Abstract
The primary purpose of companies is to create value. Companies use competitive analysis to develop their value proposition. Performing this analysis manually is a time-consuming task. Automating the process of identifying and expanding value proposition, as well as categorizing it, would bring benefits for industries. This paper aims to summarize and systematize the results of previous research on a mechanism for automatically identifying companies' value proposition. This is a novel task and with this work the author hopes to show feasibility and set a baseline. To narrow down the task, air transportation domain was selected. The goal of the research was to obtain insights and systemize values; to achieve it, the author utilized a bottom-up data-driven approach. The first step was to create a corpus of values. 96 respondents conducted a survey with open-end questions; 796 start-ups were identified and 96 annotators labelled start-ups' landing pages by annotating values. The next step was structuring data for a deeper understanding of values by examining annotations and organizing values into taxonomies. The practical use of the results includes machine learning training material for automation of value-related tasks.