Energy use pattern and benchmarking of selected greenhouses in Iran using data envelopment analysis

This paper studies the degree of technical efficiency (TE) and scale efficiency (SE) of selected greenhouses in Iran and describes the process of benchmarking energy inputs and cucumber yield. Inquiries on 18 greenhouses were conducted in a face-to-face interviewing during September–December 2008 period. A non-parametric data envelopment analysis (DEA) technique was applied to investigate the degree of TE and SE of producers, and evaluate and rank productivity performance of cucumber producers based on eight energy inputs: human labour, diesel, machinery, fertilizers, chemicals, water for irrigation, seeds and electricity, and output yield values of cucumber. DEA optimizes the performance measure of each greenhouse or decision making unit (DMU). Specifically, the DEA was used to compare the performance of each DMU in region of increasing, constant or decreasing return to scale in multiple-inputs situations. The CRS model helped us to decompose the pure TE into the overall TE and SE components, thereby allowing investigating the scale effects. The results of analysis showed that DEA is an effective tool for analyzing and benchmarking productive efficiency of greenhouses. The VRS analysis showed that only 12 out of the 18 DMUs were efficient. The TE of the inefficient DMUs, on average, was calculated as 91.5%. This implies that the same level of output could be produced with 91.5% of the resources if these units were performing on the frontier. Another interpretation of this result is that 8.5% of overall resources could be saved by raising the performance of these DMUs to the highest level.