Vol. 10 No. 1 (2021)
Full Research Articles

Contribution of periurban farming systems to local food systems: a systemic innovation perspective

Rosalia Filippini
University of Parma – Department of Management and Economic Science, Parma
Elisa Marraccini
UP 2012-10-103 InTerACT – UniLaSalle, Beauvais
Sylvie Lardon
University Clermont Auvergne, AgroParisTech, INRAE, VetAgro Sup, Territoires, F-63000 Clermont-Ferrand

Published 2021-07-24

Keywords

  • Adaptation,
  • Urban sprawl,
  • Local food network,
  • Systemic failures,
  • Italy

How to Cite

Filippini, R., Marraccini, E., & Lardon, S. (2021). Contribution of periurban farming systems to local food systems: a systemic innovation perspective. Bio-Based and Applied Economics, 10(1), 19–34. https://doi.org/10.36253/bae-10855

Abstract

The debate on food security has highlighted the connection between periurban farming systems (PFS) and local food systems (LFS) for academic research. Several researchers have called for in-depth analysis of the participation and impact of farmers in LFS, and the systemic innovation perspective can provide relevant analysis of the sustainability of this agro-food system. The objective of the current study is to investigate the integration of PFS into LFS from the systemic innovation perspective, by analysing systemic failures and merits that hinder or promote the contribution of PFS to LFS for farmers and commercial actors. The case study is the LFS of the urban Pisa region in central Italy. Results show that farmers there are adapting to urban pressure, which improves the sustainability of their farming practices. At the same time, commercial actors have a commercial opportunity to include local farmers in their economic strategy. Nevertheless, individual initiatives must be coordinated to support the sustainability of both LFS and PFS. This study thus developed an innovative method to identify systemic failures and merits for farmers and commercial actors to address sustainability strategies at the territorial level.

Metrics

Metrics Loading ...