## 5 Numerical Examples
\begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline \multicolumn{1}{c}{**Parameter**} & \multicolumn{1}{c}{\(\mathbf{\hat{\omega}^{**}}\)} & \multicolumn{1}{c}{\(\mathbf{p^{**}}\)} & \multicolumn{1}{c}{\(\mathbf{q^{**}}\)} & \multicolumn{1}{c}{\(\mathbf{n^{**}}\)} & \multicolumn{1}{c}{\(\mathbf{Q^{**}}\)} & \multicolumn{1}{c}{\(\mathbf{TP_{CTv}^{**}}\)} & \multicolumn{1}{c}{\(\mathbf{TP_{CTb}^{**}}\)} & \multicolumn{1}{c}{\(\mathbf{E_{v}^{**}}\)} & \multicolumn{1}{c}{\(\mathbf{E_{b}^{**}}\)} \\ \hline \multirow{6}{*}{_a_} & 800 & 35.3989 & 77.7273 & 130.445 & 3 & 391.335 & 5882.60 & 3580.46 & 138.451 & 176.232 \\  & 900 & 37.5738 & 83.8582 & 147.356 & 3 & 442.068 & 7636.10 & 6126.56 & 170.639 & 218.658 \\  & 1000 & 39.5397 & 90.0145 & 162.385 & 3 & 487.155 & 9375.44 & 9308.23 & 201.702 & 259.951 \\  & 1100 & 41.3220 & 96.1974 & 176.058 & 3 & 528.174 & 11102.8 & 13122.7 & 231.941 & 300.469 \\  & 1200 & 42.9478 & 102.394 & 188.692 & 3 & 566.076 & 12819.2 & 17568.1 & 261.530 & 340.420 \\ \hline \multirow{6}{*}{_b_} & 6.4 & 39.6797 & 105.581 & 174.471 & 3 & 523.413 & 10893.6 & 15912.1 & 229.316 & 296.896 \\  & 7.2 & 39.6054 & 96.9278 & 168.549 & 3 & 505.647 & 10136.4 & 12175.5 & 215.587 & 278.496 \\  & 8.0 & 39.5397 & 90.0145 & 162.385 & 3 & 487.155 & 9375.44 & 9308.23 & 201.702 & 259.951 \\  & 8.8 & 39.4855 & 84.3678 & 155.946 & 3 & 467.838 & 8610.30 & 7073.72 & 187.642 & 241.237 \\  & 9.6 & 39.4468 & 79.6732 & 149.189 & 3 & 447.567 & 7840.46 & 5314.35 & 173.382 & 222.325 \\ \hline \multirow{6}{*}{_A_} & 160 & 39.6948 & 89.9478 & 149.295 & 3 & 447.885 & 9369.53 & 9382.07 & 208.624 & 263.166 \\  & 180 & 39.6232 & 89.9818 & 155.972 & 3 & 467.916 & 9373.50 & 9344.38 & 204.974 & 261.444 \\  & 200 & 39.5397 & 90.0145 & 162.385 & 3 & 487.155 & 9375.44 & 9308.23 & 201.702 & 259.951 \\  & 220 & 39.4491 & 90.0459 & 168.564 & 3 & 505.692 & 9375.75 & 9273.45 & 198.739 & 258.643 \\  & 240 & 39.3545 & 90.0764 & 174.533 & 3 & 523.599 & 9374.75 & 9239.90 & 196.033 & 257.486 \\ \hline \multirow{6}{*}{_h_} & 0.40 & 39.5115 & 90.0073 & 163.893 & 3 & 491.679 & 9379.67 & 9316.31 & 201.057 & 259.732 \\  & 0.45 & 39.5257 & 90.0109 & 163.134 & 3 & 489.402 & 9377.55 & 9312.26 & 201.381 & 259.842 \\  & 0.50 & 39.5397 & 90.0145 & 162.385 & 3 & 487.155 & 9375.44 & 9308.23 & 201.702 & 259.951 \\  & 0.55 & 39.5537 & 90.0180 & 161.647 & 3 & 484.941 & 9373.32 & 9304.22 & 202.021 & 260.060 \\  & 0.60 & 39.5675 & 90.0216 & 160.918 & 3 & 482.754 & 9371.20 & 9300.22 & 202.338 & 260.169 \\ \hline \multirow{6}{*}{_C_T} & 40 & 39.5826 & 89.9983 & 159.210 & 3 & 477.630 & 9374.69 & 9326.12 & 203.296 & 260.672 \\  & 45 & 39.5614 & 90.0064 & 160.805 & 3 & 482.415 & 9375.12 & 9317.13 & 202.489 & 260.305 \\  & 50 & 39.5397 & 90.0145 & 162.385 & 3 & 487.155 & 9375.44 & 9308.23 & 201.702 & 259.951 \\  & 55 & 39.5176 & 90.0224 & 163.951 & 3 & 491.853 & 9375.65 & 9299.41 & 200.934 & 259.608 \\  & 60 & 39.4951 & 90.0303 & 165.502 & 3 & 496.506 & 9375.77 & 9280.67 & 200.185 & 259.276 \\ \hline \multirow{6}{*}{_C_} & 2.4 & 39.6131 & 89.7066 & 163.940 & 3 & 491.820 & 9461.10 & 9481.66 & 202.798 & 261.785 \\  & 2.7 & 39.5765 & 89.8605 & 163.161 & 3 & 489.483 & 9418.27 & 9394.75 & 202.251 & 260.868 \\ \cline{1-1}  & 3.0 & 39.5397 & 90.0145 & 162.385 & 3 & 487.155 & 9375.44 & 9308.23 & 201.702 & 259.951 \\ \cline{1-1}  & 3.3 & 39.5029 & 90.1684 & 161.614 & 3 & 484.842 & 9332.59 & 9222.09 & 201.151 & 259.032 \\ \cline{1-1}  & 3.6 & 39.4659 & 90.3224 & 160.848 & 3 & 482.544 & 9289.74 & 9136.33 & 200.598 & 258.113 \\ \hline \multirow{6}{*}{_b_} & 0.08 & 38.0601 & 89.9355 & 179.198 & 3 & 537.594 & 9467.89 & 9397.08 & 180.752 & 257.375 \\  & 0.09 & 38.8805 & 89.9759 & 170.160 & 3 & 510.480 & 9420.31 & 9351.53 & 192.197 & 258.631 \\ \cline{1-1}  & 0.10 & 39.5397 & 90.0145 & 162.38  
effect on the manufacturer's total profit and carbon emissions but a negative effect on the retailer's total profit and carbon emissions. 2.