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

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Opis treści

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.

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

Introductory word 7

Chapter 1. E-commerce in the face of information asymmetry 11
1.1. Uncertainty and information asymmetry in the digital economy 11
1.2. Challenges of the e-commerce sector 18
1.3. Advertisement portal as an e-commerce tool 24

Chapter 2. Web scraping 27
2.1. The need to implement automated data acquisition tools 27
2.1.1. Data and information as a basis of the notion of web scraping 27
2.1.2. Web scraping as a medium for obtaining information in a big data world 30
2.2. Properties of data acquisition tools 36
2.3. Use of web scraping in practice 40
2.3.1. Strengths and opportunities of data content mining 40
2.3.2. Legality and ethical use of web scraping 41

Chapter 3. Designing a web scraping tool 48
3.1. OTOMOTO – the largest Polish automotive classifieds portal 48
3.1.1. Structure of the portal 49
3.1.2. A quick look at the OTOMOTO regulations 52
3.2. Preparation for a web scraping tool project 54
3.2.1. Conceptual work. Description of the algorithm’s operation. Process diagram 54
3.2.2. Preparation of the technical environment 61
3.3. Web extractor – design and programmatic implementation 64
3.3.1. Structure of the project in the PyCharm environment 65
3.3.2. Program communication with the user – collecting information 66
3.3.3. Creation of the list of offers’ URL 79
3.3.4. Retrieving hyperlinks to particular advertisements 82
3.3.5. The process of the factual web scraping 85
3.3.6. Exporting scraped results to a Microsoft Excel spreadsheet 93
3.3.7. Program operation in practice with a sample analysis 95
3.4. Discussion 101

Conclusions 105
Appendix 107
References 111
List of Figures 127
List of Tables 129