Third-party Payment Platform Research Articles

Factors that affect individuals in using digital currency electronic payment In China: SEM and fsQCA approaches

While China's Central Bank digital currency electronic payment (DCEP) presents certain advantages over third-party payment platforms like WeChat and Alipay, its promotion faces bottlenecks and research gaps. This study employs the Unified Theory of Acceptance and Use of Technology (UTAUT) to construct a research model that identifies the various factors influencing individual adoption of DCEP. By gathering 401 surveys, this study validates the hypotheses and relationships between variables using the Structural Equation Model (SEM). Additionally, it employs the fuzzy set Qualitative Comparative Analysis (fsQCA) method to explore the factors that impact adoption intention. The SEM results reveal that perceived security, perceived usefulness, and comparative advantage significantly and positively influence the willingness to use DCEP, while perceived security and perceived usefulness also positively influence comparative advantage. Furthermore, the study finds that comparative advantage serves as an intermediary in the relationships between perceived security and usage intention, perceived security and usage intention, and perceived usefulness and usage intention. Interestingly, the fsQCA analysis reveals that privacy concerns, while commonly regarded as an important factor in affecting electronic payments, did not significantly impact usage intention in the SEM analysis. However, combining privacy concerns with other variables significantly influences usage intention. This study suggests that the analysis of factors influencing DCEP usage should be wider than single-factor analysis and account for the effects of multiple-factor combinations.

Application of SOM-GAN based deep learning technology in the security protection of rural bank depositors' funds information

Since the reform and opening up, the status of China's banking industry has been significantly improved, and the traditional banking industry has gradually cross-integrated with Internet technology [1], which has become an important support for national economic development and a core component of the financial system. For example, in the original physical bank and online bank, new Internet financial models have been expanded, such as online financial management, bank electronic accounts, mobile banking, P2P models, third-party payment platforms, crowdfunding, etc. [2]. However, in the period of rapid development of the transformation and upgrading of traditional banks facilitated by information technology, many problems have emerged, such as the relaxation of supervision, the lag of policies and regulations, and the difficulty of reasonable protection of private data, etc. These problems may affect the interests of depositors and even the state. For example, in 2022, China's Henan rural bank 40 billion event, this event involved about 400,000 depositors, and platforms such as Du Xiaoman and Xiaomi Finance have related cooperation with these rural banks. Therefore, reasonable security protection of depositors' fund information and information processing and encryption under certain deep learning technology have long become the focus of experts' research in information technology. For example, Tian Gengwen has conducted an in-depth discussion on customer information security in the digital transformation of banks [3]. For example, Yang Wanrong conducted an in-depth study on the path and measures of data security governance of small and medium-sized banks [4]. For example, Zhang Wenli, Peng Xiaolei et al have made an in-depth elaboration on the bank data security solution [5]. Following hot issues closely, this paper provides a method of deep learning technology based on SOM-GAN in the security protection of rural bank depositors' funds information, aiming to combine the advantages of self-organizing mapping neural network and generative adantagonistic network unsupervised learning. At the same time, it can complement the competition mode of self-organized neural network, generate the discriminant characteristics of adversarial network and generate real data to process and review the relevant data of the fund information security of rural bank depositors, ensure the fund management security of rural bank depositors, and realize the monitoring and analysis of their funds and the surrounding environment when depositors are storing funds. Thus, the security, confidentiality, authenticity and integrity of depositors' funds information are guaranteed, and hidden dangers such as theft of depositors' funds, loss of depositors' personal information and threats to depositors' personal information security brought about by the 40bn deposit red code incident of Henan Bank in 2022 are eliminated.

Luckin Coffees Digital Transformation: Case Study on the Impact of Digitization in the Coffee Industry

This paper examines the impact of digitalization on corporate competitiveness and analyses the digital transformation strategy and implications of the Chinese coffee chain Luckin Coffee as an example. The business model of Luckin Coffee is a new retail model based on new technology. Services are delivered through a mobile app and a network of shops, and goods are sold through third-party digital payment platforms or coupons purchased within the Luckin app, for example. Luckin Coffee's mobile app provides end-to-end customer service, including marketing, customer acquisition, customer management, and billing processes. The research in this paper finds that Luckin Coffee has successfully rebuilt its brand reputation through digital transformation, which has implications for the digital transformation of companies, and that other companies can learn from Luckin Coffee's marketing model and create their own unique and efficient operational models. However, there are some limitations to this paper's research. Companies should improve their digital transformation strategies according to their circumstances and pay more attention to the importance of digital transformation for competitiveness.

The Impacts and Measures of Third Party Platform on High School Students’ Consumer Behavior

In recent years, with the development of Internet finance in China, crowdfunding, p2p, digital currency and other financial models have gradually emerged. As a method of Internet finance, third-party payment has gradually developed more and more, and the payment methods of online banking and electronic credit cards are weakening. From the initial use of coin payment to the emergence of a series of third-party payment platforms similar to Alipay and WeChat. This brand-new consumption method has gradually taken root in people's hearts. Moreover, as high school students, we are in the initial maturity stage of physical and mental development, and there are still many gaps in some consumption behaviors, so we have been greatly affected by third-party payments in the context of Internet finance. In this work, I will talk about the impact of third-party payment platforms on the consumption behavior of high school students.

Analysis of the Marketing Strategy of Alipay Payment Method under the Internet Economy

With the rapid development of mobile payment, third-party payment platforms as well as payment services continue to innovate. The emerging payment methods have not only changed consumers' daily life, but also cultivated their consumption habits. More and more domestic and foreign companies are joining the market competition. Facing the complex market environment, how to seize the market becomes the goal of all companies. The Alipay platform stands out among many third-party payment platforms and has become the largest mobile vendor in the world. The research theme of this paper is to study the marketing strategy of Alipay, and to analyze the existing marketing problems of Alipay and to suggest solutions. This paper is based on the theories of mobile payment, marketing strategy, and user stickiness, and the current situation of Alipay to analyze the marketing strategy. Through extensive literature reading and data compilation, Alipay's marketing strategy is divided into six aspects: living payment ecosystem, fun marketing, cash withdrawal exemption, unique business, monopoly exclusivity, and transaction security. Finally, based on the above analysis, this paper makes three suggestions on how to improve Alipay's marketing strategy: strengthen the publicity work to make more consumers use Alipay with peace of mind; carry out market segmentation and provide personalized service to customers; improve product competitiveness and create brand effect.

Research on Price Influencing Factors of Third-Party Payment Platforms: An Empirical Study From China.

In this article, we use the two-sided market theory as a support and take the operating data of eight Chinese third-party payment platform companies as samples, based on pricing models and multiple regression analysis, to build a price feature model for a third-party payment platform. The results show that under the two-sided market environment, the scale of consumer and the same-side network externality of the merchant have a negative significant effect on the pricing of the third-party payment platform to the seller; The market share of the platform and the bank fee cost of the platform have a positive significant effect on the pricing of a third-party payment platform to the merchant. At the same time, the same-side network externality of the seller, the scale of a merchant, and the selection of the business model of the platform have no significant effect on the pricing of the third-party payment platform to the merchant. These conclusions provide a scientific basis for a third-party payment platform enterprise to develop an appropriate pricing strategy and operating model.

Anti-monopoly supervision model of platform economy based on big data and sentiment.

With the advent of the cloud computing era, big data technology has also developed rapidly. Due to the huge volume, variety, fast processing speed and low value density of big data, traditional data storage, extraction, transformation and analysis technologies are not suitable, so new solutions for big data application technologies are needed. However, with the development of economic theory and the practice of market economy, some links in the industrial chain of natural monopoly industries already have a certain degree of competitiveness. In this context, the article conducts a research on the anti-monopoly supervision mode of platform economy based on big data and sentiment analysis. This paper introduces the main idea of MapReduce, the current software implementation specifies a Map function that maps a set of key-value pairs into a new set of key-value pairs. It specifies a concurrent Reduce function that guarantees that each of all mapped key-value pairs share the same set of keys. establishes a vector space model, and basically realizes the extraction of text emotional elements. It introduces the theoretical controversy of antitrust regulation of predatory pricing behavior of third-party payment platforms, and conducted model experiments. The experimental results show that the throughput of 40 test users in 1 h of test is determined by two factors, QPS and the number of concurrent, where QPS = 40/(60*60) transactions/second. The time for each test user to log in to the system is 10 min, and the average response time is 10*60 s, then the number of concurrency = QPS*average response time = 40/(60*60)*10*60 = 6.66. This paper has successfully completed the research on the anti-monopoly supervision model of platform economy based on big data and sentiment analysis.

Impact of the Internet finance on Small and Medium Enterprises Financing under Big Data evolution

Internet financial model innovation is mainly reflected in big data Internet financial companies, third-party payment platforms, Peer-to-Peer Internet lending platforms, crowdfunding Internet financing platforms, etc. platform and Internet financial portal platform. The impact of Internet finance on the financing of Small and medium-sized enterprises is mainly reflected in four aspects: that is, the mechanism of reversal of traditional financial institutions; the financing objects of Small and medium-sized enterprises More comprehensive and scientific; financing services for Small and medium-sized enterprises are more targeted; financing costs for Small and medium-sized enterprises have dropped significantly.

Operational risk assessment of third-party payment platforms: a case study of China

Operational risk events have severely impacted the development of third-party payment (TPP) platforms, and have even led to a discussion on the operational risk capital charge settlement by relevant international regulators. However, prior studies have mostly focused on qualitative mechanism analysis, and have rarely examined quantitative risk assessment based on actual operational risk events. Therefore, this study attempts to assess the operational risk on TPP platforms in China by constructing a systematic framework incorporating database construction and risk modeling. First, the operational risk database that covers 202 events between Q1, 2014, and Q2, 2020 is constructed. Then, specific causes are clarified, and the characteristics are analyzed from both the trend and loss severity perspectives. Finally, the piecewise-defined severity distribution based-Loss Distribution Approach (PSD-LDA) with double truncation is utilized to assess the operational risk. Two main conclusions are drawn from the empirical analysis. First, legal risk and external fraud risk are the two main causes of operational risk. Second, the yearly Value at Risk and Expected Shortfall are 724.46 million yuan and 1081.98 million yuan under the 99.9% significance level, respectively. Our results are beneficial for both TPP platform operators and regulators in managing and controlling operational risk.

Study on Competition Status and Development of Electronic Payment

Since Taobao launched Alipay service in 2013, third-party payment platforms have begun to approach social life. In addition to the basic payment function at the beginning of development, third-party platforms led by Alipay and WeChat have diversified. With various consumption scenes as media, it has created huge economic and social benefits. At present, the third-party payment market has been basically stable, and the two giants jointly monopolize nearly 95% of the market share. WeChat and Alipay give full play to their own strengths, learn from each other's successful experience, and form a temporary balance in the game. However, there are many uncertainties in the seemingly balanced pattern. First, Apple Pay is trying to leverage the market with its user-friendliness and security advantages, with its built-in "Apple fans" and NFC near-field payment technology. Second, the central bank's upcoming launch of the digital RENMINBI also brings more uncertainty: legal digital currency may open up a new blue ocean market, enabling small and medium-sized third-party payment companies to seize the market and dilute the current monopoly. Based on the characteristics of WeChat, Alipay, Apple Pay and the digital currency of the Central Bank, this paper makes a comparative analysis of their competitive advantages, so as to predict the future trend of the third-party payment market and provide feasible suggestions for the transformation of WeChat and Alipay.

GNFCVulFinder: NDEF Vulnerability Discovering for NFC-Enabled Smart Mobile Devices Based on Fuzzing

Near-field communication (NFC) is a set of communication protocols that enable two electronic devices. Its security and reliability are welcomed by mobile terminal manufactures, banks, telecom operators, and third-party payment platforms. Simultaneously, it has also drawn more and more attention from hackers and attackers, and NFC-enabled devices are facing increasing threats. To improve the security of the NFC technology, the paper studied the technology of discovering security vulnerabilities of NFC Data Exchange Format (NDEF), the most important data transmission protocol. In the paper, we proposed an algorithm, GTCT (General Test Case Construction and Test), based on fuzzing to construct test cases and test the NDEF protocol. GTCT adopts four strategies to construct test cases, manual, generation, mutation, and “reverse analysis,” which can detect logic vulnerabilities that fuzzing cannot find and improve the detection rate. Based on GTCT, we designed an NDEF vulnerability discovering framework and developed a tool named “GNFCVulFinder” (General NFC Vulnerability Finder). By testing 33 NFC system services and applications on Android and Windows Phones, we found eight vulnerabilities, including DoS vulnerabilities of NFC service, logic vulnerabilities about opening Bluetooth/Wi-Fi/torch, design flaws about the black screen, and DoS of NFC applications. Finally, we give some security suggestions for the developer to enhance the security of NFC.

Financial Innovation in Digital Payment with WeChat towards Electronic Business Success

Financial innovation and advances in payment systems are important not only to boost remittances but also to foster the successful development of electronic businesses around the world. As such, many leading companies in electronic commerce are putting a great deal of effort into the development of their payment system to attract more users and compete with other leading companies in the market. WeChat is a social communication tool that introduced a payment function widely adopted as a third-party payment in China nowadays. The purpose of this study was to adopt WeChat as a case study to identify the influential factors that impact consumers’ intention to adopt it as digital payment. We identified several core influential factors including service quality, perceived risk, perceived security, perceived ease of use, social influence, compatibility, and age. Qualitative and quantitative analyses were performed to investigate how influential factors affect the adoption of this third-party digital payment platform. The results revealed that all identified factors have a significant influence on consumer’s intention to use digital payment, except age. This study also provided useful advice for digital payment improvement and recommendations to enhance digital payment for the success of electronic business operations. The paper provides new insight into the factors influencing consumers’ intention to use mobile digital payment.

Clustering Based on Kolmogorov–Smirnov Statistic with Application to Bank Card Transaction Data

Abstract Rapid developments in third-party online payment platforms now make it possible to record massive bank card transaction data. Clustering on such transaction data is of great importance for the analysis of merchant behaviours. However, traditional methods based on generated features inevitably lead to much loss of information. To make better use of bank card transaction data, this study investigates the possibility of using the empirical cumulative distribution of transaction amounts. As the distance between two merchants can be measured using the two-sample Kolmogorov–Smirnov test statistic, we propose the Kolmogorov–Smirnov K-means clustering approach based on this distance measure. An approximation step is conducted to ensure the feasibility of the proposed method even for large-scale transaction data, and the associated theoretical properties are investigated. Both simulations and an empirical study demonstrate that our method outperforms feature-based methods and is computationally efficient for large-scale data sets.

An Empirical Analysis to Understand Consumer Intention to Use Mobile Payment Platform: The Mediating Role of Trust

Purpose: Money transfer through third-party mobile payment platforms has become common nowadays in western countries. While in developing countries, the adoption of mobile payment channels still at the infancy stage. The current study based on diffusion of innovation theory investigates the antecedents of intention to use mobile payment channels through trust's mediating role.
 Methodology: The survey method was used to collect data from the 250 consumers using the mobile payments services of JazzCash and Easypaisa in Pakistan. Partial least square structural equation modeling (PLS-SEM) technique employed to test the collected data statistically.
 Findings: Results found the significant impact of mobility, customization, and security on trust that intends to utilize mobile-payment channels.
 Implications: The current study's findings provide guidelines to the administration of mobile payment systems to improve security features, mobility, and customization that wins customers' trust and is inclined to use mobile payment platform.

Discussion on Payment Application in Cross-border E-Commerce Platform from the Perspective of Blockchain

Features like the distributed ledger, consensus mechanism, asymmetric encryption technology, smart contract and Token of blockchain can lower transaction cost, enhance trust between customers and merchants, as well as eliminate false payment and consumer information leakage, problems which are common in current payment of cross-border E-Commerce platform. Based on the analysis of existing scholars, this paper studied two payment models: digital cash payment based on blockchain technology and the application of blockchain in third-party payment platform. Then the paper discussed the mechanism of blockchain in cross-border e-commerce payment platform, and creatively proposed a blockchain cross-border e-commerce payment platform, serving as reference and guidance for further development of blockchain technology in cross-border payment.1

A Dynamic Data Slice Approach to the Vulnerability Analysis of E-Commerce Systems

The e-commerce business process net (EBPN) is a novel formal model for describing an e-commerce system and its interactive parts, such as shoppers, merchants, and the third-party payment platforms. Vulnerability analysis has a great impact on the trustworthiness of EBPN, which is an issue stemming from data inconsistency problems. Data inconsistency problems affect the consistency of the EBPN transaction analysis. The underlying causes of inconsistent data are closely related to concurrent operations, such as control flow and data flow. However, most of the existing detection methods have difficulties characterizing the vulnerabilities and interactions of control and data flows. In this paper, we propose a new method based on the dynamic data slice (DDS) that considers both transaction consistency and data state consistency. First, by analyzing control flow characteristics of EBPN, we obtain the dynamic slice. This dynamic slice is based on all paths of the EBPN reachability graph. Second, we perform the data inconsistency analysis by considering both transaction consistency and data-state consistency. Based on these, we construct a DDS to characterize the behavioral logic and the data-dependence information. The DDS acquires the dynamic data firing sequence. Based on that sequence and a given data marking, we can construct the DDSs for several types of EBPNs. Constructing the DDS can be completed in polynomial time. The DDS is designed to characterize the behavioral logic and data-dependence information. Based on these, we design a method to judge the data constraints. This method satisfies the EBPN need for transaction consistency by considering both the control and data states. In addition, according to the data-dependence information, we can lock the vulnerable regions caused by abnormal trading data in the system. Finally, we give a method to compute the vulnerability level.

Mobile payment, third-party payment platform entry and information sharing in supply chains.

With the development of information technology, increasing retailers cooperate with third-party payment platforms (3PPs) to provide mobile payment service for consumers. The entry of 3PPs into supply chains, not only changes the cash flow, but also decreases consumer price sensitivity and stimulates demand by facilitating credit consumptions. Moreover, information sharing becomes more feasible with the help of 3PPs. To study the impacts of 3PP entry, we build game-theoretic models in a supply chain consisting of a manufacturer, a retailer and a 3PP, and derive the equilibrium in both the non-information sharing and information sharing cases. We show that the 3PP should make a reasonable commission rate which can lure the retailer to introduce the 3PP as well as maintain the 3PP’s profitability. The 3PP entry allows the retailer to set a higher price without decreasing the demand. However, to seize all of the benefit of the 3PP entry, the first mover manufacturer increases the wholesale price to a large extent. As a result, the 3PP entry causes a win-lose situation for the manufacturer and the retailer. The supply chain can be better off from the 3PP entry if it can significantly decrease consumer price sensitivity or its fixed investment cost is low. Furthermore, we find that information sharing benefits the manufacturer and the 3PP but harms the retailer. While information sharing always decreases the expected profit for the supply chain without the 3PP, it may increase that for the supply chain with the 3PP. To improve the supply chain profitability, we suggest to provide incentives for retailer information sharing if the 3PP can significantly decrease consumer price sensitivity (i.e., the proportion of the 3PP users is higher, the grace period of credit consumption is lower, or the cash opportunity cost is lower).

Implementation of an E-Payment Security Evaluation System Based on Quantum Blind Computing

E-payment has gradually become the mainstream globally in recent years. However, the security and anonymity of the traditional E-payment system are not perfectly guaranteed with the emergence of the quantum computer. In this paper, an E-payment security evaluation system based on quantum blind computing is proposed for evaluating the security of network transactions. Unitary operations and four-qubit cluster state are applied in this system to effectively defend against eavesdroppers. And a shared blind matrix used to encrypt the security scores prevents the curious third-party payment platform from obtaining the private data of users. Furthermore, our system guarantees that users cannot tamper with or disguise their security scores during transactions. We demonstrate the correctness and security of the system in detail and provide theoretical support for its extension to more types of evaluation systems.

New normal and new economy: a new growth engine for China

As the economy stepped into the “new normal,” the Chinese government has implemented various policies to transform its economic development model to pursue an innovation-driven growth. Against this background, the most innovating field is the Internet-based “new economy.” A major feature of the Chinese new economy is that it is based on a new payment system. Various new businesses have been developed owing to third-party payment platforms (particularly Alibaba's Alipay and Tencent's WeChat Pay) and a vast ecosystem has been created around them. Moreover, the development of the Chinese new economy is helping to expand consumer spending and is becoming a new economic growth engine.

Research on brush face payment system based on internet artificial intelligence

The facial information of a person has constant invariance, and at the same time, it is an ideal basis for identifying identity information through differences between different individuals. The use of face recognition in third-party payment platforms will greatly improve the efficiency and securit y of payment. Based on this, the paper studies and designs the third-party payment system for face recognition in the context of Internet artificial intelligence to improve the convenience and security of face payment.