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The purpose of this study is to develop a model of the Muslim community’s behaviour in paying zakat to contribute ideas on how to increase zakat recipients nationally, so as to improve the welfare of the wider community.

This study uses a quantitative (i.e. multiple regression analysis that involves moderating variables) and descriptive approach. Multiple regression analysis with the stepwise method is implemented to get the best regression model of community’s behaviour in paying zakat. This study takes a sample of Muslim communities in several regions (northern coast) of Central Java, Indonesia.

In the situation of the absence of government regulations relating to the obligation to pay zakat for Muslim communities, the community’s behaviour in paying zakat can be formed through two things, which are: increasing the zakat understanding and strengthening the credibility of zakat management institutions. Providing complete information to the community regarding the existence and what has been done and what will be done by the zakat management institution is very necessary.

This study has not specifically discussed the various types of zakat paid, such as commercial zakat, agricultural zakat and professional zakat. Therefore, future research can be done more specifically to determine the behaviour of paying zakat based on the type of zakat as stated.

Increasing the target of collecting zakat funds from the community nationally needs: (i) educating the community about zakat more broadly and sustainably; (ii) strengthening the credibility of the zakat management institution; and (iii) strengthening the flow of information from the zakat management institution to the community.

Research on community’s behaviour in paying zakat has never been done before. This study analyses the behaviour of paying zakat comprehensively, namely, in terms of adherence to God and the government, awareness without coercion and the behaviour of choosing a place to pay zakat.

This study aims to explore the risk management practices of Islamic microfinance institutions (IMFIs) to increase their financial performance and sustainability.

This research used a qualitative approach to increase financial performance and sustainability. The study population comprised the Baitut Tamwil Muhammadiyah (BTM) in Central Java Province, Indonesia. The data collection techniques included questionnaires and an in-depth interview, and the framework was validated by the main participants.

This study showed that BTMs have implemented risk management using different standards. However, such risk management is carried out partially while prioritising certain risks and using different methods. The risk of Sharia compliance is the most recognised risk, while financing and operational risks are the most anticipated, because these two risk types directly impact financial performance and sustainability. In general, a risk management model can improve financial performance and sustainability. Nevertheless, there are obstacles in implementing risk management at BTMs, which include weak human resources, the employee selection process, human resource development and a good control system.

This research explored best practices for risk management in IMFIs and may contribute to the development of risk management in such institutions to maintain the financial performance and sustainability of their services.

Certification information published by a company will be responded by the market. Therefore, the purpose of this study is to examine the impact of ISO 9001 certification on the stock market reaction as indicated by stock returns reaction of companies in Indonesia.

This study used event study method with the period of 13 days. It consists of 6 days before and after ISO 9001 certification announcement and 1 day at the time of the event. It analyzed by using pair sample t-test and one sample t-test. The stock return data is obtained from companies that are ISO 9001 certified and it tested for their stock reactions before and after the certification.

The results of empirical research showed that the average and companies cumulative abnormal returns in Indonesia react quickly and positively on the first day after ISO 9001 certification announcement. This study proved the differences between abnormal returns before and after the ISO 9001 certification announcement period.

The company's success in implementing ISO 9001 will have an impact on investment in the capital market with a positive response from stock market players. The implication of this study is the further research can examine directly the impact of ISO 9001 implementation on investor behavior in the capital market.

Based on the development of the literature review, this is the first study which examined the impact of ISO 9001 certification announcement on investor reactions in the short term. Therefore, companies in Indonesia need to implement a quality management system for investors in Indonesia.

This study uses an event study approach which is the development of the efficient market hypothesis theory. First, the random walk test was conducted on the Jakarta Composite Index (JCI) to test the efficiency in the weak form. Furthermore, event study analysis was carried out on JCI and nine sectoral indices to determine the impact of COVID-19 related events on price movements. The study found that JCI prices follow a random walk pattern so that the stock market in Indonesia is efficient, at least in a weak form. In the event study testing, only events related to the first confirmed case of COVID-19 and the implementation of large-scale social restriction in Indonesia affected the composite index. From a sectoral point of view, only the event of Jakarta’s call center had no impact on price changes in the sectoral index. Thus, each index had a different effect throughout the event. The reaction seen from the movement of prices for the composite and sectoral index to the public information explains that the condition of the Indonesian capital market is efficient, at least in semi-strong form.

Purpose: The purpose of this chapter is to identify various factors that may influence the adoption of online education by students in higher education institutions (HEIs) and contribute to the achievement of sustainable development goals (SDGs) post-COVID-19.

Need for the Study: The study addresses the need to ensure inclusive and equitable quality education, as emphasised by SDG4. It focuses on lifelong learning opportunities and aims to understand the impact of online education on students in HEIs. By identifying the factors that influence adoption, the study aims to contribute to the development of effective strategies for promoting online education.

Methodology: The study utilises a framework incorporating the use of Statistical Package for the Social Sciences (SPSS) and Analysis of Moment Structures (AMOS) software. The framework allows for the analysis of the collected data’s reliability, validity and adequacy.

Findings: The study’s findings indicate that providing students with affordable online higher education can facilitate skill enhancement and create job opportunities. These findings highlight the potential of online education in contributing to the achievement of SDGs, particularly SDG4.

Practical Implications: The practical implications of the study suggest that promoting affordable online higher Education can have a positive impact on students, enabling them to acquire new skills and access job opportunities. By embracing online education, institutions can contribute to the advancement of SDGs and ensure inclusive and equitable quality education for all.

Given the growing emphasis among scholars, practitioners and policymakers on financial sustainability, this study aims to explore the applicability of machine learning techniques in predicting the financial performance of microfinance institutions (MFIs).

This study gathered 9,059 firm-year observations spanning from 2003 to 2018 from the World Bank's Mix Market database. To predict the financial performance of MFIs, the authors applied a range of machine learning regression approaches to both training and testing data sets. These included linear regression, partial least squares, linear regression with stepwise selection, elastic net, random forest, quantile random forest, Bayesian ridge regression, K-Nearest Neighbors and support vector regression. All models were implemented using Python.

The findings revealed the random forest model as the most suitable choice, outperforming the other models considered. The effectiveness of the random forest model varied depending on specific scenarios, particularly the balance between training and testing data set proportions. More importantly, the results identified operational self-sufficiency as the most critical factor influencing the financial performance of MFIs.

This study leveraged machine learning on a well-defined data set to identify the factors predicting the financial performance of MFIs. These insights offer valuable guidance for MFIs aiming to predict their long-term financial sustainability. Investors and donors can also use these findings to make informed decisions when selecting their potential recipients. Furthermore, practitioners and policymakers can use these findings to identify potential financial performance vulnerabilities.

This study stands out by using a global data set to investigate the best model for predicting the financial performance of MFIs, a relatively scarce subject in the existing microfinance literature. Moreover, it uses advanced machine learning techniques to gain a deeper understanding of the factors affecting the financial performance of MFIs.

This study aims to examine the nexus between digital financial literacy and customers’ perceived financial behavior within the Kuwaiti context. Moreover, it will further explore how digital financial literacy relates to financial behavior dimensions.

Data collection was facilitated by creating a questionnaire derived from multiple literature sources. This study used a cross-sectional, time-based dimension. Data was analyzed using the partial least square (PLS) structural equation modeling approach, using the Smart-PLS 4 software for computation.

Findings demonstrated a significant relationship between digital financial literacy and financial behavior, with a path coefficient of 0.542, a p-value of 0.000 and an R² value of 0.581. The explorative model revealed substantial relationships between many dimensions of digital financial literacy and various dimensions of financial behavior. More precisely, financial knowledge, awareness and decision-making were the factors that had the most significant impact on financial behavior.

Kuwaiti policymakers should consider including digital financial literacy programs in comprehensive financial education programs to improve public understanding of digital financial instruments and their consequences.

As the authors know, this is the initial endeavor to evaluate the relationship between digital financial literacy, financial behavior and their respective dimensions.

Despite the COVID-19 recession, the collection of zakat (almsgiving) managed by the National Board of Zakat Republic of Indonesia (BAZNAS RI) has increased, especially during Ramaḍān 1441 Hijra. Previous works show a positive relationship between digital zakat campaign and zakat collection. This paper aims to study the means of digital zakat campaign during COVID-19 outbreak. This topic is theoretically and practically important in the emerging debate of Islamic marketing, notably in Islamic social finance field.

This paper uses a qualitative research approach. A case study is engaged in the selection of BAZNAS RI for a detailed discussion of a zakat organisation. Meanwhile, a netnographic approach is used to analyse the number of 549 posts from BAZNAS RI’s social media, which are Facebook, Instagram, Twitter and YouTube. Furthermore, a qualitative software analysis of NVivo 12 Plus is used in performing the analytical procedures.

This work explains the means of digital zakat campaign during COVID-19 outbreak with a case of BAZNAS RI. It is identified the number of 6 parent nodes and 64 child nodes from the analysis using NVivo 12 Plus. The authors’ parent nodes are “donation”, “infaq” (Islamic spending for charities), “Ramaḍān matters”, “ṣadaqah” (voluntary charity), “virtual events” and “zakat”. These nodes detail digital campaign of BAZNAS RI posted in its social media during COVID-19 period in Ramaḍān. A theoretical implication of inclusive marketing is derived from the analysis. It explains that the inclusiveness of digital contents is practically significant in campaigning zakat as a religious obligation that contributes to social and financial benefits.

This paper does not claim a positivist perspective on the relationship between digital zakat campaign and zakat collection. Instead, this paper explores in-depth the practice of digital zakat campaign, which the previous study confirms its association with a muzakki’s (Muslims who are obliged to pay zakat) decision to pay zakat.

This paper establishes the Islamic marketing theory that is derived from industrial practices. The inclusiveness of digital contents in zakat campaign is critical in activating zakat as a religious obligation that authentically shapes the social and economic processes of a Muslim community. This theory is practically important for 'amils (employees) of zakat institution who work in the marketing division, chiefly to create such contents to post in social media.

The authors’ node of zakat distribution for COVID-19 relief indicates the importance of a formalised zakat institution to actualise zakat’s role in handling socioeconomic problems. Thus, paying zakat formally in an authorised organisation may contribute to a greater social contribution and maṣlaḥah (public interest) than paying it informally without any effective measurement.

This study contributes to the novelty in the Islamic marketing debate within two folds. First, this paper is among the pioneers in studying digital zakat campaign during COVID-19 outbreak by using a netnographic approach. Therefore, a theoretical implication derived from industrial practices is contributed. Second, this paper details the steps in using NVivo 12 Plus to analyse the unstructured data sampled from the internet. The future studies may thus refer to this work to understand the application of netnography and the procedures in analysing data from social media using this software.

This study aims to predict the adoption of mobile services among muzakki (Islamic taxpayers) through the integrative roles of technology acceptance model (TAM), perceived trust and religiosity.

A questionnaire was distributed to 209 muzakkis as this research’s respondents. The partial least square was used to evaluate the relationship between TAM, perceived trust, religiosity and the adoption of mobile zakat services.

This study finds that perceived easiness and religiosity play a positive and significant role in increasing the adoption of mobile zakat services. Meanwhile, perceived usefulness and perceived trust do not have any influential role in generating muzakki adoption behavior.

This study underlines the importance of digital zakat institutions making easy-to-understand and easy-to-access online platforms for the broader community. In addition, they need to collaborate with formal and non-formal religious education institutions to increase zakat awareness and its benefits for marginalized groups.

To the best of the authors’ knowledge, this study is the first to integrate the TAM theory, perceived trust and religiosity in estimating muzakki adoption of mobile services.

Although Zakah is the cornerstone of the social protection system in Muslim societies, providing relief to those in need and collecting funds from those who have access to money and property, many administrative and legal improvements need to be made to ensure that Zakah funds are managed effectively and efficiently in Muslim states. It is therefore important to recognize why some Muslims are not paying their Zakah through Zakah authorities. The purpose of this paper is to propose a viable and comprehensive research model, derived from an economic and socio-psychological perspective, to provide a richer understanding of Zakah payers’ compliance behaviour.

Drawing on extant literature, this study offers a conceptual framework for a better understanding of compliance behaviour by proposing an economic and socio-psychological model based on Fischer’s tax compliance model, which could be applied cautiously in an Islamic setting like Zakah.

The four main categories of the Fischer model are derived from socio-psychological and economic perspectives, namely, attitude and perception (system fairness, ethics and peer influence); Zakah system structure (Zakah law complexity and law enforcement); non-compliance opportunity (education level, wealth source and occupation); and demographic factors (age and gender). Each has much to offer in understanding Zakah payers’ compliance decisions. To suit the nature of Zakah, the influence of Islamic religiosity and the moderating effect of trust in the Zakah institution are incorporated into the model.

Those Muslim communities that strive to have functional Zakah systems to search for solutions to the perennial problem of low Zakah funding and its damning consequences, are offered a compliance model for systematically assessing Muslims’ compliance behaviour with Zakah provisions. This framework is anticipated to offer invaluable input to policymakers in streaming and strategizing the minimization of losses of Zakah revenue to Zakah authorities.

Although behavioural models such as the theory of reasoned action and the theory of planned behaviour have been extensively used in Zakah compliance studies, to the best of the authors’ knowledge, this study is perhaps the first to apply a socio-psychological and economic framework, emerging from tax literature, in the Zakah environment to develop fully understanding of Zakah payers’ compliance decisions.