Competitive Dynamics and Digital Innovation in the U.S. Foodservice Industry

The aim of this Thesis is to summarize the work of research done together with prof. Piccoli during an arc of 12 months, and still ongoing. This research wants to define how the competitive moves of firms, intended as the way companies try to improve their position on the market, impact on their financial results. After a description of the theoretical basis of our study, the main part of the thesis describes the method used to perform this research. In coherence with previous papers, we based our analysis on articles published by an industry-specific (in this case, the foodservice industry in the US Market) online newspaper. After extracting all the articles using a Python code, we performed a structured content analysis and divided all articles regarding the year 2021 following a precise and predefined code of categorization. Then, the team proceeded to categorize each move in different groups through the innovative methodology of Human Interpretable Topics (HIT), which will be explained in Paragraph 2.4, also considering whether the move leveraged on technology, or on the service of food delivery or was intended as a response to the Covid-19 pandemic crisis. In order to keep a high level of quality in the dataset, an inter-rater reliability score was constantly calculated, and measures of coordination were put in place in case of a lowering level of consensus during the validation. 4 The results will finally be inferred with financial data of companies in order to obtain useful insights on the dynamics of firms’ competition, however this step is due to be performed in the next step of the research, not considered in this thesis. It must be noted that the results of categorization showed in this thesis will form the Gold Standard Set, also called Truth, that will form a benchmarking subset of the whole corpus of data, allowing to assess the quality of future automation in the categorization of moves through a Topic Modeling algorithm and therefore leveraging on the data of the whole dataset (that comprises over 25.000 articles). Finally, in the conclusions many considerations on the pros and cons of this methodology are being described, also considering the role that innovation played in the U.S. Foodservice industry during the pandemic.