A Bayesian approach for predicting food and beverage sales in staff canteens and restaurants

Posch, Konstantin; Truden, Christian; Hungerländer, Philipp; Pilz, Jürgen

doi:10.1016/j.ijforecast.2021.06.001

Cited by 18 publications

(23 citation statements)

References 28 publications

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“…As previously mentioned, in recent years the number of meals served for out-of-home consumption has increased (FIPE, 2019;Pires et al, 2022) due to recreational reasons and the large number of people who eat in the workplace or student canteens. Contemporaneously, the amount of FW generated in this setting is growing exponentially, highlighting how this issue represents an important focus of research agenda (Principato et al, 2021b).…”

Section: Food Waste At the Food Service Levelmentioning

confidence: 99%

“…Bearing the above issues in mind, out-of-home FW plays an important role considering that there is a clear trend toward out-of-home consumption, probably due to urbanization, rising incomes, conviviality, lack of time to prepare meals, and work commitments (d'Angelo et al, 2020;Eurostat, 2018;Lorenz et al, 2017;Pires et al, 2022;Principato et al, 2021b). It is important to understand the factors that lead to FW and carefully monitor the quantity of FW generated out-of-home.…”

mentioning

confidence: 99%

“…To date, most of the studies on out-of-home FW have focused on restaurants, school canteens, hospitals, and social centers (Dias-Ferreira et al, 2015;Filimonau et al, 2020;Kowalewska et al, 2018;Liz et al, 2016;Oliveira et al, 2020;Papargyropoulou et al, 2016), while few studies have focused on company canteens (Jungbluth et al, 2016;Lassen et al, 2019;Lorenz et al, 2020Lorenz et al, , 2017Pires et al, 2022;Posch et al, 2022;Silvennoinen et al, 2019Silvennoinen et al, , 2015 by analyzing how better foodstuff management can be a win-win solution for company economic budgets as well as for environmental issues. This paper focuses on the out-of-home FW generated in a workplace canteen of an important Italian food production company, located in Pedrignano (Parma) in the Emilia-Romagna region, where many employees eat lunch every day.…”

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confidence: 99%

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Introducing digital tools for sustainable food supply management: Tackling food loss and waste in industrial canteens

Principato,

Marchetti,

Barbanera

et al. 2023

J of Industrial Ecology

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Reducing food waste is essential if we want to create a more sustainable food system, which is why halving per capita food waste by 2030 has been included in the UN Sustainable Development Goals. The main aim of this paper is to demonstrate that by using digital tools to monitor food provisioning and management within canteens, it is possible to achieve a more sustainable food service management within industrial companies and to reduce the overall quantity and environmental impacts of food preparation and consumption thus achieving economic benefits. Longitudinal 2018 and 2019 data collected from the canteen of a major Italian food production company were analyzed. The results showed that the amount of food lost and wasted has decreased over time, reaping important environmental benefits and illustrating specific differences between the food lost in meal preparation and the food left on employees’ plates. It is therefore important to implement education initiatives and to use digital tools to share food‐related data collected within companies among both employees and kitchen and catering staff in order to raise awareness of their behavioral strengths and weaknesses. From this perspective, new interventions at both kitchen and customer/worker levels are introduced and discussed.

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Section: Food Waste At the Food Service Levelmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Introducing digital tools for sustainable food supply management: Tackling food loss and waste in industrial canteens

Principato,

Marchetti,

Barbanera

et al. 2023

J of Industrial Ecology

View full text Add to dashboard Cite

show abstract

“…For the food and beverage service in restaurants, the missing value would be due to the fact that no customers ordered them (zero order) or the stores were closed (no service). To avoid causing the inferior model fits, such circumstances are suggested to remove missing records before modeling [49].…”

Section: Missing Data Processingmentioning

confidence: 99%

An Empirical Comparison of the Sales Forecasting Performance for Plastic Tray Manufacturing Using Missing Data

et al. 2022

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The problem of missing data is frequently met in time series analysis. If not appropriately addressed, it usually leads to failed modeling and distorted forecasting. To deal with high market uncertainty, companies need a reliable and sustainable forecasting mechanism. In this article, two propositions are presented: (1) a dedicated time series forecasting scheme, which is both accurate and sustainable, and (2) a practical observation of the data background to deal with the problem of missing data and to effectively formulate correction strategies after predictions. In the empirical study, actual tray sales data and a comparison of different models that combine missing data processing methods and forecasters are employed. The results show that a specific product needs to be represented by a dedicated model. For example, regardless of whether the last fiscal year was a growth or recession year, the results suggest that the missing data for products with a high market share should be handled by the zero-filling method, whereas the mean imputation method should be for the average market share products. Finally, the gap between forecast and actual demand is bridged by employing a validation set, and it is further used for formulating correction strategies regarding production volumes.

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“…It implied that the aggregate forecast is more accurate and the intervention could increase the forecast accuracy. Posch, Truden, Hungerländer, and Pilz (2021) pointed out that most researchers on forecasting are focused on aggregate forecasting, which forecast on weekly sales rather than forecast individual item per day. Hence, the company should require the trader to order on weekly basis.…”

Section: Comparison Demand Characteristics Before and After Interventionmentioning

confidence: 99%

The Use of Intervention Approach in Individual and Aggregate Forecasting Methods for Burger Patties: A Case in Indonesia

Neisyafitri

Ongkunaruk

2022

J AGRIB RURAL DEV RES

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The Indonesian beef consumption increases sharply during Ramadan and made a difference between supply and demand. The research aimed to study the demand pattern of burger patties and determine a suitable forecasting method compared between quantitative and intervention forecasting methods. The actual demand was intervened by experts based on reasons such as supply shortage, holidays, promotion, and government projects. The daily sales of burger patties were collected for a year. Then, the data were divided into training and testing data. Later, time-series forecasting was performed by software. Then, the best forecasting method for daily data was selected between Individual forecasting and Top-Down forecasting. Similarly, for weekly data, the best forecasting method was compared between aggregate forecasting and Bottom-Up forecasting. Then, repeat the process for the intervened sales data. The result revealed that the mean absolute percentage error was improved after intervention by about 3.64%-58.83%. The combination of quantitative and qualitative approaches improved forecast accuracy. In addition, the aggregate level or weekly sales forecast had higher forecast accuracy than the disaggregated level. The Bottom-Up forecast performs better than the aggregate forecast. Hence, we recommended the company plans based on weekly data and implement Every Low Price to reduce the demand fluctuation.

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A Bayesian approach for predicting food and beverage sales in staff canteens and restaurants

Cited by 18 publications

References 28 publications

Introducing digital tools for sustainable food supply management: Tackling food loss and waste in industrial canteens

Introducing digital tools for sustainable food supply management: Tackling food loss and waste in industrial canteens

An Empirical Comparison of the Sales Forecasting Performance for Plastic Tray Manufacturing Using Missing Data

The Use of Intervention Approach in Individual and Aggregate Forecasting Methods for Burger Patties: A Case in Indonesia

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