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This study aims to propose a new simulation approach for a real-life large and complex crowd management which takes into account deep learning algorithm. Moreover, the proposed model also determines the crowd level and also sends an alarm to avoid the crowd from exceeding its limit. Also, the model estimates crowd density in the pictures through which the study evaluates the deep learning algorithm approach to address the problem of crowd congestion. Furthermore, the suggested model comprises of two main components. The first takes the images of the moving crowd and classifies them into five categories such as “heavily crowded, crowded, semi-crowded, light crowded and normal,” whereas the second one comprises of colour warnings (five). The colour of these lights depends upon the results of the process of classification. The paper is structured as follows. Section 2 describes the theoretical background; Section 3 suggests the proposed approach followed by convolutional neural network (CNN) algorithm in Section 4. Sections 5 and 6 explain the data set and parameters as well as modelling network. Experiment, results and simulation evaluation are explained in Sections 7 and 8. Finally, this paper ends with conclusion which is Section 9 of this paper.

This paper addresses the issue of large-scale crowd management by exploiting the techniques and algorithms of simulation and deep learning. It focuses on a real-life case study of Hajj pilgrimage in Saudi Arabia that exhibits intricate pattern of crowd management. Hajj pilgrimage includes performing Umrah along with hajj that involves several steps which is a sacred prayer of Muslims performed at different time span of the year. Muslims from all over the world visit the holy city of Mecca to perform Tawaf that is one of the stages included in the performance of Hajj or Umrah, it is an obligatory step in prayer. Accordingly, all pilgrims require visiting Mataf to perform Tawaf. It is essential to control the crowd performing Tawaf systematically in a constrained place to avoid any mishap. This study proposed a model for crowd management system by using image classification and a system of alarm to manage millions of people during Hajj. This proposed system highly depends on the adequate data set used to train CNN which is a deep learning technique and has recently drawn the attention of the research community as well as the industry in changing applications of image classification and the recognition of speed. The purpose is to train the model with mapped image data, making it available to be used in classifying the crowd into five categories like crowded, heavily crowded, semi-crowded, normal and light-crowded. The results produce adequate signals as they prove to be helpful in terms of monitoring the pilgrims which shows its usefulness.

After the first attempt of adding the first convolutional layer with 32 filters, the accuracy is not good and stands out at about 55%. Therefore, the algorithm is further improved by adding the second layer with 64 filters. This attempt is a success as it gives more improved results with an accuracy of 97%. After using the dropout fraction as a 0.5 to prevent overfitting, the test and training accuracy of 98% is achieved which is acceptable training and testing accuracy.

This study has proposed a model to solve the problem related to estimation of the level of congestion to avoid any accidents from happening because of it. This can be applied to the monitoring schemes that are used during Hajj, especially in crowd management during Tawaf. The model works as such that it activates an alarm when the default crowd limit exceeds. In this way, chances of the crowd reaching a dangerous level are reduced which minimizes the potential accidents that might take place. The model has a traffic light system, the appearance of red light means that the number of pilgrims in a particular area has exceeded its default limit and then it alerts to stop the migration of people to that particular area. The yellow light indicates that the number of pilgrims entering and leaving a particular area has equalized, then the pilgrims are suggested to slower their pace. Finally, the green light shows that the level of the crowd in a particular area is low and that the pilgrims can move freely in that area. The proposed model is simple and user friendly as it uses the most common traffic light system which makes it easier for the pilgrims to understand and follow accordingly.

There is a misconception that Hajj and Umarah is just a worship matter and the consequences of suspending these religious gathering due to the pandemic is only limited to delay of going Saudi Arabia to perform it. However, the purpose of this paper is to focus on the impact of the pandemic in Hajj and Umrah by exploring its impact on different stakeholders affecting its disruption due to the pandemic.

This is a library-based study that uses qualitative method to explore the impact of COVID-19 on Hajj and Umrah. Thus, provisions of Quran and hadith on Hajj and Umrah were examined as primary data for the research to establish the importance of the rituals in Islam. Guidelines set by Hajj regulators and instruments enabling them in that behalf were examined likewise. In addition, content analyses were made of relevant secondary data from published sources including articles, books, newspapers and web resources that embody scholarly, scientific and religious views on the issue being studied.

It is realised that in the first year of the pandemic, while Umrah is entirely suspended, Hajj was scaled back and performed by 10,000 people altogether, a tiny segment of the over two and half million that partook in the ritual previously. Hajj and Umrah have been greatly inhibited and jeopardised by the COVID-19 pandemic resulting in religious, social, economic, psychological effects on the eligible but affected Muslims and Muslims countries. Along these lines, recommendations were accordingly proffered on the way forward to better Hajj and Umrah management.

It is anticipated that the findings of the research would assist policy makers to comprehend the impact of the pandemic on Hajj and Umrah to ensure that the policies they make in this regard would adequately cover every aspect affecting the stakeholders which is deliberated in this research. It is also expected that the recommendations provided in this paper will assist stakeholders of Hajj and Umrah to grasp the importance of taking precautions for any crisis similar to COVID-19 when it happens.

This chapter presents findings from in-depth interviews with female pilgrims traveling from Turkey on their Hajj. The three main motives for the respondents were fulfilling one of the Five Pillars of Islam, visiting the center of the Muslim world, and seeing how others practiced Islam. For the majority of female pilgrims, the decision to go was made either jointly with their husbands or by others on their behalf. The long-lasting influences of this pilgrimage may include becoming more spiritual, peaceful, attentive, calm, tolerant, and careful. The experiences reported by respondents are discussed.

The integration of the Internet in translation creates several opportunities for translators. This study aims at examining the impact of using web-based translation (WBT) on translating religious texts.

The study followed a quasi-experimental study design. Sixty students enrolled in English Department, University of Bisha, participated in this study. The participants were divided randomly into three groups (i.e. words group, sentences group and passages group). The data was collected through a translation test and a questionnaire.

The results indicated that WBT is more beneficial in translating words than translating sentences or passages. In addition, WBT is more beneficial when words are translated from English into Arabic as well as from Arabic into English. The results from the questionnaire revealed positive attitudes toward using WBT in the process of translation.

This use of technology in translation has been examined in many studies (e.g. Bundgaard et al., 2016). WBT can be used to translate any field of knowledge. One of these fields is religious translation. According to O'Connor (2021), the study of religious translation has expanded greatly in recent years from its strong textual tradition and a constant focus on equivalence and translatability. However, very little has been done to examine the impact of WBT on translating religious texts. Therefore, this study aims at exploring the impact of WBT on translating religious texts with special reference to Islamic texts.

The purpose of this study is to analyze the crowd dynamics of the visitors at Al-Masjid al-Nabawi during the most oversaturated period to characterize the most critical conditions and suggest technical solutions to accommodate visitors and provide them safe passage.

In this study, the time of entrance from the Al-Salam Gate to the tomb and from the tomb to the exit from the Al-Baqi’ Gate has been collected in the most oversaturated period. To be precise and to model the worst case, important crowd measures of effectiveness data are collected in the two holiest times considered by Muslims, during the holy month of Ramadan and the month of Dhul-Hijjah and during the busiest hours of the day to consider safety factors while proposing future solutions. The conventional manual head-counting method has been adopted to determine the crowd density and to carry out actual counting of the visitors from the recorded videos and photos captured by the legitimate authority.

The analyses revealed that the crowd dynamics in the month of Ramadan (peak) are statistically different from those for other times (off peak). In general, the crowd dynamics at all times on days other than Ramadan are almost identical.

The results of crowd characterization from this study are expected to help optimize crowd management in the Masjid at the most critical location and time. The data collected in this study could be used for future research to simulate similar crowd scenes or for even different crowd management scenarios in case of emergencies such as fire hazards or evacuation process.

In recent days, there has been an increasing interest towards achieving sustainable tourism objectives globally and specifically in Saudi Arabia. The benefits can be maximized if the government is successful in attracting current pilgrims and influence their future intention to revisit the country as tourists. Hence, the purpose of this paper is to measure pilgrims’ revisit intentions to understand more about the possibility of their potential contribution towards the Saudi tourism and hospitality industry in the evolving circumstances.

This paper uses configuration theory to identify the “ideal” type of the pilgrims and compares this to the rest to establish if they differ and if that difference matters. Data were collected from 278 visitors to the Holy Mosque in Makkah, Saudi Arabia, to perform Umrah.

The findings show that a large deviation from the “ideal pilgrim” is negatively related to revisiting intentions and dissemination of positive word of mouth (PWOM).

The development of profiles gives a better understanding of organizations or people across several dimensions looked at holistically. Fundamental to the theory is that there are only a limited number of configurations that achieve optimal performance (however defined).

The analytical approach adopted in this paper leads to achieving verbal and statistical correspondence in tests of “gestalts”. The interest is in establishing whether this difference matters to intentions to revisit and providing PWOM.

Umrah is a religious ritual that takes place inside the Holy Mosque in Makkah. Umrah can be performed any time during the year; however, performing Umrah in the month of Ramadan is much rewarded. Although the kingdom of Saudi Arabia is hosting this event each year, studies that focus on exploring the Holy Mosque visitor segments are scarce. This study aims to explore and describe the marketing segments of Umrah performers relative to their Umrah experience inside the Holy Mosque of Makkah. Most specifically, this study aims to explore segments of Umrah performers based on their perception of servicescape, hedonic and convenience value and the visitors’ outcome behaviors [i.e. intention to revisit and positive word of mouth (PWOM)].

Mixed-method techniques of data collection [i.e. self-administered questionnaires (n = 278) and short discussions (n = 10)] were used.

Cluster analysis is used for data analysis. The findings revealed four clusters of Umrah performers: real, occasional, rational and passionate performers.

This study is a first attempt to target pilgrims based on their experience with the servicescape during the organized religious event; despite its exploratory nature, it reveals interesting insights that will be useful for managers and scholars. Although the study helps to enrich the existing knowledge on visitors’ experience and proposes some implications for practitioners, it does have some limitations. First, convenience sampling was used, and hence the findings cannot be generalized. Second, the limited period of observation did not allow the authors to provide a complete picture of the pilgrims’ behavior; for this reason, the study findings partially describe the phenomenon. Another limitation is related to the difficulty of approaching respondents from Asia or South East Asia although they constitute a significant percentage of the total Umrah performers every year; this is because of the language barrier as data was collected from only English and Arabic speakers. Hence, to overcome these limitations, it is suggested that future studies could be expanded to target Asian respondents and perhaps other nationalities; and could be undertaken in other religious contexts. Moreover, an interesting future study could be carried out to compare the same model during other religious events. Added to that, another growing area of research could be approached by researchers, such as the impact of pilgrims sharing their experiences on influencing E-PWOM.

The findings reveal several implications for policymakers and stakeholders. The segmentation of Umrah performers assists destination managers, policymakers and local firms involved in managing this mass event to identify effective marketing decision-makers, business strategies and policymakers to satisfy the needs of these visitors (Disegna et al., 2011). Particularly, the identification of the key characteristics of these visitors can help destination marketers to develop a marketing mix that suits the needs of each cluster (Smith et al., 2014). Despite that the performers’ main motivation is the religious purpose, marketing strategists can attract the attention of these visitors to visit other religious, cultural and heritage sites in the country.

Encouraging the visit to other tourist spots in Saudi has several impacts on nourishing the economy and the community. Tourism in Saudi could encourage entrepreneurs to start new ventures to satisfy the need of visitors to the country. Small-medium enterprises could benefit from tourism as they could target market niches in which leader companies are not serving. For instance, hand-made souvenirs are one of these industries that could grow to satisfy the need of visitors.

The results contribute to the literature of event segmentation by identifying visitors’ profiles to rarely investigated destinations. The findings reveal several implications for policymakers and stakeholders.

This paper aims to examine the effects of taqwa (God-consciousness) and syukr (gratitude to God) on emotional intelligence (EI) in a Muslim population in Malaysia.

Structural equation modelling tool AMOS was used to test the study’s hypotheses. In total, data were sourced from 302 Muslim employees working in Malaysia's public and private sectors.

Taqwa and syukr positively influence EI, and people with taqwa and syukr demonstrate greater levels of self-emotional appraisal compared with other emotional appraisals. This study also shows that people with taqwa and syukr give increased priority to understanding and distinguishing positive and negative emotions because of their understanding of Islamic teachings. They also exhibit concern with knowing their emotions well before advising or responding to the emotions of others. This may increase their sense of empathy, thereby improving their emotional competency and EI.

The findings indicate that taqwa and syukr predispose Muslims to EI. This study applied the Qur’anic model of self-development, which connects the origin of emotion with the soul, thereby further enriching the literature on the subject. It also highlights the importance of taqwa and syukr to Muslim employees for achieving EI that is useful in creating a harmonious atmosphere in the workplace and prosperous relationships in society.