Yes / While studies indicate that collaboration between stakeholders plays a prominent role in reducing food loss and waste (FLW), they have not specified which stakeholder group's collaboration will be more effective in reducing FLW. To fill this gap in the literature, this paper aims to identify and classify fruit and vegetable supply chain (FVSC) stakeholders according to their salience level and offer mitigation strategies for different salient stakeholder groups to tackle FLW. The study was conducted in Turkish FVSC because fruit and vegetable loss accounted for 53% of the total food loss. A multi-method approach was utilised to achieve the aim. First, 26 semi-structured interviews were conducted with Turkish FVSC experts to determine FVSC stakeholders and FLW drivers. Second, to identify and classify salient stakeholders, stakeholder mapping was undertaken. Collaboration-related mitigation strategies are offered high salient stakeholders and other stakeholder groups to reduce the amount of fruit and vegetable loss and waste. According to content analysis results, 25 supply chain actors are identified as stakeholders, and 15 are classified as salient stakeholders who can be more effective in tackling FLW. In addition, based on the results, 26 FLW drivers are identified according to different supply chain stages. Collaboration-based mitigation strategies were developed to diminish the impact of FLW causes at different stages. This study is one of the early attempts to classify food supply chain stakeholders according to saliency level. This study offers collaboration-related mitigation strategies to eliminate FLW drivers that cause loss and waste between specific stages of the FVSC. / The research was supported by The Scientific & Technological Research Council of Turkey (Tübitak 2211-A project no: 1649B031503919).
| Identifer | oai:union.ndltd.org:BRADFORD/oai:bradscholars.brad.ac.uk:10454/19069 |
| Date | 14 July 2022 |
| Creators | Surucu-Balci, Ebru, Tuna, O. |
| Source Sets | Bradford Scholars |
| Language | English |
| Detected Language | English |
| Type | Article, Published version |
| Rights | © 2022 Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)., CC-BY |
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