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The purpose of this study is to examine the effect and influence of perceived usefulness and perceived ease of use on knowledge sharing to improve and use Islamic credit cards.

Structural equation modeling was used in the analysis of the data collected from 160 respondents in four cities in Jakarta, Indonesia, using an online survey.

This study analyzes the effect of perceived usefulness and perceived ease of use on knowledge management, and also analyzes the effect of increasing knowledge management in increasing Islamic credit card users, as well as the role of knowledge management as mediation.

This study only examines Islamic credit cards by looking at the contribution of the role of perceived usefulness and perceived ease of use knowledge management that are felt by users and prospective users of Islamic credit cards.

The results of this study highlight the need for Islamic banks to provide and increase knowledge to understand and know well about Islamic credit cards, which can increase intentions to become new users.

This research provides additional knowledge on Islamic credit cards, commonly referred to as bithaqah al-l’timan, as a means of payment and cash withdrawals in accordance with applicable regulations with reference to Islamic principles and policies by providing convenience, security and comfort for credit card users and for bank customers. Sharia banking can also grow the sharia economy, which currently Indonesia is still far behind.

The authors estimate the determinants of the value of purchases of semi-durable goods using permanent and transitory income, and the demographic characteristics of customers. The purpose is to identify whether individuals face remaining liquidity constraints, and how this friction affects their purchases.

This study uses anonymized data of 516,525 credit card holders, with more than 7,501,065 records of purchases between 2010 and 2015. The authors decompose the income of individuals into permanent and transitory components to test the prevalence of the life cycle–permanent income hypothesis (LC–PIH). Determinants of the value of purchases for constrained and unconstrained consumers are estimated, considering the period in which individual characteristics are valid, the decisions not to make purchases in some months, and the potential endogeneity of the interest rate and the transitory component of income.

The authors present evidence of liquidity constraints for individuals who have used a high percentage of the credit limit on their cards. For these restricted customers, the value of purchases is inelastic to the interest rate, whereas the response is sizable for customers who are less restricted. The restricted customers increase the value of purchases when faced with increases in their credit limit. The elasticity of the value of purchases of semi-durable goods to permanent income is less than that for transitory income; regardless of the constraints, this still supports the LC–PIH.

This credit card is targeted at low- and middle-income individuals in Bogotá. Although the results might be considered as indicative of the behavior of those with similar characteristics in Colombia, the authors regard this work as the study of a particular case. A limitation of this work is that the authors do not have alternative sources of credit at an individual level.

The broad credit channel of monetary policy does not apply to the restricted customers. This should be considered not only by the monetary authority, to understand the true extent of this policy, but also by the financial institutions that use this business model. The monetary authority should be cautious not to overreact when intervening in the money market to try to prompt an adequate consumer response.

Financial institutions have the policy of modifying the credit limits of their customers' credit cards which affects the well-being of restricted customers. Given that the card is aimed at low and middle income individuals, the credit limits of customers who use a high percentage of their credit limit might be increased.

This is the first paper to study liquidity restrictions with a retail credit card in Colombia and Latin America using information on customers' characteristics. The results are highly relevant for the implementation of monetary policy.

Under the background of low consumer financial knowledge and accumulated credit card liabilities, this study investigates the relationship between financial knowledge and responsible credit card behavior using data from the 2019 China Household Finance Survey (CHFS). From the perspective of consumer economic well-being, this study defines accruing credit card debt to buy houses and cars when loans with lower interest rates are available as irresponsible credit card behavior.

This study uses probit regressions to examine the association between financial knowledge and responsible credit card behavior because the dependent variable is a dummy variable. To alleviate endogeneity problems, this study uses instrument variables and Heckman’s two-step estimation. Furthermore, to explore the potential mediators in this process, this study follows the stepwise regression method. Finally, this study introduces interaction terms to examine whether this association differs in different groups.

The results indicate that financial knowledge is conducive to increasing the probability of responsible credit card behavior. Mediating analyses reveal that the roles of financial knowledge occur by increasing the degree of concern for financial and economic information and the propensity to plan. Moderating analyses show that the effects of financial knowledge on responsible credit card behavior are stronger among risk-averse consumers and in regions with favorable digital access.

This study measures responsible credit card behavior from the perspective of the consumer’s well-being, which enriches practical implications for consumer finance. Furthermore, this study explores the potential mediators influencing the process of financial knowledge that affects responsible credit card behavior and identifies moderators to conduct heterogeneous analyses, which helps comprehensively understand the nexus between financial knowledge and credit card behavior. By achieving these contributions, this study helps to curb the adverse effects of irresponsible credit card behavior on consumers’ well-being and the economic system and helps policymakers promote financial knowledge to fully prevent irresponsible credit card behavior.

The current approach to valuing customers is based on the notion of discounted profit generated by the customers over the lifetime of the relationship, also known as customer lifetime value (CLV). However, in the financial services industry, the customers who contribute the most to the profitability of a firm are also the riskiest customers. If the riskiness of a customer is not considered, firms will overestimate the true value of that customer. This paper proposes a methodology to adjust CLV for different types of risk factors and creates a comprehensive measure of risk-adjusted lifetime value (RALTV).

Using data from a major credit card company, we develop a measure of risk adjusted lifetime value (RALTV) that accounts for diverse types of customer risks. The model is estimated using Stochastic Frontier Analysis (SFA).

Major findings indicate that rewards cardholders and affinity cardholders tend to score higher within the RALTV framework than non-rewards cardholders and non-affinity cardholders, respectively. Among the four different modes of acquisition, the Internet generates the highest RALTV, followed by direct mail.

This paper not only controls for different types of consumer risks in the financial industry and creates a comprehensive risk-adjusted lifetime value (RALTV) model but also shows empirically the value of using RALTV over CLV for predicting future performance of a set of customers. Further, we investigate the impact of a firm’s acquisition and retention strategies on RALTV. The measure of risk-adjusted lifetime value is invaluable for managers in financial services.

Despite evidence that cashless payment modes influence spending behavior, researchers have yet to explain the underlying mechanism. Cash serves as a store of value, and transactions involve the transference of ownership in circulation. This study aims to unpack why the physical and visceral nature of cash embodies psychological ownership and how the physicality of cash attenuates the awareness of spending, curtailing instinctive and unnecessary spending.

Drawing on data collected in 2013 in New Zealand, the authors conducted another study in the quite different context of China in September 2023, using identical semistructured discussion protocols. The data from 2013 involved five focus group sessions containing at least six participants, involving 31 adults who also completed an open-ended questionnaire immediately before the group discussion commenced. The data collection in 2023 used the same open-ended and semistructured discussion protocol used in 2013, resulting in 180 adult open-ended responses – a nonprobability criterion-based purposive sampling guided participant selection in the 2013 and 2023 studies.

Findings reveal that psychological ownership does manifest in the app more than in the ownership of money itself. People felt happy, confident, safe and secure while using apps that stored their money. Physical attributes of cash result from sensory perceptions of handling, counting and touching cash and coins. A sense of psychological ownership heightens spending awareness and ramifies spending behavior. The research found sadness and guilt as negative emotions when parting with money.

This study offers empirical support to explain why psychological ownership of cash regulates spending and why the psychological processes that underlie “owned” money interrupt the spending with cash.

In the past three decades, the expansion of Islamic banking has been recognized as one of the most significant financial developments across the world, and to enhance their market share in the highly competitive global banking market, these Islamic banking institutions must continue to be innovative. Credit cards are popularized worldwide; developing countries are also intrinsically motivated to adopt this product for performing financial transactions; however, understanding the factors influencing Islamic credit card (ICC) adoption remains limited, and the ICC still needs to attain adequate market share in the banking sector. Therefore, this study aims to investigate the determinants of ICC in Pakistan.

For empirical estimation, sample data from 499 respondents, including ICC users and individuals willing to use ICC, is utilized through partial least square structural equation modeling.

The results show that attitude, compatibility, perceived behavioral control and religiosity are positive, while complexity negatively affects ICC adoption. In contrast, social influence, trust and satisfaction are insignificant determinants of ICC’s intention to use in Pakistan.

As a banking service, ICCs are viewed as a new banking product in Pakistan and have limited scope in the literature. Therefore, this study contributes to the existing literature by providing more integrating policy insights to academians and banking managers on ICC service in Pakistan.

This study aims to develop a novel approach for predicting default risk in bancassurance, which plays a crucial role in the relationship between interest rates in banks and premium rates in insurance companies. The proposed method aims to improve default risk predictions and assist with client segmentation in the banking system.

This research introduces the group method of data handling (GMDH) technique and a diversified classifier ensemble based on GMDH (dce-GMDH) for predicting default risk. The data set comprises information from 30,000 credit card clients of a large bank in Taiwan, with the output variable being a dummy variable distinguishing between default risk (0) and non-default risk (1), whereas the input variables comprise 23 distinct features characterizing each customer.

The results of this study show promising outcomes, highlighting the usefulness of the proposed technique for bancassurance and client segmentation. Remarkably, the dce-GMDH model consistently outperforms the conventional GMDH model, demonstrating its superiority in predicting default risk based on various error criteria.

This study presents a unique approach to predicting default risk in bancassurance by using the GMDH and dce-GMDH neural network models. The proposed method offers a valuable contribution to the field by showcasing improved accuracy and enhanced applicability within the banking sector, offering valuable insights and potential avenues for further exploration.

With the rapid growth of the domestic lending industry, assessing whether the borrower of each loan is at risk of default is a pressing issue for financial institutions. Although there are some models that can handle such problems well, there are still some shortcomings in some aspects. The purpose of this paper is to improve the accuracy of credit assessment models.

In this paper, three different stages are used to improve the classification performance of LSTM, so that financial institutions can more accurately identify borrowers at risk of default. The first approach is to use the K-Means-SMOTE algorithm to eliminate the imbalance within the class. In the second step, ResNet is used for feature extraction, and then two-layer LSTM is used for learning to strengthen the ability of neural networks to mine and utilize deep information. Finally, the model performance is improved by using the IDWPSO algorithm for optimization when debugging the neural network.

On two unbalanced datasets (category ratios of 700:1 and 3:1 respectively), the multi-stage improved model was compared with ten other models using accuracy, precision, specificity, recall, G-measure, F-measure and the nonparametric Wilcoxon test. It was demonstrated that the multi-stage improved model showed a more significant advantage in evaluating the imbalanced credit dataset.

In this paper, the parameters of the ResNet-LSTM hybrid neural network, which can fully mine and utilize the deep information, are tuned by an innovative intelligent optimization algorithm to strengthen the classification performance of the model.

This study aims to establish that the relationship between the risky indebtedness behavior (RIB) of consumers and their attitude toward adopting buy-now-pay-later (BNPL) is not immediate but is mediated through impulse buying. Moreover, it explores how perceived risk moderates the association between the attitude to adopt BNPL and its adoption intention.

This study used the existing theoretical and empirical evidence to propose a model and validated it using the data collected from 339 young shoppers in India. Analysis of data is conducted using partial least squares structural equation modeling.

The study results show that consumers’ RIB is not directly related to their attitude toward BNPL. However, impulse buying fully mediates this relationship, influencing the attitude toward BNPL. Impulse buying and attitude serially mediate the relationship between RIB and BNPL adoption intention. Further, in the context of BNPL, perceived risk strengthens the attitude-intention gap.

This study advises policymakers and BNPL providers to carefully assess users’ creditworthiness to prevent those already in debt from entering into a detrimental loop.

This study provides novel perspectives on consumer’s RIB and BNPL within the Indian context. The study additionally identifies the mediating influence of impulse buying and the moderating effect of perceived risk on BNPL adoption intention.

This paper aims to understand if buy-now-pay-later (BNPL) services, a digital type of credit that targets young consumers, acts as a protective or a risk factor for food insecurity among young consumers in Australia.

The study uses survey data from a representative sample of young consumers aged 18–24 from all internal states and territories in Australia. Propensity score matching is used to test two hypotheses: BNPL drives young consumers to food insecurity, and food insecurity leads young consumers to use BNPL.

There is evidence that BNPL use is driving young Australian consumers to experience food insecurity, but there is no evidence of food insecurity driving the use of BNPL services.

The evidence of BNPL driving young consumers to experience food insecurity calls for the adoption of practices and stronger regulation to ensure that young users from being overindebted.

Although the link with more traditional forms of credit (such as personal loans) and consumer wellbeing has been explored more broadly, this project is the first attempt to have causal evidence of the link between BNPL and food insecurity in a high-income country, to the best of the authors’ knowledge. This evidence helps to fill the gap about the protective or risky nature of this type of digital financial product, as experienced by young Australians.