Performance appraisal is a process used for some firms in order to evaluate the efficiency and productivity of their employees for planning their promotion policy. Initially this process was carried out just by the executive staff, but recently it has evolved to an evaluation process based on the opinion of different reviewers, supervisors, collaborators, clients and the employee himself (360-degree method). In such a evaluation process the reviewers evaluate some indicators related to the employee performance appraisal. These indicators are usually subjective and qualitative in nature that implies vagueness and uncertainty in their assessment. However, most of performance appraisal models force reviewers to provide their assessments about the indicators in a unique precise quantitative domain. We consider this obligation drives to a lack of precision in the final results, so in this paper we propose a linguistic evaluation framework to model qualitative information and manage its uncertainty. Additionally due to the fact that there are different sets of reviewers taking part in the evaluation process that have a different knowledge about the evaluated employee it seems suitable to offer a flexible framework in which different reviewers can express their assessments in different linguistic domains according to their knowledge. The final aim is to compute a global evaluation for each employee, that can be used by the management team to make their decisions regarding their incentive and promotion policy.
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