Demand Supply Matching Model Pada Permasalahan On-Demand Ride Service

Handojo, Andreas (2023) Demand Supply Matching Model Pada Permasalahan On-Demand Ride Service. Doctoral thesis, Institut Teknologi Sepuluh Nopember.

Text 02411660010003-Dissertation.pdf - Accepted Version Restricted to Repository staff only until 1 April 2025. Download (3MB) | Request a copy

Abstract

Dengan semakin berkembangnya sharing economy/collaborative consumption maka muncullah bisnis baru. Salah satu bisnis yang berkembang pesat adalah on-demand ride service/ride hailing. Perkembangan ini didorong oleh kebutuhan sarana transportasi sehari-hari masyarakat perkotaan yang semakin meningkat. Keunikan dari bisnis ini adalah passenger dan driver dapat muncul dimana dan kapan pun dengan menggunakan aplikasi layanan jasa transportasi. Hal ini, tentunya menimbulkan ketidakpastian demand dan supply yang tinggi. Pihak perusahaan penyedia jasa kemudian melakukan penunjukan/assignment terhadap driver yang akan memenuhi order tersebut. Permasalahan lain adalah faktor jarak dan waktu tempuh dari driver menuju ke lokasi penjemputan. Semakin tinggi jarak dan waktu tempuh maka passenger akan menunggu lebih lama untuk mendapatkan layanan. Selain itu, dibutuhkan penentuan prioritas driver dan passenger yang memiliki keaktifan tinggi dalam menggunakan layanan. Saat ini belum terdapat penelitian yang mengatur penugasan dengan meminimasi total jarak yang ditempuh oleh driver dalam melakukan penjemputan penumpang serta mengakomodasikan kinerja historis driver dan perilaku passenger. Selain itu, belum terdapat penelitian yang mengkomodasi faktor durasi penjemputan, jarak penjemputan, driver rating, driver cancelation rate, dan meminimasi waktu tunggu passenger. Hasil pengujian yang dilakukan menunjukkan bahwa model multi layer recency frequency monetary mampu memprioritaskan pilihan driver dan passenger yang memiliki tingkat keaktifan tinggi dalam menggunakan layanan sehingga dapat menciptakan fairness terhadap pengguna lama maupun baru. Model driver passenger matching with considering driver total distance in certain time horizon dengan menggunakan metode goal programming mampu melakukan matching Pada penelitian ini dilakukan usulan penentuan prioritas keaktifan dalam menggunakan layanan dengan menggunakan metode multi layer recency frequency monetary, sehingga dapat menjaga tingkat keadilan/fairness terhadap pengguna layanan lama maupun baru, dengan demikian dapat menjaga tingkat kepuasan dari passenger dan driver terhadap pelayanan dari provider jasa layanan. Adapun proses matching dilakukan dengan menggunakan metode goal programming yang mampu melakukan pengambilan keputusan dengan mempertimbangkan berbagai macam faktor dengan tujuan meminimalisasi total jarak yang ditempuh oleh driver, pemerataan kesempatan mendapat muatan oleh driver, serta meminimasi waktu tunggu passenger. v antara driver dan passenger dengan mempertimbangkan faktor durasi penjemputan, jarak penjemputan, serta meminimasi total jarak tempuh dari driver ke pick up location dalam kurun waktu tertentu.
===============================================================================================================================
With the development of the sharing economy/collaborative consumption, new businesses emerge. One of the fast growing businesses is on-demand ride service/ride hailing. This development is driven by the increasing need for daily transportation facilities in urban communities. The uniqueness of this business is that passengers and drivers can appear anywhere and anytime by using a transportation service application. This, of course, creates high demand and supply uncertainties. The service provider company then makes an assignment for the driver, who will fulfill the order. Another problem is the distance factor and the travel time from the driver to the pick up location. The higher the distance and travel time, the longer the passenger will wait to get service. In addition, it is necessary to determine the priority of drivers and passengers who have high activity in using the service. Currently, there is no research that regulates assignments by minimizing the total distance traveled by drivers in picking up passengers and accommodating the historical performance of drivers and passenger behavior. In addition, there is no research that accommodates the factors of pickup duration, pickup distance, driver rating, driver cancellation rate, and minimizing passenger waiting time. In this research, it is proposed to determine the priority of activeness in using the service using the Multi Layer Recency Frequency Monetary method, so that it can maintain the level of fairness towards old and new service users, thereby maintaining the level of satisfaction of passengers and drivers with the services of service providers. The matching process is carried out using the Goal Programming method, which is capable of making decisions by considering various factors with the aim of minimizing the total distance traveled by drivers, equalizing opportunities for drivers to get loads, and minimizing passenger waiting time. The results of the tests carried out show that the Multi Layer Recency Frequency Monetary model is able to prioritize the choice of drivers and passengers who have a high level of activity in using the service so as to create fairness for old and new users. The Driver Passenger Matching Model with Considering Driver Total Distance in Certain Time Horizon using the goal programming method is capable of matching between drivers and passengers by considering the factors of pick-up duration, pick-up distance, and minimizing the total distance traveled from the driver to the pick-up location within a certain time.

Item Type:	Thesis (Doctoral)
Uncontrolled Keywords:	On-Demand Ride Sharing, Ride Hailing, Demand Supply Uncertainty, Multi Layer Recency Frequency Monetary, Goal Programming
Subjects:	H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management H Social Sciences > HD Industries. Land use. Labor > HD9980.5 Service industries--Quality control.
Divisions:	Faculty of Industrial Technology and Systems Engineering (INDSYS) > Industrial Engineering > 26001-(S3) PhD Thesis
Depositing User:	Andreas Handojo
Date Deposited:	20 Feb 2023 09:00
Last Modified:	20 Feb 2023 09:00
URI:	http://repository.its.ac.id/id/eprint/97642

Actions (login required)

View Item