İşletmeden işletmeye pazarlamada dijitalleşme: Deniz taşımacılığının dönüşümü için strateji ve teknolojilerin geliştirilmesi

Digitalization offers various opportunities such as access to new markets, cost reduction and competitive advantage, the ability to develop and control products more agile, by profoundly influencing the activities of almost all businesses. However, as in many B2B markets, it is observed that it is too late to adapt to this transformation in maritime transportation. In this context, it becomes crucial to emphasize the importance of digitalization to maritime businesses and to identify digital technologies that are appropriate for their purposes and nature and to propose strategies for these technologies. This study addresses the issue of digitalization in maritime transportation in the marketing communication dimension. In this regard, firstly, a literature study was carried out with a deductive approach and digital marketing technologies were handled within the scope of maritime transportation market characteristics. Then, the focus was on social media, which is accepted as the most up-to-date technology of maritime transportation digital marketing communication, and research was carried out to develop strategies for container shipping companies to use social media more effectively. In this process, it has been determined that the engagement rate calculation formulas commonly used in the social media influence literature have expired as a result of the new algorithms used by the platforms and a new calculation method has been developed. In the empirical part of the study, firstly, the current situation of container shipping companies on social media platforms has been revealed. Then a content analysis of 4076 publicly-shared posts for a year was carried out on the companies' LinkedIn pages. This process was developed based on the "Social Media Communication Model" and "Word-of-Mouth (WOM) Psychological Motivation Theory". Accordingly, a theory-based approach consisting of brand strategy (company or product), message appeal (functional or emotional), selling strategy, and external information categories was preferred in coding the posts on the LinkedIn page of the companies. In addition, LinkedIn posts have been categorized in terms of media type, message richness, and level of interactivity. In the research, the highly engaged LinkedIn messages were determined through the engagement calculation method developed as a result of qualitative and quantitative studies, and an answer was sought to the question of whether the engagement rate (target variable) could be predicted with the message characteristics (input variables). In the development of the prediction model, two different learning algorithms were applied by using IBM Watson machine learning services. According to the results of the training and test data, the accuracy rate of the Chi-square Automatic Interaction Detector algorithm was found to be higher. Accordingly, the features that affect the engagement rate of the companies' LinkedIn messages are the level of interactivity, resharing, word count, message purpose, media type, and link usage, respectively. Overall, the results of this study show that it is possible to predict the success of social media communication strategies in terms of engagement level in the container shipping markets with message-oriented features.