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Innovation in developing platform businesses is very significant nowadays due to the importance of businesses and their role in economy. As businesses will use in future the collective wisdom and extra-organizational knowledge, applying open innovation in the businesses seems to be a must. The expert participants of the research are twelve specialists and managers of platform businesses. Reviewing the theoretical foundations, four factors were extracted from the opinions of experts: attraction capacity, networking and network management, knowledge and technical capacity, and collaboration capability. Taguchi experiment design method was used for determining the role of the factors. Four levels is defined for each factor (between 0 and 0.25 for level 1, between 0.25 and 0.50 for level 2, between 0.50 and 0.75 for level 3, and between 0.75 and 1 for level 4). Using Qualitek software sixteen scenarios extracted. For determining the optimal scenario, questionnaire and fuzzy Taguchi experiments were used. The results showed that the appropriate level of platform development indicators using open innovation should be at the fourth level (0.75-1) for all four factors. That is, all four factors impact drastically the development of platform businesses. Moreover, the results of variance analysis showed that the importance of the factors in the development of the platform are, respectively, knowledge and technical capacity (42.70% of participation), attraction capacity (24.37%) and networking and network management (21.09%), and collaboration capability (6.84%).

In this article, the impact of various factors such as whether the company is public or private, certificate of clearance and the company's income on the paying tax situation by 57 large companies in the Sistan and Baluchistan province, has been investigated. Since the dependent variable of tax collection is a binary variable, probit and logit models have been used to estimate the coefficients. The results of using two models show that all three explanatory variables have a positive and significant effect on tax payment by companies. And the biggest effect is related to the certificate of clearance, state of the company, and company's income, respectively. Examining the final effects also shows that as the company's income increases, the probability of paying its taxes has decreased and this is because the company with a larger income pays taxes on time and better because of the fear of the consequences of not paying taxes and also knowing with the rules of paying taxes. Therefore, with the increase in income, the probability of paying the company tax also increases less. The Hosmer-Lemshow statistic also indicates that the models fit well and the model is consistent with the data. It is suggested that the laws be amended in such a way that it is necessary for the companies to complete the accounts so that the government can collect taxes from more companies through this law. and limit the way of tax evasion.

EXTENDED ABSTRACTINTRODUCTIONThe commodity terms of trade shocks are important to explain the macroeconomic fluctuations of oil-exporting countries. Oil price shocks are the main source of terms of trade variability in oil-exporting countries. Given the significant effects of terms of trade fluctuations on domestic macroeconomic variables, understanding the transmission and propagation of terms of trade fluctuations is crucial in the design and conduct of macroeconomic policies in oil-exporting countries. An appropriate monetary policy can help to stabilize these shocks.This study evaluates three alternative monetary policy regimes’ responses to commodity terms of trade shock and export sector productivity shock using a New Keynesian Dynamic Stochastic General Equilibrium (DSGE) model. In this study, the model has been developed based on Hove et al. (2015), Monacelli (2005) and Cashin et al. (2004) for the economy of Iran. This theoretical framework characterizes a small open oil-exporting economy by two domestic sectors: traded sector and the non-traded sector. In the non-traded sector, prices are sticky according to Calvo`s (1983). There is one external sector which is the rest of the world. Also, incomplete exchange rate pass-through is introduced via nominal rigidities on import prices. This model has been developed to evaluate the response of different monetary policy regimes to commodity terms of trade shocks and export productivity shocks. Based on empirical evidence such as Shajari et al (2015), pass-through is assumed to be incomplete in the model.Since oil exports account for a high percentage of export earnings and finance a significant portion of government spending in Iran, the analysis of different monetary policy responses to commodity terms of trade shocks in an oil-exporting country, like Iran, must be important.  This study aims at investigating the dynamic effects of commodity terms of trade shocks and evaluating the performance and the stabilization properties of various simple monetary policy rules for oil-dependent economies. Three alternative monetary policy rules have been considered: CPI inflation targeting (CIT) rule, non-traded inflation targeting (NTIT) rule, and exchange rate targeting (ET) rule. Different monetary policy rules are assessed based on the degree to which they minimize the volatility of selected macroeconomic variables as reflected by their impulse response functions. METHODOLOGYThe model is calibrated to match the key features of the Iran economy using data for the period 1991: Q1 to 2017: Q1. The series of Oil production and Non-oil production is obtained from the “Statistical Centre of Iran” The series of Interest rate and oil prices are obtained from the “Central Bank of Iran”. The series of production in the oreign intermediate sector and foreign intermediate good price are obtained from the “Archival Federal Reserve Economic Data”[1]. Other parameters were obtained from previous studies on the Iran economy and business cycle literature in the world. The model is calibrated to the Iran economy. The model is solved numerically and the parameter choices for the model are summarized in Table1. FINDINGSThe comparison of responses under different monetary policy regimes shows that CPI inflation targeting is superior to the NTIT and ET targeting when commodity terms of trade shock happen. For export productivity shock, the performance of the CIT rule is better than other examining monetary policy rules. Also, the real exchange rate, which is defined as a function of commodity terms of trade and productivity differentials, makes it possible to examine the role of export productivity shock on macroeconomic variations and test the existence of Balassa- Samuelson effect. Impulse responses to commodity terms of trade shock show increasing in total output and CPI inflation and decreasing in consumption and nominal exchange rate under three policy rules. The analysis also displays that commodity terms of trade shock induce lower responses of macroeconomic variables under CPI inflation targeting than under non-traded inflation targeting and exchange rate targeting. Under the export sector productivity shock, exported output increases while non-traded output decreases, possibly reflecting the symptoms of the Dutch disease. On the other hand, the dynamic responses of selected macroeconomic variables suggest the presence of the Balassa-Samuelson effect where an increase in productivity in the traded sector appreciates the real exchange rate and increases the prices of non-tradable goods through wage equalizations. CONCLUSIONoverall, when the economy is experiencing commodity terms of trade shocks or exported productivity shocks, CPI inflation targeting is relatively better than exchange rate targeting and non-traded inflation targeting in macroeconomic stabilization.  [1] The date of US is considered as an alternative for foreign sector data

The price of Crude Oil is Exposed to Various Factors That Cause Random, Sudden and Chaotic Price Fluctuations. Accurate Forecasting of Oil Prices Has a Central Impact on The Macro Economy. The aim of This Study is to Predict the Fluctuations of OPEC Crude Oil in The  long-term Using Chaos Theory and GMDH-GA Algorithm. First, the Daily Oil Price Time Series is Decomposed by Wavelet Transformation. Then, Chaos is Tested Using Embedding Dimension, Lyapunov Power and GA tests. Finally, Time Series Noises are Reduced by Reconstructing the Wavelet Phase Space. Three Nonlinear Models, GMDH-GA model, GMDH-GA Wavelet Model, and GMDH-GA Extended Model, Were Used to Forecast Time Series. Although the Results Showed that All three Models are Favorable in Terms of Root Mean Square Error (RMSE) and Correlation Coefficient, But the Developed GMDH-GA  Neural Network Model with low RMSE and High Correlation Coefficient is the Most Effective in Predicting the Daily Price of OPEC Crude Oil. has it.