Designing a model for Organizational performance management (oil industry case study)

Subject Areas : Industrial Management

Ghavam Saleh ¹ , Farshad Haj Alian ² , Ali Mehdizadeh Ashrafi ³ , Majid Jahangir Fard ⁴

1 - PhD Candidate, Department of Public Administration, Firoozkooh Branch, Islamic Azad University, Firoozkooh, Iran
2 - Assistant Professor, Department of Public Administration, Firoozkooh Branch, Islamic Azad University, Firoozkooh, Iran
3 - Assistant Professor, Department of Public Administration, Firoozkooh Branch, Islamic Azad University, Firoozkooh, Iran
4 - Department of Public Administration, Firoozkooh Branch, Islamic Azad University, Firoozkooh, Iran

Received: 2022-03-16 Accepted : 2022-10-10 Published : 2022-10-23

Keywords: Model Design, Organization performance management, : Oil Industry,

Abstract :

AbstractNowadays, one of the necessities for every organization is an assessment and monitoring system in performance management form, monitoring the organization’s plans with a systemic approach at all levels, besides providing the feedback required to pave the way to achieve the predetermined objectives. The present study was aimed at designing a model for an organization’s performance management in the oil industry. It was carried out in two qualitative and quantitative phases by fuzzy Delphi and exploratory factor analysis methods, as well as confirmatory factor analysis (CFA). The qualitative phase was progressed by semi-structured interviews with 20 experts in oil industry and academic experts. In the quantitative phase, 241 senior and middle managers were chosen as the statistical sample. Based on the qualitative phase’s results and the fuzzy Delphi method, four main components (regulatory, recognition of criteria and dimensions of performance, executive plan and performance measurement, and continuous performance improvement) and 31 sub-components were identified for the organization’s performance management. The results of the exploratory factor analysis in quantitative phase revealed that 96.366% of the total variance is explained by these 31 components. Furthermore, according to the confirmatory factor analysis results, regulatory component affects the recognition of performance measures dimensions with the size of 0.771; recognition of criteria and dimensions of the performance has an effect with the size of 1.063 on the executive plan and performance measurement; and finally, the executive plan and performance measurement have an effect with the size of 1.056 on the continuous improvement and modification.

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