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This paper aims to examine the current practice in Singapore regarding an inheritance issue: disposal of the residual net estate to the bayt al-māl, which is identified as the Islamic Religious Council of Singapore (Majlis Ugama Islam Singapura, MUIS). The issue arises when the deceased leaves farḍ (fixed-share) heir(s) and/or dhawū al-arḥām (outer family members) but there is no ʿaṣabah (agnatic residuary heir by blood). Farḍ legal heirs are those beneficiaries for whom the Qurʾān prescribes inheritance of a pre-determined share. Disposal of the residual net estate to the bayt al-māl results in a reduction in the share due to the farḍ legal heir or worse, a total loss to the dhawū al-arḥām legal heirs.

A qualitative approach based on library and case study research has been adopted to elaborate practices that fall under the purview of the Administration of Muslim Law Acts (AMLA), Chapter 3.

The current practice seems biased against, especially, women and spouses. It creates high dissatisfaction in the community, especially those affected by such practices. This paper elaborates on the practice of residual net estate distribution in Singapore and the contemporary practices of the four Sunni madh-habs – the Ḥanafī, Mālikī, Shāfiʿī and Ḥanbalī jurisprudential schools – in other countries.

In Singapore, Muslim law is defined and implemented by the civil court, not the Syariah Court or MUIS. The recommendation to change from the current classical practice by the Syariah Court and MUIS to the contemporary practice that is relevant to today’s context lies with the civil court and Government of Singapore. The choice for the Syariah Court and MUIS to adopt the contemporary practice as per Ḥanafī School by rule of the court or the government is beyond this research. Zayd ibn Thābit, Caliph Abū Bakr and a small number of companions held the view that the residue net estate asset must go to the bayt al-māl, the current classical practice. The contemporary practice adopted by Sayyidina ʿUthmān ibn ʿAffān, Jābir ibn Zayd and majority of the companions’ view, is not in favour of the residue net estate asset to go to the bayt al-māl; rather they view that it must be returned to the legal heirs.

Awareness in the community in the current controversial practice in Singapore when the residue net estate through the farāʾiḍ law was giving to bayt al-māl instead of returning to farḍ or dhawū al-arḥām in the absence of the ʿaṣabah legal heir as stated in the Inheritance Certificate issued by Syariah Court.

To understand the contemporary Muslim law and the practical and just application in today’s Singapore context as supported by the AMLA, Chapter 3.

This is the first study that challenges the current practice by the Syariah Court and MUIS in Singapore, thereby endeavouring to restore justice to the community.

For Bangladeshi small and medium enterprises (SMEs), the COVID-19 economic shock is remarkable in both its complexity and intensity. SMEs need systemic inspiration to solve the crisis, aligned with a moral and authentic approach that serves both the leader and the follower’s interests. This study aims to conceptualize the innovation-focused success method of SMEs before and after the pandemic to manage the crisis by establishing spiritual leadership based on Islamic perspectives.

To discuss the impact of spiritual leadership on innovation-focused SME performance configuration through the lens of a crisis, a comprehensive literature study has been carried out in which over 360 articles are read and reviewed by the authors. It has also established the reliability and validity of literature analysis. Also, a qualitative investigation has been used to support the direction of the study.

For a subsequent process of scientific deployment and evaluation of its execution, a new applied strategic innovation-focused SME success configuration through spiritual leadership development is made available. The primary value of this paradigm is the potential to calculate and treat the aspects of spiritual leadership obtained from Islamic ideas.

Prior analytical or empirical attempts from multiple viewpoints are subsequently needed to inquire about the proposed conceptualization.

Among the realistic consequences of this analysis is that while a number of leadership paradigms have been embraced by a broad body of leadership studies, the findings indicate that this paper should pay heed to the influential spiritual style of leadership, taking into account Islamic perspectives on the context of crisis. Therefore, Bangladeshi SMEs need to develop and run leadership training programs focused on the Islamic viewpoint of spirituality to encourage the actions of leaders during and after crises.

The legal and moral values of the society would ultimately be upgraded from this conceptualization. Moreover, less corruption in corporate activities would improve the economic prosperity of a nation. It would also contribute to the cross-cultural portrayal of the positive picture of Islam.

This holistic conceptualization describes the mediating role of strategic innovation practices based on theoretical foundations, which have seldom been done in previous research, between the Islamic model of spiritual leadership and SME success during and after a crisis.

The assessment of the Real Estate (RE) prices depends on multiple factors that traditional evaluation methods often struggle to fully understand. Housing prices, in particular, are the foundations for a better knowledge of the Built Environment and its characteristics. Recently, Machine Learning (ML) techniques, which are a subset of Artificial Intelligence, are gaining momentum in solving complex, non-linear problems like house price forecasting. Hence, this study deployed three popular ML techniques to predict dwelling prices in two cities in Italy.

An extensive dataset about house prices is collected through API protocol in two cities in North Italy, namely Brescia and Varese. This data is used to train and test three most popular ML models, i.e. ElasticNet, XGBoost and Artificial Neural Network, in order to predict house prices with six different features.

The models' performance was evaluated using the Mean Absolute Error (MAE) score. The results showed that the artificial neural network performed better than the others in predicting house prices, with a MAE 5% lower than the second-best model (which was the XGBoost).

All the models had an accuracy drop in forecasting the most expensive cases, probably due to a lack of data.

The accessibility and easiness of the proposed model will allow future users to predict house prices with different datasets. Alternatively, further research may implement a different model using neural networks, knowing that they work better for this kind of task.

To date, this is the first comparison of the three most popular ML models that are usually employed when predicting house prices.