ANALYSIS OF REVENUE MODEL AND COSTLY PRICE ADJUSTMENT ON TASTEIT.BKS

• Main Author: Victoria Pravitama, Elisabet
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/67721
• Institution: Institut Teknologi Bandung

Revenue management is the adoption of a data-based approach to predicting consumer behavior to maximize revenue which has been developed into tactics and strategies. From these results it can be estimated the number of orders, purchases and even product capacity that must be made. Revenue management also uses a discount system, costly price adjustment and soft customer model as one method. This final project makes a deterministic model as a revenue model using multiple linear regression betweet Tasteit.bks and competitors. As independent variables, normal prices, discount prices, and peak season factors or monthly order levels are used, while as a response variable, daily order levels are used. From the several combinations of independent variables used, the best results for the prediction of the order level are stated as follows: ????(????????????,????????????)=1,3301?9,541.10?6????????????+2,2894.10?6????????????+0,747????????. The stochastic model will use revenue and the ratio between the revenue compared to the highest revenue as a variable. From the stochastic model, it is found that the model predicts well only for the case of competitor one, namely Pleaseletme.eat. The Optimal Pricing Model is used in making price adjustments by using the Mann Whitney test first. The results of Mann Whitney test are the deterministic model which paying attention to the peak season doesn’t have a significant difference from the original data. From the Optimal Pricing Model, it is found that the lowest price model results in Tasteit.bks occurs through equations?????????????12+37197,34356 in the first case study with Pleaseletme.eat and ?????????????12+12169,95476 in the second case study with Macaronischotel_Bekasi. Ordering Limit Model that is built is expressed as linear regression using the order rate as an independent variable and the capacity of the discount price as a response so that the effectiveness of the discount system will be seen. The result of the model is the discount system used is not effective. The simulation is also done to get a limit order of discounted price. The results on Tasteit.bks are obtained as in the following equation ????(????????????????????????)=6,90+24,243????????????????????????