Global Network Economy Society: Information Needs on the Ethical Framework and Trust in Transportation and Logistics Business among Users of the Google Search Engine
Purpose: Diagnosis of information needs in the Internet network on the ethical framework and trust in the transportation and logistics business. Design/Methodology/Approach: The article uses the methods of data analysis, topic mining, data mining, trend exploration and spatial differentiation. In addition, artificial intelligence was used to identify cause-effect relationships (Granger causality) and statistical methods, descriptive statistics, Augmented Dickey-Fuller test for data stationarity and Ljung-Box test for autocorrelation. Practical Implications: Research results could be useful in three dimensions. First, they could be useful for profiling information on trust and ethical frameworks depending on the user’s country and specific point in time (fashions). Secondly, they could serve to identify areas to improve awareness in this regard. Third, they could predict the demand for information based on delayed searches and linkages between issues, which is important from the information market’s point of view. Originality/Value: The originality of the study lies in filling the cognitive gap in the diagnosis of information needs in terms of the ethical framework and trust in the transportation and logistics business. Moreover, the study noted that the information needs of this narrow group of users of information on a given topic do not disappear once they are satisfied, and there is a delayed relationship or autocorrelation between the main issues. This means that information needs are complementary to each other, are seasonal and delayed, topics are being drilled and interest deepened.