Application of artificial intelligence in food industry—a guideline
Artificial intelligence (AI) has embodied the recent technology in the food industry over the
past few decades due to the rising of food demands in line with the increasing of the world …
past few decades due to the rising of food demands in line with the increasing of the world …
Product returns management: a comprehensive review and future research agenda
Product return is a critical issue due to the uncertainty associated with the price, demand,
and quality of the product. Thus, businesses must improve their information transparency to …
and quality of the product. Thus, businesses must improve their information transparency to …
Machine-learning models for sales time series forecasting
BM Pavlyshenko - Data, 2019 - mdpi.com
In this paper, we study the usage of machine-learning models for sales predictive analytics.
The main goal of this paper is to consider main approaches and case studies of using …
The main goal of this paper is to consider main approaches and case studies of using …
Daily retail demand forecasting using machine learning with emphasis on calendric special days
J Huber, H Stuckenschmidt - International Journal of Forecasting, 2020 - Elsevier
Demand forecasting is an important task for retailers as it is required for various operational
decisions. One key challenge is to forecast demand on special days that are subject to vastly …
decisions. One key challenge is to forecast demand on special days that are subject to vastly …
Agri‐fresh produce supply chain management: a state‐of‐the‐art literature review
M Shukla, S Jharkharia - International Journal of Operations & …, 2013 - emerald.com
Purpose–The purpose of this paper is to present a literature review of the fresh produce
supply chain management (FSCM). FSCM includes the processes from the production to …
supply chain management (FSCM). FSCM includes the processes from the production to …
Attending to customer attention: A novel deep learning method for leveraging multimodal online reviews to enhance sales prediction
Although the impacts of helpful online reviews on customers' purchase decisions and
product sales have been widely investigated, review helpfulness has been commonly …
product sales have been widely investigated, review helpfulness has been commonly …
A hybrid seasonal autoregressive integrated moving average and quantile regression for daily food sales forecasting
NS Arunraj, D Ahrens - International Journal of Production Economics, 2015 - Elsevier
In the retail stage of a food supply chain, food waste and stock-outs occur mainly due to
inaccurate forecasting of sales which leads to incorrect ordering of products. The time series …
inaccurate forecasting of sales which leads to incorrect ordering of products. The time series …
A big data driven framework for demand-driven forecasting with effects of marketing-mix variables
This study aims to investigate the contributions of promotional marketing activities, historical
demand and other factors to predict, and develop a big data-driven fuzzy classifier-based …
demand and other factors to predict, and develop a big data-driven fuzzy classifier-based …
A survey of machine learning techniques for food sales prediction
G Tsoumakas - Artificial Intelligence Review, 2019 - Springer
Food sales prediction is concerned with estimating future sales of companies in the food
industry, such as supermarkets, groceries, restaurants, bakeries and patisseries. Accurate …
industry, such as supermarkets, groceries, restaurants, bakeries and patisseries. Accurate …
Optimizing the artificial neural network parameters using a biased random key genetic algorithm for time series forecasting
Abstract Artificial Neural Networks (ANN) is one of the most used methods in time series
forecasting. Mostly, it is hard to determine the design and weight parameters of ANNs by …
forecasting. Mostly, it is hard to determine the design and weight parameters of ANNs by …