# A Continuous Monitoring and Reallocation Method for Successful Decisions in Change Management
## 4 Experiments and Results
### First Experiment: Algorithm Implementation  
The application of the algorithm starts at time \(t=0\), along with the initiation of the change period. Following the algorithm flowchart presented in Figure 2, in step 1, a \(10\times 10\) performance matrix \(P_{ij}\) contains the initial values. These values are randomly selected from the range between 90% and 100% based on assumption (a) in the problem description in Section 3.1 (each worker will be able to carry out all available tasks). Consequently, each worker's performance in each possible task takes random values from 90 to 100 as an initial condition of the algorithm application. An example of such random values is shown in Table 2. \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline TIME (\(t\)) & 0 & 1 & 2 & 3 & 4 & 5 & 6 & 7 \\ \hline Resistance limits & [0,20] & [0,44] & [0,30] & [0,18] & [0,14] & [0,12] & [0,8] & [-] \\ \hline TIME (\(t\)) & 8 & 9 & 10 & 11 & 12 & 13 & 14 & 15 \\ \hline Resistance limits & [0,\(-8\)] & [0,\(-12\)] & [0,\(-20\)] & [0,\(-22\)] & [0,\(-30\)] & [0,\(-34\)] & [0,\(-34\)] & [-] \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Limits of resistance in triangular distribution (red indicates positive resistance; green indicates negative resistance). \begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline  & \multicolumn{8}{c}{**Performance (\(P_{ij}(t=0)\))**} \\ \hline \multicolumn{2}{c}{**Human**} & \multicolumn{8}{c}{**Tasks (\(j\))**} \\
**Resources (\(i\))** & **1** & **2** & **3** & **4** & **5** & **6** & **7** & **8** & **9** & **10** \\ \hline
1 & 97 & 91 & 90 & 93 & 91 & 96 & **97** & 97 & 96 & 98 \\
2 & 98 & **99** & 96 & 95 & 96 & 92 & 99 & 94 & 99 & 90 \\
3 & 94 & 93 & 90 & 94 & 96 & 94 & 95 & 92 & **99** & 90 \\
4 & **99** & 92 & 97 & 97 & 97 & 94 & 90 & 91 & 95 & 99 \\
5 & 92 & 97 & 90 & 90 & **99** & 91 & 97 & 94 & 98 & 92 \\
6 & 94 & 91 & 94 & 95 & 97 & 91 & 94 & 92 & 96 & **97** \\
7 & 98 & 95 & 91 & 99 & 94 & **98** & 98 & 99 & 94 & 98 \\
8 & 98 & 94 & **98** & 95 & 92 & 95 & 97 & 90 & 91 & 98 \\
9 & 93 & 92 & 90 & 90 & 95 & 93 & 94 & **97** & 95 & 96 \\
10 & 95 & 97 & 91 & **97** & 90 & 90 & 95 & 93 & 93 & 91 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Initial performance matrix \(P_{ij}(t=0)\) for each employee and task. In step 2, the Hungarian algorithm is employed to identify the task that each employee will perform to achieve the overall maximum performance. The optimal human resource allocation is demonstrated in Table 2. The bold numbers correspond to the optimal allocation. The third step of the algorithm is to calculate the total performance at \(t=0\) according to the optimal human resource allocation. Table 3 simplifies Table 2 by presenting only the optimal allocation of human resources to tasks, the corresponding performance values of the workers, and the total performance, which is calculated as the sum of all performance values. In a hypothetical scenario where all ten workers exhibit maximum performance levels in all tasks, the maximum total performance would be 1000 (100 \(\times\) 10). However, in this example, the optimal allocation results in a total performance of 980. At this point, the resistance to change is not yet apparent, and the calculated total performance is the initial state of the algorithm. This optimal allocation and the corresponding total performance will be used as the starting point for both the proposed method and the CCMM to facilitate a fair comparison between the two methods. In step 4, the resistance to change emerges, leading to a reduction in employee performance. A \(10\times 10\) resistance matrix (\(R_{ij}\)) is created for each employee and task, with random values in the range from 0 to 20, according to Table 1, for \(t=0\). An illustrative example of these random values is provided in Table 4.  
Subsequently, in step 5, a new performance matrix for the next time interval (\(t=1\)) is calculated using Equation (9). Steps 2 to 6 will be repeated until the end of the change