Identifying value chain trade-offs from fruit and vegetable aggregation services in Bangladesh using a system dynamics approach.

Significant progress has been made in cereal production in Bangladesh due to an agricultural policy environment that prioritizes the productivity of staple crops over fruit and vegetables (F&V). However, many smallholder farmers remain poorly connected to markets, which may lead to a limited supply response of F&V that can reduce opportunities for sufficient intake in neglected, consumer-facing, smaller retail markets. To address this issue, aggregation schemes have been conceived that collect and transport F&Vs on behalf of multiple farmers. Given the volume of horticultural produce produced and the reliance on developed transport infrastructure, aggregation schemes tend to supply wholesale and urban markets rather than underdeveloped rural and isolated markets. To this end, we investigated how a particular aggregation intervention ('Loop') could potentially improve the distribution of F&V to smaller markets whilst improving farmer benefits. We used an innovative system dynamics modeling approach based on Loop`s aggregation services in Jashore, Bangladesh, and to identify the potential trade-offs between consumer outcomes in retail markets and farmer benefits. We find that combining aggregation with a quota at the smaller market, transport subsidy, and current price growth does not result in trade-offs between consumer purchases and farmers`benefits. However, combining aggregation with current price growth can increase demand without losing farmers`benefits. The findings emphasize that standalone and multiple market-oriented interventions generate broader win-win benefits to promote inclusive food systems.

Identifying 'win-win-win' futures from inequitable value chain trade-offs: A system dynamics approach.

CONTEXT: There is growing recognition that food systems must adapt to become more sustainable and equitable. Consequently, in developing country contexts, there is increasing momentum away from traditional producer-facing value chain upgrades towards efforts to increase both the availability and affordability of nutritious foods at the consumer level. However, such goals must navigate the inherent complexities of agricultural value chains, which involve multiple interactions, feedbacks and unintended consequences, including important but often surprising trade-offs between producers and consumers. OBJECTIVE AND METHODS: Based around the 'Loop' horticultural aggregation scheme of Digital Green in Bihar, India, we develop a system dynamics modelling framework to survey the value chain trade-offs emerging from upgrades that aim to improve the availability of fruits and vegetables in small retail-oriented markets. We model the processes of horticultural production, aggregation, marketing, and retailing - searching for futures that are 'win-win-win' for: (i) the availability of fruits and vegetables in small retail markets, (ii) the profits of farmers participating in aggregation, and (iii) the sustainability of the initial scheme for Digital Green as an organisation. We simulate two internal upgrades to aggregation and two upgrades to the wider enabling environment through a series of 5000 Monte Carlo trajectories - designed to explore the plausible future dynamics of the three outcome dimensions relative to the baseline. RESULTS: We find that 'win-win-win' futures cannot be achieved by internal changes to the aggregation scheme alone, emerging under a narrow range of scenarios that boost supplies to the small retail market whilst simultaneously supporting the financial takeaways of farmers. In contrast, undesirable producer versus consumer trade-offs emerge as unintended consequences of scaling-up aggregation and the introduction of market-based cold storage. SIGNIFICANCE: This approach furthers ongoing efforts to capture complex value chain processes, outcomes and upgrades within system dynamics modelling frameworks, before scanning the horizon of plausible external scenarios, internal dynamics and unintended trade-offs to identify 'win-win-win' futures for all.