Design and Simulation a model for public policy evaluation (As evidence: Good governance role in development plans)

Subject Areas : Regional Planning

Jamal Boustanzar ¹ , Hossein Rahmanseresht ² , Fattah Sharifzadeh ³

1 - Public administration-Islamic Azad University-Tehran south branch
2 - Business administration group-Management & accounting faculty -Allameh tabatabaii Umiversity
3 - Public administration group-Management & Accounting faculty- Allame tabatabaii university

Received: 2021-06-27 Accepted : 2022-01-10 Published : 2024-02-20

Keywords: Development ", " Evaluation ", " System dynamic ", " Rule of law ", " Regulatory quality,

Abstract :

Abstract
Policies are the drivers for development. Timely and correct feedback from their evaluation can play a significant role to improve implementation and creating better results. Repetition the past approaches to implementation and evaluation development plans caused not change trends. Trends oscillation show the results is not in goal bound. So, keep this trends not successful for policy makers. This situation show there is not appropriate feedback structure between development plans implementation and evaluation, therefore evaluation process cannot produce requisite feedback for policymakers. Policymakers design corrective actions without pay attention to feedback. The current evaluation system contains some feedback, but these feedback are not accurate and in time. So, Implementation and evaluation of development plans with feedback structures are wider attention. This paper uses the system dynamics approach to design and simulation a model for development plans evaluation based on feedback loops. This study is a developmental research that used mixed research method to collect and analyze data. There are used to qualitative approach to identify variables and used to quantitative data to analyze variables behavior. Positive feedback loops are combined to design evaluation dynamic model by causal diagrams. Based on the model for effective evaluation should be evaluate results, capabilities and their cause and effect relationships. There are used actual data to run simulation for ensure the model effectiveness. The findings show that regulatory quality and rule of law are two key factors which can improve results. Therefore, policy makers should be concentrate to improve these variables and accentuate the causal relationship with other variables to boost plans performance. For this purpose, these variables should be considered as critical success factors in the formulating development plans.
 
Extended Abstract
 
Introduction
Public policy implementation is the most challenge stage in policy making process. Therefore, variety models have been developed for public policies implementation. Policy evaluation should be able to provide appropriate feedback to implementation for improvement and learning. Repetition the past approaches to evaluation development plans cannot change trends. Therefore, it is necessary to use a new approach to evaluate the effectiveness of public policies. This study used to the system dynamics approach for modeling and simulation development plans evaluation. Simulation helps to identify key variables for formulate corrective actions. The purpose of this model is to increase the evaluation capability to understand the causes for achieving the results. This model helps policy makers to formulate effective development policies.
 
Methodology
According to the systemic view, feedback loops establish simultaneously with development. Feedback loops increase our ability to understand the structure and dynamics of the development system. System dynamics approach describes systems with feedback loops. So, this approach was used to simulate implementation and evaluation of development plans. This study is a causal study because considered cause and effect relationships and is a developmental study in terms of the purpose. This study used mixed research method to collect and analyze data. Qualitative approaches used to identify variables and quantitative data use to analyze variables behavior. Quantitative data obtained from the Iran Statistic Center and Central bank of Iran. Purposeful selection of participants is very important for understanding the research question in qualitative research. In this type of research, the proposed method to determine the number of samples is the saturation approach. So, data collection continues until the new data does not provide new perspectives about research question. The statistical population was managers and experts from responsible organizations for formulation, implementation and evaluation development plans and professors who were selected using judgmental sampling method. The method of data collection is done by the interviews and analyzed using qualitative content analysis.
 
Results and Discussion
For understand the system’s behavior, the stock variables time series considering during the fourth and fifth development plans. These variables show oscillation behavior. Oscillation behavior means the current evaluation system cannot provide feedback for improve variables behavior. Positive feedback loops must be created for variables behavior to transform into a pattern of growth. Then positive feedback loops combination and design causal model for evaluation development plans. According to the proposed model, feedback link results to capabilities for effective implementation. This model emphasizes corrective actions should be developed well-set to gap, because the evaluation system can help to reduce the gap. The model simulation need to mathematical relationships. There was not equation between the variables. So, it was used regression to establish equations. Four scenarios were simulated based on the variables affecting gap reduction.

Continuation the current situation scenario: In this scenario, the variables simulated based on the calculated coefficients. The system behavior shows that if the current situation is maintained, the growth of variables will continue in the next years with a very low slope. According to the simulation results, the growth of variables will start with a delay, so the results follow the growth pattern after 1402.
Scenario1: In this scenario, regulatory quality and rule of law coefficient increased tenfold. Furthermore, the human resource empowerment coefficient increased 10% of Gap. Also, the coefficient between government effectiveness and ease of doing, which was negative based on calculations, turn to +1 for eliminate the effect of negative relationship. The results show all variables follow the growth pattern over the time with more slope than continuation the current situation scenario.
Scenario 2: The regulatory quality and rule of law coefficient increased twenty times. The results show stock variables follow the growth pattern. In fact, if the other relationships of the system do not change and only increase the coefficients of these two variables, they will cause to grow the system.
Scenario 3: According to the results of Scenario 2, in scenario 3, the regulatory quality and rule of law coefficient increased thirty times and other conditions were the same as Scenario2. The simulation result show that increasing these two variables has a significant effect on the growth rate of system variables and confirmed the findings of Scenario 2. The result show to concentrated innovations and efforts to improve two variables of regulatory quality and rule of law has a significant effect on the system and can guarantee system growth.

 
Conclusion
Findings show cause and effect relationship between outputs and inputs is necessary factor for design corrective actions to change system behavior. For this purpose, feedback should be used to improvement. In addition, feedback loops help to identify existing capabilities and how to change them to achieve goals. For effective evaluation the development plans should evaluate "results", "capabilities" and "their cause and effect relationship". This model shows the causal loops including regulatory quality, rule of law, ease of doing and Government effectiveness to cause the outputs and outcomes. Therefore, the causal relationship between these variables and other variables should be emphasized. For this purpose, these variables should be considered as critical success factors in the formulating development plans. So, policy makers should be formulate an improvement program for these variables. The proposed model helps policy makers to identify the causes of the results and to review the policy processes based on these causes.

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