Efficiency measurement of production systems that also produces some harmful environmental effects such as agricultural activities, chemical processing plants, etc. have received considerable attention from researchers recently. Rice farming is one of such production processes which typically produces two types of outputs which are economic desirable as well as environmentally undesirable. In efficiency analysis, these undesirable outputs cannot be ignored and need to be included in the model to obtain the actual estimation of firm’s efficiency. There are numerous approaches that have been used in data envelopment analysis (DEA) literature to account for undesirable outputs of which directional distance function (DDF) approach is the most widely used as it allows for simultaneous increase in desirable outputs and reduction of undesirable outputs. In situations when data uncertainty is present, interval data approach can be used to account for data uncertainty. In this paper two slack based interval DEA models were constructed for optimistic and pessimistic scenarios. The developed model was used to determine rice farmers efficiency from Kerpan, Kedah. The study found that 12 out of 40 farmers are efficient in all cases. It is found that generally, farmers who operates in optimistic scenario have higher efficiency since they are in best production situation compared to pessimistic scenario in which they operate in worst production situation. The results show that the proposed model can be applied when data uncertainty is present in the production environment.
Volume 11 | 12-Special Issue
Pages: 68-74