Our research aims to help game developers enhance the quality of Gacha games and increase their popularity among players. We used forecasting techniques and a survey of 177 participants to predict the number of downloads and identify common issues leading to player attrition. Our findings suggest accurate forecasting and issue resolution can boost downloads and player retention rates. Linear regression was the optimal method for predicting the number of downloads for Genshin Impact V3.4, with a predicted count of about 3.85 million. In contrast, exponential smoothing was the most accurate method for Honkai Impact 3rd, with a scheduled download count of 25.96 thousand. We collected data from reputable sources, including Statista, VG Insights, research articles, and YouTube videos. Our research offers practical recommendations for game developers seeking to enhance the quality of their gacha games and their popularity among players.

Background: Investigating the causes and impact of essential medicines and supplies shortages in the supply chain of the MOH in Saudi Arabia could be the initial step in setting innovative strategies for mitigating this issue. This study aimed to identify the key factors contributing to essential medicines and supplies shortages in the supply chain of the MOH in Saudi Arabia and assess their impact on healthcare delivery. Methods: A structured questionnaire was designed to collect relevant data on the causes and impact of essential medicines and supplies shortages. A representative sample of healthcare professionals, from various healthcare MOH facilities in Saudi Arabia. The Statistical Package for the Social Sciences (SPSS) software version 26 was used for the data analysis. Results: A total of 379 respondents participated in the study, 73.7% were males, 51.2% were aged 36–45 years, 23.5% were supply chain professionals, and 32.9% reported an experience of >15 years. 90.0% of the participants reported that they personally have experienced shortages of essential medicines and supplies in the MOH supply chain in KSA. Inadequate planning, forecasting, and procurement were identified as the most significant contributing factors for shortages by about half (48.5%). At least two-thirds of the participants agreed with all strategies adopted for mitigating the issue of shortages. Conclusions: The impact of shortages on patients and healthcare professionals was found to be substantial. The study also identified several key strategies to reduce shortages that received strong support from the participants.

AI applications are essential to smart logistics sector for industrial enterprises and for the fourth industrial revolution (Industry 4.0). The aim of this study is to analyze the variables that affect smart logistics and assess the efficiency of artificial intelligence applications on smart logistics. Further, the applications technology and AI has studied and the variables that influence on the adoption of AI are still unknown in this study. Moreover, the main investigation of this study is to find the impact of efficient factors on AI through integrating technology. The finding indicates the large-scale smart logistics system has a substantial impact on industrial organizations and businesses by utilizing AI applications of communication and information technology. Additionally, AI is able to offer supply chain logistics with technological assistance that combine big data, IoT, and cloud computing.

Governments utilize various media channels to disseminate knowledge pertaining to infectious diseases such as COVID-19. When it was declared a pandemic, society began to depend on the media for critical information and countermeasures that would facilitate tackling the virus. The main objective of this research is to examine the impact of verified Saudi government accounts across various media outlets on respondents’ knowledge, attitudes, and intentions regarding COVID-19. A structured online questionnaire was distributed and 315 responses were used for analysis. The results were analyzed using SPSS. The results indicate that the residents of Saudi Arabia have adequate knowledge concerning the symptoms, precautionary measures, and modes of transmission of COVID-19. The respondents have gained this knowledge from verified Saudi government accounts across various media outlets, most prominently via social media.

This paper explores the 5S management concept, its advantages and the framework required to implement the system in the Apparel Industry. The 5S method is a Japanese system that involves workplace management improvements. It further analyses the effect of the 5S method in the apparel & textile industry as a case study and how its implementation directly impacts saving time and costs. 5S process helps to eliminate waste, reduce defects, and help in improving the productivity of the business. Further, reducing clutter and junk at the workplace is hygienic and ergonomic. This research paper identifies how the 5S method is implemented in the Apparel industry and how it has helped the industry improve its waste reduction targets, profitability, and productivity. The apparel industry uses the 5S to dispose of the wastage and use the factory production layout to smooth working, wastages are cleared, and regularly maintained space. This would help minimize handling time, moving part used in apparel from one process to another quickly, and final apparel can be stitched and packed in a faster time process. This will improve the business’s profitability and enhance its competitiveness in the local and international market sectors.

The tourism industry is one of the fastest growing economic sectors in the world, and the developments in the industry are linked to the operation of tourism enterprises and the products offered by them. Being one of the most competitive industries in the business world, the management of supply and demand is essential aspect of successful management in the tourism sector. A major issue that arises in the tourism sector is the management of crowds in many of the beautiful and renowned cities in the world. The massive flow of visitors is not only an issue for the travelers, but also imposes risks on the supply chain that operates within the tourism industry. The aim of this article is to gain an understanding of supply chain applications in the tourism industry and exploration of crowd management with regards to tourism industry. The article also explores the advantages of using supply chain for crowd management in tourism industry, particularly with reference to the Saudi Arabia’s tourism industry, along with suggestions to integrate crowd management strategies in supply chain.

Microgrids are becoming popular nowadays because they provide clean, efficient, and lowcost energy. Microgrids require bulk storage capacity to use the stored energy in times of emergency or peak loads. Since microgrids are the future of renewable energy, the energy storage technology employed should be optimized to provide power balancing. Batteries play a variety of essential roles in daily life. They are used at peak hours and during a time of emergency. There are different types of batteries i.e., lithium-ion batteries, lead-acid batteries, etc. Optimal battery sizing of microgrids is a challenging problem that limits modern technologies such as electric vehicles, etc. Therefore, it is imperative to assess the optimal size of a battery for a particular system or microgrid according to its requirements. The optimal size of a battery can be assessed based on the different battery features such as battery life, battery throughput, battery autonomy, etc. In this work, the mixed-integer linear programming (MILP) based newly generated dataset is studied for computing the optimal size of the battery for microgrids in terms of the battery autonomy. In the considered dataset, each instance is composed of 40 attributes of the battery. Furthermore, the Support Vector Regression (SVR) model is used to predict the battery autonomy. The capability of input features to predict the battery autonomy is of importance for the SVR model. Therefore, in this work, the relevant features are selected utilizing the feature selection algorithms. The performance of six best-performing feature selection algorithms is analyzed and compared. The experimental results show that the feature selection algorithms improve the performance of the proposed methodology. The Ranker Search algorithm with SVR attains the highest performance with a Spearman’s rank-ordered correlation constant of 0.9756, linear correlation constant of 0.9452, Kendall correlation constant of 0.8488, and root mean squared error of 0.0525.

oining warehouses and suppliers facilities to deliver the finished product to the end customer is a complex process that requires extensive consideration. The resulting chain is an integration of such entities as the supplier, manufacturer, distributor, warehouse, retailer, and end customer. A perishable product is any product that can rot, spoil, or deteriorate rapidly and, soon after manufacture, may become unusable or obsolete. Perishable products thus have special nutritional characteristics that necessitate care and unique treatment for them. Such products can be anything that becomes outdated a short time after production or harvest, such as fruits, vegetables, meat, certain drinks, blood, and pharmaceuticals. The objective of this study is to find the best heuristics for distributing multiple perishable products as early as possible to maximize profit. Case studies involving featuring perishable products at different rates of degradation with multiple retailers and limited transportation capacity were carried out to demonstrate the effectiveness of the proposed method.