This study explored the relationships between green market orientation and competitive advantage, with a particular focus on the mediating role of green sustainable innovation. The research utilized a structured questionnaire to gather data from managers involved in environmental protection and professionals working in the manufacturing sectors of computers, electronics, optical products, and electrical equipment. The survey targeted respondents from key regions in Saudi Arabia, including Riyadh, Qassim, and the Eastern Province, resulting in a total of 273 responses. The collected data were analyzed using structural equation modeling (SEM), a robust statistical technique that allows for the examination of complex relationships between variables. The findings confirmed a mediational model where green sustainable innovation—comprising both green product and green process innovation—served as a critical intermediary linking green market orientation to competitive advantage. Furthermore, the study validated direct effects of green market orientation on both green sustainable innovation and competitive advantage. These results emphasize the dual pathways through which green market orientation influences business performance. The research concludes by offering actionable insights for Saudi managers, highlighting strategies to maximize profitability and competitiveness through the adoption and implementation of green sustainable innovation practices.

The root of the problem in this research is the fact that scientific writing with a national reputation is still low and the publication of scientific writing with a national reputation is also low, thus affecting the quality of lecturers at the University. To overcome this problem, this research developed a training management model that can improve the scientific writing skills of lecturers and familiarize lecturers to actively conduct nationally reputable scientific writing. The training management model in question is called the “National Reputable Scientific Writing Training Management” model. This type of research is development research or R&D to produce a valid, practical, and effective model, as well as all devices and research instruments related to the application of the model at the University. The results showed that: (1) the National Reputable Scientific Writing Training Management model is suitable for improving the scientific writing ability of lecturers; (2) the output of the National Reputable Scientific Writing Training Management model in the model group is significantly higher than the initial group (pre-model); (3) The average value of IP/IO from experts is 4.4 with a high category, from observers at stage I test is 4.0 with a high category, at stage II test is 4.7 with a high category and stage III test is 4.77 with a high category, so it is concluded that the National Reputable Scientific Writing Training Management model meets the criteria of effectiveness, practicality and implementation; (4) The response of university managers and respondents to the implementation of the model is quite satisfactory, both regarding the concept of the model, the application in technical implementation and their perception of the National Reputable Scientific Writing Training Management model; and (5) the National Reputable Scientific Writing Training Management model can be developed as an alternative implementation in training management at the university.

This study investigates the intricate relationship between awareness advertising and buying intention among Iraqi grocery shoppers, exploring the mediating role of consumer attitude. Employing a quantitative approach, the authors surveyed 300 shoppers. Using a random sampling technique. To ensure rigor and validity, the authors rigorously analyzed the relationships using partial least squares structural equation modelling (PLS-SEM) based on 288 valid responses. The findings reveal that awareness advertising significantly impacts buying intention, mediated by consumer attitude. These insights offer valuable management implications for product marketers. Sufficient brand awareness attracts consumer attention, shapes positive attitudes, and ultimately drives purchase decisions. This study further validates the theoretical model of consumer response by empirically establishing consumer attitude as a central intermediary between awareness advertising and buying intention within the Iraqi market context.

In this paper, we assess the results of experiment with different machine learning algorithms for the data classification on the basis of accuracy, precision, recall and F1-Score metrics. We collected metrics like Accuracy, F1-Score, Precision, and Recall: From the Neural Network model, it produced the highest Accuracy of 0.129526 also highest F1-Score of 0.118785, showing that it has the correct balance of precision and recall ratio that can pick up important patterns from the dataset. Random Forest was not much behind with an accuracy of 0.128119 and highest precision score of 0.118553 knit a great ability for handling relations in large dataset but with slightly lower recall in comparison with Neural Network. This ranked the Decision Tree model at number three with a 0.111792, Accuracy Score while its Recall score showed it can predict true positives better than Support Vector Machine (SVM), although it predicts more of the positives than it actually is a majority of the times. SVM ranked fourth, with accuracy of 0.095465 and F1-Score of 0.067861, the figure showing difficulty in classification of associated classes. Finally, the K-Neighbors model took the 6th place, with the predetermined accuracy of 0.065531 and the unsatisfactory results with the precision and recall indicating the problems of this algorithm in classification. We found out that Neural Networks and Random Forests are the best algorithms for this classification task, while K-Neighbors is far much inferior than the other classifiers.

Since 2013, the state has introduced a number of policies to strictly control the number and scale of public hospitals and to control the rapid expansion of public hospitals. After the introduction of this series of policies, the number of public hospitals in China did not continue to grow, but the number of beds in public hospitals continued to grow. This paper uses difference-in-difference (DID) method to analyze the number of public hospitals with the corresponding data of the development of private hospitals after the introduction of the policy, and the results proves that the introduction of relevant policies has an impact on the number of public hospitals, but has a limited impact on the expansion of the scale of public hospitals. At the end of the article, positive policy suggestions are given to the development of hospitals in China, such as controlling the expansion of public hospitals, strictly controlling the number of beds in public hospitals, and vigorously developing private hospitals. Promoting the development of private hospitals is an important economic supplement to China's health care.