In the context of the policy debate around business practices related to the marketing of branded food products as being identical (i.e. in their brand and appearance on the packaging) across EU Member States when, in fact, they differ significantly in composition or characteristics (i.e. in their ingredients), the European Parliament has called for a system for monitoring this issue, which is often referred to as 'dual quality'. Despite the various studies carried out by the European Commission, there currently exists no monitoring system that can be used to evaluate the presence of such practices across the EU single market. This is mainly because monitoring this practice requires readily accessible and up-to-date information on branded food products sold in supermarkets, which are generally subject to constant reformulation; in addition, new products are continually introduced to the market and older ones removed. This study aims to address this gap by assessing the feasibility of crowdsourcing (gathering citizen contributions) to collect branded food product information (i.e. photos of the front and back of pack, including information on the nutritional composition and ingredients of branded food products) to monitor dual quality cases. The analysis builds on existing practice and literature, using a data life cycle framework to identify processes and key factors for each crowdsourcing component (task, crowdsourcer, crowd, system/platform) and subcomponent (crowd management, quality assurance, incentive mechanism and technology) at each stage. The study provides insights into the challenges related to crowd participation, accuracy, representativeness and data usage. It also examines the advantages and disadvantages of crowdsourcing to monitor dual quality in the EU and makes several key recommendations for stakeholders. The study concludes that, for crowdsourcing to be a viable tool for monitoring dual quality, the crowdsourcer's value proposition must integrate the benefits and importance (e.g. access to data, knowledge, social contribution) for all participants (crowdsourcer, crowd, society) beyond any economic reward. For this to succeed, crowdsourcing must deliver a high-quality aggregated outcome and compensations that meet the value proposition (the promised benefits for all), including dual quality information. In this context, behavioural tools (e.g. nudges) and gamification (e.g. points, score tables, puzzles) can help. Finally, for crowdsourcing to function correctly, the crowdsourcer must plan and manage well, identify risks and use a valuation method that encompasses all costs and benefits to determine the value captured by the crowdsourcing organisation and its viability. The results of this study provide insights that can help Member State authorities, business and consumer representatives and other stakeholders considering implementing tools that rely on crowdsourcing for the monitoring of dual quality practices.
