Forecast data and food waste reduction How digitalization can enable sustainable food systems

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2023-06-28
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en
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With one third of the food globally being lost or wasted a turnaround in the food sector is needed. This thesis researched if digitalization could decrease food waste via forecasting and data sharing. This was researched via in debt interviews for the relation between food retailers and their suppliers. This gave a multi-point perspective on the theme. It was found that forecasting has a positive impact on the food waste reduction. Via AI and Machine learning algorithms the accuracy of the forecast has increased. Also, the availability of big data sources such as consumer data and the availability of real time data increased the effectiveness of the forecasts. Data sharing moderated the relation of forecasting on food waste reduction. If data and forecasts are shared throughout the supply chain, leading to collaborative forecasts, the resource use of the supply chain could be optimized further. Digitalization makes it possible to integrate supply chains via cloud-based programs such as EDI. A further going form of supply chain integration was found in vendor managed inventory. All interviewees highlighted the importance of data and forecast sharing, but it was not implemented broadly.
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Faculteit der Managementwetenschappen
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