Achieving TFP Growth through Generalized Models of Inverse DEA (Case Study: NIOC)

Total Factor Productivity (TFP) is a measure for assessing the productivity of a firm or organization. The level of productivity score of a firm shows that how the firm succeeds in optimizing the usage of sources and producing more outputs by certain level of inputs. Nowadays the productivity growth has a crucially important role in economics and firms competition. The industrial countries increase their outcomes not necessarily through more inputs but, by making growth in productivity. Some of the duties of executive organizations of Iran which is explained in the 4th program of development is to determine the productivity growth rate of the related products, organizing the programs, making some solutions for increasing the productivity such as that of GDP growth to be at least 31.3% and average growth of labor, capital and TFP to be at least 3.5%, 1%, 2.5% respectively. For achieving these targets, firstly, the productivity score should be calculated for every organization during previous periods of their activities. Then the effective factors of productivity growth should be determined and forecasted for the next period, to increase the productivity at least by 2.5%. In this paper we present a method based on productivity growth indexes and generalize inverse DEA. Using the proposed method, the productivity score of previous periods are calculated. Then the value of input and output changes for the next period is determined. This method is applied for a case study at National Iranian Oil Company