of digital wallet technology, it may motivate them to follow suit.
Cultural norms and values can also affect the acceptance of new payment methods. Motivation
factors refer to the incentives and reasons that drive individuals to adopt digital wallet
technology. These motivations can include convenience, security, cost savings, and the
availability of rewards or incentives for using the technology. Understanding what motivates
people can help predict their willingness to adopt Worldcoin or digital wallets. Technological
factors encompass aspects related to the digital wallet technology itself. These factors may
include the ease of use, security features, compatibility with various devices and platforms, and
the availability of customer support. A well-designed, user-friendly digital wallet technology
is more likely to be adopted. Economic factors pertain to the financial considerations that
influence the adoption of digital wallet technology. This may involve the cost of using digital
wallets, the potential for cost savings, transaction fees, and the overall economic benefits of
using such technology. Understanding how adopting Worldcoin and digital wallets can impact
an individual's finances is crucial in predicting adoption.
In researching the determinants that may influence the adoption of digital wallet
technology, exemplified by Worldcoin, with a particular emphasis on assessing the potential
effects and advantages of this technology within the FinTech sector, it is possible to create the
conceptual framework (Figure 1.1.) as follows:
6
Figure 1.2. Conceptual Framework
This conceptual framework suggests that by examining these five categories of factors
(demographic, social, motivation, technological, and economic), researchers or businesses can
better understand and predict the adoption of digital wallet technology, specifically in the
context of Worldcoin. By analyzing these aspects, they can tailor their strategies to target and
attract the most likely adopters and address potential barriers to adoption.
1.6. Significant of the Study
This research carries significant importance in shedding light on the dynamics of digital
wallet adoption. It meticulously examines the determinants that may influence individuals and
businesses in their decision to embrace digital wallet technology. By doing so, it addresses a
critical aspect of the modern financial landscape and provides valuable insights into consumer
behaviors and industry trends. Furthermore, the study places a particular emphasis on assessing
the potential effects and advantages of digital wallet technology within the rapidly evolving
FinTech sector. As FinTech continues to reshape financial services, understanding the role and
impact of digital wallets is of paramount importance. This research not only identifies potential
Demographic Factors
Social Factors
Motivation Factors The Adoption of Digital Wallet
Technology (Worldcoin)
Technological Factors
Economic Factors
7
advantages but also highlights potential challenges and risks, contributing to a comprehensive
understanding of the sector.
In a more specific context, the study narrows its focus to concentrate on the particular
case of Worldcoin digital wallets. This targeted approach allows for an in-depth analysis of a
real-world application of digital wallet technology, offering practical insights for individuals,
businesses, and stakeholders associated with Worldcoin. The findings from this specific case
can serve as a valuable reference for similar digital wallet implementations and FinTech
innovations. Overall, this study's significance extends beyond its academic contributions, as its
findings can inform decision-makers, policymakers, and industry leaders in optimizing their
strategies and approaches in the ever-evolving realm of digital finance and technology.
8
CHAPTER 2
LITERATURE REVIEW
2.1. Financial Technology and Digital Wallet
FinTech, a portmanteau of "financial technology," represents the dynamic intersection
of finance and cutting-edge technology. This rapidly evolving sector revolutionizes traditional
financial services, leveraging innovations like blockchain, artificial intelligence, and mobile
applications to enhance efficiency, accessibility, and security. From peer-to-peer lending
platforms empowering individuals to invest and borrow without intermediaries, to robo-
advisors offering personalized investment strategies, FinTech disrupts conventional banking
models. Its transformative impact extends to payment systems, insurance, wealth management,
and beyond, democratizing financial services and fostering financial inclusion on a global
scale. In this digital era, FinTech not only streamlines processes but also fosters innovation,
challenging established norms and driving the finance industry towards a more agile, inclusive,
and technologically empowered future (Cumming et al., 2023; Jabbar, 2023).
According to Startup in Thailand (2022), Thailand has demonstrated a proactive stance
in adopting emergent technologies to bolster its competitive positioning. Specifically, the
financial sector within Thailand has exhibited notable initiatives aimed at fortifying its
operational infrastructure, instituting stringent measures to safeguard consumer interests, and
fostering the cultivation of pioneering technological solutions. Regulatory bodies in Thailand
have demonstrated agility in promptly addressing deficiencies within the legal and regulatory
apparatus, prompted by the evolving landscape of domestic and international FinTech
enterprises. Figure 2.1. presents the Thai FinTech ecosystem.
9
Figure 2.1. Thai FinTech Ecosystem
Source: https://techsauce.co/report/fintech-thailand
FinTech has emerged as a transformative force in the financial industry, revolutionizing
the way financial services are delivered and consumed. This innovative sector combines
cutting-edge technology with finance to create more efficient, accessible, and convenient
solutions for businesses and consumers alike. One of the key components of FinTech is the
digital wallet, which has become increasingly popular for managing and transacting money in
today's digital age (Chen et al., 2023; Uña et al., 2023).
Digital wallets, also known as e-wallets or mobile wallets, are virtual tools that allow
users to store, manage, and make electronic payments securely through a smartphone or other
devices. These wallets have gained prominence due to their user-friendly interfaces, speed, and
convenience. Users can link their digital wallets to their bank accounts, credit cards, or other
sources of funds, enabling them to make payments, transfer money, and perform various
financial transactions with just a few taps on their devices. This technology has significantly
reduced the need for carrying physical cash or cards, streamlining the payment process and
10
making it more efficient. The rise of digital wallets has led to a variety of benefits for consumers
and businesses. One of the most notable advantages is enhanced security. Digital wallets use
encryption and other advanced security measures to protect users' financial information,
reducing the risk of fraud and unauthorized access. Digital wallets offer the convenience of
quick and contactless payments, which is especially relevant in today's fast-paced world. Users
can make payments with a simple tap or a scan, reducing the time spent in checkout lines and
making online shopping more seamless. Additionally, digital wallets are often integrated with
loyalty programs and reward systems, providing users with incentives to use them (Levitin,
2017; Kagan et al., 2023; Tookitaki, 2023). Furthermore, digital wallets play a pivotal role in
financial inclusion, as they enable people without traditional banking access to participate in
the digital economy. This is particularly important in regions with limited banking
infrastructure, where digital wallets can serve as a gateway to financial services. These wallets
have also spurred innovation by fostering the development of various FinTech services, such
as peer-to-peer payment platforms and budgeting tools, which are integrated into the wallets to
provide a comprehensive financial experience (Banerjee & Sinha, 2023; Finextra, 2023).
In Thailand, the FinTech and digital wallet sectors have experienced remarkable
growth, underpinned by supportive regulatory frameworks and government initiatives aimed
at fostering innovation and financial inclusion. The country's Securities and Exchange
Commission (SEC) has implemented a regulatory framework to manage digital wallets and
keys, ensuring clear guidelines for assessing risks, maintaining strict internal controls, and
establishing procedures for managing digital wallets and keys. Businesses are required to
comply with these regulations within six months from their effective date, underscoring
Thailand's commitment to modernizing its financial ecosystem through digitalization (Kayed,
2023). According to Acclime Thailand (2023), Thailand's FinTech landscape is characterized
by a blend of supportive governmental policies, a tech-savvy population, and a thriving startup
ecosystem. The country has witnessed a surge in digital transactions, with e-wallets and mobile
payment platforms gaining widespread popularity. The Thai government's proactive support is
evident through various initiatives, including funding avenues, mentorship programs, and
startup incubation programs, aimed at propelling the sector's expansion. Notably, the Thailand
4.0 initiative seeks to elevate the nation's financial infrastructure and foster the growth of
FinTech enterprises, offering tax benefits, funding for research and development (R&D),
startup support, and the establishment of special economic zones. For FinTech businesses
looking to enter the Thai market, the Board of Investment (BOI) application presents
11
significant benefits, including tax incentives and promoted industries within the FinTech
sector, such as digital payments and e-wallets, P2P lending platforms, blockchain technology,
and InsurTech. The BOI certification offers numerous advantages for multinational fintech
companies, including corporate income tax exemptions, foreign ownership permission,
streamlined work permit and visa processes for expatriates, and land ownership rights for
business operations. These developments signal a conducive environment for FinTech and
digital wallets in Thailand, driven by a supportive regulatory framework and government
initiatives that aim to foster innovation and financial inclusivity.
2.2. Worldcoin
Worldcoin, a digital identification platform, seeks to provide individuals worldwide
with a convenient method for verifying their humanity, differentiating them from bots and
artificial intelligence (AI) algorithms. It utilizes an iris-scanning device, the Orb, to create
unique identification codes, known as IrisCodes, which are stored on the Worldcoin
blockchain. World ID, the heart of the platform, enables users to "verify their humanness''
online while safeguarding their privacy. The World App serves as a repository for user
credentials and provides access to decentralized finance applications, while the Worldcoin
cryptocurrency token is issued to users who create a World ID and download the app. The
project has faced criticisms, including concerns about data privacy and exploitation,
particularly in the developing world, where a significant number of users are located. Ethereum
founder Vitalik Buterin and the MIT Technology Review have raised questions about data
harvesting and informed consent (Curry & Weiner, 2023; George et al., 2023).
Figure 2.2. Worldcoin’s Logo
Source: https://worldcoin.org/
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As reported by Chow (2023) and Tong (2023), the development of Worldcoin is led by
Altman, co-founder of Tools for Humanity, the company behind this initiative. Ironically,
Altman has played a significant role in the AI gold rush, which exacerbates the very problem
that Worldcoin aims to address. Worldcoin leverages cryptographic and blockchain tools
commonly associated with cryptocurrencies to build its digital passport system, which also
supports the Worldcoin crypto token and a payments platform. The World ID, created by the
Orb's iris scanning, provides a "proof of personhood" that is associated with an individual's
unique IrisCode and serves as the foundation of the platform. The IrisCode is detached from
personal information and exists to prevent multiple World IDs for a single person. This identity
is stored on the Worldcoin blockchain and is accessed using a cryptographically secure app.
Worldcoin's Orb is available in various cities worldwide. The World App functions as a
repository for World ID, ensuring privacy while facilitating access to decentralized finance
applications. Additionally, it serves as a cryptocurrency wallet and can store Bitcoin, Ethereum,
USDC, and potentially other cryptocurrencies in the future. The Worldcoin cryptocurrency
token is granted to users upon creating a World ID and downloading the World App. A
substantial number of Worldcoin tokens were airdropped to users during the platform's official
launch, and it is listed on major cryptocurrency exchanges like KuCoin and Binance. Despite
its ambitious goals, Worldcoin has faced criticism. Concerns have been raised about potential
data privacy issues and exploitation, especially in regions such as Asia and Africa, where the
platform has gained a substantial user base. Worldcoin has responded to these criticisms,
asserting that it is primarily concerned with a user's uniqueness rather than their identity (Curry
& Weiner, 2023; Hetler, 2023).
2.3. Demographic Factors
The theory related to demographic factors is of great importance in studying research
on personal characteristics. This information is used to define marketing strategies, segment
markets, and select target groups. Nessim and Wozniak (2001) provide the meaning of
demographic characteristics, which refers to information about individuals such as age, gender,
education, occupation, income, religion, and ethnicity. These factors influence consumer
behavior and are commonly used as foundational characteristics that marketers consider for
market segmentation. These variables are suitable criteria because demographic factors are
13
crucial and clearly measurable indicators in population research, making it convenient for
segmentation (Hayes et al., 2023).
Gender is a significant variable in segmenting the population's preferences and
behaviors, as different genders lead to different communication and decision-making
behaviors. Marketers often use gender as part of their strategies to target and respond to
consumer needs. Age can be used to segment consumer preferences because people of different
ages have varying needs and interests. It also influences an individual's ability to comprehend
information, with younger age groups often interested in trendy products and older age groups
focusing more on health-related products. In addition, education level influences an
individual's knowledge, attitudes, and decision-making abilities. People with different
education backgrounds have varying needs and preferences, which marketers consider when
segmenting markets. Marital Status is also a critical factor. Understanding the number and
characteristics of individuals within a household who use specific products is essential for
developing suitable marketing strategies. Moreover, marital status plays a crucial role in
determining family decision-makers, helping tailor marketing strategies effectively. Income
reflects economic and social status, indicating the purchasing power of individuals. Marketers
use income as a criterion for segmentation to meet the diverse needs of target market groups.
Different occupations reflect distinct lifestyles and interests, affecting consumer behavior and
product choices (Aksorndee, 2017; Tiplerlerd, 2015).
In a broader context, demographics are essential for businesses to understand
population characteristics, including size, distribution, and structure. Key demographic
variables, such as gender, age, education level, occupation, and income, provide insights into
consumer preferences and purchasing power. These factors help marketers tailor their
strategies, segment their markets, and meet the diverse needs of their target audience.
Additionally, lifestyle and cultural influences are considered to further understand and compare
individual behavior and product preferences, as these aspects vary significantly across the
population (Hayes et al., 2023; Hojnik et al., 2023).
2.4. Social Factors
Social factors play a significant role in shaping our behavior, attitudes, and overall well-
being. Social influence is the process by which the presence or actions of others impact an
14
individual's thoughts, feelings, or behavior. It takes various forms, such as conformity,
compliance, and obedience. Conformity involves adapting one's beliefs or behavior to match a
group or social norm, often driven by a desire to fit in. Compliance occurs when individuals
agree to a request or demand, sometimes without genuinely agreeing with it, influenced by
factors like authority or social pressure. Obedience is a more explicit form of compliance, often
seen in situations where people follow orders from an authority figure, as demonstrated in the
Milgram experiment. Social norms, the unwritten rules of a society, also shape social influence
(Cialdini & Goldstein, 2004; Gibson & Smart, 2017; Spielman et al., 2021). Social support, on
the other hand, is the network of assistance, emotional comfort, and resources that individuals
receive from their social circles, including family, friends, and communities. It plays a vital
role in mental and physical well-being. Emotional support involves empathy and care, helping
individuals cope with stress and adversity. Instrumental support provides tangible aid, such as
practical assistance or financial help. Informational support offers guidance and advice, while
appraisal support provides feedback and reassurance, often related to self-esteem and self-
worth. Social support networks are essential for social and psychological well-being, serving
as a buffer against the negative effects of stress and challenging life events (Hajli, 2014; Choi
& Noh, 2020; Asanprakit & Limna, 2023). Furthermore, social presence has gained
prominence as a crucial factor in the digital age. Social presence pertains to the extent to which
individuals in virtual or mediated environments feel connected to others. The level of social
presence depends on the medium used, with video chats offering higher social presence due to
the ability to see facial expressions and body language. Social identity and emotional
connection also play roles in social presence, influencing the strength of virtual relationships
and communities (Jin et al., 2017; Kaye et al., 2017; Mallmann & Maçada, 2021).
Hajli (2014) provided valuable insights into the social factors that affect the quality of
relationships and influence intentions related to social commerce. Molinillo et al. (2020)
conducted a study to investigate the influence of social support and community-related factors
on customer engagement and its connection to loyalty behaviors concerning social commerce
websites. The study affirmed that social support played a substantial role in impacting customer
engagement. Soodan and Rana (2020) also showed that social influence played a crucial role
in shaping the intention to adopt electronic wallets in the state of Punjab, India. Moreover,
Asanprakit and Limna (2023) highlighted the substantial influence of social factors in shaping
consumers' intent to engage in social commerce. Key components such as social norms, social
15
identity, social support, and social comparison have been identified as pivotal factors affecting
consumers' readiness to participate in social commerce.
2.5. Motivation Factors
Motivation factors such as trust, perceived risk, and reliability play a significant role in
influencing people's decisions and behaviors. Trust, a fundamental motivational factor, is the
cornerstone of many human interactions and decision-making processes. When trust is present,
individuals are more inclined to engage in positive behaviors and make certain choices. It
consists of components such as credibility, integrity, and benevolence, reflecting the perceived
competence, honesty, and genuine care of the entity in question. Trust is pivotal in personal
relationships, business transactions, and various other contexts, significantly impacting
motivation and decision-making (Tams et al., 2018; Xie et al., 2023). Furthermore, perceived
risk refers to how individuals assess potential negative consequences or uncertainties
associated with a particular decision. Different types of perceived risk, including financial,
psychological, and physical risk, can act as deterrents or motivators for specific actions.
Reducing perceived risk or providing assurances can be a powerful motivator, as people are
more likely to take action when they perceive lower risk linked to a decision (Amirtha et al.,
2020; Alrawad et al., 2023; Poon & Tung, 2023). In addition, reliability plays a crucial role in
various contexts, such as consumer choices, business relationships, and technology adoption.
It encompasses factors like consistency, dependability, and quality. Reliability motivates
individuals by minimizing uncertainty and the potential for negative surprises, fostering trust
and positive experiences. When entities consistently perform as expected and deliver on their
promises, they can motivate customer satisfaction, loyalty, and continued engagement (Al-
Kuwaiti et al., 2009; Zhao et al., 2022).
Nguyen and Huynh (2018) conducted a study exploring the roles of perceived risk and
trust in e-payment adoption. They found that perceived risk and trust play essential roles in the
structural model of e-payment adoption. Razif et al. (2020) discovered several factors that
exhibited a significant relationship with the acceptance of e-wallet platforms. These factors
include behavioral intention, perceived privacy risk, trust, perceived overall risk, and perceived
performance risk. Hossain et al. (2022) investigated the influence of trust on the intention to
use e-wallet services and confirmed a positive and significant connection between trust and the
16
intention to use e-wallet services. In addition, Senali et al. (2023) demonstrated that perceived
risk significantly influences the intention to adopt e-wallets.
2.6. Technological Factors
Technological factors, such as attitudes, perceived usefulness, and perceived ease of
use toward using technology, are pivotal in shaping the adoption and utilization of new
technologies. Attitudes toward using technology capture the user's overall feelings and beliefs
regarding the technology. Positive attitudes are closely linked to technology adoption and
engagement. When users find the technology enjoyable, relevant to their needs, or compatible
with their existing habits, their attitudes become more favorable. Perceived usefulness revolves
around the user's belief in the technology's ability to enhance performance and bring value.
When individuals see a technology as beneficial, they are more likely to embrace it, particularly
if it improves efficiency, effectiveness, or solves specific problems, and aligns with their needs.
Perceived ease of use, on the other hand, focuses on the user's perception of how user-friendly
and convenient the technology is to operate. A technology that is perceived as easy to use is
more likely to be adopted. Features like intuitive design, accessible training, clear feedback
mechanisms, and consistent functionality contribute to this perception of ease (Al-Adwan et
al., 2023; Marikyan & Papagiannidis, 2023; Rosli et al., 2023).
In the study conducted by Limna et al. (2023), it was found that the way online
consumers perceive the usefulness and ease of use of Facebook Live streaming significantly
affects their intention to make a purchase. Specifically, the convenience of leaving comments
and receiving timely responses from the host was identified as a key factor in creating a smooth
and engaging shopping experience, which, in turn, plays a pivotal role in the consumer's
decision-making process. The presence of informative content was observed to have a positive
influence on customer attitudes and behaviors. Furthermore, Hossain et al. (2022) verified that
perceived ease of use and perceived usefulness had a positive and significant connection to the
intention to use e-wallet services. Senali et al. (2023) also uncovered that the intention to adopt
e-wallets is significantly influenced by perceived usefulness, perceived ease of use.
17
2.7. Economic Factors
Economic factors are integral components of the economic landscape, significantly
shaping both consumer behavior and business strategies. Income, as a central economic factor,
serves as a fundamental determinant of an individual or household's purchasing power,
influencing the types and quality of goods and services they can afford. It also plays a role in
market segmentation, helping businesses tailor their offerings to specific income groups, and
has broader implications for savings, investment, and overall economic growth within a society
(Caswell et al., 2013; The Investopedia Team, 2023). Furthermore, consumption represents the
actions of individuals or households as they utilize their income to meet their needs and desires.
Consumer confidence, levels of debt, cultural influences, and economic cycles all influence
consumption patterns. For businesses, understanding these factors is essential for planning and
adapting to seasonal and cyclical variations in consumer behavior (Hampson et al., 2021;
Maverick et al., 2022). In addition, promotion plays a key role in influencing consumer choices
and market dynamics. Discounts are a promotional strategy with a direct connection to
economic factors, and they play a pivotal role in influencing consumer behavior and economic
dynamics. Economic health and consumer sentiment affect the effectiveness of promotional
strategies. Businesses must adjust their promotional budgets and incentives in response to
economic fluctuations and consumer perceptions. During times of economic uncertainty,
businesses often tailor their promotions to emphasize value and savings (Das et al., 2021;
Dwivedi et al., 2021; Siripipatthanakul et al., 2022).
Didied et al. (2022) unveiled that the appeal of promotions has a positive and significant
impact on the interest in using e-wallets. Putri et al. (2022) indicated that cashback promotions
have a positive and significant effect on the intention to use. These cashback promotions,
offered by various e-wallet platforms, are seen as capable of enhancing user satisfaction,
thereby motivating users to continue using the e-wallet in the future. Additionally, these
promotions serve as a means to inform the market about a new product, introduce innovative
usage methods, communicate price adjustments, explain product functionalities, detail the
services provided by the company, and rectify misconceptions. Rambe and Bangsawan (2023)
confirmed the impact of perceived benefits, convenience, discounts, safety, and risks on the
intentions to use the Indonesian digital wallet application.
18
CHAPTER 3
METHODOLOGY
3.1. Research Strategy
This study employed a quantitative approach, a systematic and empirical method of
studying a phenomenon using measurable data and statistical analysis. It involves the collection
and analysis of numerical data to draw conclusions, make predictions, and identify patterns or
relationships. In a quantitative approach, researchers typically define research questions or
hypotheses and then design studies to gather relevant data. They use various methods to collect
data, such as surveys, experiments, or observations, and convert qualitative observations or
variables into numerical data. This data is often collected from a representative sample to
generalize findings to a larger population. Statistical analysis is a key component of the
quantitative approach (Bergin, 2018; Mohajan, 2020). The quantitative approach is a valuable
research method for studying phenomena that can be measured and analyzed numerically. It
provides a structured and rigorous framework for conducting research and generating empirical
evidence (Ali & Bhaskar, 2016; Mulisa, 2022).
3.2. Sample and Sampling Technique
The study’s respondents were Thai citizens aged 18 years and older who resided in
Thailand. This demographic was selected to represent a cross-section of the Thai population
capable of engaging with digital wallet technology in their financial activities. Convenience
sampling was employed as the primary method for participant selection. Convenience sampling
is a non-probabilistic technique where individuals are chosen based on their ease of
accessibility; in this case, participants who were readily available and willing to take part in
the study. The size of the sample group was determined by calculating the sample size using
Cochran's formula (1977) at a 95% confidence level with a margin of error of ± 5%.
19
The formula includes:
Where n = The desired sample size,
P = The population’s proportion (0.5),
Z = The confidence level set by the researchers at a statistical
significance level of 0.05, the value is 1.96 (95% confidence),
D = The proportion of acceptable margin of error (0.05).
Substitute the values into the formula:
For the precision of this research, the study's sample comprised a total of 1,430
participants. This size was determined based on practical considerations, including available
resources, time constraints, and the feasibility of data collection within the research's scope.
While convenience sampling may have introduced some sampling bias, the larger sample size
aimed to mitigate this limitation by increasing the diversity of participants.
3.3. Research Instrument
This quantitative study utilized a questionnaire as a data collection tool. The researchers
divided the questionnaire into two parts. Part 1 comprised preliminary screening questions that
gathered basic demographic information about the respondents. It also included questions
20
related to an individual's behavior in using a digital wallet in Thailand. This section of the
questionnaire was designed as a checklist. Part 2 encompassed the factors that could potentially
impact the adoption of digital wallet technology, specifically examining the case of Worldcoin
digital wallets. It placed a significant emphasis on evaluating the potential impacts and benefits
of this technology within the FinTech sector. These factors encompassed social influences on
the acceptance of the Worldcoin Wallet, technological influences on its adoption, motivations
that influenced its acceptance, economic determinants affecting its acceptance, and the
intention to use the Worldcoin Wallet.
3.4. Data Collection
Closed-ended questionnaires were conducted to collect the data. The questionnaire
questions were developed based on reliable and valid research data. Furthermore, the
questionnaire was pre-tested on 30 respondents to obtain a dedicated questionnaire, as
recommended by Aithal and Aithal (2020). Moreover, the measurement instruments’ validity
was evaluated. Testing was performed to determine the dependability and accuracy of the
measurement instruments. The data collection process consisted of four key steps. These steps
were designed to ensure a systematic and comprehensive approach to gathering and analyzing
data. In the first step, data collection involved the procurement of essential demographic
information from the respondents. To be eligible for participation, respondents had to be Thai
citizens aged 18 years or older, proficient digital wallet users, and possess significant
experience in digital wallet usage. The research moved forward with the implementation of
stratified sampling. This technique aims to select samples from subgroups with similar
characteristics. Stratified sampling is essential for ensuring that the sample is representative
and reflects the diversity within the population. The third step encompassed the distribution of
questionnaires through online channels. These were disseminated via various social media
platforms, adopting both individual and community-based approaches. This approach ensures
accessibility and engagement across a broad spectrum of potential respondents. Subsequently,
all received questionnaires underwent a thorough screening process. This screening was
conducted to verify the completeness and appropriateness of the questionnaires, ensuring that
they are fit for further data analysis.
To mitigate the potential for bias in the research process, a fundamental measure was
instituted. Participants were strongly encouraged to provide their responses anonymously. By
21
assuring respondents of the anonymity of their feedback, the research aimed to promote candid
and unfiltered responses. This approach was strategically chosen to enhance the reliability and
validity of the data collected. Ethical considerations are of utmost importance in data collection
processes (Bhandari, 2021). In this study, several ethical principles were followed to ensure
the well-being and privacy of the participants. Informed consent was obtained from all
participants, providing them with a clear understanding of the purpose, procedures, and
potential risks and benefits of their involvement. Confidentiality was maintained by assigning
pseudonyms to the participants and storing all data securely, ensuring that their identities
remain anonymous. Participants had the right to withdraw from the study at any point without
facing any negative consequences. Furthermore, data was analyzed and reported in an
aggregated and anonymized manner to protect individual privacy. The study adhered to ethical
guidelines and regulations, demonstrating a commitment to respecting the rights and well-
being of the participants involved.
3.5. Data Analysis
Quantitative data was subjected to statistical analysis to uncover patterns and
relationships within the dataset. Binary regression was employed to analyze the data. The
collected data was analyzed using descriptive and inferential statistics. Descriptive statistics,
comprising frequencies and percentages, were employed to summarize the demographic
characteristics of the participants. Inferential statistics, which included chi-square tests and
logistic regression, were used to explore associations and make predictions concerning the
outcome variable based on the predictor variables. Logistic regression analysis was conducted
to investigate the relationship between the predictor variables (gender, age, education, income,
place of residence, and focus on factors) and the outcome variable. Initially, a baseline model
was established with only the constant term. Subsequently, additional predictor variables were
incorporated into the model to assess their contributions to the prediction of the outcome
variable. The performance of the logistic regression models was assessed using various
statistical measures, such as classification tables. These measures aided in evaluating the fit of
the models, the overall predictive capability, and the accuracy percentage of the predictions.
Descriptive statistics were employed to provide an overview of the sociodemographic
characteristics of the sample group, their digital wallet usage behavior, and their attitudes
toward the acceptance of the Worldcoin Wallet. This analysis encompassed social,
technological, platform-related, and economic factors influencing the acceptance of the
22
Worldcoin Wallet, as well as their intention to use the Worldcoin Wallet in Thailand. The
results were presented in tabular form, including percentages, frequency distributions, means,
and standard deviations, utilizing pre-established statistical analysis tools.
3.5.1. Percentage and Frequency Distribution
Where: P = Percentage
F = Frequency (to be converted into percentage)
N = Total frequency count
3.5.2. Mean (Average)
Where: = Mean
= Sum of all scores
N = Total number of sample groups
3.5.3. Standard Deviation
Where: S.D. = Standard Deviation
X = The score of the sample group
n = Number in the sample group
= Sum of squares of the sample group
= Sum of all scores squared
23
These statistics offer a comprehensive overview and facilitate an understanding of the
sample group's characteristics and behavior within the digital wallet context in Thailand.
3.5.4. Binary Logistic Regression Analysis Model
The analysis conducted is a Binary Logistic Regression Analysis Model, where variable
values are denoted as Y, taking on two forms: Y = 0 (no event occurs) and Y = 1 (an event
occurs). The relationship between the independent variable, denoted as X, and Y in this analysis
exhibits an S-shaped pattern, as follows:
Figure 3.1. Binary Logistic Regression Analysis Model (Kanade, 2022)
3.5.4.1. Case 1 - Single Independent Variable
In the case of Simple Regression Analysis with only one independent variable, the
equation can be represented in linear form. The details are as follows:
For the analysis described above, when Y can take on two values, it is observed that the
relationship between X and Y is not linear but takes the following form:
24
3.5.4.2. Case 2 - Multiple Independent Variables
In the analysis mentioned above, equations with more than one independent variable
take the following form:
Where: P(y) = Probability of an event occurring
Q(y) = Probability of an event not occurring
Q(y) = 1 - P(y)
P(y) greater than or equal to 0.5 indicates that an event occurs. P(y) less than 0.5
indicates that an event does not occur. Generally, 0.5 is commonly used as a threshold for data
classification.
The value of the odds ratio (OR) represents the likelihood of an event occurring
compared to the likelihood of it not occurring. If the odds value is greater than 1, it indicates
that the likelihood of an event happening is higher than the likelihood of it not happening.
Logistic regression models are often expressed in the form of the log of the odds, known
as Logit or Logistic Response Function. It is written in the equation as:
Log (Odds) =
Or Log (Odds) =
25
3.5.5. Testing the Significance of Logistic Regression Coefficients
Testing the significance of logistic regression coefficients is an important step in
understanding the relationship between independent variables and the probability of a binary
outcome in logistic regression analysis. It helps determine whether a particular independent
variable has a statistically significant impact on the outcome variable.
3.5.5.1. Wald Statistic
The Wald Statistic is used to test the hypothesis that the coefficient of the independent
variable is not equal to 0. It follows a Chi-Square distribution. The Wald Statistic follows a
Chi-Square distribution under the null hypothesis. Specifically, it follows a Chi-Square
distribution with 1 degree of freedom because you are testing a single parameter (the
coefficient). The Chi-Square distribution is a positively skewed distribution and depends on
the degrees of freedom. The shape of the Chi-Square distribution becomes more symmetric as
the degrees of freedom increase. To assess the significance of the coefficient estimate, the Wald
Statistic is compared to the Chi-Square distribution table (or a statistical software package) to
obtain a p-value. The p-value represents the probability of observing a Wald Statistic as
extreme as the one calculated, assuming the null hypothesis is true. A small p-value (typically
less than the chosen significance level, e.g., 0.05) indicates that you can reject the null
hypothesis in favor of the alternative hypothesis.
If the p-value is less than the chosen significance level, it suggests that the coefficient
is statistically significant, and you have evidence that the independent variable has a significant
impact on the dependent variable. The hypotheses tested are as follows:
H0: bi = 0; i = 1, 2, … p (The independent variable has no effect on the Odds Ratio).
H1: bi ≠ 0; i = 1, 2, … p
26
3.5.5.2. Likelihood Function
The Likelihood Function, which includes the Full model (Li) and the Simple model
(L0), is employed to test and transform the odds ratio using Log. The likelihood function and
likelihood ratio test are used to assess the significance of the variables and their odds ratios in
logistic regression models. Transforming the odds ratio using the logarithm is a common
practice to understand and interpret the effect of these variables on the outcome in terms of
log-odds. This results in the Likelihood-Ratio Test Statistics.
3.5.5.3. Hosmer-Lemeshow Goodness of Fit Test
The Hosmer-Lemeshow Goodness of Fit Test is a statistical test used to assess how
well a logistic regression model fits the observed data. It is commonly employed to evaluate
the goodness of fit in binary classification models, such as logistic regression models, by
comparing the predicted probabilities with the observed outcomes. The Hosmer-Lemeshow
test uses a Chi-Square test statistic to compare the observed and expected frequencies in these
bins. The Chi-Square statistic measures the difference between the observed and expected
values in each bin. The null hypothesis (H0) in the Hosmer-Lemeshow test is that there is no
difference between the observed and expected frequencies, indicating a good fit of the logistic
regression model. The alternative hypothesis (Ha) is that there is a significant difference,
suggesting a poor fit. The test calculates the Chi-Square statistic and its associated p-value. If
the p-value is less than a chosen significance level (e.g., 0.05), the null hypothesis would be
rejected, and it can be concluded that the model does not fit the data well. If the p-value is
significant (i.e., less than the chosen significance level), it suggests that the logistic regression
model does not provide a good fit for the observed data. This could indicate that the model has
shortcomings in capturing the relationship between the predictor variables and the binary
outcome. The hypotheses tested are:
H0: The model is a good fit.
H1: The model is not a good fit.
27
3.5.5.4. Cox & Snell R Square (Rcs2)
Goodness of fit in logistic regression is a measure of how well the logistic regression
model fits the observed data. It assesses whether the model adequately explains the variability
in the binary outcome variable. In the context of linear regression, the coefficient of
determination (R-squared) is used to quantify the percentage of variance in the dependent
variable that is explained by the independent variables. It ranges from 0 to 1, with 1 indicating
a perfect fit. Unlike linear regression, logistic regression does not use R-squared to measure
the percentage of variance explained, as the logistic model does not directly predict the
dependent variable. Instead, logistic regression models are primarily concerned with modeling
the probability of a binary outcome. Cox & Snell pseudo R-squared and other similar statistics
are used in logistic regression to provide a measure of how well the model fits the data. These
pseudo R-squared statistics range from 0 to 1 but are not directly interpreted as the percentage
of variance explained. They are a measure of how much better the model fits the data compared
to a null model (a model with no predictors). In summary, This test examines the goodness of
fit of the model and explains the percentage of variance in logistic regression analysis.
Generally, Cox & Snell R Square is less than or equal to 1.
3.5.5.5. Nagelkerke R Square (R2N)
Nagelkerke's R-squared is used to assess the goodness of fit in logistic regression and
to provide an estimate of the proportion of variance in the binary outcome variable that is
explained by the model's predictors. In general, the value of Nagelkerke R Square is greater
than Cox & Snell R Square. Nagelkerke's R-squared, like other pseudo R-squared statistics, is
a value that ranges from 0 to 1. An R2N value of 0 indicates that the model does not explain any
of the variance in the dependent variable, while an R2N value of 1 suggests that the model
perfectly explains all the variance. However, achieving an R2N of 1 is rare in practice.
28
CHAPTER 4
RESULTS
4.1. General Data Characteristics of the Respondents
Table 4.1 provides a comprehensive snapshot of the respondents' demographic
characteristics, digital wallet usage, savings, income, and social media platform preferences,
contributing to a clearer understanding of the sample's general profile.
Table 4.1. General Data Characteristics of the Respondents
General Information
Frequency
Percentage
Gender
Female
Male
721
709
50.4%
49.6%
Age
18 - 25 years old
26 - 30 years old
31 - 35 years old
36 - 40 years old
41 years old or over
189
523
288
245
185
13.2%
36.6%
20.1%
17.2%
12.9%
Educational Level
Diploma
Bachelor’s degree
Master’s degree or higher
199
487
744
13.9%
34.1%
52.0%
Occupation
Government employee
Employee
Entrepreneur
Freelance
Students
451
410
355
162
52
31.54%
28.67%
24.82%
11.33%
3.64%
Monthly Income
15,000 THB or less
15,001 - 30,000 THB
30,001 - 45,000 THB
369
281
235
25.8%
19.7%
16.4%
29
45,001 - 60,000 THB
60,001 - 75,000 THB
75,001 THB or more
83
73
389
5.8%
5.1%
27.2%
Monthly Saving
5,000 THB or less
5,001 - 10,000 THB
10,001 - 15,000 THB
15,001 THB or more
661
276
76
417
46.2%
19.3%
5.3%
29.2%
Digital Wallet
WeChat
AIS Pay
Line Pay
True Money
PromptPay
993
339
53
37
8
69.4%
23.7%
3.7%
2.6%
0.6%
Frequency
Seldom
Sometimes
Usually
Always
120
92
158
1,060
8.4%
6.4%
11.1%
74.1%
Social Media Platforms
Facebook
Instagram
Line
TikTok
X
849
460
68
32
21
59.4%
32.1%
4.8%
2.2%
1.5%
Total
1,430
100%
Table 4.1 provides an overview of the general data characteristics of the respondents
involved in the study. The respondents were almost evenly divided by gender, with 721 females
(50.4%) and 709 males (49.6%). The respondents were divided into five age groups. The
majority were between 26 to 30 years old (523 respondents, 36.6%), followed by 31 to 35 years
old (288 respondents, 20.1%), 36 to 40 years old (245 respondents, 17.2%), 18 to 25 years old
(189 respondents, 13.2%), and 41 years old or over (185 respondents, 12.9%). The respondents'
education levels varied, with the majority holding a Master’s degree or higher (744
30
respondents, 52.0%), followed by those with a Bachelor’s degree (487 respondents, 34.1%),
and those with a Diploma (199 respondents, 13.9%). Diverse occupations are represented, with
government employees forming the largest group (31.54%), followed by employees (28.67%),
entrepreneurs (24.82%), freelancers (11.33%), and students (3.64%). The monthly income of
respondents varied widely, with the largest group earning 75001 THB or more (389
respondents, 27.2%), followed by those earning 15000 THB or less (369 respondents, 25.8%),
and the other groups falling between these extremes. In terms of savings, 46.2% of respondents
(661 individuals) reported saving 5000 THB or less monthly, while 29.2% (417 individuals)
saved 15001 THB or more. The table indicates the digital wallet preferences of the respondents.
WeChat was the most popular choice (993 respondents, 69.4%), followed by AIS Pay (339
respondents, 23.7%) and Line Pay (53 respondents, 3.7%). Regarding how often respondents
used digital wallets, the majority stated they always use them (1060 respondents, 74.1%), while
a smaller fraction reported using them usually (158 respondents, 11.1%) or sometimes (92
respondents, 6.4%). The table also looks at social media platform usage among respondents.
Facebook was the most popular (849 respondents, 59.4%), followed by Instagram (460
respondents, 32.1%), and Line (68 respondents, 4.8%).
4.2. The Potential Factors Influencing the Adoption of Worldcoin
4.2.1. Influences of Demographic Factors
Table 4.2. Omnibus Test of the Model's Performance
Chi-square
df
Sig.
Step 1
Step
519.948
9
0.005
Block
519.948
9
0.005
Model
519.948
9
0.005
As depicted in Table 4.2, the chi-square value of 519.948 surpasses the critical value at
a significance level of 0.05, considering the presence of 9 degrees of freedom. This observation
signifies that the dependent variable is significantly influenced by all the independent variables
encompassed within the model. In essence, this indicates that the combined influence of the
31
independent variables carries substantive significance in determining the outcome of the
dependent variable.
Table 4.3. The Model Summary
Step
-2 log likelihood
Cox & Snell R square
Nagelkerke R square
1
1314.473a
0.305
0.422
a. Estimation terminated at iteration number 5 because parameter estimates changed by less than .001.
As presented in Table 4.3, the model, characterized by an R-squared value of 0.422,
indicates that it elucidates roughly 42.2% of the variance in the outcome. Furthermore, the
significance value of 0.05 underscores that the relationship between the independent variables
and the dependent variable holds statistical significance at the 5% level.
Table 4.4. Classification Table for Back-Testing
Predicted
Observed
Worldcoin
Percentage correct
No
Yes
Step 1
Worldcoin
No
819
124
86.9%
Ye
s
249
238
48.9%
Overall percentage
73.9%
Note: The cut-off value is .500.
As indicated in Table 4.4, the classification results revealed that the model,
incorporating all potential independent variables, demonstrated the capability to predict the
Worldcoin wallet usage in Thailand with an accuracy rate of 73.9% for cases, employing a cut-
off value of 0.500 or 50%.
32
Table 4.5. Variables in the Model
B
S.E.
Wald
df
Sig.
Exp(B)
Step 1a
Gender
-1.942
0.176
122.099
1
0.000
0.143
Age
-0.508
0.095
28.497
1
0.000
0.602
Education
0.545
0.159
11.743
1
0.001
1.724
Occupation
0.236
0.067
12.303
1
0.000
1.267
Monthly Income
-0.617
0.097
40.829
1
0.000
0.539
Monthly Saving
1.064
0.093
132.028
1
0.000
2.897
Digital Wallet
-1.800
0.146
152.480
1
0.000
0.165
Frequency
-0.413
0.082
25.201
1
0.000
0.662
Social Media
-0.591
0.121
23.725
1
0.000
0.554
Constance
3.837
0.583
43.361
1
0.000
46.374
a. Variable(s) entered in step 1: Gender, age, education, occupation, monthly income, monthly savings, digital
wallet, frequency, social media
The predictive regression equation of Model 1 using the coefficients from Table 4.5
can be described by the following equation:
𝑃 = 1
1+𝑒−𝑧 ----------- Model 1
where P is an individual’s intent to use the Worldcoin wallet in Thailand, and Z = 3.837
– 1.942(gender) – 0.508(age) + 0.545(education) + 0.236(occupation) – 0.617(monthly
income) + 1.064(monthly savings) – 1.800(digital wallet) – 0.413(frequency) – 0.591
(social media).
The statistical analysis delineated in Table 4.5 meticulously explores the influence of
various independent variables on the propensity of individuals to adopt the Worldcoin wallet
33
within Thailand. This investigation identifies several determinants—gender, age, education
level, occupation, monthly income, monthly savings, current digital wallet ownership,
frequency of digital wallet use, and social media engagement—as pivotal in shaping an
individual's intention to utilize Worldcoin. A noteworthy finding is the gender-based
differential in the adoption intent, with a transition from female (coded as 0) to male (coded as
1) leading to a pronounced decrease in the likelihood of Worldcoin utilization. The quantified
effect illustrates a reduction from a baseline value of 1 to 0.143, indicative of a substantial
decline of 0.857 in adoption intent among males compared to females. Further, the analysis
reveals an age-related decrement in the intent to adopt Worldcoin, with each incremental unit
of age diminishing the likelihood from a normative value of 1 to 0.602, thus marking a
reduction of 0.398. This suggests that younger individuals exhibit a greater propensity towards
adopting Worldcoin. Conversely, educational attainment exhibits a positive correlation with
Worldcoin adoption intent. An increase by one educational level enhances the intention to
adopt by a factor of 1.724, denoting a significant positive influence of higher education on
digital wallet adoption. Occupational status also plays a significant role, with each elevation in
occupational level correlating with a 1.267-fold increase in the intent to adopt Worldcoin. This
underscores the impact of professional status on technological adoption behaviors. Monthly
income, however, demonstrates an inverse relationship with Worldcoin adoption intent. For
each unit increment in monthly income, there is a reduction in the adoption intent from 1 to
0.539, reflecting a decrease of 0.461, suggesting that higher income individuals may exhibit
reservations towards adopting new financial technologies like Worldcoin. In contrast, an
increase in monthly savings significantly boosts the likelihood of adopting Worldcoin, with
each unit increase resulting in a 2.897-fold elevation in adoption intent, highlighting the role
of financial savings behavior in predisposing individuals towards digital wallet adoption.
Ownership of a digital wallet negatively impacts the intent to adopt Worldcoin, as each unit
increase leads to a reduced likelihood from 1 to 0.165, a decrease of 0.835. This may suggest
a loyalty or comfort with existing digital wallet solutions. Usage frequency and social media
engagement both negatively influence the adoption intent. An increase in usage frequency and
social media engagement results in reduced adoption likelihood to 0.662 and 0.554,
respectively, indicating decreases of 0.338 and 0.446. These findings may reflect the complex
interplay between technology usage patterns and the adoption of new financial technologies.
This analysis elucidates the multifaceted influences on the intention to adopt Worldcoin in
Thailand, underscoring the interrelations between demographic factors, economic behaviors,
and technology engagement in shaping digital wallet adoption preferences.
34
4.2.2. Influences of Social, Motivational, Technological, and Economic Factors
Table 4.6. Omnibus Test of the Model's Performance
Chi-square
df
Sig.
Step 1
Step
461.808
12
0.005
Block
461.808
12
0.005
Model
461.808
12
0.005
As depicted in Table 4.6, the chi-square value of 461.808 surpasses the critical value at
a significance level of 0.05, considering the presence of 12 degrees of freedom. This
observation signifies that the dependent variable is significantly influenced by all the
independent variables encompassed within the model. In essence, this indicates that the
combined influence of the independent variables carries substantive significance in
determining the outcome of the dependent variable.
Table 4.7. The Model Summary
Step
-2 log likelihood
Cox & Snell R square
Nagelkerke R square
1
1372.612a
0.276
0.382
a. Estimation terminated at iteration number 6 because parameter estimates changed by less than .001.
As presented in Table 4.7, the model, characterized by an R-squared value of 0.382,
indicates that it elucidates roughly 38.2% of the variance in the outcome. Furthermore, the
significance value of 0.05 underscores that the relationship between the independent variables
and the dependent variable holds statistical significance at the 5% level.
35
Table 4.8. Classification Table for Back-Testing
Predicted
Observed
Worldcoin
Percentage correct
No
Yes
Step 1
Worldcoin
No
855
88
90.7%
Ye
s
284
203
41.7%
Overall percentage
74.0%
Note: The cut-off value is .500.
Table 4.8 reveals that the model, incorporating all potential independent variables,
demonstrated the capability to predict the Worldcoin wallet usage in Thailand with an accuracy
rate of 74.0% for cases, employing a cut-off value of 0.500 or 50%.
Table 4.9. Variables in the Model
B
S.E.
Wald
df
Sig.
Exp(B)
Step 1a
Social Support
1.877
0.272
47.720
1
0.000
6.533
Social Presence
0.942
0.158
35.661
1
0.000
2.566
Trust
0.607
0.179
11.486
1
0.001
1.835
Perceived Risk
-0.511
0.192
7.092
1
0.008
0.600
Service Reliability
1.366
0.190
51.662
1
0.000
3.920
Perceived Usefulness
0.590
0.292
4.071
1
0.044
1.804
Perceived Ease of Use
-0.629
0.275
5.233
1
0.022
0.533
Time Saving
-0.794
0.229
11.981
1
0.001
0.452
36
Convenience
0.207
0.221
0.882
1
0.348
1.231
Consumption
-1.326
0.227
34.209
1
0.000
0.266
Discount
-0.690
0.203
11.507
1
0.001
0.502
Promotion
-1.967
0.298
43.616
1
0.000
0.140
Constance
-7.431
1.003
54.843
1
0.000
0.001
a. Variable(s) entered in step 1: Social support, social presence, trust, perceived risk, service reliability,
perceived usefulness, perceived ease of use, time saving, convenience, consumption, discount, promotion
The predictive regression equation of Model 2 using the coefficients from Table 4.9
can be described by the following equation:
𝑃 = 1
1+𝑒−𝑧 ----------- Model 2
where P is an individual’s intent to use the Worldcoin wallet in Thailand, and Z = –
7.431 + 1.877(social support) + 0.942(social presence) + 0.607(trust) –
0.511(perceived risk) + 1.366(service reliability) + 0.590(perceived usefulness) –
0.629(perceived ease of use) – 0.794(time saving) – 1.326(consumption) –
0.690(discount) – 1.967(promotion).
The empirical analysis delineated in Table 4.9 systematically explicates the statistical
relevance of each independent variable with respect to the propensity of individuals in Thailand
to utilize the Worldcoin wallet. The analysis discerns that the variables such as social support,
social presence, trust, perceived risk, service reliability, perceived usefulness, perceived ease
of use, time savings, consumption, discounts, and promotions significantly impinge upon the
dependent variable: the inclination towards adopting Worldcoin technology. More precisely,
an increment by one unit in social support is correlated with an augmentation in the likelihood
of adopting Worldcoin by a factor of approximately 6.533. An analogous increase in social
presence amplifies the odds of adopting the digital wallet by about 2.566 times. Furthermore,
an elevation in trust towards the digital wallet significantly enhances the probability of its
adoption by an estimated 1.804 times. Conversely, perceived risk is inversely associated with
the adoption of Worldcoin, where a unit increase in perceived risk correlates with a reduction
37
in the likelihood of Worldcoin adoption, decreasing the odds to 0.600. This reduction signifies
a notable decline in adoption intent by 0.400 units. Moreover, the reliability of the service
profoundly influences the likelihood of adoption in a positive manner. There is an approximate
3.920-fold increase in the likelihood of adopting Worldcoin corresponding to each unit increase
in perceived service reliability. In terms of usability, perceived usefulness bolsters the
propensity for adoption, with each unit increase enhancing the intention to adopt Worldcoin by
a factor of 1.804. Contrastingly, perceived ease of use demonstrates a negative correlation with
Worldcoin adoption; an increase by one unit in this variable diminishes the likelihood of
utilizing the Worldcoin wallet from 1 to 0.533, reflecting a decrement of 0.467. Furthermore,
the factors of time savings, consumption, discounts, and promotions exhibit diverse negative
impacts on the intention to adopt Worldcoin. Specifically, for each unit increment in time
savings, there is a reduction in the adoption likelihood from 1 to 0.452, highlighting a decrease
of 0.548. Similarly, an increment in consumption correlates with a decrease in adoption
likelihood from 1 to 0.266, indicating a significant decline of 0.734. The influences of discounts
and promotions follow suit, with unit increases resulting in respective decreases in adoption
likelihood to 0.502 and 0.140, signifying declines of 0.498 and 0.860, respectively.
38
CHAPTER 5
DISCUSSION AND CONCLUSION
5.1. Discussions
The research investigated determinants influencing the utilization of the Worldcoin
wallet within the Thai context. It elucidated that an individual's propensity towards adopting
the wallet was shaped by multifaceted elements including demographic and socio-economic
characteristics such as gender, age, educational attainment, occupational status, monthly
income, savings levels, existing digital wallet ownership, frequency of use, and social media
interaction. Significantly, gender disparities were evident, with females demonstrating a higher
propensity towards Worldcoin wallet adoption than males. This distinction could be ascribed
to variations in financial behaviors, rates of technology acceptance, or payment method
preferences, corroborating the findings of Prachayanant et al. (2023), who noted a gender-based
discrepancy in cryptocurrency game engagement. Conversely, the research highlighted an
inverse relationship between age and wallet usage intention, potentially attributable to
generational differences in technological receptiveness and payment method preferences,
aligning with Doungpitak et al. (2023)'s conclusions regarding age and digital competencies.
Educational level emerged as a positive influences on wallet adoption likelihood, suggesting
that higher education levels enhance comprehension of digital wallets' benefits and security
features, fostering trust and willingness to adopt such technologies. This concurrence is
supported by the investigations of Thetlek et al. (2023) and Doungpitak et al. (2023),
highlighting education's role in the digital sphere and token economy. The analysis further
indicated that individuals in higher-status occupations were more inclined towards Worldcoin
wallet utilization, reflecting potentially greater financial resources, familiarity with fintech, and
openness to novel payment methodologies. These observations resonate with the insights
provided by Siri and Kraiwanit (2023) regarding occupational status and financial behaviors.
Interestingly, an inverse correlation was noted between monthly income levels and the
inclination to adopt the Worldcoin wallet, suggesting that higher-income individuals might
adhere to more traditional financial practices. This notion is parallel to findings by Shaengchart
et al. (2023) regarding income's influence on market dynamics within Thailand's internet
service sector, and by Thetlek et al. (2023) concerning the token economy. Furthermore,
individuals with higher savings exhibited greater inclination towards Worldcoin wallet
39
adoption, potentially due to increased financial security, aligning with findings by Siri and
Kraiwanit (2023) on savings impact on financial decision-making. Ownership of an existing
digital wallet deterred the adoption of Worldcoin, possibly reflecting satisfaction with current
services and resistance to change, echoing Wannasawang and Kraiwanit (2023)'s findings on
digital wallet selection behaviors. Moreover, a paradoxical relationship emerged between
Worldcoin wallet usage frequency and adoption intention, suggesting a possible saturation
effect among current users, supported by Duangsin and Kraiwanit (2023)'s research on service
usage patterns. Lastly, intensive social media engagement correlated negatively with the
intention to use Worldcoin wallet, possibly due to privacy and security concerns or satisfaction
with existing payment methods, aligning with Elareshi et al. (2023), Jangjarat et al. (2023),
Nazir et al. (2023), and Singharat et al. (2023)'s analyses on social media's impact on
technological adoption and online consumer behavior.
The analysis further explored the influence of various factors on the inclination to adopt
Worldcoin technology, shedding light on the complexities of technology acceptance. Among
the variables studied, social support, social presence, trust, perceived risk, and service
reliability stand out as significant determinants of adoption likelihood. Social support and
social presence both positively affect individuals' likelihood to adopt Worldcoin, underscoring
the importance of social factors in the decision-making process regarding new technologies.
The study's findings align with those of Kulviwat et al. (2009), indicating that social influence
and adoption attitude positively affect consumers' intentions to adopt an innovation.
Specifically, the effect of social influence on adoption intention is entirely mediated by
consumer attitude. Moreover, the relationship between social influence and adoption intention
strengthens when an innovation is consumed publicly rather than privately. Similarly, trust
towards the digital wallet plays a crucial role, with increased trust associated with a higher
probability of adoption, highlighting the need for trustworthy digital services. Consistent with
Khan and Abideen (2023), perceived trust moderates the relationship between perceived risk
and usage behavior of digital wallets. Concerns over potential adverse outcomes may make
customers hesitant to use the technology, highlighting the significance of perceived trust in the
acceptance and usage of digital wallets. Consumers who trust in the reliability of the service
provider are more likely to use the service and recommend it to others. Conversely, perceived
risk inversely impacts the willingness to adopt Worldcoin, indicating that higher perceived
risks discourage adoption. This suggests that addressing and mitigating perceived risks could
be essential for increasing technology uptake. Khan and Abideen (2023) found that perceived
40
risk significantly mediates the relationship between behavioral intention and usage behavior of
digital wallets. If an individual perceives a significant level of risk associated with using a
digital wallet, their behavioral intention to use the digital wallet decreases. Furthermore, an
individual's actual usage behavior of a digital wallet is influenced by their level of perceived
risk, even if they initially intend to use the digital wallet. Service reliability also significantly
influences the adoption likelihood, with greater reliability enhancing the willingness to adopt
the wallet, emphasizing the critical role of dependable service in user acceptance. Aligned with
Rachmawati et al. (2022), the reliability factors of trust, along with regulations and policies,
greatly influenced the intention to use electronic government services. Wong and Mo (2019)
also verified that when consumers perceive a service as honest and reliable, it significantly
boosts their intention to use the service, due to their strong belief in it. In terms of usability,
perceived usefulness positively correlates with the intention to adopt Worldcoin, indicating that
recognizing the benefits and effectiveness of the digital wallet is pivotal. Consistent with the
findings of Tian et al. (2023), perceived usefulness is positively associated with behavioral
intention to use mobile payment services. However, perceived ease of use exhibits a surprising
negative correlation, suggesting that other factors might overshadow the simplicity of using
the wallet in the adoption decision process. In accordance with Gunawan et al. (2019),
perceived ease of use negatively and insignificantly affects consumer attitudes, while perceived
usefulness positively and significantly influences consumer attitudes. Furthermore, perceived
ease of use has a positive yet insignificant effect on purchase decisions, just as perceived
usefulness exhibits a positive but insignificant impact on purchase decisions. Additionally,
consumer attitudes significantly and positively affect purchase decisions. Additionally, time
savings, consumption, discounts, and promotions were found to have diverse negative impacts
on the intention to adopt Worldcoin. These findings suggest that while these factors are
typically considered benefits, they may not necessarily increase the likelihood of new
technology adoption in this context. Consistent with Rashaduzzaman (2020), time savings were
not identified as significantly influencing the development of online apparel purchase
intentions. Chen and Weber (2010) found that while discounts affect bidding behavior and
market outcomes in a second-price, sealed-bid auction, they do not alter bidders' intentions to
participate in such auctions. Nguyen and Nguyen (2022) revealed that promotional incentives
did not directly impact the intention to use mobile wallets. Instead, this relationship was
mediated by social influence and compatibility factors.
41
5.2. Conclusions
The research delves into factors influencing the adoption of the Worldcoin wallet in
Thailand, identifying demographic and socio-economic characteristics such as gender, age,
education, job status, and digital engagement as key determinants. Specifically, it notes a higher
inclination among females towards Worldcoin wallet adoption, attributing this trend to
differences in financial behaviors and technology acceptance. Age inversely affects wallet
usage intention, suggesting younger generations are more receptive to new technologies, which
parallels findings in digital literacy research. Higher education correlates with a greater
likelihood of adopting digital wallets, emphasizing the role of understanding in technology
adoption. Furthermore, the study observes that individuals in higher occupational statuses show
more openness to adopting Worldcoin, possibly due to better financial literacy and exposure to
fintech. However, there's an unexpected negative correlation between higher income levels and
wallet adoption, hinting at a preference for traditional financial practices among the wealthier.
Conversely, higher savings levels correlate positively with the inclination to adopt Worldcoin,
reflecting financial security's role in embracing new technologies. Interestingly, existing digital
wallet users displayed resistance to switching to Worldcoin, underscoring the challenges new
entrants face in changing consumer habits. A paradox emerges with frequent users showing
less intention to adopt new wallets, indicating satisfaction or saturation with current solutions.
Moreover, intense social media engagement surprisingly correlates negatively with adoption
intention, possibly due to privacy concerns.
The study also highlights the significant impact of social factors, trust, perceived risk,
and service reliability on adoption intentions. Trust and social support notably enhance the
likelihood of adopting Worldcoin, while perceived risk and service reliability concerns deter
potential users. Notably, the study contradicts expectations regarding perceived ease of use,
which showed a negative correlation with adoption intention, suggesting that simplicity alone
does not drive the adoption of new technologies. Finally, the research indicates that while time
savings, consumption, discounts, and promotions generally benefit users, they do not
necessarily increase the likelihood of adopting new technologies like Worldcoin, aligning with
previous studies indicating that such factors might not significantly influence the adoption
intentions in digital financial contexts.
42
5.3. Research Implications
The research on Worldcoin wallet adoption in Thailand provides multifaceted insights
significant for different sectors. On an academic level, it adds depth to the literature on digital
payment adoption by uncovering surprising influences, such as the significant roles
demographic factors play and how individual perceptions nuanced impact technology
adoption. This discovery encourages further academic exploration into the socio-psychological
drivers or barriers affecting the uptake of digital financial instruments. The nuanced
understanding of demographic impacts, particularly, opens new avenues for research into
personalized technology engagement strategies.
For practitioners in the industry, this study highlights the necessity of tailoring product
attributes and marketing approaches to meet the distinct expectations and profiles of different
user groups, with a strong emphasis on fostering trust and resolving compatibility issues. The
insights gained can guide financial educators and tech developers in crafting more precise
educational materials and designing interfaces that resonate more effectively with target users,
enhancing the overall user experience. Moreover, the research advises regulatory authorities to
forge conducive environments fostering the safe and efficient expansion of digital payment
systems, addressing legal, security, and usability concerns. By doing so, they can aid in
accelerating the adoption rate while ensuring user protection and system integrity.
In essence, this study provides a holistic view that could significantly influence the
trajectory of technology development, marketing strategies, and regulatory frameworks within
the digital wallet sector. By addressing these critical areas, stakeholders can collectively
advance the adoption and usability of digital payment solutions, potentially setting a
benchmark for similar innovations globally.
5.4. Policy Recommendations
To further enhance the adoption and security of digital wallets in Thailand, a
comprehensive and detailed policy framework is required. Regulators should develop and
enforce a clear set of guidelines that not only protect users but also foster transparency and
prevent fraudulent activities within digital wallet operations. These guidelines should include
standardized security protocols such as two-factor authentication and end-to-end encryption,
43
ensuring the integrity of transactions and personal data. Nationwide educational campaigns are
crucial. They should not only inform the public about the functionalities and advantages of
digital wallets but also educate them on cybersecurity practices and how to identify potential
scams. This educational push should target diverse demographic groups to ensure widespread
understanding and adoption. Financial inclusion policies should focus on eliminating barriers
for the unbanked and underbanked segments, ensuring digital wallet services are accessible
and affordable. This might include developing low-cost wallet options or subsidizing internet
access in remote areas, enabling broader economic participation. The government should
encourage a fertile environment for innovation by providing financial incentives such as grants
or tax breaks for startups and companies developing digital payment solutions. This approach
should aim to stimulate competition but also ensure consumer protection standards are
maintained. Partnerships are key; therefore, fostering collaborative efforts between the
government, financial institutions, and fintech companies can lead to the development of
interoperable and user-friendly digital wallet platforms. Such collaborations could also extend
to educational institutions for research and development purposes, enhancing the technological
underpinnings of digital wallets. Mandatory security measures should be rigorously enforced,
with clear guidelines for digital wallet providers. Users should be encouraged, through
educational campaigns, to adopt secure online practices, reducing the risk of fraud and theft.
Finally, establishing a monitoring and evaluation system is critical to track the adoption rates,
user satisfaction, and security incidents related to digital wallets. This system should inform
policy adjustments and interventions, ensuring the digital wallet ecosystem remains robust,
secure, and inclusive. Through continuous assessment and responsive policy-making, Thailand
can ensure the successful integration of digital wallets into its financial landscape, promoting
economic growth and digital inclusivity.
5.5. Limitations and Recommendations for Future Studies
The study focusing on the adoption of Worldcoin digital wallets among Thai adults
offers valuable insights while acknowledging certain limitations inherent in its design. The use
of convenience sampling and the restriction to a specific demographic within Thailand may not
accurately reflect the broader population's perspectives, highlighting the necessity for future
research to employ randomized sampling techniques and to broaden its demographic and
geographic scope for enhanced universality. Additionally, the research's reliance on cross-
sectional data and self-reported responses could limit understanding of long-term trends and
44
introduce response biases. Future investigations could benefit from adopting longitudinal study
designs and incorporating objective data metrics, such as actual user interaction logs from
digital wallet providers, to obtain a more comprehensive and unbiased view of consumer
behavior. Expanding these research dimensions would not only provide a richer and more
detailed understanding of the factors driving digital wallet adoption but also enable FinTech
stakeholders to develop more targeted and effective strategies. By considering these
enhancements, future studies can pave the way for more refined approaches, ultimately
fostering wider acceptance and optimized utilization of digital wallet technologies across
varied user segments and geographical locales.
45
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APPENDIX
57
Appendix A
Ethical Clearance Certificate
58
Appendix B
Questionnaire
Digital Wallet Dynamics: Understanding the Potential Adoption Factors of
Worldcoin in Thailand's FinTech Sector
Your responses to this questionnaire are essential for data analysis and interpretation. Consequently, we
ask for your assistance in answering the questionnaire based on your opinions and facts. The
information you provide in this questionnaire will be kept confidential to analyze the data obtained.
5 = Strongly Agree
4 = Agree
3 = Neutral
2 = Disagree
1 = Strongly Disagree
1. Gender
● Female
● Male
2. Age
● 18 - 25 years old
● 26 - 30 years old
● 31 - 35 years old
● 36 - 40 years old
● 41 years old or over
3. Educational Level
● Diploma
● Bachelor’s degree
● Master’s degree or higher
59
4. Occupation
● Government employee
● Employee
● Entrepreneur
● Freelance
● Students
5. Monthly Income
● 15,000 THB or less
● 15,001 - 30,000 THB
● 30,001 - 45,000 THB
● 45,001 - 60,000 THB
● 60,001 - 75,000 THB
● 75,001 THB or more
6. Monthly Saving
● 5,000 THB or less
● 5,001 - 10,000 THB
● 10,001 - 15,000 THB
● 15,001 THB or more
7. Digital Wallet
● WeChat
● AIS Pay
● Line Pay
● True Money
● PromptPay
8. Frequency
● Seldom
● Sometimes
● Usually
● Always
60
9. Social Media Platforms
● Facebook
● Instagram
● Line
● TikTok
● X
10. The Potential Adoption Factors of Worldcoin in Thailand's FinTech Sector
The Potential Adoption Factors of Worldcoin in Thailand's FinTech Sector
5
4
3
2
1
1. Friends or people in society sharing their experiences with using e-wallets allow
you to learn through the experiences of others.
2. E-wallets enable us to create a society, friends, and member groups
3. You trust that the e-wallet platform is a secure platform for transactions.
4. Conducting transactions on the e-wallet does not make you feel that it is an
action susceptible to fraud or data theft.
5. Merchants on the e-wallet platform are trustworthy in their services.
6. E-wallet is beneficial for you in conducting financial transactions.
7. You find using the e-wallet platform easy.
8. You feel that using the e-wallet saves you time.
9. Using the E wallet platform provides you with convenience.
10. You are likely to use the e-wallet platform continuously.
11. You are likely to use the e-wallet platform if there are good discounts.
12. You are inclined to use the e-wallet platform if there are good promotions.
61
Appendix C
Publication
62
63
64
65
66
67
68
69
70
71
RESEARCHER BIOGRAPHY
1. Tanpat Kraiwanit
Faculty of Economics, Rangsit University, Thailand
Email: tanpat.k@rsu.ac.th
Scopus Author ID: 57226276574
Dr. Tanpat Kraiwanit is an Associate Professor and the director of Ph.D. in Digital
Economy program, Faculty of Economics, Rangsit University, Pathum Thani, Thailand. His
research interests are digital economy, digital technology, innovation, cryptocurrency, sharing
economy, silver economy, social banking, and decentralized finance.
2. Pongsakorn Limna
Faculty of Economics, Rangsit University, Thailand
Email: pongsakorn.l65@rsu.ac.th
Scopus Author ID: 58315906900
Pongsakorn Limna is a Ph.D. candidate in the Ph.D. in Digital Economy program,
Faculty of Economics, Rangsit University, Pathum Thani, Thailand. His research interests are
digital economy, innovation, technology, artificial intelligence (AI), business administration,
management, communication, psychology and consumer behavior.
3. Peerapat Wattanasin
Faculty of Economics, Rangsit University, Thailand
Email: peerapat.wat64@rsu.ac.th
Scopus Author ID: 58853847300
Peerapat Wattanasin is a Ph.D. student in the Ph.D. in Digital Economy program,
Faculty of Economics, Rangsit University, Pathum Thani, Thailand. His research interests are
digital economy, financial technology (FinTech), innovation, technology, and cryptocurrency.
