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This paper aims at discussing the options available to governments when it comes to the use of technology to contain the spread of the COVID-19 virus.

This is an opinion piece, based on very recent developments (COVID-19), and based on a well-known trade-off between privacy and state surveillance, especially in times of crisis that threaten the survival of a nation.

The main finding is that technology alone will not help, and there are several reasons to doubt that the recently proposed European system to track the contagion in a privacy-preserving way (pan-European privacy preserving proximity tracing [PEPP-PT]) would be a fully effective solution.

This is a short paper, which is very dependent on current developments. It was written in a very short time, so the level of depth in the references to the literature and the caselaw is limited. The main implication is that this paper is very far from the final word in the analysis of the interplay between technology and society, especially in democratic countries.

There is a need to ensure that the temporary measures that will be adopted during the pandemic do not extend to the post-COVID-19 period.

To the best of the author’s knowledge, this is a very fresh debate; the paper is thus original and proposes one of the first structured comments to the PEPP-PT and DP-3T conceptual designs.

This study aims to examine the effectiveness of the debt modification system (DMS) in Korea. We find that DMS does have a positive effect in increasing the credit scores and annual income of DMS users. We also find that a debt management plan (DMP) is more effective in raising credit scores than personal rehabilitation (PR). However, the credit scores of DMS users in the first half of 2019 (551.1–626.1 points) are at a very low level, making it difficult to access low-interest unsecured loans from banks. Therefore, DMS in Kores is still insufficient to support the return of debt-ridden consumers to normal financial life and provide opportunities for a fresh start.

The purpose of this paper is to investigate whether religion or national culture can explain previously observed cross-country variation in trade credit.

Using the firm-level SME data from 35 European countries, religion and cultural factors of Hofstede and Schwartz, the authors provide new evidence on the determinants of the cross-country variation in trade credit.

The results indicate that religion and national culture are associated with trade credit. The authors find that the levels of trade credit are higher in Catholic countries than in Protestant ones and that peoples’ religiousness has an impact on trade credit only in Catholic countries. The authors also find that Hofstede’s cultural dimensions, such as power distance and uncertainty avoidance, are positively associated with trade credit.

Overall, authors’ findings indicate that religion and national culture are important determinants of trade credit management, and that the association between commonly used cultural values and trade credit depends on the religious, legal, and financial environment.

To the best of authors’ knowledge, this is the first study to research the relationship between national culture and trade credit.

This paper aims to present a literature review of the most recent optimisation methods applied to Credit Scoring Models (CSMs).

The research methodology employed technical procedures based on bibliographic and exploratory analyses. A traditional investigation was carried out using the Scopus, ScienceDirect and Web of Science databases. The papers selection and classification took place in three steps considering only studies in English language and published in electronic journals (from 2008 to 2022). The investigation led up to the selection of 46 publications (10 presenting literature reviews and 36 proposing CSMs).

The findings showed that CSMs are usually formulated using Financial Analysis, Machine Learning, Statistical Techniques, Operational Research and Data Mining Algorithms. The main databases used by the researchers were banks and the University of California, Irvine. The analyses identified 48 methods used by CSMs, the main ones being: Logistic Regression (13%), Naive Bayes (10%) and Artificial Neural Networks (7%). The authors conclude that advances in credit score studies will require new hybrid approaches capable of integrating Big Data and Deep Learning algorithms into CSMs. These algorithms should have practical issues considered consider practical issues for improving the level of adaptation and performance demanded for the CSMs.

The results of this study might provide considerable practical implications for the application of CSMs. As it was aimed to demonstrate the application of optimisation methods, it is highly considerable that legal and ethical issues should be better adapted to CSMs. It is also suggested improvement of studies focused on micro and small companies for sales in instalment plans and commercial credit through the improvement or new CSMs.

The economic reality surrounding credit granting has made risk management a complex decision-making issue increasingly supported by CSMs. Therefore, this paper satisfies an important gap in the literature to present an analysis of recent advances in optimisation methods applied to CSMs. The main contribution of this paper consists of presenting the evolution of the state of the art and future trends in studies aimed at proposing better CSMs.

Buying behavior has been significantly altered by technological developments as a result of the rise of the Internet. Online buying behavior is also inextricably linked to electronic payment systems, such as credit cards. This paper investigates how credit-card systems and online shopping increases compulsive buying of female and male consumers.

In the current study, the authors tested the influence of credit card possession and the role of Internet shopping on gender differences in compulsive buying in a representative German sample (n = 1,038). Binary logistic regression analysis and moderator analysis were applied.

As predicted, Internet shopping increased compulsive buying, but the association was the same for females and males. Further, credit card possession moderated the effect of gender on compulsive buying, with females showing a higher proneness to compulsive buying.

This research, which is based on a representative population study, contributes to the understanding of the role of credit cards and the one of online shopping in developing compulsive buying patterns among female and male consumers.

The purpose of this paper is to estimate the impact of credit rationing on the amount of capital allocated to inputs used by rice farmers in the Mekong River Delta (MRD).

Based on the literature review, the authors propose nine hypotheses on the determinants of access of rice farmers to credit and four hypotheses on the impact of credit rationing on the amount of capital allocated to inputs used by rice farmers in the MRD. Data were collected from 1,168 farmer households randomly selected out of 10 provinces (city) in the MRD.

Step 1 of propensity score matching (PSM) with probit regression shows that land value, income, education, gender of household head and geographical distance to the nearest credit institution affect the degree of credit rationing facing rice farmers. Step 2 of PSM estimator identifies that the amount of capital allocated to inputs such as fertilizer and hired labour increases when credit rationing decreases while that allocated to seed and pesticide is not influenced by credit rationing because rice farmers use these inputs adamantly regardless of effectiveness.

This paper sheds light on the impact of credit rationing on the amount of capital allocated to inputs used by rice farmers, which is largely different from the main focus of the extant literature just on the determinants of credit rationing facing farmers in general and rice farmers in particular.

The purpose of this paper is to evaluate the performance of Microfinance Institutions (MFIs) offering FinTech services. This study contributes to the existing literature on microfinance digitalization, financial inclusion and sustainable development. The study also takes into consideration a behavioral perspective through the efficiency evaluation process of MFIs offering FinTech services.

The following study employs the Stochastic Frontier Analysis approach to estimate the operational and social efficiency scores of the 387 MFIs over the period 2005–2019. Then, it tries to consider factors influencing MFIs' efficiency and assess their effects. Hence, two separate models for operation and social efficiency introducing a set of factors, including FinTech proxies and overconfidence proxies, are tested. The first model for operational efficiency uses a random-effects estimator while the second one for social efficiency uses a fixed-effects estimator.

The results show that innovative MFIs have weaker averages of operational efficiency than non-innovative ones but higher averages of social efficiency. This was justified by the fact that innovative MFIs are more socially oriented. Further, findings of this study depict that the proxies of FinTech affect negatively the level of operational efficiency of MFIs. They also depict a negative relationship between FinTech proxies and the level of social efficiency. These results hold through robustness tests.

The highlight of this study is that it takes heed of the indirect effect of technological innovation on the efficiency of MFIs. It has been proved that it moderates the impact of managerial overconfidence (manifested by excessive risk-taking, viz., high levels of PAR30, LGR and NIM) on the level of both operational and social efficiencies.

本文旨在對提供金融科技服務的微型金融機構的表現作出評價。我們的研究, 就現有之學術文獻而言, 在以下課題之探討上作出了貢獻: 微型金融的數字化、普惠金融、以及可持續發展。本研究亦以行為主義觀點, 對微型金融機構提供之金融科技服務的效率作出評價。

本研究使用隨機邊界分析法的理念, 去估計有關的387間微型金融機構於2005年至2019年期間、經營方面和社會方面的效率分數; 繼而嘗試找出影響微型金融機構效率的因素, 並評估這些因素的影響。為此目的, 研究人員分別測試兩個模型, 一個是探究運作方面的效率, 另一個則探究社會方面的效率。兩個模型內均放入一系列的因素, 其中包括金融科技代理和過度自信代理。探究運作方面的效率的模型使用了隨機效果估算器, 而探究社會方面的效率的模型則使用了固定效果估算器。

研究結果顯示、具創新精神的微型金融機構, 在運作方面的效率的平均值上,較沒具創新精神的為弱, 而社會方面的效率的平均值卻較高。這個結果是合理的, 因為具創新精神的微型金融機構會更著眼於社會。另外, 研究結果描繪了一個現象, 就是: 金融科技代理會對微型金融機構的運作效率水平產生負面影響; 我們也看到、金融科技代理與社會方面的效率水平之間的關聯是負面的; 這些研究結果、均通過穩健性檢驗。

本研究最突出之處為研究人員關注科技之創新會間接影響微型金融機構的效率。研究人員證明了於微型金融機構整合金融科技服務是會緩和管理上的過度自信給運作和社會兩方面的效率水平帶來的影響 (管理上的過度自信、顯露於過度的風險承擔, 即是, PAR30(貸款組合風險-30日)、LGR(貸款增長率) 和NIM(淨息差) 處於高水平)。