Designing a multi-level model of factors influencing the adoption of green food supply chains: evidence from Iran’s pasta industry

Purpose This study aims to identify, structure and model the key factors influencing the adoption of green food supply chain (GFSC) practices in Iran’s pasta industry. Given the growing need to reduce the environmental footprint of food production and distribution, the research seeks to provide a clear analytical framework for understanding the drivers and outcomes of sustainability integration in this sector. Design/methodology/approach A systematic literature review is conducted to extract relevant indicators associated with the GFSC implementation. These findings are complemented by expert consultation involving 13 specialists from academia and the pasta manufacturing industry. Fifteen influential factors are identified and evaluated through pairwise comparisons. Interpretive structural modeling (ISM) is then applied to determine the hierarchical relationships among the variables, followed by matrix impact cross-reference multiplication applied to a classification (MICMAC) analysis to assess their driving and dependence power. Findings Results reveal a four-level hierarchical structure in which environmental regulations, managerial commitment, technological capability and social responsibility function as foundational drivers of green supply chain adoption. Mid-level organizational enablers such as culture, clean technology investment, procurement practices and financial incentives link strategic goals to operational change. Outcome-oriented factors, including transparency, consumer awareness and corporate responsibility, emerge as dependent variables shaped by the broader system. Originality/value This study offers a structured multilevel model that integrates ISM and MICMAC to examine sustainability adoption in a key segment of Iran’s food industry.