Performance evaluation of two-stage network systems with tradable intermediate measures: An application to China's steel industry

When surplus intermediate measures arise in a two-stage production system, how to accurately evaluate the efficiency of the production system and quantify the actual benefits that idle resources can create is a decision-making problem that managers need to solve urgently. Traditional efficiency evaluation methods ignore the economic value of the excess intermediate measures through market transactions. To address this challenge, this paper proposes a new two-stage network data envelopment analysis (DEA) framework considering the tradability of intermediate measures, aiming to provide quantitative decision support for efficiency evaluation and optimal resource allocation. Specifically, it introduces a new production axiom that captures the possibility of trading, reconstructs the production possibility set (PPS), and subsequently develops a frontier-projection model that integrates trading decisions. The proposed model not only enables the simultaneous evaluation of overall system efficiency and the unique sub-stage efficiencies but also quantifies the additional revenue attainable through trading surplus intermediate measures, thereby offering managers a clear course of action that aligns technical improvement with financial gains. An empirical study of China's steel industry shows that this method can effectively identify efficiency bottlenecks and reveal considerable income potential (about 17.16 % on average). The conclusion has a clear decision-making reference value for promoting enterprise resource optimization and industry policy formulation.