[HTML][HTML] Forecasting: theory and practice
Forecasting has always been at the forefront of decision making and planning. The
uncertainty that surrounds the future is both exciting and challenging, with individuals and …
uncertainty that surrounds the future is both exciting and challenging, with individuals and …
Retail forecasting: Research and practice
This paper reviews the research literature on forecasting retail demand. We begin by
introducing the forecasting problems that retailers face, from the strategic to the operational …
introducing the forecasting problems that retailers face, from the strategic to the operational …
[HTML][HTML] Time-series forecasting of seasonal items sales using machine learning–A comparative analysis
There has been a growing interest in the field of neural networks for prediction in recent
years. In this research, a public dataset including the sales history of a retail store is …
years. In this research, a public dataset including the sales history of a retail store is …
Demand forecasting in supply chain: The impact of demand volatility in the presence of promotion
The demand for a particular product or service is typically associated with different
uncertainties that can make them volatile and challenging to predict. Demand …
uncertainties that can make them volatile and challenging to predict. Demand …
Which product description phrases affect sales forecasting? An explainable AI framework by integrating WaveNet neural network models with multiple regression
S Chen, S Ke, S Han, S Gupta, U Sivarajah - Decision Support Systems, 2024 - Elsevier
The rapid rise of many e-commerce platforms for individual consumers has generated a
large amount of text-based data, and thus researchers have begun to experiment with text …
large amount of text-based data, and thus researchers have begun to experiment with text …
Deep-learning model using hybrid adaptive trend estimated series for modelling and forecasting sales
Existing sales forecasting models are not comprehensive and flexible enough to consider
dynamic changes and nonlinearities in sales time-series at the store and product levels. To …
dynamic changes and nonlinearities in sales time-series at the store and product levels. To …
Optimal selection of heterogeneous ensemble strategies of time series forecasting with multi-objective programming
J Li, J Hao, QQ Feng, X Sun, M Liu - Expert Systems with Applications, 2021 - Elsevier
The excellent generalization performance of time series ensemble forecasting depends on
the accuracy and diversity of the individual models. In this paper, a heterogeneous …
the accuracy and diversity of the individual models. In this paper, a heterogeneous …
Forecasting seasonal demand for retail: A Fourier time-varying grey model
Seasonal demand forecasting is critical for effective supply chain management. However,
conventional forecasting methods face difficulties accurately estimating seasonal variations …
conventional forecasting methods face difficulties accurately estimating seasonal variations …
Post-script—Retail forecasting: Research and practice
This note updates the 2019 review article “Retail forecasting: Research and practice” in the
context of the COVID-19 pandemic and the substantial new research on machine-learning …
context of the COVID-19 pandemic and the substantial new research on machine-learning …
Data-driven demand forecast for O2O operations: An adaptive hierarchical incremental approach
Abstract Online-to-offline (O2O) refers to a new type of e-commerce that combines online
order acquisition and offline on-demand order fulfillment service. The daily demand for O2O …
order acquisition and offline on-demand order fulfillment service. The daily demand for O2O …