Varun Karamshetty, Michael Freeman, Sameer Hasija
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. © 2022 International Conference on Information Systems, ICIS 2022: "Digitization for the Next Generation". All Rights Reserved.
National University of Singapore, Singapore; INSEAD, Singapore
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