Thesis Archive
Modelling the impact of front and back end service delivery strategies on multi-stage customer waiting times and wastes generated in a quick service restaurant (2011)
David
Gonzales
Padilla
Abstract:
-In present days, there is a growing demand for many commodities that are served at an instant including food which explains the developments in the fast food industry. There are two main challenges in operating quick service restaurants (QSR) namely managing the customer waiting time and generated wastes. However, these are two conflicting goals as suggested in the literatures. Previous studies in QSR often treat front and back-end as two separate areas which often deal with each challenge one at a time. This study aims to close this gap by determining the effect of front-end strategies, back-end strategies, and its interaction in customer waiting time and food wastes in order to eliminate unrealistic assumptions. A systems perspective considering both front- and back-end is necessary in order to understand the impact of operational strategies in the real performance of a typical QSR.
The customer waiting times considered were average waiting time to line, to receive the order and to be seated. The study modeled the different back-end strategies including made-to-stock (MTS), assemble-to-order (ATO), made-to-order (MTO) with the front-end strategies which are the waiting number policy line busting and the combination of both. The model was developed and validated by dividing it into four components namely customer arrival, order arrival, food production and meal consumption. Arena 10.0 was used to simulate the QSR system and DX 6.0 for the analysis of the relationships of variables.
The impact of the service delivery strategies both in the front- and back-end of a QSR system with multi-stage customer waiting times and wastes generated were identified in this study. It was found out that front-end strategies only decrease the customer waiting time to reach the counter but not the total customer waiting time because it increase the other stages of waiting. Introducing bundled items into a QSR system also increases service time but decreases the total wastes generated. Finally, adjusting the reorder point to a lower level during peak periods reduces wastes.