Reduction of information asymmetry in e-commerce: the web scraping approach

The purpose of this work is to create an automated tool based on the web scraping technique that is designed to reduce the information asymmetry occurring in the buyer-seller relationship. The baseline environment for illustrating the problem of information asymmetry is also the automotive industry. The case of the largest automotive classifieds portal in Poland, which is OTOMOTO, was used in this study. This book is organized as follows. Chapter 1 outlines the theoretical background with specific attention dedicated to the issue of information asymmetry. Chapter 2 discusses the theoretical foundation of data extraction from internet resources (with particular focus on web scraping), their characteristics, particularly legal as well as ethical issues, and the necessity to deploy data collection technologies in the research setting. In chapter 3, a tool for data extraction created together with a suitable database to be able to harvest data from the OTOMOTO advertising site is discussed. The chapter also provides technical elements including the Python language upon which the constructed tool is predicated. Chapter 3 additionally covers a practical portion of the research in which a sample evaluation of the automotive industry in Poland is done, which draws on the data gathered from OTOMOTO advertisement portal with the assistance of the built web scraping tool. The book can be found useful for researchers, academics, and data scientists, offering scholarly insights into reducing information asymmetry in e-commerce through web scraping.