Abstract: We investigate when upcycling—defined as treating food by‐products for human consumption—mitigates climate change. Earlier research only modeled pilot‐scale upcycling experiments, which discount its real‐world complexity. To tackle this important limitation, our research involved 130 interviews, life cycle assessment, and a simulation to assess what operational structures made upcycling environmentally sustainable and superior to alternatives such as animal feeding, anaerobic digestion, composting, and landfilling. We considered wet spent grains and fruit and vegetable residues in Canada, two important streams of unavoidable residuals in Western food systems. First, we found that the simulated range of greenhouse gas impacts, +938 to −465 kg of CO2 eq. emissions per tonne of upcycled material, was more optimistic than the ranges available in the literature. No previous estimates existed for the range of impacts for real cases, −18 and −300 kg of CO2 eq. emissions per tonne of upcycled material. Second, net‐negative carbon impacts were achieved only by operational structures with a technological configuration characterized by a total energy consumption lower than 1500 kWh per tonne of upcycled materials and a geographical scale inferior to 260 km (from point of collection to point of sale). Most of the real cases identified during our fieldwork matched these operational prescriptions and achieved a carbon footprint up to 25% smaller than the carbon footprint of the substituted virgin products. Third, our analysis of both best‐case simulated performance and real performance suggested that the positive carbon impact of upcycling was roughly comparable with that produced by animal feeding and anaerobic digestion, but superior to composting and landfilling. Our study illuminates the anatomy of environmentally sustainable upcycling operations and problematizes emergent food recovery hierarchies.

Abstract: Purpose – This research proposes and illustrates a conditional view of lean supply chain management (LSCM) based upon the contextual contingent alignment between lean performance objectives (i.e., a contextual factor) and supply chain management challenges (i.e., a contingent condition) in the selection of lean approaches (i.e., a contingent event). Design/methodology/approach – Drawing on the notions of contingency-based practices and strategic fit, our LSCM reconceptualization jointly considers contextual and contingency factors in specifying what lean approaches to adopt. We illustrate using the Delphi method the practical relevance of our LSCM reconceptualization for the Canadian agri-food industry. Findings – We highlight that LSCM is founded upon alignment associations between specific lean performance objectives and supply chain challenges as well as their influence on the selection of suitable lean approaches. Our empirical illustration shows that those alignment associations do not occur at random, which supports our conditional view of LSCM. Research limitations/implications – The contextual contingent view of LSCM can inform future scholarly inquiry and can reframe practically relevant middle-range theorization on LSCM. Practical implications – The Delphi method-derived descriptive model of LSCM provides guidance to managers in the Canadian agri-food sector in identifying suitable lean approaches to adopt given the specific performance objective(s) pursued and supply chain management challenge(s) encountered. Originality/value –We advance scholarly theorization and managerial understanding of LSCM by providing a conditional conceptualization that jointly considers relevant contextual and contingency factors that hitherto have not been examined. In ascribing what lean approach(es) to adopt to the alignment associations influence between lean performance objective(s) pursued and supply chain management challenge(s) encountered, we provide compelling conceptual and empirical support for the joint conditional view of LSCM.