A novel pricing algorithm using supervised machine learning for Malaysia's E-hailing.

In the present era of the Fourth Industrial Revolution, i.e., 4IR or Industry 4.0, the digital world has witnessed enormous technological advancement. Artificial Intelligence (AI), Machine learning (ML) such as supervised learning (SL), unsupervised learning (USL), semi-supervised learning, and reinforcement learning (RL) are the most exciting recent technologies in today's world. Learning algorithms such as web search engines like Google or Yahoo, E-Mail filtering, Social Media, Airlines, E-hailing ride/price matching are the most valuable features of ML in our daily lives. The e-hailing, which is a process of ordering a cab or taxi online through a digital app, relies on machine learning to perform ride fare calculations. This paper briefly explains how e-hailing providers build dynamic pricing using reinforcement learning and associated problems in the existing pricing algorithm. Often dynamic pricing terms are unfair/discriminated pricing, and it remains controversial amongst consumers. The article discusses how supervised learning can help address pricing issues linked to the dynamic pricing algorithm's reinforcement learnings. The expected outcome of this paper is to help play a reference in creating a practical solution that can resolve pricing issues that float around dynamic pricing algorithms. [ABSTRACT FROM AUTHOR]