Distributional regression for demand forecasting in e-grocery
Ulrich M, Jahnke H, Langrock R, Pesch R, Senge R (2019) Universität Bielefeld Working Papers in Economics and Management; 09-2018.
Bielefeld: Bielefeld University, Department of Business Administration and Economics.
Diskussionspapier
| Veröffentlicht | Englisch
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Autor*in
Ulrich, Matthias;
Jahnke, HermannUniBi;
Langrock, RolandUniBi;
Pesch, Robert;
Senge, Robin
Einrichtung
Abstract / Bemerkung
E-grocery offers customers an alternative to traditional brick-and-mortar
grocery retailing. Customers select e-grocery for convenience, making use of
the home delivery at a selected time slot. In contrast to brick-and-mortar
retailing, in e-grocery on-stock information for stock keeping units (SKUs)
becomes transparent to the customer before substantial shopping effort has
been invested, thus reducing the personal cost of switching to another
supplier. As a consequence, compared to brick-and-mortar retailing, on-stock
availability of SKUs has a strong impact on the customer’s order decision,
resulting in higher strategic service level targets for the e-grocery retailer. To
account for these high service level targets, we propose a suitable model for
accurately predicting the extreme right tail of the demand distribution, rather
than providing point forecasts of its mean. Specifically, we propose the
application of distributional regression methods— so-called Generalised
Additive Models for Location, Scale and Shape (GAMLSS)—to arrive at the
cost-minimising solution according to the newsvendor model. As benchmark
models we consider linear regression, quantile regression, and some popular
methods from machine learning. The models are evaluated in a case study,
where we compare their out-of-sample predictive performance with regard to
the service level selected by the e-grocery retailer considered.
Stichworte
Forecasting;
Inventory;
E-commerce;
Retailing
Erscheinungsjahr
2019
Serientitel
Universität Bielefeld Working Papers in Economics and Management
Band
09-2018
ISSN
2196-2723
Page URI
https://pub.uni-bielefeld.de/record/2932990
Zitieren
Ulrich M, Jahnke H, Langrock R, Pesch R, Senge R. Distributional regression for demand forecasting in e-grocery. Universität Bielefeld Working Papers in Economics and Management. Vol 09-2018. Bielefeld: Bielefeld University, Department of Business Administration and Economics; 2019.
Ulrich, M., Jahnke, H., Langrock, R., Pesch, R., & Senge, R. (2019). Distributional regression for demand forecasting in e-grocery (Universität Bielefeld Working Papers in Economics and Management, 09-2018). Bielefeld: Bielefeld University, Department of Business Administration and Economics. https://doi.org/10.4119/unibi/2932990
Ulrich, Matthias, Jahnke, Hermann, Langrock, Roland, Pesch, Robert, and Senge, Robin. 2019. Distributional regression for demand forecasting in e-grocery. Vol. 09-2018. Universität Bielefeld Working Papers in Economics and Management. Bielefeld: Bielefeld University, Department of Business Administration and Economics.
Ulrich, M., Jahnke, H., Langrock, R., Pesch, R., and Senge, R. (2019). Distributional regression for demand forecasting in e-grocery. Universität Bielefeld Working Papers in Economics and Management, 09-2018, Bielefeld: Bielefeld University, Department of Business Administration and Economics.
Ulrich, M., et al., 2019. Distributional regression for demand forecasting in e-grocery, Universität Bielefeld Working Papers in Economics and Management, no.09-2018, Bielefeld: Bielefeld University, Department of Business Administration and Economics.
M. Ulrich, et al., Distributional regression for demand forecasting in e-grocery, Universität Bielefeld Working Papers in Economics and Management, vol. 09-2018, Bielefeld: Bielefeld University, Department of Business Administration and Economics, 2019.
Ulrich, M., Jahnke, H., Langrock, R., Pesch, R., Senge, R.: Distributional regression for demand forecasting in e-grocery. Universität Bielefeld Working Papers in Economics and Management, 09-2018. Bielefeld University, Department of Business Administration and Economics, Bielefeld (2019).
Ulrich, Matthias, Jahnke, Hermann, Langrock, Roland, Pesch, Robert, and Senge, Robin. Distributional regression for demand forecasting in e-grocery. Bielefeld: Bielefeld University, Department of Business Administration and Economics, 2019. Universität Bielefeld Working Papers in Economics and Management. 09-2018.
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