Modelling the Impact of Mobile Application Adoption on the Taxi Demand: An Application of a System Dynamics Approach - Abdul Ghani, Muhamad Syafiq; Abidin, Norhaslinda Zainal; Rahman, Rosshairy Abd; Wibowo, Antoni; Alwi, Azatuliffah (International Journal of Interactive Mobile Technologies (iJIM), 2021)
The improvement of technology brings a significant impact on transportation industries. The taxi industry has undergone tremendous changes with the existent of e-hailing service in the industry. Due to the introduction of mobile applications, e-hailing service takes part to compete in the market. The government has given priority to overcome the problem by introducing travel demand strategies that focus on mitigating the demand competition between the taxi and e-hailing services. One of the strategies is the adoption of a mobile application in taxi service. This paper aims to develop a system dynamics model to analyse mobile application adoption’s impact on customers’ demand on the mode share of taxi and e-hailing services as a measured output. System dynamics is a decision-experimentation method that creates a learning environment in which policymakers gain a better understanding of how the system will respond to their decisions and the potential unintended consequences of decisions. With the developed SD model, the feedback relations between mobile application adoptions on the output of taxi demand can be observed. Furthermore, the demand competition between the taxi and e-hailing services can be minimised using this SD model. The result shows that, by implementing the usage of the mobile application in taxi services, more users will be attracted to use the taxi service. With that service option, users will shift their attraction from e-hailing to taxi service, which is then able to minimise the demand competition. This research can benefit policymakers and authorities in the department of transportation to serve as a planning tool so that the demand of taxi and e-hailing services in Malaysia with the adoption of mobile application in taxi service can be predicted.