# The Role of Managerial Commitment and TPM Implementation Strategies in Productivity Benefits
## 6 Conclusions and Industrial Implications  
Based on the findings previously discussed, the research conclusions are as follows:  
1. Based on the \(R^{2}\) values, TPM implementation has a 62.8% dependence on two variables, but managerial commitment explains most of the variability in 40%. In this sense, manufacturing companies must encourage department leaders and managers to embrace their responsibility for and commitment to TPM. Similarly, managers must promote the active participation of maintenance staff and communicate a corporate vision centered on quality and equipment maintenance, and among these aspects, they must be actively involved in TPM projects. Two other responsibilities of senior managers are to make sure that staff commitment to TPM is aligned with the corporate mission and supervise tracking of the implemented maintenance plans. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Dependent Variable**} & \multicolumn{6}{c}{**Automotive Sector**} & \multicolumn{3}{c}{**Other Sectors**} \\ \cline{2-7}  & \multicolumn{6}{c}{**Independent Variable**} \\ \cline{2-7}  & **MC** & **PMI** & **TPMI** & **MC** & **PMI** & **TPMI** \\ \hline PM implementation & 0.654 & - & - & 0.631 & - & - \\ TPM implementation & 0.49 & 0.364 & - & 0.573 & 0.298 & - \\ productivity benefits & 0.277 & 0.233 & 0.436 & 0.304 & 0.210 & 0.359 \\ \hline \hline \end{tabular} MC, managerial commitment; PMI, PM implementation; TPMI, TPM implementation.  
\end{table} 
Table 11: Beta values for models. \begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Dependent Variable**} & \multicolumn{3}{c}{**Independent Variable**} \\ \cline{2-4}  & **Managerial** & **TPM** & **PM** \\  & **Commitment** & **Implementation** & **Implementation** \\ \hline TPM implementation & -0.098 to 0.1333 & - & - \\ \hline PM implementation & -0.069 to 0.141 & -0.096 to 0.115 & - \\ \hline productivity benefits & -0.032 to 0.178 & -0.035 to 0.174 & -0.104 to 0.107 \\ \hline \hline \end{tabular}
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Table 12: Confidence intervals for differences in \(\beta\). The managerial commitment latent variable explains 40.7% of PM implementation variability. Therefore, for a preventive maintenance program to be successful, managerial commitment is necessary. Hence, PM programs must be focused on adjusting and changing components before the equipment fails. Also, preventing machine failures must be promoted by managers, since they need to understand the components' life cycle and generate a replacement plan. 3. TPM is a set of programs, among which is preventive maintenance. According to the findings, PM implementation is an important antecedent to any comprehensive TPM program. In fact, in this research, PM implementation explains 22.8% of the variability of TPM implementation. These findings imply that TPM managers and operators must focus their efforts on preventive maintenance programs that consider the components' life cycle to make changes before machines fail. 4. Statistically, three latent variables explain 38.3% of the productivity benefits latent variable: TPM implementation (16.4%), managerial commitment (16.2%), and PM implementation (5.7%). Such estimates imply that managers must pay close attention to the first two variables, since they have the largest effects. Although the direct impact from PM implementation is low in productivity benefits, the indirect effect has a value of 0.097, which can explain 4.55%. In the end, the total effects of PM implementation on productivity benefits have a value of 0.218 units, and this latent variable explains up to 10.2%. In other words, preventive maintenance as a part of TPM implementation is vital if companies aim to obtain productivity benefits. 5. The total effects of managerial commitment are larger than 0.5 standard deviations, demonstrating that this variable is a key element in productivity, TPM success, and PM programs.