## 7 Conclusions  
The GESTAC model applies each of the tacit knowledge management phases. It achieves the objective of searching for solutions for business incidents logged by users, speeding up their resolution times. It identifies the sources that could provide the solutions and captures their tacit knowledge. It stores this knowledge in a KB and distributes it in the business domain for use by all authorized users. The knowledge applied as solutions to incidents is permanently evaluated and can be replaced if better sources or knowledge emerge. A prototype was implemented with a front-end and back-end architecture using software agents that were based on data input by users. The software agents can locate new and better sources and knowledge by executing deliberative processes to output results without human intervention. The communication between human agents and the system is carried out by means of software agents, including Java coding and JSON strings. This facilitates their application in distributed and changing environments. The choice of items for evaluating the sources and knowledge emerged from the combination of results yielded by surveys taken by knowledge managers from different companies and from the results tested on other confidence models. The experiments conducted on a prototype using tacit knowledge management implemented as a multiagent system demonstrated that the model's biggest advantage was that it led to shorter incident resolution times for the technicians that used the prototype compared with technicians that did not use the application for the tested domain and case. In addition to the reduction of incident resolution times, \begin{table}
\begin{tabular}{c c c} \hline \hline
**Expert** & **Evaluation Using GESTAC Prototype (from 1 to 10)** & **Evaluation without the GESTAC Prototype (from 1 to 10)** \\ \hline
1 & 6 & 4 \\
2 & 8 & 4 \\
3 & 5 & 5 \\
4 & 6 & 6 \\
5 & 9 & 7 \\
6 & 8 & 4 \\
7 & 8 & 6 \\
8 & 7 & 5 \\
9 & 9 & 5 \\
10 & 6 & 4 \\ \hline \hline \end{tabular}
\end{table} 
Table 10: Qualitative rating of incident resolution time with and without GESTAC. the system has another important advantage: the global count of benefits versus costs. The cost/hour of the technicians of small and medium enterprises (adding dedication, training of use in GESTAC, etc.) added to the cost of the development and implementation, deployment and execution of GESTAC is clearly lower than the costs of technicians in the event of not using this model. The calculations show relevant net benefit values from the first quarter of implementation, which is undoubtedly a second advantage to be taken into account. In a nutshell, these solutions can be improved using software agents to automatically search, evaluate and access databases based on the original data and fine-tune processes if better sources and knowledge emerge. Software agents permanently interact with each other and with human beings, transferring information. They are each experts in their role. By capturing and conserving the tacit knowledge of the company employees, even after they leave, GESTAC aims to contribute to the development of the organizational memory and user participation by measuring their satisfaction with the solutions offered and indirectly with the sources that provided those solutions. This should act as an incentive for the improvement of the work performed in the business domain, we consider that the research achieved the stated goals, and is worth continuing to achieve further developments and improvement in the future. It would be very beneficial to also apply the concept of imprecision used to record incident severity to the knowledge ratings. In this manner, it would be possible to apply the same piece of knowledge to other similar problems. The study carried out makes it possible to check the applicability and viability of the model presented, and its suitability for the problem to be tackled, but it has some limitations, already introduced succinctly in the previous section.