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309. Exploring the Role of Peer Learning in Supporting Decisions for Food Sharing Organisations
Invited abstract in session TD-45: Decision Support for Sustainable Operations, stream Decision Support Systems.
Tuesday, 14:30-16:00Room: 30 (building: 324)
Authors (first author is the speaker)
| 1. | Shaofeng Liu
|
| Plymouth Business School, University of Plymouth | |
| 2. | Xinyi Li
|
| University of Plymouth | |
| 3. | Dulekha Kasturiratne
|
| University of Plymouth | |
| 4. | Huilan Chen
|
| Plymouth Business School, University of Plymouth |
Abstract
More and more individuals and families have been driven into the danger zone of going hunger recently. To rescue the situation, food sharing organisations (e.g. charities) have worked untiringly. One of the key challenges facing the food sharing organisations is the lack of decision support to help improve their operations efficiency and community of practice. This paper aims to investigate the role of peer learning in the creation of closed-loop social value networks, subsequently to support food sharing organisations and communities.
A Systematic Literature and Practice Review (SLPR) has been undertaken. Based on the SLPR, a comprehensive peer learning framework for food sharing has been developed consisting of four core components: peer learning agents, peer learning modes, peer learning practice, and peer learning outcomes and impacts. The impacts of peer learning on the creation of closed-loop social value networks will be assessed via four stages of the network, including social value propositions, value beneficiaries, value delivery channels, and value capture and feedback. The peer learning framework contributes to new knowledge and practice in a number of aspects: (1) it defines relationships among the four peer learning components; (2) it establishes the main impacts of peer learning on four stages of social value networks; and (3) it provides recommendations to food sharing organisations in making efficient decisions.
Keywords
- Decision Support Systems
- Supply Chain Management
- Knowledge Engineering and Management
Status: accepted
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