Parameter identification for the decision model of uncertainty price competition in food delivery services

Abstract

The sharing economy innovation has created a new service industry sector, the ride-hailing industry. Government regulations regarding minimum tariffs change the competition map and uncertainty in that industry. This has led to predatory pricing, switching costs and pre-emptive duopoly. This study aims to determine the parameters that can affect the decision model in the uncertainty of price competition through factorial experiments. This study was conducted on two ride-hailing companies, which currently lead market share, thus establishing a duopoly market. There are many services offered by these companies. This study focuses on investigating food delivery services, which are one of the stable services during the Covid-19 pandemic. The approach that will be used in this research is a factorial experiment to determine what parameters can affect price determination with several uncertainty cases. The result is the identification of the optimal decision model, both parameters and levels in pricing. The implication of this study is fair competition for the welfare of society and the country.