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This study aims to examine the relationship between financial inclusion, CO₂ emissions and financial sustainability across 17 African countries.

Data were sourced from the World Development Indicators for the period 2004-2021. The study performs the principal component analysis, panel fixed effects model and quantile regression estimations to investigate the relationship between financial inclusion, CO₂ emissions and financial sustainability.

The study finds that an increase in automated teller machine (ATM) penetration rate, savings and credits increases CO₂ emissions. Findings also reveal that financial sustainability reduces financial inclusion, with significant negative effects on the conditional mean of CO₂ emissions and the conditional distribution of CO₂ emissions across quantiles.

This study is beneficial for policymakers, particularly in the age of digitalization and drive for low-carbon emissions, to develop green credits for energy players and investors to take up renewable and green energy projects characterized by high levels of carbon storage and carbon capture. Further, the banking sector’s credits and liquid assets should be used to finance alternative banking energy-related equipment and services, such as solar photovoltaic wireless ATMs, and fewer bank branches.

This paper aims to examine the causation linking financial technology to economic growth in the East African Community states from 1997 to 2019.

Autoregressive distributed lag is used. Gross domestic product per capita proxies economic growth, automated teller machines, point of sale, debit card ownership and mobile banking measure financial technology.

The results unveil a significant relationship between financial technology and economic growth. The findings show bidirectional causality between automated teller machine and economic growth, with unidirectional causation from economic growth to point of sales and internet banking, mobile banking and government effectiveness to economic growth. The error correction term is negatively significant, demonstrating a long-term convergence between Fintech measures and economic growth.

The governments should effectively enact and implement policies that protect investments in financial technologies to boost economic growth in the East African Community countries. The government should reduce taxes on financial technology equipment and related services. The use of automated teller machine, debit card ownership and internet banking should be encouraged through cashless transactions. Financial institutions should adopt cashless operation policies to encourage the use of financial technologies.

Research results on the bond between financial technology and economic growth are not conclusive. These studies demonstrate that technological innovations are double edged-swords, with both positive and negative sides. The results are conflicting; some reveal positive relationships, while others show negative links. Hence, research is required to fill the lacuna.

This study aims to identify the factors that could explain the intention to use Paytech services within an Islamic banking context. The authors use an extended version of the technology acceptance model to develop a causal–predictive analysis.

The research model and hypotheses were tested by applying partial least square-structured equation modeling to data collected from 214 users of Islamic banking in Saudi Arabia.

The results show that perceived trust has a highly significant direct effect on the intention to use Islamic Paytech services, whereas perceived risk has a significant indirect effect on IU.

Internet banking behavior may not be static. In technology acceptance, during the various phases from introduction to the maturity phase, the respondent’s perceptions tend to change

From the point of view of Fintech services providers, the knowledge of the factors fostering the adoption of Fintech services would allow an international expansion without the inconvenience of establishing offices or companies in countries whose legislation does not favor the operations carried out by Islamic banks.

These digital payment services would allow access to financial services to the entire Muslim population regardless of their location (Islamic and non-Islamic nations) and will also reach out to the next generation of young Muslims as a majority are “digital natives” ready for digital Islamic financial solutions.

This study is the first to explore the intention to use Paytech services by Islamic banking users in Saudi Arabia. From a theoretical perspective, this work contributes to the academic literature by analyzing the intention to use Paytech services in an Islamic banking context. On the practical front, the study identifies the crucial factors that industry players can use to design their Paytech applications and services to increase financial inclusion in Saudi Arabia and other countries with similar cultures as well as to design an international expansion without the inconvenience of establishing offices or companies in countries whose legislation does not favor the operations carried out by Islamic banks.

The objective of this study is to investigate the impact of the COVID-19 pandemic on the consumer payment behavior in Italy by correlating financial literacy with digital payment awareness, examining media anxiety and financial security, and including a gender analysis.

Consumers’ attitudes toward cashless payments were investigated using an online survey conducted from November 2021 to February 2022 on a sample of 836 Italian citizens by considering the behavioral characteristics and aspects of financial literacy. Structural equation modeling (SEM) was used to test the hypotheses and to determine whether the model was invariant by gender.

The analysis showed that the fear of contracting COVID-19 and the level of financial literacy had a direct influence on the payment behavior of Italians, which was completely different in its weighting. Fear due to the spread of news regarding the pandemic in the media indirectly influenced consumers’ noncash attitude. The preliminary results of the gender multigroup analysis showed that cashless payment was the same in the male and female subpopulations.

This research is noteworthy because of its interconnected examination. It examined the effects of the COVID-19 pandemic on people’s payment choices, assessed their knowledge, and considered the influence of media-induced anxiety. By combining these factors, the study offered an analysis from a gender perspective, providing understanding of how financial behaviors were shaped during the pandemic.

This paper aims to investigate the determinants of global interest in central bank digital currency (CBDC). It assessed whether global interest in sustainable development and cryptocurrency are determinants of global interest in CBDC.

Google Trends data were analyzed using two-stage least square regression estimation.

There is a significant positive relationship between global interest in sustainable development and global interest in CBDC. There is a significant positive relationship between global interest in cryptocurrency and global interest in the Nigeria eNaira CBDC. There is a significant negative relationship between global interest in CBDC and global interest in the eNaira CBDC. There is a significant positive relationship between global interest in CBDC and global interest in the China eCNY. There is a significant negative relationship between global interest in cryptocurrency and global interest in the Sand Dollar and DCash.

The literature has not empirically examined whether global interest in sustainable development and cryptocurrency are factors motivating global interest in CBDC. This study fills a gap in the literature by investigating whether global interest in sustainable development and cryptocurrency are factors motivating global interest in CBDC.

This paper aims to analyse the virtual currency regulation especially in Finland, Sweden and Norway. Different member states had a bit differently incorporated regulation of AMLD5. Finland has gone the furthest in regulation and even issuers of virtual currency are under the Finnish regulation.

In one hand, the study approach is legal dogmatics, but in other hand it is comparative legal research. Both approaches can be found in this paper.

The EEA is going from a more fragmented regulatory landscape based on 5th Anti-Money Laundering Directive to a more uniform regulatory approach provided by a legislative package that regulates crypto assets more broadly, coupled with an overhaul of the anti-money laundering rules, bringing them into a single European rulebook. Finland has taken a step further in this matter. Therefore, it would be reasonable for the AMLD5 scope to be expanded in this respect. It is a welcome development that the regulation will be unified and that investor protection will be better taken into account in the future as well.

This paper gives a picture of what kind of challenges is there in Fennoscandic in terms of money laundering regulation of virtual currencies. On the other hand, this paper brings into the discussion the rather clever solutions of Fennoscandic (especially Finland) regarding money laundering of virtual currencies.

This study aims to investigate the key determinants predicting users’ behavioural intention (BI) in adopting mobile payment (m-payment) in the new normal era.

The mobile technology acceptance model (MTAM) was extended through attitudes, perceived trust, perceived risk and personal innovativeness (PI) with government support (GS) functioning as a moderator. A total of 245 valid responses were gathered from Malaysian m-payment users with purposive sampling and subsequently evaluated through partial least square-structural equation modelling.

Mobile usefulness and PI significantly predicted user BI to use m-payment. Based on the moderation analysis, GS strengthened attitude-based impacts on BI towards m-payment adoption.

The empirical outcomes provide stakeholders with pivotal implications to develop holistic policies and strategies that potentially catalyse m-payment usage in the new normal era.

This research expands the current body of knowledge by assessing the factors impacting m-payment usage intention in the new normal era. The four aforementioned MTAM elements and GS (moderator) were recommended to boost model workability and offer novel evidence from a distinct viewpoint.

El objetivo de este estudio es investigar los determinantes clave que predicen la intención de comportamiento de los usuarios a la hora de adoptar el pago por móvil (m-payment) en la nueva era normal.

El modelo de aceptación de la tecnología móvil (MTAM) se amplió a través de las actitudes, la confianza percibida, el riesgo percibido y la capacidad de innovación personal, con el apoyo gubernamental como moderador. Se recogió un total de 245 respuestas válidas de usuarios malasios de pago por móvil mediante muestreo intencionado y se evaluó posteriormente mediante modelización de ecuaciones estructurales por mínimos cuadrados parciales (PLS-SEM).

La utilidad del móvil y la capacidad de innovación personal predijeron significativamente la intención de los usuarios de utilizar el pago por móvil. Según el análisis de moderación, el apoyo gubernamental reforzó los efectos basados en la actitud sobre la intención conductual de adoptar el pago por móvil.

Los resultados empíricos proporcionan a las partes interesadas implicaciones fundamentales para desarrollar políticas y estrategias holísticas que catalicen potencialmente el uso del pago móvil en la nueva era de la normalidad.

Esta investigación amplía el corpus actual de conocimientos al evaluar los factores que influyen en la intención de uso del pago por móvil en la nueva era normal. Se recomiendan los cuatro elementos MTAM mencionados y el apoyo gubernamental (moderador) para impulsar la viabilidad del modelo y ofrecer pruebas novedosas desde un punto de vista distinto.

本研究旨在探讨新常态时代用户使用移动支付（m-payment）行为意向的主要决定因素。

通过态度、感知信任、感知风险和个人创新能力, 并以政府支持作为调节因素, 对移动技术接受模型（MTAM）进行了扩展。通过有目的的抽样, 从马来西亚移动支付用户中收集了 245 份有效回复, 随后通过偏最小二乘法结构方程模型（PLS-SEM）进行了评估。

移动实用性和个人创新性可显著预测用户使用移动支付的行为意向。根据调节分析, 政府支持加强了态度对采用移动支付的行为意向的影响。

实证研究的结果为利益相关者提供了重要的启示, 有助于他们制定全面的政策和战略, 在新常态时代促进移动支付的使用。

本研究通过评估新常态时代影响移动支付使用意向的因素, 拓展了现有的知识体系。研究推荐了上述四个 MTAM 要素和政府支持（调节器）, 以提高模型的可操作性, 并从一个独特的视角提供了新的证据。

This study aims to understand consumer behaviour in the context of online food delivery (OFD), especially given the mandatory lockdown imposed in some countries that have modified the behaviour of consumers. Using model goal-directed behaviour (MGB), this study was conducted to investigate consumer perceived risk on the use of OFD services.

Responses of food delivery services users were collected online throughout April 2020 to understand their risk profile and behaviour. A total of 339 responses were collected and subsequently analysed using partial least square (PLS). Both measurement and structural model were evaluated to ensure that the structural equation modelling (SEM) is valid.

The results revealed that attitude (ATT), subjective norm (SN), positive anticipated emotion (PAE) and negative anticipated emotion (NAE) and perceived behavioural control (PBC) significantly influenced users' desire. It was also found that PBC significantly influenced users' intention. The empirical result suggests that performance, privacy, financial, physical and the risk of contracting COVID-19 negatively influenced users' desire. In contrast, only physical and the risk of contracting COVID-19 negatively influenced users' intention to use OFD services.

These findings provide OFD service providers and scholars with significant insights into what compels urbanites to adopt OFD services amid a health pandemic. It also allows OFD companies to realign their operation in addressing these concerns and changes in consumer behaviour.

Against the backdrop of the pandemic, this study provides insights for OFD providers in developing new strategies and approaches for business development and consumer retention in a post-pandemic world.

本研究擬瞭解與網上訂餐相關的消費行為；尤其當有些國家推行了改變消費者行為的強制性封鎖政策的情況下，這類研究更具意義。透過應用目標導向行為模型，本研究擬探討消費者在使用網上訂餐服務時所意識到的風險。

研究人員於 2020年4月網上收集使用訂餐服務人士的意見，以瞭解其風險狀況和行為。研究共收集了339位人士的意見，並以偏最小二乘法進行分析。測量和結構模型均加以評估，以確保結構方程模型是站得住腳的。

研究結果顯示，態度、主觀規範、預期的正面和負面情緒、以及感知的行為控制，顯著地影響了用戶的慾望。研究結果亦發現，感知的行為控制顯著地影響了用戶的意圖。研究的經驗性結果暗示了表現、私隱、金錢上的爭議、可能會導致的身體損傷和感染2019冠狀病毒病的風險，負面地影響用戶的慾望。相比之下，影響著用戶使用網上訂餐服務的意圖的因素就只有可能會導致的身體損傷和感染2019冠狀病毒病的風險。

研究的結果，為提供網上訂餐服務的營運者和研究學者提供了重要的啟示，使他們更瞭解是什麼因素會迫使都市人在與健康息息相關的大流行病期間使用網上訂餐服務。而且，提供網上訂餐服務的公司亦可藉此重新調整其營運，以能處理客戶的憂慮和應付消費行為的變化。

在大流行病肆虐的背景下，本研究為網上訂餐服務提供者給予了啟示，以便他們能在後疫情時代制定新的策略和營運方法，以拓展其業務和留住消費者。

This study aims to investigate the feasibility of employing a multi-objectives integer-programming model for effective allocation of resources for cyberfraud mitigation. The formulated objectives are the minimisation of the total allocation cost of the anti-fraud capacities and the maximisation of the forensic accounting capacities in all cyberfraud incident prone spots.

From the literature survey conducted and primary qualitative data gathered from the 17 licenced banks in South Africa on fraud investigators, the suggested fraud investigators are the organisation’s finance department, the internal audit committee, the external risk manager, accountants and forensic accountants. These five human resource capacities were considered for the formulation of the multi-objectives integer programming (MOIP) model. The MOIP model is employed for the optimisation of the employed capacities for cyberfraud mitigation to ensure the effective allocation and utilisation of human resources. Thus, the MOIP model is validated by a genetic algorithm (GA) solver to obtain the Pareto-optimum solution without the violation of the identified constraints.

The formulated objective functions are optimised simultaneously. The Pareto front for the two objectives of the MOIP model comprises the set of optimal solutions, which are not dominated by any other feasible solution. These are the feasible choices, which indicate the suitability of the MOIP to achieve the set objectives.

The results obtained indicate the feasibility of simultaneously achieving the minimisation of the total allocation cost of the anti-fraud capacities, or the maximisation of the forensic accounting capacities in all cyberfraud incident prone spots – or the trade-off between them, if they cannot be reached simultaneously. This study recommends the use of an iterative MOIP framework for decision-makers which may aid decision-making with respect to the allocation and utilisation of human resources.

The originality of this work lies in the development of multi-objectives integer-programming model for effective allocation of resources for cyberfraud mitigation.

Accounting information systems are mainly rule-based, and data are usually available and well-structured. However, many accounting systems are yet to catch up with current technological developments. Thus, artificial intelligence (AI) in financial accounting is often applied only in pilot projects. Using AI-based forecasts in accounting enables proactive management and detailed analysis. However, thus far, there is little knowledge about which prediction models have already been evaluated for accounting problems. Given this lack of research, our study aims to summarize existing findings on how AI is used for forecasting purposes in financial accounting. Therefore, the authors aim to provide a comprehensive overview and agenda for future researchers to gain more generalizable knowledge.

The authors identify existing research on AI-based forecasting in financial accounting by conducting a systematic literature review. For this purpose, the authors used Scopus and Web of Science as scientific databases. The data collection resulted in a final sample size of 47 studies. These studies were analyzed regarding their forecasting purpose, sample size, period and applied machine learning algorithms.

The authors identified three application areas and presented details regarding the accuracy and AI methods used. Our findings show that sociotechnical and generalizable knowledge is still missing. Therefore, the authors also develop an open research agenda that future researchers can address to enable the more frequent and efficient use of AI-based forecasts in financial accounting.

Owing to the rapid development of AI algorithms, our results can only provide an overview of the current state of research. Therefore, it is likely that new AI algorithms will be applied, which have not yet been covered in existing research. However, interested researchers can use our findings and future research agenda to develop this field further.

Given the high relevance of AI in financial accounting, our results have several implications and potential benefits for practitioners. First, the authors provide an overview of AI algorithms used in different accounting use cases. Based on this overview, companies can evaluate the AI algorithms that are most suitable for their practical needs. Second, practitioners can use our results as a benchmark of what prediction accuracy is achievable and should strive for. Finally, our study identified several blind spots in the research, such as ensuring employee acceptance of machine learning algorithms in companies. However, companies should consider this to implement AI in financial accounting successfully.

To the best of our knowledge, no study has yet been conducted that provided a comprehensive overview of AI-based forecasting in financial accounting. Given the high potential of AI in accounting, the authors aimed to bridge this research gap. Moreover, our cross-application view provides general insights into the superiority of specific algorithms.