| Summary: | 博士 === 國立臺灣科技大學 === 工業管理系 === 96 === Abstract
In this globalization and technology advanced environment, cross-functional new jobs are constantly created. Today’s businesses, either companies in service industry such as banks or firms in high-tech industry such as semiconductor manufacturers, are facing the problems of quick response and small lot-size diversified production. They can solve the problems with highly organizational flexibility and will be the best tool for increasing a company‘s competitiveness. However, one of the most important factors for successfully implementing organizational flexibility is personnel flexibility. Multi-functional skilled personnel virtually can satisfy the workforce assignment requirements and increase the business performance. Therefore, assigning the right employees to the right positions and then creating a collaboratively cross-functional team is one of the most crucial tasks performed by the decision makers of a company. The study on personnel assignment has received much attention in human resources management. Adjusting the requirements of positional standard and scheduling the personnel training program are two important activities in a human resources department.
For this reason, this dissertation addresses two research topics to discuss in detail multi-functional skilled personnel assignment problem by adjusting the requirements of positional standard and advancing employees’ skills through training. The first topic is to propose a systematic approach with a feedback mechanism in which the interdependences among positions and the differences among the selected employees are considered simultaneously. Unfortunately, the two combined considerations have rarely been discussed in the literature. The purpose of this approach is to obtain the best matching of candidates and positions in order to organize a collaboratively cross-functional team. In a fuzzy environment, we formulate a bi-objective binary integer programming (BOBIP) model and translate it into a fuzzy bi-objective goal programming (FBOGP) model. An elaborately designed heuristic algorithm is developed to determine the appropriate values of four important parameters in the FBOGP model, which is solved using LINDO 8.0. The results indicate that the proposed approach achieves the acceptable satisfaction level and requires less computation time than the brute force enumerative method. Additionally, several important findings and managerial implications can be observed from the results of solving the FBOGP model. The real-life usefulness of the proposed method is demonstrated by a practical application. The second topic is to extend the first topic and two important characteristics are added: (1) The non-compensation skill factor that every candidate should meet the necessary conditions of each position is first considered, and then the lowest weighted average of the skill score should be satisfied according to the compensation factor among skills. In other words, each multi-skilled employee who has to pass the required standard can be assigned to the position. In the literature, most scholars emphasized the mutual compensation instead of non-compensation factors among the candidate’s skills for personnel allocation. (2) We advance employees’ skills through training to achieve the projected performance set by a company under the conditions of limited budget for a member’s training and the total training cost for all members in a team rather than adjusting the requirements of positional standard. The empirical results reveal that the proposed multi-functional skilled personnel through training (MFSPTT) model can obtain a better solution to match the necessary performance requirement under the limited total training cost for all members in a team than the current method adopted by the case company.
In summary, the two proposed methods are suitable for practical application since these methods are more efficient than the optimal solution method. Therefore, they can be adopted by practitioners in developing decision support systems for managing human resources.
|
|---|
