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Open accessJournal ArticleDOI: 10.1016/J.SEPS.2021.101041

Food waste reduction and economic savings in times of crisis: The potential of machine learning methods to plan guest attendance in Swedish public catering during the Covid-19 pandemic

02 Mar 2021-Socio-economic Planning Sciences (Pergamon)-pp 101041
Abstract: Food waste is a significant problem within public catering establishments in any normal situation. During spring 2020 the Covid-19 pandemic placed the public catering system under greater pressure, revealing weaknesses within the system and generation of food waste due to rapidly changing consumption patterns. In times of crisis, it is especially important to conserve resources and allocate existing resources to areas where they can be of most use, but this poses significant challenges. This study evaluated the potential of a forecasting model to predict guest attendance during the start and throughout the pandemic. This was done by collecting data on guest attendance in Swedish school and preschool catering establishments before and during the pandemic, and using a machine learning approach to predict future guest attendance based on historical data. Comparison of various learning methods revealed that random forest produced more accurate forecasts than a simple artificial neural network, with conditional mean absolute prediction error of 0.15 for the trained dataset. Economic savings were obtained by forecasting compared with a no-plan scenario, supporting selection of the random forest approach for effective forecasting of meal planning. Overall, the results obtained using forecasting models for meal planning in times of crisis confirmed their usefulness. Continuous use can improve estimates for the test period, due to the agile and flexible nature of these models. This is particularly important when guest attendance is unpredictable, so that production planning can be optimized to reduce food waste and contribute to a more sustainable and resilient food system.

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Topics: Attendance (57%), Food systems (52%)
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5 results found


Journal ArticleDOI: 10.1016/J.JCLEPRO.2021.128721
Viachaslau Filimonau1, Riaz Uddin1Institutions (1)
Abstract: Past research on food waste in foodservices has focused on restaurants in general and failed to examine how/if the ownership model of a restaurant business correlates with the approaches to food waste management adopted in-house. This study employs the qualitative research methods to explore how the challenge of food waste is managed in (inter)national chain-affiliated and (local) independent restaurants. The study finds that chain-affiliated businesses routinely measure food waste and have developed consistent measures to prevent and mitigate its occurrence. In contrast, independent restaurants, particularly those specializing in ethnic cuisine, take no measurements of food waste and manage it on an ad-hoc basis. (Inter)national strategies on food waste prevention and mitigation in restaurants should therefore focus on independent foodservice operators as this is where the largest reduction potential rests. This study offers preliminary insights on the role of various stakeholders within the broader food system whose engagement is critical for effective food waste prevention and mitigation in restaurants.

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Topics: Food systems (60%), Food waste (51%)

2 Citations


Open accessJournal ArticleDOI: 10.1016/J.SEPS.2021.101145
Abstract: This study provides an XGBoost model to characterize the environmental orientation of innovative firms. This novel approach, using state-of-the-art machine learning methodologies and multiple recognized drivers of eco-innovation, provides solid empirical support for the understanding of the mechanisms that are crucial for firms' transition to a low-carbon economy. Although many drivers have been considered to affect firms’ eco-innovation, our feature selection process using the BorutaShap algorithm demonstrates that few aspects are truly relevant. Furthermore, analyzing a tree surrogate of the final model, our study explores the different paths or combinations of aspects that consistently lead to a specific eco-innovation orientation. The accuracy of the model and the large and complete spectrum of innovative companies in the sample contribute to the generalizability of the results. This study is particularly relevant because the main drivers of firms’ eco-innovative orientation depend on their innovative behavior, indicating that the managerial and policy work has to be directed to raising awareness of the different externalities derived from innovation. On one side, policy regulations should continue to pressure firms with environmental standards. On the other side, managers can stimulate the creation of a corporate innovative culture oriented toward improving operational efficiency (reducing unnecessary costs), improving the workplace environment, and focusing on new customer demands, which, in essence, will guide the organization to be more environmentally and socially responsible.

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1 Citations


Open accessJournal ArticleDOI: 10.1016/J.RESCONREC.2021.105997
Abstract: Food waste is a problem that needs to be addressed to achieve sustainable development. There is a need for interventions that can reduce food waste, including in organisations already aware of the food waste problem. Swedish school canteens have experience of food waste reduction, but need tools to achieve further reductions. This study tested four interventions (tasting spoons, awareness campaign, a plate waste tracker and a guest forecasting tool) designed to reduce food waste in school canteens. Each intervention was introduced in two school canteens, while seven school canteens acted as a reference group. The interventions were compared with baseline food waste before the intervention and with the reference group. All interventions reduced total food waste (by 6 to 44 g/guest) compared with the baseline, but the reference group also reduced its food waste. The awareness campaign reduced plate waste most, by 13 g per portion, which was 6 g/portion more than the plate waste reduction in the reference group. The forecasting and plate waste tracker interventions reduced serving waste most, by 34 and 38 g/portion, compared with 11 g/portion in the reference group. Some interventions also had an effect on waste fractions they were not designed to target, affecting the total waste by shifting the waste. Interventions should always be seen in a context and be implemented in combinations that increase overall sustainability. Thus forecasting is an effective way to reduce serving waste, plate waste tracker and awareness campaign are effective tools to reduce plate waste in school canteens.

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Topics: Food waste (52%)

Open accessJournal ArticleDOI: 10.1016/J.DIB.2021.107138
13 May 2021-Data in Brief
Abstract: This data article describes 34 datasets, compiled into one table, describing guest attendance at lunch meal servings in Swedish public schools and preschools. Fifteen of the schools and all 16 of the preschools covered belong to one municipality, while the remaining three schools belong to two other municipalities, all located in central Sweden. Data on number of plates was used as a proxy of the number of guests eating lunch. Number of used plates was recorded from late August 2010 to early June 2020, i.e. covering the period both before and during the initial phase of the Covid-19 pandemic, so that making possible to evaluate changes in guest attendance during the pandemic. Since these were real data, all data elements pertaining to exact canteens or staff identity have been removed. There is a scarcity of real business data for scientific and educational purposes, so these datasets can play an important role in research and education within catering management, consumption pattern analysis, machine learning, data mining and other fields.

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Topics: Attendance (56%)

Book ChapterDOI: 10.1016/BS.AF2S.2021.07.002
Zuhud Rozaki1Institutions (1)
01 Jan 2021-
Abstract: The Covid-19 pandemic has been a significant health crisis and has the possibility for further crises. The pandemic has also brought many challenges to food security issues in Indonesia. The country indeed has a long history of food security, and rice, as the staple food, has become the main focus of food security policies. As a country known for its agriculture, Indonesia is still struggling to reach food self-sufficiency due to some classic problems in agriculture such as agricultural land-use change, human resources, inputs, etc. Considering that local production cannot meet the national food demand, food imports were arranged. Nevertheless, this policy is not suitable for an extended period due to the risks of food import dependency. Speaking of food security challenges in the post-Covid-19 pandemic, Indonesia's high focus on rice, classic problems in agriculture, supportive regulation, and education are regarded as the main concerns. Beyond these challenges, however, food security opportunities also appeared, such as increasing awareness of food waste, strong social capital, and return to local potential to support the food security agenda. The pandemic has made many parties realize that food security issues are important and need more attention, especially in terms of how the four main aspects of food security can be met during and after the crisis.

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Topics: Food security (74%), Staple food (58%), Agriculture (55%)
References
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42 results found


Open accessBook
01 Jan 2001-
Topics: Algorithmic learning theory (60%), Semi-supervised learning (55%), Ensemble learning (54%) ... show more

18,681 Citations


Open access
01 Jan 2007-
Abstract: Recently there has been a lot of interest in “ensemble learning” — methods that generate many classifiers and aggregate their results. Two well-known methods are boosting (see, e.g., Shapire et al., 1998) and bagging Breiman (1996) of classification trees. In boosting, successive trees give extra weight to points incorrectly predicted by earlier predictors. In the end, a weighted vote is taken for prediction. In bagging, successive trees do not depend on earlier trees — each is independently constructed using a bootstrap sample of the data set. In the end, a simple majority vote is taken for prediction. Breiman (2001) proposed random forests, which add an additional layer of randomness to bagging. In addition to constructing each tree using a different bootstrap sample of the data, random forests change how the classification or regression trees are constructed. In standard trees, each node is split using the best split among all variables. In a random forest, each node is split using the best among a subset of predictors randomly chosen at that node. This somewhat counterintuitive strategy turns out to perform very well compared to many other classifiers, including discriminant analysis, support vector machines and neural networks, and is robust against overfitting (Breiman, 2001). In addition, it is very user-friendly in the sense that it has only two parameters (the number of variables in the random subset at each node and the number of trees in the forest), and is usually not very sensitive to their values. The randomForest package provides an R interface to the Fortran programs by Breiman and Cutler (available at http://www.stat.berkeley.edu/ users/breiman/). This article provides a brief introduction to the usage and features of the R functions.

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Topics: Random forest (69%), Overfitting (52%), Ensemble learning (52%) ... show more

12,765 Citations


Journal ArticleDOI: 10.1126/SCIENCE.1111772
22 Jul 2005-Science
Abstract: Land use has generally been considered a local environmental issue, but it is becoming a force of global importance. Worldwide changes to forests, farmlands, waterways, and air are being driven by the need to provide food, fiber, water, and shelter to more than six billion people. Global croplands, pastures, plantations, and urban areas have expanded in recent decades, accompanied by large increases in energy, water, and fertilizer consumption, along with considerable losses of biodiversity. Such changes in land use have enabled humans to appropriate an increasing share of the planet’s resources, but they also potentially undermine the capacity of ecosystems to sustain food production, maintain freshwater and forest resources, regulate climate and air quality, and ameliorate infectious diseases. We face the challenge of managing trade-offs between immediate human needs and maintaining the capacity of the biosphere to provide goods and services in the long term.

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8,813 Citations


Journal ArticleDOI: 10.1126/SCIENCE.1185383
12 Feb 2010-Science
Abstract: Continuing population and consumption growth will mean that the global demand for food will increase for at least another 40 years. Growing competition for land, water, and energy, in addition to the overexploitation of fisheries, will affect our ability to produce food, as will the urgent requirement to reduce the impact of the food system on the environment. The effects of climate change are a further threat. But the world can produce more food and can ensure that it is used more efficiently and equitably. A multifaceted and linked global strategy is needed to ensure sustainable and equitable food security, different components of which are explored here.

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Topics: Food security (70%), Food systems (65%), Food processing (58%) ... show more

7,758 Citations


01 Jan 2013-
Abstract: Statistics An Intduction to Stistical Lerning with Applications in R An Introduction to Statistical Learning provides an accessible overview of the fi eld of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fi elds ranging from biology to fi nance to marketing to astrophysics in the past twenty years. Th is book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classifi cation, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fi elds, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical soft ware platform. Two of the authors co-wrote Th e Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. Th is book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. Th e text assumes only a previous course in linear regression and no knowledge of matrix algebra.

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6,116 Citations


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20221
20214