## 4 Results and Discussion
### How to Improve TE  
When DMUs are nonefficient, the improvement measures can be found through the projection of each DMU on the production frontier (\(X^{*}\), \(Y^{*}\)). \[X^{*}\ =\ \theta_{v}^{*}X_{0}-SA^{*}=\sum_{i=1}^{n}\lambda_{i}^{*}X_{i} \tag{4}\]  
\[Y^{*}\ =\ Y_{0}+SB^{*}=\sum_{i=1}^{n}\lambda_{i}Y_{i} \tag{5}\]  
In order to make each DMU to be efficient, adjustments to output and input (\(\Delta X_{0},\Delta Y_{0}\)):  
\[\Delta X_{0} =X_{0}-X^{*} \tag{6}\]  
\[\Delta Y_{0} =Y^{*}+Y_{0} \tag{7}\]  
After adjusting DMUs, the input and output (\(X^{*}\), \(Y^{*}\)) is pure technology effective. In fact, that is an effective way to improve the nonefficient DMUs, and provide policy suggestions for policy-makers. Using DEAP 2.1, the output redundancy of each DMU was analyzed, and further proposed the efficiency improvement scheme in Table 6.  
In Table 6, the radial adjustment value refers to the proportionately increased quantity that is needed for all the output elements when technology efficiency is improved to 1. The transverse adjustment value refers to the decreased quantity that is needed for all the input elements after the relative reference value is taken into consideration. The transverse adjustment ratio equals the absolute value of transverse adjustment divided by the original value. In terms of the radial adjustment value, provinces with lower technology efficiency have a larger radial adjustment value, which means that higher proportionately increased quantity is needed for output elements. The transverse adjustment value must be proportionately decreased to keep the current output scale in each province. That is to say, the optimal production efficiency must be achieved with less input. Hainan performs better among these five provinces with its technology efficiency standing at 0.625, while Yunnan has the worst performance among these five provinces with its technology efficiency standing at 0.302. The radial adjustment value of Hainan is 4750.95 and \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Province**} & \multirow{2}{*}{**Radial Movement**} & \multirow{2}{*}{**Radial Movement (\%)**} & \multicolumn{3}{c}{**Slack Movement**} & \multirow{2}{*}{**OTE**} \\ \cline{3-3} \cline{5-8}  & & & **Service Fee** & & & **Labor Cost** & \\ \hline Guangxi & 8306.30 & 0.66 & \(-\)3164.85 & \(-\)3209.92 & 1.70 & 1.72 & 0.344 \\ Yunnan & 8839.85 & 0.70 & \(-\)873.30 & \(-\)4125.73 & 0.47 & 2.21 & 0.302 \\ Hainan & 4750.95 & 0.37 & \(-\)1150.95 & \(-\)4949.96 & 0.62 & 2.65 & 0.625 \\ Fujian & 8467.20 & 0.67 & \(-\)575.40 & \(-\)1750.87 & 0.31 & 0.94 & 0.332 \\ Jiangxi & 5998.45 & 0.47 & \(-\)1914.45 & \(-\)1937.74 & 1.03 & 1.04 & 0.527 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Five province cassava-production efficiency DEA improvement in 2014.  
the radial adjustment ratio is 0.37% while the radial adjustment value of Yunnan province is 8839.85 and the radial adjustment ratio is 0.70%. The data show that the optimal production efficiency can be reached in Hainan and Yunnan provinces only after the output elements in these two provinces respectively reach 4750.95 and 8839.85. In terms of transverse adjustment value in five provinces, it can be concluded that an irrational structure exists in Guangxi, Yunnan, Hainan, Fijian, and Jiangxi. If the current scale of output is kept unchanged, then the optimal production efficiency can be achieved only after some of the input elements are removed. Among the elements, the cost of labor is a stable factor when it comes to consider the effect placed on the production efficiency. Table 3 shows that the highest cost for labor, which needs to be decreased in Hainan province, is 4949.96 with its adjustment ratio at 2.65%, and service cost needs to be decreased 1150.95 with its adjustment ratio at 0.62%. In terms of transverse adjustment ratio, the technology efficiency in Fujian province is closest to the reference value.