Abstract It is important to identify sources of industrial investment growth from policy planning perspective, due to importance of manufacturing industries as the engine of economic development. SME formation is one of these sources that its impact on investment process with various methods has been studied. However, each of these studies used their specific angle and in some cases, these studies have reached different conclusions. On the other hand, many of the previous studies have applied statistical approaches and short-term, medium-term and long-term consequences of the solutions that have proposed by these studies has not considered at the same time. Therefore to address this deficiency, the holistic approach (system thinking) used to study impact of SME formation on investment growth. System Dynamics (SD) method used as a tool for implementing system thinking approach in order to use its capabilities in complex systems modeling and for achievng suitable results from simulation model. The population is Fars province in Period of 1360-1410. Vensim software has used for modeling and simulating. The results from the simulation of designed model showed, there is direct and interactive relationship between SME formation and amount of industrial investment.

Abstract Since at the present time, one of the major revenues of the government are from taxes, realizing the amount of tax revenues and making decisions of policies likely to enhance earnings in proper times with considering the tax current value is very important. According to the Markov chain method capabilities in understanding the possible random processes and dynamic programming methods, in this article, combination of these two methods with using information from income tax firms in the country in 1384-88 were used to represent a suitable pattern for discount in tax policy. Results showed that according to the prior data periods, the amount of non-received tax revenue was 3926 billion Rials. With 2% discount to customers and the tax received current value, it proceeded to 4511 billion Rials. In this way, the discount- index was determined for each year. As the process of tax revenues is also a transition period, paying taxes during the 12- month- period and the discount based on the tax current value were taking into consideration. The current value of future tax -cash flows during this period was equivalent to 16,034 billion Rials. Finally, using dynamic programming, the break event point of tax discount index was determined. Accordingly, in this manner, if the value of discount was less than 22%, the optimal policy for the government to increase the value of the received tax would be not to give discount to the customers and if the discount factor was over 22%, the favorable government policy would be providing discount to customers.