How to Seize the Opportunities of New Technologies in Life Cycle Analysis Data Collection: A Case Study of the Dutch Dairy Farming Sector

Technologies such as blockchain, big data, and the Internet of Things provide new opportunities for improving and scaling up the collection of life cycle inventory (LCI) data. Unfortunately, not all new technologies are adopted, which means that their potential is not fully exploited. The objective of this case study is to show how technological innovations can contribute to the collection of data and the calculation of carbon footprints at a mass scale, but also that technology alone is not sufficient. Social innovation is needed in order to seize the opportunities that these new technologies... Mehr ...

Verfasser: Eric Mieras
Anne Gaasbeek
Daniël Kan
Dokumenttyp: Text
Erscheinungsdatum: 2019
Verlag/Hrsg.: Multidisciplinary Digital Publishing Institute
Schlagwörter: life cycle assessment (LCA) / data collection / life cycle inventory (LCI) / social innovation / technological innovation / big data (BD) / cloud
Sprache: Englisch
Permalink: https://search.fid-benelux.de/Record/base-26636528
Datenquelle: BASE; Originalkatalog
Powered By: BASE
Link(s) : https://doi.org/10.3390/challe10010008

Technologies such as blockchain, big data, and the Internet of Things provide new opportunities for improving and scaling up the collection of life cycle inventory (LCI) data. Unfortunately, not all new technologies are adopted, which means that their potential is not fully exploited. The objective of this case study is to show how technological innovations can contribute to the collection of data and the calculation of carbon footprints at a mass scale, but also that technology alone is not sufficient. Social innovation is needed in order to seize the opportunities that these new technologies can provide. The result of the case study is real-life, large-scale data collected from the entire Dutch dairy sector and the calculation of each individual farm’s carbon footprint. To achieve this, it was important to (1) identify how members of a community can contribute, (2) link their activities to the value it brings them, and (3) consider how to balance effort and result. The case study brought forward two key success factors in order to achieve this: (1) make it easy to integrate data collection in farmers’ daily work, and (2) show the benefits so that farmers are motivated to participate. The pragmatic approach described in the case study can also be applied to other situations in order to accelerate the adoption of new technologies, with the goal to improve data collection at scale and the availability of high-quality data.