System Dynamics Modelling of Olive Supply Chain to Support Socio-ecological Gains in Multi-functional Landscape: General Model and Specification for Tunisian Semi-arid Region

Abstract

Olive value chains in the Mediterranean face linked problems: limited inclusion of smallholders, women, and youth; unpriced environmental harm; high exposure to climate and market shocks; weak incentives for stewardship; slow uptake of better practices; thin market information; infrastructure gaps; and weak ties among farmers, cooperatives, and processors. Because these pressures interact across stages, a single fix often shifts problems elsewhere. This motivates a system dynamics (SD) view that can display feedbacks, delays, and trade-offs within one structure. The paper has two aims. First, it specifies a transparent SD prototype for Tunisia’s olive sector that stakeholders can use now for discussion and later for calibration. Second, it makes three core outcomes central to analysis: socio-ecological gains (joint improvements in productivity and product quality, with lower environmental harm and fairer access to benefits), resilience (the ability to absorb shocks and recover), and inclusion (meaningful participation and benefits for smallholders, women, and youth). The first aim is not predictive: the model prototype serves as a clear boundary structure to organise participatory qualitative work—checking assumptions, locating leverage points, designing policy and technology scenarios, and sketching impact pathways—before full calibration and numerical testing. The model has seven modules. Four are supply-chain subsystems: (i) planting and tree cohorts (young, mature, senescent; rain-fed vs. irrigated), (ii) harvesting (losses, pick rates, technology adoption), (iii) processing and market allocation (extraction, capacity, local/export and premium channels), and (iv) demand (domestic and export). Three are cross-cutting: (v) ecosystem services (soil fertility, water, basic biodiversity), (vi) climate and adaptation (rainfall/heat indices, drought frequency, adaptive investment), and (vii) policy–finance (subsidies, certification premia, tax revenue, budget constraint). We present causal-loop and stock-and-flow diagrams, there variables and parameters, as well as define scenario levers. Empirical calibration and operational simulations will follow. The prototype adds value by adopting a cradle-to-cradle scope that links field stewardship and climate stress to losses, extraction, and premium channels; by keeping structural detail for drought response, stand renewal, and practice adoption; by treating resilience and inclusion as explicit outcomes with clear policy entry points; and by offering user-friendly system dynamics diagrams for co-learning. The Tunisia case is preliminary parameterized-ready yet portable to other Mediterranean regions. We outline next steps: assemble data (cooperatives, mills, prices, remote sensing), verify model structure with wider expert consultation, package an operational model version in Vensim DSS, conduct calibration and validation screening, and test policy and technology scenarios.