Loading...

Media is loading
 

Paper Number

1549

Paper Type

Complete

Description

IT-enabled food-delivery platforms increase restaurants' catchment area and reduce search costs for consumers. The former allows restaurants to pool their risks and decrease noise in demand, whereas the latter increases competition and noise in demand. Overall, it is unclear how these competing factors affect restaurants' ability to forecast their demand -a critical factor for profitability. In this paper, we empirically investigate the impact of IT-enabled food-delivery platforms on restaurants' demand forecast error. Using detailed transaction-level datasets, we find that a 10 percentage point increase in dependence on food-delivery platforms leads to a 2.83% increase in overall forecast error. We also find that the majority of increase in overall error is due to an increased error in forecasting intra-day demand "pattern", and a smaller portion is due to error in forecasting inter-day demand "amplitude". Based on our findings, we offer suggestions for restaurants on managing their relationship with IT-enabled food-delivery platforms.

Comments

08-Sharing

Share

COinS
 
Dec 12th, 12:00 AM

An Unintended Consequence of Platform Dependence: Empirical Evidence from IT-enabled Food-Delivery Platforms

IT-enabled food-delivery platforms increase restaurants' catchment area and reduce search costs for consumers. The former allows restaurants to pool their risks and decrease noise in demand, whereas the latter increases competition and noise in demand. Overall, it is unclear how these competing factors affect restaurants' ability to forecast their demand -a critical factor for profitability. In this paper, we empirically investigate the impact of IT-enabled food-delivery platforms on restaurants' demand forecast error. Using detailed transaction-level datasets, we find that a 10 percentage point increase in dependence on food-delivery platforms leads to a 2.83% increase in overall forecast error. We also find that the majority of increase in overall error is due to an increased error in forecasting intra-day demand "pattern", and a smaller portion is due to error in forecasting inter-day demand "amplitude". Based on our findings, we offer suggestions for restaurants on managing their relationship with IT-enabled food-delivery platforms.

When commenting on articles, please be friendly, welcoming, respectful and abide by the AIS eLibrary Discussion Thread Code of Conduct posted here.