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Information Journal Paper

Title

A Mathematical Model of Optimal Budget Allocation Based on Performance in the Social Security Organization

Pages

  121-146

Abstract

 This research aims to provide a performance-based Budgeting model in the Social Security Organization which has independent and similar departments across the country. The statistical population of this research is the Social Security Organization Insurance's department. Following the library reviews and adapted from the Performance Indicators of the subcommittee of the insurance company's deputy, 38 functional indicators have been identified for the departments of the provinces and their respective branches. Then, the associated information regarding these indicators, extracted from the Statistical Yearbook of Economic and Organizational Planning, have been weighted by using Shannon's entropy method. Hence, based on real data of 2017 and on the basis of the province's degree of availability and regional equilibrium, the model is formulated. The results of applying the proposed model and comparing it with the current organization show that the organization's current method in budget Allocation is not optimal.

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    APA: Copy

    Rashidi, Aziz, ABBASI, EBRAHIM, JAFARI, MOSTAFA, & MOHAMMADI, NABIOLLAH. (2018). A Mathematical Model of Optimal Budget Allocation Based on Performance in the Social Security Organization. THE JOURNAL OF PLANNING AND BUDGETING, 23(2 ), 121-146. SID. https://sid.ir/paper/383037/en

    Vancouver: Copy

    Rashidi Aziz, ABBASI EBRAHIM, JAFARI MOSTAFA, MOHAMMADI NABIOLLAH. A Mathematical Model of Optimal Budget Allocation Based on Performance in the Social Security Organization. THE JOURNAL OF PLANNING AND BUDGETING[Internet]. 2018;23(2 ):121-146. Available from: https://sid.ir/paper/383037/en

    IEEE: Copy

    Aziz Rashidi, EBRAHIM ABBASI, MOSTAFA JAFARI, and NABIOLLAH MOHAMMADI, “A Mathematical Model of Optimal Budget Allocation Based on Performance in the Social Security Organization,” THE JOURNAL OF PLANNING AND BUDGETING, vol. 23, no. 2 , pp. 121–146, 2018, [Online]. Available: https://sid.ir/paper/383037/en

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