A Novel Approach for Decision Support in Uncertain Environments: The Case of Identifying Similar News Tickers in Natural Gas Trading

As the natural gas market is characterized by price volatility and uncertainty, the participants need in using founded information for decision making in order to manage risks and profits is immense. Analyzing the information content of news tickers can provide additional information about the environment. This paper concerns the features of a novel method that encourages price prognosis in gas trading. By knowing how the market has developed regarding a certain former situation, this knowledge can be used in predicting the future market by associating a similar former state to a present state. Thereby, uncertainty about future might be reduced. Framing the research in design science, we use task-technology-fit theory and technology-acceptance-model to identify requirements and to appraise the artifact. The novel method integrates structured and unstructured data in decision support.