Improved decision aiding in human resource management

Sandra Rolim Ensslin, Leonardo Ensslin, Felipe Back and Rogério Tadeu de Oliveira Lacerda

International Journal of Productivity and Performance Management, 2013, vol. 62, issue 7, 735-757

Abstract: Purpose - Identify the criteria/KPIs to support managers during human resource allocation based on knowledge demand, which serves as a decision support tool to help maintain organizational competitiveness. Design/methodology/approach - Human resource allocation in a project management model, based on knowledge demand and using a multi‐criteria decision aiding method as an intervention instrument. Findings - Three major areas of concern were identified. In all, 76 KPIs to explain concerns associated with the values of the manager, and develop cardinal and ordinal scales for each descriptor and integrate compensation rate. Further, he was allowed to implement and evaluate the current performance of the analyzed engineer, with 44 points on a cardinal scale, and provide a model with improved actions that raised his assessment to 55,67. Originality/value - The Multi‐Criteria Decision Aiding‐Constructivist methodology (MCDA‐C) emerges as a traditional MCDA method to support decision makers in the contexts where they have a partial understanding and wish to increase their knowledge of the consequences of their values and preferences. In addition, these managers will also need to utilize time management, as people issues in the place of other functions have been highlighted in numerous published articles over how the management of human resource allocation can influence the competitive performances of an organization.

Keywords: Performance Management; Human Resource Management; HRM; MCDA‐C (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:eme:ijppmp:v:62:y:2013:i:7:p:735-757

DOI: 10.1108/IJPPM-04-2012-0039

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