How Data Science Can Support Industry Analysis: The Case of Smartphones

The following work presents a comprehensive study of the smartphone industry, with a focus on the development of an automated tool for the monitoring of the market and the recognition of direct competing products. The thesis begins with an overview of the smartphone market. The study then investigates the attractiveness of the market in the framework of Porter’s five competitive forces model, and different management styles different companies should implement to deal with the high level of environmental turbulence that characterizes this sector. The Ansoff model for the response to turbulent environments is used to further support this investigation. On the basis of said analysis, it is then presented the development of a Python programmed script that uses web scraping and a clustering algorithms to collect the technical specifications of a large number of the smartphone available on the market and proceeds to cluster the devices in order to identify similar and directly competing products. The study will show how the industry is shaped and present the main critical points that small and big firm need to deal with in order to thrive in this industry. The results will present the study of the industry in the framework of the two aforementioned models and the proof of concept of a practical tool that aims at supporting firms in dealing with the findings given by the application of said models. This thesis contributes to the understanding of the smartphone market by offering a holistic view of its current state and potential trends for the future. The application of such models ultimately point towards the crucial importance of the constant and consistent monitoring of the market as a defense towards the constant evolution and unpredictability of the Smartphone industry.