A Novel Web Scraping Technique Used for Phuket Travel Industry Decision Support System

The Internet can provide an individual with a broad area of facts and data sources. However, data available on the Internet also brings a great challenge with its volume, high-speed generation, and unorganized characteristics. Moreover, the quality and validity of Internet data vary from different sources. This leads to difficulties in collecting and processing Internet data. Nevertheless, several data collection techniques have recently been developed in order to convert entire business to consumer (B2C) and business to business (B2B) systems into well-organized data. This paper presents web scraping with Python for collecting information on accommodations, hospitals, restaurants, spas, and gyms in Phuket. The paper presents scraping processes both with and without data cleaning. The difference between these two types is that web scraping without data cleaning does not need data to be stored all the time, which can make the process shorter. However, this shorter algorithm may carry a risk in case of computer failure during processing which will result in data loss, but the risk is very unlikely when considering the speed of data processing which is worth more. The information gathered from web scraping in this research was stored in a data warehouse for further data analysis and decision support for stakeholders in Phuket.