The biggest risk that international markets carry for companies is uncertainty. In a dynamic trade environment full of uncertainties, companies need to actively carry out competitive intelligence activities in order to adapt to market conditions and survive. One of the purposes of competitive intelligence is to increase the profitability of the enterprises in foreign trade by using the information obtained about the rival companies. For this purpose, the annual import data of consumables (motor, current sensor, transformer, capacitor, diode, thermostat) used in the production of welding machines and imported by the competitive intelligence method and annual export data of welding machines were obtained. Using the available data, it is aimed to estimate the amount of imported consumables used in welding machine manufacturing for Turkey's targeted export of welding equipment. All regression analysis methods in Matlab application were applied to the data obtained to determine the method that gave the best estimation result. As a result of the analyses made, it was determined that the meaningful and best results of RMSE, MAE, MSE and R2 values were obtained from the Exponential GSR method. In the exponential GSR method, the lowest error margin values were obtained with 0.207, 0.109, 0.042 for RMSE, MAE and MSE, and the highest R2 value was obtained with 0.96. By using the function of the exponential GSR method, it has been determined that which quantities of consumables used in the production of the welding machine should be imported for the export of welding machines worth 10.000.000$ in Turkey. The determined estimation data also support the accuracy of 0.96, the R2 value obtained from the Exponential GSR method.


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