## 3 Results--Effectiveness of Pull and Push Strategies in Production and Distribution
### Impact of Delivery Times to Warehouses on Economic Efficiency
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Strategy**} & \multicolumn{2}{c}{**Stand. Dev. of**} & \multicolumn{5}{c}{**No of DCs**} \\  & **Average Sales** & **1** & **2** & **3** & **4** & **5** & **6** \\ \hline Pull daily & 3\% & 98.50\% & 98.40\% & 98.30\% & 98.30\% & 98.20\% & 98.10\% \\ Push daily & 3\% & 98.30\% & 98.30\% & 98.10\% & 98.10\% & 98.00\% & 97.90\% \\ Push weekly & 3\% & 98.70\% & 98.30\% & 98.10\% & 97.90\% & 97.40\% & 97.00\% \\ Pull daily & 6\% & 98.30\% & 97.10\% & 97.80\% & 98.00\% & 97.80\% & 97.60\% \\ Push daily & 6\% & 98.10\% & 97.90\% & 97.60\% & 97.60\% & 97.40\% & 97.20\% \\ Push weekly & 6\% & 96.20\% & 97.90\% & 94.90\% & 94.90\% & 94.30\% & 93.70\% \\ \hline \hline \end{tabular} Source: own calculations.  
\end{table} 
Table 16: Impact of distribution strategies on the level of inventories [1000 pcs.] (Gamma distribution). Three days of delivery to warehouses. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Time**} & \multicolumn{2}{c}{**1 Day**} & \multicolumn{2}{c}{**3 Days**} & \multicolumn{2}{c}{**1 Day**} & \multicolumn{2}{c}{**3 Days**} \\ \hline Distribution & \multicolumn{5}{c}{Gaussian} & \multicolumn{5}{c}{Gamma} \\ St. Dev. & 5\% & 30\% & 5\% & 30\% & 3\% & 6\% & 3\% & 6\% \\ No of DCs & 6 & 6 & 6 & 1 & 6 & 6 & 1 \\ Strategy & Push & Pull daily & weekly & Pull daily & Pull daily & Pull & Pull \\ Total Costs & 1831 & 2761 & 2224 & 3183 & 2909 & 3308 & 3366 & 3788 \\ Share in Revenue & 5.7\% & 8.6\% & 7.0\% & 9.9\% & 9.2\% & 10.3\% & 10.5\% & 11.8\% \\ \hline \hline \end{tabular} Source: own calculations.  
\end{table} 
Table 17: Comparison of results of simulations (Food). \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Strategy**} & \multicolumn{2}{c}{**Stand. Dev. of**} & \multicolumn{5}{c}{**No of DCs**} \\  & **Average Sales** & **1** & **2** & **3** & **4** & **5** & **6** \\ \hline Pull daily & 3\% & 1378 & 1551 & 1674 & 1674 & 1792 & 1919 \\ Push daily & 3\% & 1436 & 1543 & 1719 & 1719 & 1847 & 2060 \\ Push weekly & 3\% & 6260 & 6915 & 7207 & 7539 & 8201 & 8749 \\ Pull daily & 6\% & 1676 & 2055 & 2289 & 2184 & 2431 & 2642 \\ Push daily & 6\% & 2567 & 2914 & 3231 & 3203 & 3507 & 3765 \\ Push weekly & 6\% & 8668 & 10,097 & 10,124 & 10,285 & 11,160 & 12,011 \\ \hline \hline \end{tabular} Source: own calculations.  
\end{table} 
Table 16: Impact of distribution strategies on the level of inventories [1000 pcs.] (Gamma distribution). Three days of delivery to warehouses. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Time**} & \multicolumn{2}{c}{**1 Day**} & \multicolumn{2}{c}{**3 Days**} & \multicolumn{2}{c}{**1 Day**} & \multicolumn{2}{c}{**3 Days**} \\ \hline Distribution & \multicolumn{5}{c}{Gaussian} & \multicolumn{5}{c}{Gamma} \\ St. Dev. & 5\% & 30\% & 5\% & 30\% & 3\% & 6\% & 3\% & 6\% \\ No of DCs & 6 & 6 & 1 & 6 & 6 & 1 \\ Strategy & Push & Pull daily & weekly & Pull daily & Pull daily & Pull & Pull \\ Total Costs & 1831 & 2761 & 2224 & 3183 & 2909 & 3308 & 3366 & 3788 \\ Share in Revenue & 5.7\% & 8.6\% & 7.0\% & 9.9\% & 9.2\% & 10.3\% & 10.5\% & 11.8\% \\ \hline \hline \end{tabular} Source: own calculations.  
\end{table} 
Table 18: Comparison of results of simulations (Garment). Extending the delivery time to warehouses for \"Food\" products results in a 21% increase in costs (Table 17) if the demand has a Gaussian distribution and if the demand fluctuations are small (5%). The increase in costs (28%) for similar parameters is higher in the case of \"Electronics\" (Table 18), which may seem surprising, taking into account the fact that the value of these goods is higher, so the share of these costs in the sales value should be lower. The increases are smaller if it is a Gamma distribution, which may lead to the hypothesis that in the case of such a distribution, demand is difficult to satisfy, even with one-day deliveries.