This study aims at exploring the effect of four elements of an integrated marketing mix. The mix consists of both elements of the 4Ps and SIVA marketing models. These elements are product-solution, promotion-information, place-access, and price-value. A questionnaire was used to collect the required data from a sample of retailing market customers in Saudi Arabia. The total number of the questionnaires used in data analysis was 378. The study found that product-solution and place-access from customers’ perspective had significant effects on customer retention. On the other hand, price-value had a negative significant effect on customer retention, while promotion-information had no effect on customer retention. Hence, companies are called for considering products as solutions, promotion as a source of information for customers, place as an access point for such a solution, and price must be appropriate to the value that the customer gets.

The aim of this study is to investigate the influence of logistics and distribution processes on business process reengineering by adopting green innovation for sustainable transformation. Guided by the Resource-Based View (RBV), the study examines logistics and distribution processes in relation to business process reengineering (BPR), through green innovation adoption, towards achieving sustainability goals. Drawing on a conceptual framework based in supply chain management and BPR theories, the study uses Structural Equation Modeling-Partial Least Squares to analyze data collected from respondents within the target industries. The results show that streamlined logistics and distribution processes help to ensure the success of Green Innovation as part of BPR, strengthening the trend towards sustainable transformation. The study accentuates the importance of logistics management in enabling environmental stewardship and enhanced operational efficiency, providing some key ideas for improving both theoretical developments and future directions as well on practice ground to adopt sustainable supply chain trends.

The purpose of this research was to analyze the increased performance improvement in the supply chain related to the energy and utilities sector of Jordan through cloud computing, also mediated by knowledge sharing. 150 respondents were analyzed. Research suggests that there was a strong positive relationship between cloud computing and supply chain performance. In addition, cloud computing had a strong and positive correlation with the practice of knowledge sharing. The result indicates that companies with a culture of knowledge sharing among employees were more likely to incorporate the use of cloud computing. The study also indicates that cloud computing adoption had enhanced supply chain performance in the utility and energy sector within Jordan. Therefore, the study also finds that there was a strong and positive relationship between knowledge sharing and well overall performance of supply chain activities. This points to the role that knowledge-sharing practices play in improving the performance of the supply chain within Jordanian utilities and energy sectors. Furthermore, the findings of the mediation study provide strong evidence in support of our hypothesis that knowledge sharing plays a major role as a mediator relating to the relationship between cloud computing adoption and supply chain performance. The observed mediation effect suggests that the positive impact of cloud computing implementation on supply chain performance can be attributed to some extent to its facilitating knowledge exchange practices. However, this research improves the understanding of relationships among cloud computing adoption implementations and information structure flow as well as supply chain performance within Utilities These results emphasize the importance of cloud technologies as information drivers that would lead to enhanced performance in terms of supply chain operations. These are insights that can be used by organizations and businesses aiming at improving their competitiveness and efficiency levels in these sectors.

Human migration is based on pull factors that individuals evaluate when it comes to moving to a different territory. Likewise, employee attrition is a phenomenon that represents the tendency to a reduction in employees within an organization. This research paper aims to develop and evaluate machine learning algorithms, namely Decision Tree, Random Forest, and Binary Logistic Regression, to predict employee attrition using the IBM dataset available on Kaggle. The objective is to provide organizations with a proactive approach to employee retention and human resource management by creating accurate predictive models. Employee attrition has significant implications for an organization's reputation, profitability, and overall structure. By accurately predicting employee attrition, organizations can identify the factors contributing to it and implement data-driven human resources management practices. This study contributes to improving decision-making processes, including hiring and firing decisions, and ultimately enhances an organization's capital. The IBM dataset used in this study consists of anonymized employee records and their employment outcomes. It provides a comprehensive HR data representation for analysis and prediction. Three machine learning algorithms, Decision Tree, Random Forest, and Binary Logistic Regression, were utilized in this research. These algorithms were selected for their potential to improve accuracy in predicting employee attrition. The Logistic Regression model yielded the highest accuracy of 87.44% among the tested algorithms. By leveraging this study's findings, organizations can develop predictive models to identify factors contributing to employee attrition. These insights can inform strategic decisions and optimize human resource management practices.

This research aims to investigate the upcoming challenges of green innovation and sustainability in the hospitality and tourism sectors of Saudi Arabia and the mediating role of National Vision 2030 in fostering industry growth. A quantitative design was used, and a close-ended questionnaire was used to collect data from 499 respondents in the hospitality and tourism sectors of Saudi Arabia. The analysis was performed using SmartPLS and structural equation modeling (SEM). The findings indicate several upcoming challenges, such as renewable energy consumption, energy efficiency, and the changing preferences of consumers. However, these challenges can be dealt with adequate government policies and the mediating role of the Saudi Arabia 2030 vision to achieve sustainability in the hospitality and tourism sectors. These findings have theoretical and practical implications, which are discussed in the end. The scope of the findings is constrained to the geographic context of Saudi Arabia, inviting future investigations in a broader international context.

Android malware is widespread and it is considered as one of the most threatening attacks recently. The threat is targeting to damage access data or information or leaking them; in general, malicious software consists of viruses, worms, and other malware. Current malware attempts to prevent being detected by any software or anti-virus. This paper describes recent Android malware detection static and interactive approaches as well as several open-source malware datasets. The paper also examines the most current state-of-the-art Android malware identification techniques including identifying by comparative evaluation the gaps between these techniques. As a result, an API-based dynamic malware detection framework is proposed for Android to provide a dynamic paradigm for malware detection. The proposed framework was closely inspected and checked for reliability where meaningful API packages and methods were discovered.

Pyrazolones are a class of heterocyclic compounds that contain a pyrazole ring fused to a ketone group. Recent scientific research has focused extensively on the potential anti-inflammatory properties of pyrazolone compounds due to their diverse pharmacological effects in alleviating inflammation and reducing fever. This motivated us to focus on the preparation of these derivatives in a simple and eco-friendly manner. A convenient new green methodology was modified for the preparation of 1-phenyl-3,5-pyrazolidinedione by the sonicated MCR of diethyl malonate, phenylhydrazine, and a catalytic amount imidazole as homogenous organic catalyst in water green solvent in a good yield. On the other hand, some of 4-arylidinepyrazolidinedione derivatives are prepared in the same manner via the treatment of a mixture of diethyl malonate, phenylhydrazine, aromatic aldehydes, and a catalytic amount of imidazole in an aqueous medium. Our target synthesized pyrazolidinediones were elucidated via elemental and several spectral analyses. Due to the importance of pyrazolidinediones in the field of treating inflammation and relieving pain, a number of prepared compounds were chosen to test their efficacy as anti-inflammatory agents using carrageenan-induced foot edema in rats and compare the results with indomethacin, the standard drug. We found that the majority of derivatives yield promising results spanning from good to wonderful, so derivatives (15k, 15b, 15h, 15a, and 15j) yield the best results while derivative (15i) yields an average result. As for the derivative (15f), it yields the lowest results compared to the standard drug. This is due to the difference in the structural composition of these derivatives, which increases the likelihood of their use as anti-inflammatory derivatives.

Materialism has emerged as a growing global drift in the past decade. This study highlights the influence of materialism on consumers' attitudes and actions regarding the purchase of environmentally sustainable products (ESPs) in a country such as Pakistan, which environmental orientations are in the developing stage. Materialistic perspectives can hinder the formation of positive attitudes towards environmentally sustainable products, especially when consumers engage in product comparisons. To evaluate the effects of materialism and product comparisons on purchasing intentions and behaviors, a survey was conducted among university students. The results revealed that consumers tend to avoid purchasing experience goods primarily because these items require a higher degree of involvement and risk assessment due to their intangible and experiential nature. This avoidance is particularly pronounced when the subjective norms and attitudes toward these goods are influenced by materialistic values, which often prioritize tangible, ownership-oriented products.

The term dissolution of the company refers to the expiration of the legal relationship between the partners, in different words the dissolution of the moral character of the company. Basically, commercial companies are established for the purpose of achieving the objective and the profits which are impossible for each partner to achieve alone, so partners work hardly to keep this company standing and ongoing practicing its commercial activities.in this paper focuses on the most prominent reasons for the expiry of commercial companies, whether partnerships or corporations, whether by the expiration of the definite-period of the company on the Saudi System for Companies. Also each company represents a person with a moral character who is entitled to legal capacity which enables it to acquire the rights and bear the liabilities the same as the natural person. The company is entitled to practice its activities with the assigned purposes of establishment and to conclude all legal acts including selling, purchasing, renting, leasing and whatsoever. Gaining the moral character capacity makes the company entitled to be plaintiff or defendant in case of disputes with other parties. Thus, in this scientific paper shall discuss the independent reasons which are entitled by the companies in its capacity as moral persons, moreover it can go beyond to other factors as well as being dependent by liability against other companies liabilities, and having a deputy to represent this company. It is also entitled to have the nationality of the country where its management office is located.

The combined effect of serial dependency and measurement errors is known to negatively affect the statistical efficiency of any monitoring scheme. However, for the recently proposed homogenously weighted moving average (HWMA) scheme, the research that exists concerns independent and identically distributed observations and measurement errors only. Thus, in this paper, the HWMA scheme for monitoring the process mean under the effect of within-sample serial dependence with measurement errors is proposed for both constant and linearly increasing measurement system variance. Monte Carlo simulation is used to evaluate the run-length distribution of the proposed HWMA scheme. A mixed-s&m sampling strategy is incorporated to the HWMA scheme to reduce the negative effect of serial dependence and measurement errors and its performance is compared to the existing Shewhart scheme. An example is given to illustrate how to implement the proposed HWMA scheme for use in real-life applications.