64 research outputs found

    Demand Forecasting for Food Production Using Machine Learning Algorithms: A Case Study of University Refectory

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    Accurate food demand forecasting is one of the critical aspects of successfully managing restaurants, cafeterias, canteens, and refectories. This paper aims to develop demand forecasting models for a university refectory. Our study focused on the development of Machine Learning-based forecasting models which take into account the calendar effect and meal ingredients to predict the heavy demand for food within a limited timeframe (e.g., lunch) and without pre-booking. We have developed eighteen prediction models gathered under five main techniques. Three Artificial Neural Network models (i.e., Feed Forward, Function Fitting, and Cascade Forward), four Gauss Process Regression models (i.e., Rational Quadratic, Squared Exponential, Matern 5/2, and Exponential), six Support Vector Regression models (i.e., Linear, Quadratic, Cubic, Fine Gaussian, Medium Gaussian, and Coarse Gaussian), three Regression Tree models (i.e., Fine, Medium, and Coarse), two Ensemble Decision Tree (EDT) models (i.e., Boosted and Bagged) and one Linear Regression model were applied. When evaluated in terms of method diversity, prediction performance, and application area, to the best of our knowledge, this study offers a different contribution from previous studies. The EDT Boosted model obtained the best prediction performance (i.e., Mean Squared Error = 0,51, Mean Absolute Erro = 0,50, and R = 0,96)

    Food sales prediction model using machine learning techniques

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    Food sales prediction means how to obtain future results of sales of companies. The purpose of this step is to increase the profits of these companies by avoiding spoilage of food products and avoiding buying more quantities than the needs of these companies, which means the accumulation of these products in the warehouses without selling them. Stocked and expired products require a model that guesses the actual future need for these products. In this study, a model for food sales prediction using machine learning algorithms is proposed to achieve two objectives, first: make a comparison between two datasets, one dataset with a high correlation between its features, and another dataset has a low correlation between its features. The second objective is to use several machine learning algorithms for prediction and comparing between these algorithms to find the best three algorithms that give the best prediction. By using the most important metrics such as root mean square error (RMSE) and mean square error (MSE) found the best three algorithms by using the first dataset are support vector machines (SVMs), least absolute shrinkage and selection operator (LASSO), and bagging regressor) and the best three algorithms by using the second dataset are (gradient boosting, random forest regressor, and decision tree)

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

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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

    Trust in workplace canteens – using Germany and the UK as market examples.

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    It is estimated, that most employees eat one or more meals per day whilst they are at work, which is forming an important element of their overall diet. However, consumers struggle to make an informed dish decision due to a lack of information provided. Additionally, past food scares in Germany and the UK have created distrust and interest in food information. This study is identifying what is important to consumers, indicating their information needs and establishes the format that is most appropriate for the delivery of food information in workplace canteens in Germany and the UK. Providing consumers with enhanced food information can strengthen the relationship between consumer and canteen operator as well as establish trust in the food served. A mixed methodological, sequential approach was employed. Four focus groups were used to inform the design of a questionnaire (n=317), which tested criteria of importance and types of information provision that are relevant when making food choice in a workplace setting using Best-worst scaling. Through semi-structured interviews (n=10) canteen operators’ views on meeting customer needs and establishing trust in the food served were identified. Informational criteria of importance have been identified whereby, Nutrition, Value for Money and Naturalness are key elements that consumers require to make a decision about dish selection. Consumers fall into different segments; Health Conscious, Socially Responsible and Value Driven and hence rate the importance of certain informational criteria differently impacting on dish selection. Traffic Light Labelling, Information Boxes and Quality Assurance have been shown to be the most favourable way of receiving food information. Consumers align to different segments; Tech-savvy, Heuristic Processors, Brand Orientated and Systematic Processors, hence various communication channels can be explored to most effectively target consumers. This study has provided an understanding of consumers’ information requirements thus enabling canteen operators to be more competitive. The provision of food information that targets different consumer segments can demonstrate shared customers’ values and consequently, evidence operators’ commitment towards a relationship that is based on transparency and trust

    Healthy Food Environment Scoping Review

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    This work was conducted at the request of the Centre for Population Health at the NSW Ministry of Health, to inform implementation of the relevant strategic direction of the NSW Healthy Eating Active Living (HEAL) Strategy 2013–2018. It is not intended to be an exhaustive review but rather to provide an indication of the rationale for intervening and the potential effectiveness of a broad range of policy options. It is also intended to inform ongoing stakeholder consultation regarding action with respect to the food environment. This consultation will necessarily take account of other evidence of effectiveness including likely reach and population impact, as well as implementation issues such as sustainability of effects, feasibility, acceptability, equity, and other factors affectingplanning and investment decisions. It is noted that no single action contained within this evidence synthesis will in itself be sufficient to affect weight status substantially at the population level. A portfolio of interventions within the food environment, alongside action to increase physical activity and reduce sedentary behaviours, is required to halt the progress of obesity and prevent chronic disease. This sentiment has been expressed many times previously but also recently in the McKinsey paper by Dobbs et al (November 2014) relating to an economic analysis for obesity prevention: “Existing evidence indicates that no single intervention is likely to have a significant overall impact. A systemic, sustained portfolio of initiatives, delivered at scale, is needed to reverse the health burden.” Similarly, no individual sector in society can address obesity acting on its own — neither governments, retailers, consumer-goods companies, restaurants, employers, media organisations, educators, healthcare providers, or individuals.Achieving the full potential impact requires engagement from as many sectors as possible. Ideally such actions would be contained within an overarching National Nutrition Policy in Australia. Finally, we would like to echo another sentiment of the McKinsey Global Institute discussion paper, that “… our analysis is by no means complete. Rather we see our work [on a potential program to address obesity] as the equivalent of the maps used by 16th-century navigators. Some islands were missing and some islands were misshapen in these maps, but they were helpful to the sailors of the era. We are sure that we have missed some interventions and over- or underestimated the impact of others. But we hope our work to be a useful guide….”The Physical Activity Nutrition and Obesity Research Group (PANORG) is funded by the Centre for Population Health, NSW Ministry of Health. It is part of the Prevention Research Collaboration in the School of Public Health at the University of Sydney

    Child Obesity and Nutrition Promotion Intervention

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    Childhood obesity continues to be a global problem, with several regions showing increasing rates and others having one in every three children overweight despite an apparent halt or downward trend. Children are exposed to nutritional, social, and obesogenic environmental risks from different settings, and this affects their lifelong health. There is a consensus that high-quality multifaceted smart and cost-effective interventions enable children to grow with a healthy set of habits that have lifelong benefits to their wellbeing. The literature has shown that dietary approaches play key roles in improving children’s health, not only on a nutritional level but also in diet quality and patterns. An association between the nutritional strategy and other lifestyle components promotes a more comprehensive approach and should be envisioned in intervention studies. This Special Issue entitled “Child Obesity and Nutrition Promotion Intervention” combines original research manuscripts or reviews of the scientific literature concerning classic or innovative approaches to tackle this public health issue. It presents several nutritional interventions alongside lifestyle health factors, and outcome indicators of effectiveness and sustainability from traditional to ground-breaking methods to exploit both qualitative and quantitative approaches in tackling child obesity

    The Effects of Alcohol Outlets and Sales on Alcohol-Related Injuries Presenting at Emergency Departments in Perth, Australia, from 2002 to 2010

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    The study examined the effects of licensed outlets and alcohol sales on levels of alcohol-related injuries presenting to Emergency Departments in Perth, Western Australia . This retrospective population-based longitudinal study used injury and alcohol availability data. Negative binomial regression modelling with random effects demonstrated that sales per off-premise outlet and counts of on-premise outlets per postcode were significantly associated with alcohol-related injury. These findings also supported restrictions on numbers of outlets, price discounting, and trading hours

    Sustainable Consumer Behavior and Food Marketing

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    In light of the considerable impact of global food supply chains on climate change, more sustainable ways of producing, distributing, and consuming food appear critical for sustainable development. With the aim of contributing to this topic, this Special Issue on sustainable food consumption and food marketing addresses various relevant issues related to food consumption, including innovative and sustainable forms of food production and consumption, animal welfare and meat consumption, price transmission, social media communication, alternative food production, and organic agriculture, among others. As such, this Special Issue sheds light on more sustainable and carbon-friendly food production and consumption systems from various angles. It delivers valuable scientific evidence for the transformation of current carbon-based food supply chains to more eco-friendly, fair, and future-oriented food supply chains
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