برنامه‌ریزی و بودجه (Sep 2022)

Designing a Performance-based Budgeting Model with a Systematic and Mixed Approach

  • Mohammad Solgi,
  • Farhad Golmorasa,
  • Sajjad Shamsi Gooshki

Journal volume & issue
Vol. 27, no. 2
pp. 193 – 228

Abstract

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Performance-based budgeting helps organizations establish a key link between budgeting and organizational performance. Accordingly, this approach can be used in various organizations. The purpose of this study is to design a budgeting model based on the performance and evaluation of the current budgeting system in the public sector from the perspective of experts and managers in the field of budgeting. In the qualitative part of the statistical population, including experts in the field of public finance, a statistical sample of 8 of these individuals was selected using the purposive-judgmental sampling method. In the qualitative part, first by examining the current models and content analysis method, the conceptual model of the research was extracted and then to localize and saturate the conceptual model, the selected sample was interviewed. A small part of the statistical population includes managers and experts of the executive apparatus, who are selected using available sampling of a sample of 43 of these people; the Questionnaire is a data collection tool and the structural modeling method is a data analysis method in this section. The results showed that in the performance model of performance-based budgeting, input dimensions (requirements) include organizational structure, organizational culture, management style, transformational leadership, and change management; moreover, the main processes include planning, performance management, and accounting system (activity-based costing) and the output consists of optimal resource allocation, effective monitoring, and control. The results of the evaluation of the measurement and structural model of the research indicate the validity and reliability of the model, the confirmation of the structural relations, and the optimal measurement and fit of the model.

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