A new look at measuring sustainability of industrial parks: a two-stage data envelopment analysis approach

Abstract

An industrial park is a community of manufacturing and service businesses located together in a specific area. The sustainable industrial park is strategically significant for sustainable development of countries. In this paper, a gradual efficiency improvement data envelopment analysis (DEA) model is proposed to (i) measure sustainability of industrial parks, (ii) classify follower and pioneer industrial parks regarding the environmental performance, and (iii) direct the followers toward pioneers to gradually (not at once) improve their performance and make feasible improvement plans. The proposed method identifies decision-making units (DMUs) on most productive scale size (MPSS) region, and then projects other DMUs onto this region. The proposed model is extended to evaluate performance of a two-stage network structures where outputs from the first stage become inputs to second stage in addition to inputs of first stage and outputs of second stage. The proposed approach is applied to measure the sustainability of 31 Iranian industrial parks. Despite traditional DEA methods, the results indicate that inputs (outputs) should not be necessarily decreased (increased) to project the industrial parks onto the MPSS region.