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This study aims to merge the world’s proven ways of housing finance, including musharakah mutanaqisah, housing cooperatives and real estate crowdfunding, to present an alternative housing unaffordability solution based on the Islamic finance principle. It is intended to reduce the burden of funding for both sides (consumers and developers) and create win–win chances for all stakeholders, including intermediaries. By moving away from debt financing and merging the features of crowdfunding and cooperative, it is hopeful that the burden of home ownership will no longer be the case.

This paper presents the opinions of potential Chinese homebuyers (minority Muslims and most non-Muslims) and a few industry experts toward the proposed model via a mixed research method.

According to the findings, the majority of respondents agreed with the proposed paradigm. Just concerned that China’s lack of community culture and trust could pose a major threat to implementation. However, this paper argues that Chinese local governments may perform pilot testing in places where Islamic culture is prevalent. Their unique community culture and fundamental understanding of Shariah law may affect the viability of the proposed model.

The proposed model would increase the applicability of Islamic finance as a way of protecting the social order of communities in the spirit of upholding justice and fairness. A new type of housing loan based on musharakah mutanaqisah may squeeze out the real estate bubble and provide stakeholders with a multidimensional investment channel. In particular, the study identifies the impact of Chinese Islamic financing on government and cultural needs. It presents possible challenges for implementing the proposed model in reality and helps bridge the gap between theory and practice.

Despite being a Muslim-dominated country, Bangladesh has widely embraced traditional microfinance since its inception in the mid-1970s. However, Islamic microfinance, which has a lot to offer to the poor, is still in its infancy and has yet to gain momentum in the country. Therefore, the purpose of this study is to analyze the importance of Islamic microfinance and propose alternative Shariah-compliant microfinance models in Bangladesh.

This study is based on the desk research method, which relies on existing literature to collect secondary data on key concerns of traditional microfinance programs. In addition, institutional-level secondary data were also collected from the Microcredit Regulatory Authority (MRA) of Bangladesh. Guided by the Maqasid-al-Shariah, this study then proposes several Islamic microfinance models to overcome selected challenges faced by the microfinance industry in Bangladesh.

This study suggested three composite Shariah-compliant microfinance models, which are likely to help the underprivileged and thus ensure the achievement of the sustainable development goals in Bangladesh. The first model explained how the operational strategy of incumbent microfinance institutions (MFIs) could be restructured, while the second proposed the organizational strategies for establishing a new MFI. The third model used the notion of Sadaqah (charity) to address the multiple borrowing issues of the industry. Meanwhile, the successful transformation of the conventional microfinance industry to an Islamic one is dependent on the effective collaboration between the regulatory authorities, practitioners and MFIs.

Albeit the paucity of literature on the topic, the findings of this study will guide policymakers/practitioners in designing relevant microfinance models to help transform conventional microfinance into Islamic microfinance in Bangladesh.

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 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.

The purpose of this paper is to examine the adoption of Islamic finance products (murabaha, musharakah, mudarabah, salam, ijara, istisna and Qard Hassan) by small and medium-sized enterprises (SMEs) in Cameroon, a non-Islamic Sub-Saharan African country.

It used primary data collected from a cross-section of 1,358 SMEs in eight regions of Cameroon using self-administered structured questionnaires. To facilitate the analyses and interpretation, these products are grouped into four groups based on certain characteristics. A multivariate probit model is estimated to take into account the interaction between these different Islamic finance products.

This study revealed that the desire to comply with Sharia law, awareness, attitude and intention were critical determinants of the decision to adopt Islamic finance products by Cameroonian SMEs. The least influential factors were perceived behavioral control, subjective norms, enterprise characteristics (size, age and location) and socio-demographic characteristics of the entrepreneur (gender, age and marital status). The extension of the multivariate approach permitted us to compute for predicted probabilities which revealed that there exists a synergy effect between the different Islamic finance products. That is, Cameroonian SMEs combine different Islamic finance products at the same time based on their needs. This is especially the case between the partnership-based products (musharakah and mudarabah) and manufacture/rent products (istisna and ijara).

Policymakers are encouraged to develop stakeholder-oriented strategies to promote effective consumer education in Islamic finance products which will boost awareness. Also, Islamic finance institutions should endeavor to develop innovative financial products that are Sharia-compliant and economically beneficial to the individual and business needs of SMEs. Moreover, policymakers and management of Islamic finance institutions should ensure the putting in place of effective governance structures to guide Islamic finance operations. Finally, policymakers should endeavor to take into account the possible synergy between the different Islamic finance products in their quest to develop this activity.

To the best of the authors’ knowledge, this is the first study that analyses the adoption of different Islamic finance products while taking into account the possible synergy that exists between these products.

This study aims to explore the phenomenon of Islamic religious communication and how Islamic banks in Pakistan use religion-based communication, along with its expected outcomes.

Transcendental phenomenology approach is opted using a multi-stage data collection strategy consisting of observations, documentary reviews and semi-structural interviews to get deep into the phenomenon in a particular context.

Findings highlight Islamic religious communication as workplace Islamic da’wah that is majorly categorized into compulsive da’wah, objectics da’wah and impulsive da’wah, serving its role in bringing spirituality to work through work-faith integration.

The finding of the study can be used in planning, formulating and implementing Islamic da’wah-based model to induce spirituality at work.

This study is the first of its type exploring Islamic da’wah in an organizational context as a mean to bring spirituality at work.

This study aims to examine the dynamics of traditional wayang kulit or shadow puppet knowledge management in a community-based enterprise (CBE) known as “Wisata Wayang” in Wukirsari Village, Yogyakarta, Indonesia.

A qualitative case study was adopted, which allows the author to explore the dynamics or uniqueness of an event or cultural phenomenon more deeply.

The shadow puppet is an artefact of Javanese culture with rich life philosophy and wisdom. It guides people the pursuit of harmony with themselves, others, the universe and God. The success of knowledge management of the shadow puppet at CBE was supported by the high entrepreneurial orientation of the administrators. This study showed that entrepreneurial orientation should be extended into sociopreneurial with additional aspects, including preservation mission and communality, promoting the emergence of grassroots innovations. The knowledge of shadow puppet craft in this village is passed through nyantrik, also known as apprenticeship.

No previous research has explored the dynamics of traditional knowledge management in the context of CBE in Indonesia. As Indonesia has rich traditional knowledge from hundreds of tribes and prominent communal cultures, this study of community-based knowledge management contributes new insights in the knowledge management literature.

The pressing issues of climate change and environmental degradation call for a reevaluation of how we approach economic activities. Both leaders and corporations are now shifting their focus, toward adopting practices and embracing the concept of circular economy (CE). Within this context, the Food and Beverage (F&B) sector, which significantly contributes to greenhouse gas (GHG) emissions, holds the potential for undergoing transformations. This study aims to explore the role that Artificial Intelligence (AI) can play in facilitating the adoption of CE principles, within the F&B sector.

This research employs the Best Worst Method, a technique in multi-criteria decision-making. It focuses on identifying and ranking the challenges in implementing AI-driven CE in the F&B sector, with expert insights enhancing the ranking’s credibility and precision.

The study reveals and prioritizes barriers to AI-supported CE in the F&B sector and offers actionable insights. It also outlines strategies to overcome these barriers, providing a targeted roadmap for businesses seeking sustainable practices.

This research is socially significant as it supports the F&B industry’s shift to sustainable practices. It identifies key barriers and solutions, contributing to global climate change mitigation and sustainable development.

The research addresses a gap in literature at the intersection of AI and CE in the F&B sector. It introduces a system to rank challenges and strategies, offering distinct insights for academia and industry stakeholders.

Allocation of the marketing budget has become increasingly challenging due to the diverse channel exposure to customers. This study aims to enhance global marketing knowledge by introducing an ensemble attribution model to optimize marketing budget allocation for online marketing channels. As empirical research, this study demonstrates the supremacy of the ensemble model over standalone models.

The transactional data set for car insurance from an Indian insurance aggregator is used in this empirical study. The data set contains information from more than three million platform visitors. A robust ensemble model is created by combining results from two probabilistic models, namely, the Markov chain model and the Shapley value. These results are compared and validated with heuristic models. Also, the performances of online marketing channels and attribution models are evaluated based on the devices used (i.e. desktop vs mobile).

Channel importance charts for desktop and mobile devices are analyzed to understand the top contributing online marketing channels. Customer relationship management-emailers and Google cost per click a paid advertising is identified as the top two marketing channels for desktop and mobile channels. The research reveals that ensemble model accuracy is better than the standalone model, that is, the Markov chain model and the Shapley value.

To the best of the authors’ knowledge, the current research is the first of its kind to introduce ensemble modeling for solving attribution problems in online marketing. A comparison with heuristic models using different devices (desktop and mobile) offers insights into the results with heuristic models.

The study aims to investigate the impact of indirectly evoked incentives, in the form of supervisor’s preferences, on the decision about accounting policy regarding depreciation method selection and to examine subsequent post-decision distortion by evaluating the depreciation method.

The authors conducted two experiments with control and treatment groups, manipulating the supervisor’s indirectly evoked preferences. In Study 2, the authors also measured the evaluation of both depreciation methods to investigate post-decisional distortion regarding the assessment of the depreciation method chosen in a decision task. Study 1 was conducted among 85 accounting students, while Study 2 consisted of 200 accountants.

Both studies revealed the significant impact of supervisor’s indirectly evoked preferences on accounting policy decisions. Participants who were aware of supervisors’ preferences were more likely to choose the depreciation method that was consistent with those preferences. The authors also found that those participants attached a higher value to the depreciation method, providing evidence that adherence to the supervisor’s preferences results in a distorted assessment of the depreciation methods.

First, this study shows that indirectly evoked supervisors’ preferences may lead to a departure from substantive criteria resulting in low-quality accounting outcomes. Second, the assessment of the depreciation method is inseparable from the situational context, as the evaluation of the depreciation method is interdependent upon the preferences of the choice of a depreciation method and the fulfillment of those preferences.