Payment Platform Research Articles

Determinants of Environmental Pollution: Evidence from Indonesia

This study explores the nexus between electricity consumption, fossil fuel use, renewable energy adoption, population growth, GDP, and environmental pollution in Indonesia, incorporating open innovation dynamics as a novel dimension of analysis. The study uncovers significant long-term relationships between the variables using time series data from 2000 to 2023 and applying econometric techniques such as cointegration analysis, Granger causality tests, and Vector Error Correction Models (VECM). The results indicate that electricity consumption drives economic growth and CO₂ emissions, while fossil fuel dependency significantly contributes to environmental pollution. Renewable energy adoption, though growing, is insufficient to offset the environmental damage caused by fossil fuel use. The study also identifies the potential of renewable energy to mitigate pollution levels, though challenges such as technological barriers and high initial investment costs remain. Population growth intensifies energy demand and pollution, underscoring the necessity for sustainable energy policies. Additionally, the research highlights the role of open innovation, particularly in renewable energy, mobile payment platforms, and collective intelligence, in addressing Indonesia's energy-environment challenges. Policy recommendations emphasize the need for more substantial incentives for renewable energy, the regulation of fossil fuel consumption, and the development of an open innovation ecosystem that engages both the public and private sectors.

Harnessing Artificial Intelligence (AI) and Blockchain Technology for the Advancement of Finance Technology (FinTech) in Businesses

This brief investigation seeks to explore the significant impact and offer a thorough analysis of the transformative potential of artificial intelligence (AI) and blockchain technology in revolutionizing financial technologies (FinTech) within the context of African business environments. Central to this study is an examination of how AI-driven solutions and blockchain technology can improve efficiency, accessibility, and innovation in financial services. Currently, African businesses face numerous challenges that hinder their overall success. Among these are the prevalence of fraud in Africa’s economy and the absence of credit scoring and reliable risk management, leading to bad debts and poor capital management. The businesses also lack data infrastructure, regulatory compliances, customer engagement and personalisation data privacy, cybersecurity and volatile currencies. Through intensive evaluation, we will be venturing into and showcasing how applications of AI and blockchain technology address these hurdles via techniques involving fraud detection, risk mitigation, advanced credit assessments and scoring for underserved communities, loan origination systems, and automated customer support utilising tools like chatbots, bolstered market analytics, streamlined regulation conformance, and augmented financial inclusivity encompassing digital payment platforms, saving mechanisms, loans, investments, and insurance products. By leveraging AI, African businesses can propel FinTech innovation and progression, foster economic prosperity, and drive sustainable development. The paper comprehensively analyses the current state of AI-driven FinTech solutions in Africa, identifying key factors that can unlock a new era of financial innovation, potential challenges businesses may face in implementing these technologies and our comprehensive research on their solutions.

Advancing financial inclusion through digital payment platforms in emerging markets

Advancing financial inclusion in emerging markets has become a critical focus for economic development, and digital payment platforms are playing a transformative role in this process. These platforms offer a scalable solution to bridge the gap between the unbanked population and formal financial services, enabling individuals and businesses to access affordable and secure financial products. The rise of mobile technology and widespread internet penetration have provided the infrastructure for digital payments to thrive, particularly in regions where traditional banking systems are underdeveloped. Key enablers include mobile money services, fintech innovations, and supportive regulatory frameworks that promote adopting digital financial solutions. Digital payment platforms facilitate faster, more efficient transactions, reduce the reliance on cash, and open up opportunities for marginalized groups, including women and small business owners, to participate in the formal economy. They also enhance financial literacy by offering accessible financial education tools, which empower users to manage their finances more effectively. However, challenges such as limited digital literacy, regulatory barriers, cybersecurity risks, and the digital divide must be addressed to maximize the potential of these platforms. Emerging markets have witnessed significant success stories, particularly in Africa and Southeast Asia, where mobile money platforms like M-Pesa and GCash have expanded financial access to millions. These platforms contribute to financial inclusion and stimulate economic growth by integrating more people into the financial system. Moving forward, collaborative efforts between governments, private sector stakeholders, and development organizations are essential to ensuring that digital payment platforms continue to drive financial inclusion sustainably and equitably.. Keywords: Financial Inclusion, Digital Payment Platforms, Emerging Markets, Mobile Money, Fintech, Unbanked Population, Economic Development, Financial Literacy, Digital Financial Services, Mobile Technology.

Bridging India's Financial Divide: The Power of Artificial Intelligence and Machine Learning

Artificial Intelligence (AI) and Machine Learning (ML) are transforming India's financial sector, enhancing decision-making, risk assessment, and personalized services. They extend financial services to underserved populations through scalable solutions like digital lending and mobile banking, fostering financial inclusion and bridging urban-rural gaps. Notable progress has been made through initiatives like the Pradhan Mantri Jan Dhan Yojana (PMJDY), which opened over 53 crore accounts by August 2024. However, challenges such as low literacy rates, inadequate digital infrastructure, and a large informal economy persist. AI and ML address financial inclusion gaps by automating KYC processes and improving onboarding through facial recognition and identity verification. Initiatives like Aadhaar provide digital identities, enhancing access to banking. ML algorithms expand financial access by analyzing alternative data for credit scoring. Companies like Lenddo and Tala leverage ML for loans, and AI revolutionizes fraud detection by analyzing transaction data in real-time. AI integration with digital payment platforms like UPI has transformed India's financial ecosystem, processing over 15 billion transactions monthly by August 2024 (NPCI). AI-driven micro-lending platforms like Capital Float and Aye Finance address a $380 billion credit gap (BCG) by assessing creditworthiness using alternative data. AI-driven chatbots and financial products tailored to rural customers improve financial literacy and services. In agricultural finance, AI introduces lending models and enhances crop insurance through satellite data and weather patterns. Programs like PMFBY and companies like Skymet use AI for faster claims processing. AI-driven solutions in RegTech simplify compliance and improve fraud detection. Fintech collaborations and government initiatives like IndiaStack, Aadhaar, and DigiLocker promote financial inclusion. Overcoming barriers like infrastructure challenges, data privacy concerns, and AI bias is essential for leveraging AI to provide equitable financial services in India. The constructive interaction between AI and blockchain further enhances financial inclusion, creating a secure, transparent ecosystem that drives economic growth and social well-being.

Influencia de los Delitos Cibernéticos Económicos en Perú

This article aimed to analyze the influence of economic cybercrimes in Peru during the year 2024, addressing the most common modalities, their economic impact, and deficiencies in the legal framework. Economic cybercrimes, such as phishing, identity theft, attacks on payment platforms, and e-commerce scams, have grown significantly in recent years, generating substantial economic losses and affecting user confidence in digital platforms. The methodology adopted was qualitative, with an exploratory and descriptive approach. For data collection, semi-structured interviews with criminal lawyers, prosecutors, and cybersecurity experts were used, along with the analysis of relevant court cases and the documentary review of official reports. The results showed a 26% increase in economic cybercrimes compared to the year 2023. Among the conclusions of the study, the urgent need to update the Peruvian legal framework to adapt to the new criminal modalities that arise with technological advances was highlighted. This analysis sought to provide a critical view on the incidence of economic cybercrimes in Peru.

Consumer resistance to WhatsApp payment system: integrating innovation resistance theory and SOR framework

PurposeDespite an exponential rise in the frequency of online payments in India, the cause of consumer resistance towards the WhatsApp payment system (WPS) remains unexplored. This research is aimed at exploring the barriers to the adoption of WPS.Design/methodology/approachA research model was proposed using stimulus-organism-response framework and innovation resistance theory. Data were collected from 392 users of the WhatsApp application using the mall intercept technique, which also utilizes digital payment platforms. A co-variance based structural equation modelling was employed to test proposed relationships in this cross-sectional study.FindingsThe study findings indicate that personal innovativeness as a personal stimulus negatively influences the usage and value barrier, while negative word of mouth (NWOM) increases the intensity of tradition and the image barrier. Additionally, value barrier, usage barrier, risk barrier and tradition barrier were found to have a negative influence on the intention to adopt the WhatsApp payment system.Originality/valueThis research is an initial endeavour that sheds light on the consumer cognition resisting the adoption of the WPS.

The Role of Trust in the Normalization of Digital Payment Platforms in the United States

This study aims at identifying the effects of trust on the uptake and sustenance of digital payments in the United States, using Apple Pay, PayPal, and Google Pay. The study's first chapter presents the concept of digital payments and analyzes how factors like security, privacy, and perceived ease of use influence trust. Research on the topic of trust in digital transactions includes a literature review that seeks to identify the research gaps. The study employs both quantitative and qualitative research methods, including questionnaires and interviews, to collect data on the perceived level of trust across various platforms. The study outcomes show that security and privacy are paramount in influencing users’ trust, although there are differences in the different groups. Apple Pay places a significant emphasis on security, whereas Google Pay caters to younger users, albeit with some privacy concerns. The discussion brings out the similarities between the findings and prior research and provides recommendations on how digital payment platforms can cultivate and sustain trust. Final is the outline of the implications for digital payment providers and suggestions on further research, emphasizing the importance of privacy and the context-specificity of trust-building procedures.

A global adoption of cryptocurrency and blockchain technology into the healthcare system

Abstract Background/Objectives Blockchain technology is revolutionizing various industries by enhancing security, transparency, and efficiency. In healthcare, its small-scale application demonstrates the potential to transform healthcare. This study explores how cryptocurrency and blockchain technology enhance healthcare financial stability, secure medical information exchange, increase payment recovery and interoperability. Methods Guided by the Diffusion of Innovations (DOI) Theory, this study reviews 34 articles on blockchain and cryptocurrency adoption in healthcare. We performed a thematic analysis focusing on empirical data, theoretical analyses, and existing implementations. Data were categorized by DOI elements: relative advantage, compatibility, complexity, trialability, observability, and social system. The findings were synthesized into a detailed framework for adopting these technologies in healthcare. Results Our analysis shows that cryptocurrency offers a secure, decentralized payment platform, eliminating the need for third-party intermediaries. Blockchain adoption enhances payment and patient record protection. Cryptographic methods ensure data integrity, transparency, and security, preventing modifications once recorded. Altering data requires consensus from the network majority, protecting healthcare providers from ransomware attacks. Conclusions Evidence suggests that cryptocurrency and blockchain will disrupt healthcare payments, data management, and accommodate interoperability within the next decade. These technologies promise improved security, improved public health research, and increased trust in the healthcare system. Key messages • Our research will be assessing the challenges of integrating digital coins and blockchain technology into the healthcare system. • Examine the potential benefits and risks of implementing blockchain technology in healthcare settings.

Impact of Autoscaling on Application Performance in Cloud Environments

The current paper studies the impact of Autoscaling on application performance in Cloud computing environments. Cloud computing is one of the most encouraging innovations due to its vast applications. Predictive autoscaling is an advanced technique that aims to address the challenges in the autoscaling trends for large-scale systems. To account for the Quality of Service to the customer, features like load balancing according to the workload demand, understanding resource allocation and utilization, and dynamic decision-making are vital to any cloud computing application. This paper interprets these challenges and reviews a meta-reinforcement learning approach for predictive autoscaling in cloud environments. A novel RL-based predictive autoscaling approach on a popular large-scale digital payment platform system, Alipay, is compared with the existing models such as Autopilot and FIRM. The aim is to conduct a detailed analysis of performance metrics before and after autoscaling actions, aiming to identify optimal scaling strategies that minimize response time and maximize resource utilization without over- provisioning.

Trust and Religiosity: Integrating Technological Acceptance Factors into the Extended Unified Theory of Acceptance and Use of Technology (UTAUT) Model for Zakat Online Payment Systems

The aim of this study is to examine the adoption of digital zakat payment platforms among micro-entrepreneurs, incorporating trust and religiosity into the Unified Theory of Acceptance and Use of Technology (UTAUT) model. This research extends the traditional UTAUT framework by integrating trust and religiosity as additional determinants of technology adoption intention, alongside the model's core constructs of performance expectancy and social influence. Primary data for this study was gathered through a digital survey disseminated to 110 micro-entrepreneurs in the state of Kedah, all of whom are actively registered with the Malaysian Company Commission (SSM), under the auspices of the Ministry of Domestic Trade, Cooperatives, and Consumerism (KPDNKK). The methodological approach is rooted in structural equation modelling, which facilitates a rigorous empirical analysis of the relationships between technological constructs and user intention. The results reveal that trust and performance expectancy, along with social influence, significantly impact micro-entrepreneurs’ intentions to engage with online zakat payment systems. Interestingly, despite the religious nature of zakat, religiosity did not emerge as a significant predictor in the context of this digital payment adoption. This insight suggests that while religious obligation drives the act of zakat itself, it is the technological aspects of trust and anticipated performance that influence the preference for digital payment methods over traditional ones. This research provides valuable implications for zakat institutions and policymakers aiming to foster the digitalization of religious financial transactions. By highlighting key factors that influence digital adoption, the study underscores the potential for zakat management bodies to innovate and promote digital solutions that align with micro-entrepreneurs' expectations and trust requirements. Ultimately, this study charts a path forward for enhancing digital inclusivity in religious financial practices, marking a transition from conventional to modern, technology-enabled means of fulfilling zakat obligations.

Evolution of Paytm's Business Model

This case study explores the evolution of Paytm's business model, highlighting its transformation from a mobile recharge platform to a multifaceted digital services powerhouse. Initially launched in 2014 by One97 Communications as a prepaid mobile recharge and bill payment platform, Paytm rapidly diversified its offerings to include e-commerce, financial services, and digital payments, capitalizing on India's burgeoning digital economy. The study examines key phases in Paytm's business model evolution, including its expansion into the financial sector with services such as Paytm Wallet, Paytm Payments Bank, and investment products.The analysis focuses on strategic decisions that fueled Paytm's growth, such as its aggressive market penetration strategies, partnerships with major retailers and financial institutions, and its adaptation to regulatory changes. It also highlights how Paytm leveraged technology and data analytics to enhance customer experience and streamline operations, contributing to its market dominance.Furthermore, the case study addresses the challenges faced by Paytm, including intense competition, regulatory hurdles, and the need for continuous innovation to maintain its competitive edge. By examining these aspects, the study provides insights into how Paytm's adaptive business model has enabled it to remain a leading player in India's digital ecosystem.The findings underscore the importance of flexibility and diversification in sustaining growth in the rapidly evolving digital services sector. This case study offers valuable lessons for other businesses seeking to navigate the dynamic landscape of digital transformation and innovation.

Mobile Apps for Vaccination Services: Content Analysis and Quality Assessment.

Vaccination services are increasingly in demand by the public, and mobile apps are an effective tool to meet that demand. However, the characteristics and quality of these apps are unknown. Commonly used vaccination service apps on the market were surveyed with regard to quality, service content, and user experience to evaluate and guide users. The Qimai Data mobile app data analytics platform was used to search for common vaccination service apps by keyword, and the WeChat and Alipay platforms were searched for apps. The apps included in the study were independently evaluated by two reviewers using the Mobile Application Rating Scale, and the service content and user experience of the apps were analyzed. The intragroup correlation coefficient between raters was used to measure interrater reliability. In the app stores of the four major Android platforms and the iOS app store, 1092 and 207 apps were found, respectively; 189 WeChat applets and 30 Alipay applets were also found. A total of 29 apps was ultimately included in this study according to the inclusion criteria, including 21 independent apps, 4 WeChat applets, and 4 Alipay applets. Significant differences were found between independent apps and applets in terms of the quality score (t449.57=-5.301; P<.001) and the subjective quality score (z=-4.753; P<.001). No significant differences were found between iOS and Android platforms in terms of the quality score (t1404=-2.55; P=.80) and the subjective quality score (z=-0.137; P=.89). There was good intragroup consistency among the raters. In this study, independent apps and nonindependent apps that rely on social and payment platforms for implementation were included in the vaccination services category. The overall quality of these apps was acceptable. Nonindependent running apps were found to have slightly lower scores and showed room for improvement, and scores for the participatory apps were found to be generally low overall.

Evaluating the Sabah Pay Mobile Application (e-Wallet) using the Technology Acceptance Model

The Sabah Pay e-wallet has been introduced as a digital payment solution in the state of Sabah, Malaysia, as part of a digital transformation initiative. However, there is a lack of comprehensive understanding regarding its user acceptance and the factors influencing it. Specifically, there is a need to investigate whether users perceive Sabah Pay as useful and easy to use. This research problem arises due to the importance of user acceptance in the success and sustainability of the e-wallet. Hence, we used the technology acceptance model (TAM) to analyse the perceived usefulness (PU) and customer satisfaction in using the Sabah Pay mobile application and the relationship between perceived ease of use (PEOU) and customer satisfaction using the Sabah Pay mobile application. The Cronbach's Alpha and composite reliability values are higher than 0.7, and the average variance extracted (AVE) is higher than 0.5, which supports the TAM constructs' convergence validity. The square root of AVE for each construct is higher than the corresponding correlations between constructs, which suggests the discriminant validity of the constructs. We used the Partial least squares structural equation modelling (PLS-SEM) to assess the data from the 173 respondents who reported using the Sabah Pay mobile application. We found that PU did not significantly affect customer satisfaction (CS), with a p-value of 0.207, although the path coefficient is 0.109, thus disproving the null hypothesis (H1). However, we supported the second hypothesis (H2) by observing that PEOU substantially impacted CS, with a p-value of 0.000 and a path coefficient of 0.614. The correlation indices demonstrated a satisfactory relationship between the data and the model. This research adds to the body of knowledge on mobile payment platforms by shedding light on perceived usefulness and ease of use factors that most affect users' happiness with Sabah Pay. The study suggests and identifies extensive research into potential customer satisfaction aspects like safety, trust, and value. This study's findings have real-world applications for practitioners and regulators looking to improve the mobile payment platform user experience and, by extension, boost customer happiness and adoption rates.

Evolution Of The Indian Digital Payment Ecosystem And Its Global Impact: A Comparative Analysis And The Role Of Microfinance

This research seeks to understand how the Indian digital payments landscape has evolved in the last decade and what is changing in the financial world at large scale because of it. Long leaps have been made in the Indian fintech space over the years, mainly from crucial government initiatives, technological innovations, and a growing user base depending on digital payment platforms. This paper also situates India as a leader in the world of fintech innovation and uses cross-national comparisons to explore economic and social impacts and the global consequences of India's digital payment model. The paper finds that in creating a model for digital payments, India has set global standards for the development of fintech while increasing domestic financial inclusion (Kanungo &amp; Gupta, 2021). It also tells the future trends and the prospect of India's digital payment ecosystem going global in influencing financial practices.

A Wasserstein distance-based spectral clustering method for transaction data analysis

With the rapid development of online payment platforms, it is now possible to record massive transaction data. Clustering on transaction data significantly contributes to analyzing merchants’ behavior patterns. This enables payment platforms to provide differentiated services or implement risk management strategies. However, traditional methods exploit transactions by generating low-dimensional features, leading to inevitable information loss. In this study, we use the empirical cumulative distribution of transactions to characterize merchants. We adopt Wasserstein distance to measure the dissimilarity between any two merchants and propose the Wasserstein-distance-based spectral clustering (WSC) approach. Based on the similarities between merchants’ transaction distributions, a graph of merchants is generated. Thus, we treat the clustering of merchants as a graph-cut problem and solve it under the framework of spectral clustering. To ensure feasibility of the proposed method on large-scale datasets with limited computational resources, we propose a subsampling method for WSC (SubWSC). The associated theoretical properties are investigated to verify the efficiency of the proposed approach. The simulations and empirical study demonstrate that the proposed method outperforms feature-based methods in finding behavior patterns of merchants.

Adoption Dynamics of Digital Payments: An Urban Case Study on E-Money Using the Technology Acceptance Model

The utilization of e-money in Indonesia has surged, propelled by the expansion of digital payment platforms. Despite their growing prevalence, the dynamics of e-money acceptance within urban environments remain underexplored. This study innovatively extends the Technology Acceptance Model (TAM) by incorporating Perceived Security as a new variable, alongside traditional factors such as Perceived Usefulness, Perceived Ease of Use, Attitude Toward Using, Behavioral Intention to Use, and Facilitating Condition. The research focuses on Padang City, a representative urban landscape, where data was collected from 201 valid respondents through online platforms. Data analysis was conducted using Partial Least Squares Structural Equation Modeling (PLS-SEM). The integration of Perceived Security is a novel aspect of this study, reflecting its crucial role in the contemporary urban context of e-money utilization. Results reveal significant relationships among the studied variables, although the impacts of Facilitating Condition on Perceived Ease of Use and Perceived Usefulness on Behavioral Intention to Use were not supported. The findings underscore that positive attitude toward e-money significantly boost behavioral intentions to use it, primarily influenced by security perceptions and ease of use. These insights have substantial implications for policymakers and businesses focused on enhancing e-money adoption in urban settings. The study highlights the necessity of addressing user perceptions, particularly security, to foster broader acceptance. The limited influence of Facilitating Conditions suggests that improvements in infrastructure must be coupled with efforts to enhance user trust and ease of interaction with e-money platforms. This research contributes to the field by providing a deeper understanding of the factors driving e-money acceptance in urban areas, guiding targeted strategies for digital financial inclusion.

The role of business analysts in driving financial inclusion through product innovation

Business analysts play a pivotal role in advancing financial inclusion by driving product innovation tailored to underserved and marginalized populations. Their involvement is crucial in identifying and addressing gaps in financial services, ensuring that products and solutions are designed to meet diverse needs effectively. This review explores the contributions of business analysts in promoting financial inclusion through innovative product development, emphasizing their impact on creating accessible, affordable, and user-centric financial solutions. In the context of financial inclusion, business analysts utilize data-driven insights and market research to identify barriers faced by underserved communities. By analyzing customer needs, behaviors, and preferences, they provide valuable input on designing products that cater to the specific requirements of these populations. Their expertise enables the development of financial products that are not only accessible but also affordable and inclusive, such as microloans, mobile banking solutions, and digital payment platforms. Business analysts also facilitate collaboration between various stakeholders, including financial institutions, technology providers, and regulatory bodies, to ensure that innovative solutions align with industry standards and regulations. They play a critical role in bridging the gap between technical teams and end-users, translating complex requirements into actionable product features and functionalities. Their work ensures that new financial products are user-friendly and capable of addressing the unique challenges faced by marginalized groups. Furthermore, business analysts contribute to ongoing product improvements by continuously gathering and analyzing user feedback. This iterative approach allows for the refinement of financial products, ensuring that they remain relevant and effective in promoting financial inclusion. By leveraging advanced analytics and emerging technologies, business analysts help in identifying new opportunities and optimizing existing solutions to enhance financial access and participation. In conclusion, business analysts are essential in driving financial inclusion through product innovation. Their role in understanding market needs, facilitating stakeholder collaboration, and ensuring continuous improvement is critical to developing financial products that are accessible, affordable, and inclusive. Their contributions help bridge financial gaps and promote equitable access to financial services. Keywords: Business Analysts, Financial Inclusion, Product Innovation, Market Research, Financial Products, Accessibility, User-Centric Solutions.

Generative AI in Fintech: Advancing Risk Assessment and Fraud Detection in Digital Payment Technologies

This article explores the transformative potential of artificial intelligence (AI), particularly generative AI, in enhancing risk assessment and fraud detection within digital payment technologies. As financial fraud evolves in sophistication, traditional detection methods often fall short. We propose a novel approach leveraging generative AI to create synthetic data that mimics real-world scenarios, thereby training more comprehensive and adaptive fraud detection models. This article addresses limitations in historical datasets, improves the accuracy of predictive models, and reduces false positives. Furthermore, we demonstrate how this approach enables proactive detection of emerging fraud trends, allowing fintech firms to stay ahead in the ongoing arms race against fraudsters. Our findings suggest that integrating generative AI into fraud detection systems can significantly enhance the security and reliability of digital payment platforms, potentially revolutionizing risk management in the fintech industry. This article contributes to the growing body of knowledge on AI applications in financial security and provides a foundation for future developments in this critical area.

Paths to digital mobile payment platforms acceptance and usage: A topology for digital enthusiast consumers

The rapid development of digital mobile payment platforms (DMPPs) has significantlytransformed the financial services landscape, offering consumers unparalleled convenience and efficiency in payment options. This study delves into the acceptance and usability factors among digital enthusiast consumers, employing fuzzy set Qualitative Comparative Analysis (fsQCA) to uncover key determinants. Analyzing data from 325 digital enthusiasts, the research identified four distinct configural paths that significantly influence DMPP usage, revealing two primary user typologies: “systems readiness and ease of use” and “affection and secured platforms.” Performance expectancy emerged as a core condition, highlighting its critical role in driving DMPP adoption among digital enthusiasts. The study also underscored the importance of grievance redress and perceived trust as essential conditions influencing user adoption and continuous usage, emphasizing their pivotal role in enhancing user experience and fostering trust. These insights suggest that addressing users' concerns and building trust are fundamental for the sustained success of DMPPs. By tailoring DMPP features to align with the distinct preferences of the identified user typologies, service providers can significantly boost adoption rates. The fsQCA approach offers novel insights into the nuances of emerging technology acceptance and usage, underscoring the necessity of categorizing users to better understand DMPP adoption dynamics. This research provides valuable contributions to both businesses and policymakers,offering strategies to optimize DMPP design, ensure superior user experiences, and promote broader adoption. The findings highlight the dynamic interplay of user expectations and technological capabilities, essential for navigating the evolving digital financial landscape.

UNRAVELLING THE DETERMINANTS OF SOCIAL MEDIA PAYMENT PLATFORM (SMPP) USAGE: A QUALITATIVE STUDY ON USER INTENTIONS AND ADOPTION

Lately, social media companies worldwide have introduced payment features on their social media platforms. This has given social media users the option to make payments to their near and dear ones without changing the platform while engaged in chatting. The adoption of Social Media Payment Platforms (SMPP) varies across user groups and is influenced by socio-demographic characteristics, convenience, and perceived risk. Understanding these factors is essential for enhancing user engagement and trust, thereby addressing the gaps in current SMPP adoption research. The purpose of this study is to ascertain the behavioural intention and perception level of users toward Social Media Payment Platforms (SMPP) adoption and to identify the factors which motivate and inhibit from using social payment apps. To understand the intention of the users to behave and adopt SMPP, we conducted in-depth structured interviews. Qualitative analysis was used to analyse the data, using pre-defined categories (deductive) and code emerging from the respondent discussions (inductively) to identify the relevant influencing factors. Through data analysis, we identified three key themes that categorised user behaviour: socio-demographic, convivence and vulnerability to risks, which is further divided into several sub-themes such as age, gender, education, occupation under socio-demographic, while perceived usefulness (PU) and perceived ease of use (PEOU) comes under the theme of convivence and lastly, under Vulnerability of risk includes privacy, security and platform features. The findings of the study can be validated and explored in future research, which will provide a clear understanding of identifying factors that influence SMPP adoption and behaviour intention.