Abstract

Small and medium enterprises (SMEs) account for 99 % of companies operating in the European food and drink industry and, often, are part of highly fragmented and complex food chains. The article focuses on the development of a social impact assessment methodology for SMEs in selected food and drink products as part of the EU-FP7 SENSE research project. The proposed methodology employs a top-down and bottom-up approach and focuses on labour rights/working conditions along the product supply chain as the key social impact indicator, limiting key stakeholder classification to workers/employees and local communities impacted by the production process. Problems related to this emerging field are discussed, and questions for further research are expounded. The article reviews both academic and ‘grey’ literature on life cycle assessment (LCA) and its relationship to social LCA (S-LCA) and SMEs at the beginning of 2013 and includes case study evidence from the food sector. A pilot questionnaire survey sent to European food and drink sector SMEs and trade associations (as partners in the research project) about their knowledge, experience and engagement with social impacts is presented. Proposals are elaborated for a social impact assessment methodology that identifies the key data for SMEs to collect. The literature reveals the complexity of the S-LCA approach as it aims to unite disparate and often conflicting interests. Findings from the pilot questionnaire are discussed. Using a top-down and bottom-up approach, the proposed methodology assesses data from SMEs along the supply chain in order to gauge social improvements in the management of labour-related issues for different product sectors. Issues relating to the ‘attributional’ choice of a social impact indicator and key stakeholder categories are discussed. How ‘scoring’ is interpreted and reported and what the intended effect of its use will be are also elaborated upon. Whilst recognising the difficulty of devising a robust social impact assessment for SMEs in the food and drink sector, it is argued that the proposed methodology makes a useful contribution in this fast-emerging field.

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