Back to Search
Start Over
Information Communication Tools in Alternative Food Networks.
- Source :
- Procedia Computer Science; 2024, Vol. 232, p665-674, 10p
- Publication Year :
- 2024
-
Abstract
- Effective communication in food supply chains is increasingly important, especially in supply chains that strive to provide improved levels of information from producer to consumer. Such supply chains can be found in alternative food networks. Alternative food networks often adopt local and short supply chain strategies to provide embedded information between producers and consumers. Information in the supply chain of alternative food networks is communicated through face-to-face, proximate, or extended supply chain structures. The tools used to communicate information vary amongst the supply chains in alternative food networks; for example, face-to-face may adopt word-of-mouth, while proximate and extended supply chain structures may use labels, digital platforms, and websites. This paper uses Principal Component Analysis to provide an understanding of the categories and underlying dimensions of information communication tools in the supply chains of alternative food networks. A living lab approach and survey method were used for data collection. Using Principal Component Analysis, the data revealed two principal components of information communication tools, highlighting the use of on-packaging information communication tools such as packaging and labelling tools as a principal component. Another principal component was identified, backing a need for off-packaging information communication tools such as digital technologies, certificates, social media, and packaging technologies, enabling stakeholders who desire a further understanding of information regarding the processes and products. The paper concludes with the implications, limitations, and areas of future work. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 18770509
- Volume :
- 232
- Database :
- Supplemental Index
- Journal :
- Procedia Computer Science
- Publication Type :
- Academic Journal
- Accession number :
- 176148754
- Full Text :
- https://doi.org/10.1016/j.procs.2024.01.066