Dataset Information

No time to waste: assessing the performance of food waste prevention actions

ABSTRACT: As a result of the growing awareness of the need to prevent food waste, several initiatives have been launched in the last few years to reduce food waste generated across the food supply chain. However, the evaluation of food waste prevention interventions is still at an early stage of development and appropriate methods to assess their effectiveness are missing, hampering the identification of best practices amongst existing initiatives and the prioritisation of those that are most promising. To address such needs and provide a common approach to consistently assess the performance of food waste prevention initiatives, the European Commission Joint Research Centre has developed an evaluation framework for food waste prevention actions. The framework supports the EU Platform on Food Losses and Food Waste, which has been established to identify best practices and share knowledge on food waste prevention initiatives. Additionally, a food waste prevention calculator, based on life cycle thinking, has been developed to support such an evaluation by a consistent assessment of the environmental and economic benefits of such initiatives, and the identification of potential trade-offs at early design stages. The main goal of this paper is to present the evaluation framework and the calculator developed, critically discussing how future initiatives should be designed, monitored and reported, to ensure sufficient and relevant data is made available to enable their proper assessment. Crucially, this would enable practitioners and decision makers to evaluate the success of existing initiatives and give priority to the implementation of the best performing ones. Graphical abstract Image, graphical abstract

SUBMITTER: De Laurentiis V

PROVIDER: S-EPMC7444015 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:This study is based on one collaborative problem solving task from an international assessment: the Xandar task. It was developed and delivered by the Organization for Economic Co-operation and Development Program for International Student Assessment (OECD PISA) 2015. We have investigated the relationship of problem solving performance with invested time and number of actions in collaborative episodes for the four parts of the Xandar task. The parts require the respondent to collaboratively plan a process for problem solving, implement the process, reach a solution, and evaluate the solution (For a full description, see the Materials and Methods section, "Parts of the Xandar Task.") Examples of an action include posting to a chat log, accessing a shared resource, or conducting a search on a map tool. Actions taken in each part of the task were identified by PISA and recorded in the data set numerically. A confirmatory factor analysis (CFA) model looks at two types of relationship: at the level of latent variables (the factors) and at extra dependencies, which here are direct effects and correlated residuals (independent of the factors). The model, which is well-fitting, has three latent variables: actions (A), times (T), and level of performance (P). Evidence for the uni-dimensionality of performance level is also found in a separate analysis of the binary items. On the whole for the entire task, participants with more activities are less successful and faster, based on the United States data set employed in the analysis. By contrast, successful participants take more time. By task part, the model also investigates relationships between activities, time, and performance level within the parts. This was done because one can expect dependencies within parts of such a complex task. Results indicate some general and some specific relationships within the parts, see the full manuscript for more detail. We conclude with a discussion of what the investigated relationships may reveal. We also describe why such investigations may be important to consider when preparing students for improved skills in collaborative problem solving, considered a key aspect of successful 21st century skills in the workplace and in everyday life in many countries.

Dataset Information

No time to waste: assessing the performance of food waste prevention actions

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets