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In recent decades, the student population in dormitories has increased notably, primarily attributed to the growing number of international students. Dormitories serve as pivotal environments for student development. The coordination and compatibility among students can significantly influence their overall success. This study aims to introduce an innovative method for roommate selection and room allocation within dormitory settings.

In this study, initially, using multi-attribute decision-making methods including the Bayesian best-worst method and weighted aggregated sum product assessment, the incompatibility rate among pairs of students is calculated. Subsequently, using a linear mathematical model, roommates are selected and allocated to dormitory rooms pursuing the twin objectives of minimizing the total incompatibility rate and costs. Finally, the grasshopper optimization algorithm is applied to solve large-sized instances.

The results demonstrate the effectiveness of the proposed method in comparison to two common alternatives, i.e. random allocation and preference-based allocation. Moreover, the proposed method’s applicability extends beyond its current context, making it suitable for addressing various matching problems, including crew pairing and classmate pairing.

This novel method for roommate selection and room allocation enhances decision-making for optimal dormitory arrangements. Inspired by a real-world problem faced by the authors, this study strives to offer a robust solution to this problem.

Nowadays, in many organizations, products are not delivered instantly. So, the customers should wait to receive their needed products, which will form a queueing-inventory model. Waiting a long time in the queue to receive products may cause dissatisfaction and churn of loyal customers, which can be a significant loss for organizations. Although many studies have been done on queueing-inventory models, more practical models in this area are needed, such as considering customer prioritization. Moreover, in many models, minimizing the total cost for the organization has been overlooked.

This paper will compare several machine learning (ML) algorithms to prioritize customers. Moreover, benefiting from the best ML algorithm, customers will be categorized into different classes based on their value and importance. Finally, a mathematical model will be developed to determine the allocation policy of on-hand products to each group of customers through multi-channel service retailing to minimize the organization’s total costs and increase the loyal customers' satisfaction level.

To investigate the application of the proposed method, a real-life case study on vaccine distribution at Imam Khomeini Hospital in Tehran has been addressed to ensure model validation. The proposed model’s accuracy was assessed as excellent based on the results generated by the ML algorithms, problem modeling and case study.

Prioritizing customers based on their value with the help of ML algorithms and optimizing the waiting queues to reduce customers' waiting time based on a mathematical model could lead to an increase in satisfaction levels among loyal customers and prevent their churn. This study’s uniqueness lies in its focus on determining the policy in which customers receive products based on their value in the queue, which is a relatively rare topic of research in queueing management systems. Additionally, the results obtained from the study provide strong validation for the model’s functionality.

As the Hashemite Kingdom of Jordan celebrates its first centenary, this paper presents a critical reading of the development of architecture in the Kingdom reflecting the transformation of national identity.

The paper achieves this aim by performing an analytical diachronic survey of the main architectural styles and trends that emerged in Jordan and links the architectural styles and trends to four main historical periods that characterize the national temporal trajectory, supported by examples of buildings, projects and architects that represent each period.

The results show the impacts of different forms of architectural modernism on local practice and explore attempts to create a national architectural identity that range in their ideological drive from Pan-Arabism to Jordanian localism.

The research adds to the discourse on Arab cities and architecture and shows the development of architectural trends in an Arab Muslim country, focusing on the interaction of architectural modernism with local variables. The research aims to supplement literature on Arab architecture with a critical and nuanced historical account of Jordanian architecture in the English language to serve a global audience.

In offering reflections on key themes affecting sustainability in the Middle East, this paper explores how an imprecise concept such as sustainability can, co-constituted with other powerful political and economic systems, such as nation building, drive forward new agendas for urban development. Rather than focus on specific empirical findings, the paper reflects instead on some of the assumptions underpinning competing approaches to sustainability highlighting multiple alternate visions of urban sustainability. In doing so, the paper engages with the literature on sustainability, master-planning and real estate development inviting the reader in the process to think about and ponder on the role of vision in the process. The reader is therefore invited to consider the aggregate impact of individual master planned projects on the urban fabric of fast growing cities and to think about how projects such as Masdar City in Abu Dhabi and the Msheireb downtown redevelopment in Doha demonstrate how sustainability and nationalist discourses are intertwined offering competing visions of what a sustainable city might become while at the same time hiding urban inequalities in plain sight with the help of the ‘forward looking’ facade of sustainability.

The phenomenon of social withdrawal, known as the hikikomori-like idiom of distress (HLID), has been reported in many countries. This study aimed to explore profiles of Omanis who have HLID.

A cross-sectional online survey of 673 out of 1,529 Omanis identified with HLID using the Hikikomori Questionnaire (HQ-25) score of 42+.

Two profile groups were determined through cluster analysis according to socio-demographic and HQ-25 outcomes. Subjects in cluster 1 (n = 168, 24.9%) are significantly younger (p < 0.001) and more educated (p = 0.019), spend more time online (p < 0.001) and are living alone (p < 0.001) than subjects in cluster 2 (n = 505, 75.1%). More subjects in cluster 1 had a past mental illness (p = 0.037) but less previous childhood physical/emotional abuse (p = 0.029) than subjects in cluster 2. In contrast, subjects in cluster 2 had a low lack of socialization (p < 0.001), less active isolation (p < 0.001) and total HQ-25 scores (p < 0.001) than cluster 1. Subjects in Cluster 1 have more serious social withdrawal issues than those in Cluster 2, especially on a lack of socialization and isolation.

One limitation that might influence the results of this online study was that information was collected via self-report, and a cross-sectional design limits its results because it cannot assess causal inference. This study has contributed valuably to exploring different profile groups of HDLD, especially in the Arabian Gulf. The authors’ findings facilitate the development by creating innovative interventions strategically tackling different hikikomori groups.

While social withdrawal characterized by HLID has been reported proliferating in different parts of the world, little research has been forthcoming from Arabian Gulf countries. These findings suggest that there are two orthogonal clusters of HLID among Omanis. This study provides a foundation for further research on HLID, which has recently been reported in different parts of the world.