<abstract xmlns="http://www.w3.org/1999/xhtml"><p>The economic crisis, demography, technology, globalization etc. are all factors which will influence the organizational structures and business strategies. A new business strategy will require, among others, that passive Human Resources Management (HRM) change into an active one with a decisive influence upon business. The vision of an active HRM requires that HR information (IT) dedicated systems assist human resources managers in their decision-making. The existing IT systems predominantly manage the salary calculations and, possibly, the employee's professional development, two of the tasks that a human resources manager has to pursue. However, tasks such as assisting, consulting and engaging the human resources in the organization are equally important. IT systems must also develop into these directions. The present paper proposes a solution to measure the performance of human resources by creating an employee performance indicator (EPI). The paper first describes the economic phenomenon involved in the HR performance process, then the mathematical model is formulated, the algorithm is implemented, the solution of the model is analysed from a technical and economic point of view, and finally the decision is made. We use the weighted arithmetic mean to compute the EPI indicator and the correlation formula to establish the degree of relevance between the EPI indicator and the variables involved in the model. An implementation in R is given.</p></abstract>

The economic crisis, demography, technology, globalization etc. are all factors which will influence the organizational structures and business strategies. A new business strategy will require, among others, that passive Human Resources Management (HRM) change into an active one with a decisive influence upon business. The vision of an active HRM requires that HR information (IT) dedicated systems assist human resources managers in their decision-making. The existing IT systems predominantly manage the salary calculations and, possibly, the employee's professional development, two of the tasks that a human resources manager has to pursue. However, tasks such as assisting, consulting and engaging the human resources in the organization are equally important. IT systems must also develop into these directions. The present paper proposes a solution to measure the performance of human resources by creating an employee performance indicator (EPI). The paper first describes the economic phenomenon involved in the HR performance process, then the mathematical model is formulated, the algorithm is implemented, the solution of the model is analysed from a technical and economic point of view, and finally the decision is made. We use the weighted arithmetic mean to compute the EPI indicator and the correlation formula to establish the degree of relevance between the EPI indicator and the variables involved in the model. An implementation in R is given.

A Model to Measure the Performance of Human Resources in Organisations

“Vasile Goldiş” Western University of Arad

Studia Universitatis „Vasile Goldis” Arad – Economics Series

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"A Model to Measure the Performance of Human Resources in Organisations"}

The economic crisis, demography, technology, globalization etc. are all factors which will influence the organizational structures and business strategies. A...

A Model to Measure the Performance of Human Resources in Organisations

Publicado en línea: 24 mar 2018

Páginas: 57 - 73

Recibido: 01 dic 2017

Aceptado: 01 mar 2018

DOI: https://doi.org/10.2478/sues-2018-0005

Palabras clave
ongoing performance management, key performance indicators, multiple linear regression, statistical R environment

© 2018 Magnolia Tilca et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

A Model to Measure the Performance of Human Resources in Organisations

Publicado en línea: 24 mar 2018

Páginas: 57 - 73

Recibido: 01 dic 2017

Aceptado: 01 mar 2018

DOI: https://doi.org/10.2478/sues-2018-0005

Palabras claveongoing performance management, key performance indicators, multiple linear regression, statistical R environment

© 2018 Magnolia Tilca et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Palabras clave
ongoing performance management, key performance indicators, multiple linear regression, statistical R environment