2019
DOI: 10.1016/j.procir.2019.02.042
|View full text |Cite
|
Sign up to set email alerts
|

Demand forecasting in restaurants using machine learning and statistical analysis

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

0
22
0
1

Year Published

2020
2020
2023
2023

Publication Types

Select...
5
2

Relationship

0
7

Authors

Journals

citations
Cited by 55 publications
(23 citation statements)
references
References 0 publications
0
22
0
1
Order By: Relevance
“…The comparison of ML techniques to forecast curated restaurant sales is a common research question and can be seen in several recent works [14][15][16][17]. Two additional recent, non-restaurant forecasting with ML problems are also examined [11,18].…”
Section: Literature Reviewmentioning
confidence: 99%
See 3 more Smart Citations
“…The comparison of ML techniques to forecast curated restaurant sales is a common research question and can be seen in several recent works [14][15][16][17]. Two additional recent, non-restaurant forecasting with ML problems are also examined [11,18].…”
Section: Literature Reviewmentioning
confidence: 99%
“…The first important difference in researched methods is the forecasting horizon window used. Many papers either used an unclear horizon window or made forecasts of only one time step at a time [14][15][16][17][18]. Only one paper increased the forecast horizon beyond one time step [11], so we consider forecasting one week of results the main contribution of this research.…”
Section: Literature Reviewmentioning
confidence: 99%
See 2 more Smart Citations
“…• Sales forecasting (Lasek et al 2016;Xinliang and Dandan 2017) and revenue management (Noone and Maier 2015) • Demand prediction and production planning in quick service restaurants (Noone and Coulter 2012) • Demand forecasting in restaurants (Tanizaki et al 2019) However, the abilities of AI and robots in performing human tasks varies depending on the specific task and the required skills for mastering the activities of this task. The potential of AI technologies should not be assessed by looking at the occupation level.…”
Section: Automation Potentialmentioning
confidence: 99%