Developing an Organizational Performance Evaluation Model Using Grounded Theory Methodology and ARAS Method

Articles in Press

Document Type : Article

Authors

1 Professor, School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran

2 Department of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran

3 Strategy and Innovation Manager, Tejarat Iranian Digital Development, Tehran, Iran

4 School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran

Abstract

In today’s dynamic and competitive climate, organizations need to have a coherent framework for performance management. The models and frameworks in the literature may not be consistent with businesses’ changing nature and peculiar goals. They mostly rely on results and are ambiguous about how to be translated into specific performance measures. In response to these issues, this study designs a four-layer organizational performance evaluation model. Each layer of this model is broken down hierarchically into the two levels of measure domains and measures. The effects of measure domains on their next layer are determined using a novel approach based on the hierarchy of the model. Subsequently, the measures are ranked using Additive Ratio Assessment (ARAS) method. Research validity is guaranteed via data triangulation and methods triangulation. Eventually, the insights obtained from analyzing the research results are offered to the target organization to improve its performance management. The principal scientific value added by this paper is to present a new organizational performance evaluation model that offers a complete classification of performance measures and captures a comprehensive picture of business components and their relationship with organizational results. Moreover, the proposed model can improve some drawbacks of current models and their implementation challenges.

Keywords

Main Subjects

Scientia Iranica

Articles in Press, Accepted Manuscript
Available Online from 11 April 2023

Files

History

  • Receive Date: 07 June 2022
  • Revise Date: 05 December 2022
  • Accept Date: 11 April 2023

Share

How to cite

Statistics