Classification of human resources based on measurement of tacit knowledge : An empirical study in Iran

Purpose – The purpose of this paper is to investigate employees of an organization in order to evaluate and classify them based on their tacit knowledge. Therefore, in this paper, staff's tacit knowledge is measured at the individual level, in automotive sector. Design/methodology/approach – Repertory grid technique has been used as a mechanism to aid the elicitation and evaluation of individuals’ personal constructs. Then, Pathfinder analysis was carried out to examine the individual's knowledge structure. The similarities between knowledge structure of expert and novice was measured by the set‐theoretic index C, in order to classify staff and ultimately, for analysis of each group, Idiogrid software was used. Findings – Based on closeness index, all employees were classified into four categories. Respondent's perceptions were evaluated by comparing the mental model graphs of the individuals in different categories with experts’ graphs. Ultimately, the best or the most effective HR practices were determined for managing knowledge workers. Research limitations/implications – This study may help HRM department to differentiate between low and high‐performing employees for determining the most effective HR practices to manage staff. Furthermore, it has significant implications in team building and designing a knowledge map within organizations. Originality/value – This paper reveals effective linkages between human resource management and knowledge management.