TY - GEN
T1 - Price cut policy on food delivery service application using dynamic pricing model to maximize profit on restaurant
AU - Napitupulu, Grace Elfrida Sylvana
AU - Ridwan, Ari Yanuar
AU - Santosa, Budi
N1 - Publisher Copyright:
© 2023 Author(s).
PY - 2023/3/14
Y1 - 2023/3/14
N2 - Dynamic pricing is a pricing tool used to adjust prices to respond to market fluctuation and demand uncertainty. Inside the restaurant industry, common dynamic pricing strategy adopted is the pricing cut policy. The purpose of this study is to propose a pricing cut policy obtained from dynamic pricing model optimization in order to maximize profit on a restaurant through a partnership with online food delivery services. In the first phase, we determine menu items that the pricing cut will be applied to using menu engineering, one of the methods used in the restaurant industry to evaluate menu items performance. In the next phase, we forecast demand for the next period by modeling the effect of price on sales history. In the third phase, the demand model is substituted into the dynamic pricing model, which is then optimized by using non-linear programming method. The optimization result shows that the proposed model can increase restaurant revenue up to 28% compared to historical revenue. This study can be used as a tool to make decisions related to pricing on online food delivery services.
AB - Dynamic pricing is a pricing tool used to adjust prices to respond to market fluctuation and demand uncertainty. Inside the restaurant industry, common dynamic pricing strategy adopted is the pricing cut policy. The purpose of this study is to propose a pricing cut policy obtained from dynamic pricing model optimization in order to maximize profit on a restaurant through a partnership with online food delivery services. In the first phase, we determine menu items that the pricing cut will be applied to using menu engineering, one of the methods used in the restaurant industry to evaluate menu items performance. In the next phase, we forecast demand for the next period by modeling the effect of price on sales history. In the third phase, the demand model is substituted into the dynamic pricing model, which is then optimized by using non-linear programming method. The optimization result shows that the proposed model can increase restaurant revenue up to 28% compared to historical revenue. This study can be used as a tool to make decisions related to pricing on online food delivery services.
UR - http://www.scopus.com/inward/record.url?scp=85151503641&partnerID=8YFLogxK
U2 - 10.1063/5.0119146
DO - 10.1063/5.0119146
M3 - Conference contribution
AN - SCOPUS:85151503641
T3 - AIP Conference Proceedings
BT - 2nd International Conference on Design, Energy, Materials and Manufacture 2021, ICDEMM 2021
A2 - Asral, null
A2 - Ginting, Yogi Rinaldi
A2 - Negara, Dewa Ngaken Ketut Putra
A2 - Akbar, Musthafa
A2 - Syafri, null
A2 - Anuar, Kaspul
A2 - Badri, Muftil
PB - American Institute of Physics Inc.
T2 - 2nd International Conference on Design, Energy, Materials and Manufacture 2021, ICDEMM 2021
Y2 - 4 August 2021
ER -