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The presence of securities crowdfunding (SCF) FinTech in the Islamic financial landscape opens investment opportunities through shares and sukuk (Sharia bond) instruments. This study aims to examine the effect of investment risk (IR), legal risk (LR), product knowledge (PK), Sharia compliance (SC) and subjective norm (SN) on investment decisions in businesses and projects run by small and medium enterprises (SMEs).

The questionnaires were distributed to prospective investors with prior knowledge of SCF and Islamic investment. The data collected was then examined using partial least square-structural equation modeling using SmartPLS 4.0.

The results show that LR has positive and significant implications for supporting investment through SCF, while IR has the opposite. The main findings in this study explain that PK and SC are proven to strengthen the intention to invest in SCF. Meanwhile, SN, which also strengthens intention, is the greatest influence. Therefore, it is highly recommended that SCF organizers collaborate with regulators (OJK), universities, academics and the investor community, as well as Muslim entrepreneurs, to provide education and literacy regarding SCF products and the underlying contracts, along with the consequences and uniqueness of investment vis SCF.

From a managerial side, Sharia expert educators can be appointed to increase investors’ literacy and confidence to support SMEs’ business expansion via SCF. In addition, to minimize investment risk, SCF organizers are also advised to issue sukuk and shares in different low-risk businesses/sectors, followed by investment amounts that are more affordable for novice investors.

Research on SCF as an alternative to SME financing is still scarce. To the best of the author’s knowledge, this is the first research to empirically test the relationship between risk, SC, PK and SN on potential investors’ decisions to support SMEs through the SCF mechanism.

The potential growth in cryptocurrencies has raised serious ethical and religious issues leading to a new investment rethinking. This paper aims to identify the influence of religiosity on cryptocurrency acceptance through an extended technology acceptance model (TAM) model.

In the first phase, this research develops a conceptual model that extends the theory of the TAM by integrating the religiosity component. In the second phase, the proposed model is tested using search volume queries in daily frequencies from 01/01/2018 to 31/12/2022 and structural equation modeling (SEM).

The empirical results demonstrate a significant positive effect of religiosity on the intention to use cryptocurrency, the users' perceived usefulness (PU) and ease of use (PEOU). Besides, the authors note that PEOU positively influences the intention. Furthermore, religiosity indirectly affects the intention through the PEOU and positively impacts the intention through the PU. In the same way, PEOU has a considerable indirect effect on the intention through PU.

This study has practical and theoretical contributions by providing insights into the cryptocurrency acceptance factors. In other words, it contributes to the literature by extending TAM models. Practically, it helps managers determine factors affecting the intention to use cryptocurrencies. Therefore, they can adjust their industry according to the suitable characteristics for creating successful projects.

Identifying the effect of religiosity on cryptocurrency users' choices and decisions has a social added value as it provides an understanding of the evolution of psychological variants.

The findings emphasize the importance of integrating big data to analyze users' attitudes. Besides, most studies on cryptocurrency acceptance are investigated based on one kind of religion, such as Christianity or Islam. Nevertheless, this paper integrates the effect of five types of faith on the users' intentions.

The purpose of this study is to investigate the factors affecting behaviour intention (BI) to use and actual usages of investment-related FinTech services among the zoomers (Gen Z) and millennials (Gen M) retail investors of India.

The study explores the predictive relevance of actual adoption behaviour among the two different age categories of Indian retail investors. It uses the Unified Theory of Acceptance and Use of Technology-2 and the prospect theory framework as guiding frameworks. Data has been collected from 294 retail investors, actively engaged in the investment-related FinTech services. The multi-group analysis using variance-based partial least square structured equation modelling has been used to compare the two groups. The invariance between the two groups was achieved through measurement invariance assessment.

The study reveals distinct factors significantly affecting BI to use investment-related FinTech services among Gen Z and Gen M retail investors are performance expectancy (PE) to BI, perceived risk (PR) to BI, price value (PV) to BI and PR to service trust (ST).

This study provides insights for financial providers and policymakers, emphasizing different factors influencing BI to use investment-related FinTech services in both age groups. Notably, habit emerges as a common factor influencing the actual usage of investment-related FinTech services across Gen M and Gen Z retail investors in India.

This study explores the heterogeneous behaviour of the heterogenous population in the domain of technological adoption of investment-related FinTech services in India.

Thailand's Halal-friendly destination attributes are the focus of this study. The purpose of this study is to investigate the impact of Halal-friendly attributes on tourists’ intentions to visit non-Muslim destinations. Also, this study analyzes the impact of Muslim tourists’ attitudes on Halal-friendly characteristics and their intentions to visit countries that are not predominantly Muslim.

To accomplish objectives, a survey was used to gather the data by using a convenient non-probability sampling approach from Muslim-majority countries Malaysia, Indonesia and Brunei. A proposed structural equation model was used to assess the influence of the variables above on the outcomes.

This study found that the factors of Halal-friendly facilities and Halal-friendly service positively influence the visiting intentions of Indonesian, Malaysian and Brunei Muslim tourists. In contrast, the social environment, food/beverages and local and staff attributes do not influence visit intentions. The tourist attitude mediates the relationship between the intention to visit and three dimensions of Halal-friendly attributes (social environment; food/beverage; and locals and staff).

This study did not investigate different kinds of dimensions for Muslim tourists visiting Thailand, such as preferences regarding personnel and families, cultural and artistic characteristics and the attributes of events and festivals. These dimensions cover a wide range of Halal-friendly tourism aspects. Second, this research did not investigate the associations between the demographics of Muslim tourists (age, gender, education level and income level) and the model variables. Such an investigation could have helped business developers and marketers in Thailand develop an efficient strategy for target marketing. The results of this research provide fundamental guidance and information for tourist enterprises in non-Muslim nations on how to enhance Muslim travellers’ images and intentions. However, because of the influence of other variables, locations in various areas of Asia, Africa and Europe may exhibit somewhat different effective qualities (e.g. environment, culture, history, etc.).

This study sheds light on the factors contributing to visitor satisfaction in the context of a desire to go to a Halal-friendly site. This insight from this study can be adapted and applied by tourism managers and marketing executives to build or develop the Halal-friendly destination image of a tourist destination (Phuket) in the right dimensions. It is a possibility that the image of a tourist attraction has a tight relationship with travelers’ perceived value, contentment and loyalty (Hsu et al., 2008; Khunrattanaporn, 2013; Pike, 2008). Battour et al. (2022) found that Muslims’ behavioural intentions are affected by the Halal attributes of the destination. It indicates that Halal attributes are very important for Muslim tourists when selecting a destination. To attract Muslim tourists, this study can be used for strategies and planning.

This study sheds fresh light on the concept of Halal tourism. It examines the perspective of Muslim tourists using Halal goods or services in anticipation of a future trip to a non-Muslim location (Phuket). This study is crucial for destination tourism operators, managers and marketers who lead Muslim tourists to non-Muslim destinations.

This study aims to conduct a systematic literature review on consumer behavior (CB) in Islamic banking (IB), encompassing an overview of researched contexts and topics, identifying literature gaps and proposing a comprehensive future research agenda.

By using bibliometric citation and content analysis, this study investigates 135 documents sourced from Scopus indexed publications.

This study delves into the growing field of CB in IB, offering a comprehensive understanding that encompasses influential journals, theories, research context, characteristics and methods used in IB research.

To the best of the authors’ knowledge, this study is the first to provide a comprehensive review of CB studies in the IB domain detailing research topics, prevailing theories, research settings, important variables and research methods.

This chapter explores the concept of corporate social responsibility (CSR) from an Islamic Shari'ah-compliant perspective. It provides a comprehensive literature review on CSR with an explicit focus on the Islamic perspective of CSR, Islamic models of CSR, CSR practices in conventional and Islamic banks, and the consequences of CSR to Islamic banks. This chapter's main contribution lies in considering the current CSR literature from a Shari'ah perspective. Likewise, it identifies gaps in the current literature and suggests potential areas for future research. This chapter attempts to improve the understanding of how Islamic banks integrate social responsibility into their operations. The insights from this chapter are helpful to practitioners and academic scholars in Islamic finance, accounting, and CSR. This chapter emphasizes the importance of incorporating Islamic values and principles into CSR practices and encourages further research and investigation in this area.

This study aims to provide a comprehensive bibliometric investigation of the antecedents to financial stability in Islamic banking, a transition economy with a volatile stock market focusing on banks following the Shariah approach.

The data for this analysis was extracted from the Scopus database, which combines a comprehensively crafted abstract and citation database with augmented data and linked scholarly works across various disciplines. It quickly finds relevant research and provides access to reliable data and analytical tools. This study deploys “bibliometrix 3.0,” a biblioshiny R-package for influential structure and the VOS viewer for intellectual structure.

The investigation’s main findings revealed that 1,910 documents were published from 1987 to 2022. Published manuscripts received 39,050 citations, with an average of 10.18 citations per year. However, the instructed empirical research was experienced during 2009 and 2020, while earlier periods (1987–2008) were relatively inactive where banking was considered protective in the presence of BASEL-II capital accords regulations. While the International Journal of Bank Market has been at the top of the list to publish articles related to the area under investigation, the Journal of Banking and Finance is ranked one of the most cited articles. Malaysia has been at the top of the list of countries to research Islamic Sharia compliance principles in the banking industry, and International Islamic University Malaysia has produced enough evidence in this regard. The intellectual structure provided essential foundations for future research, and the bibliometric coupling approach was used.

While most of the banking research has been conducted to determine the banking business efficiency, risk and profitability, little focus is given to financial stability and that too concerning the Islamic banks. Therefore, researchers need to investigate this horizon from an Islamic banking point of view and focus on key issues that discriminate between Islamic and conventional banks in determining their stability level.

Briefly, to the best of the authors’ knowledge, this study would be the first to provide bibliometric information about financial stability keeping in view the sample data from banks with the Shariah approach. Furthermore, the proven analysis demonstrates a novel contribution that financially stable Islamic banks might strengthen the financial industry and overall economy.

This paper aims to apply several data mining techniques for predicting the daily precision improvement of Jakarta Islamic Index (JKII) prices based on big data of symmetric volatility in Indonesia’s Islamic stock market.

This research uses big data mining techniques to predict daily precision improvement of JKII prices by applying the AdaBoost, K-nearest neighbor, random forest and artificial neural networks. This research uses big data with symmetric volatility as inputs in the predicting model, whereas the closing prices of JKII were used as the target outputs of daily precision improvement. For choosing the optimal prediction performance according to the criteria of the lowest prediction errors, this research uses four metrics of mean absolute error, mean squared error, root mean squared error and R-squared.

The experimental results determine that the optimal technique for predicting the daily precision improvement of the JKII prices in Indonesia’s Islamic stock market is the AdaBoost technique, which generates the optimal predicting performance with the lowest prediction errors, and provides the optimum knowledge from the big data of symmetric volatility in Indonesia’s Islamic stock market. In addition, the random forest technique is also considered another robust technique in predicting the daily precision improvement of the JKII prices as it delivers closer values to the optimal performance of the AdaBoost technique.

This research is filling the literature gap of the absence of using big data mining techniques in the prediction process of Islamic stock markets by delivering new operational techniques for predicting the daily stock precision improvement. Also, it helps investors to manage the optimal portfolios and to decrease the risk of trading in global Islamic stock markets based on using big data mining of symmetric volatility.

This research is a pioneer in using big data mining of symmetric volatility in the prediction of an Islamic stock market index.

This research investigates the Islamic banks’ intermediation role (e.g. branches and deposits) in financing. It also examines how financing contributes to the regions' economic growth and poverty alleviation as a predictor and mediator variable.

A total of 297 observations were extracted from 33 Indonesian districts and 14 Islamic banks during the period 2012–2020. Fixed-effect regression analysis was used to examine variable’s interactions.

The empirical results indicate that Islamic banks have adopted a channelling role towards redistributing capital from lender to borrower. Besides, there are crucial roles in developing economies and reducing poverty at the district level. This study also reinforces the critical role of financing in mediating the relationship between branches and deposits as predictor variables and GDP and poverty as outcome variables.

The current study was limited to Indonesian Islamic banks and the district’s perspective. Future research needs to cover sub-districts and other poverty measurements (e.g. human education and development perspectives), including conventional and Islamic banks. It can help practitioners, regulators and researchers observe the dynamic behaviour of the banking sector to understand its role in the economic and social fields.

Bank managers and regulators should promote branches, deposits and financing. It also enlightens people about the essential role of Islamic banks and their fundamental operations in business and economics.

This study contributes to economic literature, bank managers and local governments' decision-making processes by developing and testing an economic growth and poverty model.

The purpose of this chapter is to cover banking efficiency using the concept of the Meta frontier function and to study group and subgroup differences in the production technology. This study estimates the technical efficiency (TE) and technology gap ratios (TGRs) for banks in Islamic countries. Using the assumption of the convex hull of the Meta frontier production set using the virtual Meta frontier within the nonparametric approach as presented by Battese and Rao (2002), Battese et al. (2004), and O'Donnell et al. (2007, 2008) and after relaxing this assumption, the study investigates if there is a significant difference between these two methods. To overcome the deterministic criterion addressed to nonparametric approach, the bootstrapping technique has been applied. The first part of this chapter covers the analytical framework necessary for the definition of a Meta frontier function and its estimation using nonparametric data envelopment analysis (DEA) in the case where we impose the assumption of the convex production set and follows in the case of relaxation of this assumption. Then we estimated the TE and the TGR in concave and nonconcave Meta frontier cases by applying the Bootstrap-DEA approach. The empirical part will be reserved for highlighting these methods on data bank to study the technical and technological performance level and prove if there is a difference between the two methods. Three groups of banks namely commercial, investment, and Islamic banks in 17 Islamic countries over a period of 16 years between 1996 and 2011 are used.