Feasibility assessment of neural network based expert system prototype for evaluating motivational strategies

Abstract

The main objective of the study is to check the feasibility of design and implementation of neural network based expert system for evaluating motivational strategies from employees' perspectives on ICT human resource. If feasibility exists, then the secondary objective of the study is to provide a proof of concept that such full-fledged development of an expert system can be carried out with desired results. The reason to do the study is that very few expert systems are built for HR domain and there is no existing expert system we came across for the domain we are targeting. To check the operation feasibility, we initially implemented the prototype with C++. After the initial success of prototype, we decided to switch over to MATLAB to provide a proof of concept. The reasons for switching over to MATLAB from C++ are mentioned in the paper. We used back propagation algorithm to implement neural network based expert system. We provided comparison of the results for prototype implemented in C++ and MATLAB. Based on the comparison, we decided to develop and implement the full-fledged prototype of our neural network based expert system in MATLAB. We have been able to successfully implement the prototype in two different computer languages. This proves that there exists operational and technical feasibility for the development of neural network based expert system prototype. The proposed prototype showcase that the approach we choose can help HR managers to determine right set of employees centric motivational strategies and may help them to reduce attrition rate.