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Automated Search Engine Optimization (SEO) is crucial for streamlining processes, ensuring consistency, and adapting to changes, thereby enhancing a website's overall success and visibility in the competitive online landscape. This research introduces a dataset and a baseline method for classifying website SEO ranks into three categories. Using 26 keywords, data was collected from 780 web pages across various Google rankings, and 36 ranking factors were employed to predict their rank. Key considerations for webpage preparation include anchor text, backlinks, Ref Domain, unique visits, and text length. The Random Forest model exhibited superior performance, achieving an average accuracy of 72% in predicting actual search rankings. The significance of this automated approach lies in identifying web pages requiring SEO improvements, leading to enhanced search engine rankings.

The intersection of health tourism and technology is creating 'smart destinations' that are changing the way individuals seek and experience the world's healthcare around them. This emerging innovation represents the strategic integration of new technologies and healthcare services and offers an enhanced experience to health tourists. Smart destinations use technology to deliver personalized and comprehensive healthcare solutions. These include advanced mobile health platforms, artificial intelligence analytics applications, wearable health devices, and innovative data analytics. These technologies enable remote communication, patient monitoring, and predictive analytics for personalized treatment planning. The intervention of health tourism and technology through the concept of smart destinations is reshaping the global health landscape. The introduction of advanced technologies not only increases the access and quality of medical care, but also enhances the experience of health tourists. As technology continues to advance, smart destinations play an important role in shaping the future of health tourism and connecting it with patient care. In this study, it presents the ideas that emerged as a result of the investigations about smart destinations arising from the intersection of health tourism and technology.

In recent years, the adoption of mobile CRM has become an efficient alternative in maintaining and improving performance at the firm level. This study focuses on system, service, and organizational characteristics and develops a research model based on an existing model of successful CRM development. The study hypothesizes about relationships between a number of m-CRM characteristic factors and m-CRM performance. These factors include the infrastructure readiness, system integration, location awareness, service accessibility, sector knowledge, and organizational learning. The results have important theoretical and practical implications, and the limitations of the study provide interesting avenues for future research.

As in every sector, employees contribute to health tourism. Since the subject is health, the approach of health professionals should be positive and their knowledge should be sufficient. It is important when the general awareness is thought and it was connected with the latest trends including even digital transformation. So, the connection among health professionals and the most recent factors regarding awareness should be examined by evaluating accordingly feedback from the area. This research addresses the main theme of health tourism awareness of health professionals and aims to illuminate the perspectives of employees on digital transformation in this dynamic field. The findings illustrate the enrichment of important intersections between health professionals and the expanding field of health tourism.